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Understanding and Modeling Drivers\u27 Diversion Behavior during Congestion
No full textTraffic congestion causes significant economic losses due to delays and excessive fuel consumption. Understanding drivers\u27 behaviors, particularly in terms of diversionary routing to avoid congestion, is crucial for addressing this issue. This study investigates driver behavior during congestion and develops a predictive model for route diversion decisions using about 20 million anonymized trips from global positioning system (GPS) data in Sydney, Australia. Among the most unique and significant contributions of this work was the development of a methodology to identify and graphically depict commute trips and assess the impact of prevailing traffic conditions and related driving factors on diversion likelihood without relying on access to supplemental data. Examples of driving factors considered include distances and times from origins and destinations, durations of delays caused by congestion, length of congested areas, and roadway classification. Findings indicate that experienced delay per congestion distance and remaining distance to the destination positively influence diversion, while expected increases in travel time on alternative routes discourage it. These results can enhance traffic simulation models and improve traffic management strategies. Overall, the contributions of this paper have both practical importance and theoretical applicability and provide a long-absent step toward understanding how individual drivers respond to congestion and make subsequent routing choices
TEMPORAL SCALES OF SEDIMENT ACCUMULATION, MASS WASTING, AND STRATIGRAPHY ACROSS THE MISSISSIPPI RIVER DELTA FRONT
No full textThe Mississippi River Delta Front (MRDF) is a subaqueous apron of rapidly deposited, weakly
consolidated sediment extending from the subaerial portions of the Mississippi River’s Birdsfoot Delta, historically known for sediment transport via mass wasting. To better understand the spatial and temporal dynamics of processes influencing the MRDF, 29 cores ranging from 5.8 to 8.71 meters in length were collected from the South Pass (SP) and Southwest Passes (SWP). These cores targeted specific depositional environments, including the undisturbed topset apron, medial mudflow gully, mudflow lobe, and prodelta. The cores were analyzed along their full lengths for gamma density, grain size, X-radiography, resin infused thin sections, and geochronology using 210Pb / 137Cs radionuclides. Analyzing sediment for 210Pb stair-step profiles and gamma density fluctuation reveals mass movement and deposition within gully flows up to 6 m deep, aligning with Keller et al. (2017). Mudflow gully event return periods in the SWP and SP are decadal (10.7 years) and multi-decadal (66.7 years), respectively with 210 Pb inventories and focusing factors center around the SWP gully, indicating preferential sediment loading in proximal environments and distal transport via mudflow gullies. Elements of microfabrics, including sediment grain composition, biogenic activity, biogenic debris, and sediment structures, display distinct depositional mechanisms not limited to specific environments or study sites. These microfabrics aid paleodelta reconstruction and apply to regions of sediment instability in ancient systems. Budget estimations via 137 Cs geochronology (~9.4 x 10⁶ mt y⁻¹ km⁻²) across the 306 km² study area represent 12% of the river load minus channel storage at Belle Chasse, LA, and 31% of the sediment discharge for SW Pass, South Pass, and Pass a Loutre (2008–2010, Allison et al., 2012). Extrapolated to the 2000–2500 km² MRDF region, sediment accumulation accounts for ≤77–98% of Belle Chasse’s suspended discharge. This study serves as an initial step toward a more thorough sediment mass balance for the Mississippi Birdsfoot delta (both subaerial and subaqueous), which should incorporate sediment accumulation rate (SAR) estimates for the delta platform’s wetland and cores from regions that have not yet been analyzed geochronologically
NANO-CATALYST ASSISTED LIGNIN DEPLOYMERIZATION VIA CONTINOUS ATOMIZATION AND MICROWAVE IRRADIATION
No full textLignin is the most plentiful natural aromatic polymer and is receiving the attention of the scientific community due to the high demand for new sources of energy in light of increasing fossil fuel prices and its decreasing reserves. In addition, owing to their high phenolic compound content, lignin is perceived as a prime source of aromatic building blocks. Despite the common use of conventional methods of lignin depolymerization, a plethora of research is being executed to come up with new techniques that can aid in proper lignin utilization in various applications. We used three different approaches to understand and add to the knowledge of the transformation of lignin to high-added-value chemicals/biofuels. Firstly, we conducted experiments to understand the depolymerization pathway of lignin pyrolysis and its interaction with a CuO/SiO2 catalyst via a lignin model compound (1,2 dichlorobenzene, DCB). Secondly, we used Doehlert’s design, a multivariate experimental design optimization technique, to find the optimal conditions for hydrolyzed lignin pyrolysis in the gas phase. Finally, we employed the findings from the first and second approach of the research to optimize the use of the CuO/SiO2 catalyst in lignin microwave depolymerization where we performed basic proof of concept experiments. In addition, we used COMSOL Multiphysics to model the increase in temperature profile during the process. The real values from microwave experiments were used to validate the simulated results
Optimal power flow solution via noise-resilient quantum interior-point methods
No full textThis paper presents quantum interior-point methods (QIPMs) tailored to tackle the DC optimal power flow (OPF) problem using noisy intermediate-scale quantum devices. The optimization model is redefined as a linearly constrained quadratic optimization. By incorporating the Harrow–Hassidim–Lloyd (HHL) quantum algorithm into the IPM framework, Newton\u27s direction is determined through the resolution of linear equation systems. To mitigate the impact of HHL error and quantum noise on Newton\u27s direction, we utilized a noise-tolerant quantum IPM. This approach provides high-quality OPF solutions even in scenarios where inexact solutions to the linear equation systems result in approximated Newton\u27s direction. To enhance performance in cases of slow convergence and uphold the feasibility of OPF upon convergence, we propose a classically augmented noise-tolerant QIPM. This technique is designed to expedite convergence relative to classical IPM while maintaining the accuracy of the solution. The proposed QIPM variants are studied through comprehensive simulations and error analyses on 3-bus, 5-bus, 118-bus, and 300-bus systems. By modeling the errors and incorporating quantum computer noise, we simulate the algorithms on Qiskit and classical computers to better understand their effectiveness and feasibility under realistic conditions
Altérité et Inclusion Culturelle à l’Ere des Algorithmes de l’Intelligence Artificielle
No full textAu début des années 2000, la révolution numérique engagée par le continent africain va finir par impacter tous les secteurs économiques. Cette révolution que qualifie Jean-Michel Huet de leapfrog va désormais embarquer avec elle les algorithmes : c’est l’ère de l’intelligence artificielle et des mégadonnées. Cette nouvelle technologie fracasse tous les anciens équilibres non seulement des industries culturelles et créatives mais également patrimoniaux. Ce bouleversement culturel se traduit à travers l’expression de la diversité culturelle, un élément important du patrimoine culturel. Le patrimoine culturel africain dans ce contexte de mondialisation et de globalisation fait face aux défis de préservation, de sauvegarde et de valorisation. La technologie numérique vient ainsi ouvrir des perspectives nouvelles à l’expression des diversités culturelles. Toutefois, bien que les technologies digitales aient radicalement transformé la production, la création et la diffusion des contenus culturels sous toutes ses formes, on dénote une dictature des algorithmes constituant ainsi un frein à la diversité des expressions culturelles et donc à la valorisation du patrimoine culturel africain. Ce biais algorithmique fait d’inégalités culturelles est l’essence même de notre réflexion. A travers cette réflexion, nous souhaitons explorer de façon significative les biais des algorithmes de l’intelligence artificielle ainsi que leurs opportunités au-delà des industries culturelles et créatives mais plus précisément à la valorisation du patrimoine culturel africain. Ce travail s’inscrit par conséquent dans une réflexion plus large sur le rôle det la contribution des algorithmes de l’intelligence artificielle dans l’expression des diversités culturelles, tout en préservant la richesse des diversités
An Interdisciplinary Analysis Framework for Found Object Experimental Music
Full text linkFound object experimental music consists of compositions and performances created with objects not intended for musical performance. Found objects can range from appliances and household items to power tools and consumer products to souvenirs and heirlooms. Although these objects are used with the intent of creating musical compositions, new characteristics that are not found in traditional music emerge. One major characteristic that differentiates found object music from traditional music is that the objects have inherent cultural associations and meaning outside of their use in the composition. While an analysis of the sonic structures and scores of found object experimental music is possible, the meaning of the objects and how it affects the structure and interpretation of the composition cannot be fully understood using these processes. This study details a framework for analyzing found object experimental music using interdisciplinary object analysis tools borrowed from anthropology, design theory, philosophy and art theory, and theater studies
Variation in Response to Phosphorus Among Sweetpotato (Ipomoea batatas L.) Cultivars
Full text linkPhosphorus (P) is essential for plant growth and is often a major limiting nutrient in agriculture. In sweetpotato (Ipomoea batatas), studies on the role of P on storage root yield have been limited because of the lack of response and inconsistent results across cultivars and years. Growing evidence shows that current phosphate (Pi) fertilizer rates can be reduced while maintaining productivity. Newly published molecular evidence shows differential expression of phosphate starvation response genes among sweetpotato cultivars, further supporting the hypothesis of cultivar-specific Pi sensitivity. The research herein sought to characterize root system architecture and yield response to Pi availability in greenhouse and field conditions. It has been shown that plants modify root system architecture to optimize Pi scavenging when P becomes limiting. The results show cultivar-specific variation in root system architectural adaptations in response to Pi availability, supporting the current hypothesis of cultivar-specific variation in response to Pi availability. It also helps to clarify the molecular evidence by filling in gaps in describing cultivar-specific Pi sensitivity. Results from split-root experiments designed to simulate variation in localized Pi availability corroborate the hypothesized cultivar variation in Pi sensitivity and complement the evidence implicating known P-responsive genes in the phosphate starvation pathway. Results from the field studies support molecular and physiological evidence that sweetpotato tolerates low Pi in a genotype-specific manner. A separate field study investigating the possible role of nitrogen in modulating cultivar response to Pi availability failed to show this hypothesized relationship; instead, it provided evidence that current sweetpotato cultivars tolerate Pi levels considered critical in other crops. The lack of significant yield response to P fertilization in most cultivars suggests that the current P fertilizer recommendations could be reduced without compromising sweetpotato yield. This adjustment could lead to significant cost savings for producers while reducing P losses to the environment
Petroleum Reservoir Dynamics
Full text linkThe book is structured into nine chapters, each designed to build a comprehensive understanding of reservoir engineering principles. Chapter 1 introduces the discipline and its connections with other areas of petroleum engineering. Chapters 2 through 5 address steady-state flow and its various complexities: Darcy’s equation and its limitations (Chapter 2); flow geometries and skin factor concepts (Chapter 3); compressible oil and gas flow (Chapter 4); and non-horizontal flow using the flow potential concept (Chapter 5).
In Chapter 6, the pressure diffusivity equation is explored alongside key concepts of radius of investigation and average reservoir pressure. Chapter 7 delves into the pseudo-steady-state (PSS) flow regime, its applications in multi-well drainage, and its relationship with well productivity index, inflow performance relationship, vertical flow performance, and nodal analysis.
The final chapters focus on transient radial flow and its applications in well testing. Chapter 8 introduces transient drawdown analysis. Chapter 9 discusses the superposition principle in time and space, with application to the modeling of sealing faults and buildup test analysis.
To enhance engagement and learning, each chapter includes quiz questions - primarily in a True/False format - with answers provided at the end of the book. Additionally, numerous examples are integrated throughout to demonstrate the practical significance of the concepts and their relevance to reservoir engineering practice.https://repository.lsu.edu/etext/1003/thumbnail.jp
Academic Screening in Middle School: Exploring Bivariate and Intraindividual Relations in Reading and Math Performance
Full text linkEarly adolescence is a pivotal time for academic development; however, the vast majority of research on reading and math development within a multitiered system of support has been conducted among elementary students. Using triannual (Fall, Winter, Spring) academic screening data, we examined the transactional development of reading and math skills among sixth and seventh grade students (N = 1,693) using Bayesian longitudinal structural equation modeling (SEM). We find equivocal support for four of the five types of longitudinal SEMs tested (dual-change, linear change, proportional change, latent curve with structured residuals, and random-intercepts cross-lagged models). Stable between-person differences in math and reading (i.e., latent/random intercepts) are strongly correlated regardless of the modeling approach (r =.70–.77), consistent extensive prior research in this area. However, correlated growth processes at the between-person level and within-person transactional relations of math and reading were inconsistent across models. We discuss the practical implications of these findings as well as the methodological issues with detecting within-person instructional response in triannual screening
Understanding the Superstitious Consumer: A Multi-Method Investigation of Consumer Superstition in Retail and Service Encounters
No full textConsumers may use superstitions when making purchase decisions, especially in contexts involving risk or uncertainty. For example, some people employ superstitions, such as using numbers from a fortune cookie, knocking on wood after making a significant decision, or entering a store with the left foot first, in the belief that these practices can increase the odds of success or a positive outcome (Rodriguez 2023). The psychology literature explores the topic of superstition in-depth, including how it develops and why people use it. Research in the marketing domain has explored the effects of superstition on brand preference and its impact on performance expectations. What has been substantially under-researched is how consumers utilize superstition in their decision-making processes in retail and service contexts, particularly when changes in the purchase process, such as agent type or agent behavior, influence buying patterns. The first phase of this research aims to understand the various manifestations of superstition among consumers and how they utilize these beliefs in their purchase decisions, thereby developing and validating a novel typology of superstition use. In the second phase, an empirical analysis examines how different agent types and behaviors affect superstitious consumers, exploring the impact of superstitions on consumer buying behavior