Genetic engineering of cotton: current status and perspectives

Currently, several species of the genus Gossypium are cultivated in agriculture to produce fiber. Cotton has been cultivated for a long time, however, many aspects of its cultivation and processing are still researched. Writing about the cultivation of cotton, it is worth mentioning the fundamental problems of its processing. For example, the amounts of pesticides used in the cultivation of cotton are greater than for any other crop. Chemicals sprayed on cotton fields are washed away from the fields and, reaching the fresh water sources, pollute them, causing significant damage to the environment. Fortunately, such challenges can be solved by switching to the cultivation of transgenic cotton. Transgenic cotton has already brought many important environmental, social and economic benefits, including reduce of the used pesticides, indirectly increasing of yield, minimizing environmental pollution, reducing the labor force involved and economic costs.Today, the main methods of obtaining transgenic cotton lines are still agrobacterial transformation and biolistics. In recent years, however, innovative methods of transformation have also been developed. For example, the introduction of genetic material mediated by a pollen tube for the cultivation of commercial transgenic cotton is actively used in China. Although in recent decades transgenic lines resistant to diseases, abiotic stresses and with improved fiber quality have been obtained, the dominant position in the market of transgenic cotton is still occupied by lines of plants resistant to insects and herbicides. All the above indicates an insufficient degree of integration between institutes that introduce new advanced developments and agricultural industry.In this review the results of research involving the cultivation and genetic modification of cotton were collected and summarized. The main methods of genetic transformation of cultivated representatives of the genus Gossypium, both actively used at present and still under development, were considered. The most remarkable transgenic lines were also described, among which both those that have already entered agricultural industry and those that have only recently been obtained. Thus, the reader will be able to get a general idea of the current achievements in the field of cotton genetic modification

Entropy rate estimation and compression of biological sequences

Táto diplomová práca popisuje poznatky o biologických sekvenciách, princípy odhadu entropie a možnosti kompresie DNA sekvencií pomocou substitučných metód. Text obsahuje praktickú časť, kde sú využité kompresné algoritmy a praktický odhad entropie.This master thesis describes theoretical knowledge of biological sequences, principles entropy rate estimates and possibilities of compression of DNA sequences using the substitution methods. Thesis includes practical application of the compression algorithm and practical estimation of entropy.

Automatic Application-Specific Customization of Softcore Processor Microarchitecture, Masters Thesis, May 2006

Applications for constrained embedded systems are subject to strict runtime and resource utilization bounds. With soft core processors, application developers can customize the processor for their application, constrained by available hardware resources but aimed at high application performance. The more reconfigurable the processor is, the more options the application developers will have for customization and hence increased potential for improving application performance. However, such customization entails developing in-depth familiarity with all the parameters, in order to configure them effectively. This is typically infeasible, given the tight time-to-market pressure on the developers. Alternatively, developers could explore all possible configurations, but being exponential, this is infeasible even given only tens of parameters. This thesis presents an approach based on an assumption of parameter independence, for automatic microarchitecture customization. This approach is linear with the number of parameter values and hence, feasible and scalable. For the dimensions that we customize, namely application runtime and hardware resources, we formulate their costs as a constrained binary integer nonlinear optimization program. Though the results are not guaranteed to be optimal, we find they are near-optimal in practice. Our technique itself is general and can be applied to other design-space exploration problems

VidChapters-7M: Video Chapters at Scale

Segmenting long videos into chapters enables users to quickly navigate to the information of their interest. This important topic has been understudied due to the lack of publicly released datasets. To address this issue, we present VidChapters-7M, a dataset of 817K user-chaptered videos including 7M chapters in total. VidChapters-7M is automatically created from videos online in a scalable manner by scraping user-annotated chapters and hence without any additional manual annotation. We introduce the following three tasks based on this data. First, the video chapter generation task consists of temporally segmenting the video and generating a chapter title for each segment. To further dissect the problem, we also define two variants of this task: video chapter generation given ground-truth boundaries, which requires generating a chapter title given an annotated video segment, and video chapter grounding, which requires temporally localizing a chapter given its annotated title. We benchmark both simple baselines and state-of-the-art video-language models for these three tasks. We also show that pretraining on VidChapters-7M transfers well to dense video captioning tasks in both zero-shot and finetuning settings, largely improving the state of the art on the YouCook2 and ViTT benchmarks. Finally, our experiments reveal that downstream performance scales well with the size of the pretraining dataset. Our dataset, code, and models are publicly available at https://antoyang.github.io/vidchapters.html.Comment: Accepted at NeurIPS 2023 Track on Datasets and Benchmarks; Project Webpage: https://antoyang.github.io/vidchapters.html ; 31 pages; 8 figure

Zagrożenia systemów informatycznych e-administracji - szkodliwe oprogramowanie i ataki

The paper shows risks of IT systems: technical aspects of malicious software and attacks. In the Internet and a intranet. The article presents an overview of techniques and security recommendations for companies and offices for administration, databases and data processingW pracy zostały przedstawione zagrożenia systemów informatycznych: techniczne aspekty szkodliwego oprogramowania i ataki, zarówno w Internecie, jak i intranecie. Przegląd technik i zaleceń bezpieczeństwa systemów informatycznych dla firm i instytucji zajmujących się administracją oraz bazami i przetwarzaniem danyc

Bipol: A Novel Multi-Axes Bias Evaluation Metric with Explainability for NLP

We introduce bipol, a new metric with explainability, for estimating social bias in text data. Harmful bias is prevalent in many online sources of data that are used for training machine learning (ML) models. In a step to address this challenge we create a novel metric that involves a two-step process: corpus-level evaluation based on model classification and sentence-level evaluation based on (sensitive) term frequency (TF). After creating new models to detect bias along multiple axes using SotA architectures, we evaluate two popular NLP datasets (COPA and SQUAD). As additional contribution, we created a large dataset (with almost 2 million labelled samples) for training models in bias detection and make it publicly available. We also make public our codes.Comment: 12 pages, 4 image