bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating the Nonlinear Vibration Characteristics of a GNP-Reinforced Honeycomb Sandwich Doubly Curved Shell Resting on Nonlinear Foundation
Authors: Bidgoli E. Mohammad-Rezaei , Arefi Mohammad
Published: January 2025

Effect of the nonlinear strain terms and nonlinear foundation is studied on the nonlinear vibration-based characteristics of a honeycomb shell reinforced with graphene nanoplatelets (GNPs) face–sheets. The governing motion’s equations are derived using Hamilton’s principle, in which the von Karman geometric nonlinear kinematic terms are used and a third-order nonlinear foundation. After extending the required relations for the effective characteristics of the honeycomb core as well as GNPs-reinforced face–sheets using Gibson’s formula and Halpin–Tsai, the constitutive relations are developed using the curvilinear coordinate system. After derivation of the time-dependent Partial Differential Equations (PDEs) of motion, Galerkin’s scheme is developed to arrive at a time Differential Equation (DE). To solve the nonlinear time-dependent differential equation, the perturbation technique and the modified Poincare–Lindstedt method are used to arrive at nonlinear results. After a comprehensive verification of literature results, the authors present a comprehensive parametric analysis to investigate the impact of various classes of parameters such as material, geometric and foundation on the nonlinear responses. The results of this research can be used in the design of novel structures in aerospace engineering and defense technology equipment.
Regeneration of Commercial SCR Catalyst Deactivated by Arsenic Poisoning Using a Green and Recyclable Solvent
Authors: Zhang Hongyu , Meng Juan , Chen Shuhao , Shi Weiwei , Fang Haifeng , Jiang Jie , Luo Jing , Cheng Long , Qin Hengfei
Published: January 2025

Selective catalytic reduction (SCR) is widely recognized as an effective method for denitrifying emissions in coal-fired power plants due to its straightforward application. However, a significant challenge arises from the degradation of catalysts used in these systems over time, mainly due to poisoning from arsenic. In our research, we introduce an eco-friendly technique that leverages hydrated acidic deep eutectic solvents (HDES) to extract arsenic from spent SCR catalysts. Our results demonstrate that the combined effects of the Lewis acid in ZnCl2, acting as a hydrogen bond acceptor (HBA) and the Brønsted acid site in H3PO4, acting as a hydrogen bond donor (HBD), along with 40% water, can achieve a remarkable arsenic removal rate of 98.11%. Furthermore, the regenerated catalyst exhibits an enhanced efficiency of 60.5% in the SCR of NO. Crucially, this approach preserves the structural integrity of the catalyst, marking it as a viable and sustainable option for the regeneration of spent SCR catalytic materials. This method not only enhances the removal efficiency of arsenic but also contributes to restoring the operational capabilities of the utilized catalysts.
The operator of relative complementation
Authors: Chajda Ivan , Länger Helmut
Published: January 2025

By the operator of relative complementation is meant a mapping assigning to every element [Formula: see text] of an interval [Formula: see text] of a lattice [Formula: see text] the set [Formula: see text] of all relative complements of [Formula: see text] in [Formula: see text]. Of course, if [Formula: see text] is relatively complemented then [Formula: see text] is nonempty for each interval [Formula: see text] and every element [Formula: see text] belonging to it. We study the question under what condition a complement of [Formula: see text] in [Formula: see text] induces a relative complement of [Formula: see text] in [Formula: see text]. It is well-known that this is the case provided [Formula: see text] is modular and complemented. However, we present a more general result. Further, we investigate properties of the operator of relative complementation, in particular in the case when the interval [Formula: see text] is a modular sublattice of [Formula: see text] or if it is finite. Moreover, we characterize when the operator [Formula: see text] of relative complementation satisfies the identity [Formula: see text] provided [Formula: see text] is complemented and we show a class of lattices where this identity holds. Finally, we establish sufficient conditions under which two different complements of a given element [Formula: see text] of [Formula: see text] induce the same relative complement of [Formula: see text] in this interval.
Chaotic and hypercyclic dynamics in the solution semigroup of a spatial conformable PDE
Authors: Elkhalloufy Khadija , Menchih Manal , Hilal Khalid , Kajouni Ahmed
Published: January 2025

The aim of this study is to analyze the dynamics of an initial value problem associated with a conformable spatial partial differential equation within the space [Formula: see text]. First, we demonstrate that the solution generates a strongly continuous semigroup on [Formula: see text]. Next, we construct a quasiconjugacy between this solution and another semigroup defined on a conformable weighted function space. Under specific conditions, we demonstrate that the problem exhibits both hypercyclicity and chaos.
Investigation of the influence of the loading direction on the strength of composite materials
Authors: Skvortsov Yu. V. , Evtushenko M. A. , Manukyan L. A.
Published: January 2025

Composites with various layings of unidirectional plies in the conditions of a plane stress state are considered. Using the criteria of maximum stresses and Tsai–Wu, their tensile and shear strength is investigated. The dependences of the failure stresses on the direction of loading in polar coordinates are constructed. For comparison, the results of calculations by the finite element method using the ANSYS Mechanical APDL 2020 R2 program are presented.
Modified security and cryptography-based data deduplication in cloud environment
Authors: Suresh Kumar Doddi , Srinivasu Nulaka
Published: January 2025

Data redundancy consumes huge storage space while setting up or employing cloud and fog storage. The dynamic cloud nature primarily focuses on the static environments which must be revised. Data deduplication solutions help minimize and control this issue by eradicating duplicate data from cloud storage systems. Since it might improve storage economy and security, data deduplication (DD) over encrypted data is a crucial problem in computing and storage systems. In this research, a novel approach to building secure deduplication systems across cloud and fog environments is developed. It uses MCDD and convergent cryptographic algorithms. The two most significant objectives of such systems are the focus of the suggested approach. Data redundancy must be minimized, but it also needs to be secured using a robust encryption method, which needs to be devised. The suggested approach is ideally suited for tasks like a user uploading new data to cloud storage or the fog. The proposed method might eliminate data redundancy by detecting redundancy at the block level. The testing results indicate that the recommended methodology can surpass a few cutting-edge techniques regarding computing effectiveness and security levels. The file is encrypted twice, once with the modified cryptographic model for deduplication (MCDD) and once with convergence encryption (CE).
A spheroidal dielectric compressible liquid inclusion in an infinite transversely isotropic piezoelectric matrix
Authors: Wang Xu , Schiavone Peter
Published: January 2025

We examine the three-dimensional problem associated with a spheroidal dielectric compressible liquid inclusion perfectly bonded to an infinite transversely isotropic piezoelectric matrix subjected to a uniform axisymmetric electromechanical loading at infinity. Our solution method is based on the general solution developed by [L. Kogan, C. Y. Hui and V. Molkov. Stress and induction field of a spheroidal inclusion or a penny-shaped crack in a transversely isotropic piezoelectric material. International Journal of Solids and Structures 33(19), pp. 2719–2737, 1996] describing the electroelastic field in a transversely isotropic piezoelectric solid. Specifically, the original boundary value problem is reduced to a set of four coupled linear algebraic equations. The internal uniform hydrostatic stress field within the liquid inclusion and the electroelastic field of displacements, electric potential, stresses and electric displacements in the piezoelectric matrix are then completely determined via the solution of this set of linear algebraic equations. A three-dimensional neutral liquid inclusion of arbitrary shape that does not disturb the prescribed uniform hydrostatic stresses and electric displacements in a generally anisotropic piezoelectric matrix is achieved.
Estimating Policy Functions in Payment Systems Using Reinforcement Learning
Authors: Castro Pablo , Desai Ajit , Du Han , Garratt Rodney , Rivadeneyra Francisco
Published: January 2025

This article uses reinforcement learning (RL) to approximate the policy rules of banks participating in a high-value payment system (HVPS). The objective of the RL agents is to learn a policy function for the choice of amount of liquidity provided to the system at the beginning of the day and the rate at which to pay intraday payments. Individual choices have complex strategic effects precluding a closed form solution of the optimal policy, except in simple cases. We show that, in a stylized two-agent setting, RL agents learn the optimal policy that minimizes the cost of processing their individual payments—without complete knowledge of the environment. We further demonstrate that, in more complex settings, both agents learn to reduce the cost of processing their payments and effectively respond to liquidity-delay tradeoff. Our results show the potential of RL to solve liquidity management problems in HVPS and provide new tools to assist policymakers in their mandates of ensuring safety and improving the efficiency of payment systems.
Sarcasm Identification and Classification in Hindi Newspaper Headlines
Authors: Ahmad Iram Ali , Gatla Praveen , Mundotiya Rajesh
Published: January 2025

Sarcasm identification in textual data is the most captivating area of research in the current research trends. It is a challenging task for humans as well as for the computer. In this paper, we have tried to identify sarcasm in the Hindi newspaper headlines of two of the most-read Hindi newspapers in India, namely Hindustan and Dainik Jagran. Initially, we collected 88,518 Hindi newspaper headlines and identified 1,945 headlines to be sarcastic, which we have considered for the present study. The headlines taken into consideration belong to the political domain and were published during some of the recent Legislative Assembly Elections of 2020, 2021 and 2022. Various machine learning and deep learning techniques have been used to develop the baseline models. It justifies the assumption that sarcastic text does not always bear a negative sentiment. It may bear a positive sentiment depending on the context. The present paper aims at the creation of a dataset consisting of 1,945 Hindi newspaper headlines, training and testing machine learning and deep learning models, namely Extra Trees Classifier, Random Forest Classifier, XGBClassifier, fasttext-stackedTCN and mBERT-stackedTCN for sarcasm identification on the dataset and comparing the results obtained by the models after the experiment. Out of all the choosen models, the Random Forest Classifier performs better with
F
1
score of 92.11 before data augmentation and and 90.68 after data augmentation.
Deep Learning Methods for Abstract Visual Reasoning: A Survey on Raven's Progressive Matrices
Authors: Małkiński Mikołaj , Mańdziuk Jacek
Published: January 2025

Abstract visual reasoning (AVR) domain encompasses problems solving which requires the ability to reason about relations among entities present in a given scene. While humans, generally, solve AVR tasks in a “natural” way, even without prior experience, this type of problem has proven difficult for current machine learning systems. The paper summarises recent progress in applying deep learning methods to solving AVR problems, as a proxy for studying machine intelligence. We focus on the most common type of AVR tasks—the Raven’s Progressive Matrices (RPMs)—and provide a comprehensive review of the learning methods and deep neural models applied to solve RPMs, as well as present the RPM benchmark sets. Performance analysis of the state-of-the-art approaches to solving RPMs leads to formulation of certain insights and remarks on the current and future trends in this area. We also attempt to put RPM studies in a more general perspective and demonstrate how real-world problems from the outside of AVR area can benefit from the presented research.
Proactive Conversational AI: A Comprehensive Survey of Advancements and Opportunities
Authors: Deng Yang , Liao Lizi , Lei Wenqiang , Yang Grace , Lam Wai , Chua Tat-Seng
Published: January 2025

Dialogue systems are designed to offer human users social support or functional services through natural language interactions. Traditional conversation research has put significant emphasis on a system’s response-ability, including its capacity to understand dialogue context and generate appropriate responses. However, the key element of proactive behavior – a crucial aspect of intelligent conversations – is often overlooked in these studies. Proactivity empowers conversational agents to lead conversations towards achieving pre-defined targets or fulfilling specific goals on the system side. Proactive dialogue systems are equipped with advanced techniques to handle complex tasks, requiring strategic and motivational interactions, thus representing a significant step towards artificial general intelligence. Motivated by the necessity and challenges of building proactive dialogue systems, we provide a comprehensive review of various prominent problems and advanced designs for implementing proactivity into different types of dialogue systems, including open-domain dialogues, task-oriented dialogues, and information-seeking dialogues. We also discuss real-world challenges that require further research attention to meet application needs in the future, such as proactivity in dialogue systems that are based on large language models, proactivity in hybrid dialogues, evaluation protocols and ethical considerations for proactive dialogue systems. By providing a quick access and overall picture of the proactive dialogue systems domain, we aim to inspire new research directions and stimulate further advancements towards achieving the next level of conversational AI capabilities, paving the way for more dynamic and intelligent interactions within various application domains.
Testing and Debugging Quantum Programs: The Road to 2030
Authors: Ramalho Neilson C. L. , Amario de Souza Higor , Lordello Chaim Marcos
Published: January 2025

Quantum computing has existed in the theoretical realm for several decades. Recently, quantum computing has re-emerged as a promising technology to solve problems that a classical computer could take hundreds of years to solve. However, there are challenges and opportunities for academics and practitioners regarding software engineering practices for testing and debugging quantum programs. This paper presents a roadmap for addressing these challenges, pointing out the existing gaps in the literature and suggesting research directions. We discuss the limitations caused by noise, the no-cloning theorem, the lack of a standard architecture for quantum computers, among others. Regarding testing, we highlight gaps and opportunities related to transpilation, mutation analysis, input states with hybrid interfaces, program analysis, and coverage. For debugging, we present the current strategies, including classical techniques applied to quantum programs, quantum-specific assertions, and quantum-related bug patterns. We introduce a conceptual model to illustrate concepts regarding the testing and debugging of quantum programs and the relationship between them. Those concepts are used to identify and discuss research challenges to cope with quantum programs through 2030, focusing on the interfaces between classical and quantum computing and on creating testing and debugging techniques that take advantage of the unique quantum computing characteristics.
RACEME: Embedded Intelligence for Correlation-driven Predictive Energy-harvesting Management in LoRa Networks
Authors: Jewsakul Sukanya , Ngai Edith Cheuk Han
Published: January 2025

The prolonged lifetime of energy-harvesting (EH) LoRa networks requires that all EH LoRa sensors utilize available harvested energy in an energy-neutral manner to avoid power failures. This requirement is challenging to fulfill due to the unpredictability of ambient energy sources and the spatio-temporal heterogeneity of sensors’ harvesting abilities. We present RACEME, a novel predictive EH-management framework by exploiting the embedded intelligence capability of energy-harvesting LoRa devices. It empowers energy-neutral operation in EH LoRa networks by leveraging the spatio-temporal correlation between EH LoRa sensors to optimize the harvested energy utilization. RACEME is an integrated system that consists of embedded machine learning (ML) for predictive EH management on the sensors and online cluster-based data reduction and recovery on the server. To maximize the accuracy of EH predictions, RACEME allows each sensor to implement an ML pipeline locally. Coupled with the cluster-based data-reduction feedback from the server, RACEME enables the sensors with higher harvested-energy availability and communication quality to transmit critical data more frequently in a probabilistic manner without sacrificing data quality. Compared with the state of the art, the experimental results reveal that RACEME improves EH prediction accuracy, network lifetime, and transmission overhead by up to 1.7, 2, and 8 times, respectively.
TagRecon: Fine-Grained 3D Reconstruction of Multiple Tagged Packages via RFID Systems
Authors: Wang Ziang , Duan Chunhui , Xue Jiawei , Li Fan , Feng Qihua , Zhu Yinan , Zhou Ziyang
Published: January 2025

To meet the new requirements of Industry 4.0, the logistics field has introduced 3D reconstruction technology. Computer vision-based solutions face challenges like bad lighting conditions and line-of-sight constraints. Meanwhile, the widespread adoption of RFID tags in supply chains offers an opportunity to enhance current reconstruction methods.

In this paper, we propose TagRecon, a fine-grained multi-object 3D reconstruction scheme utilizing well-deployed RFIDs. Specifically, TagRecon transforms the task of reconstruction into a problem of estimating 3D bounding boxes for tagged packages. By placing dual anchor tags on each target package, TagRecon enables accurate inference of the package’s translation and rotation using RFID-based localization and orientation sensing. Our scheme introduces a novel method to estimate rotations and translations for tagged packages, utilizing the known geometric relationship of anchor tags. Besides, to achieve simultaneous reconstruction of multiple packages, we manage to match tags from various packages through the correlation between anchor tag pairs. As far as we know, this is the first RFID-based solution that can simultaneously realize 3D translation and rotation estimation of multiple objects to a fine granularity. Experiments validate TagRecon achieves a 28.0 cm translation error and 6.8°, 6.0°, and 7.5° rotation errors for roll, pitch, and yaw angles on average.
Strong Chelating Agent Accelerated High Performance on Copper Polishing
Authors: Sheng Xingyao , Li Xiaotao , Wan Chuanyun , Sun Tao
Published: January 2025

Sustainability in Cu chemical mechanical polishing (CMP) processing for highly integrated device manufacturing demands electric energy saving and slurry consumption reduction, which can be achieved through faster CMP. A strong chelating agent, quinaldic acid (QA), was chosen to accelerate the polishing rate on Cu in an acidic H2O2-BTA system. The strong complexing capability of QA with Cu ions can facilitate the formation of a porous and loose copper oxide film on the Cu surface in acidic H2O2 solution and soften the microhardness of the Cu surface, which is beneficial for fast Cu removal in CMP process. The chemistry of QA with Cu in acidic solution was studied by electrochemical methods and physical measurements. The optimized QA containing polishing slurry produced a high Cu removal rate about 1.8 um/min with a good flatness.
Effects of Dietary Protein to Lipid Ratio and Insect Meal on Growth Performance, Feed Utilization, and the Gut Microbiome of Lake Whitefish (Coregonus clupeaformis)
Authors: Lawson Rebecca , Chen Yubing , Zhang Junyu , Chiasson Marcia A. , Ellis Jennifer , Bureau Dominique , Moccia Richard D. , Huyben David
Published: January 2025

Wild stocks of lake whitefish (Coregonus clupeaformis) are declining in the Great Lakes, and there is a lack of information on their nutritional requirements and gut health indicators to effectively culture them in an aquaculture setting. The aim of this study was to evaluate the growth performance, nutrient utilization, and gut microbiome of lake whitefish fed varying protein:lipid ratios with and without the inclusion of insect meal from black soldier fly (BSF). In total, 450 lake whitefish (301 ± 10 g) were fed one of five diets with differing protein‐to‐lipid ratios (high‐protein 54%, low‐protein 48%, high‐lipid 18%, or low‐lipid 12%), and an additional commercial control rainbow trout diet (Bluewater commercial control [BCC]). High‐protein diets included 5% BSF meal to explore its potential to partially replace fishmeal in the diet. After 16 weeks at 8.5°C, growth performance and nutrient digestibility were the highest for lake whitefish fed the high‐protein–high‐lipid (HPHL) and BCC diets, while the feed conversion ratio (FCR) was numerically lowest for the HPHL. Protein and energy retention, and lipid digestibility were highest for fish fed the HPHL and BCC diets, while the BCC diet had the highest lipid retained, concomitant with high viscerosomatic index (VSI). High lipid in fish, especially in the viscera that is removed during processing, is not desirable, thus the HPHL diet is recommended. The gut microbiome was dominated by Proteobacteria, specifically by the genera of Shewanella and Aeromonas, although feeding high‐lipid diets resulted in the lowest alpha diversity, but was not significant. These results are novel for this species, and we recommend that lake whitefish diets should be formulated to have a minimum 54:18 protein‐to‐lipid ratio. The results from this study provide baseline information on the nutrition and gut microbiome of lake whitefish, which can be used to develop a species‐specific feed rather than feeding them rainbow trout feed. However, further work on targeted breeding and genetic selection of broodstock, together with diet optimization, is needed to improve the growth performance and nutrient utilization in order to enable an effective, economical, and environmentally sustainable culture of lake whitefish.
SoC–Based Inverter Control Strategy for Grid‐Connected Battery Energy Storage in AC Microgrid
Authors: Allabadi Afaf , Abuishmais Ibrahim , Salem Qusay , Aljarrah Rafat , Al-Quraan Ayman
Published: January 2025

The successful integration of battery energy storage systems (BESSs) is crucial for enhancing the resilience and performance of microgrids (MGs) and power systems. This study introduces a control strategy designed to optimize the operation of BESSs. This control strategy optimizes the BESS operation by dynamically adjusting the inverter’s power reference, thereby, extending the battery cycle life. This approach incorporates a droop control mechanism that adjusts control actions in response to state‐of‐charge (SoC) fluctuations of the BESSs, thereby, enhancing system performance. The effectiveness of this SoC–based control strategy is demonstrated through Matlab/Simulink. It shows its capabilities in regulating power, voltage, grid synchronization, and stability. The paper utilizes a modified CIGRE MG benchmark for system evaluation. It presents case studies to demonstrate the effectiveness of the proposed control modifications. Additionally, a comparative analysis with a power–voltage (P–V) control strategy is presented. This analysis highlights the advantages of the proposed strategy in ensuring stable voltage regulation within the MG. This research provides a robust foundation for future developments in optimizing BESS integration. It offers a roadmap to advance the efficiency, reliability, and longevity of battery‐based solutions in the evolving landscape of sustainable energy systems. Additionally, it sheds light on the potential for scalability and applicability across diverse MG configurations and operational scenarios.
Bioresource Rent Value of Mt. Malindang Range Natural Park, Philippines, for Access and Benefit Sharing Scheme
Authors: Villanueva Grace V. , Calago Jersam C. , Alaman Bobby B. , Laput Joseph Glenn , Mapi-ot Emmarie F. , Parilla Richard B. , Trespalacio Gemmalyn M. , Ureta Joan U. , Ureta J. Carl
Published: January 2025

The Mt. Malindang Range Natural Park (MMRNP) in the Philippines is a vital protected area that harbors a diverse range of flora and fauna with substantial economic significance. Despite the extensive research conducted within MMRNP, the monetary value of its rich biodiversity remains vastly underestimated. This research employs a combination of key informant interviews and focus group discussions with local and indigenous people (IP) communities living near MMRNP. Value chain analysis and resource rent calculation were utilized to determine the economic value of MMNRP’s bioresources and ensure their sustainability and equitable management. Through these participatory methods, nine bioresources of significant economic importance have been identified, prioritized, and found to be collected, utilized, and traded by communities. These include five floral species: Dendrocnide sp., Calamus sp., Cinnamomum mercadoi, Agathis philippinensis, and Gymnostoma sumatranum, and four faunal species: Limnonectes sp., Apis sp., Apis cerana, and Sus philippensis. The estimated annual value of these economically important bioresources within MMRNP is PhP 42,708,861.20. Given its potential contribution to the local economy, the establishment of enabling policies to protect bioresources is crucial to mitigate the adverse impacts of natural resource exploitation on both economic growth and the development of local communities residing near MMRNP. It is strongly recommended that joint close monitoring and supervision by relevant agencies such as the Department of Environment and Natural Resources (DENR), local government units (LGUs), and Protected Area Management Boards (PAMB) be implemented. This approach will promote transparency and consensus building, ensuring the sustainable management of these invaluable bioresources for access and benefit of present and future generations.
An Enhanced Semisteady‐State Jaya Algorithm With a Control Coefficient and a Self‐Adaptive Multipopulation Strategy
Authors: Ankrah Joshua Churchill , Effah Francis Boafo , Twumasi Elvis
Published: January 2025

This paper introduces the enhanced semisteady‐state Jaya (ESJaya) algorithm, an improved version of the semisteady‐state Jaya (SJaya) algorithm. The ESJaya algorithm uses a control coefficient to regulate the influence of the best solution, achieving a better balance between exploration and exploitation. It also features a self‐adaptive multipopulation strategy and removes absolute value operators in its update equation for improved performance. Using 20 benchmark functions, the ESJaya algorithm is compared with the traditional Jaya, SJaya, and elitism‐based self‐adaptive multipopulation Jaya (SAMPEJaya) algorithms. The ESJaya algorithm ranks first in obtaining optimum values, mean accuracy, and stability, showing better overall performance than the others. The ESJaya algorithm ranks first with an average overall rank of 1.750, followed by Jaya, SAMPEJaya, and SJaya with average overall ranks of 2.650, 2.700, and 2.900, respectively. The Wilcoxon signed‐rank test confirms the statistical significance of the overall rankings. When compared with the Snow Geese Algorithm (SGA), Big Bang–Big Crunch Algorithm (BBBCA), firefly algorithm (FA), bat algorithm (BA), cuckoo search algorithm (CSA), and flower pollination algorithm (FPA), the ESJaya algorithm gives competitive results in terms of obtaining optimum values, mean accuracy, and stability. Using four real‐world engineering problems, the ESJaya algorithm is compared with the recently proposed piranha predation optimization algorithm (PPOA) and four state‐of‐the‐art algorithms, namely, the COLSHADE algorithm, the sCMAgES algorithm, the SASS algorithm, and the EnMODE algorithm. The ESJaya algorithm finds optimum solutions with good accuracy, consistency, and stability. Overall, it has a slower convergence and longer run time due to its multipopulation strategy and its search for the best solution after each solution update. However, it consistently finds more optimal solutions than other improved algorithms.
Cow’s Milk Protein May Induce Allergy and Inflammation in Intestinal Epithelial Cells Through Regulating HOTAIR Expression and NF‐κB Signaling Pathway
Authors: Mao Kangwei , Liu Jiangyan , Li Dalei , Gu Siyu , Zhang Chenxi , Li Mengmeng , Sun Jun , Wang Juan
Published: January 2025

Background: Cow’s milk protein allergy (CMPA) is associated with activation of proinflammatory signaling pathways and overexpression of inflammatory mediators. Long noncoding RNA (LncRNA) HOX transcript antisense intergenic RNA (HOTAIR) is a LncRNA, which is involved in the occurrence and development of many biological processes and diseases. HOTAIR can prevent necrotizing enterocolitis. This study aims to explore the effect of milk protein on NCM‐460 cells and its mechanism of action with HOTAIR.

Methods: NCM‐460 cells were induced by cow’s milk protein to establish in vitro cell models. CCK‐8 and EdU staining were used for evaluating the effects of cow’s milk protein on the viability and proliferation. ELISA was used for comparing the levels of inflammatory cytokines. TUNEL staining was conducted for evaluating the apoptosis. Expression levels of HOTAIR were detected by RT‐qPCR. The expression of NF‐κB signaling pathway–related molecules in cells was explored to evaluate the mechanism of HOTAIR in improving ALI.

Results: Cow’s milk protein decreased the viability NCM‐460 cells and also decreased the expression of HOTAIR. Moreover, it can induce the antiproliferative and proapoptotic effects on NCM‐460 cells, and overexpression of LncRNA HOTAIR can partially reverse the effects of cow’s milk protein. In addition, overexpression of LncRNA HOTAIR reversed the effects of cow’s milk protein on NF‐κB signaling.

Conclusions: Cow’s milk protein may induce the allergy and inflammation in intestinal epithelial cells through regulating HOTAIR expression and NF‐κB signaling pathways.
Synthesis and Characterization of Copper Ferrite Nanoparticles for Efficient Photocatalytic Degradation of Organic Dyes
Authors: Mazurenko Julia , Sijo A. K. , Kaykan Larysa , Kotsyubynsky Volodymyr , Gondek Łukasz , Zywczak Antoni , Marzec Mateusz , Vyshnevskyi Oleksii
Published: January 2025

This paper reports the successful synthesis of spinel‐type CuFe2O4 ferrite nanoparticles with an average particle size of 24 nm, produced using the citrate sol–gel autocombustion method. The structure of the synthesized material was analyzed through x‐ray diffraction (XRD) and further supported by Raman and FT‐IR spectroscopy. The analysis confirmed that the material formed a spinel ferrite structure with the Fd3m space group. Valence states and energy levels of the elements were examined using x‐ray photoelectron spectroscopy (XPS). Surface morphology was studied using scanning electron microscopy (SEM), coupled with elemental analysis. The magnetic properties of the synthesized CuFe2O4 ferrite nanoparticles were investigated using a vibrating sample magnetometer (VSM). Magnetization measurements revealed that the sample exhibited characteristic magnetic parameters of copper ferrite, with a saturation magnetization (Ms) of 23.10 emu/g, a coercivity Hc of 415 Oe, and a remnant magnetization (Mr) of 12.80 emu/g. These magnetic properties enable efficient magnetic separation of the nanoparticles from aqueous solutions, thereby enhancing process efficiency and minimizing catalyst loss during photocatalytic applications. Optical and photocatalytic properties were investigated using spectrophotometry, revealing an optical band gap of 1.85 eV, which demonstrates potential for photocatalytic activity under visible light. The CuFe2O4 ferrite effectively degraded dyes such as methylene blue (MB), malachite green (MG), Safranine (S), Congo Red (CR), and Rhodamine B (RhB) within 180 min, highlighting its practical application potential. The study identified that hydroxyl radicals (·OH), generated from H2O2 decomposition under visible light irradiation, played a critical role in enhancing the efficiency of the photo‐Fenton reaction. A proposed mechanism involves the excitation of CuFe2O4 under visible light, facilitating electron transfer that leads to the generation of ·OH radicals, which degrade the dye molecules. Among the tested dyes, CR exhibited the highest degradation percentage with a rate constant of 0.033 min⁻1 and followed a pseudo‐first‐order kinetic model. The effect of hydrogen peroxide concentration on dye degradation efficiency was also evaluated.
Accumulation of CD38 in Hybrid Epithelial/Mesenchymal Cells Promotes Immune Remodeling and Metastasis in Breast Cancer
Authors: Visal Tanvi H. , Bayraktar Recep , den Hollander Petra , Attathikhun Michael A. , Zhou Tieling , Wang Jing , Shen Li , Minciuna Corina-Elena , Chen Meng , Barrientos-Toro Elizve , Batra Harsh , Raso Maria Gabriela , Yang Fei , Parra Edwin R. , Sahin Aysegul A. , Calin George A. , Mani Sendurai A.
Published: January 2025

Triple-negative breast cancer (TNBC) is a highly metastatic subtype of breast cancer. The epithelial-to-mesenchymal transition is a nonbinary process in the metastatic cascade that generates tumor cells with both epithelial and mesenchymal traits known as hybrid EM cells. Recent studies have elucidated the enhanced metastatic potential of cancers featuring the hybrid EM phenotype, highlighting the need to uncover molecular drivers and targetable vulnerabilities of the hybrid EM state. Here, we discovered that hybrid EM breast tumors are enriched in CD38, an immunosuppressive molecule associated with worse clinical outcomes in liquid malignancies. Altering CD38 expression in tumor cell impacted migratory, invasive, and metastatic capabilities of hybrid EM cells. Abrogation of CD38 expression stimulated an antitumor immune response, thereby preventing the generation of an immunosuppressive microenvironment in hybrid EM tumors. CD38 levels positively correlated with PD-L1 expression in samples from patients with TNBC. Moreover, targeting CD38 potentiated the activity of anti–PD-L1, eliciting strong antitumor immunity, with reduced tumor growth in hybrid EM models. Overall, this research exposes upregulation of CD38 as a specific survival strategy utilized by hybrid EM breast tumors to suppress immune cell activity and sustain metastasis, with strong implications in other carcinomas that have hybrid EM properties.

Significance: Hybrid cells co-featuring epithelial and mesenchymal traits in triple-negative breast cancer express elevated levels of CD38 to induce immunosuppression and metastasis, indicating CD38 inhibition as potential strategy for treating breast cancer.
Follow-up Analysis Enhances Understanding of Molecular Residual Disease in Localized Non–Small Cell Lung Cancer
Authors: Zhang Jia-Tao , Liu Si-Yang , Gao Xuan , Liu Si-Yang Maggie , Yan Bingfa , Huang Chen , Jiao Zicong , Yan Hong-Hong , Pan Yi , Dong Song , Gao Wei , Gong Yuhua , Tu Hai-Yan , Xia Xue-Feng , Zhou Qing , Zhong Wen-Zhao , Yang Xue-Ning , Yi Xin , Wu Yi-Long
Published: January 2025

Purpose:

The prognostic value of molecular residual disease (MRD) in non–small cell lung cancer (NSCLC) is well established, with treatment-guiding results anticipated. Here, we present updated analyses from our previously published cohort study of 261 patients with NSCLC undergoing complete resection.

Experimental Design:

A total of 261 patients with stage I to III lung cancer who underwent radical surgery were enrolled. Enrolled patients underwent follow-up blood draws according to the predefined time points after surgery. As of December 31, 2023, with a median follow-up of 43.4 months, 948 postoperative blood samples were collected.

Results:

Landmark and longitudinal MRD exhibited positive predictive values of 91.3% and 92.8%, respectively, with a median lead time of 5.2 months. Negative predictive values were 76.5% and 93.2%, respectively. Patients with landmark undetectable MRD could not benefit from adjuvant therapy through the updated follow-up (P = 0.529). Among the 13 patients with recurrent NSCLC and longitudinal undetectable MRD, seven (53.8%) had brain-only metastases, and four (30.8%) had no updated blood samples for over 6 months prior to recurrence. Besides, for those with longitudinal detectable MRD, higher maximum variant allele frequency (>0.55%) and ctDNA level (>13 hGE/mL) were associated with a high risk of short-term recurrence. Additionally, updated follow-up data further support that the peak time for detectable MRD was 18 months after landmark detection.

Conclusions:

These findings suggest the significant potential of MRD in guiding personalized treatment for NSCLC. Postoperative longitudinal undetectable MRD can indicate a cured population.
Co-blocking TIGIT and PVRIG Using a Novel Bispecific Antibody Enhances Antitumor Immunity
Authors: Lin Yuan , Lin Kan , Fu Qiang , Sun Xing , Wang Huan , Su Lu , Xu Yanhui , Liao Cheng
Published: January 2025

T-cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domains (TIGIT) and poliovirus receptor–related immunoglobulin domain (PVRIG) are immune checkpoints co-expressed on activated T and NK cells, contributing to tumor immune evasion. Simultaneous blockade of these pathways may enhance therapeutic efficacy, positioning them as promising dual targets for cancer immunotherapy. This study aimed to develop a bispecific antibody (BsAb) to co-target TIGIT and PVRIG. Expression of TIGIT and PVRIG was assessed on tumor-infiltrating lymphocytes from patients with various cancers, including non–small cell lung cancer (n = 63) and colorectal cancer (n = 26). The BsAb was engineered by fusing anti-PVRIG nanobodies to the N terminus of anti-TIGIT antibodies. Functional characterization of the BsAb was performed in vitro and in vivo, including assessments of T- and NK-cell activation and cytotoxicity. Pharmacokinetics and safety profiles were evaluated in cynomolgus monkeys. Statistical analyses were conducted using the Student t test. The results showed that the BsAb effectively blocked TIGIT and PVRIG from binding their respective ligands, CD155 and CD112, leading to significant increases in T-cell activation (2.8-fold; P < 0.05) and NK-cell cytotoxicity (1.8-fold; P < 0.05). In vivo, the BsAb demonstrated potent antitumor activity, both as a monotherapy and in combination with anti–PD-1 or anti–PD-L1, in humanized peripheral blood mononuclear cell–reconstituted and transgenic mouse models. Pharmacokinetic studies in cynomolgus monkeys revealed a favorable profile, with no dose-limiting toxicities observed after four repeated doses of 200 mg/kg. These findings provide compelling preclinical evidence for the therapeutic potential of targeting the TIGIT–PVRIG axis with a BsAb. This approach shows promise for enhancing antitumor immunity and warrants further investigation in clinical trials.
Table 1 from A Cost-Effective Two-Step Approach for Multi-Cancer Early Detection in High-Risk Populations
Authors: Geng Shuaipeng , Li Shiyong , Wu Wei , Chang Yinyin , Mao Mao
Published: January 2025

Case–control cohort demographic
Data from A Cost-Effective Two-Step Approach for Multi-Cancer Early Detection in High-Risk Populations
Authors: Geng Shuaipeng , Li Shiyong , Wu Wei , Chang Yinyin , Mao Mao
Published: January 2025

Abstract
In population-wide cancer screening, three key issues need to be focused on: the number of cancer cases identified, the number of false positives, and the cost. OncoSeek is a multi-cancer early detection (MCED) test using seven protein tumor markers and artificial intelligence. SeekInCare is an MCED test that integrates the seven protein tumor markers and four cancer genomic features from cell-free DNA by shallow whole-genome sequencing. In a two-step approach, the initial screening is conducted using OncoSeek, and SeekInCare is then used as the secondary test for individuals who tested positive by OncoSeek. We simulated a screening in five million adults ages ≥50 years with a cancer incidence rate of 1.9%. Whereas at 91.0% specificity OncoSeek had 441,450 false positives, using the two-step approach significantly reduced false positives to 34,335 (0.7%). Although SeekInCare and Galleri identified more cancer cases (32,015 and 27,455, respectively) than the two-step MCED (21,280), their total costs reached $3,750 million and $4,745 million, respectively. As the positive predictive value of two-step MCED (38.3%) was comparable with SeekInCare (27.7%) and Galleri (38.3%), it reduced the cost by 5.3-fold and 6.6-fold, respectively, amounting to a total cost of $713.6 million and a cost of $143 per individual screened. The cost of per cancer case detected was $117,133 for SeekInCare and $172,828 for Galleri, which were 3.5-fold and 5.2-fold higher, respectively, than the two-step MCED ($33,534). The two-step approach not only significantly reduces false positives but also cuts down the screening cost substantially, making it a cost-effective strategy for population-wide cancer screening.
Significance:
Large-scale screening inevitably leads to significant financial burdens on the healthcare system, which is a key factor constraining nationwide screenings. The two-step MCED approach not only maintains comparable performance but also substantially alleviates financial strains compared with the direct use of next-generation sequencing–based MCED tests for massive screenings.
A Comparative randomised controlled trial of Homeopathy –vs- Allopathy in Acute Otitis Media and its recurrence in Children
Authors: Varanasi Roja , Bhalerao Rupali , Sumithran Paul , Rompicherla Kiranmayee G. , Singh Pramodji , Ramteke Sunil , Karthikeyan D. , Ramesh Dubashi , Subbarayalu Bhuvaneswari , Chauhan Shraddha , Venugopal Jayakrishnan , Kampilli Shravani , Meena Ajay , Kumar Arvind , Siddiqui Vaqar Ahmed , Oberai Praveen , Manchanda Raj K.
Published: January 2025

Objective: This study evaluates the efficacy of homeopathic treatments for Acute Otitis Media (AOM) in children, comparing outcomes to standard allopathic treatments. Building on promising pilot study results that suggested homeopathy's non-inferiority, this multicenter trial aims to validate these findings and assess their broader clinical applicability.

Method: This open-label, randomized controlled trial was conducted on children (aged 02 to 12 years), suffering from acute otitis media. Primary outcome was changes in Acute Otitis Media-Severity of Symptoms (AOM-SOS) scale and Tympanic Membrane Examination scale (TMES) over 21 days and time to improvement in pain through FPS-R (Facial Pain Scale-Revised) over 10 days. The secondary outcomes were the need for antibiotics during acute AOM and the recurrence over 12 months.

Results: Intention to treat analysis was carried out on 222 children; Homeopathy(n=116)(H-group), Allopathy(n=106) (A-group). Statistically significant reduction in AOM-SOS+TMES score in H-group compared to A-group was observed at time point day 3 (mean diff.±sd: 1.67±0.47; 95% CI: 0.75 to 2.59; p=0.001), at day 7 (mean diff.±sd: 1.22±0.56; 95% CI: 0.13 to 2.31, p=0.028) favored homeopathy. However, the median time for FPS-R score to become zero by day 10 (H= 3 days, A= 4 days) was statistically insignificant (p=0.29). None of the children in the H group required antibiotics whereas it was required in 14 children(12.4%) in A group .

Conclusion: Homeopathic treatment helped in managing acute otitis media in children similar to that of Allopathic treatment. Homeopathy can be a safe treatment approach in managing in this condition. Further blinded studies are warranted.
Clinical Outcomes of the PAUL® Glaucoma Implant for secondary glaucoma after vitreoretinal surgery
Authors: Weber Constance , Schipper Pascal , Walz Wolfgang , Raming Kristin , Künzel Sandrine , Holz Frank G. , Liegl Raffael , Mercieca Karl
Published: January 2025

Background:
To report clinical outcomes from a single-center cohort undergoing PAUL® Glaucoma Implant (PGI) surgery for secondary glaucoma after vitreoretinal surgery (VR).

Methods:
Retrospective review of patients undergoing PGI surgery at the University Eye Hospital Bonn, Germany, from 04/2021 to 05/2023.

Results:
33 eyes of 33 patients were included. Mean number of preoperative VR surgeries was 2 (1-4), the majority following retinal detachment (23 eyes, 69.7%). 18 eyes had previous silicone oil tamponade (54.4%). Complete (without drops) and qualified (with or without drops) success rates (95% CI) after one year were 69.7% (54.5–84.8) and 97% (90.9-100) for Criterion A (IOP≤21mmHg), 66.7% (51.5-81.8) and 87.9% (51.5-81.8) for Criterion B (IOP≤18mmHg), 54.5% (39.4-72.7) and 72.7% (54.5-87.9%) for Criterion C (IOP≤15mmHg) and 24.2% (9.1-39.4) and 30.3% (15.2-48.4) for Criterion D (IOP≤12mmHg) respectively. Mean IOP decreased from 25.64 mmHg (14-49 mmHg) to 13.59 mmHg (8-20 mmHg) (reduction of 41.1%) after 12 months with a reduction of IOP-lowering agents from 3.21 (1 – 5) to 0.38 (0 – 3). Seven eyes (21.2%) developed postoperative complications, most of which eventually resolved. Two eyes had a tube flushing because of high postoperative IOP with silicone oil obstruction. Postoperative non-glaucoma related procedures were performed in 10 eyes (24.4%). None of these led to high IOP or further complications in the postoperative phase.

Conclusions:
PGI surgery is an effective procedure for reducing both IOP and topical therapy in patients with uncontrolled secondary glaucoma following vitreoretinal surgery. Non-glaucoma related procedures can be safely performed after PGI implantation with good IOP control.