Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Parameters on Semantic Segmentation: A Case Study on the CamVid Dataset

Image segmentation is an important topic of remote sensing image processing. High-resolution remote sensing images contain complex object information. The application of traditional segmentation methods is greatly restricted. Deep learning is suitable for processing remote sensing images due to the complex multi-layer nonlinear transformation characteristics. Many image semantic segmentation methods based on deep learning were proposed, which realizes an end-to-end semantic segmentation workflow. Most of those studies focused on the design of network architectures. In contrast, the impact of parameters on final segmentation accuracy was not fully exploited. In this context, with the CamVid dataset and popular U-Net convolutional neural network and DeeplabV3+, this paper explored the impact of the max Epoch and the initial learning rate on the segmentation results. The study results show that in Deeplab V3+, when the MaxEpochs parameters are different and the InitialLearningRate parameters are the same, the improvement of Global Accuracy is not obvious. When the InitialLearningRate parameters are different and the MaxEpochs parameters are the same, the Global Accuracy has been greatly improved, increasing by about 3%. In U-Net, when the MaxEpochs parameters are different and the InitialLearningRate parameters are the same, the Global Accuracy is improved by about 1%. When the InitialLearningRate parameters are different and the MaxEpochs parameters are the same, the Global Accuracy is greatly improved, increasing by 24%. They can be concluded that the max epochs have slight impact on the final global accuracy, in contrast, the InitialLearningRate has a great impact on the experimental results.
A Magnetic Yagi-Uda Antenna With Vertically Polarized Endfire Radiation in Millimeter-Wave Band Applying Higher-Order Mode

A magnetic Yagi-Uda antenna applying higher-order mode in millimeter-Wave band with vertically polarized endfire radiation is proposed in this paper. Surface wave mode analysis is applied to spot TE mode for magnetic Yagi-Uda antenna in contrast to TM mode for electric Yagi-Uda antenna. A modified structure evolved from conventional U-shaped cavity is used to address the reversed current issue for higher order mode, which exhibits a more uniform phase distribution at the Yagi-Uda array end. Then a composite end-feeding structure with reflector integrated is further introduced to minimize its parasitic effects for practical antenna design in millimeter-wave band. To validate the design, a prototype with a size of 2. 7λ0×1. 25λ0×0. 088λ0 is fabricated and tested. It can achieve an endfire gain of 8-11 dBi within 24-26 GHz with -10-dB impedance band covering an even wider frequency range. The measured front-to-back ratio (FBR) is larger than 16.1 dB. Vertically polarized radiation is realized with cross-polarization level lower than -20 dB at endfire direction.
Low-rank tensor completion using nonconvex total variation

In this work, we study the tensor completion problem in which the main point is to predict the missing values in visual data. To greatly benefit from the smoothness structure and edge-preserving property in visual images, we suggest a tensor completion model that seeks gradient sparsity via the l0-norm. The proposal combines the low-rank matrix factorization which guarantees the low-rankness property and the nonconvex total variation (TV). We present several experiments to demonstrate the performance of our model compared with popular tensor completion methods in terms of visual and quantitative measures.
Surgical Treatment of Bone Sarcoma

Simple Summary Even today, a malignant bone tumor is still a threatening condition for the patient. Such tumors are difficult to treat and they require an interdisciplinary approach to ensure the best possible outcome. This review article provides an overview of the three dominating bone sarcoma entities: osteosarcoma, chondrosarcoma, and Ewing sarcoma. Their prognoses and main pillars of treatment (chemotherapy, radiotherapy, surgery) are laid out with a special focus on the surgical management of this condition. Five cases are described to illustrate different surgical strategies such as biological reconstruction and implantation of a megaprosthesis. Finally, an outline of future developments in the field of tumor surgery is presented with a special focus on technical innovations to help improve surgical outcome and implant survival. Abstract Bone sarcomas are rare primary malignant mesenchymal bone tumors. The three main entities are osteosarcoma, chondrosarcoma, and Ewing sarcoma. While prognosis has improved for affected patients over the past decades, bone sarcomas are still critical conditions that require an interdisciplinary diagnostic and therapeutic approach. While radiotherapy plays a role especially in Ewing sarcoma and chemotherapy in Ewing sarcoma and osteosarcoma, surgery remains the main pillar of treatment in all three entities. After complete tumor resection, the created bone defects need to be reconstructed. Possible strategies are implantation of allografts or autografts including vascularized bone grafts (e.g., of the fibula). Around the knee joint, rotationplasty can be performed or, as an alternative, the implantation of (expandable) megaprostheses can be performed. Challenges still associated with the implantation of foreign materials are aseptic loosening and infection. Future improvements may come with advances in 3D printing of individualized resection blades/implants, thus also securing safe tumor resection margins while at the same time shortening the required surgical time. Faster osseointegration and lower infection rates may possibly be achieved through more elaborate implant surface structures.
Learning Tone Curves for Local Image Enhancement

Image enhancement methods can be formulated as global transformations, local transformations, pixel-wise processing, or a mixture of these operations. Global transformations are limited in enhancing local image regions. Existing local and pixel-wise methods mitigate this issue, but give rise to the additional challenge of limited interpretability. Bridging the gap between global and local methods, we propose a local tone mapping network (LTMNet) that learns a grid of tone curves to locally enhance an image. Tone curves are commonly used by photo-editing software and offer an intuitive representation to photographers, facilitating subsequent customization of the image. Tone curves are also widely used in image signal processors (ISPs), making our method easy to deploy on cameras. Because existing datasets contain image enhancement and photofinishing beyond global and local tone mapping, we also propose a new dataset representative of local tone mapping—the LTM dataset. We evaluate our method on this new dataset as well as MIT-Adobe and HDR+ datasets. We show that the proposed LTMNet outperforms existing methods in local tone mapping while achieving competitive performance modeling additional photofinishing. Furthermore, we show that our method can be assistive in user-interactive photo-editing tools. Our code, model, and data will be released publicly at https://github.com/SamsungLabs/ltmnet.
Patterns of Co‐Residential Relationships Across Cohorts in Post‐Socialist Countries: Less Time for Childbearing?

Co‐residential partnerships are a pre‐condition for childbearing and less time is spent in these unions when there is difficulty finding partners, a delay in union formation, and partnership instability. Our study explores patterns in co‐residential partnerships across birth cohorts in 11 post‐socialist countries to assess changes in the number of years spent in these partnerships and the patterns underlying any trend. Using the Harmonized Histories dataset, based on partnership data from generations and gender surveys, we calculate changes in co‐residential union trends. In about half of the countries, the share of women who have not entered a co‐residential union by age 30 increased, whereas the proportion still in their first union by this age decreased universally. The latter trend, reflecting union instability, pre‐dates the transition from socialism. Delays in starting the first union were seen in only a few countries immediately after the transition began but more countries experienced union postponement in coming‐of‐age cohorts in the 2000s. A declining median age at first union in the former Soviet republics before and immediately after the transition from socialism balances the impact of increased union instability. Overall, the number of years spent in a co‐residential union before age 30 declined across the Central and South‐Eastern European countries, especially in Hungary. Union dynamics may have contributed to declining fertility in these countries. In contrast, little or no change in time spent in unions in the post‐Soviet countries indicates that union dynamics were less likely to have influenced these women’s fertility behavior.
The Effectiveness of Blended Synchronous and Asynchronous Learning for Teaching Reading Comprehension

Some studies investigated the use of synchronous and asynchronous learning in EFL classrooms. However, the investigation of blended synchronous and asynchronous learning use in the reading comprehension class was scarce. Therefore, the researchers in this present study focused on investigating the effectiveness of the blended synchronous and asynchronous learning implementation for teaching reading comprehension. This study aimed to know whether or not there was a significant difference in the students’ reading comprehension ability before and after the blended synchronous and asynchronous learning implementation. This was a pre-experimental study with a one-group pretest-posttest design. Meanwhile, the population in this study were three classes of the third-semester students of non-English departments of a university in Jombang. One class consisting of twenty-five students was taken as the sample using purposive sampling. The experimental students were given a pretest of reading comprehension before getting the six-meeting treatment of blended synchronous and asynchronous learning. After the treatment finished, they did the reading comprehension posttest. After all the reading scores were collected, the descriptive statistics, normality test, and paired sample t-test were applied using SPSS. The t-test result showed that the obtained t-count (11.616) was higher than the t-table (2.063). That result revealed that the students’ reading comprehension ability was significantly different before and after the blended synchronous and asynchronous learning application. Thus, blended synchronous and asynchronous learning was effective for teaching reading comprehension. Then, it is highly recommended for EFL lecturers to combine synchronous and asynchronous learning in their remote English classes.
An enhanced J‐integral for hydraulic fracture mechanics

This article revisits the formulation of the J‐integral in the context of hydraulic fracture mechanics. We demonstrate that the use of the classical J‐integral in finite element models overestimates the length of hydraulic fractures in the viscosity‐dominated regime of propagation. A finite element analysis shows that the inaccurate numerical solution for fluid pressure is responsible for the loss in accuracy of the J‐integral. With this understanding, two novel contributions are presented. The first contribution consists of two variations of the J‐integral, termed the JHFM$J_{HFM}$ and JHFMA$J_{HFM}^A$ ‐integral, that demonstrate an enhanced ability to predict viscosity‐dominated propagation. In particular, such JHFM$J_{HFM}$ ‐integrals accurately extract stress intensity factors in both viscosity and toughness‐dominated regimes of propagation. The second contribution consists of a methodology to extract the propagation velocity from the energy release rate applicable throughout the toughness‐viscous propagation regimes. Both techniques are combined to form an implicit front‐tracking JHFM$J_{HFM}$ ‐algorithm capable of quickly converging on the location of the fracture front independently to the toughness‐viscous regime of propagation. The JHFM$J_{HFM}$ ‐algorithm represents an energy‐based alternative to the aperture‐based methods frequently used with the Implicit Level Set Algorithm to simulate hydraulic fracturing. Simulations conducted at various resolutions of the fracture suggest that the new approach is suitable for hydro‐mechanical finite element simulations at the reservoir scale.
Refractive Index and Abbe Number Tuning via 3D Printable Optical Quality Silica–Titania–Germania Glasses

The development of optical quality GeO2–TiO2–SiO2 glasses compatible with direct ink writing (DIW) 3D printing is reported in this study. Colloidal GeO2 and TiO2–SiO2 core–shell feedstocks are prepared by a sol–gel method and converted to printable inks for DIW. Printed inks are subsequently densified to glass using heat treatment at temperatures up to 1100 °C in air. A series of print‐compatible glass compositions are prepared, yielding transparent glass with the highest refractive index n = 1.576. Herein, it is shown that more TiO2 can be incorporated into the glass without haziness or scattering through the addition of GeO2. The mechanisms for this are discussed, and it is shown that crystallization persists in these glasses despite the lack of visible light scattering. Finally, the combination of both TiO2 and GeO2 into a ternary glass also is used to independently tune the dispersion properties of the glass, as demonstrated by measured refractive indices and Abbe numbers, which has potential implications for 3D‐printed optics.
Classification of Muscle Invasive Bladder Cancer to Predict Prognosis of Patients Treated with Immunotherapy

Background Recently, immunotherapies have been approved for advanced muscle invasive bladder cancer (MIBC) treatment, but only a small fraction of MIBC patients could achieve a durable drug response. Our study is aimed at identifying tumor microenvironment (TME) subtypes that have different immunotherapy response rates. Methods The mRNA expression profiles of MIBC samples from seven discovery datasets (GSE13507, GSE31684, GSE32548, GSE32894, GSE48075, GSE48276, and GSE69795) were analyzed to identify TME subtypes. The identified TME subtypes were then validated by an independent dataset (TCGA-MIBC). The subtype-related biomarkers were discovered using computational analyses and then utilized to establish a random forest predictive model. The associations of TME subtypes with immunotherapy therapeutic responses were investigated in a group of patients who had been treated with immunotherapy. A prognostic index model was constructed using the subtype-related biomarkers. Two nomograms were built by the subtype-related biomarkers or the clinical parameters. Results Two TME subtypes, including ECM-enriched class (EC) and immune-enriched class (IC), were found. EC was associated with greater extracellular matrix (ECM) pathways, and IC was correlated with immune pathways, respectively. Overall survival was significantly greater for tumors classified as IC, whereas the EC subtype had a worse prognosis. A total of nine genes (AKAP12, APOL3, CXCL13, CXCL9, GBP4, LRIG1, PEG3, PODN, and PTPRD) were selected by computational analyses to construct the random forest model. The area under the curve (AUC) values for this model were 0.827 and 0.767 in the testing and external validation datasets, respectively. Therapeutic response rates were greater in IC patients than in EC patients (28 percent vs. 18 percent). Patients with a high prognostic index had a poorer prognosis than those with a low prognostic index. The nomogram constructed from nine genes and stage achieved a C-index of 0.71. Conclusion The present investigation defined two distinct TME subtypes and developed models to assess immunotherapeutic treatment outcomes.
Gene Set Enrichment Analysis Reveals That Fucoidan Induces Type I IFN Pathways in BMDC

Fucoidan, a sulfated polysaccharide extracted from brown seaweed, has been proposed to effectively treat and prevent various viral infections. However, the mechanisms behind its antiviral activity are not completely understood. We investigate here the global transcriptional changes in bone marrow-derived dendritic cells (BMDCs) using RNA-Seq technology. Through both analysis of differentially expressed genes (DEG) and gene set enrichment analysis (GSEA), we found that fucoidan-treated BMDCs were enriched in virus-specific response pathways, including that of SARS-CoV-2, as well as pathways associated with nucleic acid-sensing receptors (RLR, TLR, NLR, STING), and type I interferon (IFN) production. We show that these transcriptome changes are driven by well-known regulators of the inflammatory response against viruses, including IRF, NF-κB, and STAT family transcription factors. Furthermore, 435 of the 950 upregulated DEGs are classified as type I IFN-stimulated genes (ISGs). Flow cytometric analysis additionally showed that fucoidan increased MHCII, CD80, and CD40 surface markers in BMDCs, indicative of greater antigen presentation and co-stimulation functionality. Our current study suggests that fucoidan transcriptionally activates PRR signaling, type I IFN production and signaling, ISGs production, and DC maturation, highlighting a potential mechanism of fucoidan-induced antiviral activity.
Multimedia Engineering Drawing Animations to Improve Vocational High School Students' Technical Drawing Concepts

The purpose of the research to develop innovative multimedia animation engineering drawing (MMAED) in the field of technology and engineering in Vocational High Schools. The research method used is research and development which broadly covers the manufacturing, and testing stages. The study population was vocational students in the fields of technology and engineering expertise. Learning is done in two different classes, namely: Class A as a control class, and class B as an experimental class. Data collection tools in the form of tests, rubrics, and questionnaires. Data were analyzed by descriptive analysis, percentage, and N-gain. The results of this study are Multimedia Animation Engineering Drawing (MMAED) with special characteristics that are accessible or affordable to the eyes and logic of students, by orthogonal projection material that requires imagination or imagination of the appearance of an object. The mastery of the concept of orthogonal projection material has increased after using MMAED, so that it reaches a high category.
Surface Hydrophilic Modification for Chip of Centrifugal Microfluidic Immunoassay System

The surface of a centrifugal microfluidic immunoassay system chip such as polymethyl methacrylate (PMMA) is often hydrophobic, which leads to problems such as poor liquid transfer efficiency and easy-to-block siphon channels, leading to bad fluid control. Therefore, surface hydrophilic modification for such chips is necessary to improve the rapidity and sensitivity of the system. Chemical modification is commonly used, but there is little research on the hydrophilic effect of different concentrations of hydrophilic reagents. According to function requirements for different microchannels of the chip (some only need to ensure the liquid can flow into the next chamber, and some also need to ensure the function of “closing the door” during immunoassay incubation), we explored the best combination of hydrophilic reagent and concentration through experiments. Firstly, three hydrophilic reagents were used for modification. Secondly, the hydrophilic effects of different reagents and concentrations were explored by contact angle test, the influence of different modification methods on liquid transfer efficiency was characterized by residual liquid calculation in the chamber. Finally, the effect of different hydrophilic reagents on absorbance was also tested. By experimental results and comprehensively considering the stability of the modification effect and the function requirements, Tween-20 (2.0% v/v) was chosen as the modifying reagents of the first siphon valve and the second siphon valve, and TritonX-100 (2.0% v/v) was chosen for the third siphon valve, which effectively reduces the contact angle and improves the liquid transfer efficiency, leading to further improvement of the rapidity and sensitivity of the centrifugal microfluidic immunoassay system by efficient siphoning and high plasma separation efficiency (99%).
Comparing Methods for Extractive Summarization of Call Centre Dialogue

This paper provides results of evaluating some text summarisation techniques for the purpose of producing call summaries for contact centre solutions. We specifically focus on extractive summarisation methods, as they do not require any labelled data and are fairly quick and easy to implement for production use. We experimentally compare several such methods by using them to produce summaries of calls, and evaluating these summaries objectively (using ROUGE-L) and subjectively (by aggregating the judgements of several annotators). We found that TopicSum and Lead-N outperform the other summarisation methods, whilst BERTSum received comparatively lower scores in both subjective and objective evaluations. The results demonstrate that even such simple heuristics-based methods like Lead-N can produce meaningful and useful summaries of call centre dialogues.
Synthesis, Characterization and Application of Amine-Functionalized Hierarchically Micro-Mesoporous Silicon Composites for CO2 Capture in Flue Gas

An efficient CO2 adsorbent with a hierarchically micro-mesoporous structure and a large number of amine groups was fabricated by a two-step synthesis technique. Its structural properties, surface groups, thermal stability and CO2 adsorption performance were fully investigated. The analysis results show that the prepared CO2 adsorbent has a specific hierarchically micro-mesoporous structure and highly uniformly dispersed amine groups that are favorable for the adsorption of CO2. At the same time, the CO2 adsorption capacity of the prepared adsorbent can reach a maximum of 3.32 mmol-CO2/g-adsorbent in the actual flue gas temperature range of 303–343 K. In addition, the kinetic analysis results indicate that both the adsorption process and the desorption process have rapid adsorption/desorption rates. Finally, the fitting of the CO2 adsorption/desorption experimental data by Avrami’s fractional kinetic model shows that the CO2 adsorption rate is mainly controlled by the intra-particle diffusion rate, and the temperature has little effect on the adsorption rate.
Temporal and spatial Taylor's law: Application to Japanese subnational mortality rates

Taylor's law is a widely observed empirical pattern that relates the variances to the means of population densities. We present four extensions of the classical Taylor's law (TL): (1) a cubic extension of the linear TL describes the mean–variance relationship of human mortality at subnational levels well; (2) in a time series, long‐run variance measures not only variance but also autocovariance, and it is a more suitable measure than variance alone to capture temporal/spatial correlation; (3) an extension of the classical equally weighted spatial variance takes account of synchrony and proximity; (4) robust linear regression estimators of TL parameters reduce vulnerability to outliers. Applying the proposed methods to age‐specific Japanese subnational death rates from 1975 to 2018, we study temporal and spatial variations, compare different coefficient estimators, and interpret the implications. We apply a clustering algorithm to the estimated TL coefficients and find that cluster memberships are strongly related to prefectural gross domestic product. The time series of spatial TL coefficients has a decreasing trend that confirms the narrowing gap between rural and urban mortality in Japan.