While many organizational actors, including firms, governments, universities, and non-profit organizations may have an impact on the innovative capacity of the firms with which they engage, we have little knowledge of their relative importance. The literature on innovation intermediaries reports on the impact of specific types of organizations, but has not considered the relative importance of different types of organizations. While the studies using Community Innovation Survey (CIS) data are able to consider relative effects, data on the nature of those effects are limited. In the interests of a better understanding of the relative nature and degree of the innovation enabling contributions of a range of organizational actors, I conduct a comparative examination of the contributions of firms, governments, universities, industry associations, and research institutes. Using survey data from a sample of 499 firms, I identify the actors that are most strongly associated with each of ten innovation intermediation activities.

In this study, I examine if higher levels of ambient air pollution impact educational outcomes. According to the literature review, CO, O3, PM10 and PM2.5 are found to be four pollutants that could have an impact on cognitive ability, so I focus on these air pollutants. I analyze provincial test results for the province of British Columbia, and Secondary School Literacy Test results from the province of Ontario (OSSLT) with air pollution and weather data corresponding to the locations and dates in which tests took place. A longitudinal approach is used, in which test results are compared within a school over time with a fixed effects model chosen to control for school and year fixed effects. Correlations are found among the four pollutants in the two provinces, therefore, an integrated Air Quality Index (AQI) is calculated to further examine the relationship between air pollution and educational outcomes. In British Columbia, I find that there is a negative impact of ambient air pollution on student’s test results: a one standard deviation increase in AQI leads to a 0.23 percentage points decrease in student average grade. Furthermore, I find that in BC, air pollution’s impact on students with special needs experience about 3.4 times of the average impact of other students. In Ontario, I do not find significant association between OSSLT results and the AQI, and this might be because of not having enough observations in Ontario school dataset and lots of missing data in air pollution dataset. However, the association between ambient air pollution and OSSLT results is found to be negative overall, congruent with results from BC.

Purpose of study: Examine ASO (soft) and Malleoloc semi-rigid stirrup (SRS) ankle orthosis designs on ankle kinematics during field-sport movements: sprint, one-legged jump, and 45-degree cut. Participants: 13 competitive Ultimate players who regularly wore an ankle orthosis during physical activity. Methods: ASO or Malleoloc orthosis was randomly assigned to each person. Kinematic data were captured while the participants performed several trials for each movement in a motion analysis laboratory. Participants repeated the protocol with the other orthosis. Results: ASO allowed significantly more plantar-flexion during weight acceptance of the planting foot in cutting (p=0.038). In jumping, the Malleoloc allowed significantly more eversion-inversion range during stance (p=0.048) and eversion-inversion angular velocity from midstance to toe-off (p=0.026). Qualitative data also showed a significant preference for ASO. Conclusion: Hypotheses that ankle inversion and eversion would be greater with the ASO; and plantar-flexion and dorsiflexion would be greater with the Malleoloc were refuted.

Through the ages dissatisfaction with his environment has provoked man to envision the ideal or "utopian" setting which would be more to his liking. The discontent of today's youth with the world it has inherited echoes the complaints of past generations and yet is of particular significance and relevance to the twelfth grade student soon to enter the college community where protests are becoming increasingly more articulate and effective. Established institutions and behavior codes are challenged with impunity although critics charge that such dissent is irresponsible and unsupported by positive, alternative proposals for improvement.

This was a study to ascertain the nature and scope of industrial arts activities in the elementary schools of West Texas.

This thesis is a comparison and result evaluation of arithmetic, handwriting, spelling, and reading goals by students in the second grade at Sam Houston Elementary School in Denton, Texas.

This study considers chemical compounds that can exert their activity by interacting with a target protein or other molecular receptors. Our aim is to develop machine learning models that can predict if a chemical compound will be active in a particular test/assay. We will use data from assays that are present in the PubChem knowledgebase, specifically in its segment called BioAssays which reports the results of many high-throughput screening experiments. PubChem BioAssays is a valuable resource that contains information from a large number of experiments. In one assay, sometimes many hundreds or even many thousands of chemicals are tested. Data from these experimental assays contain information about chemicals that are active as well as chemicals that are not active in the assay. These represent an interesting resource of experimental data that are well suited for classification purposes. We will approach the problem by evaluating different ways that chemical compounds can be numerically described by means of so-called fingerprints, and then apply different machine learning (ML) and deep learning (DL) models to classify active and inactive chemicals for a number of assays. In this study, we will make comprehensive comparisons of the types of ML/DL models and types of fingerprint features that describe chemicals, and evaluate combinations of models and fingerprints that work best for the problem in question. Our focus is on finding those combinations which are useful for distinguishing active from inactive compounds in single PubChem assays. We will evaluate the methods across 10 assays and will examine the effects of 11 types of fingerprints. For example, PubChem fingerprints and MACCS keys fingerprints. For the evaluation, up to now we performed 88 experiments for each dataset and 968 in total for all 10 PubChem assays. These experiments involved approximately 6,000 interactions between chemicals and their targets. The implementation of this project has been done using MATLAB. Based on these and additional experiments, we will be in a position to propose which combination of fingerprints and ML/DL models works best in the above mentioned task. Such modeling will be useful to predict activity for chemicals that are not yet tested.

Since the retail industry has been drastically affected due to the growth of online shopping, companies have become more aware of higher competition in their current physical stores. Since there is still demand for companies to have physical stores, they have to understand the values those remaining physical stores possess and understand the undergoing changes in the sector. The change has created a value of digitalization and as it looks the digital environment remains cheaper than labour work in stores which in turn creates a certain attraction of lowering cost and maximizing profit. But statistics have shown that retail suffers low retention rates, and it relates to costs of recruiting, education, loss of sales, service quality and much more. It has become more important due to the high turnover cost to retain employees, and especially those who are “talented” and to attract those employees has become more important. Our research is based on different literature which revolves around the fields of employee retention factors and retention strategies within the retail industry. There is a high academic attention towards retention strategies in general, but far less attention is paid towards the retail industry. We chose a manager approach toward investigating our research questions, since the majority of earlier studies have based their research from employees' perspectives toward why they leave their jobs, or why they stay. Our thesis answers the research question of “What strategies or activities are made by managers in order to retain talented employees within the Swedish retail sector?”. In order to find an answer to our research question, we conducted a qualitative study which involved interviewing managers within the Swedish retail industry. Through thematic analysis we discussed different key takeaways from our empirical findings, which we compared to our theoretical framework, in order to later conclude our discussion into our conclusion chapter. Our findings show how different retention factors, namely: Social support, development opportunities, autonomy, compensation and work life balance are being implemented in practice within different organizations. While our thesis provides answers on how retention factors are being implemented within the Swedish retail sector, it is necessary to research the subject further in order to gain more detailed insights on the implementation of the retention methods and strategies used, as well as gaining an employee perspective on how the effectiveness of each method and strategy are being perceived.

Alzheimer's disease (AD) is the most common cause of dementia initially characterised by short-term memory deficits followed by a progressive cross domain cognitive and functional decline over time and loss of independence in carrying out activities of daily living (ADL). Apathy and depression are also the two most frequent neuropsychiatric sequalae associated with AD and have an impact on patients' ability to execute ADLs. Little is still known if apathy subdomains differently predict ADL performance in these patients. In this study, we aimed to quantitatively investigate if global apathy and depression predict ADL performance. We also wanted to establish if the apathy evaluation scale (AES) items resolve into three factors as proposed by Marin and if those factors differently predict performance of ADLs. We recruited a sample of 115 patients diagnosed with probable or possible AD. Basing on current literature, we hypothesised that apathy and depression predict ADL performance. We also hypothesised that AES items will load into three factors relating to cognitive, behavioural and affective apathy subdomains and that these subdomains will differentially predict ADL performance in our patient sample. Our results indicated that high apathy and depression symptoms were associated with problems to carryout ADLs. They also indicated that AES items resolved into a three factor solution in analogy with Marin's conceptualisation but they did not cluster in the manner that he proposed. Finally, when these factors are regressed simultaneously, (derived from factor analysis) only behavioural apathy significantly predicted ADLs.

This Master’s thesis describes the goals and conditions for the foundation of the center for pastime activities for children and youth. The final prospectus goes from the complete analysis of the market in term of potential customers and also of current competition. It analyses a need of finance on behalf of the earnings and expenses comparison.