bluuebunny/crossref_metadata_2025 huggingface dataset:
Structure-based design of glycoprotein subunit vaccines for mumps
Authors: Loomis Rebecca J. , Lai Yen-Ting , Sowers Sun B. , Fisher Brian , Derrien-Colemyn Alexandrine , Ambrozak David R. , Tsybovsky Yaroslav , Crooke Stephen N. , Latner Donald R. , Kong Wing-Pui , Ruckwardt Tracy J. , Plotkin Stanley A. , Kwong Peter D. , Mascola John R. , Graham Barney S. , Hickman Carole J. , Stewart-Jones Guillaume B. E.
Published: November 2024

Mumps virus (MuV) is a highly contagious paramyxovirus that is endemic in most regions of the world and continues to cause outbreaks even in highly immunized populations. Outbreaks of mumps in countries with high measles, mumps, and rubella vaccination coverage have been attributed to waning immunity and antigenic differences between the Jeryl Lynn vaccine strain (genotype A) and circulating wild-type viruses. To obtain a subunit vaccine, we used structure-based design to engineer the mumps fusion (F) glycoprotein stabilized in its prefusion conformation (Pre-F) as well as a chimeric immunogen comprising Pre-F linked to mumps hemagglutinin neuraminidase (HN); in mice, both Pre-F antigen and the chimeric antigen elicited potent cross-reactive plaque reducing neutralizing titers to genotypes A, G, and H mumps. A crystal structure of mumps Pre-F at 2.16 Å resolution validated the stabilization strategy, while a post-fusion form of F was engineered as a comparator. Monoclonal antibodies to mumps Pre-F and HN were isolated from immunized mice; 7 of 14 Pre-F-specific antibodies and 9 of 15 HN-specific antibodies were capable of neutralizing genotype G MuV with a range of potencies. Additionally, 7 of 14 Pre-F-specific antibodies neutralized genotype A mumps. Structural and binding analyses of Pre-F-specific antibodies revealed binding to four discrete neutralizing antigenic sites and binding analyses of HN-specific antibodies revealed binding to five discrete neutralizing antigenic sites. Overall, the PreF and the chimeric Pre-F/HN immunogens are promising candidates to boost MMR-elicited immunity to mumps or as a next-generation vaccine.
Subchronic elevation in ambient temperature drives alterations to the sperm epigenome and accelerates early embryonic development in mice
Authors: Trigg Natalie , Schjenken John E. , Martin Jacinta H. , Skerrett-Byrne David A. , Smyth Shannon P. , Bernstein Ilana R. , Anderson Amanda L. , Stanger Simone J. , Simpson Ewan N. A. , Tomar Archana , Teperino Raffaele , Conine Colin C. , De Iuliis Geoffry N. , Roman Shaun D. , Bromfield Elizabeth G. , Dun Matthew D. , Eamens Andrew L. , Nixon Brett
Published: November 2024

Forecasted increases in the prevalence and severity of extreme weather events accompanying changes in climatic behavior pose potential risk to the reproductive capacity of humans and animals of ecological and agricultural significance. While several studies have revealed that heat stress induced by challenges such as testicular insulation can elicit a marked negative effect on the male reproductive system, and particularly the production of spermatozoa, less is known about the immediate impact on male reproductive function following subchronic whole-body exposure to elevated ambient temperature. To address this knowledge gap, we exposed unrestrained male mice to heat stress conditions that emulate a heat wave (daily cycle of 8 h at 35 °C followed by 16 h at 25 °C) for a period of 7 d. Neither the testes or epididymides of heat-exposed male mice exhibited evidence of gross histological change, and similarly, spermatozoa of exposed males retained their functionality and ability to support embryonic development. However, the embryos generated from heat-exposed spermatozoa experienced pronounced changes in gene expression linked to acceleration of early embryo development, aberrant blastocyst hatching, and increased fetal:placental weight ratio. Such changes were causally associated with an altered sperm small noncoding RNA (sncRNA) profile, such that these developmental phenotypes were recapitulated by microinjection of wild-type embryos sired by control spermatozoa with RNAs extracted from heat-exposed spermatozoa. Such data highlight that even relatively modest excursions in ambient temperature can affect male reproductive function and identify the sperm sncRNA profile as a particular point of vulnerability to this imposed environmental stress.
Cell type–specific gene therapy confers protection against motor neuron disease caused by a TFG variant
Authors: Lettman Molly M. , Mendina Caitlin A. , Burkard Emma , Alvin James R. , Zhu Yunyun , Coon Joshua J. , Audhya Anjon
Published: November 2024

Inherited forms of motor neuron disease (MND), including hereditary spastic paraplegias (HSP), are associated with the death or dysfunction of nerve cells that control skeletal muscle activity. However, in some cases, the impacts of genetic variants underlying MND act in a non–cell autonomous manner, instead affecting the function of other cell types necessary for neuronal maintenance. Pathological mutations in TFG, which have been implicated in HSP, lead to axonopathy within the corticospinal tract, but it remains unclear whether this problem arises due to perturbations within neurons or supporting neuroglia. To address this question, we leveraged a rat model harboring the recessive TFG p.R106C mutation (mRATBN7.2, g.11:43897639C>T, c.316C>T), which recapitulates multiple phenotypes associated with HSP in humans, including progressive motor deficits, leg spasticity, and indications of an inflammatory response within the motor cortex. In particular, we took advantage of cell type–specific gene therapies to demonstrate that the reintroduction of wild-type TFG into synapsin 1-positive neurons provides robust protection against MND, whereas its expression in GFAP-positive glial cells provides no significant improvement in quantitative measures of gait, despite a dramatic reduction in the presence of reactive astrocytes throughout the brain. These data strongly suggest that therapeutic approaches targeting neurons should be pursued in cases of TFG-HSP, with our animal model offering a unique platform for preclinical assessment.
Targeted engineering of camelina and pennycress seeds for ultrahigh accumulation of acetyl-TAG
Authors: Alkotami Linah , White Dexter J. , Schuler Kathleen M. , Esfahanian Maliheh , Jarvis Brice A. , Paulson Andrew E. , Koley Somnath , Kang Jinling , Lu Chaofu , Allen Doug K. , Lee Young-Jin , Sedbrook John C. , Durrett Timothy P.
Published: November 2024

Acetyl-TAG (3-acetyl-1,2-diacylglycerol), unique triacylglycerols (TAG) possessing an acetate group at the
sn
-3 position, exhibit valuable properties, such as reduced viscosity and freezing points. Previous attempts to engineer acetyl-TAG production in oilseed crops did not achieve the high levels found in naturally producing
Euonymus
seeds. Here, we demonstrate the successful generation of camelina and pennycress transgenic lines accumulating nearly pure acetyl-TAG at 93 mol% and 98 mol%, respectively. These ultrahigh acetyl-TAG synthesizing lines were created using gene-edited
FATTY ACID ELONGASE1
(
FAE1
) mutant lines as an improved genetic background to increase levels of acetyl-CoA available for acetyl-TAG synthesis mediated by the expression of EfDAcT, a high-activity diacylglycerol acetyltransferase isolated from
Euonymus fortunei
. Combining EfDAcT expression with suppression of the competing TAG-synthesizing enzyme DGAT1 further enhanced acetyl-TAG accumulation. These ultrahigh levels of acetyl-TAG exceed those in earlier engineered oilseeds and are equivalent or greater than those in
Euonymus
seeds. Imaging of lipid localization in transgenic seeds revealed that the low amounts of residual TAG were mostly confined to the embryonic axis. Similar spatial distributions of specific TAG and acetyl-TAG molecular species, as well as their probable diacylglycerol (DAG) precursors, provide additional evidence that acetyl-TAG and TAG are both synthesized from the same tissue-specific DAG pools. Remarkably, this ultrahigh production of acetyl-TAG in transgenic seeds exhibited minimal negative effects on seed properties, highlighting the potential for production of designer oils required for economical biofuel industries.
Human ITGAV variants are associated with immune dysregulation, brain abnormalities, and colitis
Authors: Ghasempour Sina , Warner Neil , Guan Rei , Rodari Marco M. , Ivanochko Danton , Whittaker Hawkins Ryder , Marwaha Ashish , Nowak Jan K. , Liang Yijing , Mulder Daniel J. , Stallard Lorraine , Li Michael , Yu Daniel D. , Pluthero Fred G. , Batura Vritika , Zhao Mo , Siddiqui Iram , Upton Julia E.M. , Hulst Jessie M. , Kahr Walter H.A. , Mendoza-Londono Roberto , Charbit-Henrion Fabienne , Hoefsloot Lies H. , Khiat Anis , Moreira Diana , Trindade Eunice , Espinheira Maria do Céu , Pinto Pais Isabel , Weerts Marjolein J.A. , Douben Hannie , Kotlarz Daniel , Snapper Scott B. , Klein Christoph , Dowling James J. , Julien Jean-Philippe , Joosten Marieke , Cerf-Bensussan Nadine , Freeman Spencer A. , Parlato Marianna , van Ham Tjakko J. , Muise Aleixo M.
Published: November 2024

Integrin heterodimers containing an Integrin alpha V subunit are essential for development and play critical roles in cell adhesion and signaling. We identified biallelic variants in the gene coding for Integrin alpha V (ITGAV) in three independent families (two patients and four fetuses) that either caused abnormal mRNA and the loss of functional protein or caused mistargeting of the integrin. This led to eye and brain abnormalities, inflammatory bowel disease, immune dysregulation, and other developmental issues. Mechanistically, the reduction of functional Integrin αV resulted in the dysregulation of several pathways including TGF-β–dependent signaling and αVβ3-regulated immune signaling. These effects were confirmed using immunostaining, RNA sequencing, and functional studies in patient-derived cells. The genetic deletion of itgav in zebrafish recapitulated patient phenotypes including retinal and brain defects and the loss of microglia in early development as well as colitis in juvenile zebrafish with reduced SMAD3 expression and transcriptional regulation. Taken together, the ITGAV variants identified in this report caused a previously unknown human disease characterized by brain and developmental defects in the case of complete loss-of-function and atopy, neurodevelopmental defects, and colitis in cases of incomplete loss-of-function.
Stabilizing effect of the spacetime expansion on the Euler–Poisson equations in Newtonian cosmology
Authors: Gong Xinyu , Wei Changhua
Published: November 2024

The validity of the cosmic no-hair theorem for polytropic perfect fluids has been established by (Brauer et al 1994 Class. Quantum Grav. 11 2283) within the context of Newtonian cosmology, specifically under conditions of exponential expansion. This paper extends the investigation to assess the nonlinear stability of homogeneous Newtonian cosmological models under general accelerated expansion for perfect fluids. With appropriate assumptions regarding the expansion rate and decay properties of the homogeneous solution, our results demonstrate that the Euler–Poisson system admits a globally classical solution for initial data that are small perturbations to the homogeneous solution. Additionally, we establish that the solution asymptotically approaches the homogeneous solution as time tends to infinity. The theoretical framework is then applied to various types of perfect fluids, including isothermal gases, Chaplygin gases, and polytropic gases.
Efficient cross-domain fault diagnosis via distributed multi-source domain deep transfer learning
Authors: Wan Lanjun , Ning Jiaen , Li Yuanyuan , Li Changyun
Published: November 2024

In actual industrial production, the working conditions of rotating machinery are complex and changeable, and the health-state monitoring data are increasingly large and difficult to label, which will seriously restrict the accuracy and efficiency of the cross-domain fault diagnosis (CDFD) of rotating machinery. Therefore, an efficient multi-source domain deep transfer learning (MDDTL) method for CDFD of rotating machinery is proposed. First, an MDDTL model is constructed to improve the accuracy of CDFD. In the model, a dual-phase domain alignment strategy is designed, which considers the alignment of feature distributions between each source and target domain pair in the feature space and that of the prediction probabilities between domain-specific fault classifiers in the output space. The fault prediction results from multiple different fault classifiers are merged dynamically by the proposed imbalanced adaptive prediction strategy. Secondly, a data-parallel distributed training scheme for the MDDTL model is proposed. Based on the idea of data parallelism, the distributed parallel training of the MDDTL model is performed with a Horovod-graphics processing unit platform, and the parameters are synchronously updated with the bandwidth-optimal Ring-AllReduce architecture. Under the premise of ensuring the accuracy of FD, the training time of the MDDTL model is significantly reduced. Finally, extensive experiments are conducted to verify the effectiveness of the proposed MDDTL method. The results demonstrate that the proposed method not only effectively improves the accuracy of CDFD of rotating machinery but also significantly improves the training efficiency of the MDDTL model. After adopting the proposed method, the diagnosis accuracies achieved under two different cross-working condition scenarios reach 97.09% and 97.87% respectively, and the model training time is reduced by 73.62% when facing a large-scale rotating machinery training set.
Three-dimensional reconstruction and damage localization of bridge undersides based on close-range photography using UAV
Authors: Jiang Shang , Zhang Yufeng , Wang Feiyu , Xu Yichao
Published: November 2024

Damage inspection on the undersides of bridges is an important and challenging part of routine bridge inspections. A method for 3D reconstruction and damage localization of bridge undersides based on close-range photography by unmanned aerial vehicle (UAV) and stereo vision combined with deep learning algorithms is proposed, the specific contributions include: (1) proposing a close-range photography method for acquiring high-resolution images from multiple perspectives of the bridge underside by UAVs, serving as the data source for damage analysis; (2) applying a deep learning-assisted segmentation method to optimize the multi-view geometry-based 3D reconstruction method, improving the efficiency of three-dimensional reconstruction, and defining the projection direction from the 3D reconstruction results to obtain ultra-high-resolution panoramic images of the bridge underside; (3) addressing the issue of detecting minor damages in large panoramic images by using a slice-assisted reasoning module and a lightweight convolutional YOLO v8 network to identify exposed steel bars corroded due to concrete damage in the panoramic images, and defining a coordinate system to localize the damages on the bridge underside. The proposed method was applied to damage detection and localization on the underside of a 160 m span main span of an in-service concrete bridge. The results demonstrate that the proposed method can quickly and accurately identify exposed steel bar corrosion on the bridge underside and output reports, proving the practicality of the proposed method.
Research on the visual measurement algorithm of cam base circle radius based on virtual structured light plane
Authors: Hu Zhengyi , He Jinglin
Published: November 2024

Using line structured light vision measurement technology, it is possible to perform non-contact measurement of the cam’s base circle radius. To address the issue of the structured light plane not being perpendicular to the axis of the cam being measured, this paper obtains the axis equation of the cam being measured through calibration, and based on the axis equation, it obtains the spatial equation of a virtual light plane that is perpendicular to the axis. The point cloud on the surface of the cam is projected onto the virtual plane, and the base circle radius of the cam is obtained using the coordinates of the projected points. To improve the measurement accuracy of the cam’s base circle radius, this paper designs a base revision model to address measurement errors caused by the non-coincidence of bases. The measurement results of the base circle radii of four cams on the engine camshaft show that the line structured light vision measurement technology meets the measurement requirements and is feasible for non-contact measurement. The innovation presented herein lies in the development of a cloud acquisition model predicated on line structured light vision technology, which effectively converts a complex spatial curve fitting challenge into a simpler planar curve fitting problem. This transformation not only streamlines the measurement process for the cam base circle radius but also significantly enhances the measurement precision of engine camshafts.
Study of magnetic field error suppression methods based on atomic parameters of cell in atomic co-magnetometer rotation measurement
Authors: Liu Ye , Fan Wenfeng , Liu Yao , Ma Longyan , Quan Jiale , Zhou Saixin , Pang Haoying , Quan Wei
Published: November 2024

We propose a new model for magnetic field errors based on the rotation measurement of the K-Rb-

21

Ne

co-magnetometer, considering the density ratio and spin collisions. The spin polarization characteristics of different alkali metal density ratios were analyzed by creating five cells with different density ratios, and the correctness of the magnetic field error model was verified experimentally. Moreover, the effects of five different alkali metal density ratios of cells on the sensitivity, long-term stability and magnetic field error suppression of the K-Rb-

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co-magnetometer were investigated experimentally. When the density ratio is 1:107, there can be the optimal magnetic field error suppression effect, sensitivity and long-term stability. According to the derived magnetic field error equation, the magnetic noise error of the K-Rb-

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co-magnetometer with an optimized density ratio is reduced by nearly 5 times from 260°/h/nT to 56.5°/h/nT, the sensitivity is improved from 2.9×10−5 °/s/Hz

1
/
2

to 7.0×10−6 °/s/Hz

1
/
2

at 1 Hz, and the long-term stability Allan variance over two hours is improved from 1.9×10−2 °/h to 8.9×10−3 °/h. This result provides a theoretical basis for designing the parameters of the K-Rb-

21

Ne

co-magnetometer cell.
A novel method for anomaly detection and correction of GNSS time series
Authors: Li Haiyang , Xie Yilin , Meng Xiaolin , Wu Shuguang , Xu Jianping , Wang Xiang
Published: November 2024

Global navigation satellite systems (GNSS) provides a novel means for deformation monitoring, which is an important guarantee for structures. Accurately separating its linear and nonlinear signals, and noise in GNSS time series is the foundation for analyzing deformation mechanisms and the prerequisite for assessing the status. However, extracting deformation signals is a challenging obstacle to applying GNSS for deformation monitoring. Aimed at that, a new method is proposed in this study. Fine-tuning the window size and threshold of the Hampel filter (HF) through grid search allows for initial anomaly detection and correction. Optimizing the K parameter of the K-nearest neighbors algorithm via rigorous K-fold cross-validation ensures further smoothing of the filtered data, which overcomes the limitations of the HF in handling continuous anomalies. Experimental results demonstrate that the proposed method improves performance by approximately 62% compared to traditional methods and by around 40% relative to interquartile range (IQR) and other methods. This study presents an effective approach for detecting and eliminating outliers in GNSS deformation monitoring, offering noteworthy theoretical and practical implications.
Fault detection of RV reducer cycloidal gear under robot working conditions based on optimization improved envelope spectrum sideband energy ratio
Authors: Shen Yankang , Guo Yu , Fan Jiawei , Wu Xianliang
Published: November 2024

Under industrial robot operating conditions, the cycloidal gear in the rotary vector (RV) reducer in the robot joint runs in a compound rotation motion with a low-speed and incomplete cycle, which complicates the fault detection for the cycloidal gear. Until now, no effective detection method for the cycloidal gear tooth fault under industrial robot operating conditions has been reported. Consequently, a method based on optimization improved envelope spectrum (IES) sideband energy ratio is proposed in this paper. Firstly, encoder signals are acquired and used to estimate the instantaneous angular speed signals, which are then separated into two sets of data based on rotation directions. Then, the data corresponding to the approximately stable speed is truncated and connected to form a constructed signal. Next, the coherence of the constructed signal is calculated using the fast spectral coherence algorithm. Subsequently, the IES sideband energy ratio is used as the objective value, and a global optimization algorithm is employed to determine the integration frequency band of the IES. Finally, the IES of this frequency band is calculated to obtain the fault-related order characteristics. An RV reducer test rig was used for the experiment, and the analysis results from the proposed approach, cyclic spectral coherence, and IES via feature optimization-gram were contrasted. Experiment results show that the proposed method is valid for the detection of tooth faults in the cycloidal gear of the RV reducer in robot operating conditions.
Sparse representation-based noise reduction for BOTDR monitoring signals in foundation pit anchor cables
Authors: Li Zi-xiang , Cai Hai-bing , Hou Gong-yu
Published: November 2024

Brillouin optical time-domain reflectometer (BOTDR) systems are commonly challenged by low signal-to-noise ratio (SNR) in foundation pit monitoring. This study proposes a noise-suppression method for BOTDR signals utilizing sparse representation (SR). The method involves creating an initial dictionary from the eigenvectors of the normalized graph Laplace matrix. The K-singular value decomposition and orthogonal matching pursuit algorithms are combined to update the dictionary and coefficient matrix, facilitating the SR of the signal’s intrinsic features and the removal of random noise. This results in improved quality of the reconstructed signal. An experimental system for BOTDR temperature sensing was developed to assess the algorithm’s denoising capabilities. The algorithm showed significant improvements in SNR and reductions in sample entropy (SE) compared to techniques such as wavelet threshold denoising, empirical wavelet transform, and empirical mode decomposition. Specifically, the average SNR increase was 27.4%, 15.4%, 13.1%, and 17.9%, while the average SE decrease was 24.4%, 16.0%, 15.4%, and 47.9% for the respective comparisons. The proposed Laplace-based dictionary also outperformed the discrete cosine transform dictionary. Field tests were conducted at the Beijing Stomatological Hospital, where the algorithm applied to on-site anchor cable fiber optic monitoring signals, achieving an average SE decrease of 45.2%. The research provides an effective denoising method for the application of BOTDR technology in foundation pit monitoring, underscoring the approach’s novelty and practical application.
Multi-parameter correlation analysis and multi-step prediction of seawater quality based on graph spatio-temporal analysis network
Authors: Zhu Qiguang , Shen Zhen , Qiao Wenjing , Wu Zhen , Chen Ying
Published: November 2024

In recent years, with the increasing pollution of near-shore waters, the water quality pollution incidents have been aggravated, which seriously threatens many aspects of coastal economic development, ecological environment and living health. Therefore, there is an urgent need for an effective method to predict the water quality of near-shore waters. However, due to seasonal changes, ocean currents, biological activities and other factors, the marine environment has strong complexity and uncertainty, which leads to the monitoring data of seawater quality parameters are unstable, non-linear and other characteristics. At the same time, there are interactions between different parameters, so it is not easy to dig deeper into the information in the data, and the accuracy of the existing prediction methods for multi-parameter multi-step prediction of seawater quality is generally low. To solve the above problems, a new graph neural network model is proposed in this paper. The model can effectively extract the local time correlation, global time correlation and spatial correlation in non-Euclidean space of seawater quality parameter data from multiple dimensions. Finally, this paper evaluates the model performance using the seawater parameter data from the near-shore waters of Beibu Gulf, and compared with the five baseline models, the model proposed in this paper shows the best performance in all the defined evaluation indexes.
Augmented deep transfer learning for SRP condition monitoring via physically-informed WGAN-GP approach
Authors: Zuo Jiye , Lei Miaoxin , Wang Shuqiang , Dong Shimin , Li Weicheng
Published: November 2024

Traditional dynamometer card sensors are costly and complex, making them unsuitable for real-time sucker rod pumping (SRP) well diagnostics. Recently, SRP diagnosis models using motor power curves offer an alternative, but irregular power curves and limited labeled data present challenges. To address this, we propose a deep transfer model enhanced by Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) data augmentation. First, a physics-driven model reconstructs polished rod torque from motor power, emphasizing fault features. Second, WGAN-GP generates faulty SRP torque-displacement samples to expand training data. Finally, a fully parameter-tuned deep transfer SRP diagnosis framework is established, which improves the automatic learning of advanced fault features and enhances diagnostic accuracy using the augmented dataset. Experiments confirm the model’s superior performance and generalization.
SDCSN: a hierarchical parallel localization method for pipeline leakage based on vibration signals
Authors: Zhang Xia , Li Juan
Published: November 2024

In applying deep learning methods to detecting and localising pipeline leaks, improving the fitness of deep learning methods to leak signals is an important task. We propose a novel detection model called stacked dilated convolutional shrinkage network. This model incorporates a stacked dilated convolution module specifically designed for vibration signals, enabling the extraction of rich multi-scale local features. Moreover, implementing the residual shrinkage building unit module for noise reduction in the network architecture. Building upon this foundation, we introduce a new concept centred around hierarchical leakage discrimination and parallel prediction positioning. This approach enables accurate assessment of leakage levels and precise identification of multiple leakage points. Finally, the performance of the proposed method is verified in real experiments and the optimal settings for the dilated rate are determined. The results demonstrate a maximum classification accuracy rate reaching 98.94%.
Inter-center comparison of proton range verification prototypes with an anthropomorphic head phantom
Authors: Hueso-González Fernando , Berthold Jonathan , Wohlfahrt Patrick , Bortfeld Thomas , Khamfongkhruea Chirasak , Tattenberg Sebastian , Zarifi Melek , Verburg Joost , Richter Christian
Published: November 2024

Objective. To compare in reproducible and equalized conditions the performance of two independent proton range verification systems based on prompt gamma-ray detectors from two different proton therapy centers. Approach. An anthropomorphic head phantom with calibrated stopping power, serving as ground truth, was irradiated with comparable treatment plans, spot positions and energies in both facilities. Clinical beam current, tumor contour and dose were used. The absolute range measurement was compared to the expected value according to the ground truth. The statistical precision was assessed by repeating each measurement ten times. Sensitivity to relative range shifts was evaluated by introducing 2 mm and 5 mm plastic slabs on half of the field. Main results. The resulting absolute range accuracy was within 2.4 mm in all cases. Relative range shifts were detected with deviations lower than 14%. Significance. The performance of both systems was deemed worthy of clinical application for the detection of range deviations. This study represents the first comparison of independent prompt gamma-ray-based proton range verification systems under equalized conditions with realistic treatment fields and beam currents.
Bimodal PET/MRI generative reconstruction based on VAE architectures
Authors: Gautier V , Bousse A , Sureau F , Comtat C , Maxim V , Sixou B
Published: November 2024

Objective. In this study, we explore positron emission tomography (PET)/magnetic resonance imaging (MRI) joint reconstruction within a deep learning framework, introducing a novel synergistic method. Approach. We propose a new approach based on a variational autoencoder (VAE) constraint combined with the alternating direction method of multipliers (ADMM) optimization technique. We explore three VAE architectures, joint VAE, product of experts-VAE and multimodal JS divergence (MMJSD), to determine the optimal latent representation for the two modalities. We then trained and evaluated the architectures on a brain PET/MRI dataset. Main results. We showed that our approach takes advantage of each modality sharing information to each other, which results in improved peak signal-to-noise ratio and structural similarity as compared with traditional reconstruction, particularly for short acquisition times. We find that the one particular architecture, MMJSD, is the most effective for our methodology. Significance. The proposed method outperforms conventional approaches especially in noisy and undersampled conditions by making use of the two modalities together to compensate for the missing information.
Searching for Gravitational Wave Optical Counterparts with the Zwicky Transient Facility: Summary of O4a
Authors: Ahumada Tomás , Anand Shreya , Coughlin Michael W. , Gupta Vaidehi , Kasliwal Mansi M. , Karambelkar Viraj R. , Stein Robert D. , Waratkar Gaurav , Swain Vishwajeet , Jegou du Laz Theophile , Anumarlapudi Akash , Andreoni Igor , Bulla Mattia , Srinivasaragavan Gokul P. , Toivonen Andrew , Wold Avery , Bellm Eric C. , Cenko S. Bradley , Kaplan David L. , Sollerman Jesper , Bhalerao Varun , Perley Daniel , Salgundi Anirudh , Suresh Aswin , Hinds K-Ryan , Reusch Simeon , Necker Jannis , Cook David O. , Pletskova Natalya , Singer Leo P. , Banerjee Smaranika , Barna Tyler , Copperwheat Christopher M. , Healy Brian , Kiendrebeogo R. Weizmann , Kumar Harsh , Kumar Ravi , Pezzella Marianna , Sagués-Carracedo Ana , Sravan Niharika , Bloom Joshua S. , Chen Tracy X. , Graham Matthew , Helou George , Laher Russ R. , Mahabal Ashish A. , Purdum Josiah , Anupama G. C. , Barway Sudhanshu , Basu Judhajeet , Raman Dhananjay , Roychowdhury Tamojeet
Published: November 2024

During the first half of the fourth observing run (O4a) of the International Gravitational Wave Network, the Zwicky Transient Facility (ZTF) conducted a systematic search for kilonova (KN) counterparts to binary neutron star (BNS) and neutron star–black hole (NSBH) merger candidates. Here, we present a comprehensive study of the five high-significance (False Alarm Rate less than 1 yr−1) BNS and NSBH candidates in O4a. Our follow-up campaigns relied on both target-of-opportunity observations and re-weighting of the nominal survey schedule to maximize coverage. We describe the toolkit we have been developing, Fritz, an instance of SkyPortal, instrumental in coordinating and managing our telescope scheduling, candidate vetting, and follow-up observations through a user-friendly interface. ZTF covered a total of 2841 deg2 within the skymaps of the high-significance GW events, reaching a median depth of g ≈ 20.2 mag. We circulated 15 candidates, but found no viable KN counterpart to any of the GW events. Based on the ZTF non-detections of the high-significance events in O4a, we used a Bayesian approach, nimbus, to quantify the posterior probability of KN model parameters that are consistent with our non-detections. Our analysis favors KNe with initial absolute magnitude fainter than −16 mag. The joint posterior probability of a GW170817-like KN associated with all our O4a follow-ups was 64%. Additionally, we use a survey simulation software, simsurvey, to determine that our combined filtered efficiency to detect a GW170817-like KN is 36%, when considering the 5 confirmed astrophysical events in O3 (1 BNS and 4 NSBH events), along with our O4a follow-ups. Following Kasliwal et al., we derived joint constraints on the underlying KN luminosity function based on our O3 and O4a follow-ups, determining that no more than 76% of KNe fading at 1 mag day−1 can peak at a magnitude brighter than −17.5 mag.
Application of the Nirmala Index in Nanotechnology: Optimizing Molecular Structures for Advanced Nanomaterials
Authors: Prashanth K K , Annasagaram Gayathri , Parvathi M , Kumar Deepasree S , Shettar Anita , Uma S
Published: November 2024

Chemical graph theory has played a key role in advancing our understanding of molecular structure by producing degree-based topological indices that forecast crucial physical and chemical properties. In this paper we attempt to investigate this recently defined Nirmala index as an invariant from different topological angles and applications on multiple molecular graph structures such as triangular, double, and alternate quadrilateral snake structures. This index offers a more profound comprehension of the connections between molecular structures and attributes. The next generation of ground breaking developments in nanotechnology, where the creation of devices and functional nanomaterials hinges on molecular interaction at the nanoscale, may also be greatly influenced by this index. These indices have potential applications in drug delivery systems and in molecular structure optimization related to nanotechnological fields like nanophotonics and nanoelectronics. Consequently, the Nirmala index will pave the way for the development of more sophisticated tools for the production of high-performing nanoscale materials.
Structural, morphological and Magnetic studies of Soft magnetic Fe-Si-B Metallic Glass ribbons
Authors: Dhanalakshmi K. , Revathi V.
Published: November 2024

A comparative study of two metallic glass ribbons produced by two different industries namely M/s Honeywell corporation, U.S.A., and M/s Vijay electricals. The potential of different experimental techniques like XRD, SEM and EDAX and VSM has been carried out for two soft metallic glass ribbons. XRD studies reveal that for sample A has two broad peaks and sample B shows the absence of any sharp peaks indicating crystalline secondary phases are <5%. Morphological studies show that sample A has homogeneous matrix whereas sample B has crystallites of varied shapes and sizes distributed in the range of 5-40 μm. EDAX for both the samples A and B was done to investigate the compositional elements. VSM measurements reveals sample B to exhibit a relatively larger anisotropy compared to sample A.
Investigation of the Dielectric Characteristics of Chromium-substituted Zinc and Cobalt Nanoferrite Systems
Authors: Lakshmi M. , Sreelalitha K. , Sarah P. , Samba Sivaiah B , Naveen D.
Published: November 2024

The series of Cr-substituted Zn and Co nanoferrite systems having the chemical composition CrxZnFe2–xO4 and CrxCoFe2–xO4 (0.0 ≤ x ≤0.5) were prepared by sol–gel technique. The present investigation aims to compare the impact of Cr3+ concentration on dielectric characteristics of Zn and Co-nanoferrite systems. The investigation of various dielectric characteristics was conducted using an LCR meter at 1kHz frequency and across the frequency range of 100Hz to 1MHz. The measurements were conducted at room temperature. In the case of both ferrite systems, the plots of frequency Vs dielectric constant (ε′) and AC conductivity (σac) show a common dielectric behavior of spinel ferrites. The plots of frequency Vs dissipation factor (D) of Cr- Cr-substituted zinc and Cobalt nanoferrite samples were observed to be unusual and display a relaxation peak at a particular frequency. In the current study, CrxZnFe2-xO4(x=0.2 and 0.3) and CrxCoFe2–xO4 (x=0.3) ferrite samples were found to exhibit very high values of dielectric constant. So these ferrites may be useful for a wide range of applications in electrical storage devices. According to LCR reports, all the Cr3+ substituted ferrite samples in both ferrite systems exhibit higher dielectric constant and AC conductivity values. Possible mechanisms that may be accountable for the outcomes are thoroughly scrutinized in this paper.
Accelerating solutions of the Korteweg–de Vries equation
Authors: Winkler Maricarmen A , Asenjo Felipe A
Published: November 2024

The Korteweg–de Vries equation is a fundamental nonlinear equation that describes solitons with constant velocity. On the contrary, here we show that this equation also presents accelerated wavepacket solutions. This behavior is achieved by putting the KdV equation in terms of the Painlevé I equation. The accelerated waveform solutions are explored numerically showing their accelerated behavior explicitly.
Ethnobotany of Plants Around Anaphalis javanica in the ‘Penanjakan Resort’ Area of Bromo Tengger Semeru National Park (BTSN)
Authors: Alifah Luthfi , Rahma Melati Julia , Batoro Jati
Published: November 2024

This research was conducted to reveal the potential of plants around Edelweiss Flowers (Anaphalis javanica) in the BTSN Penanjakan Resort Area and their benefits according to the local community. This study was carried out by plant inventory by use purposive sampling to choose the study site to 5 points with a plot size of 2×2 m2. Semi-structured interviews were carried out to find out the types of plants and their benefits. The results of the interviews were compiled to determine the significance of cultural interest index (ICS) and described based on ICS calculations. This study indicated that 17 different plant species were present around the growth site of Anaphalis javanica in the Penanjakan Resort Area of BTSN with the highest ICS value in Debregeasia longifolia or “mencogan” which has other benefits as a good water absorber.
COVID-19 Pandemic and Transformation of Activity Space: Implications for Urban Area Planning in the Yogyakarta Metropolitan Area
Authors: Shalihati Sakinah Fathrunnadi , Kurniawan Andri , Giyarsih Sri Rum , Marwasta Djaka
Published: November 2024

Travel patterns and spatial behavior of people in the Yogyakarta Metropolitan Area during the COVID-19 pandemic have experienced adjustments due to restrictions on out-of-home activities. Spatial behavior has information on the coordinates of the location of the activity visited, and the area that represents this behavior is called activity space. Exploration of activity space may play an essential part in urban area planning. This study utilizes travel activity diary data before and during the pandemic for change analysis with a quantitative approach. Data before the pandemic used the Probability Proportional to Size method and random selection of respondents. While re-measurement during the pandemic, respondents were collected using convenience sampling on 109 individuals willing to re-engage in the survey while still considering population size. The generalization of findings applies to workers and part of middle-income families. A literature review strengthens the empirical findings and explores their implications. The findings indicate that the coverage area for activities has shrunk due to the pandemic, with most activity places falling within a short distance of one’s residence and from one another. The consistency of these findings in the future has implications for providing more flexible, multifunctional, and decentralized spaces equipped with safe and comfortable paths for active transportation modes and integrated with reliable communication technology services.
The Relationship Between LST, NDVI, NDBI, and OTCI in Urban Green Space in Jakarta With Geospatial Data
Authors: Azaria Linda
Published: November 2024

Mapping uses geospatial data on the Vegetation Index, Chlorophyll Index or OTCI, Land Surface Temperature, the Built-up area Index in Jakarta and calculates the correlation of these variables using the Pearson correlation method with samples as many as 30. The correlation results of NDBI, NDVI, LST, and OTCI show that there are strong and not strong relationships between the two variables. There are strong correlations between the two variables, these are NDBI and LST with a correlation of 0.751, NDBI with NDVI has -0.904, NDVI with LST has -0.711, and OTCI with NDVI has 0.428. Meanwhile, the correlation is less strong between the two variables, these are OTCI and LST with a correlation of -0.140 and OTCI with NDBI with a correlation of -0.268.
Identification of Groundwater Aquifer Layers in Manyarejo Subdistrict Using the Schlumberger Configuration Geoelectric Method
Authors: Mosakarli Mayo , Irawan Listyo Yudha
Published: November 2024

Research was conducted to determine the groundwater aquifer layer in Manyarejo Village, Gresik Regency using the Schlumberger configuration 1D geoelectric method. This method is carried out by injecting an electric current into the earth through two electrodes and their potential current. If an electric current is injected into a medium and the potential voltage difference is measured, the resistance value of the medium can be estimated. This research was carried out at 8 points with a track length of 300-700 meters. Then measure with a resistivity meter. Then the data obtained is processed with the IP2Win application to create a picture of the subsurface structure. After interpretation, the results showed that the aquifer consists of 3 layers consisting of clay, clay sand, sand with clay and gravel. And groundwater in aquifer 1 is directed to the West (GL-8), while aquifer 2 is directed to the West and is directed to the North (GL-6). Aquifer 3. Groundwater is found in the resistivity value range of 1 to 100 Ohm Meters. In general, groundwater in aquifer 1 has a resistivity value 1 to 10 Ohm meters, while in aquifer 2 it has a resistivity value of 5 to 20 Ohm meters.
Smart Environment Implementation Study in Samarinda
Authors: Setyasih Iya’ , Satria Janu Purba , Sulistioadi Yohanes Budi , Setiawan Yunianto , Anwar Yaskinul , Juhardika Aureliya C , Masita
Published: November 2024

Samarinda, as a buffer for the Indonesian Capital City (IKN), needs to carry out development transformation to suit developments in science and technology and needs. The aim is to overcome environmental problems that cause increased flooding, traffic jams and under resourced neighbourhoods, making Samarinda City an uncomfortable place to live. To overcome this, it is necessary to apply the smart environment concept. This research examines the implementation of a smart environment, and the obstacles faced in its implementation in Samarinda City. Research analysis uses SWOT by determining the IFAS and EFAS for implementing the smart environment. The results of the SWOT analysis are in quadrant I (x, y = 1.71; 1.10), meaning that the implementation of a smart environment in Samarinda City needs to be carried out with a growth strategy (intensifying existing resources). The obstacles to implementing a smart environment in Samarinda City in the environmental protection program are not yet using IoT to monitor pollution, the high volume of waste that has not been handled, the absence of regional regulations regarding the use of renewable energy and energy efficient building design. For this reason, support and cooperation from the government, private sector and society is needed.
Strain analysis in a 3D printed car brake pedal by numerical and experimental methods
Authors: Cristian Dudescu Mircea , Racz Laszlo , Vilău Cristian
Published: November 2024

This paper presents the strain analysis in a brake pedal manufactured by additive technologies. A commercial plastic pedal made by injection moulding was optically scanned using a scanning system based on fringes projection. The result was a CAD model of the pedal that can be used in both numerical simulations and 3D printing. Two models of the pedal with 100% infill rate and a grid infill pattern were produced by 3D printing on an industrial printer, the difference between the two models is laying in the orientation of the printed part in the printer workspace. Resistive strain gauges were applied to determine the mechanical behaviour of the printed pedals regarding the injection moulded version. To perform a comparative study of the experimentally obtained results, pedals with similar mechanical characteristics to those measured experimentally were analysed numerically by the finite element method. The numerical results showed a good convergence with the experimental results, with relative deviations of 13% for the printed pedal with outer filaments oriented longitudinally to its longitudinal axis, 7.3% for the printed pedal with outer filaments oriented transversely and 2.8% for the homogeneous (injected) pedal. The results also demonstrated the possibility of replacing in the future complex, parts made today by conventional technologies with 3D printed elements having mechanical characteristics allowing them to fulfil a functional role.
Optimizing Milling Processes through FEA: An In-depth Analysis of Cutting Tool Geometric Parameters and Their Impact on Performance of milling.
Authors: Necpal Martin , Peterka Jozef , Vozár Marek
Published: November 2024

In the rapidly advancing world of manufacturing, the optimization of cutting processes is of paramount importance for enhancing efficiency and product quality. This work underscores the necessity of employing Finite Element Analysis (FEM) for a comprehensive understanding and improvement of cutting processes. By leveraging DEFORM we create a detailed 2D simulation of the milling process, allowing for an unprecedented inspection of the procedure in a virtual environment. Central to our investigation is the variation of geometric parameters of the cutting tool within the FEM simulation model, offering insights into how minute alterations can significantly affect the outcome of the milling process. The study systematically analyzes the impact of the milling tool’s geometric parameters on various process parameters, including chip formation and cutting forces. This analysis is critical for identifying optimization opportunities in tool design and process settings. Furthermore, we delve into the stress-strain state of the cutting zone, a factor crucial for understanding the material behavior under operational conditions and ensuring the structural integrity of the final product. Through our findings, we demonstrate that strategic modifications in the geometric parameters of the cutting tool can lead to substantial improvements in process performance. This research not only contributes to the body of knowledge on milling processes but also provides practical recommendations for engineers and manufacturers striving to optimize their cutting operations through the application of FEM.