High-pressure adsorption of supercritical gases on activated carbons: An improved approach based on the density functional theory and the bender equation of state

Adsorption of nitrogen, argon, methane, and carbon dioxide on activated carbon Norit R1 over a wide range of pressure (up to 50 MPa) at temperatures from 298 to 343 K (supercritical conditions) is analyzed by means of the density functional theory modified by incorporating the Bender equation of state, which describes the bulk phase properties with very high accuracy. It has allowed us to precisely describe the experimental data of carbon dioxide adsorption slightly above and below its critical temperatures. The pore size distribution (PSD) obtained with supercritical gases at ambient temperatures compares reasonably well with the PSD obtained with subcritical nitrogen at 77 K. Our approach does not require the skeletal density of activated carbon from helium adsorption measurements to calculate excess adsorption. Instead, this density is treated as a fitting parameter, and in all cases its values are found to fall into a very narrow range close to 2000 kg/m(3). It was shown that in the case of high-pressure adsorption of supercritical gases the PSD could be reliably obtained for the range of pore width between 0.6 and 3 run. All wider pores can be reliably characterized only in terms of surface area as their corresponding excess local isotherms are the same over a practical range of pressure.

Web services based state of the environment reporting

The Environmental Sciences Division within Queensland Environmental Protection Agency works to monitor, assess and model the condition of the environment. The Division has as a legislative responsibility to produce a whole-of-government report every four years dealing environmental conditions and trends in a ”State of the Environment report” (SoE)[1][2][3]. State of Environment Web Service Reporting System is a supplementary web service based SoE reporting tool, which aims to deliver accurate, timely and accessible information on the condition of the environment through web services via Internet [4][5]. This prototype provides a scientific assessment of environmental conditions for a set of environmental indicators. It contains text descriptions and tables, charts and maps with spatiotemporal dimensions to show the impact of certain environmental indicators on our environment. This prototype is a template based indicator system, to which the administrator may add new sql queries for new indicator services without changing the architecture and codes of this template. The benefits are brought through a service-oriented architecture which provides an online query service with seamless integration. In addition, since it uses web service architecture, each individual component within the application can be implemented by using different programming languages and in different operating systems. Although the services showed in this demo are built upon two datasets of regional ecosystem and protection area of Queensland, it will be possible to report on the condition of water, air, land, coastal zones, energy resources, biodiversity, human settlements and natural culture heritage on the fly as well. Figure 1 shows the architecture of the prototype. In the next section, I will discuss the research tasks in the prototype.

Numerical method for determination of the NMR frequency of the single-qubit operation in a silicon-based solid-state quantum computer

A numerical method is introduced to determine the nuclear magnetic resonance frequency of a donor (P-31) doped inside a silicon substrate under the influence of an applied electric field. This phosphorus donor has been suggested for operation as a qubit for the realization of a solid-state scalable quantum computer. The operation of the qubit is achieved by a combination of the rotation of the phosphorus nuclear spin through a globally applied magnetic field and the selection of the phosphorus nucleus through a locally applied electric field. To realize the selection function, it is required to know the relationship between the applied electric field and the change of the nuclear magnetic resonance frequency of phosphorus. In this study, based on the wave functions obtained by the effective-mass theory, we introduce an empirical correction factor to the wave functions at the donor nucleus. Using the corrected wave functions, we formulate a first-order perturbation theory for the perturbed system under the influence of an electric field. In order to calculate the potential distributions inside the silicon and the silicon dioxide layers due to the applied electric field, we use the multilayered Green's functions and solve an integral equation by the moment method. This enables us to consider more realistic, arbitrary shape, and three-dimensional qubit structures. With the calculation of the potential distributions, we have investigated the effects of the thicknesses of silicon and silicon dioxide layers, the relative position of the donor, and the applied electric field on the nuclear magnetic resonance frequency of the donor.

Model-Driven safety evaluation with state-event-based component failure annotations

Over the past years, the paradigm of component-based software engineering has been established in the construction of complex mission-critical systems. Due to this trend, there is a practical need for techniques that evaluate critical properties (such as safety, reliability, availability or performance) of these systems. In this paper, we review several high-level techniques for the evaluation of safety properties for component-based systems and we propose a new evaluation model (State Event Fault Trees) that extends safety analysis towards a lower abstraction level. This model possesses a state-event semantics and strong encapsulation, which is especially useful for the evaluation of component-based software systems. Finally, we compare the techniques and give suggestions for their combined usage

The views of corporate managers on the current state of, and future prospects for, social reporting in Bangladesh: an engagement based study

Purpose – This paper seeks to respond to recent calls for more engagement-based studies of corporate social reporting (CSR) practice by examining the views of corporate managers on the current state of, and future prospects for, social reporting in Bangladesh. Design/methodology/approach – The paper uses a series of interviews with senior managers from 23 Bangladeshi companies representing the multinational, domestic private and public sectors. Findings – Key findings are that the main motivation behind current reporting practice lies in a desire on the part of corporate management to manage powerful stakeholder groups, whilst perceived pressure from external forces, notably parent companies' instructions and demands from international buyers, is driving the process forward. In the latter context it appears that adoption of international social accounting standards and codes is likely to become more prevalent in the future. Reservations are expressed as to whether such a passive compliance strategy is likely to achieve much in the way of real changes in corporate behaviour, particularly when Western developed standards and codes are imposed without consideration of local cultural, economic and social factors. Indeed, such imposition could be regarded as little more than an example of the erection of non-tariff trade barriers rather than representing any meaningful move towards empowering indigenous stakeholder groups. Originality/value – The paper contributes to the literature on CSR in developing countries where there is a distinct lack of engagement-based published studies.

A method for automatically eliciting node weights in a hierarchical knowledge-based structure for reasoning with uncertainty

Hierarchical knowledge structures are frequently used within clinical decision support systems as part of the model for generating intelligent advice. The nodes in the hierarchy inevitably have varying influence on the decisionmaking processes, which needs to be reflected by parameters. If the model has been elicited from human experts, it is not feasible to ask them to estimate the parameters because there will be so many in even moderately-sized structures. This paper describes how the parameters could be obtained from data instead, using only a small number of cases. The original method [1] is applied to a particular web-based clinical decision support system called GRiST, which uses its hierarchical knowledge to quantify the risks associated with mental-health problems. The knowledge was elicited from multidisciplinary mental-health practitioners but the tree has several thousand nodes, all requiring an estimation of their relative influence on the assessment process. The method described in the paper shows how they can be obtained from about 200 cases instead. It greatly reduces the experts’ elicitation tasks and has the potential for being generalised to similar knowledge-engineering domains where relative weightings of node siblings are part of the parameter space.

Ontology-based protein-protein interactions extraction from literature using the hidden vector state model

This paper proposes a novel framework of incorporating protein-protein interactions (PPI) ontology knowledge into PPI extraction from biomedical literature in order to address the emerging challenges of deep natural language understanding. It is built upon the existing work on relation extraction using the Hidden Vector State (HVS) model. The HVS model belongs to the category of statistical learning methods. It can be trained directly from un-annotated data in a constrained way whilst at the same time being able to capture the underlying named entity relationships. However, it is difficult to incorporate background knowledge or non-local information into the HVS model. This paper proposes to represent the HVS model as a conditionally trained undirected graphical model in which non-local features derived from PPI ontology through inference would be easily incorporated. The seamless fusion of ontology inference with statistical learning produces a new paradigm to information extraction.

A Cognitive Science Reasoning in Recognition of Emotions in Audio-Visual Speech

In this report we summarize the state-of-the-art of speech emotion recognition from the signal processing point of view. On the bases of multi-corporal experiments with machine-learning classifiers, the observation is made that existing approaches for supervised machine learning lead to database dependent classifiers which can not be applied for multi-language speech emotion recognition without additional training because they discriminate the emotion classes following the used training language. As there are experimental results showing that Humans can perform language independent categorisation, we made a parallel between machine recognition and the cognitive process and tried to discover the sources of these divergent results. The analysis suggests that the main difference is that the speech perception allows extraction of language independent features although language dependent features are incorporated in all levels of the speech signal and play as a strong discriminative function in human perception. Based on several results in related domains, we have suggested that in addition, the cognitive process of emotion-recognition is based on categorisation, assisted by some hierarchical structure of the emotional categories, existing in the cognitive space of all humans. We propose a strategy for developing language independent machine emotion recognition, related to the identification of language independent speech features and the use of additional information from visual (expression) features.

Resting state morphology predicts the effect of theta burst stimulation in false belief reasoning:ventrolateral prefrontal cortex in false belief reasoning

When required to represent a perspective that conflicts with one's own, functional magnetic resonance imaging (fMRI) suggests that the right ventrolateral prefrontal cortex (rvlPFC) supports the inhibition of that conflicting self-perspective. The present task dissociated inhibition of self-perspective from other executive control processes by contrasting belief reasoning-a cognitive state where the presence of conflicting perspectives was manipulated-with a conative desire state wherein no systematic conflict existed. Linear modeling was used to examine the effect of continuous theta burst stimulation (cTBS) to rvlPFC on participants' reaction times in belief and desire reasoning. It was anticipated that cTBS applied to rvlPFC would affect belief but not desire reasoning, by modulating activity in the Ventral Attention System (VAS). We further anticipated that this effect would be mediated by functional connectivity within this network, which was identified using resting state fMRI and an unbiased model-free approach. Simple reaction-time analysis failed to detect an effect of cTBS. However, by additionally modeling individual measures from within the stimulated network, the hypothesized effect of cTBS to belief (but, importantly, not desire) reasoning was demonstrated. Structural morphology within the stimulated region, rvlPFC, and right temporoparietal junction were demonstrated to underlie this effect. These data provide evidence that inconsistencies found with cTBS can be mediated by the composition of the functional network that is being stimulated. We suggest that the common claim that this network constitutes the VAS explains the effect of cTBS to this network on false belief reasoning. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.

(Table, Appendix C) Metal content of nodules at Sea Scope stations based upon XRF analyses at the Ore Microscopy Laboratory, Washington State Unicersity, USA

New information on possible resource value of sea floor manganese nodule deposits in the eastern north Pacific has been obtained by a study of records and collections of the 1972 Sea Scope Expedition. Nodule abundance (percent of sea floor covered) varies greatly, according to photographs from eight stations and data from other sources. All estimates considered reliable are plotted on a map of the region. Similar maps show the average content of Ni, Cu, Mn and Co at 89 stations from which three or more nodules were analyzed. Variations in nodule metal content at each station are shown graphically in an appendix, where data on nodule sizes are also given. Results of new analyses of 420 nodules from 93 stations for mn, fe, ni, cu, CO, and zn are listed in another appendix. Relatively high Ni + Cu content is restricted chiefly to four groups of stations in the equatorial region, where group averages are 1.86, 1.99, 2.47, and 2.55 weight-percent. Prepared for United States Department of the Interior, Bureau of Mines. Grant no. GO284008-02-MAS. - NTIS PB82-142571.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.

Reasoning about change over time: Actions, events and their effects

This paper presents a new formalism for reasoning about change over time. The formalism derives a clean separation between the notion of states and situations. It allows more flexible temporal causal relationships than do other formalisms for reasoning about causal change, such as the situation calculus and the event calculus. It includes effects that start during, immediately after, or some time after their causes, and which end before, simultaneously with, or after their causes. A formal distinction between actions, action-types and events is proposed, which allows the expression of common-sense causal laws at high level. It is shown how these laws can be used to deduce state change over time at low level, when events occur under certain preconditions hold. Two problems that beset most interval-based temporal systems, i.e., the so-called dividing instant problem and intermingling problem, are absent from the formalism.