Miracle-dz/UniFAR-FTUs huggingface dataset:
Co-Optimizing Post-Contingency Transmission Switching in Power System Operation Planning

Proença Rosa Saavedra, Raphael Augusto; Street de Aguiar, Alexandre (Advisor). Co-Optimizing Post-Contingency Transmission Switching in Power System Operation Planning. Rio de Janeiro, 2019. 71p. Dissertação de Mestrado – Departamento de Engenharia Elétrica, Pontifícia Universidade Católica do Rio de Janeiro. Transmission switching has been previously shown to offer significant benefits to power system operation, such as cost savings and reliability enhancements. Within the context of co-optimized electricity markets for energy and reserves, this work addresses the co-optimization of post-contingency transmission switching in power system operation planning. The proposed models for unit commitment and economic dispatch differ from existing formulations due to the joint consideration of three major complicating factors. First, transmission switching actions are considered both in the preand post-contingency states, thereby requiring binary post-contingency variables. Secondly, generation scheduling and transmission switching actions are co-optimized. In addition, the time-coupled operation of generating units is precisely characterized. The proposed models are formulated as challenging mixed-integer programs for which the off-the-shelf software customarily used for simpler models may lead to intractability even for moderatelysized instances. As a solution methodology, we present enhanced versions of an exact nested column-and-constraint generation algorithm featuring the inclusion of valid constraints to improve the overall computational performance. Numerical simulations demonstrate the effective performance of the proposed approach as well as its economic and operational advantages over existing models disregarding post-contingency transmission switching.
A Lightweight Hybrid Representation for Virtual Complex Scenes

While virtual scenes with complex geometries and highresolution physically based rendering(PBR) material textures are capable of representing details, they often occupy a large amount of memory and require significant manual editing by artists. In this paper, we introduce a new framework for representing virtual scenes more efficiently. Our framework utilizes a lightweight hybrid representation that combines traditional polygon-based meshes and material textures with learned neural textures. By using simplified geometries and lower-resolution PBR material textures, our representation achieves a compact size while maintaining the freedom for user-friendly scene editing of materials and illuminations. Additionally, we have designed a hybrid rendering pipeline to render the lightweight representation with ray-traced visual quality at real-time frame rates. Our approach reduces memory requirements, eliminates the need for manual editing, and is easy to train. We demonstrate the effectiveness of our framework on a variety of virtual complex scenes.
Pairwise Feature Learning for Unseen Plant Disease Recognition

With the advent of Deep Learning, people have begun to use it with computer vision approaches to identify plant diseases on a large scale targeting multiple crops and diseases. However, this requires a large amount of plant disease data, which is often not readily available, and the cost of acquiring disease images is high. Thus, developing a generalized model for recognizing unseen classes is very important and remains a major challenge to date. Existing methods solve the problem with general supervised recognition tasks based on the seen composition of the crop and the disease. However, ignoring the composition of unseen classes during model training can lead to a reduction in model generalisation. Therefore, in this work, we propose a new approach that leverages the visual features of crop and disease from the seen composition, using them to learn the features of unseen crop-disease composition classes. We show that our proposed method can improve the classification performance of these unseen classes and outperform the state-of-the-art in the identification of multiple crop-diseases.
Metric Temporal Description Logics with Interval-Rigid Names

In contrast to qualitative linear temporal logics, which can be used to state that some property will eventually be satisfied, metric temporal logics allow us to formulate constraints on how long it may take until the property is satisfied. While most of the work on combining description logics (DLs) with temporal logics has concentrated on qualitative temporal logics, there is a growing interest in extending this work to the quantitative case. In this article, we complement existing results on the combination of DLs with metric temporal logics by introducing interval-rigid concept and role names. Elements included in an interval-rigid concept or role name are required to stay in it for some specified amount of time. We investigate several combinations of (metric) temporal logics with AℒC by either allowing temporal operators only on the level of axioms or also applying them to concepts. In contrast to most existing work on the topic, we consider a timeline based on the integers and also allow assertional axioms. We show that the worst-case complexity does not increase beyond the previously known bound of 2-ExpSpace and investigate in detail how this complexity can be reduced by restricting the temporal logic and the occurrences of interval-rigid names.
Welfare-to-Work: Which Policies Work and Why?

THIS LECTURE CONSIDERS the arguments behind the expansion in welfare to work programmes that occurred over the last decade and reviews the effectiveness of alternative approaches to enhancing labour-market attachment and earnings among the low skilled. It concerns the ‘iron triangle’ of welfare reform—that is the three, often conflicting, goals: raising the living standards of those on low incomes; encouraging work and economic self-sufficiency; and keeping government costs low. Many different policies can be cast in terms of these broad aims, albeit with different weights attached to each of the goals. In the UK there are active labour-market programmes like the New Deal and there are also financial incentive programmes like the Working Families Tax Credit (WFTC). Although the latter are often classed as welfare policies and the former as active labour-market policies, both are motivated by similar concerns over low incomes and low labour-market attachment and share many similar design features. The key organising idea in this lecture is to provide an integrated view of the way the wide array of ‘welfare to work’ and ‘make work pay’ policies affect the earnings, incomes, and incentives of
THE EFFECT OF TAM AND ATTITUDES TOWARD ADVERTISING ON INTENTION TO USE QRIS

QRIS is the Quick Response Code Indonesian Standard, which is a national QR code standard to facilitate QR code payments in Indonesia, which was launched by Bank Indonesia and the Indonesian Payment System Association (ASPI) in 2019. This research was conducted to look at the effect of the Technology Acceptance Model (TAM), which consists of perceived ease of use and perceived benefits, as well as additional attitude towards advertising variables on people's intention to use QRIS. The population in this study are all Indonesian citizens who have seen advertisements for using QRIS. The research minimum sample is 120 samples using purposive sampling method. Data analysis technique using SEM-PLS. The results of this study indicate that TAM and attitudes towards advertising have a positive and significant effect on the intention to use QRIS.
University of Southern Denmark Comprehensive Genomic Profiling of Androgen-Receptor-Negative Canine Prostate Cancer

Canine carcinomas have been considered natural models for human diseases; however, the genomic profile of canine prostate cancers (PCs) has not been explored. In this study, 14 PC androgen-receptor-negative cases, 4 proliferative inflammatory atrophies (PIA), and 5 normal prostate tissues were investigated by array-based comparative genomic hybridization (aCGH). Copy number alterations (CNAs) were assessed using the Canine Genome CGH Microarray 4 × 44K (Agilent Technologies). Genes covered by recurrent CNAs were submitted to enrichment and cross-validation analysis. In addition, the expression levels of TP53, MDM2 and ZBTB4 were evaluated in an independent set of cases by qPCR. PC cases presented genomic complexity, while PIA samples had a small number of CNAs. Recurrent losses covering well-known tumor suppressor genes, such as ATM, BRCA1, CDH1, MEN1 and TP53, were found in PC. The in silico functional analysis showed several cancer-related genes associated with canonical pathways and interaction networks previously described in human PC. The MDM2, TP53, and ZBTB4 copy number alterations were translated into altered expression levels. A cross-validation analysis using The Cancer Genome Atlas (TCGA) database for human PC uncovered similarities between canine and human PCs. Androgen-receptor-negative canine PC is a complex disease characterized by high genomic instability, showing a set of genes with similar alterations to human cancer.
3. Looking for Lexical Signatures in Gomorrah

Gomorrah is an Italian crime drama TV series that has been appreciated worldwide, being sold in 190 countries, despite its wide use of Neapolitan dialect, hardly understandable without the use of subtitles even for most Italians. Scholars immediately approached the study of this serial phenomenon, analysing it from different points of view, framing it within the broader context of studies on the new Italian television and its serial products. Our approach to Gomorrah , taking these elements into account, adds a new perspective that concerns character recognition, an emerging branch of research, to associate dialogues with characters and identify the verbal features of characters. We have then chosen Gomorrah as a challenging dataset to perform character recognition. We rely on the transcripts of the series after a pre-processing stage to standardize the lexicon despite the vagaries of dialect and remove stopwords. A machine learning approach, based on a selection of tools, is then employed to identify characters from the lexicon they employ. The problem is approached as a multi-class classification scheme. We compare several representations of texts, including the simple one-hot encoding and more advanced embedding techniques. The results are presented through a confusion matrix, which can also serve to identify similarities in the linguistic profiles of characters.
A higher order Root-MUSIC and its real polynomial form

This paper presents a real polynomial form of the popular Root-MUSIC direction-of-arrival (DOA) algorithm. To transform Root-MUSIC into real coefficients polynomial with the help of conformal transformation, we propose a higher order Root-MUSIC whose variable is only defined on the unit upper semicircle. Furthermore, this paper also improves the results obtained by J.Selva in 2005.
PAPER PRESENTED AT INTERNATIONAL WORKSHOP ON INCREASING WHEAT YIELD POTENTIAL, CIMMYT, OBREGON, MEXICO, 20–24 MARCH 2006 Genetic progress in yield potential in wheat: recent advances and future prospects

Knowledge of the changes in physiological traits associated with genetic gains in yield potential is essential to improve understanding of yield-limiting factors and to inform future breeding strategies. Recent advances in genetic yield potential and associated physiological changes in wheat (Triticum aestivum L.) are reviewed. Genetic gains in yield potential worldwide have been both positively correlated with harvest index (HI) and above-ground dry matter (AGDM), with more frequent reports of yield progress associated with biomass since about 1990. It is concluded that an important aim of future breeding will be the increase of biomass production while maintaining the present values of HI. In winter wheat recent biomass progress has been positively associated with pre-anthesis radiation-use efficiency (RUE) and water-soluble carbohydrate (WSC) content of stems at anthesis. Present results in two doubled-haploid (DH) populations show a positive linear relationship between stem WSC and grain yield in the UK environment. Results from various investigations worldwide in recent years have demonstrated that biomass increases have been associated with particular introductions of alien genes into wheat germplasm, e.g. the 1BL.1RS wheat-rye translocation and the 7DL.7Ag wheat-Agropyron elongatum translocation. Present results confirm a positive effect of 1BL.1RS on harvest biomass in two DH populations in the UK. The future prospects for identifying physiological traits to raise yield potential are considered with particular reference to winter wheat grown in northwestern Europe. It is proposed that optimized rooting traits, an extended stem-elongation phase, greater RUE, greater stem WSC storage and optimized ear morphology will be important for breeding progress in yield potential in future years.
International entrepreneurship intention of Omani youths: an empirical causal approach

ABSTRACT This paper aims to investigate international entrepreneurship from a causal perspective for the Omani youths’ case study. Anchored on the Theory of Planned Behaviour (TPB), the empirical study assessed the influence of familiarity with globalization, attitude towards globalization, buying behaviour, and social norms about international trade on Omani's intention to engage in international entrepreneurship. The sample consisted of 1359 Omani millennials and Generation-z, who participated in a survey analysed using structural equation. The results highlighted the significant role of personal and social drivers on Omanis’ international entrepreneurial intention. The results confirmed the suitability of the TPB for determining international entrepreneurship intention and have interesting implications for all working towards the facilitation and development of international entrepreneurship as a career solution to deal with an increasing unemployment rate in the region.
To Explore the Mechanism of Hawthorn in the Intervention of Hyperlipidemia Based on the Gene Expression Omnibus and Network Pharmacology

A common clinical treatment for hyperlipidemia in China is hawthorn, a traditional Chinese herb. However, few researches have been done on its active ingredients and their possible mechanisms for treating hyperlipidemia. The active chemical constituents of hawthorn were obtained from the encyclopedia of traditional Chinese medicine, the bioavailability and druglikeness properties of each active ingredient of hawthorn were analyzed using SwissADME and their possible targets of action were predicted using SwissTargetPrediction and PharmMapper. Then, we used the Gene Expression Omnibus-related gene microarray data to mine the differentially expressed genes for hyperlipidemia. Meanwhile, we collected relevant targets of hyperlipidemia through the DrugBank, Online Mendelian Inheritance in Man, GeneCards, DisGeNET and Therapeutic Target Database. Based on this data, a component-target-disease pathway and a protein-protein interaction networks were constructed using search tool for the retrieval of interacting genes/proteins. Finally, Metascape was systematically used to analyze the targets of hawthorn intervention in hyperlipidemia. A total of 8 active components and 312 hawthorn targets were gathered and 343 prospective targets associated with hyperlipidemia were predicted, 25 of which shared targets with hawthorn-related targets. Gene ontology enrichment analysis revealed that the mechanism of action of hawthorn in intervention of hyperlipidemia lies in the regulation of lipid metabolism, nutrition level, hormone level and cholesterol transport process. The Kyoto encyclopedia of genes and genomes enrichment analysis revealed that the peroxisome proliferator activated receptor signaling pathway contained the majority of the core targets. Molecular docking verified that hawthorn could bind closely to the core targets. According to the findings of network pharmacology and enrichment analysis, we predicted that the main active components of hawthorn to intervene in hyperlipidemia are epicatechin, officinalic acid and quercetin, which mainly intervene in hyperlipidemia through the peroxisome proliferator activated receptor signaling pathway.
Іn vitro ANTILEUKEMIC ACTIVITY OF Euphorbia echinus EXTRACT

Aim . Cancer continues to pose a serious threat to human health. Euphorbia plants are rich in phenolics, aromatic esters, steroids and several bioactive compounds. Studies have shown the presence of a large number of bioactive compounds in E. echinus including flavonoids, phenolics, and proanthocyanins. Method . There it was investigated cytotoxic effects of E. echinus methanolic extract on K562, HL60, Ishikawa, Raji and SH-SY5Y cells.
Electron spin relaxation in cryptochrome-based magnetoreception

The radical pair model of the avian magnetoreceptor relies on long ‐ lived electron spin coherence. Dephasing, resulting from interactions of the spins with their fluctuating environment, is generally assumed to degrade the sensitivity of this compass to the direction of the Earth's magnetic field. Here we argue that certain spin relaxation mechanisms can enhance its performance. We focus on the flavin ‐ tryptophan radical pair in cryptochrome, currently the only candidate magnetoreceptor molecule. Correlation functions for fluctuations in the distance between the two radicals in Arabidopsis thaliana cryptochrome 1 were obtained from molecular dynamics simulations and used to calculate the spin relaxation caused by modulation of the exchange and dipolar interactions. We find that intermediate spin relaxation rates afford substantial enhancements in the sensitivity of the reaction yields to an Earth ‐ strength magnetic field. Supported by calculations using toy radical pair models, we argue that these enhancements could be consistent with the molecular dynamics and magnetic interactions in avian cryptochromes.
Scholarship & Creative Works @ Digital UNC Scholarship & Creative Works @ Digital UNC

Valproic acid (VPA) is used worldwide to treat epilepsy, migraine headaches and bipolar disorder. However, VPA is teratogenic and in utero exposure can lead to congenital malformations. Using inbred C57BL/6J (B6) and DBA/2J (D2) mice, we asked whether genetic variation could play a role in susceptibility to VPA teratogenesis. While B6 fetuses were more susceptible than D2 fetuses to digit and vertebral malformations, D2 fetuses were more susceptible to rib malformations. In a reciprocal cross between B6 and D2, genetically identical F 1 mice carried in a B6 mother had a greater percentage of vertebral malformations following prenatal VPA exposure than F 1 mice carried in a D2 mother. This reciprocal F 1 difference is known as a maternal effect and shows that maternal genotype/uterine environment is an important mediator of VPA teratogenecity. VPA is a histone deacetylase inhibitor and it is possible that the differential teratogenesis in B6 and D2 is due to strain differences in histone acetylation. We observed strain differences in acetylation of histones H3 and H4 in both embryo and placenta following in utero VPA exposure, but additional studies are needed to determine the significance of these changes in mediating teratogenesis. Our results provide additional support that genetic factors, both maternal and fetal, play a role in VPA teratogenesis. Lines of mice derived from B6 and D2 will be a useful model for elucidating the genetic architecture underlying susceptibility to VPA teratogenesis.
Adopting Self-Supervised Learning into Unsupervised Video Summarization through Restorative Score.

In this paper, we present a new process for creating video summaries in an unsupervised manner. Our approach involves training a transformer encoder model to reconstruct missing frames in a video in a self-supervised way using the partially masked video as input. We then introduce an algorithm that utilizes the above-trained encoder to generate an importance score for each frame. Such frame importance scores are used to create the summary of the video. We show that the reconstruction loss of the model for a video with masked frames correlates with the representativeness of the remaining frames in the video. We validate the effectiveness of our approach on two benchmark datasets of TVSum and SumMe. We demonstrate that it outperforms state-of-the-art (SOTA) methods. Additionally, our approach is more stable during the training process compared to SOTA techniques based on generative adversarial learning. Our source code is publicly available1.
Measurement of the ratio of branching fractions

The interest to the rare radiative decays of the B-mesons at LHCb is mostly aroused due to the measurement of the photon polarization in the B s 0 → ϕγ decay, which may provide a sensitive probe for the Standard Model. The LHCb experiment has started to take data at the energy of √s = 7 TeV in 2010 and the current paper presents the result of the studies of the two rare radiative decays B 0 → K * γ and B s 0 → ϕγ with 340 pb −1 of data taken in the first half of 2011. With this data we have a preliminary measurement of = 1.52±0.14( stat. )±0.10( syst. )±0.12( f s /f d ) and assuming the measured value of ( B 0 → K * γ ) = (4.33 ± 0.15) × 10.5 we infer ( B s 0 → ϕγ ) = (2.8 ± 0.5) × 10 −5 [1]
The effect of students’ attitudes and concerns on statistical concepts performance: A SEM approach

The purpose of this study was to investigate how the attitudes and concerns of higher learning students made an impact on their performance in the fundamental concepts of the statistics course. Despite being classified as one of the important areas of scientific, industrial, or social problems, students generally perceive statistics as a challenging course to understand. This negative perception leads to a set of complex emotional reactions that may cause great discomfort, resulting in negative consequences, such as anxiety. A sample of 248 UiTM Pahang Branch students, enrolled in a basic statistics course, was randomly selected using a stratified sampling technique. This study employed Structural Equation Modeling (SEM) method to assess the linear relationship model between students' attitudes and concerns, and their performance in statistics examinations. The findings indicated that both students' attitudes and concerns showed a significant negative influence on their performance in statistics examinations, resulting in poor academic performance. Hence, to foster students' academic success in statistics courses, it is essential to cultivate a positive attitude and enhance their confidence levels.
Prokaryotic diversity of Boiling Springs Lake, Lassen Volcanic National Park

iii ACKNOWLEDGEMENTS.v TABLE OF CONTENTS.vi LIST OF TABLES.ix LIST OF FIGURES.x CHAPTER 1: BACKGROUND AND OBJECTIVES.1 Overview.1 Site Description.2 Thermoacidophilic Life.6 Cultivation vs. Culture Independent Investigation.10 Molecular Estimates of Diversity.12 CHAPTER 2: CLONE LIBRARY AND PHYLOGENY.22 Introduction.22 Methods.24 Sample Collection.24 Acridine Orange Direct Counts (AODC). 26 Nucleic Acid Extractions.26 Creation of Site D rRNA Gene Clone Library.28 Sequence Analysis and Phylogeny Estimation.29 Results.31