bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effects of energy density and heat treatment on the properties of 3D printed tungsten
Authors: Chen wenlian , Yang yihang 
Published: December 2023

Abstract

A large temperature gradient led to rapid temperature changes in the selective laser melting (SLM) process, resulting in high residual stress and micro-cracks, which were the main challenges faced by the 3D printing of tungsten (W) materials. On the other hand, the volumetric energy density had a significant effect on the density of the pure W structural component fabricated by SLM. It was difficult to eliminate defects in the formed parts solely by optimizing SLM technology parameters. The crystalline W powder with a concentrated grain size was used as the raw material, and substrate preheating was adopted to prepare the W structural component with a lattice structure by selective laser melting (SLM). The processed samples were subsequently subjected to heat treatment at 1100℃, 1400℃, 1700℃and 1900℃ for 2 hours. The mechanical properties and microstructure of the specimens at different heat treatment temperatures were analyzed. The results indicate that the optimal volumetric energy density for obtaining a theoretical density of 96.2% is around 972 J/mm3. After the heat treatment at 1700℃, the samples achieved the best mechanical performance, with an ultimate compressive strength and microhardness reaching 1200 MPa and 457HV, respectively. The fracture morphology shows cleavage fracture characteristics, and microcracks were largely eliminated after the heat treatment at 1700℃, indicating strong metallurgical bonding between layers and particles.
Study on the structural optimization of a gas distributor of vertical adsorption tower based on CFD
Authors: Guo Bingchao , Yan Yongfei , Li Cunlei , Zeng Lei , Ning Yiwan 
Published: December 2023

Abstract
The vertical adsorption tower serves as a crucial tool for the adsorption and separation of methane in the coalbed. Nonetheless, the complexities and variations inherent in the adsorption process pose challenges that hinder the fulfillment of actual production requirements. To enhance the uniformity of gas distribution, the installation of an appropriate gas distributor becomes necessary. To investigate this matter, computational fluid dynamics (CFD) was employed to conduct numerical simulations comparing the effects of various gas distributors, including no gas distributor, conical gas distributor, truncated cone gas distributor, and a combination of sieve plate and baffle on the flow field of coalbed methane within the vertical adsorption tower. The simulation results were evaluated based on the smoothness of the velocity vector and velocity curve, enabling the determination of the uniformity of the gas distribution. With the installation of a single sieve plate as the gas distributor, the majority of airflow predominantly exits from the middle section of the vertical adsorption tower; however, the distribution is still insufficiently uniform. The incorporation of Type I and Type II gas distributors improved the gas flow field to some extent, but uneven distribution persisted. Notably, the installation of a type III gas distributor consisting of a combination of sieve plate and baffle enhances the uniformity of gas distribution. Further optimization of the type III gas distributor revealed that the most favorable outcome, with the greatest uniformity and effectiveness, occurs when the baffle diameter (d) measures 0.1 m and the distance (h) between the sieve plate and the baffle measures 0.15 m, resulting in a ratio of (d) to (h) equal to k = 1.5.
Ynet: Research on Deep Learning Model Driven by Multi-scale Analysis and Its Application to Image Segmentation
Authors: Meng Wenzhe , Zhu Xiaoliang , Li Hanyu , Li Yanxiang , Ma Dehua , Xu Siping 
Published: December 2023

Abstract
In the field of image reconstruction and defuzzification, processing of images using frequency domain features of images is becoming popular. In the field of medical image segmentation, however, there are relatively few studies on processing using frequency domain features. Inspired by this point, this paper proposes a method of wavelet transform-based image enhancement module, which aims to separate the high-frequency and low-frequency features in the original image, and then the image is enhanced with features to improve the segmentation accuracy of the model. A single-branch network like Unet will mix high-frequency and low-frequency information during the learning process, resulting in the discarding of some useful information, to avoid this, this paper designs a novel two-branch network named YNet, which employs two encoders that are used to learn the high-frequency and low-frequency information of the image, respectively. To effectively fuse the features learned by the two encoders, this paper introduces a frequency feature fusion module based on the attention mechanism to fuse the features of the two branches, and this fusion method effectively alleviates the problem of information loss brought by the traditional feature fusion. Then it is input into the same decoder for processing. The results show that this study achieved excellent segmentation accuracy on the Kvasir-SEG, CVC-ClinicDB, ISIC2018, and DSB2018 datasets, as demonstrated by the mDice, mIoU, mPrecision, and mRecall metrics. This is of great significance for the medical image segmentation field regarding the effective integration of deep learning and machine learning.
PlGF and VEGF-A/PlGF heterodimer are crucial in the recruitment and activation of immune cells during choroidal neovascularization
Authors: Tarallo Valeria , Trotta Sara Magliacane , Panico Sonia , D’Orsi Luca , Mercadante Grazia , Cicatiello Valeria , Falco Sandro 
Published: December 2023

Abstract
Recruitment and activation of inflammatory cells, such as retinal microglia/macrophages, in the sub-retinal space contribute significantly to the pathogenesis of age-related macular degeneration (AMD). In this study, we utilized the full functional knockout of placental growth factor (PlGF), the PlGF-DE knockin mouse, to investigate the functional role of vascular endothelial growth factor (VEGF-A), PlGF and VEGF-A/PlGF heterodimer in immune homeostasis and activation during pathological laser-induced choroidal neovascularization (CNV). Our findings demonstrate that, while there is no difference in healthy conditions, PlGF-DE-Ki mice exhibit decreased microglia reactivity and reduced recruitment of both microglia and monocyte-macrophages, compared to wild-type mice during laser-induced CNV. This impairment is associated with a reduction in VEGF receptor 1 (VEGFR-1) phosphorylation in the retinae of PlGF-DE-Ki mice compared to C57Bl6/J mice. Corroborating these data, intravitreal delivery of PlGF or the heterodimer in PlGF-DE-Ki mice rescued the immune cell response at the early phase of CNV compared to VEGF-A delivery. In summary, our study suggests that targeting PlGF and the VEGF-A/PlGF heterodimer thereby preventing VEGFR-1 activation could represents a potential therapeutic approach for the management of inflammatory processes in diseases such as AMD.
Design optimization of effective modulus through variation in pore geometries of Stainless Steel 316L
Authors: Bhowmik Krishnendu , Dey Swati , Datta Sagnik , Das Apurba , Chowdhury Amit Roy , Datta Shubhabrata 
Published: December 2023

Abstract
Three-dimensional finite element analyses are carried out using cubic shaped representative volume element with spherical and ellipsoidal pores. The aim of this present study is to design a metal block with targeted effective modulus of elasticity in different directions with various types of pore morphology and %porosity. Parametric study in terms of porosity percentage, number of pores, axis ratio (ratio of major to minor axis of ellipsoidal pores) and orientation angle are performed. Scaffold used for bone grafting is anisotropic in nature. Adequate selection of the parameter can define the effective moduli in X and Y directions. Design optimization is employed using genetic algorithm to achieve the required properties. Artificial neural network metamodels are developed using finite element simulated data to act as the objective functions. In present study stainless steel (316L) is considered for the analysis. However, present method can be applied in material independent way.
Genetic diversity analysis of Pandanus amaryllifolius using EST-SSR and iPBS markers
Authors: Sidek Norhafizah , Tan Boon Chin , Mebus Katharina , Taheri Sima , Budi Setiawan Agus , Teo Chee How 
Published: December 2023

Abstract

Pandanus amaryllifolius, a tropical fragrant screw pine, is commonly used in cooking and traditional medicine. Despite the fact that various studies have been conducted on the metabolite, transcriptome and proteome profiles of P. amaryllifolius, there is a scarcity of molecular markers suitable for genetic improvement. Therefore, this research aimed to analyse the genetic diversity of P. amaryllifolius using EST-SSR markers derived from transcriptome dataset and iPBS marker system. Using the leaf transcriptomes of three biological replicates, we successfully generated 157,467 unigenes from P. amaryllifolius, with an average length of 1,084 base pairs. Of these, 66,820 EST-SSRs were identified, presenting one SSR for every 2.6 kb of distribution density. The most common SSRs were dinucleotides (45.54%), followed by mononucleotides (32.65%). Out of 48,816 developed EST-SSR markers, we randomly selected 30 for the genetic diversity analysis among 24 P. amaryllifolius accessions, together with sixteen iPBS markers for P. amaryllifolius diversity study. Only two EST-SSR and three iPBS markers showed polymorphic bands, indicating a low polymorphism level among 24 P. amaryllifolius accessions. Diversity analysis using EST-SSR markers revealed 3 polymorphic bands with an average polymorphic information content (PIC) value of 0.26. Meanwhile, the iPBS markers generated10 polymorphic bands with an average PIC value of 0.16. The UPGMA cluster analysis differentiated accessions into 5 clusters with iPBS markers and 2 clusters with EST-SSR markers, indicating that iPBS marker system is more effective in identifying the polymorphism of this species. The present work provides a great resource for identifying genes and developing markers in P. amaryllifolius.
RotMix and RotCom: Two Regularization Strategies with Contrastive Learning for Few-shot Classification
Authors: Ma Kunkun , Zhang Baopeng , Teng Zhu , Zou Junnan , Fan Jianping 
Published: December 2023

Abstract
Few-shot learning (FSL) aims to recognize new classes by adapting prior knowledge with extremely limited few-shot examples. The key challenge lies in eliminating the induction bias between SEEN classes and UNSEEN classes. Performance improvements mainly focus on enhancing feature representations or category embeddings, or designing new loss functions, while largely ignoring efficient data augmentation techniques for enhanced training. In light of this, we propose a novel embedding model called MixNet, which encodes the diversity of classes to eliminate induction bias, and evolves prior knowledge through contrastive learning. It captures sketchy patterns and focuses on detailed characteristics. Our contrastive adaptation model implicitly learns the UNSEEN embeddings to alleviate the over-fitting problem with limited labeled data.\textbf{ } Furthermore, we propose two data augmentation methods named RotMix and RotCom to exploit the extra information, which can boost the generalization ability of few-shot models. The proposed RotMix and RotCom involve random rotation and random grayscale of any patch in the original image, which encourage the model to pay attention to multiple discriminative regions of the object rather than the most salient discriminative region. Extensive experiments are conducted on widely used few-shot recognition benchmarks, including miniImageNet and tieredImageNet, verifying that our MixNet with RotMix and RotCom can boost significant performance compared with both classic and recent popular metric-based methods. Besides, we also compare the proposed methods against other augmentation methods such as Cutout, Mixup, and CutMix. Experimental results reflect the competing performance of RotMix and RotCom.
Glutathione-depleting liposome adjuvant for augmenting the efficacy of a Glutathione covalent inhibitor oridonin for acute myeloid leukemia therapy
Authors: Liu Yi , Wang Xiaoning , Feng Hui , Li Xinyan , Yang Runyu , Zhang Mengyao , Du Yue , Liu Ruimin , Luo Minna , Li Zhiyi , Liu Bo , Wang Jincheng , Wang Wenjuan , An Feifei , Niu Fan , He Pengcheng 
Published: December 2023

Abstract
Background
Discrepancies in the utilization of reactive oxygen species (ROS) between cancer cells and their normal counterparts constitute a pivotal juncture for the precise treatment of cancer, delineating a noteworthy trajectory in the field of targeted therapies. This phenomenon is particularly conspicuous in the domain of nano-drug precision treatment. Despite substantial strides in employing nanoparticles to disrupt ROS for cancer therapy, current strategies continue to grapple with challenges pertaining to efficacy and specificity. One of the primary hurdles lies in the elevated levels of intracellular glutathione (GSH). Presently, predominant methods to mitigate intracellular GSH involve inhibiting its synthesis or promoting GSH efflux. However, a conspicuous gap remains in the absence of a strategy capable of directly and efficiently clearing GSH.
Methods
We initially elucidated the chemical mechanism underpinning oridonin, a diminutive pharmacological agent demonstrated to perturb reactive oxygen species, through its covalent interaction with glutathione. Subsequently, we employed the incorporation of maleimide-liposomes, renowned for their capacity to disrupt the ROS delivery system, to ameliorate the drug's water solubility and pharmacokinetics, thereby enhancing its ROS-disruptive efficacy. In a pursuit to further refine the targeting for acute myeloid leukemia (AML), we harnessed the maleic imide and thiol reaction mechanism, facilitating the coupling of Toll-like receptor 2 (TLR2) peptides to the liposomes' surface via maleic imide. This strategic approach offers a novel method for the precise removal of GSH, and its enhancement endeavors are directed towards fortifying the precision and efficacy of the drug's impact on AML targets.
ResultsWe demonstrated that this peptide-liposome-small molecule machinery targets AML and consequently induces cell apoptosis both in vitro and in vivo through three disparate mechanisms: (I) Oridonin, as a Michael acceptor molecule, inhibits GSH function through covalent bonding, triggering an initial imbalance of oxidative stress. (II) Maleimide further induces GSH exhaustion, aggravating redox imbalance as a complementary augment with oridonin. (III) Peptide targets TLR2, enhances the directivity and enrichment of oridonin within AML cells.
ConclusionsThe rationally designed nanocomplex provides a ROS drug enhancement and targeted delivery platform, representing a potential solution by disrupting redox balance for AML therapy.
Using a Physics Constrained U-Net for Real-Time Compatible Extraction of Physical Features from WEST Divertor Hot-Spots
Authors: Gorse Valentin , Mitteau Raphaël , Marot Julien 
Published: December 2023

Abstract

The WEST (W Environment in Steady-state Tokamak) divertor serves as the primary element for heat exhaust and contributes critically to plasma control. The divertor receives intense heat fluxes, potentially leading to damage to the plasma facing units. Hence, it is of major interest for the safety of divertor operation to detect and characterize the hot spots appearing on the divertor surface. This is done through the use of infrared (IR) cameras, which provide a thermal mapping of the divertor surface. In this work, a knowledge-informed divertor hot spot detector is demonstrated, that explicitly accounts for hot spot structure and temperature repartition. A novel neural network, termed as Constrained U-Net, is proposed, which uses as input the bounding boxes of hot spots from prior automatic detection. The Constrained U-Net addresses jointly image segmentation and regression of physical parameters, while remaining compatible with the practical constraints of real-time use. The detector is trained on simulated data and applied to real-world infrared images. On simulated images, it yields a precision of 0.98, outperforming a classical U-Net, and Max-Tree. Visual results obtained on real-world acquisitions from the WEST Tokamak illustrate the reliability of the proposed method for safety studies on hot spots.
Self-management of COPD supported by eHealth: Patients’ attitudes towards monitoring, risk prediction and virtual coaching
Authors: Hurmuz Marian Z. M. , Braake Eline te , Jansen-Kosterink Stephanie M. , Grünloh Christiane 
Published: December 2023

Abstract
Purpose
Chronic obstructive pulmonary disease (COPD) has a high burden on patients, tremendously affecting their quality of life. For patients to be more pro-active, self-management is important. To improve self-management, health data collection is needed for monitoring, which can be used for risk predictions and personalised coaching. Within the RE-SAMPLE project, we want to include these features in an eHealth technology. This study aims to investigate the attitudes of adults with COPD towards health monitoring, risk predictions and virtual coaching.
Methods
We conducted workshops and interviews with persons diagnosed with COPD. Six persons participated in the workshops which focused on topics for virtual coaching. 10 Persons participated in the interviews focusing on monitoring, risk prediction and virtual coaching.
Results
For participants, collecting and having access to health data is an important aspect of health monitoring. Furthermore, participants were positive towards a technology which visualizes health data for monitoring. Regarding risk predictions, participants were not all convinced about its usefulness. Finally, participants were quite positive about including a virtual coach within a self-management eHealth technology.
Conclusion
Taking all into consideration, we noticed that most participants felt that persons who are more recently diagnosed with COPD would benefit more from using a self-management eHealth technology. Based on our findings, we discuss implications for design in this paper.
Research on Control of Single-point Magnetic Levitation System based on Improved DDPG
Authors: Wang YongZhuang , Zhang Zhenli , Cao Zehua , Yang Jie , Yu Jintao , Qin Yao 
Published: December 2023

Abstract
To address the limitations of the traditional maglev control algorithm that relies on mathematical models and is difficult to deploy, a single-point maglev system controller with improved DDPG based on reinforcement learning is designed. First, the experimental platform of a single-point maglev system and its simulation model are built based on physical parameters; second, the piecewise inverse proportional reward function is proposed to improve the steady-state accuracy and response time of the maglev system; then, the DDPG control flow is improved to make the controller meet the requirements of physical deployment; Finally, the effects of reward function, training step, and model variation on the control performance are analyzed by software simulation and experimental comparison. The results show that the improved DDPG controller with a piecewise inverse proportional reward function shortens the response time and reduces the steady-state error of the system. In addition, the control results obtained by using the same parameters of the controller with different models are basically the same, which verifies the advantage of model-independent reinforcement learning. It is a good reference for the control of single-point levitation-like systems.
Early Diagnosis of Solitary Functioning Kidney: Comparing the Prognosis of Renal Agenesis and Multicystic Dysplastic Kidney
Authors: Flögelova Hana , Bouchalova Katerina , Smakal Oldrich , Halek Jan , Langova Katerina , Cizkova Katerina 
Published: December 2023

Abstract
Background
Individuals with congenital solitary functioning kidney (SFK) are at an increased risk of kidney damage. According to some studies, the risk is higher in unilateral renal agenesis (URA) than in unilateral multicystic dysplastic kidney (UMCDK). We hypothesized that with early detection of children with URA and UMCDK, there would be no difference in the presence of hypertension, proteinuria, and reduced glomerular filtration rate (GFR) between URA and UMCDK.
Methods
Based on a long-term follow-up protocol, we evaluated a cohort of 160 children followed from birth for SFK (84 with URA and 76 with UMCDK) detected by prenatal or routine neonatal ultrasound screening. Hypertension, proteinuria and elevated GFR were monitored as markers of kidney damage. We compared the characteristics and outcomes of the subgroups of children with URA and UMCDK.
Results
GFR was reduced in 42 (26.2%) children, of whom 41 showed only mild reduction. Hypertension and proteinuria were found in 22 (13.8%) and 14 (8.8%) children, respectively.
Combined kidney damage was present in 57 (35.6%) children. The UMCDK and URA subgroups differed in GFR at final examination, with UMCDK patients being significantly more likely to have normal GFR compared to URA patients (82% vs 67%; p = 0.039).
Conclusions
One third of the children showed signs of SFK damage, albeit mild. Patients with URA had reduced GFR significantly more often than those with UMCDK, but did not differ in the rates of hyperfiltration injury or congenital anomalies of the kidneys and urinary tract (CAKUT) in SFK.
Genetic influence on bone mineral density for Japanese women: a twin study
Authors: Saeki Soichiro , Tomizawa Rie , Minamitani Kaori , Nakata Ken , Honda Chika 
Published: December 2023

Abstract
Background
Osteoporosis is a major risk factor for fractures among the elderlies. Despite osteoporosis being a significant concern in super-aged societies such as Japan, the heritability of bone mineral density within the Japanese populace remains unexplored.
Methods
The bone area ratio (BAR, %) of 298 healthy, female Japanese twins (comprising 149 pairs, 136 monozygotic and 13 dizygotic twin pairs) registered in the Osaka University Twin Registry was measured using quantitative ultrasound. Classical twin analysis was employed to ascertain the heritability of bone mineral density.
Results
The heritability of bone mineral density for the entire cohort was 0.51 (95% confidence intervals (CI) 0.38–0.63). For the subset of subjects younger than 50 years, the effects of menopause were adjusted, and the best-fit model was also found to be the AE model, with a heritability estimate of 0.53 (95% CI: 0.34–0.72).
Conclusions
Compared to women from other countries, Japanese women appear to exhibit relatively lower heritability of bone mineral density. Consequently, environmental factors may exert a more significant influence on osteoporosis in Japanese women compared to women of other races and ethnicities.