Paso Robles Children\u27s Museum Redesign

For this project, we plan to redesign the Paso Robles Children\u27s Museum website, utilizing Squarespace. Currently, the website has an outdated look and feel, and the information is somewhat disorganized. Having intuitive navigation is a crucial part of good user experience, as users should not have to dig through the site to find what they are looking for (Hallman, 2022). In our redesign, we plan to regroup related content into sections that mimic websites of other established museums, so the structure is more familiar. The other main issue we want to address is the site’s aesthetic; our goal is to modernize the website while still retaining its core branding. To do this, we will work with the museum director to find the most fitting template for the new site on Squarespace, and then customize it accordingly with a revamped color palette, new photos, and new fonts. Our project aims to improve upon The Paso Robles Children’s Museum’s online presence and recognition in general. Redesigning the website with a focus on functionality and implementing good UI/UX design will help users navigate the site with ease, minimize confusion, and ultimately increase user retention. Our project will align Paso Robles Children’s Museum’s website with the current market standards and trends, while placing the museum’s educational value and community impact at the forefront

Crop Diseases Identification Using Deep Learning in Application

This comprehensive review paper explores the profound impact of deep learning in the context of agriculture, with a specific focus on its crucial role in crop disease analysis and management. Deep learning techniques have exhibited remarkable potential to revolutionize agricultural practices, enhancing efficiency, sustainability, and resilience. The introductory section sets the stage by emphasizing the significant role of deep learning in agriculture, offering insights into its transformative applications, including disease detection, yield prediction, precision agriculture, and resource optimization. Subsequent sections delve into the fundamental aspects of deep learning, beginning with an exploration of its relevance and its practical implementations in crop disease detection. These discussions illuminate the essential techniques and methodologies that drive this technology, stressing the critical importance of data quality, model generalization, computational resources, and cost considerations. The paper also addresses ethical and environmental concerns, emphasizing the imperative of responsible and sustainable deep learning applications in agriculture. Furthermore, the document outlines the limitations and challenges faced in this field, encompassing data availability, ethical considerations, and computational resource accessibility, offering valuable insights for future research and development. This paper underscores the immense potential of deep learning to revolutionize agriculture by improving disease management, resource allocation, and overall sustainability. While persistent challenges exist, such as data quality and accessibility, the promise of harnessing deep learning to address global food security challenges is exceptionally encouraging. This comprehensive review serves as a foundational resource for ongoing research and innovation within the agricultural domain

Long-lived photoexcited states in polydiacetylenes with different molecular and supramolecular organization

With the aim of determining the importance of the molecular and supramolecular organization on the excited states of polydiacetylenes, we have studied the photoinduced absorption spectra of the red form of poly[1,6-bis(3,6-didodecyl-N-carbazolyl)-2,4-hexadiyne] (polyDCHD-S) and the results compared with those of the blue form of the same polymer. An interpretation of the data is given in terms of both the conjugation length and the interbackbone separation also in relation to the photoinduced absorption spectra of both blue and red forms of poly[1,6-bis(N-carbazolyl)-2,4-hexadiyne] (polyDCHD), which does not carry the alkyl substituents on the carbazolyl side groups. Information on the above properties is derived from the analysis of the absorption and Raman spectra of this class of polydiacetylenes

Design and development of a direct injection system for cryogenic engines

The cryogenic engine has received increasing attention due to its promising potential as a zero-emission engine. In this study, a new robust liquid nitrogen injection system was commissioned and set up to perform high-pressure injections into an open vessel. The system is used for quasi-steady flow tests used for the characterisation of the direct injection process for cryogenic engines. An electro-hydraulic valve actuator provides intricate control of the valve lift, with a minimum cycle time of 3 ms and a frequency of up to 20 Hz. With additional sub-cooling, liquid phase injections from 14 to 94 bar were achieved. Results showed an increase in the injected mass with the increase in pressure, and decrease in temperature. The injected mass was also observed to increases linearly with the valve lift. Better control of the injection process, minimises the number of variables, providing more comparable and repeatable sets of data. Implications of the results on the engine performance were also discussed

Nitrogen dioxide gas-sensing properties of hydrothermally synthesized WO3 · nH2O nanostructures

Nitrogen dioxide (NO2) has been identified as a serious air pollutant that threats to our environment, human life and world ecosystems. Therefore, detection of this air pollutant is crucial. Metal oxide semiconductor is one of the best approaches frequently used to detect NO2 at relatively low temperatures. Hydrated tungsten trioxide (WO3 · H2O), an n-type semiconductor, is regarded to be a promising material for fabricating gas sensors, which are widely used in environmental and safety monitoring. In this work, WO3 · nH2O nanoparticles have been synthesized using a polyfunctional surfactant-mediated hydrothermal approach in the addition of H2C2O4 and K2SO4 at a molar ratio of 1 : 1. This paper has also reported the effect of reaction temperature (120°C to 200°C) on morphological changes and gas-sensing performance. The characterization of these synthesized nanostructures was carried out by UV–Vis absorption spectroscopy, X-ray diffraction and field-emission scanning electron microscopy (FESEM). The UV absorption peak was obtained around 300 nm. FESEM analysis showed sheet-like structures come together to form flower-type morphology. The synthesized WO3 · nH2O flower-like structures was then used for NO2 gas-sensing application. The prepared sensors showed considerably better sensor response (Rg/Ra = 17.48) at 185°C for 25 ppm NO2

Utdelningspolitiken bland svenska familjeägda företag : En kvantitativ studie om utdelnings utvecklingen hos svenska familjeägda företag under perioden 2010-2019

Syftet med denna studie är undersöka hur utdelningsnivån hos familjeägda företag i svenska börsmarknaden utvecklats under åren 2010-2019. Vidare observeras huruvida svenska familjeföretagens utdelningsandel förhåller sig gentemot Australien, Asiatiska- och Europeiska länderna. Studien har tillämpat en kvantitativ forskningsansats och med ett fokus på ett icke-sannolikhetsurval som består av börsnoterade företag som är noterade på Nasdaq OMX Nordic. Den inhämtade datan har samlats från företagens årsredovisningar och finansiella databasen, Börsdata. Utifrån undersökningens empiri och analys kan det konkulderas att utveckling av utdelningar och nettoresultaten hos svenska familjeföretag uppvisade likheter till studiens teoretiska referensram, Lintners modell och Modigliani & Millers irrelevans teori. Utdelningsandelen hos svenska börsnoterade familjeföretag uppnådde procentuellt högre utdelningsandel i jämförelse med Australien, Asiatiska- och Europeiska länderna.

Utdelningspolitiken bland svenska familjeägda företag : En kvantitativ studie om utdelnings utvecklingen hos svenska familjeägda företag under perioden 2010-2019

Syftet med denna studie är undersöka hur utdelningsnivån hos familjeägda företag i svenska börsmarknaden utvecklats under åren 2010-2019. Vidare observeras huruvida svenska familjeföretagens utdelningsandel förhåller sig gentemot Australien, Asiatiska- och Europeiska länderna. Studien har tillämpat en kvantitativ forskningsansats och med ett fokus på ett icke-sannolikhetsurval som består av börsnoterade företag som är noterade på Nasdaq OMX Nordic. Den inhämtade datan har samlats från företagens årsredovisningar och finansiella databasen, Börsdata. Utifrån undersökningens empiri och analys kan det konkulderas att utveckling av utdelningar och nettoresultaten hos svenska familjeföretag uppvisade likheter till studiens teoretiska referensram, Lintners modell och Modigliani & Millers irrelevans teori. Utdelningsandelen hos svenska börsnoterade familjeföretag uppnådde procentuellt högre utdelningsandel i jämförelse med Australien, Asiatiska- och Europeiska länderna.