Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultra-Smooth Polishing of Single-Crystal Silicon Carbide by Pulsed-Ion-Beam Sputtering of Quantum-Dot Sacrificial Layers

Single-crystal silicon carbide has excellent electrical, mechanical, and chemical properties. However, due to its high hardness material properties, achieving high-precision manufacturing of single-crystal silicon carbide with an ultra-smooth surface is difficult. In this work, quantum dots were introduced as a sacrificial layer in polishing for pulsed-ion-beam sputtering of single-crystal SiC. The surface of single-crystal silicon carbide with a quantum-dot sacrificial layer was sputtered using a pulsed-ion beam and compared with the surface of single-crystal silicon carbide sputtered directly. The surface roughness evolution of single-crystal silicon carbide etched using a pulsed ion beam was studied, and the mechanism of sacrificial layer sputtering was analyzed theoretically. The results show that direct sputtering of single-crystal silicon carbide will deteriorate the surface quality. On the contrary, the surface roughness of single-crystal silicon carbide with a quantum-dot sacrificial layer added using pulsed-ion-beam sputtering was effectively suppressed, the surface shape accuracy of the Ø120 mm sample was converged to 7.63 nm RMS, and the roughness was reduced to 0.21 nm RMS. Therefore, the single-crystal silicon carbide with the quantum-dot sacrificial layer added via pulsed-ion-beam sputtering can effectively reduce the micro-morphology roughness phenomenon caused by ion-beam sputtering, and it is expected to realize the manufacture of a high-precision ultra-smooth surface of single-crystal silicon carbide.
Validation and improvment of atmospheric correction methods for ocean colour images in optically complex coastal waters

To acquire marine parameters from remote sensing ocean color data, the sensor-measured signal needs to be corrected for the atmospheric contribution. Indeed, the solar radiation reflected by air molecules and atmospheric aerosols is significant in the sensor bands of interest for ocean color applications. The removal of the atmospheric contribution is called the atmospheric correction (AC). In open ocean waters, the AC relies on the assumption that the water is totally absorbent in the near infrared (NIR) part of the spectral region, allowing to retrieve the atmospheric contribution and to extrapolate it to the visible spectral range, and thus to determine the marine signal that contains the information on the optical properties of seawaters. However, this assumption is not valid in highly productive and turbid coastal waters. Hence, AC approaches for coastal waters need to rely on alternative assumptions. This Ph. D. thesis has as main objective to validate and improve these AC methods developed for contrasted coastal waters, with a focus on MODIS Aqua images. First, a validation and comparison of existing AC methods, relying on diverse assumptions and methods, is performed. Therefore, four commonly used AC methods are selected, (1) the standard NIR AC approach of NASA, (2) the NIR similarity spectrum AC approach including assumptions of spatial homogeneity in the water and aerosol reflectance, (3) the switching algorithm using the short wave infrared bands for AC in highly turbid waters, (4) an Artificial Neural Network algorithm. With the help of a validation exercise based on in situ data and as a function of the water type, several areas of improvement are delineated, including the use of spectral relationships to constrain NIR-modelling schemes. Modified NIR-modelling schemes are suggested for the standard NASA and NIR similarity spectrum AC methods. Both are forced with globally valid spectral relationships. Sensitivity studies and validation exercises, using MODIS-Aqua images in the Eastern English Channel/North Sea and French Guiana waters, are conducted showing that the suggested modified NIR-modelling schemes improve the estimations of the marine signal in contrasted coastal waters.
Assessment of a deep learning model for COVID-19 classification on chest radiographs: a comparison across image acquisition techniques and clinical factors

Abstract. Purpose The purpose is to assess the performance of a pre-trained deep learning model in the task of classifying between coronavirus disease (COVID)-positive and COVID-negative patients from chest radiographs (CXRs) while considering various image acquisition parameters, clinical factors, and patient demographics. Methods Standard and soft-tissue CXRs of 9860 patients comprised the “original dataset,” consisting of training and test sets and were used to train a DenseNet-121 architecture model to classify COVID-19 using three classification algorithms: standard, soft tissue, and a combination of both types of images via feature fusion. A larger more-current test set of 5893 patients (the “current test set”) was used to assess the performance of the pretrained model. The current test set contained a larger span of dates, incorporated different variants of the virus and included different immunization statuses. Model performance between the original and current test sets was evaluated using area under the receiver operating characteristic curve (ROC AUC) [95% CI]. Results The model achieved AUC values of 0.67 [0.65, 0.70] for cropped standard images, 0.65 [0.63, 0.67] for cropped soft-tissue images, and 0.67 [0.65, 0.69] for both types of cropped images. These were all significantly lower than the performance of the model on the original test set. Investigations regarding matching the acquisition dates between the test sets (i.e., controlling for virus variants), immunization status, disease severity, and age and sex distributions did not fully explain the discrepancy in performance. Conclusions Several relevant factors were considered to determine whether differences existed in the test sets, including time period of image acquisition, vaccination status, and disease severity. The lower performance on the current test set may have occurred due to model overfitting and a lack of generalizability.
A Comparison of the Polyphenolic and Free Radical Scavenging Activity of Cold Brew versus Hot Brew Black Tea (Camellia Sinensis, Theaceae)

Recently, a new trend called cold brewing gained popularity in the tea and coffee beverage industry. Cold brew and hot brew black tea may have different sensory qualities and antioxidant levels because of their polyphenolic properties and brewing processes. The objectives of this study were to determine antioxidant properties and polyphenolic content of commercial brands of cold brew and hot brew black tea. The total phenolic content of the cold brew tea was determined to be 0.19 mg/mL gallic acid equivalents/100 g and hot brew tea was 0.43 mg/mL gallic acid equivalents/100 g when assayed by Folin-Ciocalteu’s reagent method. The total flavonoid content of the cold brew tea was 0.40 mg/mL catechin equivalents/100 g and hot brew was 1.01 mg/mL catechin equivalents/100 g. Moreover, antioxidant capacity of cold brew and hot brew black tea was analyzed where their ability to scavenge DPPH radicals was 86.3% and 88.1% respectively. There was a significant difference in total phenolic content between hot brew and cold brew (p = 0.004). Similarly, there was a significant difference in total flavonoid between cold brew and hot brew (p = 0.004). Additionally, there was a significant difference in DPPH scavenging activity between cold brew and hot brew (p = 0.016). Overall, it can be concluded that although cold brew tea contained a lower amount of phenolics and flavonoids as compared to hot brew tea, they both were able to scavenge DPPH radicals in nearly same capacity.
Triple Amplification Strategy for the Improved Efficiency of a Microplate-Based Assay for the Chemiluminescent Detection of DNA

Abstract Significant research efforts are currently focused on advancing DNA detection methodology. Various nanoparticles (NPs), which are currently the most widely used solid-phase carriers for nucleic acid assays, have a number of essential drawbacks. Microtiter plates provide a simple and economical alternative to the NPs. This article reports the development of a sandwich assay for DNA detection using a microtiter plate as the solid carrier. A capture oligonucleotide modified with fluorescein was bound to the anti-fluorescein antibody adsorbed on the polystyrene microplate surface. A hepatitis B virus DNA fragment was used as the model analyte. To improve the assay sensitivity, the biotinylated reporter oligonucleotide and streptavidin-horseradish polyperoxidase (polyHRP) conjugate were used to provide an amplified detection system. Additional amplification was achieved because the peroxidase activity was measured by a chemiluminescent method using the 3-(10′-phenothiazinyl)propane-1-sulfonate/N-morpholinopyridine pair as an enhancing reagent. The detection limit of the developed assay was 0.9 pM with a linear dynamic range from 0.9 to 100 pM. This method may be used as a platform for the development of sensitive DNA assays.
Modelling the dynamic behaviour of junction fires with a coupled atmosphere–fire model

Dynamic fire behaviour involves rapid changes in fire behaviour without significant changes in ambient conditions, and can compromise firefighter and community safety. Dynamic fire behaviour cannot be captured using spatial implementations of empirical fire-spread models predicated on the assumption of an equilibrium, or quasi-steady, rate of spread. In this study, a coupled atmosphere–fire model is used to model the dynamic propagation of junction fires, i.e. when two firelines merge at an oblique angle. This involves very rapid initial rates of spread, even with no ambient wind. The simulations are in good qualitative agreement with a previous experimental study, and indicate that pyro-convective interaction between the fire and the atmosphere is the key mechanism driving the dynamic fire propagation. An examination of the vertical vorticity in the simulations, and its relationship to the fireline geometry, gives insight into this mechanism. Junction fires have been modelled previously using curvature-dependent rates of spread. In this study, however, although fireline geometry clearly influences rate of spread, no relationship is found between local fireline curvature and the simulated instantaneous local rate of spread. It is possible that such a relationship may be found at larger scales.
A multi‐scale plane‐detection method based on the Hough transform and region growing

The detection of planes from 3D point clouds plays an important role in fields such as 3D modelling, rock mechanics, registration and robotics. A multi‐scale plane‐detection method is proposed, based on extracting growth units using the Hough transform and subsequent region growing into actual plane boundaries. Because the approximate geometric features of the original plane area can be obtained from the growth units, discriminant conditions for adaptive plane growing could be provided for the growing stage. In order to detect physical planes at different scales, a strategy of multi‐scale normal estimation is introduced. Simulated icosahedron point clouds, together with actual engineering point clouds, were used to test the performance of the proposed method. Experimental results show that planar point clouds could be detected effectively, especially with rock‐mass engineering applications.
Edinburgh Research Explorer KU_ED at SocialDisNER: Extracting Disease Mentions in Tweets Written in Spanish

This paper describes our system developed for the Social Media Mining for Health (SMM4H) 2022 SocialDisNER task. We used several types of pre-trained language models, which are trained on Spanish biomedical literature or Spanish Tweets. We showed the difference in performance depending on the quality of the tokenization as well as introducing silver standard annotations when training the model. Our model obtained a strict F1 of 80.3% on the test set, which is an improvement of +12.8% F1 (24.6 std) over the average results across all submissions to the SocialDisNER challenge.
YB-1 Is a Novel Target for the Inhibition of α-Adrenergic-Induced Hypertrophy

Cardiac hypertrophy resulting from sympathetic nervous system activation triggers the development of heart failure. The transcription factor Y-box binding protein 1 (YB-1) can interact with transcription factors involved in cardiac hypertrophy and may thereby interfere with the hypertrophy growth process. Therefore, the question arises as to whether YB-1 influences cardiomyocyte hypertrophy and might thereby influence the development of heart failure. YB-1 expression is downregulated in human heart biopsies of patients with ischemic cardiomyopathy (n = 8), leading to heart failure. To study the impact of reduced YB-1 in cardiac cells, we performed small interfering RNA (siRNA) experiments in H9C2 cells as well as in adult cardiomyocytes (CMs) of rats. The specificity of YB-1 siRNA was analyzed by a miRNA-like off-target prediction assay identifying potential genes. Testing three high-scoring genes by transfecting cardiac cells with YB-1 siRNA did not result in downregulation of these genes in contrast to YB-1, whose downregulation increased hypertrophic growth. Hypertrophic growth was mediated by PI3K under PE stimulation, as well by downregulation with YB-1 siRNA. On the other hand, overexpression of YB-1 in CMs, caused by infection with an adenovirus encoding YB-1 (AdYB-1), prevented hypertrophic growth under α-adrenergic stimulation with phenylephrine (PE), but not under stimulation with growth differentiation factor 15 (GDF15; n = 10–16). An adenovirus encoding the green fluorescent protein (AdGFP) served as the control. YB-1 overexpression enhanced the mRNA expression of the Gq inhibitor regulator of G-protein signaling 2 (RGS2) under PE stimulation (n = 6), potentially explaining its inhibitory effect on PE-induced hypertrophic growth. This study shows that YB-1 protects cardiomyocytes against PE-induced hypertrophic growth. Like in human end-stage heart failure, YB-1 downregulation may cause the heart to lose its protection against hypertrophic stimuli and progress to heart failure. Therefore, the transcription factor YB-1 is a pivotal signaling molecule, providing perspectives for therapeutic approaches.
A FeFET-Based ADC Offset Robust Compute-In-Memory Architecture for Streaming Keyword Spotting (KWS)

Keyword spotting (KWS) on edge devices requires low power consumption and real-time response. In this work, a ferroelectric field-effect transistor (FeFET)-based compute-in-memory (CIM) architecture is proposed for streaming KWS processing. Compared with the conventional sequential processing scheme, the inference latency is reduced by 7.7 × ∼17.6× without energy efficiency loss. To make the KWS models robust to hardware non-idealities such as analog-to-digital converter (ADC) offset, an offset-aware training scheme is proposed. It consists of ADC offset noise injection and frame-wise normalization. This scheme effectively improves the mean accuracy and chip yield by 1.5%∼5.2%, and 5%∼39%, for TC-ResNet and DS-TC-ResNet (with MatchboxNet configuration), respectively. The proposed CIM architecture is implemented with ferroelectric field-effect transistor technology, with simulated low energy consumption of 1.65 μJ/decision for 12-word keyword spotting using TC-ResNet8.
Automatic Task-Level Thinking Steps Help Large Language Models for Challenging Classification Task

Large language models (LLMs) have shown incredible performance on many tasks such as dialogue generation, commonsense reasoning and question answering. In-context learning (ICL) is an important paradigm for adapting LLMs to the downstream tasks by prompting few demonstrations. However, the distribution of demonstrations can severely affect the performance, especially for challenging classification tasks. In this paper, we propose the concept of task-level thinking steps that can eliminate bias introduced by demonstrations. Further, to help LLMs distinguish confusing classes, we design a progressive revision framework, which can improve the thinking steps by correcting hard demonstrations. Experimental results prove the superiority of our proposed method, achieving best performance on three kinds of challenging classification tasks in the zero-shot and few-shot settings. Besides, with task-level thinking steps, automatically generated chain-of-thoughts (CoTs) bring more competitive performance.
Station-level ridership on Mexico City's subway and BRT

The Mexico City Metropolitan Area (MCMA) faces pressing mobility and environmental challenges. A growing group of academics, NGOs, international institutions, and government agencies point to the need to expand and improve the public transportation system, as well as move towards more sustainable urban development patterns. Transit-oriented development (TOD), an urban planning concept based on the coordination of transit infrastructure with dense, compact, and mixed-use neighborhoods, has been identified as a potential tool to address critical mobility, environmental, accessibility, and equity issues in the MCMA. Yet, an effective TOD polic7 will require an understanding of the factors associated with transit ridership, particularly those related to the built-environment and land use. Traditional ridership estimation methods are data-intensive and prohibitively costly for many developing-world cities. In addition, they are not designed to analyze the influence of station-level characteristics. Direct ridership modelling (ORM), a "sketch-planning" tool that uses multivariate regressions to predict station-level ridership, is a viable alternative that allows planners to achieve reasonable estimates quickly and economically, while also enabling the analysis of the relationship between the station-area built environment and transit ridership. In this thesis, I use data from a variety of public and open data sources to estimate direct ridership models for Mexico City's Metro and BRT systems, including sociodemographic, land use, built environment, transit system, and relative location characteristics. I And that some of the variables included have different effects on BRT and Metro, suggesting that the two systems play different roles within the public transportation network. Mainly, Metro ridership is driven by employment, while station-area population drives BRT ridership. C'olectivos, a privately owned and operated semi-formal network of vans and microbuses -which had been hard to analyze due to lack of dataare important determinants of ridership in the mass-transit system. Interestingly, I also find evidence that built-environment characteristics, such as well-connected street grids, influence transit ridership. T discuss the implications of these results for a TOD policy in the Mexico City Metropolitan Area. The results point to the need of further research concerning travel and the built environment in developing­ world cities, and support the claim that "sketch-planning" tools estimated with public and open data sources are useful to complement demand forecasts. Thesis Supervisor: P. Christopher Zegras Associate Professor of Urban Studies and Planning
Triple-Band Zeroth-Order Epsilon-Negative Antenna Using Two Pseudo-Open Termination Unit Cells for C-Band Applications

In this letter, a triple-band zeroth-order-resonance (ZOR) epsilon-negative antenna using two series pseudo-open termination (P-OT) unit cells is proposed, for the case where shunt ZOR <inline-formula><tex-math notation="LaTeX">$({\boldsymbol{f}_{\boldsymbol{sh}}})$</tex-math></inline-formula> is higher than series ZOR <inline-formula><tex-math notation="LaTeX">$({\boldsymbol{f}_{\boldsymbol{se}}})$</tex-math></inline-formula>. Epsilon-negative transmission line (ENG TL) resonates a shunt ZOR, while the two series P-OT unit cells resonate two series ZORs (<inline-formula><tex-math notation="LaTeX">${\boldsymbol{f}_{\boldsymbol{se}}}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">${\boldsymbol{f}_{\boldsymbol{se1}}}$</tex-math></inline-formula>). Both the P-OT unit cells create different capacitances with the ENG TL to resonate <inline-formula><tex-math notation="LaTeX">${\boldsymbol{f}_{\boldsymbol{se}}}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">${\boldsymbol{f}_{\boldsymbol{se}1}}$</tex-math></inline-formula>. An electric field distribution vector is used to verify the resonances for zeroth order, and it is found that all the three resonances follow zeroth-order characteristics. The P-OT unit cells can be placed anywhere around the ENG TL to get proper matching. The measured resonances are 5.95 GHz <inline-formula><tex-math notation="LaTeX">$({\boldsymbol{f}_{\boldsymbol{se}1}})$</tex-math></inline-formula>, 6.26 GHz <inline-formula><tex-math notation="LaTeX">$({\boldsymbol{f}_{\boldsymbol{se}}})$</tex-math></inline-formula>, and 6.91 GHz <inline-formula><tex-math notation="LaTeX">$({\boldsymbol{f}_{\boldsymbol{sh}}})$</tex-math></inline-formula> covering the satellite transmission frequencies of the C-band. The measured peak gains are 1.14, 1.39, and 2.19 dBi for <inline-formula><tex-math notation="LaTeX">$({\boldsymbol{f}_{\boldsymbol{se}1}})$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">${\boldsymbol{f}_{\boldsymbol{se}}}$</tex-math></inline-formula>, and <inline-formula><tex-math notation="LaTeX">${\boldsymbol{f}_{\boldsymbol{sh}}}$</tex-math></inline-formula>, respectively. <inline-formula><tex-math notation="LaTeX">${\boldsymbol{f}_{\boldsymbol{se}1}}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">${\boldsymbol{f}_{\boldsymbol{se}}}$</tex-math></inline-formula> have peak gain at the left and the right side of the <inline-formula><tex-math notation="LaTeX">$\varphi = {\text{0}^{\circ}}$</tex-math></inline-formula> plane, respectively, while <inline-formula><tex-math notation="LaTeX">${\boldsymbol{f}_{\boldsymbol{sh}}}$</tex-math></inline-formula> has peak gains at both the right and the left sides of the <inline-formula><tex-math notation="LaTeX">$\varphi = {\text{0}^{\circ}}$</tex-math></inline-formula> plane.
Differential Post-Translational Modifications of Proteins in Bladder Ischemia

Clinical and basic research suggests that bladder ischemia may be an independent variable in the development of lower urinary tract symptoms (LUTS). We have reported that ischemic changes in the bladder involve differential expression and post-translational modifications (PTMs) of the protein’s functional domains. In the present study, we performed in-depth analysis of a previously reported proteomic dataset to further characterize proteins PTMs in bladder ischemia. Our proteomic analysis of proteins in bladder ischemia detected differential formation of non-coded amino acids (ncAAs) that might have resulted from PTMs. In-depth analysis revealed that three groups of proteins in the bladder proteome, including contractile proteins and their associated proteins, stress response proteins, and cell signaling-related proteins, are conspicuously impacted by ischemia. Differential PTMs of proteins by ischemia seemed to affect important signaling pathways in the bladder and provoke critical changes in the post-translational structural integrity of the stress response, contractile, and cell signaling-related proteins. Our data suggest that differential PTMs of proteins may play a role in the development of cellular stress, sensitization of smooth muscle cells to contractile stimuli, and deferential cell signaling in bladder ischemia. These observations may provide the foundation for future research to validate and define clinical translation of the modified biomarkers for precise diagnosis of bladder dysfunction and the development of new therapeutic targets against LUTS.