bluuebunny/crossref_metadata_2025_split huggingface dataset:
MetaPhyNet: intelligent design of large-scale metasurfaces based on physics-driven neural network
Authors: Su Jian Lin , You Jian Wei , Chen Long , Yu Xin Yi , Yin Qing Chun , Yuan Guo Hang , Huang Si Qi , Ma Qian , Zhang Jia Nan , Cui Tie Jun 
Published: May 2024

Abstract
Metasurface has garnered extensive attention across multiple disciplines owing to its profound capability in electromagnetic (EM) manipulations. To determine its EM characteristics accurately, full-wave simulations are essential. These simulations necessitate significant amounts of time and memory resources, hindering the efficiency of the design process. In this article, we propose MetaPhyNet, a novel physics-driven neural network based on temporal coupled-mode theory (CMT) to address the challenges of low efficiency and high memory consumption in large-scale metasurface design. In the proposed approach, a surrogate model is developed to achieve rapid prediction of the EM responses of ultra-large-scale metasurfaces. In comparison with the full-wave EM simulation, the proposed model reduces the simulation time of the ultra-large-scale metasurface by up to two orders of magnitude and the memory consumption by more than two orders of magnitude. Our proposed approach aims to enhance the efficiency and intelligence in metasurface design by leveraging the principles of CMT within a neural network framework. Through this innovative integration of physics-based modeling and machine learning, we seek to achieve significant advancements in the design efficiency of metasurfaces. We apply the proposed model to optimize the design of two metasurface absorbers to showcase the effectiveness of our proposed approach. Simulations and experimental results are provided to demonstrate the value and impact of our approach in addressing existing challenges in full-wave EM simulation-based design optimizations of metasurfaces.
Aerodynamic modeling and performance analysis of model predictive controller for fixed wing vertical takeoff and landing unmanned aerial vehicle
Authors: Getachew Melkamu Tadesse , Zeleke Dinku Seyoum 
Published: May 2024

Abstract
This research focuses mainly on the aerodynamic modelling and performance analysis of a model predictive controller for a hybrid fixed-wing vertical takeoff and landing of unmanned aerial vehicle. The aerodynamics, which comprises several aerodynamic characteristics including the lift, drag, and thrust coefficients, is modelled using Newton’s second law of motion. The force and moment equations were obtained, and they were then converted into matrix and state equation form, together with the transformation matrices. The essential equations with six degrees of freedom (6 DoF) and 12 state matrices including the control input and manipulating variables were obtained. The proposed model predictive controller (MPC) was designed using the optimal model predictive controller design parameters, such as a sampling time of 0.1, a prediction horizon of 15, a control horizon of 3 and additional controller settings. With a settling period of 3 s, an overshoot of 0.5865, and a steady state inaccuracy of 0.00785, the MATLAB simulation demonstrates that the system variables, including roll, pitch, and yaw, are stabilized. This MPC control is more effective in anticipating and optimizing the UAV than other control strategies. Eventually, the controller’s simulation on MATLAB Simulink demonstrates the controller’s ability to stabilize and control the system in a real-time application. Autonomous vertical takeoff and landing operations depend heavily on the mathematical model and architecture of the flight controller. Among the uses are inspection, monitoring, and rescue.
Microstructural characterization and analysis of nitinol-based self-healing metals matrix composite of A356 alloy produced by high-pressure die casting
Authors: Sharma Sumit , Nandan Gopal , Tyagi R K 
Published: May 2024

Abstract
A self-healing non-ferrous metal-matrix composite is prepared by the high-pressure die-casting process. It includes casting set-up, sample preparation of metal matrix composite (MMC), microstructural characterization, and analysis of its ability to close the crack. Aluminum alloy (A356) is deployed as a matrix material in the MMC. Nitinol is a smart alloy produced by a combination of Nickel and Titanium in equal mass proportion. Apart from excellent mechanical properties it also exhibits super-elasticity and shape-memory effect. The wire of the Nitinol is integrated as reinforcement within the matrix of A356 alloy through a high-pressure die-casting process. The recovery percentage of the metal matrix composite and microstructural evaluation are reported. The deployment of shape memory wire provides the ability to recover the matrix material even from plastic strain by just heating the sample slightly above the activation temperature of the Nitinol wire. Microstructural evaluation indicates fair integration of the reinforcement within the matrix material. Gaining the ability for 30.27% angular restoration and 19.37% crack closer is a very positive sign for designing self-healing metallic materials.
Leakage detection of an acoustic emission pipeline based on an improved transformer network
Authors: Lang Xianming , Wang Chunyu 
Published: May 2024

Abstract
Pipeline leakage detection is an integral part of pipeline integrity management. Combining AE (Acoustic Emission) with deep learning is currently the most commonly used method for pipeline leakage detection. However, this approach is usually applicable only to specific situations and requires powerful signal analysis and computational capabilities. To address these issues, this paper proposes an improved Transformer network model for diagnosing faults associated with abnormal working conditions in acoustic emission pipelines. First, the method utilizes the temporal properties of the GRU and the positional coding of the Transformer to capture and feature extract the data point sequence position information to suppress redundant information, and introduces the largest pooling layer into the Transformer model to alleviate the overfitting phenomenon. Second, while retaining the original attention learning mechanism and identity path in the original DRSN, a new soft threshold function is introduced to replace the ReLU activation function with a new threshold function, and a new soft threshold module and adaptive slope module are designed to construct the improved residual shrinkage unit (ASB-STRSBU), which is used to adaptively set the optimal threshold. Finally, pipeline leakage is classified. The experimental results show that the NDRSN model is able to make full use of global and local information when considering leakage signals and can automatically learn and acquire the important parameters of the input features in the spatial and channel domains. By optimizing the GRU improved Transformer network recognition model, the method significantly reduces the model training time and computational resource consumption while maintaining high leakage recognition accuracy. The average accuracy reached 93.97%. This indicates that the method has good robustness in acoustic emission pipeline leakage detection.
Prediction on partial replacement of cement and coarse aggregate by zeolite powder and steel slag in high-performance concrete
Authors: R Arvind Saravan , Annadurai R 
Published: May 2024

Abstract
High performance concrete is obtained by the inclusion of mineral admixtures like silica fume and fly ash in the concrete. The research explores the viability and performance of sustainable concrete by introducing zeolite powder as a partial substitute for cement and steel slag as a partial replacement for coarse aggregate in M-70 grade concrete. Zeolite powder, possessing pozzolanic properties, is a natural or synthetic aluminosilicate material, while steel slag is an industrial byproduct with potential as an alternative aggregate source. The main objective is to investigate the impact of zeolite powder and steel slag on the development of High-Performance Concrete (M-70) in accordance with Bureau of Indian standards. The formulation of high-performance concrete involved replacing 12.5%, 15%, and 17.5% of the cement with zeolite powder and varying the proportion of steel slag as a replacement for coarse aggregate (ranging from 30% to 55%). A comprehensive mechanical test was conducted on these specimens and compared with conventional concrete. Among the 19 mixes, the optimal combination was identified, incorporating 15% zeolite powder as a cement replacement and 45% steel slag as a coarse aggregate replacement, resulting in superior performance compared to conventional concrete. This mix was further studied for non-destructive testing, and microstructural analysis. Subsequently, the experimental results were compared with predicted outcomes using the Taguchi method. The close alignment between the values obtained experimentally and those predicted further validates the effectiveness of the optimized mix.
A multifidelity approach to continual learning for physical systems
Authors: Howard Amanda , Fu Yucheng , Stinis Panos 
Published: May 2024

Abstract
We introduce a novel continual learning method based on multifidelity deep neural networks. This method learns the correlation between the output of previously trained models and the desired output of the model on the current training dataset, limiting catastrophic forgetting. On its own the multifidelity continual learning method shows robust results that limit forgetting across several datasets. Additionally, we show that the multifidelity method can be combined with existing continual learning methods, including replay and memory aware synapses, to further limit catastrophic forgetting. The proposed continual learning method is especially suited for physical problems where the data satisfy the same physical laws on each domain, or for physics-informed neural networks, because in these cases we expect there to be a strong correlation between the output of the previous model and the model on the current training domain.
The brain insulin receptor gene network and associations with frailty index
Authors: Selenius Jannica S , Silveira Patricia P , Haapanen Markus J , von Bonsdorff Mikaela , Lahti Jari , Eriksson Johan G , Wasenius Niko S 
Published: May 2024

Abstract

Objective
To investigate longitudinal associations between variations in the co-expression-based brain insulin receptor polygenic risk score and frailty, as well as change in frailty across follow-up.

Methods
This longitudinal study included 1605 participants from the Helsinki Birth Cohort Study. Biologically informed expression-based polygenic risk scores for the insulin receptor gene network, which measure genetic variation in the function of the insulin receptor, were calculated for the hippocampal (hePRS-IR) and the mesocorticolimbic (mePRS-IR) regions. Frailty was assessed in at baseline in 2001–2004, 2011–2013 and 2017–2018 by applying a deficit accumulation-based frailty index. Analyses were carried out by applying linear mixed models and logistical regression models adjusted for adult socioeconomic status, birthweight, smoking and their interactions with age.

Results
The FI levels of women were 1.19%-points (95% CI 0.12–2.26, P = 0.029) higher than in men. Both categorical and continuous hePRS-IR in women were associated with higher FI levels than in men at baseline (P &lt; 0.05). In women with high hePRS-IR, the rate of change was steeper with increasing age compared to those with low or moderate hePRS-IR (P &lt; 0.05). No associations were detected between mePRS-IR and frailty at baseline, nor between mePRS-IR and the increase in mean FI levels per year in either sex (P &gt; 0.43).

Conclusions
Higher variation in the function of the insulin receptor gene network in the hippocampus is associated with increasing frailty in women. This could potentially offer novel targets for future drug development aimed at frailty and ageing.
A Comparative Analysis of Secreted miRNAs Reveals Candidate Biomarkers for Pleural Mesothelioma Detection
Authors: Kraft A , Meerang M , Kirschner M B , Boeva V , Opitz I 
Published: May 2024

Abstract

Background
MicroRNAs secreted by tumour cells through exosomes or in non-encapsulated form, were shown to promote tumour growth and treatment resistance, underscoring their potential as cancer biomarkers.

Aims
Here, we compare miRNAs secreted by pleural mesothelioma (PM) primary cells with miRNAs secreted by non-PM cells, in order to identify diagnostic biomarkers of this devastating disease.

Methods
We established primary cell cultures from pleural effusion of 12 PM and 7 non-PM patients. Secreted miRNAs were profiled as: (1) total secreted miRNA in cell culture supernatant (Sup), and (2) exosomal (Exo) miRNAs. Exosomes were extracted using iZON qEV columns. RNA was extracted with mirVana PARIS kit. Sequencing libraries were prepared using the QIAseq miRNA Library Kit (Qiagen). Reads were mapped on the mature miRNA sequences (MirBaseDB), followed by DESeq2 differential expression analysis. MiRNA target genes were selected using MirDB and functionally annotated using DAVID.

Results
We identified 309 and 84 deregulated miRNAs in PM-Exo and PM-Sup samples, respectively (p-value &lt;0.05, Fig. 1A). Among the up-regulated miRNAs, we found let-7c-3p and miR-16-5p, which are known tumour suppressors, and miR-23a-3p and miR-30a-5p (Fig. 1B). Interestingly, miR-30a-5p belongs to the same family as miR-30e-5p, which together with miR-23a-3p was previously identified as part of the long survival signature in PM. Additionally, we identified 11 miRNAs that showed up-regulation in both PM-Exo and PM-Sup. Further analysis of these candidate miRNAs revealed that exosomal expression of miR-30a-5p was a significant predictor of patient survival (Fig. 1C). Finally, we identified potential target genes of the 11 up-regulated miRNAs - the target genes were significantly associated with transcriptional regulation and cell division (p-value &lt;0.05).

Conclusion
Our comparative analysis of secreted miRNAs identified 11 candidate biomarkers for PM. Our findings emphasise the importance of the PM secretome in advancing our understanding of mesothelioma biology and discovering novel cell-free biomarkers. Further in-depth analyses are currently underway.
Investigating the Effect of Liver Regeneration on Tumor Growth: Development of a Mouse Model with Orthotopic Implantation of Patient-derived HCC Organoids
Authors: Sedlaczek P , Haak F , Aegerter N L E , Müller P , Piscuoglio S , Coto-Llerena M , Soysal S D , Hess G F , Kollmar O 
Published: May 2024

Abstract

Background
Recurrence after hepatocellular carcinoma (HCC) treatment is a significant problem. It affects more than 70% of patients undergoing liver resection. Recurrence can arise from undetected micro metastasis or de novo cancer. Clinical and experimental studies suggest that liver regeneration ensuing surgical resection may activate occult micro-metastasis leading to regeneration induced tumor recurrence. However, in vivo patient-derived organoid (PDO) HCC models that are translatable to patient tumors are sparse.

Aims
Here, we aim to establish a new in vivo model to understand the impact of liver regeneration on HCC tumor growth.

Methods
PDOs were generated from HCC tissue obtained from patients undergoing liver resection at the Clarunis University Digestive Health and Care Center and transduced with firefly luciferase. Implantation was performed via laparotomy and orthotopic injection of the organoids in the right superior liver lobe. Tumor growth is monitored by in vivo bioluminescence imaging until the endpoint of the experiment. As a primary endpoint tumor growth two weeks after liver resection was defined. Experimental groups underwent either minor (30%) or major (65%) hepatectomy of tumor-free liver, whereas the control group received a re-laparotomy with subsequent closure of the abdomen. Normal liver and tumor tissue were characterized using immunohistochemistry.

Results
Two HCC-PDO lines were successfully implanted. Compared to the control, after minor and major liver resection the mean weight increased significantly to 0.82% (p &lt; 0.0001) respectively 0.99% (p &lt; 0.0001). Preliminary data about the tumor volume have yet to be concluded. Histology and immunohistochemistry staining for HCC confirmed the origin of the PDOs from the original patient tumor.

Conclusion
The establishment of an orthotopic xenograft mouse model for HCC PDO was successful. Through liver resection, a regenerative environment could be achieved, to investigate the molecular behavior of HCC recurrence after surgery. This offers the basis to study potential new targets and mechanisms to improve HCC-treatment.
Spatial Transcriptomics Reveals Interaction of Injury-Derived Osteopontin with Mesothelial Cells in Serosal Scarring
Authors: Bayer J , Slade B , Yarahmadov T , Sanchez-Taltavull D , Purvanov V , Borbély Y , Candinas D , Legler D , Kubes P , Stroka D , Zindel J 
Published: May 2024

Abstract

Background
Abdominal surgeries are often live-saving procedures. However, surgical interventions in the peritoneal cavity can cause the formation of post-surgical adhesions. These irreversible scar bands can trigger severe complications, such as chronic pelvic pain, small bowel obstruction, and infertility in women. Unfortunately, no effective treatment options for adhesion patients exist. On a cellular level, mesothelium-derived mesenchymal myofibroblasts have been identified as key pro-fibrotic players in adhesion formation.

Aims
Our aim is to study the molecular mechanisms of mesothelial cell recruitment in serosal repair and scarring, and thereby to identify potential targets for specific pharmacological anti-adhesion treatments.

Methods
We used a mesothelial cell reporter mouse system (Wt1CreERT2xRosa26tdTomato) and experimental injury models to study the differences of mesothelial cell recruitment to sites of adhesion formation in comparison to wound sites healing scar-free. To answer how injury zones affect the accumulation of mesothelial cells, we used untargeted spatial transcriptomics, identifying candidate molecules that were i) upregulated in adhesion formation sites, ii) not highly expressed in scar-free wound sites, and iii) had the potential to interact with mesothelial cells.

Results
We observed strong spatiotemporal correlation between accumulation of tdTomato+ cells and consecutive scarring. Spatial deconstruction of scar-specific signaling identified the candidate molecule Secreted phosphoprotein 1; an inflammatory zone-specific gene that encodes Osteopontin (OPN). After confirming increased OPN protein levels 7d post-surgery, we investigated its effect on adhesion formation using Spp1-/- mice. Indeed, Spp1-deficient mice showed significantly lower adhesion scores compared to control mice. Mechanistically, recombinant OPN had no chemotactic effect on primary human mesothelial cells, however triggered the upregulation of transcription factors associated with mesothelial-to-mesenchymal transition.

Conclusion
Together, these findings suggest a pivotal role for OPN in linking inflammation at injury sites with mesothelial cell recruitment in post-surgical serosal scarring. Therefore, OPN represents a potential target for novel pharmacological strategies to specifically inhibit scarring without affecting normal wound repair.
Long-Term Follow-Up after Ureteral Reimplantation in Children: A 12-Year Analysis
Authors: Gerwinn T , Zellner M , Prouza A , Kennedy U , Horst M , Mazzone L 
Published: May 2024

Abstract

Background
Ureteral reimplantation (UR) is a well-established procedure, yet there exists a notable absence of evidence-based guidelines for postoperative follow-up. Existing literature suggests that routine follow-up extending beyond one year may not yield significant advantages, particularly for asymptomatic children. However, it is crucial to acknowledge that many studies supporting this assertion rely on relatively short observation periods.

Aims
This study seeks to address the potential emergence of late-presenting complications post UR. Our objective is to comprehensively evaluate our patient cohort for the incidence of conditions warranting the establishment of standardized, long-term follow-up practices after UR.

Methods
Retrospective review of 137 medical records from children who underwent UR at our institution between January 2006 and June 2013. Inclusion criteria required a minimum 10-year postoperative follow-up.

Results
Fifty-three renal units in 34 children met inclusion criteria. Ureterovesical junction (UVJ) obstruction occurred in 7.5% of the units and was diagnosed within eight months after UR. Obstruction occurred exclusively after Politano-Leadbetter reimplantation and was silent in all cases. Postoperative UTIs occurred in 9 children. Notably, these were all singular events without signs for recurrent reflux. A decade after surgery, one child developed chronic kidney disease (CKD) due to preexisting reflux nephropathy (RN), while one child was newly diagnosed with RN during follow-up despite the timely surgical correction of vesicoureteral reflux (VUR). or hypertension linked to RN were recorded.

Conclusion
Children with uncomplicated postoperative recoveries within the first-year, devoid of evident UVJ obstruction, exhibit a low subsequent risk, suggesting limited benefit from repeated scheduled long-term follow-up. Nevertheless, we recommend that general practitioners conduct regular monitoring, considering individual risk factors, to enhance the detection of late-onset hypertension or proteinuria as potential indicators of RN during adolescence.
Retroperitoneoscopic Renal Surgery in Infants &lt;10kg, Description of First 50 Patients
Authors: Sanchez O , Birraux J , Andrieu Vidal I , Broennimann E , Stathopoulos E , Alam M , Sommer C 
Published: May 2024

Abstract

Background
Most paediatric urologists have adopted minimally invasive surgery when approaching the kidney for reconstructive or ablative surgery. Although small weight has previously been described as a limiting factor for retroperitoneoscopic surgery, as of 2017, we have approached all non-oncological initial renal surgery by retroperitoneoscopy regardless of patient weight, with a standardised technique for port placement and initial dissection.

Aims
The aim is to present our current experience and short-term results with a minimally invasive approach to renal surgery in small patients.

Methods
We present a description of the cohort and performed operations with conversion and intra-operative complication rate.

Results
The median age of our patients is 4,7 months (26days-12months), mean weight is 5,8Kg (3,5 Kg-9,6 Kg) F:M 16:34, we performed 12 nephrectomies, 5 hemi-nephrectomies, 3 uretero-ureterostomies, 30 pyeloplasties, with 3 patients presenting with crossing vessels. No patient needed transfusion; 1 patient presented with nephrostomy catheter migration needing a second anaesthesia on day 1. We had to perform 1 conversion to open surgery because of unclear anatomy following percutaneous drainage. No patients showed significant loss of function on the remaining pole after hemi-nephrectomy.

Conclusion
The retroperitoneoscopic approach and its advantages in terms of minimal post-operative pain, quick recovery and reliable results can safely be offered to all our paediatric patients for routine and complex non-oncological renal surgery.