Use of closed systems in the Hospital Pharmacy

Objective: In the setting of the increasing use of closed systems for reconstitution and preparation of these drugs, we intend to analyze the correct use of these systems in the Hospital Pharmacy, with the objective to minimize the risks of exposure not only for those professionals directly involved, but also for all the staff in the unit, taking also into account efficiency criteria. Method: Since some systems protect against aerosol formation but not from vapours, we decided to review which cytostatics should be prepared using an awl with an air inlet valve, in order to implement a new working procedure. We reviewed the formulations available in our hospital, with the following criteria: method of administration, excipients, and potential hazard for the staff handling them. We measured the diameters of the vials. We selected drugs with Level 1 Risk and also those including alcohol-based excipients, which could generate vapours. Outcomes: Out of the 66 reviewed formulations, we concluded that 11 drugs should be reconstituted with this type of awl: busulfan, cabazitaxel, carmustine, cyclophosphamide, eribulin, etoposide, fotemustine, melphalan, paclitaxel, temsirolimus and thiotepa; these represented an 18% of the total volume of formulations. Conclusions: The selection of healthcare products must be done at the Hospital Pharmacy, because the use of a system with an air valve inlet only for those drugs selected led to an outcome of savings and a more efficient use of materials. In our experience, we confirmed that the use of the needle could only be avoided when the awl could adapt to the different formulations of cytostatics, and this is only possible when different types of awls are available. Besides, connections were only really closed when a single awl was used for each vial. The change in working methodology when handling these drugs, as a result of this study, will allow us to start different studies about environmental contamination as a future line of work.

Categories, Allegories, and Circuit Design

Languages based upon binary relations offer an appealing setting for constructing programs from specifications. For example, working with relations rather than functions allows specifications to be more abstract (for example, many programs have a natural specification using the converse operator on relations), and affords a natural treatment of non-determinism in specifications. In this paper we present a novel pictorial interpretation of relational terms as simple pictures of circuits, and a soundness/completeness result that allows relational equations to be proved by pictorial reasoning.

Cost efficient supply processes for the Compact Slim Elevator Door

The aim of this thesis was to observe possibilities to enhance the development of manufacturing costs savings and competitiveness related to the compact KONE Renova Slim elevator door. Compact slim doors are especially designed for EMEA markets. EMEA market area is characterized by highly competitive pricing and lead times which are manifested as pressures to decrease manufacturing costs and lead times of the compact elevator door. The new elevator safety code EN81-20 coming live during the spring 2016 will also have a negative impact on the cost and competitiveness development making the situation more acute. As a sheet metal product the KONE Renova slim is highly variable. Manufacturing methods utilized in the production are common and robust methods. Due to the low volumes, high variability and tight lead times the manufacturing of the doors is facing difficulties. Manufacturing of the doors is outsourced to two individual suppliers Stera and Wittur. This thesis was implemented in collaboration with Stera. KONE and Stera pursue a long term and close partnership where the benefits reached by the collaboration are shared equally. Despite the aims, the collaboration between companies is not totally visible and various barriers are hampering the development towards more efficient ways of working. Based on the empirical studies related to this thesis, an efficient standardized (A+) process was developed for the main variations of the compact elevator door. Using the standardized process KONE is able to order the most important AMDS door variations from Stera with increased quality, lower manufacturing costs and manufacturing lead time compared to the current situation. In addition to all the benefits, the standardized (A+) process also includes risks in practice. KONE and the door supplier need to consider these practical risks together before decisions are made.

Compactness in quasi-Banach function spaces and applications to compact embeddings of Besov-type spaces

There are two main aims of the paper. The first one is to extend the criterion for the precompactness of sets in Banach function spaces to the setting of quasi-Banach function spaces. The second one is to extend the criterion for the precompactness of sets in the Lebesgue spaces $L_p(\Rn)$, $1 \leq p < \infty$, to the so-called power quasi-Banach function spaces. These criteria are applied to establish compact embeddings of abstract Besov spaces into quasi-Banach function spaces. The results are illustrated on embeddings of Besov spaces $B^s_{p,q}(\Rn)$, $0

Plasma diagnostics and ITO film deposition by RF-assisted closed-field dual magnetron system

Deposition of indium tin oxide (ITO) among various transparent conductive materials on flexible organic substrates has been intensively investigated among academics and industrials for a whole new array of imaginative optoelectronic products. One critical challenge coming with the organic materials is their poor thermal endurances, considering that the process currently used to produce industry-standard ITO usually involves relatively high substrate temperature in excess of 200°C and post-annealing. A lower processing temperature is thus demanded, among other desires of high deposition rate, large substrate area, good uniformity, and high quality of the deposited materials. For this purpose, we developed an RF-assisted closed-field dual magnetron sputtering system. The “prototype” system consists of a 3-inch unbalanced dual magnetron operated at a closed-field configuration. An RF coil was fabricated and placed between the two magnetron cathodes to initiate a secondary plasma. The concept is to increase the ionization faction with the RF enhancement and utilize the ion energy instead of thermal energy to facilitate the ITO film growth. The closed-field unbalanced magnetrons create a plasma in the intervening region rather than confine it near the target, thus achieving a large-area processing capability. An RF-compensated Langmuir probe was used to characterize and compare the plasmas in mirrored balanced and closed-field unbalanced magnetron configurations. The spatial distributions of the electron density ne and electron temperature Te were measured. The density profiles reflect the shapes of the plasma. Rather than intensively concentrated to the targets/cathodes in the balanced magnetrons, the plasma is more dispersive in the closed-field mode with a twice higher electron density in the substrate region. The RF assistance significantly enhances ne by one or two orders of magnitude higher. The effect of various other parameters, such as pressure, on the plasma was also studied. The ionization fractions of the sputtered atoms were measured using a gridded energy analyzer (GEA) combined with a quartz crystal microbalance (QCM). The presence of the RF plasma effectively increases the ITO ionization fraction to around 80% in both the balanced and closed-field unbalanced configurations. The ionization fraction also varies with pressure, maximizing at 5-10 mTorr. The study of the ionization not only facilitates understanding the plasma behaviors in the RF-assisted magnetron sputtering, but also provides a criterion for optimizing the film deposition process. ITO films were deposited on both glass and plastic (PET) substrates in the 3-inch RF-assisted closed-field magnetrons. The electrical resistivity and optical transmission transparency of the ITO films were measured. Appropriate RF assistance was shown to dramatically reduce the electrical resistivity. An ITO film with a resistivity of 1.2×10-3 Ω-cm and a visible light transmittance of 91% was obtained with a 225 W RF enhancement, while the substrate temperature was monitored as below 110°C. X-ray photoelectron spectroscopy (XPS) was employed to confirm the ITO film stoichiometry. The surface morphology of the ITO films and its effect on the film properties were studied using atomic force microscopy (AFM). The prototype of RF-assisted closed-field magnetron was further extended to a larger rectangular shaped dual magnetron in a flat panel display manufacturing system. Similar improvement of the ITO film conductivities by the auxiliary RF was observed on the large-area PET substrates. Meanwhile, significant deposition rates of 25-42 nm/min were achieved.

2-categories and cyclic homology

The topic of this thesis is the application of distributive laws between comonads to the theory of cyclic homology. The work herein is based on the three papers 'Cyclic homology arising from adjunctions', 'Factorisations of distributive laws', and 'Hochschild homology, lax codescent,and duplicial structure', to which the current author has contributed. Explicitly, our main aims are: 1) To study how the cyclic homology of associative algebras and of Hopf algebras in the original sense of Connes and Moscovici arises from a distributive law, and to clarify the role of different notions of bimonad in this generalisation. 2) To extend the procedure of twisting the cyclic homology of a unital associative algebra to any duplicial object defined by a distributive law. 3) To study the universality of Bohm and Stefan’s approach to constructing duplicial objects, which we do in terms of a 2-categorical generalisation of Hochschild (co)homology. 4) To characterise those categories whose nerve admits a duplicial structure.

An algorithm for the inclusion of RC compact models of packages into board level thermal simulation tools

International audience

A distributed, compact routing protocol for the Internet

The Internet has grown in size at rapid rates since BGP records began, and continues to do so. This has raised concerns about the scalability of the current BGP routing system, as the routing state at each router in a shortest-path routing protocol will grow at a supra-linearly rate as the network grows. The concerns are that the memory capacity of routers will not be able to keep up with demands, and that the growth of the Internet will become ever more cramped as more and more of the world seeks the benefits of being connected. Compact routing schemes, where the routing state grows only sub-linearly relative to the growth of the network, could solve this problem and ensure that router memory would not be a bottleneck to Internet growth. These schemes trade away shortest-path routing for scalable memory state, by allowing some paths to have a certain amount of bounded “stretch”. The most promising such scheme is Cowen Routing, which can provide scalable, compact routing state for Internet routing, while still providing shortest-path routing to nearly all other nodes, with only slightly stretched paths to a very small subset of the network. Currently, there is no fully distributed form of Cowen Routing that would be practical for the Internet. This dissertation describes a fully distributed and compact protocol for Cowen routing, using the k-core graph decomposition. Previous compact routing work showed the k-core graph decomposition is useful for Cowen Routing on the Internet, but no distributed form existed. This dissertation gives a distributed k-core algorithm optimised to be efficient on dynamic graphs, along with with proofs of its correctness. The performance and efficiency of this distributed k-core algorithm is evaluated on large, Internet AS graphs, with excellent results. This dissertation then goes on to describe a fully distributed and compact Cowen Routing protocol. This protocol being comprised of a landmark selection process for Cowen Routing using the k-core algorithm, with mechanisms to ensure compact state at all times, including at bootstrap; a local cluster routing process, with mechanisms for policy application and control of cluster sizes, ensuring again that state can remain compact at all times; and a landmark routing process is described with a prioritisation mechanism for announcements that ensures compact state at all times.

Subject categories used in Nuclear science abstracts, 1967-1975 /

"TID-26500/R1. Distribution category: UC-2."

Regular homomorphisms of minimal sets

The classification of minimal sets is a central theme in abstract topological dynamics. Recently this work has been strengthened and extended by consideration of homomorphisms. Background material is presented in Chapter I. Given a flow on a compact Hausdorff space, the action extends naturally to the space of closed subsets, taken with the Hausdorff topology. These hyperspaces are discussed and used to give a new characterization of almost periodic homomorphisms. Regular minimal sets may be described as minimal subsets of enveloping semigroups. Regular homomorphisms are defined in Chapter II by extending this notion to homomorphisms with minimal range. Several characterizations are obtained. In Chapter III, some additional results on homomorphisms are obtained by relativizing enveloping semigroup notions. In Veech's paper on point distal flows, hyperspaces are used to associate an almost one-to-one homomorphism with a given homomorphism of metric minimal sets. In Chapter IV, a non-metric generalization of this construction is studied in detail using the new notion of a highly proximal homomorphism. An abstract characterization is obtained, involving only the abstract properties of homomorphisms. A strengthened version of the Veech Structure Theorem for point distal flows is proved. In Chapter V, the work in the earlier chapters is applied to the study of homomorphisms for which the almost periodic elements of the associated hyperspace are all finite. In the metric case, this is equivalent to having at least one fiber finite. Strong results are obtained by first assuming regularity, and then assuming that the relative proximal relation is closed as well.

Photocatalytic Degradation of Anthracene in Closed System Reactor

Polycyclic aromatic hydrocarbons (PAHs) represent a large class of persistent organic pollutants in an environment of special concern because they have carcinogenic and mutagenic activity. In this paper, we focus on and discuss the effect of different parameters, for instance, initial concentration of Anthracene, temperature, and light intensity, on the degradation rate. These parameters were adjusted at pH 6.8 in the presence of the semiconductor materials (TiO2) as photocatalysts overUVlight. The main product of Anthracene photodegradation is 9,10-Anthraquinone which isidentified and compared with the standard compound by GC-MS. Our results indicate that the optimum conditions for the best rate of degradation are 25 ppm concentration of Anthracene, regulating the reaction vessel at 308.15 K and 2.5 mW/cm(2) of light intensity at 17 5mg/100 mL of titanium dioxide (P25).

Operatory kompozycji i miary Carlesona w teorii przestrzeni Hardy’ego-Orlicza na obszarach

Wydział Matematyki i Informatyki: Zakład Teorii Interpolacji i Aproksymacji

Generating Discriminative Objective Proposals via Submodular Ranking

Object recognition has long been a core problem in computer vision. To improve object spatial support and speed up object localization for object recognition, generating high-quality category-independent object proposals as the input for object recognition system has drawn attention recently. Given an image, we generate a limited number of high-quality and category-independent object proposals in advance and used as inputs for many computer vision tasks. We present an efficient dictionary-based model for image classification task. We further extend the work to a discriminative dictionary learning method for tensor sparse coding. In the first part, a multi-scale greedy-based object proposal generation approach is presented. Based on the multi-scale nature of objects in images, our approach is built on top of a hierarchical segmentation. We first identify the representative and diverse exemplar clusters within each scale. Object proposals are obtained by selecting a subset from the multi-scale segment pool via maximizing a submodular objective function, which consists of a weighted coverage term, a single-scale diversity term and a multi-scale reward term. The weighted coverage term forces the selected set of object proposals to be representative and compact; the single-scale diversity term encourages choosing segments from different exemplar clusters so that they will cover as many object patterns as possible; the multi-scale reward term encourages the selected proposals to be discriminative and selected from multiple layers generated by the hierarchical image segmentation. The experimental results on the Berkeley Segmentation Dataset and PASCAL VOC2012 segmentation dataset demonstrate the accuracy and efficiency of our object proposal model. Additionally, we validate our object proposals in simultaneous segmentation and detection and outperform the state-of-art performance. To classify the object in the image, we design a discriminative, structural low-rank framework for image classification. We use a supervised learning method to construct a discriminative and reconstructive dictionary. By introducing an ideal regularization term, we perform low-rank matrix recovery for contaminated training data from all categories simultaneously without losing structural information. A discriminative low-rank representation for images with respect to the constructed dictionary is obtained. With semantic structure information and strong identification capability, this representation is good for classification tasks even using a simple linear multi-classifier.

Real-time alert correlation with type graphs

The premise of automated alert correlation is to accept that false alerts from a low level intrusion detection system are inevitable and use attack models to explain the output in an understandable way. Several algorithms exist for this purpose which use attack graphs to model the ways in which attacks can be combined. These algorithms can be classified in to two broad categories namely scenario-graph approaches, which create an attack model starting from a vulnerability assessment and type-graph approaches which rely on an abstract model of the relations between attack types. Some research in to improving the efficiency of type-graph correlation has been carried out but this research has ignored the hypothesizing of missing alerts. Our work is to present a novel type-graph algorithm which unifies correlation and hypothesizing in to a single operation. Our experimental results indicate that the approach is extremely efficient in the face of intensive alerts and produces compact output graphs comparable to other techniques.

Search for Higgs Boson Production Beyond the Standard Model Using the Razor Kinematic Variables in pp Collisions at √s=8 TeV and Optimization of Higgs Boson Identification Using a Quantum Annealer

In the first part of this thesis we search for beyond the Standard Model physics through the search for anomalous production of the Higgs boson using the razor kinematic variables. We search for anomalous Higgs boson production using proton-proton collisions at center of mass energy √s=8 TeV collected by the Compact Muon Solenoid experiment at the Large Hadron Collider corresponding to an integrated luminosity of 19.8 fb^-1.

In the second part we present a novel method for using a quantum annealer to train a classifier to recognize events containing a Higgs boson decaying to two photons. We train that classifier using simulated proton-proton collisions at √s=8 TeV producing either a Standard Model Higgs boson decaying to two photons or a non-resonant Standard Model process that produces a two photon final state.

The production mechanisms of the Higgs boson are precisely predicted by the Standard Model based on its association with the mechanism of electroweak symmetry breaking. We measure the yield of Higgs bosons decaying to two photons in kinematic regions predicted to have very little contribution from a Standard Model Higgs boson and search for an excess of events, which would be evidence of either non-standard production or non-standard properties of the Higgs boson. We divide the events into disjoint categories based on kinematic properties and the presence of additional b-quarks produced in the collisions. In each of these disjoint categories, we use the razor kinematic variables to characterize events with topological configurations incompatible with typical configurations found from standard model production of the Higgs boson.

We observe an excess of events with di-photon invariant mass compatible with the Higgs boson mass and localized in a small region of the razor plane. We observe 5 events with a predicted background of 0.54 ± 0.28, which observation has a p-value of 10^-3 and a local significance of 3.35σ. This background prediction comes from 0.48 predicted non-resonant background events and 0.07 predicted SM higgs boson events. We proceed to investigate the properties of this excess, finding that it provides a very compelling peak in the di-photon invariant mass distribution and is physically separated in the razor plane from predicted background. Using another method of measuring the background and significance of the excess, we find a 2.5σ deviation from the Standard Model hypothesis over a broader range of the razor plane.

In the second part of the thesis we transform the problem of training a classifier to distinguish events with a Higgs boson decaying to two photons from events with other sources of photon pairs into the Hamiltonian of a spin system, the ground state of which is the best classifier. We then use a quantum annealer to find the ground state of this Hamiltonian and train the classifier. We find that we are able to do this successfully in less than 400 annealing runs for a problem of median difficulty at the largest problem size considered. The networks trained in this manner exhibit good classification performance, competitive with the more complicated machine learning techniques, and are highly resistant to overtraining. We also find that the nature of the training gives access to additional solutions that can be used to improve the classification performance by up to 1.2% in some regions.