Amphibian yolk platelet ultrastructure visualized by freeze-etching

Amphibian yolk platelets are composed of lipoprotein subunits arranged in an ordered crystalline structure. Freeze-etch electron microscopy of isolated Xenopus platelets provides a direct view of the structure of the crystal and aids the interpretation of fracture phenomena in lipoprotein systems. A study has been made both of fracture faces and of faces produced by fracturing and etching following partial dissolution of platelets in electrolyte solutions. In freeze-etch replicas, main body crystals appear to be composed of dimers. Rectangular and semihexagonal patterns are seen in fracture faces. Rectangular patterns are seen also in faces produced by partial dissolution and revealed by fracturing and etching. Dissolution faces with possible semihexagonal patterns are distinct but infrequent. Based on this evidence, a new closest-packing model of platelet structure is proposed using lipovitellin dimers as building blocks, with one molecule of the second major protein component, phosvitin, associated with each monomer of the lipovitellin dimer. © 1972 Academic Press, Inc.

The Danger Theory and Its Application to Artificial Immune Systems

Over the last decade, a new idea challenging the classical self-non-self viewpoint has become popular amongst immunologists. It is called the Danger Theory. In this conceptual paper, we look at this theory from the perspective of Artificial Immune System practitioners. An overview of the Danger Theory is presented with particular emphasis on analogies in the Artificial Immune Systems world. A number of potential application areas are then used to provide a framing for a critical assessment of the concept, and its relevance for Artificial Immune Systems.

'Artificial Immune Systems Tutorial'

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.

Artificial Immune Tissue using Self-Organizing Networks

As introduced by Bentley et al. (2005), artificial immune systems (AIS) are lacking tissue, which is present in one form or another in all living multi-cellular organisms. Some have argued that this concept in the context of AIS brings little novelty to the already saturated field of the immune inspired computational research. This article aims to show that such a component of an AIS has the potential to bring an advantage to a data processing algorithm in terms of data pre-processing, clustering and extraction of features desired by the immune inspired system. The proposed tissue algorithm is based on self-organizing networks, such as self-organizing maps (SOM) developed by Kohonen (1996) and an analogy of the so called Toll-Like Receptors (TLR) affecting the activation function of the clusters developed by the SOM.

Elucidating the interactions between the adhesive and transcriptioanl functions of beta-catenin in normal and cancerous cells

Wnt signalling is involved in a wide range of physiological and pathological processes. The presence of an extracellular Wnt stimulus induces cytoplasmic stabilisation and nuclear translocation of beta-catenin, a protein that also plays an essential role in cadherin-mediated adhesion. Two main hypotheses have been proposed concerning the balance between beta-catenin's adhesive and transcriptional functions: either beta-catenin's fate is determined by competition between its binding partners, or Wnt induces folding of beta-catenin into a conformation allocated preferentially to transcription. The experimental data supporting each hypotheses remain inconclusive. In this paper we present a new mathematical model of the Wnt pathway that incorporates beta-catenin's dual function. We use this model to carry out a series of in silico experiments and compare the behaviour of systems governed by each hypothesis. Our analytical results and model simulations provide further insight into the current understanding of Wnt signalling and, in particular, reveal differences in the response of the two modes of interaction between adhesion and signalling in certain in silico settings. We also exploit our model to investigate the impact of the mutations most commonly observed in human colorectal cancer. Simulations show that the amount of functional APC required to maintain a normal phenotype increases with increasing strength of the Wnt signal, a result which illustrates that the environment can substantially influence both tumour initiation and phenotype.

'Artificial Immune Systems Tutorial'

The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.

Artificial Immune Tissue using Self-Organizing Networks

As introduced by Bentley et al. (2005), artificial immune systems (AIS) are lacking tissue, which is present in one form or another in all living multi-cellular organisms. Some have argued that this concept in the context of AIS brings little novelty to the already saturated field of the immune inspired computational research. This article aims to show that such a component of an AIS has the potential to bring an advantage to a data processing algorithm in terms of data pre-processing, clustering and extraction of features desired by the immune inspired system. The proposed tissue algorithm is based on self-organizing networks, such as self-organizing maps (SOM) developed by Kohonen (1996) and an analogy of the so called Toll-Like Receptors (TLR) affecting the activation function of the clusters developed by the SOM.

The Danger Theory and Its Application to Artificial Immune Systems

Over the last decade, a new idea challenging the classical self-non-self viewpoint has become popular amongst immunologists. It is called the Danger Theory. In this conceptual paper, we look at this theory from the perspective of Artificial Immune System practitioners. An overview of the Danger Theory is presented with particular emphasis on analogies in the Artificial Immune Systems world. A number of potential application areas are then used to provide a framing for a critical assessment of the concept, and its relevance for Artificial Immune Systems.

The Danger Theory and its Application to Artificial Immune Systems

Over the last decade, a new idea challenging the classical self-non-self viewpoint has become popular amongst immunologists. It is called the Danger Theory. In this conceptual paper, we look at this theory from the perspective of Artificial Immune System practitioners. An overview of the Danger Theory is presented with particular emphasis on analogies in the Artificial Immune Systems world. A number of potential application areas are then used to provide a framing for a critical assessment of the concept, and its relevance for Artificial Immune Systems. Notes: Uwe Aickelin, Department of Computing, University of Bradford, Bradford, BD7 1DP

An ecosystem of products and systems for ambient intelligence – the AAL4ALL users perspective

Texto completo em atas de encontros científicos internacionais com arbitragem

Low‑cost origami fabrication of 3D self‑aligned hybrid microfluidic structures

[EN] 3D microfluidic device fabrication methods are normally quite expensive and tedious. In this paper, we present an easy and cheap alternative wherein thin cyclic olefin polymer (COP) sheets and pressure sensitive adhesive(PSA) were used to fabricate hybrid 3D microfluidic structures, by the Origami technique, which enables the fabrication of microfluidic devices without the need of any alignment tool. The COP and PSA layers were both cut simultaneously using a portable, low-cost plotter allowing for rapid prototyping of a large variety of designs in a single production step. The devices were then manually assembled using the Origami technique by simply combining COP and PSA layers and mild pressure. This fast fabrication method was applied, as proof of concept, to the generation of a micromixer with a 3D-stepped serpentine design made of ten layers in less than 8 min. Moreover, the micromixer was characterized as a function of its pressure failure, achieving pressures of up to 1000 mbar. This fabrication method is readily accessible across a large range of potential end users, such as educational agencies (schools,universities), low-income/developing world research and industry or any laboratory without access to clean room facilities, enabling the fabrication of robust, reproducible microfluidic devices.

Simulation tools for the analysis of single electronic systems

Developments in theory and experiment have raised the prospect of an electronic technology based on the discrete nature of electron tunnelling through a potential barrier. This thesis deals with novel design and analysis tools developed to study such systems. Possible devices include those constructed from ultrasmall normal tunnelling junctions. These exhibit charging effects including the Coulomb blockade and correlated electron tunnelling. They allow transistor-like control of the transfer of single carriers, and present the prospect of digital systems operating at the information theoretic limit. As such, they are often referred to as single electronic devices. Single electronic devices exhibit self quantising logic and good structural tolerance. Their speed, immunity to thermal noise, and operating voltage all scale beneficially with junction capacitance. For ultrasmall junctions the possibility of room temperature operation at sub picosecond timescales seems feasible. However, they are sensitive to external charge; whether from trapping-detrapping events, externally gated potentials, or system cross-talk. Quantum effects such as charge macroscopic quantum tunnelling may degrade performance. Finally, any practical system will be complex and spatially extended (amplifying the above problems), and prone to fabrication imperfection. This summarises why new design and analysis tools are required. Simulation tools are developed, concentrating on the basic building blocks of single electronic systems; the tunnelling junction array and gated turnstile device. Three main points are considered: the best method of estimating capacitance values from physical system geometry; the mathematical model which should represent electron tunnelling based on this data; application of this model to the investigation of single electronic systems. (DXN004909)

High Precision Plasma Etch for Pattern Transfer: Towards Fluorocarbon Based Atomic Layer Etching

A basic requirement of a plasma etching process is fidelity of the patterned organic materials. In photolithography, a He plasma pretreatment (PPT) based on high ultraviolet and vacuum ultraviolet (UV/VUV) exposure was shown to be successful for roughness reduction of 193nm photoresist (PR). Typical multilayer masks consist of many other organic masking materials in addition to 193nm PR. These materials vary significantly in UV/VUV sensitivity and show, therefore, a different response to the He PPT. A delamination of the nanometer-thin, ion-induced dense amorphous carbon (DAC) layer was observed. Extensive He PPT exposure produces volatile species through UV/VUV induced scissioning. These species are trapped underneath the DAC layer in a subsequent plasma etch (PE), causing a loss of adhesion. Next to stabilizing organic materials, the major goals of this work included to establish and evaluate a cyclic fluorocarbon (FC) based approach for atomic layer etching (ALE) of SiO2 and Si; to characterize the mechanisms involved; and to evaluate the impact of processing parameters. Periodic, short precursor injections allow precise deposition of thin FC films. These films limit the amount of available chemical etchant during subsequent low energy, plasma-based Ar+ ion bombardment, resulting in strongly time-dependent etch rates. In situ ellipsometry showcased the self-limited etching. X-ray photoelectron spectroscopy (XPS) confirms FC film deposition and mixing with the substrate. The cyclic ALE approach is also able to precisely etch Si substrates. A reduced time-dependent etching is seen for Si, likely based on a lower physical sputtering energy threshold. A fluorinated, oxidized surface layer is present during ALE of Si and greatly influences the etch behavior. A reaction of the precursor with the fluorinated substrate upon precursor injection was observed and characterized. The cyclic ALE approach is transferred to a manufacturing scale reactor at IBM Research. Ensuring the transferability to industrial device patterning is crucial for the application of ALE. In addition to device patterning, the cyclic ALE process is employed for oxide removal from Si and SiGe surfaces with the goal of minimal substrate damage and surface residues. The ALE process developed for SiO2 and Si etching did not remove native oxide at the level required. Optimizing the process enabled strong O removal from the surface. Subsequent 90% H2/Ar plasma allow for removal of C and F residues.

A self-inducible heterologous protein expression system in Escherichia coli

International audience

Through Wafer 3D Vertical Micro-Coaxial Probe for High Frequency Material Characterization and Millimeter Wave Packaging Systems

This work presents the development of an in-plane vertical micro-coaxial probe using bulk micromachining technique for high frequency material characterization. The coaxial probe was fabricated in a silicon substrate by standard photolithography and a deep reactive ion etching (DRIE) technique. The through-hole structure in the form of a coaxial probe was etched and metalized with a diluted silver paste. A co-planar waveguide configuration was integrated with the design to characterize the probe. The electrical and RF characteristics of the coaxial probe were determined by simulating the probe design in Ansoft’s High Frequency Structure Simulator (HFSS). The reflection coefficient and transducer gain performance of the probe was measured up to 65 GHz using a vector network analyzer (VNA). The probe demonstrated excellent results over a wide frequency band, indicating its ability to integrate with millimeter wave packaging systems as well as characterize unknown materials at high frequencies. The probe was then placed in contact with 3 materials where their unknown permittivities were determined. To accomplish this, the coaxial probe was placed in contact with the material under test and electromagnetic waves were directed to the surface using the VNA, where its reflection coefficient was then determined over a wide frequency band from dc-to -65GHz. Next, the permittivity of each material was deduced from its measured reflection coefficients using a cross ratio invariance coding technique. The permittivity results obtained when measuring the reflection coefficient data were compared to simulated permittivity results and agreed well. These results validate the use of the micro-coaxial probe to characterize the permittivity of unknown materials at high frequencies up to 65GHz.