bluuebunny/crossref_metadata_2025 huggingface dataset:
Seismic Performance of Bridge Pile Foundations in Karst Areas
Authors: Huang Jiadong , Tan Ping , He Dehua , Yang Bin , Ma Chunjing
Published: October 2024

The current bridge pile foundation design specifications in China provide only general principles for karst areas and do not provide a method to calculate the safe cave roof thickness or the vertical displacement of the pile foundation. Additionally, previous studies have not adequately considered the interaction between bridge pile foundations and caves under seismic loads. Therefore, the national design code does not provide an effective basis or reference for calculating the seismic performance of pile foundations in complex karst areas. This study establishes a numerical model of the pile-foundation-cave interaction system. The dynamic responses of the pile foundation displacement, stress, plastic strain, and bending moment subject to ground motion after inversion are analyzed. The effects of different factors on the safe cave roof thickness and vertical displacement of the pile foundation are investigated, and multiple regression models are obtained and optimized. Finally, parametric sensitivity analysis is conducted for each influencing factor. The results demonstrate that the safe cave roof thickness is between 2.5[Formula: see text]m and 5.7[Formula: see text]m and the vertical displacement is between 0.0075[Formula: see text]m and 0.06[Formula: see text]m. The sensitivity factors for the safe cave roof thickness in the case where the cavern shape is simplified to a rectangle, in descending order, are the rock cohesion, pile diameter, initial load at the top of the pile, cave size, and the peak value of ground motion. The sensitivity factors for the vertical displacement of the pile foundation, in descending order, are the peak value of ground motion, initial load at the top of the pile, cave size, and pile diameter. The conclusions provide valuable insights into the design optimization of rock-socketed pile foundations in karst regions.
Plane Wave Finite Element Method for the Dynamic Response of the Periodic Pile-Type Composite Ground Under a Harmonic Concentrated Load
Authors: Liu Yang , Lu Jian-Fei
Published: October 2024

In this study, a simplified model for the pile-type composite ground, namely, the periodic pile-type composite ground (PPCG) model is proposed. The PPCG in this study is assumed to be periodic in the horizontal directions and finite in the vertical direction. For investigation of the dynamic response of the PPCG to a harmonic concentrated load, a plane wave finite element (PWFE) method for the PPCG under the load is developed in this study. To develop the method, the concentrated load is decomposed into its wavenumber domain components by the 2D Fourier transform first. The response of the PPCG to a wavenumber domain load component is represented by a set of plane waves, and the variables associated with each plane wave are discretized via the FEM along the vertical direction of the PPCG. The finite element equations for each plane wave of the PPCG are developed via the virtual work principle. To obtain the overall dynamic response of the PPCG to the concentrated load by synthesizing the responses due to all load components effectively, the mode superposition method is used to construct the response of the PPCG to the load component, and the polar coordinate system-based inverse Fourier transform method is developed for the inversion of the 2D Fourier transform with respect to the wavenumber. With the developed method, some numerical results about the dynamic response of the PPCG to the concentrated load are presented.
Sound Insulation Characteristic Analysis of Corrugated Core Sandwich Panel by Using Differential Quadrature Finite Element Method
Authors: Li Zhen , Wang Qingshan , Yang Qing , Qin Bin
Published: October 2024

This paper proposes a universal vibroacoustic coupling theoretical analysis model for investigating the sound insulation characteristic of corrugated core sandwich panel (CCSP) under different boundary conditions. The vibroacoustic coupling model consists of CCSP (structural field) and two three-dimensional acoustic cavities which simulate the incident sound field and accept the sound field, respectively. Based on first-order shear deformation plate and shell theories and acoustic theory, the dynamic model of CCSP and three-dimensional acoustic cavities are established by employing the differential quadrature finite element method in conjunction with the energy principle. The coupling of CCSP and three-dimensional acoustic cavities is realized by the velocity continuity condition at the acoustic–structure interfaces. The validation of the vibroacoustic coupling model is verified by comparing the results calculated by the established model with the corresponding results calculated by ABAQUS. The influence of model parameters on the vibroacoustic characteristic of vibroacoustic coupling model is investigated systematically for determining the critical structure parameters which have influence on the vibroacoustic behaviors. The effect of critical structure parameters on the sound insulation characteristic of CCSP is analyzed systematically for the optimization of the sound insulation performance of CCSP and provides theoretical basis and technique guidance.
Static Analysis and Damping Capacity (Energy Absorption) of Sandwich Annular Sector Plates with Facesheets Reinforced with GPLs Considering Agglomeration and a Negative Poisson’s Ratio Metallic Lattice Core
Authors: Gong Qingzhong , Nan Wenhu
Published: October 2024

This paper investigates the natural frequency and static analysis of a sandwich annular sector plate with a core exhibiting a negative Poisson’s ratio lattice structure, along with facesheets reinforced with agglomerated graphene nanoplatelets (GPL). Both complete and partial agglomeration states are considered using the Eshelby–Mori–Tanaka micromechanical model. The governing equations of motion are derived using Hamilton’s principle, based on First Shear Deformation (FSD) plate theory and the finite element method. The sandwich plates exhibit an ultra-light characteristic, attributable to the auxetic honeycomb core layer, which possesses a negative Poisson’s ratio, and are further reinforced by two laminated skin layers. The study examines the impact of various parameters, including the geometry of the auxetic honeycomb unit cell, the weight fraction of GPL, and the distribution of GPL on the natural frequency, displacement of the center point of the auxetic honeycomb core, and specific absorbed energy of the sandwich plate. The natural frequency decreases with increasing inclination angle, becoming less sensitive as the ratio [Formula: see text], increases. A 57.14% drop occurs for [Formula: see text] when the angle rises from 10[Formula: see text] to 60[Formula: see text], while for [Formula: see text], and 2.5, the reductions are 25.82%, 13.72%, and 9.23%, respectively. Adding 0.1% GPL without agglomeration raises the natural frequency by 237.85%, enhancing stiffness, but full agglomeration cuts this to 12.47%. The X-pattern has the strongest effect, and the O-pattern the least, with distribution patterns becoming more influential as GPL weight fraction rises. In the partial agglomeration state, performance is optimal when [Formula: see text]. For a GPL weight fraction from 0.2% to 1%, displacement drops by 77.94% at [Formula: see text] and by 71.68% at [Formula: see text].
Multivariate activation functions
Authors: Ivaniuk Andrii
Published: October 2024

Activation functions are critical components in neural network architectures, significantly influencing model performance and learning efficiency. While traditional univariate activation functions have been extensively studied and optimized, the exploration of multidimensional (multivariate) activation functions remains relatively nascent. In this paper, a comprehensive study of various multidimensional activation functions is presented, focusing on both Gaussian Mixture Models (GMM) and interpolation-based methods with learnable parameters. Through extensive experiments, the performance of these novel activation functions is evaluated in diverse neural network architectures and tasks. Results demonstrate that while the proposed multidimensional activation functions achieve performance on par with known activation functions like Swiglu, they do not consistently outperform it. This investigation provides valuable insights into the potential and limitations of multidimensional activation functions, paving the way for future research in this promising area of deep learning.
Partial Multi-Label Learning via Exploiting Instance and Label Correlations
Authors: Liang Weichao , Gao Guangliang , Chen Lei , Wang Youquan
Published: October 2024

The goal of partial multi-label learning is to induce a multi-label classifier from partial multi-label data where each instance is annotated with a number of candidate labels but only a subset of them are valid. Many of the existing studies either fail to fully utilize instance and label correlations to eliminate noisy labels or build an over-simplified multi-label classifier, both of which are unfavorable for the improvement of generalization performance. In this article, we put forward a novel model named P
ml-ilc
to learn a multi-label classifier from partial multi-label data. Specifically, P
ml-ilc
first encodes instances and labels into a compact semantic space and takes full advantage of instance and label correlations to eliminate noisy labels. Then, it induces a linear mapping from the feature space to the label space while exploiting label-specific features and instance correlations to facilitate the multi-label classifier learning process. Finally, the above two steps are combined into a joint optimization problem and an efficient alternating optimization procedure is developed to find a satisfactory solution. Extensive experiments show that P
ml-ilc
achieves superior performance on both real-world and synthetic partial multi-label datasets in terms of different evaluation metrics.
Streaming Enumeration on Nested Documents
Authors: Muñoz Martín , Riveros Cristian
Published: October 2024

Some of the most relevant document schemas used online, such as XML and JSON, have a nested format. In the past decade, the task of extracting data from nested documents over streams has become especially relevant. We focus on the streaming evaluation of queries with outputs of varied sizes over nested documents. We model queries of this kind as Visibly Pushdown Annotators (VPAnn), a computational model that extends visibly pushdown automata with outputs and has the same expressive power as monadic second-order logic over nested documents. Since processing a document through a VPAnn can generate a massive number of results, we are interested in reading the input in a streaming fashion and enumerating the outputs one after another as efficiently as possible, namely, with constant delay. This article presents an algorithm that enumerates these elements with constant delay after processing the document stream in a single pass. Furthermore, we show that this algorithm is worst-case optimal in terms of update-time per symbol and memory usage.
Computing MEMs and Relatives on Repetitive Text Collections
Authors: Navarro Gonzalo
Published: October 2024

We consider the problem of computing the Maximal Exact Matches (MEMs) of a given pattern

\(P[1\mathinner{.. }m]\)

on a large repetitive text collection

\(T[1\mathinner{.. }n]\)

over an alphabet of size

\(\sigma\)

, which is represented as a (hopefully much smaller) run-length context-free grammar of size

\(g_{rl}\)

. We show that the problem can be solved in time

\(O(m^{2}\log^{\epsilon}n)\)

, for any constant

\(\epsilon\,{\gt}\,0\)

, on a data structure of size

\(O(g_{rl})\)

. Further, on a locally consistent grammar of size

\(O(\delta\log\frac{n\log\sigma}{\delta\log n})\)

, the time decreases to

\(O(m\log m(\log m+\log^{\epsilon}n))\)

. The value

\(\delta\)

is a function of the substring complexity of

\(T\)

and

\(\Omega(\delta\log\frac{n\log\sigma}{\delta\log n})\)

is a tight lower bound on the compressibility of repetitive texts

\(T\)

, so our structure has optimal size in terms of

\(n\)

,

\(\sigma\)

, and

\(\delta\)

. We extend our results to several related problems, such as finding

\(k\)

-MEMs, MUMs, rare MEMs, and applications.

Categories and Subject Descriptors: E.1 [
Data structures
]; E.2 [
Data storage representations
]; E.4 [
Coding and information theory
]: Data compaction and compression; F.2.2 [
Analysis of algorithms and problem complexity
]: Nonnumerical algorithms and problems—
Pattern matching, Computations on discrete structures, Sorting and searching.
Taxonomy and Survey of Collaborative Intrusion Detection System using Federated Learning
Authors: Wardana Aulia Arif , Sukarno Parman
Published: October 2024

This review article looks at recent research on Federated Learning (FL) for Collaborative Intrusion Detection Systems (CIDS) to establish a taxonomy and survey. The motivation behind this review comes from the difficulty of detecting coordinated cyberattacks in large-scale distributed networks. Collaborative anomalies are one of the network anomalies that need to be detected through robust collaborative learning methods. FL is promising collaborative learning method in recent research. This review aims to offer insights and lesson learn for creating a taxonomy of collaborative anomaly detection in CIDS using FL as a collaborative learning method. Our findings suggest that a taxonomy is required to map the discussion area, including an algorithm for training the learning model, the dataset, global aggregation model, system architecture, security, and privacy. Our results indicate that FL is a promising approach for collaborative anomaly detection in CIDS, and the proposed taxonomy could be useful for future research in this area. Overall, this review contributes to the growing knowledge of FL for CIDS, providing insights and lessons for researchers and practitioners. This research also concludes significant challenges, opportunities, and future directions in CIDS based on collaborative anomaly detection using FL.
Deformable Mapping of Rectal Cancer Whole-Mount Histology with Restaging MRI at Voxel Scale: A Feasibility Study
Authors: Miranda João , Heiselman Jon S. , Firat Canan , Chakraborty Jayasree , Vanguri Rami S. , Assuncao Antonildes N. , Nincevic Josip , Kim Tae-Hyung , Rodriguez Lee , Urganci Nil , Gonen Mithat , Garcia-Aguilar Julio , Gollub Marc J. , Shia Jinru , Horvat Natally
Published: October 2024

Accurate coregistration of preoperative MRI and whole-mount histology was feasible using an advanced deformable image registration technique in patients with rectal adenocarcinoma.
Connecting transcriptomics with computational modeling to reveal developmental adaptations in pediatric human atrial tissue
Authors: Salameh Shatha , Guerrelli Devon , Miller Jacob A. , Desai Manan , Moise Nicolae , Yerebakan Can , Bruce Alisa , Sinha Pranava , d’Udekem Yves , Weinberg Seth H. , Posnack Nikki Gillum
Published: October 2024

To date, our knowledge of the temporal changes that cardiomyocytes undergo during postnatal development is limited. In this study, we demonstrate age-dependent adaptations in the gene expression profile of >100 atrial tissue samples collected from congenital heart disease patients. We coupled transcriptomics datasets with computational modeling to simulate action potentials and calcium transients for different pediatric age groups.
Leveraging Big Data Analytics for Understanding Consumer Behavior in Digital Marketing: A Systematic Review
Authors: Theodorakopoulos Leonidas , Theodoropoulou Alexandra
Published: October 2024

The integration of big data analytics in digital marketing has fundamentally transformed how organizations understand and influence consumer behavior. This systematic review explores the potential of big data to offer deep insights into consumer preferences and behaviors. The current literature on big data and consumer behavior showcases its potential in enhancing marketing and customer experiences. However, significant gaps exist, such as longitudinal studies on how continuous big data–driven personalization affects consumer trust and loyalty over time. Addressing these gaps will advance academic understanding and offer practical insights for optimizing marketing strategies and improving customer experiences ethically. Focusing on these areas will contribute to a holistic view of big data’s responsible use in digital marketing. By utilizing large datasets, businesses can now tailor their marketing strategies to individual consumers, enhancing customer satisfaction and engagement. Adopting the PRISMA methodology, this review synthesizes recent literature to evaluate the benefits of big data in digital marketing. The research was conducted through a rigorous five‐stage process, encompassing the identification of key research questions, database searches, and the critical analysis of selected articles: (1) defining the initial topic, (2) developing the appropriate research questions, (3) identifying the necessary keywords, (4) identifying and searching databases, and finally (5) accessing and reading the articles. The databases that were searched were as follows: Scopus, Web of Science, Emerald Insight, Springer Link, and ScienceDirect. The articles that were selected were 19, in a total sum of 265 identified articles. The findings consolidate current knowledge on how big data analytics can optimize marketing strategies and consumer experiences. Ultimately, this review underscores the transformative potential of big data in digital marketing, highlighting its role in enhancing customer insights and driving more effective marketing strategies.
A Universal Source DC–DC Boost Converter for PEMFC‐Fed EV Systems With Optimization‐Based MPPT Controller
Authors: Hussaian Basha C. H. , Rafikiran Shaik , Touti Ezzeddine , Bechir Graba Besma , Aoudia Mouloud
Published: October 2024

Conventional energy networks produce energy with less efficiency. Also, these source’s development costs and size are more. So, the world is focusing on renewable energy networks for energy production to the consumer. In this work, a proton exchange membrane fuel stack (PEMFS) technology is selected for energy feeding to the hydrogen vehicle. The merits of this stack are more abundant, faster fuel stack operational response, and more efficient for electrical automotive networks. However, the fuel stack’s energy production is nonlinear and its operational point varies concerning the fuel stack device operating temperature. The particle swarm optimized adaptive network‐based fuzzy inference system (PSO‐ANFIS) is proposed in this work to find the operational point of the fuel cell network. The features of this hybrid methodology are the low number of iteration values required, low convergence time, low‐level dependence on the fuel stack, and high compliance for the quick deviations of the fuel system temperature. The operating efficiency and tracking time of the proposed maximum power point tracking (MPPT) controller are 95.60% and 0.1089 s. Another issue of the fuel cell is high output current generation and less voltage production. This condition is happening in the fuel cell because of its chemical reaction dynamics, internal resistance of the cell, and electrochemical potential. Due to this excess current flow in the fuel cell, the direct fuel stack‐fed electrical networks face the issue of high power conduction losses. To reduce the power conduction losses of the system, a single‐switch power circuit is used to reduce fuel source current, thereby optimizing the excessive power losses of the system. The whole fuel stack energy production network is analyzed by selecting the MATLAB Window.
Some Information Measures for Interval‐Valued Hesitant Fuzzy Sets in Multiple Criteria Decision‐Making
Authors: Chen Kun , Tan Jiyu , Zhu Chuanxi , Liu Gaochang
Published: October 2024

In the fields of information science and artificial intelligence, dealing with uncertainty, fuzziness, and complexity has always been a hot and difficult research topic. Especially in modern society, with the continuous development of science and technology, people are facing more and more complex problems. Interval‐valued hesitant fuzzy set (IVHFS) is an extended form of a fuzzy set. It can more flexibly express and handle uncertainty and fuzziness in decision‐making processes. However, in the practical application of the IVHFS, its information measurement is crucial, which is directly related to the application value of the IVHFS in various fields. Therefore, studying the information measurement of the IVHFS has important theoretical significance and practical value for the fields of information science and artificial intelligence. In spite of significant advances, entropy and similarity as the well‐known information measures for interval‐valued hesitant fuzzy information have not yet been thoroughly researched. In this contribution, we investigate information measures in the IVHFS, including nonprobabilistic entropy, similarity, and cross‐entropy. We first analyze the change law of hesitating uncertainty and fuzzy uncertainty in geometric space, and a nonprobabilistic entropy measurement method and its axiomatic definition for IVHFS are further developed. Then, a novel similarity measurement formula for IVHFS and its axiomatic requirements are proposed on the basis of the two nonfuzzy elements ( and ). Furthermore, the novel similarity measure is used to construct the cross‐entropy measure for IVHFS and its axiomatic requirements based on the association between the similarity and the cross‐entropy. Lastly, a MAGDM method is proposed by using the developed three information measures, and the efficacy of the proposed method is demonstrated by a numerical example of emergency communication support capacity evaluation. Comparative analysis and computational cost analysis are implemented to demonstrate the superiority and validity of the proposed information measures.
Comparative Profitability Analysis of Monoculture and Intercropping Land‐Use Systems: The Case of Smallholder Farmers in North‐Western Ethiopia
Authors: Belay Yonas Belete , Melka Yoseph
Published: October 2024

Tree plantations have become a common economic activity in the Ethiopian Highlands, particularly in our study areas. This is mainly due to the degradation and restrictions of natural forests, the introduction and expansion of fast‐growing tree species, and the potential short‐term economic benefits of woodlot plantations. Our research was conducted in Dangila and the nearby Adiskedam Woreda in North‐western Ethiopia to evaluate the profitability of monoculture and intercropping land‐use systems. We used the land expectation value (LEV) model developed by Faustmann to assess the profitability of the different land‐use systems in the study area. We obtained production costs and benefits of the land‐use system from the farmers through questionnaires and key informant interviews. Data analysis was carried out using Excel (2016) and SPSS statistical software. The findings revealed that the Acacia decurrens (Ad) farming practice showed the highest LEV at all interest levels, followed by intercropping land use. At a 15% interest rate, the eucalyptus with maize (E + M) land‐use system was the second most profitable with a value of 3677.5 USD. However, at 5% and 2% interest rates, the Ad with maize (Ad + M) land‐use system demonstrated the second highest LEV of 14,585.6 and 39,695.1 USD, respectively. The M land‐use system had the lowest LEV at all interest rates except at a 15% interest rate. The sensitivity analysis showed that fluctuations in product prices significantly impacted all land use systems, except M. In addition, changes in interest rates were the secondary factor affecting the Ad, E, and Ad + M land‐use systems. The LEV of M monoculture was notably influenced by the wage rate; however, it had the least impact on the other land‐use systems. Taking into account the interests of farmers, the profitability of land‐use systems, and the perception of farmers concerning adjacent land productivity, Ad and Ad intercropping with the M farming systems are recommended, and identifying the optimal mix of intercropping and optimum tree rotation age is fundamental in the future, which could increase productivity and make the farmer more profitable.
Performance of International Global Models and Official Tropical Cyclone Forecasts Over the Bien Dong Sea for the Period 2012–2019
Authors: Vo Van Hoa , Mai Khanh Hung , Du Duc Tien , Robert Hole Lars , Dang Dinh Quan , Tran Anh Duc , Pham Thi Hang , Hoang Gia Nam
Published: October 2024

This research validates tropical cyclone (TC) forecasts from the National Centre for Hydro‐Meteorological Forecasting of Vietnam, the Regional Specialized Meteorological Center (RSMC) Tokyo, and global models (the Japanese Meteorological Agency [JMA], global spectral model [GSM], the National Centers for Environmental Prediction [NCEP], Global Forecast System [GFS], and the European Centre for Medium‐Range Weather Forecasts [ECMWF] Integrated Forecasting System [IFS]) for 72 activated TCs over the Bien Dong Sea. The best quality track forecasts come from the IFS and then GFS and GSM, while the GFS provides a good intensity forecast compared to IFS and GSM. The official guidance and model track forecast tend to be slower and leftward compared to observations (negative biases of along and cross‐track errors). Regarding the ECMWF’s ensemble track forecast, the strike probability forecast is quite overforecast/overconfident, especially for a lead time of 72 h and at high probabilities.
A Multiple Case Study Exploring Person‐Centred Care in Care Homes
Authors: Hodge Gary , Byng Richard , Page Georgia , Lang Iain , Pearce Susie
Published: October 2024

Background: There are 14,228 care homes in England with a population of approximately 372,035 residents, many of whom are living with frailty or multiple and complex comorbidities. Policy and international literature advocate that care homes provide high‐quality person‐centred care that meets each person’s specific needs. This study aims to provide an exploration of person‐centred care in care homes in the South West of England from the perspective of all those involved.

Methods: A qualitative multiple case study design was used across seven care homes in a region of South West England. Semistructured interviews were conducted with 61 participants (residents, family and health and care professionals). Nonparticipant observations were undertaken in communal areas to understand the practices and cultures of the care homes. All data were analysed using reflexive thematic analysis.

Findings: The findings are presented as six themes, they are adjusting to the transition into a care home; people at the centre of care; the place we call home with the people we call family; working across the boundaries of care; supporting, valuing and empowering care home teams; and managing complex and challenging moments of care.

Conclusion: This study demonstrates a whole system understanding of person‐centred care across seven care homes. The main components of person‐centred care appear to be relational. These relationships take place in cultures and systems that are complex and challenging with care boundaries that need to be navigated. Navigating these care boundaries requires a people‐centred care approach built on partnerships and mutual respect.
Potential Mechanisms of Interstitial Lung Disease Induced by Antibody–Drug Conjugates Based on Quantitative Analysis of Drug Distribution
Authors: Koganemaru Shigehiro , Fuchigami Hirobumi , Morizono Chihiro , Shinohara Hiroko , Kuboki Yasutoshi , Furuuchi Keiji , Uenaka Toshimitsu , Doi Toshihiko , Yasunaga Masahiro
Published: October 2024

Antibody–drug conjugates (ADC) are a rapidly advancing category of therapeutic agents with notable anticancer efficacy. However, the emergence of interstitial lung disease as a severe ADC-associated adverse event highlights the need to better understand the underlying mechanisms. In this study, xenograft model mice with tumors expressing different levels of the trophoblast antigen 2 (TROP2) were generated by subcutaneously transplanting the various TROP2-expressing cancer lines. The mice received different doses of TROP2–eribulin, a novel TROP2-targeting ADC, composed of an anti-TROP2 antibody and the eribulin payload, joined by a cleavable linker. The concentration and distribution of TROP2–eribulin, as well as the pharmacokinetics of eribulin release, were assessed in tumor and lung tissues. Analysis of tumor tissue showed that the concentration of released eribulin was approximately 10-fold higher in NCI-H2110 (high TROP2 expression) than in A549 (low TROP2 expression), whereas analysis of lung tissue showed that TROP2–eribulin was distributed in lung tissue in a dose-dependent manner, regardless of TROP2 expression, with significantly more eribulin released in the high-dose group than in the other dose groups (P < 0.05). Immunofluorescence assay analysis showed that TROP2–eribulin localized to alveolar macrophages. In the analysis using human leukemia monocytic cell, the concentration of eribulin released from TROP2–eribulin was significantly reduced by the use of an Fc receptor inhibitor (P < 0.05). These results revealed that Fcγ receptor–mediated uptake by alveolar macrophages releases the cytotoxic payload into lung tissue, helping to clarify the pathogenesis of ADC-induced interstitial lung disease.
Automated Breast Density Assessment for Full-Field Digital Mammography and Digital Breast Tomosynthesis
Authors: Jiang Shu , Bennett Debbie L. , Chen Simin , Toriola Adetunji T. , Colditz Graham A.
Published: October 2024

Mammographic density is a strong risk factor for breast cancer and is reported clinically as part of Breast Imaging Reporting and Data System (BI-RADS) results issued by radiologists. Automated assessment of density is needed that can be used for both full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT) as both types of exams are acquired in standard clinical practice. We trained a deep learning model to automate the estimation of BI-RADS density from a prospective Washington University clinic-based cohort of 9,714 women, entering into the cohort in 2013 with follow-up through October 31, 2020. The cohort included 27% non-Hispanic Black women. The trained algorithm was assessed in an external validation cohort that included 18,360 women screened at Emory from January 1, 2013, and followed up through December 31, 2020, that included 42% non-Hispanic Black women. Our model-estimated BI-RADS density demonstrated substantial agreement with the density as assessed by radiologists. In the external validation, the agreement with radiologists for category B 81% and C 77% for FFDM and B 83% and C 74% for DBT shows important distinction for separation of women with dense breast. We obtained a Cohen’s κ of 0.72 (95% confidence interval, 0.71–0.73) in FFDM and 0.71 (95% confidence interval, 0.69–0.73) in DBT. We provided a consistent and fully automated BI-RADS estimation for both FFDM and DBT using a deep learning model. The software can be easily implemented anywhere for clinical use and risk prediction.

Prevention Relevance: The proposed model can reduce interobserver variability in BI-RADS density assessment, thereby providing more standard and consistent density assessment for use in decisions about supplemental screening and risk assessment.
Table S6 from A Precision Engineered Interleukin-2 for Bolstering CD8+ T- and NK-cell Activity without Eosinophilia and Vascular Leak Syndrome in Nonhuman Primates
Authors: Ma Lina , Acuff Nicole V. , Joseph Ingrid B. , Ptacin Jerod L. , Caffaro Carolina E. , San Jose Kristine M. , Aerni Hans R. , Carrio Roberto , Byers Anthony M. , Herman Rob W. , Pavlova Yelena , Pena Michael J. , Chen David B. , Buetz Christen , Ismaili Taylor K. , Pham Helene V. , Cucchetti Margot , Sassoon Ingrid , Koriazova Lilia K. , Leveque Joseph A. , Shawver Laura K. , Mooney Jill M. , Milla Marcos E.
Published: October 2024

Table S6
Table S5 from A Precision Engineered Interleukin-2 for Bolstering CD8+ T- and NK-cell Activity without Eosinophilia and Vascular Leak Syndrome in Nonhuman Primates
Authors: Ma Lina , Acuff Nicole V. , Joseph Ingrid B. , Ptacin Jerod L. , Caffaro Carolina E. , San Jose Kristine M. , Aerni Hans R. , Carrio Roberto , Byers Anthony M. , Herman Rob W. , Pavlova Yelena , Pena Michael J. , Chen David B. , Buetz Christen , Ismaili Taylor K. , Pham Helene V. , Cucchetti Margot , Sassoon Ingrid , Koriazova Lilia K. , Leveque Joseph A. , Shawver Laura K. , Mooney Jill M. , Milla Marcos E.
Published: October 2024

Table S5
Table S4 from A Precision Engineered Interleukin-2 for Bolstering CD8+ T- and NK-cell Activity without Eosinophilia and Vascular Leak Syndrome in Nonhuman Primates
Authors: Ma Lina , Acuff Nicole V. , Joseph Ingrid B. , Ptacin Jerod L. , Caffaro Carolina E. , San Jose Kristine M. , Aerni Hans R. , Carrio Roberto , Byers Anthony M. , Herman Rob W. , Pavlova Yelena , Pena Michael J. , Chen David B. , Buetz Christen , Ismaili Taylor K. , Pham Helene V. , Cucchetti Margot , Sassoon Ingrid , Koriazova Lilia K. , Leveque Joseph A. , Shawver Laura K. , Mooney Jill M. , Milla Marcos E.
Published: October 2024

Table S4
Figure S5 from A Precision Engineered Interleukin-2 for Bolstering CD8+ T- and NK-cell Activity without Eosinophilia and Vascular Leak Syndrome in Nonhuman Primates
Authors: Ma Lina , Acuff Nicole V. , Joseph Ingrid B. , Ptacin Jerod L. , Caffaro Carolina E. , San Jose Kristine M. , Aerni Hans R. , Carrio Roberto , Byers Anthony M. , Herman Rob W. , Pavlova Yelena , Pena Michael J. , Chen David B. , Buetz Christen , Ismaili Taylor K. , Pham Helene V. , Cucchetti Margot , Sassoon Ingrid , Koriazova Lilia K. , Leveque Joseph A. , Shawver Laura K. , Mooney Jill M. , Milla Marcos E.
Published: October 2024

Figure S5
Figure 4 from A Precision Engineered Interleukin-2 for Bolstering CD8+ T- and NK-cell Activity without Eosinophilia and Vascular Leak Syndrome in Nonhuman Primates
Authors: Ma Lina , Acuff Nicole V. , Joseph Ingrid B. , Ptacin Jerod L. , Caffaro Carolina E. , San Jose Kristine M. , Aerni Hans R. , Carrio Roberto , Byers Anthony M. , Herman Rob W. , Pavlova Yelena , Pena Michael J. , Chen David B. , Buetz Christen , Ismaili Taylor K. , Pham Helene V. , Cucchetti Margot , Sassoon Ingrid , Koriazova Lilia K. , Leveque Joseph A. , Shawver Laura K. , Mooney Jill M. , Milla Marcos E.
Published: October 2024

SAR’245 promotes CD8 T- and NK-cell proliferation and cytotoxicity in vitro. A, CMV+ donors were cultured with CMV peptide and rhIL-2 or SAR’245 for 5 days. The MFI of Ki67, CD25, perforin, and granzyme B on CMV+ CD8 T cells is reported. N = 2 donors. Data representative of two or more independent experiments. B, NK cell expression of Ki67, CD25, perforin, and granzyme B after a 5-day culture with rhIL-2 or SAR’245. N = 2 donors. Data representative of two or more independent experiments. C, Bulk PBMC or D, Enriched NK cells were primed overnight with rhIL-2 or SAR’245. Cells were then incubated with K562 target cells for 4 hours and percentage killing was measured. N = 3 donors. Data representative of one or more independent experiments. Data are shown as average ± SEM. MFI, median fluorescence intensity; NK, natural killer; rhIL-2, recombinant human interleukin-2.
Figure 2 from A Precision Engineered Interleukin-2 for Bolstering CD8+ T- and NK-cell Activity without Eosinophilia and Vascular Leak Syndrome in Nonhuman Primates
Authors: Ma Lina , Acuff Nicole V. , Joseph Ingrid B. , Ptacin Jerod L. , Caffaro Carolina E. , San Jose Kristine M. , Aerni Hans R. , Carrio Roberto , Byers Anthony M. , Herman Rob W. , Pavlova Yelena , Pena Michael J. , Chen David B. , Buetz Christen , Ismaili Taylor K. , Pham Helene V. , Cucchetti Margot , Sassoon Ingrid , Koriazova Lilia K. , Leveque Joseph A. , Shawver Laura K. , Mooney Jill M. , Milla Marcos E.
Published: October 2024

Pharmacokinetic and pharmacodynamic profiles of SAR’245 in NHP following variable dosing schedules. SAR’245 administered at 0.1 mg/kg i.v. to cynomolgus monkeys on a QW, Q2W, Q3W, or Q4W dosing schedule for three repeat dosing rounds. A, Plasma PK analysis was performed after the first and the third i.v. bolus doses of SAR’245. B, Changes in WBC from Q2W and Q3W groups in response to repeat dosing with SAR’245. C, Changes in lymphocyte and eosinophil counts from Q2W and Q3W groups. D, Changes (%) in CD8+ T cells in peripheral blood following each repeated dose in Q2W and Q3W dose groups. E, Ki67+ % in CD8 T in peripheral blood following each of three repeat doses of SAR’245 in all dose groups. Reported as mean ± standard error of the mean (SEM) of N = 3 animals.
Prediction of Significant Lesions on Capsule Endoscopy in Patients with Suspected Small Bowel Bleeding: External Validation of SSB Capsule Dx Score
Authors: Lima Capela Tiago , Cúrdia Gonçalves Tiago , Rosa Bruno , Cotter José
Published: October 2024

Introduction: Deciding which patients with suspected small bowel bleeding (SSB) would benefit most from small bowel capsule endoscopy (SBCE) is challenging. Our aim was to perform an external validation of the recently developed SSB Capsule Diagnostic (Dx) score that includes 3 variables (hospital admission with overt bleeding, hemoglobin <6.4 g/dL and age <54 years) and has been shown to be potentially useful in limiting the use of SBCE in SSB low-risk patients. Methods: Retrospectively included all adult patients submitted to SBCE for SSB between November 2007 and December 2019. Patients’ demographic, clinical and laboratorial data at the time of SBCE were recorded. Small bowel lesions were classified according to Saurin classification. The SSB Capsule Dx score was calculated, and its calibration and discrimination ability were assessed. Results: We assessed 473 SBCEs for SSB. Patients’ mean age was 61.2 ± 17.9 years and 65.8% were female. P2 lesions were present in 36.2% of SBCEs. There was a significant association between the score and P2 lesions (p < 0.001). Mean score was −0.21 ± 0.87 having a fair accuracy toward the outcome (C-statistic 0.700; 95% confidence interval, 0.652–0.749; p < 0.001). A cutoff value of 0 was found to have a high sensitivity (86.0%) and negative predictive value (84.9%) for the diagnosis of P2 lesions at SBCE. Conclusion: Patients with a SSB Capsule Dx score <0 are unlikely to have a significant lesion on SBCE, thus its routine use in the clinical practice may be useful in the identification of low-risk SSB patients.
Understanding how Fathers Influence Their Child’s Eating Behaviour
Authors: Avery Amanda ,   on behalf of the EFAD Public Health Specialist Group
Published: October 2024

Understanding how fathers engage in feeding while experiencing disadvantage is important for family-focused interventions. A cross-sectional online survey involving 264 Australian fathers was conducted to explore feeding involvement and the relationships between feeding practices, food insecurity, and household and work chaos. Practices related to coercive control, structure, and autonomy support were measured for two age groups (<2 years and 2-5 years). Multivariable linear regression was used to examine the associations for each practice. Three-quarters of the sample were food insecure, impacting adults more than children, and correlated with household chaos. Food insecurity was associated with increased 'persuasive feeding' and 'parent-led feeding' in younger children. Household chaos was positively associated with coercive control practices in both younger and older child groups, with the strongest associations for 'using food to calm' and 'overt restriction', respectively. In older child groups, household chaos was negatively associated with 'offer new foods' and 'repeated presentation of new foods'. Structure practices had no significant relationships with any factors, and work chaos did not predict any feeding practices. These findings emphasize a need for societal and structural support to address food insecurity and household chaos. Tailored strategies are crucial to support fathers in responsive feeding.
Untersuchung von OCT-Biomarker-Kandidaten bei Makulaödemen infolge diabetischer Retinopathie und Netzhautvenenverschlüssen
Authors: Augustin Albert
Published: October 2024

To improve the understanding of potential pathological mechanisms of macular edema (ME), we try to discover biomarker candidates related to ME caused by diabetic retinopathy (DR) and retinal vein occlusion (RVO) in spectral-domain optical coherence tomography images by means of deep learning (DL). 32 eyes of 26 subjects with non-proliferative DR (NPDR), 77 eyes of 61 subjects with proliferative DR (PDR), 120 eyes of 116 subjects with branch RVO (BRVO), and 17 eyes of 15 subjects with central RVO (CRVO) were collected. A DL model was implemented to guide biomarker candidate discovery. The disorganization of the retinal outer layers (DROL), i.e., the gray value of the retinal tissues between the external limiting membrane (ELM) and retinal pigment epithelium (RPE), the disrupted and obscured rate of the ELM, ellipsoid zone (EZ), and RPE, was measured. In addition, the occurrence, number, volume, and projected area of hyperreflective foci (HRF) were recorded. ELM, EZ, and RPE are more likely to be obscured in RVO group and HRFs are observed more frequently in DR group (all P ≤ 0.001). In conclusion, the features of DROL and HRF can be possible biomarkers related to ME caused by DR and RVO in OCT modality.
Optimal Strategies for Screening Common Birth Defects in Children of Low- and Middle-Income Countries: A Systematic Review
Authors: Zaki Umaima , Qazi Saqib Hamid , Shamim Urooj , Fatima Shibrah , Das Jai K. , Bhutta Zulfiqar A.
Published: October 2024

Introduction: Congenital anomalies are one of the major causes of the global burden of diseases, and low- and middle-income countries (LMICs) are disproportionately affected. This review assesses the prenatal and postnatal screening methods and compares the prevalence of major congenital anomalies in LMICs. Methodology: We conducted a systematic search in MEDLINE/PubMed, CINAHL, Cochrane databases of systematic reviews, clinical trials.gov for relevant studies using Medical Subject Headings and keywords. We categorized the studies into different systems and screening methods depending on the time the tests were conducted (prenatal or postnatal). The studies were then subjected to detailed descriptive analysis. Results: A total of 59 studies were selected for analysis; these focused on screening methods for congenital anomalies and compared their prevalence with regards to different systems. The most common screening techniques both prenatal and postnatal included antenatal ultrasound, fetal echocardiography, pulse oximetry, and clinical examination. The most common congenital abnormalities involved the central nervous system (neural tube defects) and musculoskeletal (clubfoot), followed by gastrointestinal (omphalocele and gastroschisis) and cardiovascular (structural heart defect). Overall, different systems had varying prevalences of different birth defects, ranging from 0.28 to 8.5%. In contrast, the prevalence of musculoskeletal system disorders varied from 1.01% to 3.96%, in the cardiovascular system from 0.57% to 10.4%, and in the urogenital group from 0.83% to 5.9%. Conclusion: The review highlights the lack of screening programs and studies, especially in the primary and secondary care settings in LMICs, and limited studies do indicate a high burden of various congenital anomalies. There is a need for guidelines and programs in global maternal and child health programs to include timely screening and management of common birth defects in LMICs.
Correlation of Magnetic Resonance Imaging and Computed Tomography with Biological Factor Expression and Lymph Node Metastasis in Aggressive Prostate Cancer
Authors: Ji Guanghai , Liu Fei , Chen Zhiqing , Peng Jie , Deng Hao , Xiao Sheng , Li Yun
Published: October 2024

Introduction: This article focused on probing the correlation of magnetic resonance imaging (MRI) and computed tomography (CT) manifestations with biological factor expression and lymph node metastasis (LNM) in aggressive prostate cancer (PCa). Methods: A total of 136 PCa patients underwent surgical treatment and received CT and MRI examinations before surgery, whereby the apparent diffusion coefficient (ADC) values of quantitative MRI (qMRI) parameters were obtained. Patients were categorized into the non-aggressive PCa group and the aggressive PCa group according to the postoperative pathological results and Gleason scores. The expression of biological factors (prostate-specific antigen [PSA], proliferating cell nuclear antigen [PCNA], p27, and Ki-67) in both groups was tested. CT and MRI manifestations of aggressive PCa patients were analyzed. The qMRI parameters, biological factors levels, and LNM were compared in two groups; the relationships between CT and MRI manifestations, qMRI parameters, and positive expression of biological factors and LNM were probed in two groups. Results: In the aggressive PCa group, MRI and CT presented different degrees of abnormal prostate changes. In the aggressive PCa group, PSA and p27 expression and ADC values were lower, and PCNA and Ki-67, and LNM rates were higher. Patients’ LNM rate was higher than that of ≤2 cm when the tumor diameter was >2 cm. ADC values were positively correlated with PSA and p27 positive expression and negatively correlated with PCNA, Ki-67, and LNM in the aggressive PCa group. Conclusion: MRI and CT manifestations of aggressive PCa had certain characteristics; MRI manifestations and qMRI possessed a correlation with biological factors and LNM; ADC could be employed to assess the aggressiveness of PCa.
Efficacy of Haploidentical Allogeneic Hematopoietic Cell Transplantation following Two Courses of Venetoclax and Azacytidine Therapy in Patients over 55 Years Old with Acute Myelogenous Leukemia
Authors: Cao Junjie , Zhuang Xianxu , Luo Danjie , Pei Renzhi , Lu Ying , Chen Dong , Li Shuangyue , Du Xiaohong , Liu Xuhui
Published: October 2024

Introduction: The combination of venetoclax (VEN) and azacytidine (AZA) has demonstrated potential in achieving rapid and effective remissions in elderly patients with acute myeloid leukemia (AML). Allogeneic hematopoietic stem cell transplantation is a promising potential cure for high-risk AML, as VEN-based therapies have a worse prognosis in elderly patients. This study aimed to assess the efficacy of sequential haploidentical HSCT following two courses of VEN and AZA therapy in patients with AML aged 55 years and older. Methods: We conducted a retrospective study on AML patients aged 55–70 years who received intensive chemotherapy or two courses of VEN/AZA therapy, followed by haploidentical allo-HSCT (haplo-HSCT) based on disease risk degree, measurable residual disease status, and patient’s preference. Results: Between January 2019 and December 2023, 141 newly diagnosed AML patients received initial treatment with intensive chemotherapy or VEN/AZA therapy. Among them, 64 patients received haplo-HSCT, while 77 did not. The 1-year overall survival (OS) and relapse-free survival (RFS) of patients who received haplo-HSCT were significantly higher than those who did not receive haplo-HSCT (p < 0.05). Among patients who received transplantation, there was no significant difference in 1-year OS and RFS between the VEN/AZA and intensive chemotherapy groups: 76.3% versus 69.3% (p = 0.367) for OS, and 74.5% versus 69.7% (p = 0.473) for RFS. High-risk ELN stratification and the presence of ≥4 gene mutations were associated with lower OS and RFS in both univariate and multivariate analyses. Conclusions: AML patients over 55 years of age who received haplo-HSCT after two courses of VEN/AZA therapy had outcomes similar to those who received haplo-HSCT after intensive chemotherapy, suggesting that two courses of VEN/AZA therapy as a bridge to haplo-HSCT are feasible for patients over 55 years old.