The performance of poly(styrene)-block-poly(2-vinyl pyridine)-block- poly(styrene) triblock copolymers as pH-driven actuators

Poly(styrene)-block-poly(2-vinyl pyridine)-block-poly(styrene) (PS-b-P2VP-b-PS) triblock copolymers were synthesised by anionic polymerisation. Thick films were cast from solution and their structure analysed by small angle X-ray scattering (SAXS). Longer annealing times led to more ordered structures whereas short evaporation times effectively "lock" the polymer chains in a disordered state by vitrification. Well-ordered structures not only provide an isotropic network, which reduces localised stress within the material, but are also essential for fundamental studies of soft matter because their activity on the molecular scale must be analysed and understood prior to their use in technological applications. Well-characterised PS-b-P2VP-b-PS materials have been coupled to a pH-oscillating reaction and their potential application as responsive actuators is discussed. This journal is © The Royal Society of Chemistry.

Semiconductor optical amplifier-based nonlinear optical-loop mirror with feedback

The behavior of a semiconductor optical amplifier (SOA)-based nonlinear loop mirror with feedback has been investigated as a potential device for all-optical signal processing. In the feedback device, input signal pulses (ones) are injected into the loop, and amplified reflected pulses are fed back into the loop as switching pulses. The feedback device has two stable modes of operation - block mode, where alternating blocks of ones and zeros are observed, and spontaneous clock division mode, where halving of the input repetition rate is achieved. Improved models of the feedback device have been developed to study its performance in different operating conditions. The feedback device could be optimized to give a choice of either of the two stable modes by shifting the arrival time of the switching pulses at the SOA. Theoretically, it was found possible to operate the device at only tens of fJ switching pulse energies if the SOA is biased to produce very high gain in the presence of internal loss. The clock division regime arises from the combination of incomplete SOA gain recovery and memory of the startup sequence that is provided by the feedback. Clock division requires a sufficiently high differential phase shift per unit differential gain, which is related to the SOA linewidth enhancement factor.

Connection of Network Sensors to Distributed Information Measurement and Control System for Education and Research

The development of the distributed information measurement and control system for optical spectral research of particle beam and plasma objects and the execution of laboratory works on Physics and Engineering Department of Petrozavodsk State University are described. At the hardware level the system is represented by a complex of the automated workplaces joined into computer network. The key element of the system is the communication server, which supports the multi-user mode and distributes resources among clients, monitors the system and provides secure access. Other system components are formed by equipment servers (CАМАC and GPIB servers, a server for the access to microcontrollers MCS-196 and others) and the client programs that carry out data acquisition, accumulation and processing and management of the course of the experiment as well. In this work the designed by the authors network interface is discussed. The interface provides the connection of measuring and executive devices to the distributed information measurement and control system via Ethernet. This interface allows controlling of experimental parameters by use of digital devices, monitoring of experiment parameters by polling of analog and digital sensors. The device firmware is written in assembler language and includes libraries for Ethernet-, IP-, TCP- и UDP-packets forming.

Device for Counting of the Glass Bottles on the Conveyor Belt

In the present paper the results from designing of device, which is a part of the automated information system for counting, reporting and documenting the quantity of produced bottles in a factory for glass processing are presented. The block diagram of the device is given. The introduced system can be applied in other discrete productions for counting of the quantity of bottled production.

Fullerene-capped copolymers for bulk heterojunctions: device stability and efficiency improvements

A fullerene end-capped polymer-compatibilizer based on poly(3-hexylthiophene) (P3HT) was synthesized and demonstrated to have a remarkable effect on both the stability and efficiency of devices made from exemplar P3HT and [6,6]-phenyl C61-butyric acid methyl ester (PCBM). P3HT with ethynyl chain-ends and α-azido-ω-bromo-PS were prepared via Grignard metathesis (GRIM) and atom transfer radical polymerisation, respectively. “Click” chemistry resulted in the preparation of poly(3-hexylthiophene)-block-ω-bromo-polystyrene (P3HT-b-PS-Br), and subsequent atom transfer radical addition chemistry with fullerene (C60) yielded the donor–acceptor block copolymer P3HT-b-PS-C60. Both P3HT-b-PS-Br and P3HT-b-PS-C60 were considered as compatibilizers with P3HT/PCBM blends, with the study detailing effects on active-layer morphology, device efficiency and stability. When used at low concentrations, both P3HT-b-PS-Br (1%) and P3HT-b-PS-C60 (0.5%) resulted in considerable 28% and 35% increases in efficiencies with respect to devices made from P3HT/PCBM alone. Furthermore, P3HT-b-PS-C60 (0.5%) resulted in an important improvement in device stability.

A Bayesian neural network algorithm identifies patients in whom post-EVAR surveillance may be unnecessary

Lifelong surveillance is not cost-effective after endovascular aneurysm repair (EVAR), but is required to detect aortic complications which are fatal if untreated (type 1/3 endoleak, sac expansion, device migration). Aneurysm morphology determines the probability of aortic complications and therefore the need for surveillance, but existing analyses have proven incapable of identifying patients at sufficiently low risk to justify abandoning surveillance. This study aimed to improve the prediction of aortic complications, through the application of machine-learning techniques. Patients undergoing EVAR at 2 centres were studied from 2004–2010. Aneurysm morphology had previously been studied to derive the SGVI Score for predicting aortic complications. Bayesian Neural Networks were designed using the same data, to dichotomise patients into groups at low- or high-risk of aortic complications. Network training was performed only on patients treated at centre 1. External validation was performed by assessing network performance independently of network training, on patients treated at centre 2. Discrimination was assessed by Kaplan-Meier analysis to compare aortic complications in predicted low-risk versus predicted high-risk patients. 761 patients aged 75 +/− 7 years underwent EVAR in 2 centres. Mean follow-up was 36+/− 20 months. Neural networks were created incorporating neck angu- lation/length/diameter/volume; AAA diameter/area/volume/length/tortuosity; and common iliac tortuosity/diameter. A 19-feature network predicted aor- tic complications with excellent discrimination and external validation (5-year freedom from aortic complications in predicted low-risk vs predicted high-risk patients: 97.9% vs. 63%; p < 0.0001). A Bayesian Neural-Network algorithm can identify patients in whom it may be safe to abandon surveillance after EVAR. This proposal requires prospective study.

Design strategies for an artificial neural network based algorithm for automatic incident detection on major arterial streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our nation’s highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Design Strategies for an Artificial Neural Network Based Algorithm for Automatic Incident Detection on Major Arterial Streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our national highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Verification of the indoor gps system by comparison with points calibrated using a network of laser tracker measurements

This paper details a method of determining the uncertainty of dimensional measurement for a three dimensional coordinate measurement machine. An experimental procedure was developed to compare three dimensional coordinate measurements with calibrated reference points. The reference standard used to calibrate these reference points was a fringe counting interferometer with the multilateration technique employed to establish three dimensional coordinates. This is an extension of the established technique of comparing measured lengths with calibrated lengths. Specifically a distributed coordinate measurement device was tested which consisted of a network of Rotary-Laser Automatic Theodolites (R-LATs), this system is known commercially as indoor GPS (iGPS). The method was found to be practical and able to establish that the expanded uncertainty of the basic iGPS system was approximately 1 mm at a 95% confidence level. © Springer-Verlag Berlin Heidelberg 2010.

Artificial neural network application in short-term prediction in an oscillating water column

Oscillating Water Column (OWC) is one type of promising wave energy devices due to its obvious advantage over many other wave energy converters: no moving component in sea water. Two types of OWCs (bottom-fixed and floating) have been widely investigated, and the bottom-fixed OWCs have been very successful in several practical applications. Recently, the proposal of massive wave energy production and the availability of wave energy have pushed OWC applications from near-shore to deeper water regions where floating OWCs are a better choice. For an OWC under sea waves, the air flow driving air turbine to generate electricity is a random process. In such a working condition, single design/operation point is nonexistent. To improve energy extraction, and to optimise the performance of the device, a system capable of controlling the air turbine rotation speed is desirable. To achieve that, this paper presents a short-term prediction of the random, process by an artificial neural network (ANN), which can provide near-future information for the control system. In this research, ANN is explored and tuned for a better prediction of the airflow (as well as the device motions for a wide application). It is found that, by carefully constructing ANN platform and optimizing the relevant parameters, ANN is capable of predicting the random process a few steps ahead of the real, time with a good accuracy. More importantly, the tuned ANN works for a large range of different types of random, process.

Fabrication of sub-10 nm lamellar structures by solvent vapour annealing of block copolymers

Fabrication of nanoscale patterns through the bottom-up approach of self-assembly of phase-separated block copolymers (BCP) holds promise for nanoelectronics applications. For lithographic applications, it is useful to vary the morphology of BCPs by monitoring various parameters to make “from lab to fab” a reality. Here I report on the solvent annealing studies of lamellae forming polystyrene-blockpoly( 4-vinylpyridine) (PS-b-P4VP). The high Flory-Huggins parameter (χ = 0.34) of PS-b-P4VP makes it an ideal BCP system for self-assembly and template fabrication in comparison to other BCPs. Different molecular weights of symmetric PS-b-P4VP BCPs forming lamellae patterns were used to produce nanostructured thin films by spin-coating from mixture of toluene and tetrahydrofuran(THF). In particular, the morphology change from micellar structures to well-defined microphase separated arrangements is observed. Solvent annealing provides a better alternative to thermal treatment which often requires long annealing periods. The choice of solvent (single and dual solvent exposure) and the solvent annealing conditions have significant effects on the morphology of films and it was found that a block neutral solvent was required to realize vertically aligned PS and P4VP lamellae. Here, we have followed the formation of microdomain structures with time development at different temperatures by atomic force microscopy (AFM). The highly mobilized chains phase separate quickly due to high Flory-Huggins (χ) parameter. Ultra-small feature size (~10 nm pitch size) nanopatterns were fabricated by using low molecular weight PSb- P4VP (PS and P4VP blocks of 3.3 and 3.1 kg mol-1 respectively). However, due to the low etch contrast between the blocks, pattern transfer of the BCP mask is very challenging. To overcome the etch contrast problem, a novel and simple in-situ hard mask technology is used to fabricate the high aspect ratio silicon nanowires. The lamellar structures formed after self-assembly of phase separated PS-b-P4VP BCPs were used to fabricate iron oxide nanowires which acted as hard mask material to facilitate the pattern transfer into silicon and forming silicon nanostructures. The semiconductor and optical industries have shown significant interest in two dimensional (2D) molybdenum disulphide (MoS2) as a potential device material due to its low band gap and high mobility. However, current methods for its synthesis are not ‘fab’ friendly and require harsh environments and processes. Here, I also report a novel method to prepare MoS2 layered structures via self-assembly of a PS-b-P4VP block copolymer system. The formation of the layered MoS2 was confirmed by XPS, Raman spectroscopy and high resolution transmission electron microscopy.

Photonic integrated circuits development: a universal transceiver for NG-PON2

In the last years there has been a clear evolution in the world of telecommunications, which goes from new services that need higher speeds and higher bandwidth, until a role of interactions between people and machines, named by Internet of Things (IoT). So, the only technology able to follow this growth is the optical communications. Currently the solution that enables to overcome the day-by-day needs, like collaborative job, audio and video communications and share of les is based on Gigabit-capable Passive Optical Network (G-PON) with the recently successor named Next Generation Passive Optical Network Phase 2 (NG-PON2). This technology is based on the multiplexing domain wavelength and due to its characteristics and performance becomes the more advantageous technology. A major focus of optical communications are Photonic Integrated Circuits (PICs). These can include various components into a single device, which simpli es the design of the optical system, reducing space and power consumption, and improves reliability. These characteristics make this type of devices useful for several applications, that justi es the investments in the development of the technology into a very high level of performance and reliability in terms of the building blocks. With the goal to develop the optical networks of future generations, this work presents the design and implementation of a PIC, which is intended to be a universal transceiver for applications for NG-PON2. The same PIC will be able to be used as an Optical Line Terminal (OLT) or an Optical Network Unit (ONU) and in both cases as transmitter and receiver. Initially a study is made of Passive Optical Network (PON) and its standards. Therefore it is done a theoretical overview that explores the materials used in the development and production of this PIC, which foundries are available, and focusing in SMART Photonics, the components used in the development of this chip. For the conceptualization of the project di erent architectures are designed and part of the laser cavity is simulated using Aspic™. Through the analysis of advantages and disadvantages of each one, it is chosen the best to be used in the implementation. Moreover, the architecture of the transceiver is simulated block by block through the VPItransmissionMaker™ and it is demonstrated its operating principle. Finally it is presented the PIC implementation.

TRIB2 in normal and malignant hematopoiesis - a transcription factor network

Hematopoiesis is the tightly controlled and complex process in which the entire blood system is formed and maintained by a rare pool of hematopoietic stem cells (HSCs), and its dysregulation results in the formation of leukaemia. TRIB2, a member of the Tribbles family of serine/threonine pseudokinases, has been implicated in a variety of cancers and is a potent murine oncogene that induces acute myeloid leukaemia (AML) in vivo via modulation of the essential myeloid transcription factor CCAAT-enhancer binding protein α (C/EBPα). C/EBPα, which is crucial for myeloid cell differentiation, is commonly dysregulated in a variety of cancers, including AML. Two isoforms of C/EBPα exist - the full-length p42 isoform, and the truncated oncogenic p30 isoform. TRIB2 has been shown to selectively degrade the p42 isoform of C/EBPα and induce p30 expression in AML. In this study, overexpression of the p30 isoform in a bone marrow transplant (BMT) leads to perturbation of myelopoiesis, and in the presence of physiological levels of p42, this oncogene exhibited weak transformative ability. It was also shown by BMT that despite their degradative relationship, expression of C/EBPα was essential for TRIB2 mediated leukaemia. A conditional mouse model was used to demonstrate that oncogenic p30 cooperates with TRIB2 to reduce disease latency, only in the presence of p42. At the molecular level, a ubiquitination assay was used to show that TRIB2 degrades p42 by K48-mediated proteasomal ubiquitination and was unable to ubiquitinate p30. Mutation of a critical lysine residue in the C-terminus of C/EBPα abrogated TRIB2 mediated C/EBPα ubiquitination suggesting that this site, which is frequently mutated in AML, is the site at which TRIB2 mediates its degradative effects. The TRIB2-C/EBPα axis was effectively targeted by proteasome inhibition. AML is a very difficult disease to target therapeutically due to the extensive array of chromosomal translocations and genetic aberrations that contribute to the disease. The cell from which a specific leukaemia arises, or leukaemia initiating cell (LIC), can affect the phenotype and chemotherapeutic response of the resultant disease. The LIC has been elucidated for some common oncogenes but it is unknown for TRIB2. The data presented in this thesis investigate the ability of the oncogene TRIB2 to transform hematopoietic stem and progenitor cells in vitro and in vivo. TRIB2 overexpression conferred in vitro serially replating ability to all stem and progenitor cells studied. Upon transplantation, only TRIB2 overexpressing HSCs and granulocyte/macrophage progenitors (GMPs) resulted in the generation of leukaemia in vivo. TRIB2 induced a mature myeloid leukaemia from the GMP, and a mixed lineage leukaemia from the HSC. As such the role of TRIB2 in steady state hematopoiesis was also explored using a Trib2-/- mouse and it was determined that loss of Trib2 had no effect on lineage distribution in the hematopoietic compartment under steady-state conditions. The process of hematopoiesis is controlled by a host of lineage restricted transcription factors. Recently members of the Nuclear Factor 1 family of transcription factors (NFIA, NFIB, NFIC and NFIX) have been implicated in hematopoiesis. Little is known about the role of NFIX in lineage determination. Here we describe a novel role for NFIX in lineage fate determination. In human and murine datasets the expression of Nfix was shown to decrease as cells differentiated along the lymphoid pathway. NFIX overexpression resulted in enhanced myelopoiesis in vivo and in vitro and a block in B cell development at the pre-pro-B cell stage. Loss of NFIX resulted in disruption of myeloid and lymphoid differentiation in vivo. These effects on stem and progenitor cell fate correlated with changes in the expression levels of key transcription factors involved in hematopoietic differentiation including a 15-fold increase in Cebpa expression in Nfix overexpressing cells. The data presented support a role for NFIX as an important transcription factor influencing hematopoietic lineage specification. The identification of NFIX as a novel transcription factor influencing lineage determination will lead to further study of its role in hematopoiesis, and contribute to a better understanding of the process of differentiation. Elucidating the relationship between TRIB2 and C/EBPα not only impacts on our understanding of the pathophysiology of AML but is also relevant in other cancer types including lung and liver cancer. Thus in summary, the data presented in this thesis provide important insights into key areas which will facilitate the development of future therapeutic approaches in cancer treatment.

A BACKING DEVICE BASED ON AN EMBEDDED STIFFENER AND RETRACTABLE INSERTION TOOL FOR THIN-FILM COCHLEAR ARRAYS

Intracochlear trauma from surgical insertion of bulky electrode arrays and inadequate pitch perception are areas of concern with current hand-assembled commercial cochlear implants. Parylene thin-film arrays with higher electrode densities and lower profiles are a potential solution, but lack rigidity and hence depend on manually fabricated permanently attached polyethylene terephthalate (PET) tubing based bulky backing devices. As a solution, we investigated a new backing device with two sub-systems. The first sub-system is a thin poly(lactic acid) (PLA) stiffener that will be embedded in the parylene array. The second sub-system is an attaching and detaching mechanism, utilizing a poly(N-vinylpyrrolidone)-block-poly(d,l-lactide) (PVP-b-PDLLA) copolymer-based biodegradable and water soluble adhesive, that will help to retract the PET insertion tool after implantation. As a proof-of-concept of sub-system one, a microfabrication process for patterning PLA stiffeners embedded in parylene has been developed. Conventional hotembossing, mechanical micromachining, and standard cleanroom processes were integrated for patterning fully released and discrete stiffeners coated with parylene. The released embedded stiffeners were thermoformed to demonstrate that imparting perimodiolar shapes to stiffener-embedded arrays will be possible. The developed process when integrated with the array fabrication process will allow fabrication of stiffener-embedded arrays in a single process. As a proof-of-concept of sub-system two, the feasibility of the attaching and detaching mechanism was demonstrated by adhering 1x and 1.5x scale PET tube-based insertion tools and PLA stiffeners embedded in parylene using the copolymer adhesive. The attached devices survived qualitative adhesion tests, thermoforming, and flexing. The viability of the detaching mechanism was tested by aging the assemblies in-vitro in phosphate buffer solution. The average detachment times, 2.6 minutes and 10 minutes for 1x and 1.5x scale devices respectively, were found to be clinically relevant with respect to the reported array insertion times during surgical implantation. Eventually, the stiffener-embedded arrays would not need to be permanently attached to current insertion tools which are left behind after implantation and congest the cochlear scala tympani chamber. Finally, a simulation-based approach for accelerated failure analysis of PLA stiffeners and characterization of PVP-b-PDLLA copolymer adhesive has been explored. The residual functional life of embedded PLA stiffeners exposed to body-fluid and thereby subjected to degradation and erosion has been estimated by simulating PLA stiffeners with different parylene coating failure types and different PLA types for a given parylene coating failure type. For characterizing the PVP-b-PDLLA copolymer adhesive, several formulations of the copolymer adhesive were simulated and compared based on the insertion tool detachment times that were predicted from the dissolution, degradation, and erosion behavior of the simulated adhesive formulations. Results indicate that the simulation-based approaches could be used to reduce the total number of time consuming and expensive in-vitro tests that must be conducted.

Structural Connectivity Of The Default Mode Network And Cognition In Alzheimer׳s Disease.

Disconnectivity between the Default Mode Network (DMN) nodes can cause clinical symptoms and cognitive deficits in Alzheimer׳s disease (AD). We aimed to examine the structural connectivity between DMN nodes, to verify the extent in which white matter disconnection affects cognitive performance. MRI data of 76 subjects (25 mild AD, 21 amnestic Mild Cognitive Impairment subjects and 30 controls) were acquired on a 3.0T scanner. ExploreDTI software (fractional Anisotropy threshold=0.25 and the angular threshold=60°) calculated axial, radial, and mean diffusivities, fractional anisotropy and streamline count. AD patients showed lower fractional anisotropy (P=0.01) and streamline count (P=0.029), and higher radial diffusivity (P=0.014) than controls in the cingulum. After correction for white matter atrophy, only fractional anisotropy and radial diffusivity remained significantly lower in AD compared to controls (P=0.003 and P=0.05). In the parahippocampal bundle, AD patients had lower mean and radial diffusivities (P=0.048 and P=0.013) compared to controls, from which only radial diffusivity survived for white matter adjustment (P=0.05). Regression models revealed that cognitive performance is also accounted for by white matter microstructural values. Structural connectivity within the DMN is important to the execution of high-complexity tasks, probably due to its relevant role in the integration of the network.