SU-8-Based Microchips for Capillary Electrophoresis and Electrospray Ionization Mass Spectrometry

Miniaturization of analytical instrumentation is attracting growing interest in response to the explosive demand for rapid, yet sensitive analytical methods and low-cost, highly automated instruments for pharmaceutical and bioanalyses and environmental monitoring. Microfabrication technology in particular, has enabled fabrication of low-cost microdevices with a high degree of integrated functions, such as sample preparation, chemical reaction, separation, and detection, on a single microchip. These miniaturized total chemical analysis systems (microTAS or lab-on-a-chip) can also be arrayed for parallel analyses in order to accelerate the sample throughput. Other motivations include reduced sample consumption and waste production as well as increased speed of analysis. One of the most promising hyphenated techniques in analytical chemistry is the combination of a microfluidic separation chip and mass spectrometer (MS). In this work, the emerging polymer microfabrication techniques, ultraviolet lithography in particular, were exploited to develop a capillary electrophoresis (CE) separation chip which incorporates a monolithically integrated electrospray ionization (ESI) emitter for efficient coupling with MS. An epoxy photoresist SU-8 was adopted as structural material and characterized with respect to its physicochemical properties relevant to chip-based CE and ESI/MS, namely surface charge, surface interactions, heat transfer, and solvent compatibility. As a result, SU-8 was found to be a favorable material to substitute for the more commonly used glass and silicon in microfluidic applications. In addition, an infrared (IR) thermography was introduced as direct, non-intrusive method to examine the heat transfer and thermal gradients during microchip-CE. The IR data was validated through numerical modeling. The analytical performance of SU-8-based microchips was established for qualitative and quantitative CE-ESI/MS analysis of small drug compounds, peptides, and proteins. The CE separation efficiency was found to be similar to that of commercial glass microchips and conventional CE systems. Typical analysis times were only 30-90 s per sample indicating feasibility for high-throughput analysis. Moreover, a mass detection limit at the low-attomole level, as low as 10E+5 molecules, was achieved utilizing MS detection. The SU-8 microchips developed in this work could also be mass produced at low cost and with nearly identical performance from chip to chip. Until this work, the attempts to combine CE separation with ESI in a chip-based system, amenable to batch fabrication and capable of high, reproducible analytical performance, have not been successful. Thus, the CE-ESI chip developed in this work is a substantial step toward lab-on-a-chip technology.

Australian innovation ecosystem: A critical review of the national innovation support mechanisms

Innovation is understood as the combination of existing ideas or the generation of new ideas into new processes, products and services, and widely viewed as the main driver of growth in contemporary economies. In the age of the knowledge economy, successful economic development is intimately linked to a country’s capacity to generate, acquire, absorb, disseminate, and apply innovation towards advanced technology products and services. This development approach is labelled as knowledge-based economic development and highly associated with a capacity embodied in a country’s national innovation ecosystem. The research reported in this paper aims to critically review the Australian innovation ecosystem in order to provide a better understanding on the potential impacts of policy and support mechanisms on the innovation and knowledge generation capacity. The investigation places Australia’s innovation system and national-level innovation support mechanisms under the microscope. The methodology of the study is twofold. Firstly, it undertakes a critical review of the literature and government policy documents to better understand the innovation policy and support mechanisms in the country. It, then, conducts a survey to capture Australian innovation companies’ perceptions on the role and effectiveness of the existing innovation incentive programs. The paper concludes with a discussion on the key insights and findings and potential policy and support directions of the country to achieve a flourishing knowledge economy.

Integrated Information and Communication Technology Strategies for Competitive Higher Education in Asia and the Pacific

Developing countries in Asia and the Pacific are rapidly reaching middle income economic status. Their competitive advantage is shifting from labor-intensive industries and natural resource-based economies to knowledge-based economies that innovate and create new products and services. Early adoption of information and communication technology (ICT) can allow countries to leapfrog over the traditional development pathway into production of knowledge-based products and services. Since higher education institutions (HEIs) are considered a primary engine of economic growth, adoption of ICT is imperative for securing competitive advantage. ICT is thought to be one of the fastest growing industries and is frequently heralded as a transforming influence on higher education systems globally and, consequently, is enhancing the competitive advantage of countries. It is increasingly becoming evident that an institution-wide ICT strategy covering all evolving functions of competitive HEIs is necessary. Such a system may be designed as an integrated platform but implemented in phases.

Tertiary Treatment of Ayr Municipal Wastewater using Bioremediation: A Pilot-Scale Study. A Report Prepared for the Burdekin Shire Council and the Burdekin Rangeland Reef Initiative

This joint DPI/Burdekin Shire Council project assessed the efficacy of a pilot-scale biological remediation system to recover Nitrogen (N) and Phosphorous (P) nutrients from secondary treated municipal wastewater at the Ayr Sewage Treatment Plant. Additionally, this study considered potential commercial uses for by-products from the treatment system. Knowledge gained from this study can provide directions for implementing a larger-scale final effluent treatment protocol on site at the Ayr plant. Trials were conducted over 10 months and assessed nutrient removal from duckweed-based treatments and an algae/fish treatment – both as sequential and as stand-alone treatment systems. A 42.3% reduction in Total N was found through the sequential treatment system (duckweed followed by algae/fish treatment) after 6.6 days Effluent Retention Time (E.R.T.). However, duckweed treatment was responsible for the majority of this nutrient recovery (7.8 times more effective than algae/fish treatment). Likewise, Total P reduction (15.75% reduction after 6.6 days E.R.T.) was twice as great in the duckweed treatment. A phytoplankton bloom, which developed in the algae/fish tanks, reduced nutrient recovery in this treatment. A second trial tested whether the addition of fish enhanced duckweed treatment by evaluating systems with and without fish. After four weeks operation, low DO under the duckweed blanket caused fish mortalities. Decomposition of these fish led to an additional organic load and this was reflected in a breakdown of nitrogen species that showed an increase in organic nitrogen. However, the Dissolved Inorganic Nitrogen (DIN: ammonia, nitrite and nitrate) removal was similar between treatments with and without fish (57% and 59% DIN removal from incoming, respectively). Overall, three effluent residence times were evaluated using duckweed-based treatments; i.e. 3.5 days, 5.5 days and 10.4 days. Total N removal was 37.5%, 55.7% and 70.3%, respectively. The 10.4-day E.R.T. trial, however, was evaluated by sequential nutrient removal through the duckweed-minus-fish treatment followed by the duckweed-plus-fish treatment. Therefore, the 70.3% Total N removal was lower than could have been achieved at this retention time due to the abovementioned fish mortalities. Phosphorous removal from duckweed treatments was greatest after 10.4-days E.R.T. (13.6%). Plant uptake was considered the most important mechanism for this P removal since there was no clay substrate in the plastic tanks that could have contributed to P absorption as part of the natural phosphorous cycle. Duckweed inhibited phytoplankton production (therefore reducing T.S.S) and maintained pH close to neutral. DO beneath the duckweed blanket fell to below 1ppm; however, this did not limit plant production. If fish are to be used as part of the duckweed treatment, air-uplifts can be installed that maintain DO levels without disturbing surface waters. Duckweed grown in the treatments doubled its biomass on average every 5.7 days. On a per-surface area basis, 1.23kg/m2 was harvested weekly. Moisture content of duckweed was 92%, equating to a total dry weight harvest of 0.098kg/m2/week. Nutrient analysis of dried duckweed gave an N content of 6.67% and a P content of 1.27%. According to semi-quantitative analyses, harvested duckweed contained no residual elements from the effluent stream that were greater than ANZECC toxicant guidelines proposed for aquaculture. In addition, jade perch, a local aquaculture species, actively consumed and gained weight on harvested duckweed, suggesting potential for large-scale fish production using by-products from the effluent treatment process. This suggests that a duckweed-based system may be one viable option for tertiary treatment of Ayr municipal wastewater. The tertiary detention lagoon proposed by the Burdekin Shire Council, consisting of six bays approximately 290 x 35 metres (x 1.5 metres deep), would be suitable for duckweed culture with minor modification to facilitate the efficient distribution of duckweed plants across the entire available growing surface (such as floating containment grids). The effluent residence time resulting from this proposed configuration (~30 days) should be adequate to recover most effluent nutrients (certainly N) based on the current trial. Duckweed harvest techniques on this scale, however, need to be further investigated. Based on duckweed production in the current trial (1.23kg/m2/week), a weekly harvest of approximately 75 000kg (wet weight) could be expected from the proposed lagoon configuration under full duckweed production. A benefit of the proposed multi-bay lagoon is that full lagoon production of duckweed may not be needed to restore effluent to a desirable standard under the present nutrient load, and duckweed treatment may be restricted to certain bays. Restored effluent could be released without risk of contaminating the receiving waterway with duckweed by evacuating water through an internal standpipe located mid-way in the water column.

A hybrid agent architecture for modeling autonomous agents in SAGE

This paper highlights the Hybrid agent construction model being developed that allows the description and development of autonomous agents in SAGE (Scalable, fault Tolerant Agent Grooming Environment) - a second generation FIPA-Compliant Multi-Agent system. We aim to provide the programmer with a generic and well defined agent architecture enabling the development of sophisticated agents on SAGE, possessing the desired properties of autonomous agents - reactivity, pro-activity, social ability and knowledge based reasoning. © Springer-Verlag Berlin Heidelberg 2005.

Place making for knowledge generation and innovation: Planning and branding Brisbane’s knowledge community precincts

Knowledge generation and innovation have been a priority for global city administrators particularly during the last couple of decades. This is mainly due to the growing consensus in identifying knowledge-based urban development as a panacea to the burgeoning economic problems. Place making has become a critical element for success in knowledge-based urban development as planning and branding places is claimed to be an effective marketing tool for attracting investment and talent. This paper aims to investigate the role of planning and branding in place making by assessing the effectiveness of planning and branding strategies in the development of knowledge and innovation milieus. The methodology of the study comprises reviewing the literature thoroughly, developing an analysis framework, and utilizing this framework in analyzing Brisbane’s knowledge community precincts—namely Boggo Road Knowledge Precinct, Kelvin Grove Urban Knowledge Village, and Sippy Downs Knowledge Town. The analysis findings generate invaluable insights in Brisbane’s journey in place making for knowledge and innovation milieus and communities. The results suggest as much as good planning, branding strategies and practice, the requirements of external and internal conditions also need to be met for successful place making in knowledge community precincts.

Decision support requirements for intelligent operation of southern grid in India

Control centers (CC) play a very important role in power system operation. An overall view of the system with information about all existing resources and needs is implemented through SCADA (Supervisory control and data acquisition system) and an EMS (energy management system). As advanced technologies have made their way into the utility environment, the operators are flooded with huge amount of data. The last decade has seen extensive applications of AI techniques, knowledge-based systems, Artificial Neural Networks in this area. This paper focuses on the need for development of an intelligent decision support system to assist the operator in making proper decisions. The requirements for realization of such a system are recognized for the effective operation and energy management of the southern grid in India The application of Petri nets leading to decision support system has been illustrated considering 24 bus system that is a part of southern grid.

A survey of indian logic from the point of view of computer science

Indian logic has a long history. It somewhat covers the domains of two of the six schools (darsanas) of Indian philosophy, namely, Nyaya and Vaisesika. The generally accepted definition of Indian logic over the ages is the science which ascertains valid knowledge either by means of six senses or by means of the five members of the syllogism. In other words, perception and inference constitute the subject matter of logic. The science of logic evolved in India through three ages: the ancient, the medieval and the modern, spanning almost thirty centuries. Advances in Computer Science, in particular, in Artificial Intelligence have got researchers in these areas interested in the basic problems of language, logic and cognition in the past three decades. In the 1980s, Artificial Intelligence has evolved into knowledge-based and intelligent system design, and the knowledge base and inference engine have become standard subsystems of an intelligent system. One of the important issues in the design of such systems is knowledge acquisition from humans who are experts in a branch of learning (such as medicine or law) and transferring that knowledge to a computing system. The second important issue in such systems is the validation of the knowledge base of the system i.e. ensuring that the knowledge is complete and consistent. It is in this context that comparative study of Indian logic with recent theories of logic, language and knowledge engineering will help the computer scientist understand the deeper implications of the terms and concepts he is currently using and attempting to develop.

Machine recognition of printed Kannada text

This paper presents the design of a full fledged OCR system for printed Kannada text. The machine recognition of Kannada characters is difficult due to similarity in the shapes of different characters, script complexity and non-uniqueness in the representation of diacritics. The document image is subject to line segmentation, word segmentation and zone detection. From the zonal information, base characters, vowel modifiers and consonant conjucts are separated. Knowledge based approach is employed for recognizing the base characters. Various features are employed for recognising the characters. These include the coefficients of the Discrete Cosine Transform, Discrete Wavelet Transform and Karhunen-Louve Transform. These features are fed to different classifiers. Structural features are used in the subsequent levels to discriminate confused characters. Use of structural features, increases recognition rate from 93% to 98%. Apart from the classical pattern classification technique of nearest neighbour, Artificial Neural Network (ANN) based classifiers like Back Propogation and Radial Basis Function (RBF) Networks have also been studied. The ANN classifiers are trained in supervised mode using the transform features. Highest recognition rate of 99% is obtained with RBF using second level approximation coefficients of Haar wavelets as the features on presegmented base characters.

Demanda de información sobre capital intelectual en las Universidades públicas españolas

[ES] En el actual contexto de la Sociedad del Conocimiento las instituciones de educación superior deben prestar una atención preferente a las nuevas demandas informativas de sus stakeholders. El objetivo de este trabajo será evidenciar la necesidad de que las universidades incorporen información sobre capital intelectual en su actual sistema de información contable.

Dialog Systems based on Markov decision processes over two real tasks

In this work the state of the art of the automatic dialogue strategy management using Markov decision processes (MDP) with reinforcement learning (RL) is described. Partially observable Markov decision processes (POMDP) are also described. To test the validity of these methods, two spoken dialogue systems have been developed. The first one is a spoken dialogue system for weather forecast providing, and the second one is a more complex system for train information. With the first system, comparisons between a rule-based system and an automatically trained system have been done, using a real corpus to train the automatic strategy. In the second system, the scalability of these methods when used in larger systems has been tested.

Neural and computational representations of decision variables

These studies explore how, where, and when representations of variables critical to decision-making are represented in the brain. In order to produce a decision, humans must first determine the relevant stimuli, actions, and possible outcomes before applying an algorithm that will select an action from those available. When choosing amongst alternative stimuli, the framework of value-based decision-making proposes that values are assigned to the stimuli and that these values are then compared in an abstract “value space” in order to produce a decision. Despite much progress, in particular regarding the pinpointing of ventromedial prefrontal cortex (vmPFC) as a region that encodes the value, many basic questions remain. In Chapter 2, I show that distributed BOLD signaling in vmPFC represents the value of stimuli under consideration in a manner that is independent of the type of stimulus it is. Thus the open question of whether value is represented in abstraction, a key tenet of value-based decision-making, is confirmed. However, I also show that stimulus-dependent value representations are also present in the brain during decision-making and suggest a potential neural pathway for stimulus-to-value transformations that integrates these two results.

More broadly speaking, there is both neural and behavioral evidence that two distinct control systems are at work during action selection. These two systems compose the “goal-directed system”, which selects actions based on an internal model of the environment, and the “habitual” system, which generates responses based on antecedent stimuli only. Computational characterizations of these two systems imply that they have different informational requirements in terms of input stimuli, actions, and possible outcomes. Associative learning theory predicts that the habitual system should utilize stimulus and action information only, while goal-directed behavior requires that outcomes as well as stimuli and actions be processed. In Chapter 3, I test whether areas of the brain hypothesized to be involved in habitual versus goal-directed control represent the corresponding theorized variables.

The question of whether one or both of these neural systems drives Pavlovian conditioning is less well-studied. Chapter 4 describes an experiment in which subjects were scanned while engaged in a Pavlovian task with a simple non-trivial structure. After comparing a variety of model-based and model-free learning algorithms (thought to underpin goal-directed and habitual decision-making, respectively), it was found that subjects’ reaction times were better explained by a model-based system. In addition, neural signaling of precision, a variable based on a representation of a world model, was found in the amygdala. These data indicate that the influence of model-based representations of the environment can extend even to the most basic learning processes.

Knowledge of the state of hidden variables in an environment is required for optimal inference regarding the abstract decision structure of a given environment and therefore can be crucial to decision-making in a wide range of situations. Inferring the state of an abstract variable requires the generation and manipulation of an internal representation of beliefs over the values of the hidden variable. In Chapter 5, I describe behavioral and neural results regarding the learning strategies employed by human subjects in a hierarchical state-estimation task. In particular, a comprehensive model fit and comparison process pointed to the use of "belief thresholding". This implies that subjects tended to eliminate low-probability hypotheses regarding the state of the environment from their internal model and ceased to update the corresponding variables. Thus, in concert with incremental Bayesian learning, humans explicitly manipulate their internal model of the generative process during hierarchical inference consistent with a serial hypothesis testing strategy.

2.0 funtsezko tresna bezala informazioaren kudeaketan

[EU]Ezagutzaren gizartean aurkitzen gara eta informazioak enpresa munduan hartu duen garrantziak garapen berriak ekarri ditu bai ikerketan bai informazio eta komunikazio teknologietan (IKT). Beraz, enpresek informazioa era sistematiko batean kudeatu beharra dute ez badute lehiakortasuna galdu nahi. Egoera honetan, zaintza teknologikoak paper garrantzitsu bat betetzen du informazioa lortzeaz, gordetzeaz eta transmititzeaz arduratzen den sistema baita. Baina sistema honen irispena mugatuta egongo da erabiltzen diren baliabideengatik. Gainera, muga hori garrantzi handiagoa hartzen du ETEtan, Euskal Herriko ekonomia-ehunaren oinarria, non baliabideak minimoak diren eta enpresa handiagoekin lehiatu behar diren. Egoera honi aurre egiteko, 2.0 tresnak aurkezten dira, zaintza teknologikorako baliagarriak diren tresnak, kostu eta denbora minimoak eskatzen dituztenak. Horrela, lan hau Euskal Herriko ETEtan zaintza teknologikoaren egoera aztertzera eta bere beharretara egokitzen diren soluzio teknologikoak planteatzera zuzenduta joango da, 2.0 tresnak oinarri moduan daudela.

Spoken document representations for probabilistic retrieval

This paper presents some developments in query expansion and document representation of our spoken document retrieval system and shows how various retrieval techniques affect performance for different sets of transcriptions derived from a common speech source. Modifications of the document representation are used, which combine several techniques for query expansion, knowledge-based on one hand and statistics-based on the other. Taken together, these techniques can improve Average Precision by over 19% relative to a system similar to that which we presented at TREC-7. These new experiments have also confirmed that the degradation of Average Precision due to a word error rate (WER) of 25% is quite small (3.7% relative) and can be reduced to almost zero (0.2% relative). The overall improvement of the retrieval system can also be observed for seven different sets of transcriptions from different recognition engines with a WER ranging from 24.8% to 61.5%. We hope to repeat these experiments when larger document collections become available, in order to evaluate the scalability of these techniques.

A vision-based remote control

This Chapter presents a vision-based system for touch-free interaction with a display at a distance. A single camera is fixed on top of the screen and is pointing towards the user. An attention mechanism allows the user to start the interaction and control a screen pointer by moving their hand in a fist pose directed at the camera. On-screen items can be chosen by a selection mechanism. Current sample applications include browsing video collections as well as viewing a gallery of 3D objects, which the user can rotate with their hand motion. We have included an up-to-date review of hand tracking methods, and comment on the merits and shortcomings of previous approaches. The proposed tracker uses multiple cues, appearance, color, and motion, for robustness. As the space of possible observation models is generally too large for exhaustive online search, we select models that are suitable for the particular tracking task at hand. During a training stage, various off-the-shelf trackers are evaluated. From this data differentmethods of fusing them online are investigated, including parallel and cascaded tracker evaluation. For the case of fist tracking, combining a small number of observers in a cascade results in an efficient algorithm that is used in our gesture interface. The system has been on public display at conferences where over a hundred users have engaged with it. © 2010 Springer-Verlag Berlin Heidelberg.