Miracle-dz/UniFAR-FTUs huggingface dataset:
Minimizing Deformations during HP MJF 3D Printing

(1) Background: The purpose of this study was to investigate deformations that occur during additive manufacturing by the HP (Hewlett-Packard) Multi Jet Fusion (MJF) process. These deformations affect the final properties of 3D-printed parts, and proper compensating technology has to be developed in order to minimize these deformations. (2) Methods: Parts were printed with powder composed of nylon plastic infused with glass beads (PA12GB). The HP MJF technology was used during investigations. All parts (specimens) were measured at different points over an extended period to follow the deformations at each point. Different finite element simulations were performed to compare them with real results and assess the viability of using simulations to save time. Various modules of the Digimat software, such as additive manufacturing (AM), material focused (MF), finite element (FE), and computer-aided engineering (CAE), were used to run the simulations. (3) Results: It was found that the printing position of the part in the printer had an impact on deformations. When the part was simulated in a tilted position but alone (deformation: 7.19 mm), the value of the deformation was 1.49 mm greater than when the other parts (two comparable parts) were simulated at the same time (deformation: 5.7 mm). The difference between the simulation with the three parts together (deformation: 5.7 mm) and reality (deformation: 3.44 mm) was 2.26 mm. Finally, the difference between the simulated single part (deformation: 7.19 mm) and the real part (deformation: 3.44) was 3.75 mm. (4) Conclusions: The results of this study will contribute to a better understanding of deformation mechanisms and will suggest solutions for improving the quality of printed parts. Three-dimensional printing is a rapidly growing technology that offers numerous possibilities across various fields. However, one commonly encountered issue is the deformation of printed parts. Methods for minimizing deformations were studied during the 3D printing process using HP MJF technology. Various factors contributing to deformation were investigated, and different techniques for reducing them were explored.
Comparison between Van Genuchten and Brooks-Corey Parameterizations in the Solution of Multiphase Problems in Rigid One-Dimensional Porous Media

Abstract Multiphase problems in porous media involve the complex flow of multiple fluid phases within porous structures, covering areas of Engineering, Medicine, Geology, among others. Understanding these phenomena is crucial in natural processes, resource management, and Engineering system design. Due to its great importance, several researchers have contributed by developing different formulations to describe the multiphase problem. Through laboratory experiments, research lines emerged to numerically determine relative permeability and capillary pressure, parameters that were previously obtained only through experiments, giving rise to two distinct models to solve the flow problem: the van Genuchten and Brooks-Corey parameterizations. This work aims to analyze, through numerical simulations, the resolution of multiphase problems in rigid porous media using both parameterization models, in order to compare the efficiency of each method in different settings. Apparently, this study is unique in its focus, uncovering valuable insights into performance and applicability of both parameterization, providing a comprehensive view of their advantages and constraints in several settings. The results of this study have indicated an advantage in employing Brooks-Corey parameterization, particularly in reducing the error between the numerical and analytical solutions. The findings of this study can help, for example, to better understand oil recovery from naturally fractured reservoirs.
Novel Sweat-Based Wearable Device for Advanced Monitoring of Athletic Physiological Biometrics

Blood testing has traditionally been the gold standard for the physiological analysis and monitoring of professional athletes. In recent years, blood testing has moved out of the laboratory thanks to portable handheld devices, such as lactate meters. However, despite its usefulness and widespread use, blood testing has several drawbacks and limitations, such as the need for the athlete to stop exercising for blood extraction and the inability to have data continuously collected. In this scenario, sweat has become an alternative to blood testing because of its rich content of electrolytes and metabolites, as well as small quantities of sugars, proteins, and ions. Nevertheless, there are few devices capable of analyzing this biofluid and providing useful information to users. In this paper, an electronic system designed for the autonomous analysis of sweat electrolytes and metabolites along with heart rate dynamics is presented. This system is part of a novel wearable device tailored for athletes that offers to the user a real-time assessment of their physiological status and performance.
Statistical network analysis for epilepsy MEG data

Brain network analysis has attracted the interest of neuroscience researchers in studying brain diseases. Mag-netoencephalography (MEG) is especially proper for analyzing functional connectivity due to high temporal and spatial resolution. The application of graph theory for functional connectivity analysis has been studied widely, but research on network modeling for MEG still needs more. Temporal exponential random graph model (TERGM) considers temporal dependencies of networks. We performed the brain network analysis, including static / temporal network statistics, on two groups of epilepsy patients who removed the left (LT) or right (RT) part of the brain and healthy controls. We investigate network di ﬀ erences using Multiset canonical correlation analysis (MCCA) and TERGM between epilepsy patients and healthy controls (HC). The brain network of healthy controls had fewer temporal changes than patient groups. As a result of TERGM, on the simulation networks, LT and RT had less stable state than HC in the network connectivity structure. HC had a stable state of the brain network.
A Two-Layer Distributed Fault Diagnosis Method Based on Correlation Feature Transfer for Large-Scale Sequential Process Industries

Plant-wide process monitoring and fault diagnosis are key technologies to ensure the high-efficiency and safety of the production. This article pays close attention to the new characteristics in modern large-scale sequential industries, including long process, multiunit cooperation, and strong coupling among subblocks. A two-layer distributed fault diagnosis method based on feature transfer is proposed. By characterizing the coupling correlation between subblocks and imposing the feature heredity of adjacent subblocks into plant-wide process modeling, a distributed fault diagnosis framework at the subblock layer and the process layer is developed. First, the process decomposition is performed and we obtain several sequential subblocks. For each subblock, the local tangent space alignment (LTSA) algorithm is employed to perform the nonlinear dimension reduction. Then, canonical correlation analysis (CCA) is used to characterize the coupling relationships among subblocks and the internal unique features of each subblock and the external features related to other subblocks are extracted by CCA. In the feature extraction process, we use the external features as the input of the next adjacent subblock to model the chain feature transfer effect between subblocks. On this basis, the internal and external monitoring statistics for each subblock are constructed and the corresponding control limits are determined by kernel density estimation (KDE). In this way, the subblock layer monitoring model is developed, where the internal fluctuations and underlying propagation tendency of anomalies can be monitored in a fine-scale manner. The plant-wide process monitoring results are reached based on all the monitoring submodels via Bayesian fusion. Finally, the internal and external statistics-based contribution plots are designed for fault diagnosis and the fault-relevant variables can be located. The proposed framework is testified on a real hot strip mill process and the results show its effectiveness.
A Tutorial on Downlink Precoder Selection Strategies for 3GPP MIMO Codebooks

This paper deals with the evolution of downlink codebook based multiple-input multiple-output (MIMO) within the third generation partnership project (3GPP) through release 15 to 17. There exist already several tutorials on this topic. However, to the authors’ knowledge, the comparison in terms of complexity performance trade-off between practical precoder selection strategies in frequency or delay domain has not been tackled so far in the literature. This paper describes with matrix formalism the two main codebook types specified within 3GPP, i.e., Type-I codebook (low resolution) and Type-II codebook (high resolution). The Rel. 17 port selection is also detailed as well as the multi-user MIMO (MU-MIMO) precoding strategy to be applied relying on Type-II codebook feedback. For the enhanced Type-II codebook, two main practical precoder selection strategies are detailed at the UE side (i) based on singular value decomposition per sub-band in the frequency domain, (ii) based on wideband singular decomposition in the delay domain. Monte Carlo simulations demonstrate that the delay domain strategy performance may suffer from spatial interference for single user MIMO high rank transmissions when the channel is both spatially correlated and frequency selective. On the other hand, the frequency domain strategy complexity increases linearly with the number of sub-bands while it is not the case for the delay domain selection strategy. As a result, the delay domain selection strategy is particularly relevant for Rel. 17 Type-II codebook port selection or for a low frequency selective channel with few significant consecutive delays.
Application Analysis of Artificial Intelligence Technology in Electrical Engineering Teaching

This article combines the characteristics of artificial intelligence technology and educational technology to realize the possibility of application in electrical automatic control systems, and applies artificial intelligence and educational technology to electrical engineering examples such as monitoring fire alarm open circuit design and smoke box appearance inspection in power transformation and distribution systems. Analyze the impact of artificial intelligence on electrical automation technology. The research results show that artificial intelligence and education can make electrical automation technology have the characteristics of simplification, distribution, informatization, diversity, flexibility, continuity, real-time and control complexity. Use artificial intelligence technology and educational technology to effectively analyze and process electrical engineering related parameters and data, reduce the use of lines and transformers, simplify work procedures, reduce error rates, save manpower, material resources and costs, and improve the accuracy of automatic control.
Vegetation height estimates for a mixed temperate forest using satellite laser altimetry

Data from the Geoscience Laser Altimeter System (GLAS) aboard the Ice Cloud and land Elevation Satellite (ICESat) offer an unprecedented opportunity for canopy height retrieval at a regional to global scale. The data also provide useful information for forest stand level assessment at coincident locations. In this study height indices from light detection and ranging (LiDAR) waveforms were explored as a means of extracting canopy height; these were examined with reference to a mixed temperate forest in Gloucestershire, UK, containing planted stands with a mean age of 51 years and mean maximum height of 26.6 m. A method based on using a terrain index (TI; maximum minus minimum elevations from a 7×7 subset 10‐m resolution digital terrain model (DTM)) to adjust the waveform extent (WE; signal begin minus signal end) produced an R 2 value of 0.89 when regressed against field measurements of maximum canopy height at footprint locations (field height = 0.91(WE−TI)+4.86; root mean squared error (RMSE) = 2.99 m, coefficient significance p<0.001, intercept significance p>0.01). Multiple regression performed on both WE and TI with field measurements produced an R 2 of 0.90 and an RMSE of 2.86 m (field height = 1.0208WE−0.7310TI; coefficient significance p<0.001, intercept not significant). Maximum canopy height estimates using an automated approach to ground return identification based on iterative fitting of Gaussian peaks (GP1_2MAXAMP) to the waveform explained 74% of variance when compared to field measurements (field height = 1.05(GP1_2MAXAMP); RMSE = 4.53 m, coefficient significance p<0.001, intercept not significant). The ability of satellite LiDAR to retrieve data for such a complex and diverse area further indicates the potential of this technique for both carbon accounting and forest management.
Three‐dimensional surface deformation derived from airborne interferometric UAVSAR: Application to the Slumgullion Landslide

In order to provide surface geodetic measurements with “landslide‐wide” spatial coverage, we develop and validate a method for the characterization of 3‐D surface deformation using the unique capabilities of the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) airborne repeat‐pass radar interferometry system. We apply our method at the well‐studied Slumgullion Landslide, which is 3.9 km long and moves persistently at rates up to ∼2 cm/day. A comparison with concurrent GPS measurements validates this method and shows that it provides reliable and accurate 3‐D surface deformation measurements. The UAVSAR‐derived vector velocity field measurements accurately capture the sharp boundaries defining previously identified kinematic units and geomorphic domains within the landslide. We acquired data across the landslide during spring and summer and identify that the landslide moves more slowly during summer except at its head, presumably in response to spatiotemporal variations in snowmelt infiltration. In order to constrain the mechanics controlling landslide motion from surface velocity measurements, we present an inversion framework for the extraction of slide thickness and basal geometry from dense 3‐D surface velocity fields. We find that the average depth of the Slumgullion Landslide is 7.5 m, several meters less than previous depth estimates. We show that by considering a viscoplastic rheology, we can derive tighter theoretical bounds on the rheological parameter relating mean horizontal flow rate to surface velocity. Using inclinometer data for slow‐moving, clay‐rich landslides across the globe, we find a consistent value for the rheological parameter of 0.85 ± 0.08.
The Characteristics of New Zealand Oolong Tea

ii Acknowledgements iii Table of contents iv List of Figures viii List of Tables ix List of Nomenclature x List of Abbreviations xi Chapter 1: Introduction 1 1.1 Tea 1 1.2 The types of tea 1 1.3 Oolong tea 1 1.4 Oolong Tea in New Zealand and New Zealand Oolong Tea Industry 2 1.5 History of New Zealand Oolong Tea Research 2 Chapter2: Literature Review 3 2.1 Tea Plant 3 2.2 Tea plants growth situation and process 3 2.3 Tea Processing 5 2.3.
Ultracompact Polarization-Insensitive Waveguide Crossing Based on Dielectric Metasurface

A compact polarization-insensitive silicon waveguide crossing is proposed and experimentally demonstrated. The dielectric metasurface can extremely manipulate the effective refractive profile to keep high transmittance in the propagation direction and shrink the device footprint. Our designed crossing has an ultra-wideband operating bandwidth covering 1200 nm to 1700 nm for dual-polarization (insertion loss < 0.4 dB) and an ultra-compact footprint of only <inline-formula> <tex-math notation="LaTeX">$4.8\times 4.8\,\,\mu \text{m}^{2}$ </tex-math></inline-formula>. The simulated results indicate the device has a good fabrication tolerance. Subsequently, an ultra-densely (<inline-formula> <tex-math notation="LaTeX">$30\times 30\,\,\mu \text{m}^{2}$ </tex-math></inline-formula>) polarization-multiplexed integrated circuit consisting of a crossing and four polarization splitter-rotators is designed and fabricated. The measured circuit is characterized with low insertion loss and low crosstalk over 100 nm bandwidth. These compact components and circuits pave an alternative way for large-scale high-capacity optical communication system.
Targeted Alpha Therapy: All We Need to Know about 225Ac’s Physical Characteristics and Production as a Potential Theranostic Radionuclide

The high energy of α emitters, and the strong linear energy transfer that goes along with it, lead to very efficient cell killing through DNA damage. Moreover, the degree of oxygenation and the cell cycle state have no impact on these effects. Therefore, α radioisotopes can offer a treatment choice to individuals who are not responding to β− or gamma-radiation therapy or chemotherapy drugs. Only a few α-particle emitters are suitable for targeted alpha therapy (TAT) and clinical applications. The majority of available clinical research involves 225Ac and its daughter nuclide 213Bi. Additionally, the 225Ac disintegration cascade generates γ decays that can be used in single-photon emission computed tomography (SPECT) imaging, expanding the potential theranostic applications in nuclear medicine. Despite the growing interest in applying 225Ac, the restricted global accessibility of this radioisotope makes it difficult to conduct extensive clinical trials for many radiopharmaceutical candidates. To boost the availability of 225Ac, along with its clinical and potential theranostic applications, this review attempts to highlight the fundamental physical properties of this α-particle-emitting isotope, as well as its existing and possible production methods.
Testing a Home Solution for Preparing Young Children for an Awake MRI: A Promising Smartphone Application

Thanks to its non-invasive nature and high-resolution imaging capabilities, magnetic resonance imaging (MRI) is a valuable diagnostic tool for pediatric patients. However, the fear and anxiety experienced by young children during MRI scans often result in suboptimal image quality and the need for sedation/anesthesia. This study aimed to evaluate the effect of a smartphone application called COSMO@home to prepare children for MRI scans to reduce the need for sedation or general anesthesia. The COSMO@home app was developed incorporating mini-games and an engaging storyline to prepare children for learning goals related to the MRI procedure. A multicenter study was conducted involving four hospitals in Belgium. Eligible children aged 4–10 years were prepared with the COSMO@home app at home. Baseline, pre-scan, and post-scan questionnaires measured anxiety evolution in two age groups (4–6 years and 7–10 years). Eighty-two children participated in the study, with 95% obtaining high-quality MRI images. The app was well-received by children and parents, with minimal technical difficulties reported. In the 4–6-year-old group (N = 33), there was a significant difference between baseline and pre-scan parent-reported anxiety scores, indicating an increase in anxiety levels prior to the scan. In the 7–10-year-old group (N = 49), no significant differences were observed between baseline and pre-scan parent-reported anxiety scores. Overall, the COSMO@home app proved to be useful in preparing children for MRI scans, with high satisfaction rates and successful image outcomes across different hospitals. The app, combined with minimal face-to-face guidance on the day of the scan, showed the potential to replace or assist traditional face-to-face training methods. This innovative approach has the potential to reduce the need for sedation or general anesthesia during pediatric MRI scans and its associated risks and improve patient experience.
Precipitation Variation and Its Impacts in Sichuan in the Last 50 Years

Based on the daily precipitation data of 133 stations in Sichuan from 1961 to 2008, precipitation variation and its impacts are analyzed in this paper. Results indicate that during 1961-2008, the spatial distribution of the annual precipitation variation in Sichuan shows an increase-decrease-increase situation from west to east: increase in most parts of Ganzi and Liangshan, decrease in Aba and most parts of Sichuan Basin and increase in the northeastern part of the basin. The linear trend coefficient field in the spatial changes of the rainstorm days also displays an increase-decrease-increase situation from west to east: increase in most parts of Ganzi, Liangshan and Panzhihua, remarkable decrease in the western and central parts of the basin and significant increase in the northeastern part of the basin. Apart from some parts of the central and southern basin, the rainstorm intensity in the province tended to increase, and the trend in the northeastern part of the basin was notable. The variation trend of the heavy rain days is close to that of the rainstorm, showing an increase-decrease-increase change from west to east. Except for some parts of Ganzi, the number of moderate and light rain days in most parts of Sichuan decreased. On the contrary, the number of days without rain increased greatly in most parts of the province, except for part of western Sichuan Plateau.
Genomic evolution of BA.5.2 and BF.7.14 derived lineages causing SARS-CoV-2 outbreak at the end of 2022 in China

Since the end of 2022, when China adjusted its COVID-19 response measures, the SARS-CoV-2 epidemic has rapidly grown in the country. It is very necessary to monitor the evolutionary dynamic of epidemic variants. However, detailed reports presenting viral genome characteristics in China during this period are limited. In this study, we examined the epidemiological, genomic, and evolutionary characteristics of the SARS-CoV-2 genomes from China. We analyzed nearly 20,000 genomes belonging to 17 lineages, predominantly including BF.7. 14 (22.3%), DY.2 (17.3%), DY.4 (15.5%), and BA.5. 2.48 (11.9%). The Rt value increased rapidly after mid-November 2022, reaching its peak at the end of the month. We identified forty-three core mutations in the S gene and forty-seven core mutations in the ORF1ab gene. The positive selection of all circulating lineages was primarily due to non-synonymous substitutions in the S1 region. These findings provide insights into the genomic characteristics of SARS-CoV-2 genomes in China following the relaxation of the ‘dynamic zero-COVID’ policy and emphasize the importance of ongoing genomic monitoring.