Miracle-dz/UniFAR-FTUs huggingface dataset:
Remote Sensing Surveillance of NO2, SO2, CO, and AOD along the Suez Canal Pre- and Post-COVID-19 Lockdown Periods and during the Blockage

This study investigates the impact of the COVID-19 pandemic and the Ever Given ship blockage on the air quality in Suez Canal region. Nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and aerosol optical depth (AOD) were studied, and data were obtained from satellite instruments. The study compared monthly average data for 2020, 2021, and 2022 with a baseline period of 2017–2019 to investigate the pandemic’s effect. The study also analyzed the corresponding period of the canal blockage to identify its impact on air pollution levels. The pandemic had a significant role in decreasing NO2 by 2.5 × 1014 molecule/cm2 and SO2 by 0.05 DU due to reduced car traffic and industrial activities. A reduction in AOD by 20% and CO concentration in the range from 3.5% to 4.7% was reported in early 2020. During the blockage, NO2 and SO2 levels decreased by 14.4% and 66.0%, respectively, while CO and AOD index increased by 12.68% and 51.0%, respectively. The study concludes that the containment measures during the pandemic had a positive impact on the environment, which shows how the reduction in the anthropogenic activities, especially industrial and transportation activities, have improved the air quality. Thus, stricter actions are needed to protect the environment; for example, the transition towards the using of electric vehicle is necessary, which is part of Egypt’s strategy to transition towards a green economy. The government should also adopt a policy to trade carbon emissions reduction certificates to help reduce air pollution.
Alternative algorithms for computing generic μ∗-sequences and local Euler obstructions of isolated hypersurface singularities

A new algorithm is introduced for computing [Formula: see text]-sequences of isolated hypersurface singularities. It is shown that the new algorithm results in better performance, compared to our previous algorithm that utilizes parametric local cohomology systems, in computation speed. Furthermore, it can be used to compute local Euler obstruction of a hypersurface with an isolated singularity. The key idea of the new algorithm is computing standard bases in a local ring over a field of rational functions.
Detection of noisy rectangular targets in high spatial resolution images

ABSTRACT Human-related targets in high-spatial-resolution images often present rectangular shapes, such as most buildings, farmland, etc. However, their edges often encounter bending or missing parts as well as redundancy, making them difficult to detect by current breaking-assembling strategies that initially detect line segments and then gather them into potential rectangles. We propose a rectangle-detection method that uses a whole-object detection strategy that detects rectangles as integrated units to avoid these problems. Comparison experiments with a state-of-the-art method on both synthesized and high-spatial-resolution images indicate that our method performs well in detecting rectangles both in accuracy and time-cost aspects, especially when the edges are noisy.
Pengaruh Literasi Keuangan, Persepsi Kredibilitas Dan Persepsi Manfaat Terhadap Minat Penggunaan E-Money GoPay Pada Masa Pandemi Covid-19

Penelitian ini bertujuan untuk mengetahui pengaruh Literasi keuangan, Persepsi Kredibilitas dan Persepsi Manfaat Terhadap Minat Penggunaan E-money GoPay Pada Masa Pandemi Covid-19. Penelitian ini merupakan penelitian kuantitatif. Sumebr data yang digunakan terdiri dari data primer dan data sekunder. Populasi dalam penelitian ini adalah masyarakat pengguna GoPay di Kabupaten Buleleng. Metode pengumpulan data menggunakan kuisioner dengan google form dan diukur menggunakan skala likert. Teknik pengambilan sampel menggunakan metode purposive sampling dengan 270 responden. Metode analisis data dalam penelitian ini menggunakan analisis regresi berganda diolah dengan bantuan program SPSS versi 22. Hasil penelitian ini menunjukkan bahwa literasi keuangan berpengaruh positif signifikan terhadap minat penggunaan E-money GoPay pada masa pandemi covid-19. Persepsi kredibilitas berpengaruh positif signifikan terhadap minat penggunaan E-money GoPay pada masa pandemi covid-19. Persepsi manfaat berpengaruh positif signifikan terhadap minat penggunaan E-money GoPay pada masa pandemi covid-19.
Playing for and against the microphone : the theatrical soundstage, the cinematic meeting interface

This article argues for an analogy between the early talkies and the video telephony software-based theatre productions that have proliferated since the outbreak of the COVID-19 pandemic: both the crude sound equipment employed for the late 1920s films and the static streaming and recording devices used to make online theatre/theatre online productions require the performer's close proximity to the microphone. The latter kind of artwork's 'user interface stage' is the site of a paradox, simultaneously fragmenting the spacetime of a written scene and reconstituting the fragments in alternately theatrical and cinematic fashions. I use Mint Theatre's The Gin Chronicles in New York (2020) as a source of examples of this innate contradiction's potential to transcend the notion of medium specificity (and its 'betrayal') that surrounded the emergence of the talkie and to help forge a new model for the Foucauldian heterotopia.
Self-Attention-Based Uplink Radio Resource Prediction in 5G Dual Connectivity

Mobile communication technology is evolving rapidly and becoming increasingly ubiquitous, thereby increasing the demand for uplink data-intensive applications (e.g., personal broadcasting and live augmented/virtual reality videos). Recently, to facilitate a cost-effective and smooth transition from 4G to 5G networks, most carriers leverage existing 4G infrastructures using a dual connectivity (DC) feature. DC increases uplink throughput and mobility robustness; however, it also causes unprecedented dynamic fluctuations in radio channels due to the coverage discrepancy between 4G and 5G networks. Thus, in this article, we propose a self-attention-based deep learning model to predict uplink radio resources in 5G DC. We trained the proposed model on commercial 5G DC traffic data from three major carriers in South Korea and obtained an average prediction accuracy of 95.08% under various mobility and cell-load conditions. The proposed model explains the rationale for the obtained predictions by highlighting the parts of the input time-series data that are important to realize accurate prediction. We also demonstrate the usability of the proposed model using a network emulator based on real-world 5G trace data. Extensive evaluations demonstrate that the existing congestion control algorithms can achieve excellent performance when used with the proposed model.
Field Coupling-Based Image Filter for Sand Painting Stylization

Sand painting is a very new and popular performance art technique, and it has important meaning for the artistic creation. Computer-aided sand painting is now in the ascendant, whose fully automated mechanism is still an attractive challenge. Image data field, inspired from short-range nuclear force in physics, is introduced into sand painting stylization. With preserving edges and features, a fully automatic image filter pipeline based on image field coupling is proposed, which consists of three main steps, including image data field generating, multiscale field coupling, and additional details optimizing. The visual comparisons indicate that the proposed pipeline and image filter are feasible and effective, and sand painting-like artistic images can be produced by using multiscale field coupling. The qualities of various rendering images are also investigated from the perspective of feature similarity measures. The quantitative and qualitative results suggest that the field coupling-based filter is appropriate for sand painting stylization, and the time cost is satisfied for practice applications. Generally, the proposed method provides a reference for automatic creation of computer-aided sand painting art.
Automation of Optimization Synthesis for Modular Technological
Equipment

Technological equipment design based on functionally modular methods is widely used in various technical fields. The designed object can be a technological machine, a production line, or a manufacturing complex. Special attention is paid to the optimization of its structure. The sequence of performing all stages of the optimization synthesis problem is presented in the article. To find a solution to this task, the developer should apply the complete or directed search of acceptable structure options and determine the best one using some optimization criteria to evaluate their quality. It can be simple enough if the designed technical system structure consists of no more than several elements. For example, if the number of alternative elements options is several dozen, it takes much time to accomplish the search correctly. Thus, the greater the number of components considered, the more difficult it is to do all the necessary calculations manually. In this case, machine resources should be involved. This scientific work aims to identify procedures of optimization synthesis that can be automated. Also, appropriate software has to be developed. Our computer program is based on the algorithm of a complete search of all options of the technical system structure. It can process an extensive array of input data and produce all possible and logically permissible results in the form the designer can analyze using the Pareto method to choose the best one. This software can be used for any technical system with a modular structure.
Calreticulin Mutations in Myeloproliferative Neoplasms Patients Diagnosed in UKM Medical Centre

Introduction: Calreticulin (CALR) mutations are one of the molecular markers that has been incorporated for the diagnosis of myeloproliferative neoplasms (MPN) in the revised 2017 WHO Classification of Haematopoietic and Lymphoid Tumors. This study was performed to determine the prevalence of CALR mutations in patients with MPN diagnosed in UKMMC and to compare their demographics plus laboratory features with other MPN patients. Meth- ods: A total of 59 MPN patients who tested negative for JAK2V617Fmutation were selected and 21 MPN patients positive for JAK2V617F were included as controls. Screening for CALR exon 9 was done by multiplex polymerase chain reaction (PCR) followed by Sanger sequencing. Results: A total of six JAK2 V617F negative MPN samples were found to be positive for CALR mutations. Out of these six, three patients with CALR mutations were of type I mutation, two were type II while one was a mutation in the stretch III region. None of the twenty one JAK2 V617F positive MPN samples were positive for CALR mutation. Clinical phenotypes for those positive for CALR were restricted to Essential Thrombocythemia (ET), Primary Myelofibrosis (PMF) and one case of atypical Chronic Myeloid Leukaemia (CML). Conclusion: CALR mutations constituted 10.16% from the MPN patients who were negative for JAK2V617F mutation with no significant differences in platelet counts, hemoglobin (Hb), hematocrit and white cell counts as compared to MPN patients with JAK2 V617F mutations. Testing for CALR mutations among those who are negative for JAK2V617F within Malaysian population maybe worthwhile and require larger scale studies.
Probabilistic analysis method of turbine blisk with multi-failure modes by two-way fluid-thermal-solid coupling

This study develops multi-extremum response surface method (MERSM) for the probabilistic analysis of aeroengine turbine blisk with the coexistence of many failure modes by considering two-way fluid-thermal-solid coupling under complex working condition. The mathematical model of MERSM was established with respect to the random input variables of inlet temperature, inlet velocity, density of material, and rotor speed, and the output responses of the maximum values of deformation, stress, and strain. The comprehensive probabilistic analysis of turbine blisk was completed based on MERSM. The results demonstrate that the comprehensive reliability degree of turbine blisk is 0.9944 when the allowable deformation, stress, and strain are 2.6 × 10−3 m, 1.26 × 109 Pa, and 6.75 × 10−3 m/m, respectively. The main factors influencing the comprehensive reliability degree of turbine blisk are rotor speed and gas temperature. The secondary factors are inlet velocity and density of material. As revealed from the comparison of methods, MERSM improves the computational speed and efficiency with the guarantee of accuracy. The efforts of this paper provide a promising approach for the nonlinear transient reliability analysis of complex structures with multi-failure modes and two-way fluid-thermal-solid coupling.
Mathematical concepts and novel heuristic methods for data clustering and visualization

This thesis advances a data clustering methodology that, unlike many others, does not impose a solution, but rather suggests an "acceptable" one. Specifically, a method is presented where the elements of the data proximity are reordered into an "acceptable" block form, enabling the visualization of the data structure. Three intuitive qualitative criteria for an "acceptable" block form are given. Quantitatively, this "blockness" is measured by two values: the Bond Energy (previously defined) and the Linear Placement (applied to the situation for the first time). The problem of minimizing these quantities is NP-complete (no exact efficient solution is known), and the thesis develops two heuristic solutions. The first one consists of linearizing the Minimum Spanning Tree (MST) via optimal linear placement. The second one linearizes the dendrogram as generated by the single-link algorithm. The effectiveness of those methods are studied by means of several examples (7 artificially generated data sets and 9 real-world data sets). It is shown that the MST Linearization is competitive with 4 other algorithms, frequently encountered because of their simplicity or performance. In addition, the thesis makes significant contributions by solving two problems of importance to data clustering. The first problem is that of defining a "good" distance measure for qualitative variables. Our solution is: found through the use of semantic trees. The second problem is that of selecting appropriate scaling factors for the coordinate axes, a difficult choice because the clusters can be adversely affected; this problem undercuts the notion of a "cluster" itself. We define a "cluster" as a region over which the probability density function is unimodal. It is then shown that, when the empirical probability distributions are used, such regions are asymptotically "scale invariant". However, this notion of cluster, which is based on the distribution density function, poses a difficulty when the clustering itself involves the notion of distance. This incompatibility is reconciled by showing that points contained in a level set of the (estimated) density function are also the points contained in the MST thresholded at certain value. This result provides a justification for the use distance as a basis for clustering.
Reinforcement Learning-Based Resource Allocation for Coverage Continuity in High Dynamic UAV Communication Networks

Unmanned aerial vehicles mounted aerial base stations (ABSs) are capable of providing on-demand coverage in next-generation mobile communication system. However, resource allocation for ABSs to provide continuous coverage is challenging, since the high dynamic of ABSs and time-varying air-to-ground channel would result in channel state information (CSI) mismatch between resource allocation decision and implementation. In consequence, the coverage of ABSs is discontinuous in spatial-temporal dimensions, i.e., the variance of user rate between adjacent time slots is large. To ensure the coverage continuity, we design a resource allocation method based on deep reinforcement learning (RDRL). Capable of adaptively tuning neural network structures, RDRL could satisfy coverage requirements by jointly allocating subchannels and power for ground users. Meanwhile, the temporal channel correlation is taken into account in the design of reward function in RDRL, which aims to alleviate the influence of CSI mismatch between method decision and implementation. Moreover, RDRL can apply a pre-trained model of previous coverage requirement to current requirement to reduce computation complexity. Experimental results show that the rate variance of RDRL can be reduced by 66.7% and spectral efficiency of RDRL can be increased by 34.7% compared with benchmark algorithms, which ensures the coverage continuity.
Millimeter-wave Substrate Integrated Printed Ridge Gap Waveguide Leaky-Wave Antenna for WiGig Applications

Abstract Millimeter-wave Substrate Integrated Printed Ridge Gap Waveguide Leaky-Wave Antenna for WiGig Applications Mohammad Reza Rahimi, MASc. Concordia University, 2018 Leaky-wave antennas have been an interesting topic for researchers for more than half a century. As millimeter-wave frequencies applications are in high demand for communication companies due their wider bandwidth, designing a leaky-wave antenna, for this frequency range is becoming more challenging with the demand for low-loss and low-cost components. Since high-performance hollow waveguides, as a low loss guiding structure, drives the cost to an unacceptable level and microstrip technology, as a low-cost transition, has an unacceptably high loss. Therefore, the requirements for a new technology that achieves both low cost and high performance feels more tangible. The new technology of substrate integrated printed ridge gap waveguide that was proposed in 2016 shows promising characteristics as a new modified gap waveguide structure for millimeter-wave applications in terms of low insertion loss and low cost. Therefore, it is necessary to propose a new desirable class of microwave components based on this technology. Here, we propose the use of this technology to design three leaky-wave antennas. The work of this thesis is divided into three major parts: (1) designing a periodic structure which has a leaky mode for a specific range of frequencies, and (2) designing a 1D-periodic leaky-wave antenna based on a periodic structure and connecting the antenna to the standard 50 Ω equipment. For achieving this purpose a quasi-TEM transition and a transition from microstrip to substrate integrated ridge gap waveguide has been designed. In addition, the slots of the proposed antenna are designed in order to have an almost constant leakage ratio through the whole operating frequency band. (3) The third part will discuss a linear array of the proposed antenna in which a new termination has been considered which results in a shorter physical length. The proposed antennas can be easily fabricated with a low-cost multi-layered PCB technology. In addition, all these antennas designed for the WiGig applications which are more attractive for today's requirements. Keywords: Leaky-wave antenna; gap waveguide; electromagnetic band gap
PENYELESAIAN CHINESE POSTMAN PROBLEM PADA GRAF BERARAH DENGAN METODE HEURISTIK

Penelitian ini membahas salah satu masalah penentuan rute optimal yang dapat diformulasikan sebagai masalah arc routing, yaitu Chinese Postman Problem (CPP). Masalah ini mencari rute perjalanan dengan biaya minimum sehingga setiap sisi/jalan harus dilewati minimal satu kali. CPP dapat diterapkan pada graf tak berarah ataupun graf berarah dan dapat diselesaikan dengan beberapa cara. Dalam penelitian ini, CPP diterapkan pada graf berarah dan diselesaikan dengan metode heuristik. Metode ini terdiri atas beberapa tahap dan menggunakan beberapa algoritme. Dalam penelitian ini, CPP diimplementasikan dalam masalah pembuangan sampah.
Upper Tract Urothelial Carcinoma: A Rare Malignancy with Distinct Immuno-Genomic Features in the Era of Precision-Based Therapies

Upper tract urothelial carcinoma (UTUC) is a rare malignancy, occurring in 5–10% of patients diagnosed with UC, and involves the renal pelvis, calyces, or ureters. UTUC can be sporadic or hereditary as a clinical manifestation of Lynch syndrome. Therapeutic management of these patients is challenging. Following risk stratification of localized disease, patients with low-grade UTUC may undergo kidney-sparing surgery or radical nephroureterectomy (RNU) and/or chemoablation with mitomycin-c instillation to reduce recurrence. In high-grade disease, RNU followed by adjuvant chemotherapy remains the standard of care. For decades, platinum-based chemotherapy has been the cornerstone of treatment for locally advanced and metastatic disease. The aim of the present review is to summarize recent advances in UTUC’s therapeutic management through the lens of its genomic and immune landscape. Accumulating knowledge on the genetic and immune aspects of UTUC tumors has increased our understanding of their underlying biology, supporting a luminal papillary, T-cell depleted contexture and enrichment in fibroblast growth factor receptor (FGFR) expression. These advances have fueled successful clinical testing of several precision-based therapeutic approaches, including immune checkpoint inhibitors (ICIs), the antibody–drug conjugates (ADCs) enfortumab vedotin and sacituzumab govitecan, and agents targeting the FGFR axis such as erdafitinib and other kinase inhibitors, allowing their entry into the therapeutic armamentarium and improving the prognosis of these patients. Not all patients respond to these precision-based targeted therapies; thus, validating and expanding the toolkit of potential biomarkers of response or resistance, including molecular subtypes, FGFR pathway gene alterations, DNA repair gene defects, tumor mutational burden (TMB), circulating tumor DNA (ctDNA), nectin-4, TROP2, and programmed death ligand-1 (PD-L1), are key to maximizing the benefit to these particular subgroups of patients.
Localization in the presence of a distracter and reverberation in the frontal horizontal plane. II. Model algorithms

Previously, it was shown that humans are able to localize a broadband noise burst quite well, even if it is presented in the presence of a second distracting broadband noise burst at 0-dB target-to-distracter ratio. In this investigation, different model algorithms are tested for their ability to predict the psychoacoustic results. First, a long-time and a running cross-correlation algorithm are introduced to simulate the psychoacoustic experiments. Both algorithms, which are used to analyze the time window in which target and distracter are presented, are not able to estimate the target position as accurately as human listeners. Therefore, a listening test was conducted to find out, if the listeners used the part of the distracter that preceded the target in the previous tests as a reference. The outcome indicates that the onsets of test sound and distracter must be separated temporally; otherwise, human localization performance deteriorates rapidly. These results are incorporated into the interaural cross-correlation difference (ICCD) model, the third model approach that is introduced. For each frequency band, the interaural time differences of the test sound are calculated from the difference in the interaural cross correlation (ICC) of the total sound (target signal+distracter) and the ICC of the distracter alone. The latter is calculated from the part of the distracter that precedes the test sound. The model is able to demonstrate a number of psychoacoustic effects, including shifts in the auditory events for low target-to-distracter ratios.