cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Experimental Evaluation of the PHP's cURL Library Performance
Creators: name: Kalmukov, Yordan
Publisher: name: arXiv
Year: 2024
Subjects: subject: Distributed, Parallel, and Cluster Computing (cs.DC)
subject: FOS: Computer and information sciences
subject: 68M14 (Distributed systems), 68M20 (Performance evaluation), 68M11 (Internet topics)

description: cURL (libcurl) is a popular and widely used library distributed with the php interpreter. It allows php applications to connect to and communicate with external resources (servers) by using wide variety of communication protocols. In most cases it is the preferred way of consuming external REST web services. Programmers usually use it for granted without even thinking of any performance issues. During an experimental analysis of the Hadoop's WebHDFS API throughput, it has been noted that read (download) speed from WebHDFS reduces with increasing the file size. However, this issue does not happen when writing to WebHDFS. Since the communication between the php application and the WebHDFS API is handled by the php's cURL library, then the cause of the download speed decrease could be either the cURL library itself or the API. This paper presents a series of experimental analyses aiming to determine the cause of the download speed decrease in previous experiments - whether it is the WebHDFS API or the php's cURL library. Both parties are tested in multiple ways separately and independently of each other. Results clearly prove (in two different ways) that the cause of the download speed decrease is the php's cURL library itself, not the consumed API.
The Impact of Different Fermentations on the Antifungal Activity of Sourdough Bread
Creators: Bumanis, Zoe
Publisher: name: University of Alberta Library
Year: 2024

Bread is considered a staple food in North America and Europe, but due to its neutral pH and high water activity it is vulnerable to spoilage by Penicillium spp., a problem that costs the commercial baking industry millions each year and contributes significantly to global food waste. Common methods of chemical preservation like calcium propionate (CalPro) and sorbic acid are falling out of favour with ingredient-conscious consumers, leaving a hole in the market for a bread with few or reduced preservatives. Sourdough, a mixture of water and flour fermented by lactobacilli and yeasts, is often used in bread production to improve flavour, texture, and to contribute to leavening. It has also displayed preservative effects against mould which increase the shelf life of the product.

The antifungal impact of 12 strains of lactobacilli incorporated into 10% sourdough breads were compared to one another and revealed to result in equivalent shelf life when inoculated with the highly-resistant spoilage organism Penicillium roqueforti. However, altering the time and temperature combinations used in fermentation and proofing protocols resulted in an increase in shelf life which matched that of bread containing 0.3% calcium propionate, even in a 'worst-case' exposure scenario. It was also determined that a combination of 0.1% calcium propionate and sourdough was similarly effective in delaying fungal spoilage. The inclusion of buckwheat in the fermentations and the subsequent impact on shelf life was recorded for the first time, and the benefits of isomerized ɑ-acids sourced from hops were supported by the findings of this study, which identified both additives as effective ways to extend the mould-free shelf life of sourdough bread past what is possible using only wheat flour.

This research posits that a three-pronged approach utilising the products of sourdough fermentation, antifungal adjuncts, and a clean processing area can not only reduce instances of fungal contamination but also lead to improved resistance and extended shelf life when contamination does occur in preservative-free or reduced-preservative bread, providing a benefit that cannot be achieved by any one of these factors alone.
Scheduling of Distributed Applications on the Computing Continuum: A Survey
Creators: name: Mehran, Narges
name: Kimovski, Dragi
name: Hellwagner, Hermann
name: Roman, Dumitru
name: Soylu, Ahmet
name: Prodan, Radu
Publisher: name: arXiv
Year: 2024
Subjects: subject: Distributed, Parallel, and Cluster Computing (cs.DC)
subject: FOS: Computer and information sciences

description: The demand for distributed applications has significantly increased over the past decade, with improvements in machine learning techniques fueling this growth. These applications predominantly utilize Cloud data centers for high-performance computing and Fog and Edge devices for low-latency communication for small-size machine learning model training and inference. The challenge of executing applications with different requirements on heterogeneous devices requires effective methods for solving NP-hard resource allocation and application scheduling problems. The state-of-the-art techniques primarily investigate conflicting objectives, such as the completion time, energy consumption, and economic cost of application execution on the Cloud, Fog, and Edge computing infrastructure. Therefore, in this work, we review these research works considering their objectives, methods, and evaluation tools. Based on the review, we provide a discussion on the scheduling methods in the Computing Continuum.
description: 7 pages, 3 figures, 3 tables
Beyond Traditional Beamforming: Singular Vector Projection for MU-MIMO
Creators: name: Ullah, Md Saheed
name: Murshed, Rafid Umayer
name: Saquib, Mohammad
name: Uddin, Md. Forkan
Publisher: name: arXiv
Year: 2023
Subjects: subject: Signal Processing (eess.SP)
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: This letter introduces a low-complexity beamforming approach for MU-MIMO systems with multiple data streams per user, minimizing inter-user interference and improving spectral efficiency (SE). The Interference-Optimized Singular Vector Beamforming (IOSVB) algorithm is developed by correlating inter-user interference with channel singular vectors. It blends interference minimization and SE maximization by identifying ideal singular vectors. Extensive simulations demonstrate that IOSVB provides near-optimal SE performance, closely matching exhaustive search results while reducing the computational overhead. This novel approach in MU-MIMO systems is a promising option for future 6G wireless communication networks due to its excellent performance and reduced complexity.
description: 5 pages, 4 figures, published in IEEE Wireless Communications Letters
Generative AIBIM: An automatic and intelligent structural design pipeline integrating BIM and generative AI
Creators: name: He, Zhili
name: Wang, Yu-Hsing
name: Zhang, Jian
Publisher: name: arXiv
Year: 2023
Subjects: subject: Machine Learning (cs.LG)
subject: Computer Vision and Pattern Recognition (cs.CV)
subject: FOS: Computer and information sciences

description: AI-based structural design represents a transformative approach that addresses the inefficiencies inherent in traditional structural design practices. This paper innovates the existing AI-based design frameworks from four aspects and proposes Generative AIBIM: an intelligent design pipeline that integrates BIM and generative AI. First, the proposed pipeline not only broadens the application scope of BIM, which aligns with BIM's growing relevance in civil engineering, but also marks a significant supplement to previous methods that relied on CAD drawings. Second, a two-stage generation framework incorporating generative AI (TGAI), inspired by the human drawing process, is designed to simplify the complexity of the design problem. Third, for the AI model in TGAI, this paper pioneers to fuse physical conditions into diffusion models (DMs) to build a novel physics-based conditional diffusion model (PCDM). In contrast to conventional DMs, on the one hand, PCDM directly predicts shear wall drawings to focus on similarity, and on the other hand, PCDM effectively fuses cross-domain information, i.e., design drawings, timesteps, and physical conditions, by integrating well-designed attention modules. Additionally, a new evaluation system including objective and subjective measures is designed to evaluate models' performance, complementing the evaluation system in the traditional methods. The quantitative results demonstrate that PCDM significantly surpasses recent SOTA techniques across both measures. The qualitative results highlight PCDM's superior capabilities in generating high-perceptual-quality drawings adhering to essential design criteria. In addition, benefiting from the fusion of physical conditions, PCDM effectively supports diverse and creative designs tailored to building heights and seismic precautionary intensities, showcasing its unique generation and generalization abilities.
description: 46 pages, 11 figures. Published in Information Fusion. https://www.sciencedirect.com/science/article/pii/S1566253524004329
Cantera-Based Python Computer Program for Solving Steam Power Cycles with Superheating
Creators: name: Marzouk, Osama A.
Publisher: name: arXiv
Year: 2024
Subjects: subject: Computational Engineering, Finance, and Science (cs.CE)
subject: Numerical Analysis (math.NA)
subject: FOS: Computer and information sciences
subject: FOS: Mathematics
subject: J.6; I.6.3
subject: 65-04, 78-10

description: One of the main sources of electricity generation is power plants that use water (steam) to rotate turbines, which drive large electric generators. The steam can be generated from renewable or non-renewable energy sources, such as geothermal energy and nuclear fuels. Having an analysis tool for modeling the performance of such steam power plants can greatly help in reaching optimum designs, leading to less fuel consumption, reduced pollution, and cheaper electricity. It is further advantageous if such modeling tool is free to access, does not require many inputs from the user, and gives results in a very short time. These remarks establish a motivation for the current study. This article documents a computer code written in the Python programming language for numerically analysing the main processes in a steam power cycle with superheating. The code utilizes built-in thermodynamic properties for water in the open-source software package "Cantera". A validation case with a benchmarking example in the literature using an independent source of water properties suggests that the developed code is correct. The code can be viewed as an extension to the Python examples for thermodynamic and power generation applications. Cantera can handle both subcritical and supercritical types of superheating. In the subcritical superheating, the steam absolute pressure does not exceed 220.9 bar. In the supercritical superheating, water becomes in a special condition called supercritical fluid, with absolute pressures above 220.9 bar.
description: 11 pages, 4 tables, journal paper
Methanogenic Biodegradation of Polycyclic Aromatic Hydrocarbons in Oil Sands Tailings
Creators: Guo, Henian
Publisher: name: University of Alberta Library
Year: 2024

The current hot water extraction method to recover bitumen from excavated oil sands ores after surface mining generates large volumes of fluid fine tailings that are temporarily deposited in oil sands tailings ponds. Promising techniques for tailings ponds reclamation such as end-pit lakes are facing potential challenges including the aquatic toxicity and methane emissions caused by tailing-derived hydrocarbons such as polycyclic aromatic hydrocarbons (PAHs). However, little information is available about efficient PAHs determination in tailings as well as the behavior of PAHs under methanogenic conditions in tailings. Therefore, method development for determination of PAHs and the investigation of the potential for PAH biodegradation under methanogenic conditions are the aims of this study. Conventional methods for PAHs determination in solid samples such as soils and sediments yielded poor recovery of PAHs from oil sands tailings due to the potential adsorption of PAHs onto the fine particles and organic compounds of tailings. Thus, an optimized method for PAHs determination in tailings was developed, which achieved ~94% pooled mean recovery of PAHs. The optimized method includes: (1) pre-treatment of FFT sample with DCM for 24 hours before extraction; (2) extraction of PAHs from the pre-treated FFT with DCM in a Soxhlet extractor for 24 hours; (3) purification of the extract with a silica gel chromatography column using DCM as eluent; (4) measurement on GC-MS. This method has high sensitivity and reproducibility and was used for the detection of PAHs in the bench-scale biodegradation experiments in this study. Sealed anaerobic microcosms containing tailing samples from 3 tailings ponds operated by Syncrude Canada Limited (Syncrude), Canadian Natural Resources Limited (CNRL), and Albian Sands Energy Incorporated (Albian), were set up to simulate methanogenic conditions below mudline of tailings ponds and to test if indigenous microbial community is capable to degrade PAHs. After ~700 days incubation under methanogenic conditions, no degradation of 6 abundant PAHs (naphthalene, phenanthrene, pyrene, dibenzofuran, fluorene, and dibenzothiophene) in tailings occurred, although toluene (added as a solvent of PAHs) was degraded within ~300 days in Syncrude and Albian microcosms. However, future degradation of PAHs can be expected since the potential PAHs degraders such as Clostridia have high relative abundance in the indigenous microbial communities of oil sands tailings.
Experimental demonstration of a simple free-space loss model for diffuse reflections in guided-mode LiDAR
Creators: name: Baudenon, Quentin
name: Hopkins, Ben
name: Pulikkaseril, Cibby
Publisher: name: arXiv
Year: 2023
Subjects: subject: Optics (physics.optics)
subject: FOS: Physical sciences

description: The growing use of photonic integrated circuits in light detection and ranging (LiDAR) sensors has made the speckle and phase distribution of the reflected light relevant for coupling into the guided modes of these systems. We adopt the use of a simplified diffuse surface model to show the average coupling efficiency of reflected speckle into guided modes can be predicted from the optical intensity at the target. For the first time, we provide experimental results to show that this relationship is valid for predicting free-space loss as a function of range. We intend to aid optics design for integrated photonic LiDAR systems, providing a simple and accurate model to predict the free-space loss from a representative target at all distances.
description: 8 pages, 5 figures
A Review on Industrial Augmented Reality Systems for the Industry 4.0 Shipyard
Creators: name: Fraga-Lamas, Paula
name: Fernandez-Carames, Tiago M
name: Blanco-Novoa, Oscar
name: Vilar-Montesinos, Miguel
Publisher: name: arXiv
Year: 2024
Subjects: subject: Distributed, Parallel, and Cluster Computing (cs.DC)
subject: Human-Computer Interaction (cs.HC)
subject: FOS: Computer and information sciences

description: Shipbuilding companies are upgrading their inner workings in order to create Shipyards 4.0, where the principles of Industry 4.0 are paving the way to further digitalized and optimized processes in an integrated network. Among the different Industry 4.0 technologies, this article focuses on Augmented Reality, whose application in the industrial field has led to the concept of Industrial Augmented Reality (IAR). This article first describes the basics of IAR and then carries out a thorough analysis of the latest IAR systems for industrial and shipbuilding applications. Then, in order to build a practical IAR system for shipyard workers, the main hardware and software solutions are compared. Finally, as a conclusion after reviewing all the aspects related to IAR for shipbuilding, it is proposed an IAR system architecture that combines Cloudlets and Fog Computing, which reduce latency response and accelerate rendering tasks while offloading compute intensive tasks from the Cloud.
description: Accepted version of an IEEE Access journal article
Simulated impacts of black bear predation on neonatal loss in boreal caribou
Creators: Horne, Liam Gleason
Publisher: name: University of Alberta Library
Year: 2024

Boreal caribou (Rangifer tarandus caribou) populations are declining across their range and the direct cause is predation. Black bears (Ursus americanus) can be significant predators of caribou neonates, but at high black bear densities in the boreal forest only a small proportion of bears could kill neonates without extirpating them. Bear predation is likely driven by bear density and spatial overlap with caribou neonates, but the interactive effect of density and overlap on predation rates is poorly understood. Using a simulation parameterized by empirical black bear and caribou data, we assessed i) how bear movement, habitat use, and density interact to influence predation on caribou neonates, and ii) whether caribou spatially separate from bears during calving to reduce predation risk (spatial separation hypothesis). We placed simulated neonates (≤2 weeks old) in either high-quality calving habitat or throughout caribou range. Neonates remained immobile and were killed when the movement paths of GPS-collared bears came within a specified detection distance. Simulations indicated that individual bears rarely kill neonates, but high-density bear populations can cause high neonatal mortality. However, reducing bear density did not result in a proportional reduction in predation. Bears were less likely to kill neonates in high-quality calving habitat than neonates with no habitat preference, supporting the spatial separation hypothesis. We emphasize the importance of predator density estimates to understand and effectively manage predation in systems with low-density, secondary prey such as boreal caribou. Removing bears is likely not an effective strategy to reduce bear predation on boreal caribou neonates. Future studies should aim to improve our understanding of how landscape alteration may affect bear demography.
SI Shen Feschrift-revised
Creators: name: Xiong, Ziqing
name: Lynch, Rebecca
name: Gubbins, Emma
name: Shultz, Mary
Publisher: name: AIP Publishing
Year: 2024
Subjects: classificationCode: 34
subject: Chemical sciences
subject: FOS: Chemical sciences
classificationCode: 51
subject: Physical sciences
subject: FOS: Physical sciences
classificationCode: 41
subject: Environmental sciences

description: On line supplement
Boysidia Ancey 1881
Creators: name: Gojšina, Vukašin
name: Hunyadi, András
name: Sutcharit, Chirasak
name: Tongkerd, Piyoros
name: Auffenberg, Kurt
name: Grego, Jozef
name: Vermeulen, Jaap J.
name: Reischütz, Alexander
name: Páll-Gergely, Barna
Publisher: name: Zenodo
Year: 2025
Subjects: Biodiversity
Taxonomy
Animalia
Mollusca
Gastropoda
Stylommatophora
Hypselostomatidae
Boysidia

description: GenusBoysidiaAncey, 1881
Pupa (Boysidia) Ancey, 1881: 373.
Diagnosis.
The genus Boysidia remains unrevised. This is urgently needed because many species are misunderstood due to poor original descriptions / drawings or the uncertain status of type specimens. The genus currently includes the following species: Boysidia chiangmaiensis Panha & J. B. Burch, 2002, B. conspicua (Möllendorff, 1885), B. dilamellaris D. - N. Chen, Y. - H. Liu & W. - X. Wu, 1995, B. dorsata (Ancey, 1881), B. gracilis F. Haas, 1937, B. guiyangensis T. - C. Luo, D. - N. Chen, G. - Q. Zhang, La. Zhang, Li Zhang & T. - W. Li, 1998, B. hangchowensis (Pilsbry & Y. Hirase, 1908), B. houaphanica Inkhavilay & Sutcharit, 2024, B. huangguoshuensis T. - C. Luo, D. - N. Chen & G. - Q. Zhang, 2000, B. hunana (Gredler, 1881), B. jinpingensis M. Tian, B. Fao & Y. - X. Chen, 2015, B. nanjiangensis Z. - L. Zhang, W. - H. Zhang & T. - C. Luo, 2011, B. orientalis B. Rensch, 1935, B. phatangensis Dumrongrojwattana & Assawawattagee, 2018, B. ringens van Benthem Jutting, 1950; B. robusta Bavay & Dautzenberg, 1912, B. shilinensis D. - N. Chen, M. Wu & G. - Q. Zhang, 1999, B. strophostoma (Möllendorff, 1885), B. taibaiensis D. - N. Chen, M. Wu & G. - Q. Zhang, 1999, B. tamtouriana Pokryszko & Auffenberg, 2009, B. tholos Panha & J. B. Burch, 2002, B. tongguanensis D. - N. Chen & W. - H. Zhang, 2002, B. xianfengensis W. - H. Zhang, D. - N. Chen & W. - C. Zhou, 2014, B. xiaoguanensis W. - H. Zhang, D. - N. Chen & W. - C. Zhou, 2014, B. xishanensis D. - N. Chen, M. Wu & G. - Q. Zhang, 1999, B. xiuwenensis W. - H. Zhang, T. - C. Luo & W. - C. Zhou, 2010.
The species listed below are excluded from the genus Bensonella and transferred to Boysidia due to the following traits (not shared among all these species): i) apertural dentition more similar to Boysidia (columellar lamella very strong and long, absence of three barriers on the parietal side); ii) surface sculpture similar to Boysidia (radial growth lines, no spiral striae); iii) larger shell sizes (frequently over 4 mm), which is more common in Boysidia representatives.
description: Published as part of Gojšina, Vukašin, Hunyadi, András, Sutcharit, Chirasak, Tongkerd, Piyoros, Auffenberg, Kurt, Grego, Jozef, Vermeulen, Jaap J., Reischütz, Alexander & Páll-Gergely, Barna, 2025, A new start? Revision of the genera Anauchen, Bensonella, Gyliotrachela and Hypselostoma (Gastropoda, Eupulmonata, Hypselostomatidae) of Southeast Asia with description of 46 new species, pp. 1-338 in ZooKeys 1235 on pages 1-338, DOI: 10.3897/zookeys.1235.145281
Cycling on rough roads: A model for resistance and vibration
Creators: name: Turner, Miles M.
Publisher: name: arXiv
Year: 2024
Subjects: subject: Popular Physics (physics.pop-ph)
subject: Biological Physics (physics.bio-ph)
subject: Classical Physics (physics.class-ph)
subject: FOS: Physical sciences

description: Minimising opposing forces is a matter of interest to most cyclists. These forces arise from passage through air ("drag") and interaction with the road surface ("resistance"). Recent work recognises that resistance forces arise not only from the deformation of the tyre ("rolling resistance") but also from irregularities in the road surface ("roughness resistance"), which lead to power dissipation in the body of the rider through vibration. The latter effect may also have an adverse impact on human health. In this work we offer a quantitative theory of roughness resistance and vibration that links these effects to a surface characterisation in terms of the International Roughness Index (IRI). We show that the roughness resistance and the Vibration Dose Value (or VDV, the usual vibration dosage metric) can be expressed in terms of elementary formulae. The roughness resistance depends only on the vertical stiffness of the bicycle and the roughness index. Surprisingly, other apparently relevant parameters, such as physiological characteristics of the bicycle rider and other features of the bicycle, do not enter. For roads of moderate roughness, roughness resistance is larger than rolling resistance. For very rough roads, roughness resistance is larger than aerodynamic drag. So only on roads of high quality (in most jurisdictions, accounting for less than 10~\% of the total) can roughness resistance be ignored. Roughness resistance can be mitigated by reducing the vertical stiffness of the bicycle. In common with other recent reports, we find that almost any cycling activity will breach public health guidelines relating to Vibration Dose Value.
Automatized Self-Supervised Learning for Skin Lesion Screening
Creators: name: Useini, Vullnet
name: Tanadini-Lang, Stephanie
name: Lohmeyer, Quentin
name: Meboldt, Mirko
name: Andratschke, Nicolaus
name: Braun, Ralph P.
name: García, Javier Barranco
Publisher: name: arXiv
Year: 2023
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Artificial Intelligence (cs.AI)
subject: FOS: Computer and information sciences

description: Melanoma, the deadliest form of skin cancer, has seen a steady increase in incidence rates worldwide, posing a significant challenge to dermatologists. Early detection is crucial for improving patient survival rates. However, performing total body screening (TBS), i.e., identifying suspicious lesions or ugly ducklings (UDs) by visual inspection, can be challenging and often requires sound expertise in pigmented lesions. To assist users of varying expertise levels, an artificial intelligence (AI) decision support tool was developed. Our solution identifies and characterizes UDs from real-world wide-field patient images. It employs a state-of-the-art object detection algorithm to locate and isolate all skin lesions present in a patient's total body images. These lesions are then sorted based on their level of suspiciousness using a self-supervised AI approach, tailored to the specific context of the patient under examination. A clinical validation study was conducted to evaluate the tool's performance. The results demonstrated an average sensitivity of 95% for the top-10 AI-identified UDs on skin lesions selected by the majority of experts in pigmented skin lesions. The study also found that the tool increased dermatologists' confidence when formulating a diagnosis, and the average majority agreement with the top-10 AI-identified UDs reached 100% when assisted by our tool. With the development of this AI-based decision support tool, we aim to address the shortage of specialists, enable faster consultation times for patients, and demonstrate the impact and usability of AI-assisted screening. Future developments will include expanding the dataset to include histologically confirmed melanoma and validating the tool for additional body regions.
description: 11 pages, 4 figures
O'ZBEKISTONDA MAJBURIY SUG'URTA BOZORIDA YANGI INNOVATSIYALARNING AHAMIYATI
Creators: name: Masimdjanova, Muqaddam
Publisher: name: Zenodo
Year: 2024

description: Majburiy sug'urta bozorining O'zbekistonda rivojlanishi, zamonaviy texnologiyalarni joriy etish va iqtisodiyotning umumiy barqarorligini oshirish o'rtasidagi aloqani o'rganishga bag'ishlangan. Ushbu maqola, yangi texnologik innovatsiyalar qanday qilib sug'urta sohasining samaradorligini yaxshilashi, mijozlar uchun qulayliklar yaratishi va sug'urta kompaniyalari faoliyatining samaradorligini oshirishi mumkinligini tahlil qiladi. Shuningdek, O'zbekistondagi sug'urta bozorini yanada rivojlantirish uchun amaliy takliflar keltiriladi.
Technosignatures longevity and Lindy's law
Creators: name: Balbi, A.
name: Grimaldi, C.
Publisher: name: arXiv
Year: 2024
Subjects: subject: Popular Physics (physics.pop-ph)
subject: Instrumentation and Methods for Astrophysics (astro-ph.IM)
subject: FOS: Physical sciences

description: The probability of detecting technosignatures (i.e. evidence of technological activity beyond Earth) increases with their longevity, or the time interval over which they manifest. Therefore, the assumed distribution of longevities has some bearing on the chances of success of technosignature searches, as well as on the inferred age of technosignatures following a first contact. Here, we investigate the possibility that the longevity of technosignatures conforms to the so-called Lindy's law, whereby, at any time, their remaining life expectancy is roughly proportional to their age. We show that, if Lindy's law applies, the general tenet that the first detected technosignature ought to be very long lived may be overruled. We conclude by discussing the number of emitters that had to appear, over the history of the Galaxy, in order for one of them to be detectable today from Earth.
description: 9 pages, 4 figures
Applying Integrated Management Systems to the Application of Process Safety Management in the Food Processing Industry
Creators: Sistilli, Amanda M
Publisher: name: University of Alberta Library
Year: 2024

Process safety incidents in the food processing industry in North America are a consistent trend. The food processing industry uses ammonia in cooling systems for refrigeration and freezers. While ammonia used in refrigeration only accounts for 2% of total ammonia produced, the food processing industry accounts for the majority of ammonia releases in North America. Process Safety Management is a management system used to mitigate and prevent process safety incidents such as ammonia releases but would need to be implemented in the food processing industry in addition to food safety management systems that these processers are required to have in place. Barriers to the effective implementation of multiple management systems such as resource limitations, leads to the need for creative solutions to implementation. Integrated management systems are a tool that can be leveraged to find common facets across these management system standards and implement them in a way that optimizes resource and complements each management system in achieving its respective goal. This thesis reviews an integrated management system case study of a US Frozen Food Manufacturer that adheres to both OSHA 1910.119 Process Safety Management regulations and the SQF Food Manufacturing Standard. Current and potential integration of both management systems were studied. The proposed integration was completed following the methodology outlined in the Integrated Use of Management System Standards Handbook by International Organization for Standardization (ISO). Interviews with employees and a review of the organization’s governance documents were used to map the organization’s operating and supporting processes. A clause-by-clause comparison was completed for OSHA 1910.119 and SQF Food Manufacturing Standard. By leveraging the areas of commonalitybetween the two standards, a recommendation for further integration was proposed. This research aims to provide a roadmap to food processing organizations looking to improve their process safety iiiand food safety performance in a way that also provides operational efficiencies and add to the body of research on integration case studies, opportunities and limitations.
The Use of Terrestrial Laser Scanners for 3-Dimensional Modelling and Quantification of the effects of Competition and Phenology on Plant Structure with Fractal Analysis and Quantitative Structural Modelling Tools
Creators: Alencastro, Felipe
Publisher: name: University of Alberta Library
Year: 2024

Terrestrial laser scanners (TLS) are active remote sensing sensors that use light to measure distances between the sensor and objects generating a three-dimensional dataset. This technology has been used in a diverse range of ecological studies measuring plant and vegetation properties. In the present dissertation, I used three-dimensional modelling algorithms on TLS derived point-clouds to assess plant structural parameters, plant competition, and the effects of plant phenological processes on tree structure.

Chapter 2 uses the Quantitative structure Model (QSM) to assess lianas and host-trees structural metrics in three different lianas infestation scenarios. The findings reveal that liana infestation impacts hosting trees differently. Lifeform structural metrics showed that lianas wood elements can reach much longer lengths than the elements of the host trees indicating a better space distribution. Also, the total wood volume proportion presented by each lifeform varies with the tree size and the level of liana infestation. In the end, two QSM derived metrics were proposed to evaluate liana infestation on trees of different sizes and ecosystems.

In chapter 3, fractal analysis was used to identify structural differences between trees living in forested and open-field environments. This study showed that the competition against neighboring plants in forested areas affects tree development and space occupancy. Trees living in open-field conditions occupy the space more efficiently and present more symmetric architecture than trees living in the forest, indicating less environmental stress.

The presence of leaves has a great impact on plant three-dimensional modelling, space occupancy, and tree architecture. In chapter 4, fractal analysis was used to explore the effect of the change of leave coverage on temperate broad-leaf tree species during the winter and spring seasons on tree architecture. The findings showed that trees occupy the space more efficiently during the leafed season. Last, Chapter 5 presents the summary of this thesis findings and provides directions for future research on three-dimensional modelling of plants using TLS point-clouds.
Know Your Place for Mental Health on the Prairies: Tacting a Topography of Learning from Alberta for Curricula and Educational Studies
Creators: Holt, Regan C.
Publisher: name: University of Alberta Library
Year: 2024

How might we understand the role of place within mental health? Already exposed as a teacher to a harmful curriculum of place in Alberta, I posed this question based on the opinion that place

relations mattered for making sense of mental health here. Local educators and many beyond, may need to be made aware of a long-running local curriculum on the prairies once invested in

perpetuating the eugenics project. Violent and racist, this mental health initiative applied pioneering metaphors, ancient philosophy, medicalized definitions, and ideals shaped by settler colonialism to garner public support. In resistance, I purposely sought place-conscious ideas in and around amiskwaciy wâskahikan on Treaty 6 territory or Edmonton, Alberta, Canada. A review focusing on intercultural, transdisciplinary, lyrical, and decolonizing sensibilities assisted with generating tact-full educational exercises for grounding the co-creative approach introduced as an innovation for academic and critical ecohermeneutic research. Of late, ecohermeneutics has

emerged from the texts of curriculum studies as a philosophical, place-conscious practice of interpretation to question and challenge conceptual notions associated with collective

mis/understandings and broken relations in Canada. From four rounds of one-on-one meetings with former junior high students over eight months, possible alternative, conceptual responses

relevant to the contexts of present-day schooling were expressed and gathered. Following each round, I met with a local Knowledge Keeper, providing ecological teachings and translations of place names that emerged through my former students’ resonant descriptions. Then, layered images from the field were arranged alongside our transcribed interpretations.
title: The Interaction of Domestic Politics and English Naval Operations During the Civil War and Interregnum, 1642-1660
Creators: name: Crowson, Don P.
Publisher: name: Old Dominion University
publisherIdentifier: https://ror.org/04zjtrb98
publisherIdentifierScheme: ROR
Year: 2006

description: The interaction of domestic politics and the English Navy during the Civil Wars and the following interregnum is analyzed. The period of interest is during the reign of Charles I (1646-1649); the Commonwealth (1649-1653), when the government functioned essentially as a republic; and the Protectorate, (1653-1660), when the executive function was performed first by Oliver Cromwell and then by his son, Richard Cromwell. A brief description of the immediate preceding years is included to establish the political climate of the time.

The major events with political implications are considered in detail. They are: (1) the struggle between Parliament and the King to gain control of the Navy at the beginning of the Civil War; (2) the revolt of a significant portion of the Navy in 1648 against Parliamentary control in favor of King Charles; (3) the "Western Design" application of the Navy by Oliver Cromwell to solve his financial problems by interdicting the Spanish plate fleet from the Americas; and (4) the involvement of the Navy in the restoration of Charles II to the throne during the politically chaotic period after Oliver Cromwell's death when his son, Richard, served as the Lord Protector.

Two themes throughout the thesis are the relative significance of the political bias of the senior naval officers and the administrative changes to support the current regime. A third theme involves the propensity of the crews to respond to a variety of factors including conditions of service, pre-conditioning to obey officers, and loyalty to the King. The situations under which those inclinations were subject to change or complete breakdown are described.
Adaptive mesh refinement for electromagnetic simulation
Creators: name: Belokrys-Fedotov, Alexey
name: Garanzha, Vladimir
name: Kamenski, Lennard
name: Chikitkin, Alexandr
name: Pesnya, Evgeniy
name: Aseev, Nikita
name: Vorobyev, Andrey
Publisher: name: arXiv
Year: 2023
Subjects: subject: Numerical Analysis (math.NA)
subject: FOS: Mathematics
subject: 65N50

description: We consider problems related to initial meshing and adaptive mesh refinement for the electromagnetic simulation of various structures. The quality of the initial mesh and the performance of the adaptive refinement are of great importance for the finite element solution of the Maxwell equations, since they directly affect the accuracy and the computational time. In this paper, we describe the complete meshing workflow, which allows the simulation of arbitrary structures. Test simulations confirm that the presented approach allows to reach the quality of the industrial simulation software.
description: Reproduced with permission of Springer Nature Switzerland. The final authenticated version is available online at: https://doi.org/10.1007/978-3-031-59652-0_7
Transcultural Singing Between Continents: A Multimodal Reflection of Hybridity in the Ukrainian-Canadian Vernacular Song Repertoire
Creators: Zaitseva-Herz, Olga
Publisher: name: University of Alberta Library
Year: 2024

This study investigates the degree of multimodal hybridity observed in the collection of Ukrainian-Canadian vernacular songs. It is grounded in the compilation of songs assembled by Robert Klymasz during his field research in the 1960s, conducted among Ukrainian immigrants residing on the Canadian prairies. Historically, Canadian and European ethnomusicologists have usually regarded these songs, many of which demonstrate hybrid qualities, as being marginal. A significant portion of Klymasz's collection remains unexamined and unpublished, making this dissertation the first comprehensive analysis of this archive material. This research specifically centers on the analysis of vocal techniques employed by singers, a topic that has not yet been explored. The present study adopts an approach that incorporates both ethnomusicological and musicological perspectives to examine voice performances, melodies and forms. This investigation aims to conduct an analysis of the different components inside songs, with the expectation that this methodology will provide new perspectives and enhance our understanding of the degree of hybridity in components such as singing styles, techniques, and melodies in addition to the lyrical content. Moreover, this study incorporates statistical methodologies developed from mathematical analysis, namely empirical means and variances of melodic data. These techniques facilitate the depiction of the enduring qualities and changes within musical textures found in the songs. Previous scholarly inquiries have allocated less attention to the voice and performance-focused elements of Ukrainian-Canadian songs, in favour of their lyrics. They have also viewed them mainly from the perspective of pre-immigration surrounding without investigating their multifaceted hybridity. Therefore, the current research contributes to the academic discourse by reinforcing and expanding the concept that vernacular diaspora song traditions should not be solely perceived as preserved relics originating from pre-emigration cultures. The primary aim of this research is to develop a comprehension of the complex connections between pre-migration and post-migration encounters, as demonstrated in the musical textures found within the vernacular song repertoire. Rather than relying on traditional academic assumptions of marginalization, isolation, and contrast, the examination of diverse elements within these community songs reveals their sophisticated fusion and interconnection.
SegNet: A Segmented Deep Learning based Convolutional Neural Network Approach for Drones Wildfire Detection
Creators: name: Jonnalagadda, Aditya V.
name: Hashim, Hashim A.
Publisher: name: arXiv
Year: 2024
Subjects: subject: Computer Vision and Pattern Recognition (cs.CV)
subject: Artificial Intelligence (cs.AI)
subject: Image and Video Processing (eess.IV)
subject: FOS: Computer and information sciences
subject: FOS: Electrical engineering, electronic engineering, information engineering

description: This research addresses the pressing challenge of enhancing processing times and detection capabilities in Unmanned Aerial Vehicle (UAV)/drone imagery for global wildfire detection, despite limited datasets. Proposing a Segmented Neural Network (SegNet) selection approach, we focus on reducing feature maps to boost both time resolution and accuracy significantly advancing processing speeds and accuracy in real-time wildfire detection. This paper contributes to increased processing speeds enabling real-time detection capabilities for wildfire, increased detection accuracy of wildfire, and improved detection capabilities of early wildfire, through proposing a new direction for image classification of amorphous objects like fire, water, smoke, etc. Employing Convolutional Neural Networks (CNNs) for image classification, emphasizing on the reduction of irrelevant features vital for deep learning processes, especially in live feed data for fire detection. Amidst the complexity of live feed data in fire detection, our study emphasizes on image feed, highlighting the urgency to enhance real-time processing. Our proposed algorithm combats feature overload through segmentation, addressing challenges arising from diverse features like objects, colors, and textures. Notably, a delicate balance of feature map size and dataset adequacy is pivotal. Several research papers use smaller image sizes, compromising feature richness which necessitating a new approach. We illuminate the critical role of pixel density in retaining essential details, especially for early wildfire detection. By carefully selecting number of filters during training, we underscore the significance of higher pixel density for proper feature selection. The proposed SegNet approach is rigorously evaluated using real-world dataset obtained by a drone flight and compared to state-of-the-art literature.
Quantitatively Modelling the Transition from Non-Genetic to Genetic Antimicrobial Resistance
Creators: Guthrie, Joshua D
Publisher: name: University of Alberta Library
Year: 2024

Antimicrobial resistance is a growing global health crisis that requires an interdisciplinary approach to better understand and combat. Physics-based modelling has provided valuable insights into the underlying mechanisms of antimicrobial resistance and the quantitative behaviour of resistant cell populations. Antimicrobial resistance can arise through genetic mutations and from non-genetic mechanisms that arise due to underlying stochastic physical processes which occur during gene expression. Non-genetic resistance results in phenotypic heterogeneity in genetically identical cell populations, which enables a fraction of the population to survive during drug treatment. Although genetic and non-genetic mechanisms have been investigated individually, it remains unclear how non-genetic resistance alters the evolution of antimicrobial resistance. In this thesis, physics-based methods are used to develop and analyze a phenomenological model of cell population dynamics to investigate the evolution of antimicrobial resistance during drug treatment. The model quantifies the transition from reversible non-genetic resistance to permanent genetic resistance and is used to make quantitative predictions about antimicrobial resistance evolution in cell populations. A deterministic framework that utilizes population growth equations is used to investigate regimes where stochastic fluctuations in population dynamics are negligible and standard numerical methods are used to solve these equations. In regimes where stochastic fluctuations play an important role in the population dynamics leading to antimicrobial resistance, the model is reformulated in a stochastic framework as a set of continuous-time stochastic processes and simulated using Monte Carlo methods. The structure and parameter values of the model are guided by experimental studies of non-genetic and genetic antimicrobial resistance in fungi, with parameter scans being used to investigate changes in subpopulation fitness and their effect on the survival and evolution of the population. The research presented in this thesis supports previous experimental and qualitative findings of antimicrobial resistance evolution by showing quantitatively that non-genetic resistance aids the survival of cell populations undergoing drug treatment and increases the probability of an antimicrobial resistance mutation appearing in the population. Additionally, a novel hypothesis about the evolution of antimicrobial resistance in cell populations is suggested, namely that increased survival due to non-genetically resistant cells results in intraspecific competition between subpopulations and hinders the evolution of antimicrobial resistance. The research presented in this thesis has advanced our understanding of antimicrobial resistance by providing a quantitative framework for investigating the transition from non-genetic to genetic resistance.
Understanding the Influence of Data Characteristics on the Performance of Point-of-Interest Recommendation Algorithms
Creators: name: Dietz, Linus W.
name: Sánchez, Pablo
name: Bellogín, Alejandro
Publisher: name: arXiv
Year: 2023
Subjects: subject: Information Retrieval (cs.IR)
subject: FOS: Computer and information sciences

description: Point-of-interest (POI) recommendations are essential for travelers and the e-tourism business. They assist in decision-making regarding what venues to visit and where to dine and stay. While it is known that traditional recommendation algorithms' performance depends on data characteristics like sparsity, popularity bias, and preference distributions, the impact of these data characteristics has not been systematically studied in the POI recommendation domain. To fill this gap, we extend a previously proposed explanatory framework by introducing new explanatory variables specifically relevant to POI recommendation. At its core, the framework relies on having subsamples with different data characteristics to compute a regression model, which reveals the dependencies between data characteristics and performance metrics of recommendation models. To obtain these subsamples, we subdivide a POI recommendation data set on New York City and measure the effect of these characteristics on different classical POI recommendation algorithms in terms of accuracy, novelty, and item exposure. Our findings confirm the crucial role of key data features like density, popularity bias, and the distribution of check-ins in POI recommendation. Additionally, we identify the significance of novel factors, such as user mobility and the duration of user activity. In summary, our work presents a generic method to quantify the influence of data characteristics on recommendation performance. The results not only show why certain POI recommendation algorithms excel in specific recommendation problems derived from a LBSN check-in data set in New York City, but also offer practical insights into which data characteristics need to be addressed to achieve better recommendation performance.
description: Published in Information Technology & Tourism, 2025