bluuebunny/crossref_metadata_2025 huggingface dataset:
Stereotactic Magnetic Resonance-Guided Adaptive and Non-Adaptive Radiotherapy on Combination MR-Linear Accelerators: Current Practice and Future Directions
Authors: Bryant John Michael , Weygand Joseph , Keit Emily , Cruz-Chamorro Ruben , Sandoval Maria L. , Oraiqat Ibrahim M. , Andreozzi Jacqueline , Redler Gage , Latifi Kujtim , Feygelman Vladimir , Rosenberg Stephen A.
Published: March 2023

Stereotactic body radiotherapy (SBRT) is an effective radiation therapy technique that has allowed for shorter treatment courses, as compared to conventionally dosed radiation therapy. As its name implies, SBRT relies on daily image guidance to ensure that each fraction targets a tumor, instead of healthy tissue. Magnetic resonance imaging (MRI) offers improved soft-tissue visualization, allowing for better tumor and normal tissue delineation. MR-guided RT (MRgRT) has traditionally been defined by the use of offline MRI to aid in defining the RT volumes during the initial planning stages in order to ensure accurate tumor targeting while sparing critical normal tissues. However, the ViewRay MRIdian and Elekta Unity have improved upon and revolutionized the MRgRT by creating a combined MRI and linear accelerator (MRL), allowing MRgRT to incorporate online MRI in RT. MRL-based MR-guided SBRT (MRgSBRT) represents a novel solution to deliver higher doses to larger volumes of gross disease, regardless of the proximity of at-risk organs due to the (1) superior soft-tissue visualization for patient positioning, (2) real-time continuous intrafraction assessment of internal structures, and (3) daily online adaptive replanning. Stereotactic MR-guided adaptive radiation therapy (SMART) has enabled the safe delivery of ablative doses to tumors adjacent to radiosensitive tissues throughout the body. Although it is still a relatively new RT technique, SMART has demonstrated significant opportunities to improve disease control and reduce toxicity. In this review, we included the current clinical applications and the active prospective trials related to SMART. We highlighted the most impactful clinical studies at various tumor sites. In addition, we explored how MRL-based multiparametric MRI could potentially synergize with SMART to significantly change the current treatment paradigm and to improve personalized cancer care.
Evaluation of Bortezomib-BeEAM (2BeEAM) as Chemotherapy Regimen Prior to ASCT in Patients with Mantle Cell Lymphoma
Authors: Huwyler Fabrizio , Kunz Rebekka , Bacher Ulrike , Hoffmann Michèle , Novak Urban , Daskalakis Michael , Banz Yara , Pabst Thomas
Published: March 2023

(1) Background: First-line therapy in fit MCL patients may comprise high-dose chemotherapy (HDCT) with autologous transplantation to consolidate remission before maintenance treatment. However, optimization of HDCT is an unmet clinical need given the substantial relapse rate of first-line treatment, while the use of bortezomib is a promising candidate to be added to standard HDCT. (2) Methods: We analyzed 11 consecutive patients with MCL who received bortezomib added to standard BeEAM (2BeEAM) HDCT at a single academic institution. We assessed safety, feasibility, toxicities, and survival rates. (3) Results: All patients had stage III or IV disease. We found that six patients (55%) developed new or worsening of preexisting peripheral neuropathy following administration of 2BeEAM HDCT. One patient relapsed within the first six months after HDCT, whereas three patients never reached complete remission. After a median follow-up of 22 months, the PFS was 64% and the OS 64% at the last follow-up assessment. At this time, 55% of patients were in CR. (4) Conclusions: The use of bortezomib added to standard BeEAM HDCT is associated with relevant toxicities, particularly with regards to additional neuropathy. Moreover, the anti-lymphoma efficacy of 2BeEAM HDCT appears to be modest; therefore, other therapeutic options should be evaluated for consolidation in this patient group.
Macrophages Promote Tumor Cell Extravasation across an Endothelial Barrier through Thin Membranous Connections
Authors: Genna Alessandro , Duran Camille L. , Entenberg David , Condeelis John S. , Cox Dianne
Published: March 2023

Macrophages are important players involved in the progression of breast cancer, including in seeding the metastatic niche. However, the mechanism by which macrophages in the lung parenchyma interact with tumor cells in the vasculature to promote tumor cell extravasation at metastatic sites is not clear. To mimic macrophage-driven tumor cell extravasation, we used an in vitro assay (eTEM) in which an endothelial monolayer and a matrigel-coated filter separated tumor cells and macrophages from each other. The presence of macrophages promoted tumor cell extravasation, while macrophage conditioned media was insufficient to stimulate tumor cell extravasation in vitro. This finding is consistent with a requirement for direct contact between macrophages and tumor cells. We observed the presence of Thin Membranous Connections (TMCs) resembling similar structures formed between macrophages and tumor cells called tunneling nanotubes, which we previously demonstrated to be important in tumor cell invasion in vitro and in vivo. To determine if TMCs are important for tumor cell extravasation, we used macrophages with reduced levels of endogenous M-Sec (TNFAIP2), which causes a defect in tunneling nanotube formation. As predicted, these macrophages showed reduced macrophage-tumor cell TMCs. In both, human and murine breast cancer cell lines, there was also a concomitant reduction in tumor cell extravasation in vitro when co-cultured with M-Sec deficient macrophages compared to control macrophages. We also detected TMCs formed between macrophages and tumor cells through the endothelial layer in the eTEM assay. Furthermore, tumor cells were more frequently found in pores under the endothelium that contain macrophage protrusions. To determine the role of macrophage-tumor cell TMCs in vivo, we generated an M-Sec deficient mouse. Using an in vivo model of experimental metastasis, we detected a significant reduction in the number of metastatic lesions in M-Sec deficient mice compared to wild type mice. There was no difference in the size of the metastases, consistent with a defect specific to tumor cell extravasation and not metastatic outgrowth. Additionally, with an examination of time-lapse intravital-imaging (IVI) data sets of breast cancer cell extravasation in the lungs, we could detect the presence of TMCs between extravascular macrophages and vascular tumor cells. Overall, our data indicate that macrophage TMCs play an important role in promoting the extravasation of circulating tumor cells in the lungs.
Precision Oncology Targets in Biliary Tract Cancer
Authors: Farha Nicole , Dima Danai , Ullah Fauzia , Kamath Suneel
Published: March 2023

Targeted therapies in biliary tract cancer (BTC) are emerging as options for patients not who do not respond to first-line treatment. Agents acting on tumor-specific oncogenes in BTC may target fibroblast growth factor receptor 2 (FGFR2), isocitrate dehydrogenase (IDH), B-raf kinase (BRAF), and human epidermal growth factor receptor 2 (HER-2). Additionally, given the heterogeneous genetic landscape of advanced BTCs, many harbor genetic aberrations that are common among solid tumors, including RET fusions, tropomyosin receptor kinase (TRK) fusions, and high tumor mutational burden (TMB). This review aims to provide updates on the evolving array of therapeutics available, and to summarize promising works on the horizon.
Application of Deep Eutectic Solvents (DES) for the Synthesis of Iron Heterogeneous Catalyst: Application to Sulfamethoxazole Degradation by Advanced Oxidation Processes
Authors: Puga Antón , Rosales Emilio , Pazos Marta , Sanromán María Angeles
Published: March 2023

The development of novel approaches to the remotion of pharmaceuticals in wastewater is a subject of concern due to their effect on living beings and the environment. Advanced oxidation processes and the use of relevant catalysts are feasible treatment alternatives that require further development. The development of suitable heterogeneous catalysts is a necessity. This work proposes the synthesis of an iron catalyst in a deep eutectic solvent (Fe-DES) composed of choline chloride and citric acid, which was physically and chemically characterized using SEM-EDS and TEM, FTIR, RAMAN, XRD and XPS. The characterisation confirmed the presence of iron in the form of hematite. Fe-DES was shown to be a multipurpose catalyst that can be applied in the removal of sulfamethoxazole as a reagent in the Fenton and electro-Fenton processes and as an activator of peroxymonosulfate (PMS) processes. After testing the catalyst with the aforementioned techniques, the best result was achieved by combining these processes in an electro-PMS, with great efficiency achieved by dual activation of the PMS with the catalyst and electric field, attaining total elimination at natural pH in 90 min. Furthermore, the degradation was confirmed by the detection of short-chain carboxylic acids (oxalic, succinic, and acetic) and reduction in toxicity values. These results confirm the suitability of Fe-DES to degrade high-priority pharmaceutical compounds.
Real-Time UV/VIS Spectroscopy to Observe Photocatalytic Degradation
Authors: Woo Sanguk , Jung Hyein , Yoon Yohan
Published: March 2023

In this work, we have developed a real-time UV/VIS spectroscopy method using a broadband Xenon Arc lamp to detect photocatalytic reactions in real time. A CMOS camera was used instead of an output slit to capture all spectral information simultaneously, which can enable a real-time detection of the UV/VIS absorption of the analytes within a single frame of the camera. To verify real-time spectroscopy, a wavelength calibration process was performed using three laser line filters and a didymium glass filter sample. To demonstrate that this real-time spectroscopic setup can be used for rapid measurements, MB samples were used to observe the real-time photocatalytic degradation of MB by TiO2 nanoparticles. For real-time measurement, four samples with different TiO2 nanoparticle quantities showed different photocatalytic degradation mechanisms. By plotting the spectra every 20 ms, the series of spectra clearly showed the degradation of MB in real time.
Skeletonema marinoi Extracts and Associated Carotenoid Fucoxanthin Downregulate Pro-Angiogenic Mediators on Prostate Cancer and Endothelial Cells
Authors: Calabrone Luana , Carlini Valentina , Noonan Douglas M. , Festa Marco , Ferrario Cinzia , Morelli Danilo , Macis Debora , Fontana Angelo , Pistelli Luigi , Brunet Christophe , Sansone Clementina , Albini Adriana
Published: March 2023

The exploration of natural preventive molecules for nutraceutical and pharmaceutical use has recently increased. In this scenario, marine microorganisms represent an underestimated source of bioactive products endowed with beneficial effects on health that include anti-oxidant, anti-inflammatory, differentiating, anti-tumor, and anti-angiogenic activities. Here, we tested the potential chemopreventive and anti-angiogenic activities of an extract from the marine coastal diatom Skeletonema marinoi Sarno and Zingone (Sm) on prostate cancer (PCa) and endothelial cells. We also tested one of the main carotenoids of the diatom, the xanthophyll pigment fucoxanthin (Fuco). Fuco from the literature is a potential candidate compound involved in chemopreventive activities. Sm extract and Fuco were able to inhibit PCa cell growth and hinder vascular network formation of endothelial cells. The reduced number of cells was partially due to growth inhibition and apoptosis. We studied the molecular targets by qPCR and membrane antibody arrays. Angiogenesis and inflammation molecules were modulated. In particular, Fuco downregulated the expression of Angiopoietin 2, CXCL5, TGFβ, IL6, STAT3, MMP1, TIMP1 and TIMP2 in both prostate and endothelial cells. Our study confirmed microalgae-derived drugs as potentially relevant sources of novel nutraceuticals, providing candidates for potential dietary or dietary supplement intervention in cancer prevention approaches.
Effect of Platinum Ribbons on Photoelectric Efficiencies of Dye-Sensitized Solar Cells
Authors: Lai Wen-Feng , Chiang Yu-Chih , Yueh Jiun-How , Lin Tz-Feng , Liu Jih-Hsin , Lai Ying-Nan , Lai Wen-Hsuan , Hsu Wei-Chou , Huang Chia-Yi
Published: March 2023

In this study, we fabricate a counter electrode by coating a Pt ribbon onto a fluorine-doped tin oxide glass substrate with a Pt layer. The Pt ribbon gives rise to a protrusive structure of the counter electrode, produced by photolithography, sputtering and lift-off processes. The experimental results reveal that the photoelectric efficiency of the dye-sensitized solar cell (DSSC) with the Pt ribbon (5.32%) is 21% higher than that of the DSSC without a Pt ribbon (4.38%). This infers that Pt ribbons can increase the photoelectric efficiencies of DSSCs. The DSSC with the Pt ribbon has a large photoelectric efficiency of 5.32%, not only because the protrusive structure has specific channels for directional electron transport, but also because of its large surface area. The method that is proposed herein has the advantages of a low production cost and easy fabrication that can be applied to various electrode structures.
Tribological Behavior and Self-Healing Properties of Ni3Al Matrix Self-Lubricating Composites Containing Sn-Ag-Cu and Ti3SiC2 from 20 to 800 °C
Authors: Huang Yuchun , Ma Haishu , Meng Yubo , Liu Xiyao
Published: March 2023

As a high-temperature structural material, Ni3Al matrix composites are often used to manufacture basic mechanical components that need to be used in high-temperature conditions. To meet the increasing demand for metal matrix composites with an excellent tribological performance over a wide temperature range, Ni3Al matrix self-lubricating composites containing Sn-Ag-Cu and Ti3SiC2 (NST) were synthesized via laser-melting deposition. Dry sliding friction tests of NST against Si3N4 ball were undertaken from 20 to 800 °C to investigate the tribological behavior and wear-triggered self-healing properties. The results show that the tribological behaviors of NST are strongly dependent on the testing temperature and self-healing properties. At low and moderate temperatures from 20 to 400 °C, as the Sn-Ag-Cu flows into the cracks and is oxidized during sliding friction, while the cracks on the worn surface are filled with oxides consisting mainly of Al2O3, SnO2 and CuO. At higher temperatures of 600 and 800 °C, the cracks are filled by the principal oxides of Al2O3, TiO2 and SiO2 due to the partial decomposition and oxidation of Ti3SiC2. Compared with other testing temperatures, the recovery ratio relative to the Ni3Al base alloy of the cracks on the worn surface of NST is the highest at 400 °C, which is about 76.4%. The synergistic action mechanisms of Sn-Ag-Cu and Ti3SiC2 on the crack self-healing from 20 to 800 °C play a significant role in forming a stable solid lubricating film, improving the anti-friction and wear resistance of NST. The results provide a solution allowing for metal matrix composites to achieve excellent lubrication stability over a wide temperature range by virtue of the crack self-healing properties.
A Guiding Framework for Process Parameter Optimisation of Thermal Spraying
Authors: Venkatachalapathy Viswanathan , Katiyar Nirmal Kumar , Matthews Allan , Endrino Jose Luis , Goel Saurav
Published: March 2023

Currently, most thermal spray coating service providers expect original equipment manufacturers (OEMs) to suggest the coating recipe, comprising of the right coating equipment, starting process parameters, type of inert gases, and robot program. The microstructure and mechanical properties may not comply in the first few runs. Feedback from a competent material testing service provider forms the initial step to adjust the parameters in the development journey, toward identifying the processing parameters required to obtain an acceptable coating. With the surge of interest in sustainable manufacturing, the time spent on trials in the future will shrink, and a more rigorous process needs to be applied to achieve the “right-first-time manufacturing” approach in thermal spraying. However, a framework for the systematic development of thermal spray parameter optimisation is lacking. This article provides a framework, based on a logical acumen, in selecting the right process parameters, using available data and prior knowledge about the thermal spraying process. To that end, the article summarises the extant developmental journey of thermal spray process parameters, by covering the aspects of equipment choice, robot and spray parameters, and how to minimise iterations, using diagnostic tools to get to the end solution most efficiently. This article, in its current form, will serve as a good guide for early career engineers and scientists or workers, to minimise the time processing window, by avoiding endless iterations to deposit a certain type of coating using thermal spraying. Besides, this work is also aimed at transforming academic research innovations to a robust and repeatable industrial manufacturing process.
Bioactive Glass Applications in Different Periodontal Lesions: A Narrative Review
Authors: Shaikh Muhammad Saad , Fareed Muhammad Amber , Zafar Muhammad Sohail
Published: March 2023

Tissue engineering in the orofacial region with bioactive components by the activation of immune complexes or other proteins is the current focus of biomaterials research. Consequently, natural ground materials and tissue components are being created. Bioactive glass is one of the most promising biomaterials and has bioactive properties making it suited for a range of different clinical dental applications, including the regeneration of hard tissues in the craniofacial region. This narrative review provides a summary of the favorable properties and recent applications of bioactive glass materials for the management of periodontal lesions. Bioactive glass mimics natural calcified tissues in terms of composition and has a bioactive role in bone regeneration. The present review concluded that bioactive glass materials have a promising potential for various periodontal applications including the repair of infrabony defects, gingival recession, furcation defects, and guided tissue regeneration. However, further in vivo studies and clinical trials are warranted to advance and validate the potential of bioactive glass for periodontal applications and translate its usage in dental clinics for periodontology.
Single-Crystal X-ray Diffraction Analysis of Inclusion Complexes of Triflate-Functionalized Pillar[5]arenes with 1,4-Dibromobutane and n-Hexane Guests
Authors: Vinodh Mickey , Alshammari Shaima G. , Al-Azemi Talal F.
Published: March 2023

Herein, we report the single-crystal X-ray diffraction analysis of supramolecular host–guest systems based on triflate-functionalized pillar[5]arenes and 1,4-dibromobutane or n-hexane. The guest molecule was stabilized inside the pillar[5]arene cavity by C–H⋯π and C–H⋯O interactions. These inclusion complexes were further self-assembled into supramolecular networks by various non-bonding interactions such as C-H⋯O, C-H⋯F, Br⋯Br, F⋯F, etc. The intermolecular interactions present in these systems were investigated in detail. One of the supramolecular systems analyzed in this study exhibited intermolecular F⋯F interactions which were operative between the adjacent pillararene rims. It was observed that the type of guest molecule considerably influenced the mutual interactions of pillararene macrocycles and their networking pattern in the crystal. The inclusion complexes were further studied by Hirshfeld surface analysis which not only provided a visual representation of the intermolecular interactions experienced by the systems but gave a quantitative account of these various interactions.
“Quo Vadis Diagnosis”: Application of Informatics in Early Detection of Pneumothorax
Authors: Kumar V. Dhilip , Rajesh P. , Geman Oana , Craciun Maria Daniela , Arif Muhammad , Filip Roxana
Published: March 2023

A pneumothorax is a condition that occurs in the lung region when air enters the pleural space—the area between the lung and chest wall—causing the lung to collapse and making it difficult to breathe. This can happen spontaneously or as a result of an injury. The symptoms of a pneumothorax may include chest pain, shortness of breath, and rapid breathing. Although chest X-rays are commonly used to detect a pneumothorax, locating the affected area visually in X-ray images can be time-consuming and prone to errors. Existing computer technology for detecting this disease from X-rays is limited by three major issues, including class disparity, which causes overfitting, difficulty in detecting dark portions of the images, and vanishing gradient. To address these issues, we propose an ensemble deep learning model called PneumoNet, which uses synthetic images from data augmentation to address the class disparity issue and a segmentation system to identify dark areas. Finally, the issue of the vanishing gradient, which becomes very small during back propagation, can be addressed by hyperparameter optimization techniques that prevent the model from slowly converging and poorly performing. Our model achieved an accuracy of 98.41% on the Society for Imaging Informatics in Medicine pneumothorax dataset, outperforming other deep learning models and reducing the computation complexities in detecting the disease.
An Efficient 2D DOA Estimation Algorithm Based on OMP for Rectangular Array
Authors: Wang Chuang , Hu Jianmin , Zhang Qunying , Yuan Xinhao
Published: March 2023

Recently, orthogonal matching pursuit (OMP) has been widely used in direction of arrival (DOA) studies, which not only greatly improves the resolution of DOA, but can also be applied to single-snapshot and coherent source cases. When applying the OMP algorithm to the rectangular array DOA of the millimeter-wave radar, it is necessary to reshape the two-dimensional (2D) signal into a long one-dimensional (1D) signal. However, the long 1D signal will greatly increase the number and length of atoms in the complete dictionary of the OMP algorithm, which will greatly increase the amount of computation. Taking advantage of the sparsity of targets in the DOA space, an efficient 2D DOA estimation algorithm based on OMP for rectangular array is proposed. The main idea is to reduce the number of atoms in the complete dictionary of the OMP algorithm, thereby greatly reducing the amount of computation required. A simulation verifies that the efficiency of the proposed algorithm is much higher than the conventional algorithm with almost the same estimation accuracy.
Optical and SAR Image Registration Based on Multi-Scale Orientated Map of Phase Congruency
Authors: Jia Leilei , Dong Jian , Huang Siyuan , Liu Limin , Zhang Junning
Published: March 2023

Optical and Synthetic Aperture Radar (SAR) images are highly complementary, and their registrations are a fundamental task for other remote sensing applications. Traditional feature-matching algorithms fail to solve the significant nonlinear radiation difference (NRD) caused by different sensors. To address this problem, a robust registration algorithm with the multi-scale orientated map of phase congruency (MSPCO) is proposed. First, a nonlinear diffusion scale space is established to obtain the scale invariance of feature points. Compared with the linear Gaussian scale space, the nonlinear diffusion scale space can better preserve the edge and texture information. Second, to ensure the quantity and repeatability of features, corner points and edge points are detected on the moment map of phase congruency, respectively, which is the foundation to the next feature matching. Third, the MSPCO descriptor is constructed via the orientation of phase congruency (PCO). PCO is highly robust to NRD, and the different scales of PCOs enhance the robustness of the descriptor. Finally, a feature-matching strategy based on an effective scale ratio is proposed, which reduces the number of comparisons among features and improves computational efficiency. The experimental results show that the proposed method is better than the existing feature-based methods in terms of the number of correct matches and registration accuracy. The registration accuracy is only inferior to that of the most advanced template matching method, and the accuracy difference is within 0.3 pixels, which fully demonstrates the robustness and accuracy of the proposed method in optical and SAR image registration.
Secure Multi-Level Privacy-Protection Scheme for Securing Private Data over 5G-Enabled Hybrid Cloud IoT Networks
Authors: Budati Anil Kumar , Vulapula Sridhar Reddy , Shah Syed Bilal Hussian , Al-Tirawi Anas , Carie Anil
Published: March 2023

The hybrid cloud is a secure alternative for enterprises to exploit the benefits of cloud computing to overcome the privacy and security concerns of data in IoT networks. However, in hybrid cloud IoT, sensitive items such as keys in the private cloud can become compromised due to internal attacks. Once these keys are compromised, the encrypted data in the public cloud are no longer secure. This work proposes a secure multilevel privacy-protection scheme based on Generative Adversarial Networks (GAN) for hybrid cloud IoT. The scheme secures sensitive information in the private cloud against internal compromises. GAN is used to generate a mask with the input of sensory data-transformation values and a trapdoor key. GAN’s effectiveness is thoroughly assessed using Peak Signal-to-Noise Ratio (PSNR), computation time, retrieval time, and storage overhead frameworks. The obtained results reveal that the security scheme being proposed is found to require a negligible storage overhead and a 4% overhead for upload/retrieval compared to the existing works.
Efficient Reversible Data Hiding Using Two-Dimensional Pixel Clustering
Authors: Yuan Junying , Zheng Huicheng , Ni Jiangqun
Published: March 2023

Pixel clustering is a technique of content-adaptive data embedding in the area of high-performance reversible data hiding (RDH). Using pixel clustering, the pixels in a cover image can be classified into different groups based on a single factor, which is usually the local complexity. Since finer pixel clustering seems to improve the embedding performance, in this manuscript, we propose using two factors for two-dimensional pixel clustering to develop high-performance RDH. Firstly, in addition to the local complexity, a novel factor was designed as the second factor for pixel clustering. Specifically, the proposed factor was defined using the rotation-invariant code derived from pixel relationships in the four-neighborhood. Then, pixels were allocated to the two-dimensional clusters based on the two clustering factors, and cluster-based pixel prediction was realized. As a result, two-dimensional prediction-error histograms (2D-PEHs) were constructed, and performance optimization was based on the selection of expansion bins from the 2D-PEHs. Next, an algorithm for fast expansion-bin selection was introduced to reduce the time complexity. Lastly, data embedding was realized using the technique of prediction-error expansion according to the optimally selected expansion bins. Extensive experiments show that the embedding performance was significantly enhanced, particularly in terms of improved image quality and reduced time complexity, and embedding capacity also moderately improved.
Comparative Study of the Parameter Acquisition Methods for the Cauer Thermal Network Model of an IGBT Module
Authors: An Tong , Zhou Rui , Qin Fei , Dai Yanwei , Gong Yanpeng , Chen Pei
Published: March 2023

Under the operating conditions of high power and high switching frequency, an insulated gate bipolar transistor (IGBT) chip can produce relatively large power loss, causing the junction temperature to rise rapidly; consequently, the reliability of the IGBT module can be seriously affected. Therefore, it is necessary to accurately predict the junction temperature of the IGBT chip. The resistance capacitance (RC) thermal network model is a commonly used method for IGBT junction temperature prediction. In this paper, the model parameters are obtained by two methods to establish the Cauer thermal network models of the IGBT module. The first method is to experimentally obtain the transient thermal impedance curve of the IGBT module and the structure function and then extract the individual thermal parameters of the Cauer thermal network model; the second method is to obtain the thermal parameters of the thermal network model directly by using theoretical formulas that consider the influence of the heat spreading angle. The predicted junction temperatures of the Cauer thermal network models established by the two methods are compared with the junction temperatures obtained from infrared (IR) measurements during the power cycling test, the junction temperatures measured by the temperature-sensitive electrical parameter (TSEP) method, and the junction temperatures calculated by finite element (FE) analysis. Additionally, the Cauer thermal network models established by the two methods are compared and verified. The results indicate that the Cauer thermal network model established based on theoretical formulas can accurately predict the maximum junction temperature of the IGBT chip, and the calculated temperature for each layer, from the IGBT chip layer to the ceramic layer, also accords well with the FE results. The Cauer thermal network model established based on the experimental test and the structure function can accurately predict the average junction temperature of the IGBT chip.
High-Embedded Low-Distortion Multihistogram Shift Video Reversible Data Hiding Based on DCT Coefficient
Authors: Yang Yuhang , Xiang Xuyu , Qin Jiaohua , Tan Yun , Wang Zhangdong , Liu Yajie
Published: March 2023

Video reversible data hiding technology can be applied to copyright protection, medical images, the military, and other fields, but it cannot guarantee high visual quality with an effective embedded capacity. In this paper, a high-embedding and low-distortion reversible data hiding scheme based on a discrete cosine transform (DCT) coefficients method is proposed. The scheme first decodes the original video stream with entropy, obtains all the DCT blocks, and selects the embeddable DCT blocks according to the capacity of the zero factor. Then, it divides the coefficients in the DCT blocks into the shift and embedding coefficients. The shift coefficients directly generate a one-dimensional histogram; the embedding coefficients generate a two-dimensional histogram according to paired strategies. Finally, the secret data can be successfully embedded according to the proposed two-dimensional histogram shift reversible data hiding scheme. This scheme performed more effectively than existing schemes in terms of the embedded capacity, peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM).
Analysis of Voltage Control Strategies for DC Microgrid with Multiple Types of Energy Storage Systems
Authors: Yang Zhichun , Wang Chenxia , Han Ji , Yang Fan , Shen Yu , Min Huaidong , Hu Wei , Song Huihui
Published: March 2023

Direct-current (DC) microgrids have gained worldwide attention in recent decades due to their high system efficiency and simple control. In a self-sufficient energy system, voltage control is an important key to dealing with upcoming challenges of renewable energy integration into DC microgrids, and thus energy storage systems (ESSs) are often employed to suppress the power fluctuation and ensure the voltage stability. In this paper, the performances of three voltage control strategies for DC microgrids are compared, including the proportion integration (PI) control, the fuzzy PI control and particle swarm optimization (PSO) PI control. Particularly, two kinds of ESSs including battery and advanced adiabatic compressed air energy storage (AA-CAES) with different operational characteristics are installed in the microgrid, and their impacts on voltage control are investigated. The control performances are comprehensively compared under different control schemes, various scenarios of renewable energy fluctuations, participation in the control of the two ESSs or not, and different fault conditions. Additionally, the dynamic performances of the ESSs are exhibited. The results verify the validity of the control schemes and the feasibility of the configuration of the ESSs into the DC microgrid.
Information Security Architecture Design for Cyber-Physical Integration System of Air Traffic Management
Authors: Lu Xin , Dong Ruochen , Wang Qing , Zhang Lizhe
Published: March 2023

With the continuous expansion of air traffic flow, the increasingly serious aviation network security threats have a significant and far-reaching impact on the safe operation of the aviation industry. The networked air traffic management (ATM) system is an integrated space–air–ground network integrating communication, network, satellite, and data chain technology, which adopts a network-centric structure to provide network-enabled services and applications for the air transportation system. In view of the serious network threats faced by networked ATM, this paper studies the basic theories and key technologies of ATM information security assurance and designs a credible security architecture to provide comprehensive and systematic security assurance for networked ATM. Starting from the problems and development trend of ATM security assurance, this paper investigates the dynamic and complex data processing process of ATM system, analyzes the complex interaction between its cyber and physical system, and then constructs the networked ATM cyber–physical fusion system model and threat model. Furthermore, the causal relationship between ATM security threat alert information is mapped into a Bayesian network, and the game model of networked ATM is proposed using Bayesian Nash equilibrium strategy. At last, the information security assurance architecture of networked ATM system based on blockchain technology is formed by establishing a distributed co-trust mechanism and multi-chain storage structure. We expect this paper to bring some inspiration to the related research in academia and aviation so as to provide useful reference for the construction of ATM safety and security system and the development of technology.
Temporary Bonding and Debonding in Advanced Packaging: Recent Progress and Applications
Authors: Mo Zihao , Wang Fangcheng , Li Jinhui , Liu Qiang , Zhang Guoping , Li Weimin , Yang Chunlei , Sun Rong
Published: March 2023

Temporary bonding/debonding (TBDB) technologies have greatly contributed to the reliable fabrication of thin devices. However, the rapid development of large-scale, high-precision and ultra-thin devices in the semiconductor field has also proposed more stringent requirements for TBDB technologies. Here, we deliberate the recent progress of materials for temporary bonding and different debonding technologies over the past decade. Several common debonding methods are described, including thermal slide, wet chemical dissolution, mechanical peeling and laser ablation. We review the current status of different debonding technologies and highlight the applications of TBDB technologies in advanced electronic packaging. Possible solutions are proposed for the challenges and opportunities faced by different TBDB technologies. Ultimately, we attempt to propose an outlook on their future development and more possible applications. We believe that the simple schematics and refined data presented in this review would give readers a deep understanding of TBDB technologies and their vast application scenarios in future advanced electronic packaging.
Pyrenean Silver Fir Forests Retain Legacies of Past Disturbances and Climate Change in Their Growth, Structure and Composition
Authors: Gazol Antonio , González de Andrés Ester , Colangelo Michele , Valeriano Cristina , Camarero Jesús Julio
Published: March 2023

Recent drought-induced dieback alters forest dynamics, which are also shaped by past management. In western Pyrenean silver fir (Abies alba) stands, dieback concurs in space and time with the legacies of past management, but the impacts on forest growth, structure and composition are unknown. We aim to disentangle how dieback interacts with the legacies of past human use and modulates the recent dynamics of silver fir forests. To this end, we sampled eleven silver fir forests across wide climatic gradients and included declining and non-declining sites. We measured radial growth, structure, composition, understory cover and type and amount of deadwood. Silver fir growth declines in response to late-summer drought. In declining sites, most defoliated stands showed the lowest silver fir density and were those where growth depended more on water availability. Tree death enhanced the cover of dominant understory plants such as Buxus sempervirens. Past management activities leave an imprint in the growth of silver fir, such as releases due to past logging, but also affect the number of stumps and snags and the current tree density. A more extensive monitoring will be required to fully disentangle the multiple influences of past management legacies and current climate change on forest dynamics.
Equivalent Modes of Reimbursement in Augmented Contests
Authors: Cohen Chen , Darioshi Roy , Nitzan Shmuel
Published: March 2023

This article presents an equivalence theorem in the context of Tullock’s augmented lottery contest with external or internal cost reimbursement. Three alternative modes of reimbursement are studied. The equivalence implies that, even though the augmented contest is vulnerable to framing biases, it is strategically neutral.
Prenatal Environmental Stressors and DNA Methylation Levels in Placenta and Peripheral Tissues of Mothers and Neonates Evaluated by Applying Artificial Neural Networks
Authors: Stoccoro Andrea , Nicolì Vanessa , Coppedè Fabio , Grossi Enzo , Fedrizzi Giorgio , Menotta Simonetta , Lorenzoni Francesca , Caretto Marta , Carmignani Arianna , Pistolesi Sabina , Burgio Ernesto , Fanos Vassilios , Migliore Lucia
Published: March 2023

Exposure to environmental stressors during pregnancy plays an important role in influencing subsequent susceptibility to certain chronic diseases through the modulation of epigenetic mechanisms, including DNA methylation. Our aim was to explore the connections between environmental exposures during gestation with DNA methylation of placental cells, maternal and neonatal buccal cells by applying artificial neural networks (ANNs). A total of 28 mother–infant pairs were enrolled. Data on gestational exposure to adverse environmental factors and on mother health status were collected through the administration of a questionnaire. DNA methylation analyses at both gene-specific and global level were analyzed in placentas, maternal and neonatal buccal cells. In the placenta, the concentrations of various metals and dioxins were also analyzed. Analysis of ANNs revealed that suboptimal birth weight is associated with placental H19 methylation, maternal stress during pregnancy with methylation levels of NR3C1 and BDNF in placentas and mother’s buccal DNA, respectively, and exposure to air pollutants with maternal MGMT methylation. Associations were also observed between placental concentrations of lead, chromium, cadmium and mercury with methylation levels of OXTR in placentas, HSD11B2 in maternal buccal cells and placentas, MECP2 in neonatal buccal cells, and MTHFR in maternal buccal cells. Furthermore, dioxin concentrations were associated with placental RELN, neonatal HSD11B2 and maternal H19 gene methylation levels. Current results suggest that exposure of pregnant women to environmental stressors during pregnancy could induce aberrant methylation levels in genes linked to several pathways important for embryogenesis in both the placenta, potentially affecting foetal development, and in the peripheral tissues of mothers and infants, potentially providing peripheral biomarkers of environmental exposure.
Comprehensive Transcriptome Analysis of Responses during Cold Stress in Wheat (Triticum aestivum L.)
Authors: Li Lei , Han Chenglin , Yang Jinwei , Tian Zhiqiang , Jiang Ruyun , Yang Fei , Jiao Kemeng , Qi Menglei , Liu Lili , Zhang Baozhu , Niu Jishan , Jiang Yumei , Li Yongchun , Yin Jun
Published: March 2023

Wheat production is often impacted by pre-winter freezing damage and cold spells in later spring. To study the influences of cold stress on wheat seedlings, unstressed Jing 841 was sampled once at the seedling stage, followed by 4 °C stress treatment for 30 days and once every 10 days. A total of 12,926 differentially expressed genes (DEGs) were identified from the transcriptome. K-means cluster analysis found a group of genes related to the glutamate metabolism pathway, and many genes belonging to the bHLH, MYB, NAC, WRKY, and ERF transcription factor families were highly expressed. Starch and sucrose metabolism, glutathione metabolism, and plant hormone signal transduction pathways were found. Weighted Gene Co-Expression Network Analysis (WGCNA) identified several key genes involved in the development of seedlings under cold stress. The cluster tree diagram showed seven different modules marked with different colors. The blue module had the highest correlation coefficient for the samples treated with cold stress for 30 days, and most genes in this module were rich in glutathione metabolism (ko00480). A total of eight DEGs were validated using quantitative real-time PCR. Overall, this study provides new insights into the physiological metabolic pathways and gene changes in a cold stress transcriptome, and it has a potential significance for improving freezing tolerance in wheat.
Metabonomic Analysis of Silkworm Midgut Reveals Differences between the Physiological Effects of an Artificial and Mulberry Leaf Diet
Authors: Li Juan , Deng Jing , Deng Xuan , Liu Lianlian , Zha Xingfu
Published: March 2023

Bombyx mori is a model lepidopteran insect of great economic value. Mulberry leaves are its only natural food source. The development of artificial diets can not only resolve the seasonal shortage of mulberry leaves but also enable changes to be made to the feed composition according to need. Metabolomic differences between the midguts of male and female silkworms fed either on fresh mulberry leaves or an artificial diet were studied using liquid chromatography–mass spectrography (LC-MS/MS) analysis. A total of 758 differential metabolites were identified. Our analysis showed that they were mainly involved in disease resistance and immunity, silk quality, and silkworm growth and development. These experimental results provide insights into the formulation of optimized artificial feed for silkworms.
Banker Plant Bonuses? The Benefits and Risks of Including Brassicas in Field Margins to Promote Conservation Biocontrol of Specialist Pests in Oilseed Rape
Authors: Skellern Matthew. P. , Clark Suzanne J. , Ferguson Andrew W. , Watts Nigel P. , Cook Samantha M.
Published: March 2023

European agri-environment schemes include the use of flower-rich field margins to promote on-farm biodiversity, but species mixtures rarely include Brassicaceae. As pests of oilseed rape (OSR; Brassica napus) and their parasitoids are mostly brassica specialists, including brassica ‘banker plants’ in the mixtures would help support these important biocontrol agents and improve pest control throughout the crop rotation. We assessed the potential of six brassicaceous plants (replicated plots grown in the field) to enhance populations of parasitoids of OSR pests whilst minimising proliferation of their pest hosts. Fodder radish (Raphanus sativus) facilitated high production of parasitoids of the pollen beetle pest (Brassicogethes aeneus) but may proliferate Ceutorhynchus weevil pests due to low parasitism. Turnip rape (B. rapa) and the B. rapa hybrid ‘Tyfon’ showed potential to perform a trap cropping function for pests, but their early flowering phenology resulted in B. aeneus larvae escaping parasitisation, potentially assisting proliferation of this pest. Forage rape B. napus exhibited similarly high B. aeneus parasitoid production characteristics to R. sativus but did not potentiate problems with other pests, indicating that it would be a favourable banker plant option. Careful selection of plants in field margin mixtures is therefore needed to maximise their benefits and ideally the whole crop pest-beneficial complex needs to be studied, as focus on a single major pest risks unintended consequences with other pest problems.
Developing a Warning Model of Potentially Inappropriate Medications in Older Chinese Outpatients in Tertiary Hospitals: A Machine-Learning Study
Authors: Hu Qiaozhi , Tian Fangyuan , Jin Zhaohui , Lin Gongchao , Teng Fei , Xu Ting
Published: March 2023

Due to multiple comorbid illnesses, polypharmacy, and age-related changes in pharmacokinetics and pharmacodynamics in older adults, the prevalence of potentially inappropriate medications (PIMs) is high, which affects the quality of life of older adults. Building an effective warning model is necessary for the early identification of PIMs to prevent harm caused by medication in geriatric patients. The purpose of this study was to develop a machine learning-based model for the warning of PIMs in older Chinese outpatients. This retrospective study was conducted among geriatric outpatients in nine tertiary hospitals in Chengdu from January 2018 to December 2018. The Beers criteria 2019 were used to assess PIMs in geriatric outpatients. Three problem transformation methods were used to tackle the multilabel classification problem in prescriptions. After the division of patient prescriptions into the training and test sets (8:2), we adopted six widely used classification algorithms to conduct the classification task and assessed the discriminative performance by the accuracy, precision, recall, F1 scores, subset accuracy (ss Acc), and Hamming loss (hm) of each model. The results showed that among 11,741 older patient prescriptions, 5816 PIMs were identified in 4038 (34.39%) patient prescriptions. A total of 41 types of PIMs were identified in these prescriptions. The three-problem transformation methods included label power set (LP), classifier chains (CC), and binary relevance (BR). Six classification algorithms were used to establish the warning models, including Random Forest (RF), Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), CatBoost, Deep Forest (DF), and TabNet. The CC + CatBoost model had the highest accuracy value (97.83%), recall value (89.34%), F1 value (90.69%), and ss Acc value (97.79%) with a good precision value (92.18%) and the lowest hm value (0.0006). Therefore, the CC + CatBoost model was selected to predict the occurrence of PIM in geriatric Chinese patients. This study’s novelty establishes a warning model for PIMs in geriatric patients by using machine learning. With the popularity of electronic patient record systems, sophisticated computer algorithms can be implemented at the bedside to improve medication use safety in geriatric patients in the future.