MEASUREMENT OF THE ABSOLUTE EFFICIENCY OF A SEMICONDUCTOR DETECTOR USING AN ISOTROPIC SPHERICAL SOURCE

The calibration of hyper pure germanium semiconductor detectors is required to calculate the activity of radioactive sources. To find out the activity, the detector full-energy peak efficiency is required. The full-energy peak efficiency of HPGe semiconductor detector for an isotropic radiating spherical source is obtained xperimentally. We compared the measured efficiency values with theoretical calculations. Furthermore, the variation of the window materials of the detector on the full-energy peak efficiency have been studied. By comparison, the theoretical and experimental full-energy peak efficiency values are in good agreement. The difference percentage between the measured efficiency values and the calculated ones is less than 4%

Tribological behaviour of H- and W-DLC coatings: Effects of environment and temperature on adhesion

The objective of this study was to gain insight into the friction, aluminum adhesion, and wear mechanisms of diamond-like carbon (DLC) coatings, and to provide guidelines for coating design and development. Mechanisms that control the tribological behaviour of DLC coatings and the effects of dopants (i.e. hydrogen (H-DLC), and tungsten (W-DLC)) against aluminum alloys were investigated under various environments and test temperatures. The effects of temperature and an oxygen-rich environment on dopant-free DLC, H- DLC, and W- DLC were investigated. Experimental analyses of dopant-free DLC showed that, when it was tested in an atmosphere consisting of 50% oxygen and 45% moisture, a high COF of 0.6 observed during the running-in against aluminum was eliminated compared to environment without moisture. At elevated temperatures, presence of hydrogen reduced the COF of H-DLC (e.g., to 0.06 at 200 oC). W-DLC coatings provided a low COF of 0.18 and minimized aluminum adhesion at temperatures ranging between 400 oC and 500 oC, which was attributed to the formation of a tungsten oxide film. Additionally, DLC coatings were found to generate a low COF at subzero temperatures (-196 oC), with W-DLC and H-DLC generating a COF of 0.18. The work of adhesion (W ad ) was determined using a nano-indentation pull-off force method. In this way, insight was gained into the nature of atomic interactions contributing to tribological mechanisms at elevated temperatures. The results showed that the adhesion of the diamond tip against all four samples tested (H-DLC, dopant-free DLC, W-DLC, and aluminum) decreased with temperature. At 25 °C, no aluminum adhesion was observed on the diamond tip, due to OH passivation of the diamond surface in agreement with the low COF of 0.12 for the dopant-free DLC coating. The elimination of meniscus forces due to adsorbed water molecules on the sample surface was identified as an important factor contributing to the adhesion at room temperature. The results also confirmed that the hydrogen in the H-DLC mitigated interatomic interactions at the surface and reduced Wad to as low as 0.01 J/m 2 at 200 oC. At 25 °C, there was no aluminum adhesion observed on the diamond tip, due to OH passivation of the diamond surface in agreement with the low COF of 0.12 for the dopant-free DLC coating

Chromatographic Separation, Total Determination and Chemical Speciation of Mercury in Environmental Water Samples Using 4-(2-Thiazolylazo) Resorcinol-Based Polyurethane Foam Sorbent-Packed Column

A simple method has been developed for quantitative retention of traces of mercury(II) ions from aqueous media using polyurethane foams (PUFs) loaded with 4-(2-thiazolylazo) resorcinol (TAR). The kinetics and thermodynamics of the sorption of mercury(II) ions onto PUFs were studied. The sorption of mercury(II) ions onto PUF follows a first-order rate equation with k = 0.176 ± 0.010 min−1. The negative values of ΔH and ΔS may be interpreted as the exothermic chemisorption process and indicative of a faster chemisorption onto the active sites of the sorbent. The sorption data followed Langmuir, Freundlich and Dubinin-Radushkevich (D–R) isotherm models. The D-R parameters β, KDR and E were 0.329 mol2 kJ−2, 0.001 μmol g−1 and 1.23 ± 0.07 kJ/mol for the TAR-loaded PUFs, respectively. An acceptable retention and recovery (99.6 ± 1.1%) of mercury(II) ions in water at ≤10 ppb by the TAR-treated PUFs packed columns were achieved. A retention mechanism, involving absorption related to “solvent extraction” and an “added component” for surface adsorption, was suggested for the retention of mercury(II) ions by the used solid phase extractor. The performance of TAR-immobilized PUFs packed column in terms of the number (N), the height equivalent to a theoretical plate (HETP), the breakthrough and critical capacities of mercury(II) ion uptake by the sorbent packed column were found to be 50.0 ± 1.0, 1.01 ± 0.02 mm, 8.75 and 13.75 mg/g, respectively, at 5 mL/min flow rate

In vitro antimicrobial, anticancer, and apoptosis-inducing effects of the methanolic extract of Launaea mucronata

Traditional medicine is widely used in the treatment and management of various ailments due to its low toxicity, low number of side effects and low cost. Many components of common fruits and vegetables play crucial roles as chemopreventive or chemotherapeutic agents. This study aimed to evaluate in vitro the antioxidant, cytotoxic and antimicrobial activities of Launaea mucronata’s methanolic stems and leaves extract. In this screening study, Launaea mucronata’s methanolic extracts showed remarkably antifungal activity against Candida albicans. The maximum zone of inhibition of the methanolic extract of Launaea mucronata leaves was detected against Proteus vulgaris with inhibition zones of 17.8 mm and 14.6 mm, respectively. 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay results showed high antioxidant activity for the extract almost comparable to that of ascorbic acid at 30 µg/ml, which indicates that it might potentially be developed into a successful antioxidant agent. Meanwhile, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay was performed by screening the extract against HepG2 (Hepatocellular), A549 (Lung), HCT116 (Colon) and MCF7 (Breast) cancer cells and it was found that the extract exerted its highest activity against A549 cells with an IC50 value of 14.9 µg/ml. The extracts also shown lower cytotoxic activity against normal, healthy MRC-5 cells, with IC50 values of 204.83 g/ml for the stem extract and 412.4 g/ml for the leaves extract, respectively. This suggests that the extract is safe for normal, healthy cells, which is an important characteristic of any possible anticancer treatment. The antiproliferative and apoptosis activities of our selected plant showed that the extracts induced S-phase arrest and apoptosis in A549 cells. This high cytotoxic activity of the extract indicates that highly bioactive pure compounds could potentially be isolated from the extract in future studies and further developed into an anticancer agent specifically against lung cancer. Therefore, the current study has proven the potential of Launaea mucronata’s methanolic extract as a source of potent antioxidant and anticancer agent

Framställning av en utvärderingsapplikation med Node.js

Webbapplikationer baseras på en klient-server modell. På klientsidan används HTML, CSS och JavaScript för att implementera struktur, estetik och interaktivitet till varje enskild webbsida. På serversidan stöds logiken i webbapplikationen av en solution stack som består av ett operativsystem, en DBMS, en webbserver och ett skriftspråk. Dessa nämnda mjukvarulösningar representerar de traditionella lösningar som används för framtagning av serverbaserade lösningar. Node.js är en alternativ teknologi som skapar serverbaserade lösningar med hjälp av JavaScript, som normalt används för utveckling av klientbaserade lösningar. Syftet med detta arbete är att ge en översikt över Node.js och dess moduler, samt demonstrera hur de används genom framtagning av en webbapplikation där man utför utvärderingar under en föreläsning. Slutsatsen är att Node.js är en teknologi, som erbjuder lösningar baserade på både prestanda och lägre minnesförbrukning. Eftersom Node.js lösningar är skrivna i JavaScript, kan det vara ett enklare alternativ att använda för frontendutvecklare.Web-based applications follow a client-server model. On the client side, HTML, CSS and JavaScript are web-technologies employed to implement the structure, style and interactivity of web pages respectively. On the server side, the logic of web application is supported by a solution stack, which defines the operating system, the web-server, the database management system and the programming language. The forementioned software systems are the traditional technologies employed to develop web systems. Node.js is an alternative web technology that provides both a web server and a programming capabilities using JavaScript. This means that JavaScript can now be used both on client and server sides. This work aims to provide an overview of Node.js and its packages, as well as a demon- stration of their use with the implementation of a web application for lecture eva- luation. As a conclusion, Node.js is a competitive server side technology because Node.js provides solutions based on both performance and low memory consump- tion. Moreover, as Node.js applications are written in JavaScript, it might be a easier option to use for front-end developers.

Machine Learning analysis of text in a Clinical Decision Support System

Nurses at the Uppsala Emergency Medical Dispatch Center uses a computerized dispatcher system to prioritize patients calling the emergency number (112). The dispatchers at the emergency dispatcher center register information into that system to help them determine the treatment necessary for the patient’s condition. One thing the nurses want to find out is whether a specific patient will require admission to the hospital. In addition to structured data from the decision support system, notes written by dispatchers are documented. In this work, we have analyzed ways we can use the text from ambulance dispatchers to predict outcomes using methods that enable computers to understand natural language called Natural Language Processing, and have been implemented using machine learning approaches such as Classification and Deep Learning developed in Python, SKLearn and Keras. To perform training using our data along with these approaches, we transformed our data using three types of representations: Bag-of-words, Tf*IDF and word vectors. The aim of these representations and approaches is for our machine learning models to be able to predict the likelihood of outcomes based on a given set of data. The results from the training gave us an understanding that some models performed better than the others, but also that the imbalance of the data prevented the models from generating more accurate result.

Machine Learning analysis of text in a Clinical Decision Support System

Nurses at the Uppsala Emergency Medical Dispatch Center uses a computerized dispatcher system to prioritize patients calling the emergency number (112). The dispatchers at the emergency dispatcher center register information into that system to help them determine the treatment necessary for the patient’s condition. One thing the nurses want to find out is whether a specific patient will require admission to the hospital. In addition to structured data from the decision support system, notes written by dispatchers are documented. In this work, we have analyzed ways we can use the text from ambulance dispatchers to predict outcomes using methods that enable computers to understand natural language called Natural Language Processing, and have been implemented using machine learning approaches such as Classification and Deep Learning developed in Python, SKLearn and Keras. To perform training using our data along with these approaches, we transformed our data using three types of representations: Bag-of-words, Tf*IDF and word vectors. The aim of these representations and approaches is for our machine learning models to be able to predict the likelihood of outcomes based on a given set of data. The results from the training gave us an understanding that some models performed better than the others, but also that the imbalance of the data prevented the models from generating more accurate result.

Urban Aquaponics : Sustainable Integration of Aquaponics within the City of Malmö

With increasing urban expansion and rising global demand for food production, integrating aquaponics within the urban contexts can be considered an alternative sustainable solution to enrich the local production and self-sufficiency. In this research, we aim to study the aquaponics system and provide a design guide for implementing the urban version of the system in the city of Malmo. The design guide will be also practically tested in a form of an architectural proposal at the end of the research. To reach the results, various case studies and academic research were investigated. In addition to other qualitative and quantitative methodologies, such as interviews, questionnaire, and ethnographic studies that contributed to making progress during the research’s different phases. The analysis of data was to generate sustainable bases for urban aquaponics that go in line with the city’s conditions and citizens’ aspirations. Accordingly, several methods and techniques were deducted to be used for the sustainable integration of the aquaponics system within the urban context of Malmo. Nevertheless, the integration process can contribute to including other operations with the aim of increasing aquaponics sustainability and solving urban issues within the context. However, the design guide produced in this paper is mainly for the city of Malmo, but it can be adjusted to other social and geographical contexts.

Does the cookie taste good when learning what it consists of? : A quantitative study on online behavior advertising and generation X & Ys attitude regarding it

Purpose: The purpose of this study is to investigate the different consumption attitudes of generation X & Y and their privacy concerns regards to company’s use of online behavior advertisement (hereafter referred to as OBA) Research questions: RQ1. What are the differences in consumption behavior between generations X and Y regarding the effect of OBA? RQ2. What are the differences between Generation X & Y regarding privacy concerns about OBA? Method: Due to this thesis’s purpose and research questions, a quantitative method was chosen which investigated 3 hypotheses that are used to answer the purpose and research questions. The survey was distributed through Facebook and led to the respondent group consisting of 281 respondents from both generations X & Y. The answers were analyzed by using t-tests in IBM SPSS 26. Conclusion: This thesis concluded that there is a significant difference between generation X & Y. Generation Y are less concerned about their privacy and have a more positive view of personalized content. Generation Y is more likely to click on advertisements that come up for them as well as appreciating adapted advertisements. This could explain why OBA has gained increased interest over the years from marketers and companies. The results also indicated that a majority never clear their web browser from cookies which is one of the cornerstones for OBA to work, which may indicate that both generations want customized content when using the internet and social medi