1,883 research outputs found
The Role of Transporters in Future Chemotherapy
The expression of membrane transporter is often altered in cancer cells compared to their corresponding healthy cells. Since these proteins, classified into solute carriers (SLCs) and ATP-binding cassettes (ABCs), can carry not only endogenous compounds, nutrients, and metabolites, but also drugs across the cell membranes, they have a crucial role in drug exposure and clinical outcomes of chemotherapeutics. Curiously, up-regulation of SLCs can be exploited to deliver chemotherapeutics, their prodrugs, and diagnostic radio-tracers to gain cancer cell-selective targeting, as exemplified with L-type amino acid transporter 1 (LAT1). SLCs can also be inhibited to limit the nutrient uptake of cancer cells and thus, cell growth and proliferation. Furthermore, LAT1 can be utilized to deliver ABC-inhibitors selectively into the cancer cells to block the efflux of other chemotherapeutics suffering from acquired or intrinsic efflux transport-related multidrug resistance (MDR). Taking into account the current literature, compounds that can affect transporter up- or down-regulation of transporters in a cancer cell-selective manner could be a valuable tool and promising chemotherapy form in the future
An empirical study series to investigate the research synthesis of complex health care interventions and related methodological issues
Purpose: This thesis aimed to evaluate how theory-orientated approach to research synthesis of complex health care interventions may facilitate better understanding of intervention mechanisms. Thesis intended also to evaluate how qualitative research compliments a systematic review and meta-analysis of complex health care interventions, especially what participants’ perceive as effective intervention features and how this compares with systematic review and meta-analysis evidence. By combining these different approaches thesis aimed to improve reporting of reviews of complex health care interventions by providing more detailed information about intervention mechanisms that appear to be associated with a successful intervention.
Methods: The thesis was built on a series of empirical studies. Multiple bibliographic databases and references of retrieved articles were searched for relevant review articles, randomised controlled and qualitative studies. Random-effects meta-analyses were conducted to estimate effectiveness of psycho-educational smoking cessation interventions, while behaviour change techniques used in the studies and their suitability to change behavioural determinants were evaluated using a framework by Michie et al. (2008). Thematic analysis was conducted to explore qualitative studies, while narrative analysis was used to bring the different case studies together.
Results: Psycho-educational interventions significantly increased point prevalent and continuous smoking cessation, and despite superficial differences, interventions appear to deploy similar behaviour change techniques. Qualitative research suggested considerable variation in patients’ expectations and experiences of psycho-educational interventions, but combined results suggested that many of the techniques used in psycho-educational interventions appear to be well matched with patients’ experiences of successful interventions.
Conclusions: Although questions remain about how to distinguish characteristics of an effective intervention, the theory-orientated approach to systematic review and meta-analysis was able to provide a detailed analysis of the intervention techniques to help in the design of future interventions. This approach, however, is labour intensive in its present form
Comparison and optimization of built-up roof and prefabricated roof element
Abstract. The aim for this thesis was to get optimized solution for prefabricated roof elements with different joint types and span lengths. In this thesis built-up roof structure and prefabricated roof element were compared and these both structures were done by using load-bearing steel sheets. The purpose was to get the most functional solution for prefabricated roof elements that steel consumption is low. This would also give recommended measurements for elements from calculations and costs.
In this thesis basic calculations for thin steel sheets were used from Eurocodes. Program called Poimu were also used. Poimu can calculate different roof structures with steel sheets either it is element or built-up roof structure. When calculating costs, experiences of the company and contractors were used.
Because of this thesis, comparable material for prefabricated roof element solutions were obtained, as well as information on how these roof structures differ from each other and how much steel each joint type consumes comparing to another joint type or span length. The most important result of this thesis can be the tables where built-up roof structure and prefabricated roof element were compared. These comparisons reveal the best solution for the given loads and the measurements that were used in this example building. Poimu program gave the thinnest possible steel thickness for different span lengths with dimensioning factor of the structure. The most important result was the market price which were set for the prefabricated roof element.
The results from this thesis can be used when this kind of roof structures are examined. It is also possible to utilize the results for future projects where load-bearing steel sheets are used. This leads to that results from this thesis are not commonly generalizable but on the other hand, the results provide good information on how much these compared structures differ in terms of durability and the amount of steel.Paikallarakennetun katon ja esivalmistetun kattoelementin vertailu sekä optimointi. Tiivistelmä. Tämän diplomityön tavoitteena oli saada eristetyille esivalmistetuille kattoelementeille optimoitu ratkaisu eri liitostyypeissä eri jänneväleillä. Työssä vertailtiin perinteistä paikallarakennettua kattorakennetta esivalmistettuihin kattoelementteihin. Kummassakin tapauksessa on käytetty kantavia poimulevyjä, jotka on olleet kummassakin vertailurakenteessa tyypiltään samat. Tarkoituksena oli saada toimivin ja näin ollen vähiten terästä kuluttavin ratkaisu, jonka seurauksena saataisiin suositellut mitat esivalmistetulle kattoelementille annetuilla kuormilla laskelmien ja kustannuksien kautta.
Tässä työssä käytettiin Eurokoodin esittämiä laskelmia ohuen teräslevyn kestävyyden laskemiseksi. Käytössä oli myös ohjelma nimeltä Poimu, joka mitoittaa niin kattoelementtejä kuin poimulevy kattorakenteita. Kustannuksia laskettaessa on käytetty hyödyksi työn tilaajan antamia tietoja aiheesta sekä kyselty urakoitsijoilta heidän kokemuksiaan tämän tyyppisten elementtien asennuksesta.
Tämän työn tuloksena saatiin vertailukelpoista materiaalia yleistyviin kattoelementti -ratkaisuihin ja myös tietoa siitä, miten tässä työssä tutkitut kattorakenteet poikkeavat toisistaan ja kuinka paljon terästä kukin liitostyyppi kuluttaa verrattuna johonkin toiseen liitokseen tai jänneväliin. Tämän diplomityön tärkeimpinä tuloksina voidaan pitää saatuja vertailutaulukoita esivalmistetun kattoelementin ja paikallarakennetun kattorakenteen välillä. Näistä vertailuista saadaan selville parhain ratkaisu annetuille kuormille ja esitetylle rakennukselle. Poimu ohjelmasta saatiin ohuin mahdollinen teräspaksuus erijännevälille sekä myös eri rakenteiden mitoittava tekijä. Tärkeimpänä tuloksena pystyttiin myös asettamaan eristetylle esivalmistetulle kattoelementille markkinahinta.
Tuloksia voidaan käyttää tarkasteltaessa tämän tyyppisiä kattorakenteita. Tuloksia on myös mahdollista hyödyntää tulevissa projekteissa, joissa on käytössä saman tyyppinen poimulevy, näin ollen tulokset eivät ole yleisesti yleistettävissä, mutta toisaalta tulokset antavat hyvää tietoa siitä, kuinka paljon työssä verratut rakenteet poikkeavat toisistaan kestävyyden ja teräksen kulutuksen suhteen
Deep convolutional neural networks for estimating porous material parameters with ultrasound tomography
We study the feasibility of data based machine learning applied to ultrasound
tomography to estimate water-saturated porous material parameters. In this
work, the data to train the neural networks is simulated by solving wave
propagation in coupled poroviscoelastic-viscoelastic-acoustic media. As the
forward model, we consider a high-order discontinuous Galerkin method while
deep convolutional neural networks are used to solve the parameter estimation
problem. In the numerical experiment, we estimate the material porosity and
tortuosity while the remaining parameters which are of less interest are
successfully marginalized in the neural networks-based inversion. Computational
examples confirms the feasibility and accuracy of this approach
The role of marketing communications in an innovation commercialization process of a start-up company
Abstract. This study was undertaken as a master’s thesis in marketing in the spring of 2016. The aim of the study is to investigate the role of marketing communications in the innovation commercialization process in start-up companies and offer guidelines for start-up companies on utilizing marketing communications tools in the commercialization of innovative products. The reason for choosing this particular topic is that start-ups have a major role in creating innovations, but they may have trouble with commercializing them. We believe that marketing communications have the potential to enhance the possibilities of a company to success in their commercialization process.
This research is a qualitative case study of four start-ups that have discovered some form of new technological innovation and utilize it in their product. The primary data is collected using semi-structured interviews and puzzle exercise.
The theoretical part of the study is divided for three sections. The first theme contains topics of innovation, innovation strategy, product development and innovation commercialization process. The second theme is going through theory of marketing communications. The third section is theoretical framework which is built to combine theories regarding the innovation commercialization process and marketing communications. The theoretical framework is the basis which our research is built upon. The empirical part of our thesis comprises an analysis of our research data which is presented in a thematic order that follows order of our theoretical framework. In the chapter, we draw comparisons between theory and empirical data.
As a conclusion, we have formulated a start-up verified framework that is based on our theoretical framework, but altered to meet the commercialization process of a start-up company. The start-up-verified framework is applied in answering the research questions. As the main result we found out that the role of marketing communications is essential throughout the innovation commercialization process even though its importance and purpose fluctuates between different stages of the process. During the process of commercialization, the role of marketing communications evolves from preparing activities into implementation of actions.
This thesis contributes to the previous studies on commercialization process, as there are no studies made on within this specific start-up context combining commercialization and marketing communications. From a theoretical standpoint the results of this study highlight the iterative nature of the phases of commercialization process. As a managerial implication, our start-up verified framework serves outlines for discussion about marketing communications and how it could be connected to their commercialization process. Limitations of this thesis concern relatively small sample size of empirical data, which leads us to believe that our research does not reach a degree of validity that would be suitable for making generalizations. We also knowingly ignore whatever happens after the last stage of commercialization process, so we do not argue how a start-up company would continue to develop if we knew that the commercialization process had been carried out successfully
Demonstration of Optical Nonlinearity in InGaAsP/InP Passive Waveguides
We report on the study of the third-order nonlinear optical interactions in
InGaAsP/InP strip-loaded waveguides. The material
composition and waveguide structures were optimized for enhanced nonlinear
optical interactions. We performed self-phase modulation, four-wave mixing and
nonlinear absorption measurements at the pump wavelength 1568 nm in our
waveguides. The nonlinear phase shift of up to has been observed in
self-phase modulation experiments. The measured value of the two-photon
absorption coefficient was 15 cm/GW. The four-wave mixing conversion
range, representing the wavelength difference between maximally separated
signal and idler spectral components, was observed to be 45 nm. Our results
indicate that InGaAsP has a high potential as a material platform for nonlinear
photonic devices, provided that the operation wavelength range outside the
two-photon absorption window is selected
Transport model for hot positrons in layered structures
The transport of hyperthermal, monoenergetic (≤10-eV) positrons injected in metal bilayer structures is investigated. The transport is modeled using the Boltzmann equation and the two-flux approximation. Analyzing reported experimental data in terms of the developed model enables us to separate the different scattering channels and to estimate the mean free paths for these events. Our study is the first quantitative treatment of hot positrons, and the extracted transport parameters agree with theoretical predictions.Peer reviewe
DeepTx: Deep Learning Beamforming with Channel Prediction
Machine learning algorithms have recently been considered for many tasks in
the field of wireless communications. Previously, we have proposed the use of a
deep fully convolutional neural network (CNN) for receiver processing and shown
it to provide considerable performance gains. In this study, we focus on
machine learning algorithms for the transmitter. In particular, we consider
beamforming and propose a CNN which, for a given uplink channel estimate as
input, outputs downlink channel information to be used for beamforming. The CNN
is trained in a supervised manner considering both uplink and downlink
transmissions with a loss function that is based on UE receiver performance.
The main task of the neural network is to predict the channel evolution between
uplink and downlink slots, but it can also learn to handle inefficiencies and
errors in the whole chain, including the actual beamforming phase. The provided
numerical experiments demonstrate the improved beamforming performance.Comment: 27 pages, this work has been submitted to the IEEE for possible
publication; v2: Fixed typo in author name, v3: a revisio
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