A belief revision framework for revising epistemic states with partial epistemic states

Belief revision performs belief change on an agent’s beliefs when new evidence (either of the form of a propositional formula or of the form of a total pre-order on a set of interpretations) is received. Jeffrey’s rule is commonly used for revising probabilistic epistemic states when new information is probabilistically uncertain. In this paper, we propose a general epistemic revision framework where new evidence is of the form of a partial epistemic state. Our framework extends Jeffrey’s rule with uncertain inputs and covers well-known existing frameworks such as ordinal conditional function (OCF) or possibility theory. We then define a set of postulates that such revision operators shall satisfy and establish representation theorems to characterize those postulates. We show that these postulates reveal common characteristics of various existing revision strategies and are satisfied by OCF conditionalization, Jeffrey’s rule of conditioning and possibility conditionalization. Furthermore, when reducing to the belief revision situation, our postulates can induce Darwiche and Pearl’s postulates C1 and C2.

Revision over Partial Pre-orders: A Postulational Study

Belief revision is the process that incorporates, in a consistent way,
a new piece of information, called input, into a belief base. When both belief
bases and inputs are propositional formulas, a set of natural and rational properties, known as AGM postulates, have been proposed to define genuine revision operations. This paper addresses the following important issue : How to revise a partially pre-ordered information (representing initial beliefs) with a new partially pre-ordered information (representing inputs) while preserving AGM postulates? We first provide a particular representation of partial pre-orders (called units) using the concept of closed sets of units. Then we restate AGM postulates in this framework by defining counterparts of the notions of logical entailment and logical consistency. In the second part of the paper, we provide some examples of revision operations that respect our set of postulates. We also prove that our revision methods extend well-known lexicographic revision and natural revision for both cases where the input is either a single propositional formula or a total pre-order.

A Coordination and Ligand Replacement Based Three-Input Colorimetric Logic Gate Sensing Platform for Melamine, Mercury Ions, and Cysteine

Discrimination of different species in various target scopes within a single sensing platform can provide many advantages such as simplicity, rapidness, and cost effectiveness. Here we design a three-input colorimetric logic gate based on the aggregation and anti-aggregation of gold nanoparticles (Au NPs) for the sensing of melamine, cysteine, and Hg2+. The concept takes advantages of the highly specific coordination and ligand replacement reactions between melamine, cysteine, Hg2+, and Au NPs. Different outputs are obtained with the combinational inputs in the logic gates, which can serve as a reference to discriminate different analytes within a single sensing platform. Furthermore, besides the intrinsic sensitivity and selectivity of Au NPs to melamine-like compounds, the “INH” gates of melamine/cysteine and melamine/Hg2+ in this logic system can be employed for sensitive and selective detections of cysteine and Hg2+, respectively.

Iso-Quality of Service: Fairly Ranking Servers for Real-Time Data Analytics

We present a mathematically rigorous Quality-of-Service (QoS) metric which relates the achievable quality of service metric (QoS) for a real-time analytics service to the server energy cost of offering the service. Using a new iso-QoS evaluation methodology, we scale server resources to meet QoS targets and directly rank the servers in terms of their energy-efficiency and by extension cost of ownership. Our metric and method are platform-independent and enable fair comparison of datacenter compute servers with significant architectural diversity, including micro-servers. We deploy our metric and methodology to compare three servers running financial option pricing workloads on real-life market data. We find that server ranking is sensitive to data inputs and desired QoS level and that although scale-out micro-servers can be up to two times more energy-efficient than conventional heavyweight servers for the same target QoS, they are still six times less energy efficient than high-performance computational accelerators.

Modeling of titanium alloys by using artificial neural networks

Titanium alloy exhibits an excellent combination of bio-compatibility, corrosion resistance, strength and toughness. The microstructure of an alloy influences the properties. The microstructures depend mainly on alloying elements, method of production, mechanical, and thermal treatments. The relationships between these variables and final properties of the alloy are complex, non-linear in nature, which is the biggest hurdle in developing proper correlations between them by conventional methods. So, we developed artificial neural networks (ANN) models for solving these complex phenomena in titanium alloys.

In the present work, ANN models were used for the analysis and prediction of the correlation between the process parameters, the alloying elements, microstructural features, beta transus temperature and mechanical properties in titanium alloys. Sensitivity analysis of trained neural network models were studied which resulted a better understanding of relationships between inputs and outputs. The model predictions and the analysis are well in agreement with the experimental results. The simulation results show that the average output-prediction error by models are less than 5% of the prediction range in more than 95% of the cases, which is quite acceptable for all metallurgical purposes.

14C as a tool to trace terrestrial carbon in a complex lake system: implications for foodweb structure and carbon cycling

Carbon and nitrogen stable isotope analysis (SIA) has identified the terrestrial subsidy of freshwater food-webs but relies on different 13C fractionation in aquatic and terrestrial primary producers. However dissolved inorganic carbon (DIC) is partly comprised of 13C depleted respiration of terrestrial C and ‘old’ C derived from weathering of catchment geology. SIA thus fails to differentiate between the contribution of old and recently fixed terrestrial C. DIC in alkaline lakes is partially derived from weathering of 14C-free carbonaceous bedrock This
yields an artificial age offset leading samples to appear significantly older than their actual age. As such, 14C can be used as a biomarker to identify the proportion of autochthonous C in the food-web. With terrestrial C inputs likely to increase, the origin and utilisation of ‘old’ or ‘recent’ allochthonous C in the food-web can also be determined. Stable isotopes and 14C were measured for biota, particulate organic matter (POM), DIC and dissolved organic carbon (DOC) from Lough Erne, Northern Ireland, a humic but alkaline lake. High winter δ15N values in calanoid zooplankton (δ15N =24‰) relative to phytoplankton and POM (δ15N =6‰ and 12‰ respectively) may reflect several microbial trophic levels between terrestrial C and calanoids. Furthermore winter calanoid 14C ages are consistent with DOC from inflowing rivers (87 and 75 years BP respectively) but not phytoplankton (355 years BP). Summer calanoid δ13N, δ15N and 14C (312 years BP) indicate greater reliance on phytoplankton. There is also temporal and spatial variation in DIC, DOC and POM C isotopes.

14C as a tool to trace terrestrial carbon in a complex lake system: implications for food-web structure and carbon cycling

Globally lakes bury and remineralise significant quantities of terrestrial C, and the associated flux of terrestrial C strongly influences their functioning. Changing deposition chemistry, land use and climate induced impacts on hydrology will affect soil biogeochemistry and terrestrial C export¹ and hence lake ecology with potential feedbacks for regional and global C cycling. C and nitrogen stable isotope analysis (SIA) has identified the terrestrial subsidy of freshwater food webs. The approach relies on different ¹³C fractionation in aquatic and terrestrial primary producers, but also that inorganic C demands of aquatic primary producers are partly met by ¹³C depleted C from respiration of terrestrial C, and ‘old’ C derived from weathering of catchment geology. SIA thus fails to differentiate between the contributions of old and recently fixed terrestrial C. Natural abundance ¹⁴C can be used as an additional biomarker to untangle riverine food webs² where aquatic and terrestrial δ ¹³C overlap, but may also be valuable for examining the age and origin of C in the lake. Primary production in lakes is based on dissolved inorganic C (DIC). DIC in alkaline lakes is partially derived from weathering of carbonaceous bedrock, a proportion of which is¹⁴C-free. The low ¹⁴C activity yields an artificial age offset leading samples to appear hundreds to thousands of years older than their actual age. As such, ¹⁴C can be used to identify the proportion of autochthonous C in the food-web. With terrestrial C inputs likely to increase, the origin and utilisation of ‘fossil’ or ‘recent’ allochthonous C in the food-web can also be determined. Stable isotopes and 14C were measured for biota, particulate organic matter (POM), DIC and dissolved organic carbon (DOC) from Lough Erne, Northern Ireland, a humic alkaline lake. Temporal and spatial variation was evident in DIC, DOC and POM C isotopes with implications for the fluctuation in terrestrial export processes. Ramped pyrolysis of lake surface sediment indicates the burial of two C components. ¹⁴C activity (507 ± 30 BP) of sediment combusted at 400˚C was consistent with algal values and younger than bulk sediment values (1097 ± 30 BP). The sample was subsequently combusted at 850˚C, yielding 14C values (1471 ± 30 BP) older than the bulk sediment age, suggesting that fossil terrestrial carbon is also buried in the sediment. Stable isotopes in the food web indicate that terrestrial organic C is also utilised by lake organisms. High winter δ ¹⁵N values in calanoid zooplankton (δ ¹⁵N = 24%¸) relative to phytoplankton and POM (δ ¹⁵N = 6h and 12h respectively) may reflect several microbial trophic levels between terrestrial C and calanoids. Furthermore winter calanoid 14C ages are consistent with DOC from an inflowing river (75 ± 24 BP), not phytoplankton (367 ± 70 BP). Summer calanoid δ ^13C, δ ¹⁵N and ¹⁴C (345 ± 80 BP) indicate greater reliance on phytoplankton.

¹ Monteith, D.T et al., (2007) Dissolved organic carbon trends resulting from changes in atmospheric deposition chemistry. Nature, 450:537-535

² Caraco, N., et al.,(2010) Millennial-aged organic carbon subsidies to a modern river food web. Ecology,91: 2385-2393.

Forward and backward least angle regression for nonlinear system identification

A forward and backward least angle regression (LAR) algorithm is proposed to construct the nonlinear autoregressive model with exogenous inputs (NARX) that is widely used to describe a large class of nonlinear dynamic systems. The main objective of this paper is to improve model sparsity and generalization performance of the original forward LAR algorithm. This is achieved by introducing a replacement scheme using an additional backward LAR stage. The backward stage replaces insignificant model terms selected by forward LAR with more significant ones, leading to an improved model in terms of the model compactness and performance. A numerical example to construct four types of NARX models, namely polynomials, radial basis function (RBF) networks, neuro fuzzy and wavelet networks, is presented to illustrate the effectiveness of the proposed technique in comparison with some popular methods.

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.

Information Gathering and Processing with Fluorescent Molecules

Molecular information gathering and processing – a young field of applied chemistry - is undergoing good growth. The progress is occurring both in terms of conceptual development and in terms of the strengthening of older concepts with new examples. This review critically surveys these two broad avenues. We consider some cases where molecules emulate one of the building blocks of electronic logic gates. We then examine molecular emulation of various Boolean logic gates carrying one, two or three inputs. Some single-input gates are popular information gathering devices. Special systems, such as ‘lab-on-a-molecule’ and molecular keypad locks, also receive attention. A situation deviating from the Boolean blueprint is also discussed. Some pointers are offered for maintaining the upward curve of the field.

Metallosupramolecular Materials for Electronic Applications: Molecular Boolean Computation

It is an exciting era for molecular computation because molecular logic gates are being pushed in new directions. The use of sulfur rather than the commonplace nitrogen as the key receptor atom in metal ion sensors is one of these directions; plant cells coming within the jurisdiction of fluorescent molecular thermometers is another, combining photochromism with voltammetry for molecular electronics is yet another. Two-input logic gates benefit from old ideas such as rectifying bilayer electrodes, cyclodextrin-enhanced room-temperature phosphorescence, steric hindrance, the polymerase chain reaction, charge transfer absorption of donor–acceptor complexes and lectin–glycocluster interactions. Furthermore, the concept of photo-uncaging enables rational ways of concatenating logic gates. Computational concepts are also applied to potential cancer theranostics and to the selective monitoring of neurotransmitters in situ. Higher numbers of inputs are also accommodated with the concept of functional integration of gates, where complex input–output patterns are sought out and analysed. Molecular emulation of computational components such as demultiplexers and parity generators/checkers are achieved in related ways. Complexity of another order is tackled with molecular edge detection routines.

Temporal and spatial patterns in α- and γ-hexachlorocyclohexane concentrations in industrially contaminated rivers

Fluxes of HCH isomers α- and γ-HCH dynamics were determined in four industrial U.K. rivers feeding the North Sea. Sampling was conducted weekly basis over a 2-year period. This was complemented by discrete studies of events where two hourly sampling periods were used to investigate the fine time scale dynamics of fluxes. Two intensively industrialized rivers had average isomer concentrations of ~20 ng L^-1 for both isomers, while average concentrations in the two less industrialized rivers ranged between 1.5 and 5.0 ng L^-1. α-HCH concentrations showed no strong temporal patterns on any river, which contrasts with γ-HCH levels that increased considerably during late summer/early autumn following sustained periods of low river flow. Sampling during high river flow events on rivers with differing HCH pollution histories both showed the same dynamics in HCH isomer concentrations. γ-HCH concentrations decreased 4-fold during events while α-HCH-concentrations stayed constant. The increases in γ-HCH concentrations under low flow conditions and the rapid dilution of this isomer during events indicate that γ-HCH has current inputs to these river systems. It was calculated that these four rivers export 30.8 kg yr^-1 of γ-HCH and 14.8 kg yr^-1 of α-HCH to the North Sea.

Fluxes of organic contaminants from the river catchment into, through and out of the Humber Estuary, UK

This paper summarises the work done on the distribution and reactivity of organic contaminants (simazine, atrazine, lindane, fluoranthene, pyrene, PCB 77, PCB 118) in the Humber Estuary and associated major rivers, as part of the LOIS programme. The preliminary flux calculations show that the most important contributors of selected organic contaminants were the rivers Trent (45% of simazine, 20% of atrazine), Aire (30% of simazine and 33% of atrazine), Don (36 and 37% of fluoranthene and pyrene) and Ouse (18% of fluoranthene and pyrene). For lindane and PCBs, the Aire and Ouse were the key sources. The water flow in all the rivers shows strong seasonal variations, as do the contaminant concentrations. As a result, the mean daily fluxes of these contaminants displayed a strong seasonality. Annual mean concentrations of simazine and atrazine decreased by more than 50% over the period 1994-1995 in most of the rivers, probably as a result of their restricted use in the UK. Mass balance calculations show that the Humber is a sink for atrazine, lindane, PCB 77 and PCB 118, although the degree of removal is generally much lower for atrazine and lindane than for PCB 77 and PCB 118. Mass balance results also show that the Humber can either be a source of fluoranthene and pyrene (in the suspended particulate phase), or a sink (in the dissolved phase), although overall the Humber acts as sink. The budget exercise represents an attempt to quantify the input and output of selected organic contaminants from catchment to ocean. However, due to limited data and assumptions involved in calculations, the estimates should be considered as an order of magnitude approximation. Further improvement both in resolution and accuracy is required.

A critical review of labelling techniques used to quantify rhizosphere carbon-flow

The rhizosphere is a major sink for photo-assimilated carbon and quantifying inputs into this sink is one of the main goals of rhizosphere biology as organic carbon lost from plant roots supports a higher microbial population in the rhizosphere compared to bulk soil. Two fundamentally different¹⁴CO₂ labelling strategies have been developed to estimate carbon fluxes through the rhizosphere - continuous feeding of shoots with labelled carbon dioxide and pulse-chase experiments. The biological interpretation that can be placed on the results of labelling experiments is greatly biased by the technique used. It is the purpose of this paper to assess the advantages, disadvantages and the biological interpretation of both continuous and pulse labelling and to consider how to partition carbon fluxes within the rhizosphere. © 1994 Kluwer Academic Publishers.

An Evaluation of Vaneless Diffuser Modelling Methods as a Means of Improving the Off-Design Performance Prediction of Centrifugal Compressors

An evaluation of existing 1-D vaneless diffuser design tools in the context of improving the off-design performance prediction of automotive turbocharger centrifugal compressors is described. A combination of extensive gas stand test data and single passage CFD simulations have been employed in order to permit evaluation of the different methods, allowing conclusions about the relative benefits and deficiencies of each of the different approaches to be determined. The vaneless diffuser itself has been isolated from the incumbent limitations in the accuracy of 1-D impeller modelling tools through development of a method to fully specify impeller exit conditions (in terms of mean quantities) using only standard test stand data with additional interstage static pressure measurements at the entrance to the diffuser. This method allowed a direct comparison between the test data and 1-D methods through sharing common inputs, thus achieving the aim of diffuser isolation.

Crucial to the accuracy of determining the performance of each of the vaneless diffuser configurations was the ability to quantify the presence and extent of the spanwise aerodynamic blockage present at the diffuser inlet section. A method to evaluate this critical parameter using CFD data is described herein, along with a correlation for blockage related to a new diffuser inlet flow parameter ⚡, equal to the quotient of the local flow coefficient and impeller tip speed Mach number. The resulting correlation permitted the variation of blockage with operating condition to be captured.