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CEYHUN KIRIMLI

Calculus II Lecture Notes

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Bollworms are among the most damaging pests in cotton cultivation, affecting the bolls where the cotton fibers are formed. There are several species of bollworms, each capable of causing significant yield loss and quality degradation if not effectively managed. Here’s a detailed look at the primary bollworm species affecting cotton: Cotton Bollworm (Helicoverpa armigera): Also known as the corn earworm or the Old World bollworm, this pest is found in many regions around the world. It is highly polyphagous (feeds on many different plants) and poses a threat not only to cotton but also to maize, tomatoes, and legumes. The larvae bore into the cotton bolls, feeding on the developing seeds and fibers, which can lead to boll rot. Pink Bollworm (Pectinophora gossypiella): A significant pest of cotton, the pink bollworm larvae infest the cotton bolls, feeding on the seeds and lint. This can severely damage or destroy the bolls. In regions where pink bollworms are prevalent, they have been a major driver for the adoption of genetically engineered Bt cotton, which expresses a bacterium gene toxic to certain insects. Tobacco Budworm (Heliothis virescens): Closely related to the cotton bollworm, the tobacco budworm primarily attacks tobacco but is also a common pest in cotton. It primarily damages the flowers and bolls of the cotton plant. Differentiating between the tobacco budworm and the cotton bollworm based on appearance can be challenging, but it is crucial for effective management. American Bollworm (Helicoverpa zea): Known in some regions as the corn earworm, it is similar in behavior to Helicoverpa armigera and poses a threat to a variety of crops, including cotton. The larvae attack the cotton bolls, leading to direct damage to the cotton lint and seeds. Management Strategies: Cultural Controls: Crop rotation, destruction of crop residues, and deep plowing can help break the pest’s life cycle. Timing of planting can also be adjusted to avoid peak pest infestation. Biological Controls: Natural enemies like Trichogramma wasps, which parasitize bollworm eggs, and predators such as lacewings and ladybugs can be encouraged. Bacillus thuringiensis (Bt) products can also be sprayed, which are particularly effective against young larvae. Chemical Controls: Insecticides may be required when infestation levels exceed economic thresholds. However, resistance management must be considered, alternating modes of action to avoid developing resistance. Genetic Approaches: Bt cotton, genetically modified to express Bacillus thuringiensis toxin, has been highly effective in controlling bollworms and has dramatically reduced the reliance on chemical insecticides. Monitoring and Scouting: Regular field scouting and using pheromone traps to monitor adult populations can help in timely and targeted application of control measures. The effective management of bollworms often requires an integrated approach

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Context. WASP-76 b has been a recurrent subject of study since the detection of a signature in high-resolution transit spectroscopy data indicating an asymmetry between the two limbs of the planet. The existence of this asymmetric signature has been confirmed by multiple studies, but its physical origin is still under debate. In addition, it contrasts with the absence of asymmetry reported in the infrared (IR) phase curve. Aims. We provide a more comprehensive dataset of WASP-76 b with the goal of drawing a complete view of the physical processes at work in this atmosphere. In particular, we attempt to reconcile visible high-resolution transit spectroscopy data and IR broadband phase curves. Methods. We gathered 3 phase curves, 20 occultations, and 6 transits for WASP-76 b in the visible with the CHEOPS space telescope. We also report the analysis of three unpublished sectors observed by the TESS space telescope (also in the visible), which represents 34 phase curves. Results. WASP-76 b displays an occultation of 260±11 and 152±10 ppm in TESS and CHEOPS bandpasses respectively. Depending on the composition assumed for the atmosphere and the data reduction used for the IR data, we derived geometric albedo estimates that range from 0.05 ± 0.023 to 0.146 ± 0.013 and from <0.13 to 0.189 ± 0.017 in the CHEOPS and TESS bandpasses, respectively. As expected from the IR phase curves, a low-order model of the phase curves does not yield any detectable asymmetry in the visible either. However, an empirical model allowing for sharper phase curve variations offers a hint of a flux excess before the occultation, with an amplitude of ∼40 ppm, an orbital offset of ∼−30◦ , and a width of ∼20◦ . We also constrained the orbital eccentricity of WASP-76 b to a value lower than 0.0067, with a 99.7% confidence level. This result contradicts earlier proposed scenarios aimed at explaining the asymmetry observed in high-resolution transit spectroscopy. Conclusions. In light of these findings, we hypothesise that WASP-76 b could have night-side clouds that extend predominantly towards its eastern limb. At this limb, the clouds would be associated with spherical droplets or spherically shaped aerosols of an unknown species, which would be responsible for a glory effect in the visible phase curves.

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Presenter: Chen Li, PhD. Professor, Department of Computer Science, University of California Irvine Abstract Many data analytics projects have collaborators with complementary backgrounds, including biologists, bioinformaticians, computer scientists, and AI/ML experts. Many of them have limited experience to code, set up a computing infrastructure, and use MLmodels. Existing tools and services, such as email attachments, GitHub, and Google Drive are inefficient for sharing data and analyses. In this talk, we present an open source system called Texera that provides a cloud computing platform for collaborators to share data and analyses as workflows. After seven years of development, the system has a rich set of powerful features, such as shared editing, shared execution, version control, commenting, debugging, user-defined functions in multiple languages (e.g., Python, R, Java), and support of state-of-the-art AI/ML techniques. Its backend parallel engine enables scalable computation on large data sets using computing clusters. We will show a demo of the system, and present our vision supported by a recent NIH award, dkNET(NIDDK Information Network, https://dknet.org), to serve the diabetes, endocrinology, and metabolic diseases research communities through the FAIR sharing of data and knowledge. Resource link: https://github.com/Texera/texera Upcoming webinars schedule: https://dknet.org/about/webinar

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The computation of anti-derivatives is just an in-tellectual challenge, we know how to take deriv-atives, but … can we invert the process? We call this Computing the indefinite integral . In the last presentation we have seen a few indefinite integrals (we called them bricks), but they did not include the anti-derivative of many functions! We are going to try and do better !

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