OVERPARKED AND UNDERSERVED: ANALYZING THE CONTRADICTION IN PARKING POLICIES IN PHILADELPHIA’S UNIVERSITY CITY DISTRICT

Despite the extensive attention given to broader transportation planning issues, parking studies have received insufficient focus. While many existing parking studies rely on quantitative data and modeling methods, there is a notable gap in research that incorporates interviews with key stakeholders at the grassroots level to truly understand the nuances of parking management and policies. Parking significantly influences the built environment, travel behaviors, housing patterns, and the overall community well-being. This study reveals the oversupplied parking spaces fail to meet residents’ needs by integrating data from the 2023 Parking Inventory in the University City District and insights from interviews with a city planner, a real estate developer, and a parking lot owner. This paper aims to shed light on this critical aspect of parking policies and propose actionable strategies to address the challenges and opportunities associated with parking

Reducing Dairy Milk Waste Through Dynamic Pricing Model Execution in a Retail Setting

Food waste is a significant challenge worldwide, with far-reaching implications for sustainability, food security, and economic efficiency. In the United States alone, an estimated 40% of total food produced goes uneaten, amounting to 218 billion dollars or 1.3% of Gross Domestic Product (GDP). Perishable food waste, including dairy products, constitutes a substantial portion of this waste, with dairy waste alone estimated at approximately 25 billion pounds annually. This study focuses on dairy milk waste, which is a major contributor to overall food waste, and explores the use of dynamic pricing as a potential solution to reduce waste in the retail sector. We developed a dynamic pricing model based on pasteurized milk shelf life and we evaluated its performance by deploying it in a retail store setting. The study evaluated consumer choice and willingness to pay when presented with (i) product groups that have three different levels of remaining shelf life left (high, medium, and low), (ii) two different pricing models (static, dynamic), and (iii) three different types of dairy milk products (whole, reduced, and fat-free). The study also evaluated the potential food waste reduction at the retail level and the economics for the retailer when static vs. dynamic pricing model is used. The study hypothesized that the implementation of shelf-life-based dynamic pricing would not significantly affect overall consumer demand for fluid milk and the factors governing consumer preferences. Additionally, it was hypothesized that consumer purchasing behavior for milk with the highest shelf life would partially but uniformly shift towards milk with lower shelf life. Finally, the study hypothesized that the implementation of dynamic pricing would weakly improve retailer revenue from fluid milk sales. We conducted a two-week study using ½ Gal pasteurized milk from Cornell Dairy, categorized into High Shelf-Life (21-8 days left), Medium Shelf-Life (7-4 days left), and Low Shelf-Life (3- 0 days left). Each week a different pricing model was implemented and evaluated; static pricing model in week 1 where all products had a uniform price of $2.59, and dynamic pricing model in week 2 where product with high, medium, and low shelf-life had a price of$3.39, $2.59, and$1.39, respectively. The product was placed with other brands of pasteurized milk, but clearly separated and marked, including (i) displaying the shelf life left with color coded sticker on each container, (ii) displaying shelf life left, price, and milk type with stickers on the product shelves, and (iii) providing a large informational sign with information on the study, shelf life left, and prices. Results indicated a noticeable impact of dynamic pricing model on consumer purchasing patterns, with a shift towards purchasing milk with shorter shelf lives. This suggests that dynamic pricing can be an effective tool in reducing food waste while maintaining consumer engagement. Additionally, there was a weak increase in retailer revenue, indicating that dynamic pricing can be economically sustainable for the retailer. These findings underscore the potential of dynamic pricing strategies to balance economic viability with environmental sustainability in the retail sector. This study contributes to the limited body of research on impact of dynamic pricing strategies on food waste reduction, highlighting the importance of innovative approaches in addressing this complex food industry challenge. The findings of this study have implications for policymakers, retailers, and consumers, emphasizing the need for collaborative efforts to reduce food waste and promote sustainability

Combining reproductive outcomes predictors and automated estrus alerts recorded during the voluntary waiting period identified subgroups of cows with different reproductive performance potential

The objective was to compare differences in reproductive performance for dairy cows grouped based on the combination of data for predictors available during the prepartum period and before the end of the VWP, automated estrus alerts (AEA) during the VWP, and the combination of both factors. In a cohort study, data for AEA and potential predictors of the percentage of cows inseminated in estrus (AIE) and pregnancies per AI (P/AI) for first service, and the percentage of cows pregnant by 150 DIM (P150) were collected from -21 to 49 DIM for lactating Holstein cows (n=886). The association between each reproductive outcome with calving season (cool, warm), calving-related events (yes, no), genomic daughter pregnancy rate (gDPR; high, medium, low), days in the close-up pen (ideal, not ideal), health disorder events (yes, no), rumination time (high or low CV prepartum and high or low increase rate postpartum), and milk yield (MY) by 49 DIM (high, medium, low) were evaluated in univariable and multivariable logistic regression models. Individual predictors (health disorders, gDPR, and MY) associated with the three reproductive outcomes in all models were used to group cows based on risk factors (RF; yes, n=535 or no, n=351) for poor reproductive performance. Specifically, cows were included in the RF group if any of the following conditions were met: the cow was in the high MY group, had low gDPR, or had at least one health disorder recorded. Cows were grouped into estrus groups during the VWP based on records of AEA (E-VWP, n=476 or NE-VWP, n=410). Finally, based on the combination of levels of AEA and RF cows were grouped into an estrus and no RF (E-NoRF, n=217), no estrus and RF (NE-RF, n=276), no estrus and no RF (NE-NoRF, n=134), and estrus and RF (E-RF, n=259) groups. Cows received AIE up to 31 d after the end of the VWP, and if not AIE, received timed AI after an Ovsynch plus progesterone protocol. Logistic and Cox proportional hazard regression compared differences in reproductive outcomes for different grouping strategies. The NoRF (AIE:76.9%; P/AIE:53.1%; P150:84.5%) and E-VWP (AIE:86.8%; P/AIE:44.8%; P150:82.3%) groups had more cows AIE, P/AI, and P150 than the RF (AIE:64.5%; P/AIE:34.9%; P150:72.9%) and NE-VWP (AIE:50.0%; P/AIE:38.9%; P150:72.1%) groups, respectively. When both factors were combined, the largest and most consistent differences were between the E-NoRF (AIE:91.3%; P/AIE:58.7%; P150:88.5%) and NE-RF groups (AIE:47.3%; P/AIE:35.8%; P150:69.5%). Compared with the whole population of cows or cows grouped based on a single factor, the E-NoRF and NE-RF groups had the largest and most consistent differences with the whole cow cohort. The E-NoRF and NE-RF group also had statistically significant differences of a large magnitude when compared with the remaining cow cohort after removal of the respective group. We conclude that combining data for AEA during the VWP with other predictors of reproductive performance could be used to identify groups of cows with larger differences in expected reproductive performance than if AEA and the predictors are used alone

Data and scripts from: Analyzing Trends in Americans with Disabilities Act Judicial Opinions Using Latent Dirichlet Allocation

Dataset is licensed under CC BY 4.0. Code is licensed under GNU GPLv3.These files contain data supporting all results reported in Mitchell, Analyzing Americans with Disabilities Act Judicial Opinions Using Latent Dirichlet Allocation. I found quantitative trends in judicial opinions regarding reasonable accommodations under the Americans with Disabilities Act since the passage of the Americans with Disabilities Act Amendments Act of 2008. Thousands of opinions were processed using Latent Dirichlet Allocation via MALLET. That output was further processed with regard to the venue and date in which the opinion was published

An Untraditional Approach to Traditional Fire Management: A Case Study of Australia's Arnhem Land Fire Abatement Northern Territory Organization

The Arnhem Land Fire Abatement Northern Territory organization is revolutionary in its approach to fire management, setting the tone for the future of wildfire management across the world.Wildfire is central to Australia’s natural landscape and history. The organization, Arnhem Land Fire Abatement Northern Territory (ALFA NT), combines traditional fire knowledge with scientific fire knowledge to create a system that challenges conventional wildfire management. My research explores three major questions: how are traditional fire knowledge and scientific fire knowledge being combined in this organization? What impact does knowledge combining have on the environment? What impacts does knowledge combining have on Indigenous communities? ALFA NT combines Indigenous fire wisdom with science in governance and burning methods. Knowledge combining improves environmental outcomes, but also raises concerns about its effect on traditional practices and Indigenous culture. ALFA NT is revolutionary in its approach to fire management, setting the tone for the future of wildfire management across the world

Heat Transfer in Intramedullary Rod in Tibia on Cold Day©

Many patients with orthopedic implants complain of pain associated with cold temperatures. This study aims to investigate how the temperature of the tissue in the lower leg is affected by the presence of a metal implant on a cold day. Two bioheat transfer models were made using eccentric cones and cylindrical solids to create our domain of interest, the region from the popliteal crease of the knee to the lateral malleolus at the ankle; the dimensions were based on average values for a 20 year old male, which was the demographic that most commonly received this implant [1]. The applicable parameters for modeling include heat conductivity, density, specific heat, and heat transfer coefficient. One model included a stainless steel rod placed in the medullary cavity of the tibia. The other model, which contains no implant, was used as a control. The models contain three boundary conditions: two thermal insulation boundaries at the top and bottom of the model, and a convective heat flux for the skin in contact with environmental air. The temperature profile of the lower leg was obtained in the model through a parasagittal cut plane evaluated 120 minutes after being exposed to an external temperature of 4.45°C. After running the model with a fine mesh (being the ideal mesh size) three points were taken just below the skin on the anterior side of the leg where thermoreceptors are located. The temperature vs. time graphs were evaluated at the three points between the two models, which found the temperature graph to be lower for the model with the implant. The temperature difference has a maximum of 0.33°C which, although slight, may stimulate the sensitive thermoreceptors that cause the perception of cool sensation. Sensitivity of the result to uncertainty was analyzed through varying the thermal conductivity of the rod’s stainless steel, convective heat transfer coefficient for the convective boundary condition, blood perfusion rates, and metabolic rates. The overall uncertainty of the cut-point temperature was found to be 4.68℃. Due to uncertainties in the blood flow, it is difficult to offer strong conclusions since this uncertainty is greater than the difference in temperatures with and without the implant. Our results do suggest, however, that the implant will not significantly affect the perception of cold sensation and that cold temperatures in the tissue surrounding the implant are unlikely to be the source of reported pain