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Clinical trials involving paired organs often yield a mixture of unilateral and bilateral data, where each subject may contribute either one or two responses. While unilateral responses from different individuals can be treated as independent, bilateral responses from the same individual are likely correlated. Various statistical methods have been developed to account for this intra-subject correlation in the bilateral data, and in practice, it is crucial to select a model that properly accounts for this correlation to ensure accurate inference. Previous research has investigated goodness-of-fit test statistics for correlated bilateral data under different group settings, assuming fully observed paired outcomes. In this work, we extend these methods to the more general and practically common setting where unilateral and bilateral data are combined. We examine the performance of various goodness-of-fit statistics under different statistical models, including the Clayton copula model. Simulation results indicate that the performance of the goodness-of-fit tests is model-dependent, especially when the sample size is small and/or the intra-subject correlation is high. However, the three bootstrap methods generally offer more robust performance. In real world applications from otolaryngologic and ophthalmologic studies, model choice significantly impacts conclusions, emphasizing the need for appropriate model assessment in practice. Full article

(This article belongs to the Topic Application of Biostatistics in Medical Sciences and Global Health)

23 pages, 20324 KiB

Open AccessArticle

Hyperparameter Tuning of Artificial Neural Network-Based Machine Learning to Optimize Number of Hidden Layers and Neurons in Metal Forming

by Ebrahim Seidi, Farnaz Kaviari and Scott F. Miller

J. Manuf. Mater. Process. 2025, 9(8), 260; https://doi.org/10.3390/jmmp9080260 (registering DOI) - 3 Aug 2025

Abstract

Cold rolling is widely recognized as a key industrial process for enhancing the mechanical properties of materials, particularly hardness, through strain hardening. Despite its importance, accurately predicting the final hardness remains a challenge due to the inherently nonlinear nature of the deformation. While several studies have employed artificial neural networks to predict mechanical properties, architectural parameters still need to be investigated to understand their effects on network behavior and model performance, ultimately supporting the design of more effective architectures. This study investigates hyperparameter tuning in artificial neural networks trained using Resilient Backpropagation by evaluating the impact of varying number of hidden layers and neurons on the prediction accuracy of hardness in 70-30 brass specimens subjected to cold rolling. A dataset of 1000 input–output pairs, containing dimensional and hardness measurements from multiple rolling passes, was used to train and evaluate 819 artificial neural network architectures, each with a different configuration of 1 to 3 hidden layers and 4 to 12 neurons per layer. Each configuration was tested over 50 runs to reduce the influence of randomness and enhance result consistency. Enhancing the network depth from one to two hidden layers improved predictive performance. Architectures with two hidden layers achieved better performance metrics, faster convergence, and lower variation than single-layer networks. Introducing a third hidden layer did not yield meaningful improvements over two-hidden-layer architectures in terms of performance metrics. While the top three-layer model converged in fewer epochs, it required more computational time due to increased model complexity and weight elements. Full article

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21 pages, 26631 KiB

Open AccessTechnical Note

Induced Polarization Imaging: A Geophysical Tool for the Identification of Unmarked Graves

by Matthias Steiner and Adrián Flores Orozco

Remote Sens. 2025, 17(15), 2687; https://doi.org/10.3390/rs17152687 (registering DOI) - 3 Aug 2025

Abstract

The identification of unmarked graves is important in archaeology, forensics, and cemetery management, but invasive methods are often restricted due to ethical or cultural concerns. This necessitates the use of non-invasive geophysical techniques. Our study demonstrates the potential of induced polarization (IP) imaging as a non-invasive remote sensing technique specifically suited for detecting and characterizing unmarked graves. IP leverages changes in the electrical properties of soil and pore water, influenced by the accumulation of organic matter from decomposition processes. Measurements were conducted at an inactive cemetery using non-invasive textile electrodes to map a documented grave from the early 1990s, with a survey design optimized for high spatial resolution. The results reveal a distinct polarizable anomaly at a 0.75–1.0 m depth with phase shifts exceeding 12 mrad, attributed to organic carbon from wooden burial boxes, and a plume-shaped conductive anomaly indicating the migration of dissolved organic matter. While electrical conductivity alone yielded diffuse grave boundaries, the polarization response sharply delineated the grave, aligning with photographic documentation. These findings underscore the value of IP imaging as a non-invasive, data-driven approach for the accurate localization and characterization of graves. The methodology presented here offers a promising new tool for archaeological prospection and forensic search operations, expanding the geophysical toolkit available for remote sensing in culturally and legally sensitive contexts. Full article

(This article belongs to the Special Issue Advances in Remote Sensing and Geophysical Methods to the Earth’s Surface and Shallow Subsurface Characterization)

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24 pages, 607 KiB

Open AccessArticle

ESG Reporting in the Digital Era: Unveiling Public Sentiment and Engagement on YouTube

by Dmitry Erokhin

Sustainability 2025, 17(15), 7039; https://doi.org/10.3390/su17157039 (registering DOI) - 3 Aug 2025

Abstract

This study examines how Environmental, Social, and Governance (ESG) reporting is communicated and perceived on YouTube. A dataset of 553 relevant videos and 5060 user comments was extracted on 2 April 2025 ranging between 2014 and 2025, and sentiment, topic, and stance analyses were applied to both transcripts and comments. The majority of video content strongly endorsed ESG reporting, emphasizing themes such as transparency, regulatory compliance, and financial performance. In contrast, viewer comments revealed diverse stances, including skepticism about methodological inconsistencies, accusations of greenwashing, and concerns over politicization. Notably, statistical analysis showed minimal correlation between video sentiment and audience sentiment, suggesting that user perceptions are shaped by factors beyond the tone of the videos themselves. These findings underscore the need for more rigorous ESG frameworks, enhanced standardization, and proactive stakeholder engagement strategies. The study highlights the value of online platforms for capturing stakeholder feedback in real time, offering practical insights for organizations and policymakers seeking to strengthen ESG disclosure and communication. Full article

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16 pages, 2036 KiB

Open AccessArticle

Scalable Chemical Vapor Deposition of Silicon Carbide Thin Films for Photonic Integrated Circuit Applications

by Souryaya Dutta, Alex Kaloyeros, Animesh Nanaware and Spyros Gallis

Appl. Sci. 2025, 15(15), 8603; https://doi.org/10.3390/app15158603 (registering DOI) - 2 Aug 2025

Abstract

Highly integrable silicon carbide (SiC) has emerged as a promising platform for photonic integrated circuits (PICs), offering a comprehensive set of material and optical properties that are ideal for the integration of nonlinear devices and solid-state quantum defects. However, despite significant progress in nanofabrication technology, the development of SiC on an insulator (SiCOI)-based photonics faces challenges due to fabrication-induced material optical losses and complex processing steps. An alternative approach to mitigate these fabrication challenges is the direct deposition of amorphous SiC on an insulator (a-SiCOI). However, there is a lack of systematic studies aimed at producing high optical quality a-SiC thin films, and correspondingly, on evaluating and determining their optical properties in the telecom range. To this end, we have studied a single-source precursor, 1,3,5-trisilacyclohexane (TSCH, C₃H₁₂Si₃), and chemical vapor deposition (CVD) processes for the deposition of SiC thin films in a low-temperature range (650–800 °C) on a multitude of different substrates. We have successfully demonstrated the fabrication of smooth, uniform, and stoichiometric a-SiCOI thin films of 20 nm to 600 nm with a highly controlled growth rate of ~0.5 Å/s and minimal surface roughness of ~5 Å. Spectroscopic ellipsometry and resonant micro-photoluminescence excitation spectroscopy and mapping reveal a high index of refraction (~2.7) and a minimal absorption coefficient (<200 cm⁻¹) in the telecom C-band, demonstrating the high optical quality of the films. These findings establish a strong foundation for scalable production of high-quality a-SiCOI thin films, enabling their application in advanced chip-scale telecom PIC technologies. Full article

(This article belongs to the Section Materials Science and Engineering)

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18 pages, 3020 KiB

Open AccessArticle

JAK2/STAT3 Signaling in Myeloid Cells Contributes to Obesity-Induced Inflammation and Insulin Resistance

by Chunyan Zhang, Jieun Song, Wang Zhang, Rui Huang, Yi-Jia Li, Zhifang Zhang, Hong Xin, Qianqian Zhao, Wenzhao Li, Saul J. Priceman, Jiehui Deng, Yong Liu, David Ann, Victoria Seewaldt and Hua Yu

Cells 2025, 14(15), 1194; https://doi.org/10.3390/cells14151194 (registering DOI) - 2 Aug 2025

Abstract

Adipose tissue inflammation contributes to obesity-induced insulin resistance. However, increasing evidence shows that high BMI (obesity) is not an accurate predictor of poor metabolic health in individuals. The molecular mechanisms regulating the metabolically activated M1 macrophage phenotype in the adipose tissues leading to insulin resistance remain largely unknown. Although the Janus Kinase (Jak)/signal transducer and activator of transcription 3 (Stat3) signaling in myeloid cells are known to promote the M2 phenotype in tumors, we demonstrate here that the Jak2/Stat3 pathway amplifies M1-mediated adipose tissue inflammation and insulin resistance under metabolic challenges. Ablating Jak2 in the myeloid compartment reduces insulin resistance in obese mice, which is associated with a decrease in infiltration of adipose tissue macrophages (ATMs). We show that the adoptive transfer of Jak2-deficient myeloid cells improves insulin sensitivity in obese mice. Furthermore, the protection of obese mice with myeloid-specific Stat3 deficiency against insulin resistance is also associated with reduced tissue infiltration by macrophages. Jak2/Stat3 in the macrophage is required for the production of pro-inflammatory cytokines that promote M1 macrophage polarization in the adipose tissues of obese mice. Moreover, free fatty acids (FFAs) activate Stat3 in macrophages, leading to the induction of M1 cytokines. Silencing the myeloid cell Stat3 with an in vivo siRNA targeted delivery approach reduces metabolically activated pro-inflammatory ATMs, thereby alleviating obesity-induced insulin resistance. These results demonstrate Jak2/Stat3 in myeloid cells is required for obesity-induced insulin resistance and inflammation. Moreover, targeting Stat3 in myeloid cells may be a novel approach to ameliorate obesity-induced insulin resistance. Full article

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22 pages, 1496 KiB

Open AccessReview

Drosophila melanogaster: How and Why It Became a Model Organism

by Maria Grazia Giansanti, Anna Frappaolo and Roberto Piergentili

Int. J. Mol. Sci. 2025, 26(15), 7485; https://doi.org/10.3390/ijms26157485 (registering DOI) - 2 Aug 2025

Abstract

Drosophila melanogaster is one of the most known and used organisms worldwide, not just to study general biology problems but above all for modeling complex human diseases. During the decades, it has become a central tool to understand the genetics of human disease, how mutations alter the behavior and health of cells, tissues, and organs, and more recently to test new compounds with a potential therapeutic use. But how did this small insect become so crucial in genetics? And how is it currently used in the study of human conditions affecting millions of people? In this review, we retrace the historical origins of its adoption in genetics laboratories and list all the advantages it provides to scientific research, both for its daily usage and for the fine tuning of gene regulation through genetic engineering approaches. We also provide some examples of how it is used to study human diseases such as cancer, neurological and infectious diseases, and its importance in drug discovery and testing. Full article

(This article belongs to the Special Issue Drosophila: A Versatile Model in Biology and Medicine—2nd Edition)

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20 pages, 4663 KiB

Open AccessArticle

Investigation on Imbibition Recovery Characteristics in Jimusar Shale Oil and White Mineral Oil by NMR

by Dunqing Liu, Chengzhi Jia and Keji Chen

Energies 2025, 18(15), 4111; https://doi.org/10.3390/en18154111 (registering DOI) - 2 Aug 2025

Abstract

Recovering oil by fracturing fluid imbibition has demonstrated significant potential for enhanced oil recovery (EOR) in tight oil reservoirs. White mineral oil (WMO), kerosene, or saturated alkanes with matched apparent viscosity have been widely used as “crude oil” to investigate imbibition mechanisms in light shale oil or tight oil. However, the representativeness of these simulated oils for low-maturity crude oils with higher viscosity and greater content of resins and asphaltenes requires further research. In this study, imbibition experiments were conducted and T₂ and T₁–T₂ nuclear magnetic resonance (NMR) spectra were adopted to investigate the oil recovery characteristics among resin–asphaltene-rich Jimusar shale oil and two WMOs. The overall imbibition recovery rates, pore scale recovery characteristics, mobility variations among oils with different occurrence states, as well as key factors influencing imbibition efficiency were analyzed. The results show the following: (1) WMO, kerosene, or alkanes with matched apparent viscosity may not comprehensively replicate the imbibition behavior of resin–asphaltene-rich crude oils. These simplified systems fail to capture the pore-scale occurrence characteristics of resins/asphaltenes, their influence on pore wettability alteration, and may consequently overestimate the intrinsic imbibition displacement efficiency in reservoir formations. (2) Surfactant optimization must holistically address the intrinsic coupling between interfacial tension reduction, wettability modification, and pore-scale crude oil mobilization mechanisms. The alteration of overall wettability exhibits higher priority over interfacial tension in governing displacement dynamics. (3) Imbibition displacement exhibits selective mobilization characteristics for oil phases in pores. Specifically, when the oil phase contains complex hydrocarbon components, lighter fractions in larger pores are preferentially mobilized; when the oil composition is homogeneous, oil in smaller pores is mobilized first. Full article

(This article belongs to the Special Issue New Progress in Unconventional Oil and Gas Development: 2nd Edition)

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19 pages, 865 KiB

Open AccessArticle

What Are US Undergraduates Taught and What Have They Learned About US Continental Crust and Its Sedimentary Basins?

by Clinton Whitaker Crowley and Robert James Stern

Geosciences 2025, 15(8), 296; https://doi.org/10.3390/geosciences15080296 (registering DOI) - 2 Aug 2025

Abstract

We need to educate students and the public about addressing natural resource challenges to maintain civilization moving into a sustainable future. Because US mineral and energy resources are found in its continental crust and sedimentary basins, introductory geology students need to be well-informed about US crust and basins. We think that creating effective videos about these topics is the best way to engage students to want to learn more. In preparation for making these videos, we researched what introductory geology students are taught and what they learn about these topics. Student interviews informed us about learned curriculum, and taught curriculum was analyzed using a novel keyword-counting method applied to textbook indices. We found that geophysics is stressed twice as much as geology, radiometric dating, and sedimentary basins. We expected that students would have learned more about geophysics and less about the other topics; however, this was not the case. Students knew more about geology, and less about geophysics, radiometric dating, and sedimentary basins. To make effective videos on these topics, we need to explain the following threshold concepts: seismic refraction to scaffold student understanding of crustal geophysics, as well as radiometric dating and deep time to understand crustal geology and the economic importance of sedimentary basins. Full article

(This article belongs to the Section Sedimentology, Stratigraphy and Palaeontology)

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30 pages, 1130 KiB

Open AccessReview

Beyond the Backbone: A Quantitative Review of Deep-Learning Architectures for Tropical Cyclone Track Forecasting

by He Huang, Difei Deng, Liang Hu, Yawen Chen and Nan Sun

Remote Sens. 2025, 17(15), 2675; https://doi.org/10.3390/rs17152675 (registering DOI) - 2 Aug 2025

Abstract

Accurate forecasting of tropical cyclone (TC) tracks is critical for disaster preparedness and risk mitigation. While traditional numerical weather prediction (NWP) systems have long served as the backbone of operational forecasting, they face limitations in computational cost and sensitivity to initial conditions. In recent years, deep learning (DL) has emerged as a promising alternative, offering data-driven modeling capabilities for capturing nonlinear spatiotemporal patterns. This paper presents a comprehensive review of DL-based approaches for TC track forecasting. We categorize all DL-based TC tracking models according to the architecture, including recurrent neural networks (RNNs), convolutional neural networks (CNNs), Transformers, graph neural networks (GNNs), generative models, and Fourier-based operators. To enable rigorous performance comparison, we introduce a Unified Geodesic Distance Error (UGDE) metric that standardizes evaluation across diverse studies and lead times. Based on this metric, we conduct a critical comparison of state-of-the-art models and identify key insights into their relative strengths, limitations, and suitable application scenarios. Building on this framework, we conduct a critical cross-model analysis that reveals key trends, performance disparities, and architectural tradeoffs. Our analysis also highlights several persistent challenges, such as long-term forecast degradation, limited physical integration, and generalization to extreme events, pointing toward future directions for developing more robust and operationally viable DL models for TC track forecasting. To support reproducibility and facilitate standardized evaluation, we release an open-source UGDE conversion tool on GitHub. Full article

(This article belongs to the Section AI Remote Sensing)

11 pages, 398 KiB

Open AccessPerspective

Implications of Metabolic Bariatric Surgery on Reproductive Health

by Amihai Rottenstreich and Yitka Graham

J. Clin. Med. 2025, 14(15), 5446; https://doi.org/10.3390/jcm14155446 (registering DOI) - 2 Aug 2025

Abstract

In the last two decades, metabolic and bariatric surgery (MBS) has become the mainstay of treatment for severe and complex obesity. The majority of patients undergoing MBS are women of childbearing age. Coupled with the dramatic increase in the utilization of MBS, caregivers are likely to encounter patients who have undergone MBS in routine practice. From this perspective, we highlight the different reproductive health challenges and issues encountered throughout the pre-operative, peri-operative, and postoperative phases. Full article

(This article belongs to the Section Obstetrics & Gynecology)

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16 pages, 336 KiB

Open AccessArticle

Mongols, Apocalyptic Messianism, and Later Medieval Christian Fears of Mass Conversion to Judaism

by Irven Michael Resnick

Histories 2025, 5(3), 36; https://doi.org/10.3390/histories5030036 (registering DOI) - 2 Aug 2025

Abstract

The capture of Jerusalem during the First Crusade, the extirpation of various heresies in the twelfth and thirteen centuries, the gradual expansion of Christian rule in the Iberian peninsula, and the mass conversion of Jews to Christianity there during the fourteenth century, all seemed to support a Christian triumphalism that imagined that as the End Time approached, Jews and other infidels would inevitably be absorbed into the Church. Nonetheless, an expanding medieval awareness of the many ‘Others’ beyond Christendom contributed to Christian anxieties that Jews (or Muslims) might expand their number through mass conversion, and not Christians. This paper will examine some sources of this anxiety. Full article

(This article belongs to the Section Cultural History)

23 pages, 2750 KiB

Open AccessArticle

Seasonal Sea Surface Temperatures from Mercenaria spp. During the Plio-Pleistocene: Oxygen Isotope Versus Clumped Isotope Paleothermometers

by Garrett F. N. Braniecki, Donna Surge and Ethan G. Hyland

Geosciences 2025, 15(8), 295; https://doi.org/10.3390/geosciences15080295 (registering DOI) - 2 Aug 2025

Abstract

The Mid-Piacenzian Warm Interval (MPWI) is marked by warmer temperatures and higher atmospheric CO₂ levels than today, making it an analogue for late-21st-century-warming, whereas the early Pleistocene cooling is more like today. We compare seasonal growth temperatures derived from oxygen isotope ratios (δ¹⁸O) and clumped isotopes (∆₄₇) in Mercenaria. Modern shells were previously collected from coastal NC. The fossil shells are from the Duplin (MPWI) and Waccamaw Formations (early Pleistocene), NC. Oxygen isotope ratios range from −2.2‰ to 2.3‰ (modern), −0.9‰ to 2.4‰ (MPWI), and −0.9‰ to 2.9‰ (early Pleistocene). The values of Δ₄₇ range from 0.576‰ to 0.639‰ (modern), 0.566‰ to 0.621‰ (MPWI), and 0.581‰ to 0.615‰ (early Pleistocene). We show that Mercenaria do not require a species-specific ∆₄₇ calibration. Modern and MPWI ∆₄₇-derived summer/winter temperatures (SST_∆47) and seasonal amplitudes are indistinguishable from δ¹⁸O-derived temperatures. The early Pleistocene summer SST_∆47 is indistinguishable from δ¹⁸O-derived temperatures, but the winter SST_∆47 is warmer by 5 °C and may reflect within-shell time averaging. The modern summer/winter SST_∆47 are indistinguishable from the MPWI, but the MPWI has a lower seasonal amplitude by 5 °C. Compared to our calculated δ¹⁸O_sw values, modeled values for the MPWI are within error but are much lower, and they are not within error for the early Pleistocene. Full article

(This article belongs to the Special Issue Pliocene Studies in Paleobiology, Paleoenvironment and Paleoclimate)

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19 pages, 1159 KiB

Open AccessArticle

A Biased–Randomized Iterated Local Search with Round-Robin for the Periodic Vehicle Routing Problem

by Juan F. Gomez, Antonio R. Uguina, Javier Panadero and Angel A. Juan

Mathematics 2025, 13(15), 2488; https://doi.org/10.3390/math13152488 (registering DOI) - 2 Aug 2025

Abstract

The periodic vehicle routing problem (PVRP) is a well-known challenge in real-life logistics, requiring the planning of vehicle routes over multiple days while enforcing visitation frequency constraints. Although numerous metaheuristic and exact methods have tackled various PVRP extensions, real-world settings call for additional features such as depot configurations, tight visitation frequency constraints, and heterogeneous fleets. In this paper, we present a two-phase biased–randomized algorithm that addresses these complexities. In the first phase, a round-robin assignment quickly generates feasible and promising solutions, ensuring each customer’s frequency requirement is met across the multi-day horizon. The second phase refines these assignments via an iterative search procedure, improving route efficiency and reducing total operational costs. Extensive experimentation on standard PVRP benchmarks shows that our approach is able to generate solutions of comparable quality to established state-of-the-art algorithms in relatively low computational times and stands out in many instances, making it a practical choice for real life multi-day vehicle routing applications. Full article

(This article belongs to the Special Issue Optimization Algorithms for Operations Research and Scheduling Problems)

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13 pages, 1397 KiB

Open AccessArticle

RSPH4A-PCDx: An Index to Predict Lung Function Decline in Primary Ciliary Dyskinesia

by Gabriel Román-Ríos, Gabriel Rosario-Ortiz, Marcos J. Ramos-Benitez, Ricardo A. Mosquera and Wilfredo De Jesús-Rojas

Adv. Respir. Med. 2025, 93(4), 27; https://doi.org/10.3390/arm93040027 (registering DOI) - 2 Aug 2025

Abstract

Primary ciliary dyskinesia (PCD) is a rare, genetically heterogeneous disorder that impairs mucociliary clearance and leads to progressive lung disease. This study aimed to characterize lung function decline in a genetically homogeneous cohort of Puerto Rican patients with RSPH4A-associated PCD and to develop a clinical tool to predict lung function decline and support transplant referral decisions. We conducted a retrospective chart review of patients (n = 25) with a confirmed RSPH4A [c.921+3_6delAAGT] genetic variant, collecting longitudinal spirometry data and applying linear regressions to calculate each patient’s individual FEV₁ decline. The median FEV₁ at diagnosis was 55%, with a median annual decline of −0.75% predicted. Adults exhibited significantly lower lung function compared to pediatric patients, while no difference was seen between males and females. Based on this observed decline, we developed the Predicted Capacity Decline Index (PCDx), an index that estimates the age and time until a patient reaches the 30% FEV₁ threshold, the point at which lung transplant referral is typically considered. Our findings underscore the need for early intervention and suggest that genotype-specific tools like the PCDx may enhance clinical decision-making in managing progressive lung disease in PCD. Full article

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