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genetic code, class xii, cbse,

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GENETIC CODE
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Bacterial Identification and Classifications

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A botany file is similar to a chemistry practical file but specifically focuses on experiments and observations related to plants. It typically includes detailed descriptions of plant-related experiments, such as germination studies, growth experiments, tissue culture techniques, plant anatomy investigations, and ecological surveys. The file may contain records of plant specimens collected, their classification, characteristics, and ecological significance. Additionally, it may include diagrams, photographs, drawings, tables, and data analysis related to plant research. Like a chemistry practical file, a botany file serves as a documentation of practical work conducted in the field of botany and is often used for assessment and educational purposes.

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Cotton crops are vulnerable to a variety of sucking pests, which can severely impact plant health, yield, and fiber quality. These pests primarily feed on plant sap, extracting nutrients directly from the plant's vascular system. Here's a breakdown of some of the most significant sucking pests in cotton cultivation: Aphids: Cotton aphids or melon aphids can cause direct damage by sucking sap and indirect damage by secreting honeydew, which encourages sooty mold growth. This can interfere with photosynthesis and weaken the plant. Aphids can also transmit viral diseases. Whiteflies: Two species, the silverleaf whitefly and the bandedwinged whitefly, are particularly troublesome. They not only suck sap from the underside of leaves, causing yellowing and leaf drop, but their honeydew excretion promotes sooty mold and they can transmit several plant viruses. Thrips: While thrips can chew on plants, their primary damage to cotton is through sucking. They attack the cotton plant during its seedling stage, which can stunt growth and reduce vigor. Thrips are also capable of transmitting the Cotton Bud disease. Spider Mites: These are not insects but arachnids. Spider mites, such as the two-spotted spider mite, suck cell contents from the leaves, leading to speckled discoloration and potentially significant leaf loss if infestations are severe. Leafhoppers: Including various species, leafhoppers can cause direct damage through feeding, which results in leaf curling and stunted growth. They can also be vectors for plant diseases. Mealybugs: These pests are less common but can be problematic, especially in clustered planting conditions. They suck sap and secrete honeydew, which leads to sooty mold. Mealybugs can also spread viruses. Stink Bugs: Although primarily known for their chewing mouthparts, certain stink bugs can cause damage similar to sucking pests by injecting saliva into the plant and sucking out nutrients, leading to boll damage and stained lint. Management Strategies: Cultural Controls: This includes practices such as crop rotation, using resistant varieties, and managing planting and harvesting times to avoid peak pest populations. Biological Controls: Beneficial insects like lady beetles, lacewings, and predatory mites can naturally control sucking pest populations. Parasitic wasps also play a role in controlling aphid and whitefly populations. Chemical Controls: Insecticides may be used but should be chosen carefully to minimize resistance development and preserve beneficial insects. Systemic insecticides can be particularly effective against sucking pests. Integrated Pest Management (IPM): Combining multiple control strategies based on monitoring and thresholds to apply the most effective and environmentally sensitive approach. Effective management of sucking pests in cotton requires a thorough understanding of the pest species present, their life cycles, and the ecological balance of the field environment.

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Small size (20-300 nm) / bacteria (size measured in μm) Viral genome – single type of nucleic acid: DNA – dezoxyriboviruses RNA - riboviruses Totally dependant on living cells for all metabolic processes May infect humans, animals, plants, bacteria, fungi,parasites, insects Virion = viral corpuscle = elementary, infectious unit. Only visible by electron microscopy. Laboratory diagnosis of viral infections Methods: • Cytology • Electron microscopy • Cultivation • Detection of viral proteins • Serology • Molecular diagnosis (detection of genetic material i.e. nucleic acids) PPT prepared by Dr. Prince C P

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Monika Rani

Context. Determining the size distribution of asteroids is key to understanding the collisional history and evolution of the inner Solar System. Aims. We aim to improve our knowledge of the size distribution of small asteroids in the main belt by determining the parallaxes of newly detected asteroids in the Hubble Space Telescope (HST) archive and subsequently their absolute magnitudes and sizes. Methods. Asteroids appear as curved trails in HST images because of the parallax induced by the fast orbital motion of the spacecraft. Taking into account the trajectory of this latter, the parallax effect can be computed to obtain the distance to the asteroids by fitting simulated trajectories to the observed trails. Using distance, we can obtain the absolute magnitude of an object and an estimation of its size assuming an albedo value, along with some boundaries for its orbital parameters. Results. In this work, we analyse a set of 632 serendipitously imaged asteroids found in the ESA HST archive. Images were captured with the ACS/WFC and WFC3/UVIS instruments. A machine learning algorithm (trained with the results of a citizen science project) was used to detect objects in these images as part of a previous study. Our raw data consist of 1031 asteroid trails from unknown objects, not matching any entries in the Minor Planet Center (MPC) database using their coordinates and imaging time. We also found 670 trails from known objects (objects featuring matching entries in the MPC). After an accuracy assessment and filtering process, our analysed HST asteroid set consists of 454 unknown objects and 178 known objects. We obtain a sample dominated by potential main belt objects featuring absolute magnitudes (H) mostly between 15 and 22 mag. The absolute magnitude cumulative distribution logN(H > H0) ∝ αlog(H0) confirms the previously reported slope change for 15 < H < 18, from α ≈ 0.56 to α ≈ 0.26, maintained in our case down to absolute magnitudes of around H ≈ 20, and therefore expanding the previous result by approximately two magnitudes. Conclusions. HST archival observations can be used as an asteroid survey because the telescope pointings are statistically randomly oriented in the sky and cover long periods of time. They allow us to expand the current best samples of astronomical objects at no extra cost in regard to telescope time.

Hubble Asteroid Hunter III. Physical properties of newly found asteroids

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HotJupiters are amongthebest-studied exoplanets, but it is still poorly understood how their chemical composition and cloud properties vary with longitude. Theoretical models predict that clouds may condense on the nightside and that molecular abundances can be driven out of equilibrium by zonal winds. Here we report a phase-resolved emission spectrum of the hot Jupiter WASP-43b measured from 5–12µ 5–12µ 5–12µm with JWST’s Mid-Infrared Instrument (MIRI). 1524 ±35 1524 ±35 and 863±23 The spectra reveal a large day–night temperature contrast (with average brightness temperatures of 1524 ± 35 863 ±23 863 ±23Kelvin, respectively) and evidence for water absorption at all orbital phases. Comparisons with three-dimensional atmospheric models show that both the phase curve shape and emission spectra strongly suggest the presence of nightside clouds which become optically thick to thermal emission at pressures greater than ∼100mbar. The dayside is consistent with a cloudless atmosphere above the mid-infrared photosphere. Con3trary to expectations from equilibrium chemistry but consistent with disequilibrium kinetics models, methane is not detected on the nightside (2σ upper limit of 1–6 parts per million, depending on model assumptions).

Nightside clouds and disequilibrium chemistry on the hot Jupiter WASP-43b

Sérgio Sacani

We explore different scenarios to explain the chemical difference found in the remarkable giant-giant binary system HD138202+CD−3012303. For the first time, we suggest how to distinguish these scenarios by taking advantage of the extensive convective envelopes of giant stars. Methods. We carried out a high-precision determination of stellar parameters and abundances by applying a full line-by-line differential analysis on GHOST high-resolution spectra. We used the FUNDPAR program with ATLAS12 model atmospheres and specific opacities calculated for an arbitrary composition through a doubly iterated method. Physical parameters were estimated with the isochrones package and evolutionary tracks were calculated via MIST models. Results. We found a significant chemical difference between the two stars (∆[Fe/H]∼0.08dex), which is largely unexpected considering the insensitivity of giant stars to planetary ingestion and diffusion effects. We tested the possibility of engulfment events by using several different combinations of stellar mass, ingested mass, metallicity of the engulfed object and different convective envelopes. However, the planetary ingestion scenario does not seem to explain the observed differences. For the first time, we distinguished the source of chemical differences using a giant-giant binary system. By ruling out other possible scenarios such as planet formation and evolutionary effects between the two stars, we suggest that primordial inhomogeneities might explain the observed differences. This remarkable result implies that the metallicity differences that were observed in at least some main-sequence binary systems might be related to primordial inhomogeneities rather than engulfment events. We also discuss the important implications of finding primordial inhomogeneities, which affect chemical tagging and other fields such as planet formation. We strongly encourage the use of giantgiant pairs. They are a relevant complement to main-sequence pairs for determining the origin of the observed chemical differences in multiple systems.

Disentangling the origin of chemical differences using GHOST

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