bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Research on the Ignition Characteristics and Inhibition Strategy for Venting Emissions Mixture of Failure LiFePO4 Battery
Authors: Wang Yan , Zhang Zhaozhi , Yu Ruiguang , Li Yalun , Wang Hewu , Lu Languang , Feng Xuning , Ouyang Minggao
Published: December 2024

When the concentration of a gas is below its lower flammable limit and the content of a liquid is below its minimum explosible concentration, their combined fuel mixture can be ignitable. The flammability characteristics and inhibition strategies for battery emission mixtures deserve further in-depth research attention. This article presents experimental research on the ignition characteristics and inhibition strategy for a venting emission mixture of a failure LiFePO4 battery. By identifying the components of venting emissions, ignition experiments for gases, electrolyte mist, their combination fuels, and mixtures with additives are performed to determine the flammable parameters, including ignition sensitivity and severity. The hybrid combination of non-flammable venting gases and electrolyte mist has the potential to induce ignition. However, there still exists a non-ignition region, where the gas concentration ratio (mg) is below 0.15 and the liquid concentration ratio (ml) is below 0.1. A safety design principle can be proposed: increasing ignition temperature, prolonging ignition time, and reducing maximum pressure. Adhering to this principle, a non-flammable electrolyte consisting of 1 mol LiPF6 in EC:DEC = 1:1 vol%, with FEC at 10% and VC at 1%, can be considered as an optimization strategy. In comparison to the original gas–liquid mixtures, the region where no ignition occurs becomes wider when both the mg is below 0.45 and the ml is below 0.3. The new two-phase mixture has an ignition temperature of 835 °C, which is, respectively, 50% higher than that of the original mixture. Overall, this experimental research demonstrates an innovative methodology for assessing the battery venting emission mixture safety while proposing a design principle for modifying non-flammable electrolyte functional materials. Consequently, these findings can contribute to formulating more suitable preventive and protective measures for commercial electric vehicles and battery energy storage systems’ thermal safety designs.
Recent Advances in Lithium Iron Phosphate Battery Technology: A Comprehensive Review
Authors: Chen Tao , Li Man , Bae Joonho
Published: December 2024

Lithium iron phosphate (LFP) batteries have emerged as one of the most promising energy storage solutions due to their high safety, long cycle life, and environmental friendliness. In recent years, significant progress has been made in enhancing the performance and expanding the applications of LFP batteries through innovative materials design, electrode engineering, and manufacturing techniques. This review paper provides a comprehensive overview of the recent advances in LFP battery technology, covering key developments in materials synthesis, electrode architectures, electrolytes, cell design, and system integration. This review paper aims to provide a comprehensive overview of the recent advances in lithium iron phosphate (LFP) battery technology, encompassing materials development, electrode engineering, electrolytes, cell design, and applications. By highlighting the latest research findings and technological innovations, this paper seeks to contribute to the continued advancement and widespread adoption of LFP batteries as sustainable and reliable energy storage solutions for various applications. We also discuss the current challenges and future prospects for LFP batteries, emphasizing their potential role in sustainable energy storage solutions for various applications, including electric vehicles, renewable energy integration, and grid-scale energy storage.
A Multimodal Machine Learning Model in Pneumonia Patients Hospital Length of Stay Prediction
Authors: Annunziata Anna , Cappabianca Salvatore , Capuozzo Salvatore , Coppola Nicola , Di Somma Camilla , Docimo Ludovico , Fiorentino Giuseppe , Gravina Michela , Marassi Lidia , Marrone Stefano , Parmeggiani Domenico , Polistina Giorgio Emanuele , Reginelli Alfonso , Sagnelli Caterina , Sansone Carlo
Published: December 2024

Hospital overcrowding, driven by both structural management challenges and widespread medical emergencies, has prompted extensive research into machine learning (ML) solutions for predicting patient length of stay (LOS) to optimize bed allocation. While many existing models simplify the LOS prediction problem to a classification task, predicting broad ranges of hospital days, an exact day-based regression model is often crucial for precise planning. Additionally, available data are typically limited and heterogeneous, often collected from a small patient cohort. To address these challenges, we present a novel multimodal ML framework that combines imaging and clinical data to enhance LOS prediction accuracy. Specifically, our approach uses the following: (i) feature extraction from chest CT scans via a convolutional neural network (CNN), (ii) their integration with clinically relevant tabular data from patient exams, refined through a feature selection system to retain only significant predictors. As a case study, we applied this framework to pneumonia patient data collected during the COVID-19 pandemic at two hospitals in Naples, Italy—one specializing in infectious diseases and the other general-purpose. Under our experimental setup, the proposed system achieved an average prediction error of only three days, demonstrating its potential to improve patient flow management in critical care environments.
Advancing 3D Engineered In Vitro Models for Heart Failure Research: Key Features and Considerations
Authors: van Doorn Elisa C. H. , Amesz Jorik H. , Manintveld Olivier C. , de Groot Natasja M. S. , Essers Jeroen , Shin Su Ryon , Taverne Yannick J. H. J.
Published: December 2024

Heart failure is characterized by intricate myocardial remodeling that impairs the heart’s pumping and/or relaxation capacity, ultimately reducing cardiac output. It represents a major public health burden, given its high prevalence and associated morbidity and mortality rates, which continue to challenge healthcare systems worldwide. Despite advancements in medical science, there are no treatments that address the disease at its core. The development of three-dimensional engineered in vitro models that closely mimic the (patho)physiology and drug responses of the myocardium has the potential to revolutionize our insights and uncover new therapeutic avenues. Key aspects of these models include the precise replication of the extracellular matrix structure, cell composition, micro-architecture, mechanical and electrical properties, and relevant physiological and pathological stimuli, such as fluid flow, mechanical load, electrical signal propagation, and biochemical cues. Additionally, to fully capture heart failure and its diversity in vivo, it is crucial to consider factors such as age, gender, interactions with other organ systems and external influences—thereby recapitulating unique patient and disease phenotypes. This review details these model features and their significance in heart failure research, with the aim of enhancing future platforms that will deepen our understanding of the disease and facilitate the development of novel, effective therapies.
Breath-Holding as a Stimulus to Assess Peripheral Oxygenation Flow Using Near-Infrared Spectroscopic Imaging
Authors: Leiva Kevin , Gonzalez Isabella , Murillo Juan , Espinosa Aliette , Kirsner Robert S. , Godavarty Anuradha
Published: December 2024

A mammalian breath-hold (BH) mechanism can induce vasoconstriction in the limbs, altering blood flow and oxygenation flow changes in a wound site. Our objective was to utilize a BH paradigm as a stimulus to induce peripheral tissue oxygenation changes via studies on control and diabetic foot ulcer (DFU) subjects. Subjects were imaged under a breath-hold paradigm (including 20 s BH) using a non-contact spatio-temporal-based NIRS device. Oxygenated flow changes were similar between darker and lighter skin colors but differed between wound site and normal background tissues. Thus, the ability of peripheral vasculature to response to oxygenation demand can be assessed in DFUs.
Methods for Rapid Characterization of Tunable Microbubble Formulations
Authors: Harpster Savannah L. , Piñeiro Alexandra M. , Wong Joyce Y.
Published: December 2024

To optimize microbubble formulations for clinical applications, the size distribution, concentration, and acoustic intensity must be rapidly measurable to allow for the successful iteration of microbubble design. In this paper, a comprehensive method was developed to compare microbubble formulations with different lipid shell compositions using optical and acoustic methods of measurement to collect the size distribution, concentration, and mean scattering intensity. An open-source ImageJ macro code was modified for the selective counting and sizing of brightfield microbubble images. A high-throughput agarose phantom was designed to collect multiple scattering reflections of microbubble samples to estimate the echogenicity of each microbubble solution. The information contained in the size distribution and concentration, combined with the instantaneous scattering power, can identify modifications needed for prototyping specific microbubble formulations.
Analysis and Testing of a Flyable Micro Flapping-Wing Rotor with a Highly Efficient Elastic Mechanism
Authors: Pan Yingjun , Su Huijuan , Guo Shijun , Chen Si , Huang Xun
Published: December 2024

A Flapping-Wing Rotor (FWR) is a novel bio-inspired micro aerial vehicle configuration, featuring unique wing motions which combine active flapping and passive rotation for high lift production. Power efficiency in flight has recently emerged as a critical factor in FWR development. The current study investigates an elastic flapping mechanism to improve FWRs’ power efficiency by incorporating springs into the system. The elastic force counteracts the system inertia to accelerate or decelerate the wing motion, reducing the power demand and increasing efficiency. A dynamic model was developed to simulate the unique kinematics of the FWR’s wing motions and its elastic mechanism, considering the coupling of aerodynamic and inertial forces generated by the wings, along with the elastic and driven forces from the mechanism. The effects of the spring stiffness on the aerodynamic performance and power efficiency were investigated. The model was then verified through experimental testing. When a spring stiffness close to the mechanical system resonance was applied, the power efficiency of the test model increased by 16% compared to the baseline model without springs, generating an equivalent average lift. With an optimal elastic flapping mechanism for greater lift and lower power consumption, the FWR was fully constructed with onboard power and a control receiver weighing 27.79 g, successfully achieving vertical take-off flight. The current model produces ten times greater lift and has nearly double the wing area of the first 2.6 g flyable FWR prototype.
Detecting Hypoxia Through the Non-Invasive and Simultaneous Monitoring of Sweat Lactate and Tissue Oxygenation
Authors: Cheng Cindy , Ganguly Sayan , Li Pei , Tang Xiaowu
Published: December 2024

Hypoxia, characterized by inadequate tissue oxygenation, may result in tissue damage and organ failure if not addressed. Current detection approaches frequently prove insufficient, depending on symptoms and rudimentary metrics such as tissue oxygenation, which fail to comprehensively identify the onset of hypoxia. The European Pressure Ulcer Advisory Panel (EPUAP) has recognized sweat lactate as a possible marker for the early identification of decubitus ulcers, nevertheless, neither sweat lactate nor oxygenation independently provides an appropriate diagnosis of hypoxia. We have fabricated a wearable device that non-invasively and concurrently monitors sweat lactate and tissue oxygenation to fill this gap. The apparatus comprises three essential components: (i) a hydrogel-based colorimetric lactate biosensor, (ii) a near-infrared (NIR) sensor for assessing tissue oxygenation, and (iii) an integrated form factor for enhanced wearability. The lactate sensor alters its hue upon interaction with lactate in sweat, whereas the NIR sensor monitors tissue oxygenation levels in real-time. The device underwent testing on phantom exhibiting tissue-mimicking characteristics and on human sweat post aerobic and anaerobic activities. Moreover, the device was demonstrated to be capable of real-time “on-body” simultaneous monitoring of sweat lactate spikes and tissue oxygenation (StO2) drops, which showed strong correlation during a hypoxia protocol. This innovative technology has a wide range of potential applications, such as post-operative care, sepsis detection, and athletic performance monitoring, and may provide economical healthcare solutions in resource-limited regions.
Self-Assembled Lubricin (PRG-4)-Based Biomimetic Surface-Enhanced Raman Scattering Sensor for Direct Droplet Detection of Melamine in Undiluted Milk
Authors: Han Mingyu , Hlaing Mya Myintzu. , Stoddart Paul R. , Greene George W.
Published: December 2024

Surface-enhanced Raman scattering (SERS) is a powerful optical sensing platform that amplifies the target signals by Raman scattering. Despite SERS enabling a meager detection limit, even at the single-molecule level, SERS also tends to equally enhance unwanted molecules due to the non-specific binding of noise molecules in clinical samples, which complicates its use in complex samples such as bodily fluids, environmental water, or food matrices. To address this, we developed a novel non-fouling biomimetic SERS sensor by self-assembling an anti-adhesive, anti-fouling, and size-selective Lubricin (LUB) coating on gold nanoparticle (AuNP) functionalized glass slide surfaces via a simple drop-casting method. Compared to a conventional AuNPs-SERS substrate, the biomimetic SERS meets the requirements of simple preparation and enables direct droplet detection without any sample pre-treatment. Atomic force microscopy was used to confirm the self-assembled Lubricin coating on the AuNP surface, acting as an anti-fouling and size-selective protection layer. A series of Raman spectra were collected using melamine as the target analyte, which was spiked into 150 mM NaCl solution or undiluted milk. It was demonstrated that the LUB coating effectively prevents the detrimental fouling generated by the proteins and fats in milk, ensuring the clear detection of melamine. Our sensor showed high selectivity and could detect melamine in milk at concentrations as low as 1 ppm. Given that the EU/US legal limit for melamine in food is 2.5 ppm, this sensor offers a promising, cost-effective solution for routine screening and has potential applications for detecting food adulteration in the food safety, environmental monitoring, aquaculture, and biomedical fields.
Optimized Extraction of Polyphenols from Kiwifruit Peels and Their Biological Activities
Authors: Shkeir Batoul , El Darra Nada , Azakir Bilal , Khazaal Salma , Sokhn Elie Salem , Koubaa Mohamed , Maroun Richard G. , Louka Nicolas , Debs Espérance
Published: December 2024

(1) Background: Kiwifruit is a globally valued fruit. Its industrial processing produces a substantial amount of waste, particularly peels, which present an appealing potential source of bioactive compounds. This study focuses on optimizing the extraction of phenolics from kiwi peels using a water bath (WB) and infrared irradiation (IR) and assessing their biological activities. (2) Methods: Optimal conditions for polyphenol extraction from kiwifruit peels, in terms of temperature and time, were determined using Response Surface Methodology. Total phenolic content (TPC) was measured by the Folin–Ciocalteu method, and antioxidant activity was assessed utilizing the DPPH method. Antibacterial activities against Bacillus cereus, Staphylococcus aureus, Escherichia coli, and Salmonella Typhimurium were determined using the minimum inhibitory concentration (MIC). The lyophilized extract was tested for its anticancer effect on A549 lung cancer cell lines. The phytochemical profiles of the WB and IR extracts were analyzed through High-Performance Liquid Chromatography (HPLC). (3) Results: The optimal extraction conditions for the WB method were found to be 75 °C for 35 min, and 90 °C for 5 min for IR. The corresponding TPC obtained by IR was 21 mg GAE/g DM, which was 4.4 times higher than that obtained by WB (4.8 mg GAE/g DM). This indicates that IR was more efficient in extracting phenolics from kiwi peels. The antioxidant activity under the optimum conditions of WB and IR was 14 mg TE/g DM and 16 mg TE/g DM, respectively. Both the WB and IR extracts demonstrated antibacterial activity against B. cereus with an MIC value of 25 mg/mL. Additionally, the IR extract displayed an antibacterial effect against S. aureus, with an MIC value of 50 mg/mL. The WB and IR kiwi peel extracts were effective in significantly reducing A549 cell viability at 50 µg/mL and 100 µg/mL, respectively. Caffeic acid (0.54 ppm) and catechin (5.44 ppm) were the major polyphenols identified in WB and IR extracts, as determined by HPLC. (4) Conclusions: IR was more efficient in extracting phenolics from kiwi peels than WB. The findings also suggest that kiwi peel can be effectively utilized as an antioxidant, antibacterial, and anticancer agent.
Feasibility Study of Magnesium Slag, Fly Ash, and Metakaolin to Replace Part of Cement as Cementitious Materials
Authors: Wei Fulu , Xiao Hairong , Zhang Jia , He Zhenqing , Cao Xuanhao , Guan Bowen
Published: December 2024

To achieve the efficient utilization of magnesium slag, this study investigates the use of magnesium slag, fly ash, and metakaolin as partial substitutes for cement in cementitious materials. The reactivity of these materials is assessed based on the compressive strength of mortar. The response surface methodology is employed to explore the influence of material proportions on the strength performance of cement mortar. The mechanisms underlying strength development in the composite system are examined through XRD, SEM, TG-DTG, and BET analyses. Additionally, the effect of magnesium slag on the drying shrinkage properties of cement mortar is studied. The experimental results indicate that magnesium slag exhibits low reactivity and cannot be used alone as an active admixture. The optimal proportion of magnesium slag, fly ash, metakaolin, and cement is 10:10:10:70, achieving over 80% of the strength of pure cement mortar and approximately 1.5 times the strength of cement mortar containing 30% magnesium slag. Furthermore, magnesium slag helps mitigate the volume shrinkage caused by drying in cement mortar. Therefore, this study can facilitate the comprehensive utilization of magnesium slag in the construction sector, reducing its negative impact on the ecological environment.
Assessment of Mechanical Behavior and Microstructure of Unsaturated Polyester Resin Composites Reinforced with Recycled Marble Waste
Authors: Baghloul Rahima , Babouri Laidi , Hebhoub Houria , Boukhelf Fouad , El Mendili Yassine
Published: December 2024

The quarrying and utilization of natural stones such as marble and granite are growing rapidly in developing countries. However, the processing, cutting, sizing, and shaping of these stones to render them functional generates huge quantities of waste and dust. These materials are often disposed of openly in the environment, and their potentially hazardous nature has negative repercussions on both the environment and human health. In this study, marble waste (MW) was used as a filler in the unsaturated polyester resin (UPR) matrix to enhance performance and characteristics while adding value to the waste and minimizing manufacturing costs. For this purpose, samples of UPR/MW composites were produced with 0, 5, 10, 15, and 20 wt.% of MW incorporated into the UPR. A full characterization that focused on the microstructure, thermal stability, and physical and mechanical properties was carried out. The results revealed that the use of 10 to 15% of MW improves mechanical performance, with increases from 17 to 26 kJ/m2, 14 to 17 MPa, and 794 to 1522 GPa in impact strength, tensile strength, and elastic modulus, respectively. By introducing a 20% MW filler, the composite loses its performance, particularly Shore D hardness, and becomes very brittle. Thermogravimetric analysis (TGA) indicated significant thermal stabilization, with a delay in the start decomposition temperature of 28 °C for 20 UPR/MW compared to 0 UPR/MW. Additionally, morphological and microstructural tests, namely, FT-IR, XRD, and SEM analysis, show a microstructural change, including the formation of crystalline phases, enhancing matrix-filler interactions due to the creation of Mg-O and Ca-O chemical bonds and the forming of filler agglomeration at high introduction rates that lead to defects in the microstructure. These results confirmed the mechanical results of the UPR/MW composites.
Therapeutic Exploitation of Neuroendocrine Transdifferentiation Drivers in Prostate Cancer
Authors: Maylin Zoe R. , Smith Christopher , Classen Adam , Asim Mohammad , Pandha Hardev , Wang Yuzhuo
Published: December 2024

Neuroendocrine prostate cancer (NEPC), an aggressive and lethal subtype of prostate cancer (PCa), often arises as a resistance mechanism in patients undergoing hormone therapy for prostate adenocarcinoma. NEPC is associated with a significantly poor prognosis and shorter overall survival compared to conventional prostate adenocarcinoma due to its aggressive nature and limited response to standard of care therapies. This transdifferentiation, or lineage reprogramming, to NEPC is characterised by the loss of androgen receptor (AR) and prostate-specific antigen (PSA) expression, and the upregulation of neuroendocrine (NE) biomarkers such as neuron-specific enolase (NSE), chromogranin-A (CHGA), synaptophysin (SYP), and neural cell adhesion molecule 1 (NCAM1/CD56), which are critical for NEPC diagnosis. The loss of AR expression culminates in resistance to standard of care PCa therapies, such as androgen-deprivation therapy (ADT) which target the AR signalling axis. This review explores the drivers of NE transdifferentiation. Key genetic alterations, including those in the tumour suppressor genes RB1, TP53, and PTEN, and changes in epigenetic regulators, particularly involving EZH2 and cell-fate-determining transcription factors (TFs) such as SOX2, play significant roles in promoting NE transdifferentiation and facilitate the lineage switch from prostate adenocarcinoma to NEPC. The recent identification of several other key novel drivers of NE transdifferentiation, including MYCN, ASCL1, BRN2, ONECUT2, and FOXA2, further elucidates the complex regulatory networks and pathways involved in this process. We suggest that, given the multifactorial nature of NEPC, novel therapeutic strategies that combine multiple modalities are essential to overcome therapeutic resistance and improve patient outcomes.
The Optical Sensing of Volatile Organic Compounds Using Porphyrins
Authors: Ermakova Elizaveta V. , Bessmertnykh-Lemeune Alla
Published: December 2024

The detection of volatile organic compounds (VOCs) is a rapidly growing research area due to the importance of VOCs in environmental pollution, human health assessment, food quality control, and homeland security. Optical sensing materials based on porphyrins are particularly appealing for VOCs detection, owing to availability of porphyrins, their exceptional optical and binding properties, as well as their photo and chemical stability. As research and technology continue to advance, optical sensors involving these materials are expected to play an increasing role in various applications. This article presents an overview of porphyrin-based sensing materials developed for use as optical sensors for VOCs in a gaseous phase. First, sensing films composed exclusively of porphyrin molecules are discussed, followed by the materials obtained by grafting or the incorporation of porphyrins into organic and inorganic polymer matrices. Considering the growing interest in multianalyte analysis with porphyrin-based sensor arrays, special attention is devoted to this area.
Making a Difference from Day One: The Urgent Need for Universal Neonatal Hearing Screening
Authors: Athanasopoulos Michail , Samara Pinelopi , Batsaouras Georgios , Athanasopoulos Ioannis
Published: December 2024

Neonatal hearing screening (NHS) is a critical public health measure for early identification of hearing loss, ensuring timely access to interventions that can dramatically improve a child’s language development, cognitive abilities, and social inclusion. Beyond clinical benefits, NHS provides long-term advantages in education and quality of life. Given that congenital hearing loss affects approximately 1–2 in every 1000 newborns worldwide, the case for universal screening is clear. Countries like the United States and Australia have successfully implemented NHS, leading to earlier diagnoses, improved language development, and better educational outcomes. In Europe, while many nations have adopted NHS, consistency remains a challenge. Countries such as Norway and the United Kingdom stand out for their well-established systems, whereas others, like Greece, have made notable progress but have yet to mandate NHS nationwide. This highlights the need for cohesive national policies across Europe to ensure universal coverage. Screening methods such as Transient Evoked Otoacoustic Emissions (TEOAE) and Automated Auditory Brainstem Response (AABR) are established tools for detecting hearing impairments in neonates. Despite their demonstrated efficacy, NHS remains inconsistent globally, particularly in low- and middle-income regions that lack mandatory policies or access to reliable screening technologies. This perspective advocates for the urgent need to make NHS mandatory in all countries, emphasizing its societal benefits and cost-effectiveness. Early diagnosis supports prompt intervention, like hearing aids or cochlear implants, which are most effective when implemented before six months. It also empowers families to make informed decisions, fosters educational inclusion, and mitigates the social and emotional challenges of undiagnosed hearing loss. Policymakers, healthcare providers, and international organizations must prioritize universal NHS to ensure no child is left behind due to unaddressed hearing loss.
Sensory and Motor Function, Pain, and Health Status in Children with Arthrogryposis and Myelomeningocele
Authors: Bartonek Åsa , Eriksson Marie
Published: December 2024

Background/Objectives: Proprioception and sensory disorders have been reported in children with arthrogryposis multiplex congenita (AMC) and myelomeningocele (MMC), but valid and reliable assessment tools are limited in accurately identifying the sensory aspects of motor disorders. This study aimed to investigate the somatosensory status in the feet and legs. An additional purpose of this study was to explore pain, skin irritations, and health status. Methods: Nineteen children with AMC, twenty-three with MMC, and twenty-two typically developing (TD) children (7–18 years old) were tested using a somatosensory test battery in ankle kinesthesia and in identifying four different types of floors. Results: In the AMC and MMC groups, the threshold to perceive the somatosensory stimuli was not achieved by all participants. MMC participants perceived somatosensory stimuli less than TD participants in all tests, with a higher level of the lesion and more affected ambulation. The MMC group identified one floor significantly less often than the TD group. The AMC group performed better than the MMC group in two-point discrimination, vibration sensation, and some light-touch pressure tests. There were no differences among the TD, AMC, and MMC groups in ankle kinesthesia. Pain was reported by four (21%) subjects in the AMC group and five (22%) in the MMC group, and skin irritations were reported by three (13%) participants in the MMC group. There was no difference among the TD, AMC, and MMC groups in health status as reported using the EQ-5D-Y visual analog scale. Conclusions: Although differences in sensory aspects were the most evident between the groups, assessments of activity and participation levels in the rehabilitation of children with disabilities are also recommended.
Clinical Potential of Misshapen/NIKs-Related Kinase (MINK) 1—A Many-Sided Element of Cell Physiology and Pathology
Authors: Kot Anna , Koszewska Dominika , Ochman Błażej , Świętochowska Elżbieta
Published: December 2024

Misshapen/NIKs-related kinase (MINK) 1 belongs to the mammalian germinal center kinase (GCK) family. It contains the N-terminal, conserved kinase domain, a coiled-coil region, a proline-rich region, and a GCK, C-terminal domain with the Citron-NIK-Homology (CNH) domain. The kinase is an essential component of cellular signaling pathways, which include Wnt signaling, JNK signaling, pathways engaging Ras proteins, the Hippo pathway, and STRIPAK complexes. It thus contributes to regulating the cell cycle, apoptosis, cytoskeleton organization, cell migration, embryogenesis, or tissue homeostasis. MINK1 plays an important role in immunological responses, inhibiting Th17 and Th1 cell differentiation and regulating NLRP3 inflammasome function. It may be considered a link between ROS and the immunological system, and a potential antiviral target for human enteroviruses. The kinase has been implicated in the pathogenesis of sepsis, rheumatoid arthritis, asthma, SLE, and more. It is also involved in tumorigenesis and drug resistance in cancer. Silencing MINK1 reduces cancer cell migration, suggesting potential for new therapeutic approaches. Targeting MINK1 could be a promising treatment strategy for patients insensitive to current chemotherapies, and could improve their prognosis. Moreover, MINK1 plays an important role in the nervous system and the cardiovascular system development and function. The modulation of MINK1 activity could influence the course of neurodegenerative diseases, including Alzheimer’s disease. Further exploration of the activity of the kinase could also help in gaining more insight into factors involved in thrombosis or congenital heart disease. This review aims to summarize the current knowledge on MINK1, highlight its therapeutic and prognostic potential, and encourage more studies in this area.
Asymmetric Imidazolium-Based Ionic Liquid Crystal with Enhanced Ionic Conductivity in Low-Temperature Smectic Phases
Authors: Kim Yuna , Jeevika Alagan , Suwa Tomoya , Kubo Kazuya , Iimura Ken-ichi
Published: December 2024

We report the synthesis and characterization of a novel asymmetric imidazolium-based ionic liquid crystal (ILC) dimer exhibiting stable smectic phases over a wide temperature range, including room temperature. This unique molecular structure, combining two distinct mesogenic cores, reduces packing density, which enhances ion mobility and achieves high ionic conductivity in the smectic phase (0.1 mS cm−1 at 40 °C). Electrochemical impedance spectroscopy (EIS) confirmed improved ionic conductivity at lower temperatures, along with a stable electrochemical window of ±3 V. Application as a solid-state electrolyte in an electrochromic device demonstrated effective switching behavior and reversible redox cycles. These findings suggest that this asymmetric imidazolium-based ILC is a viable candidate for advanced electrochemical applications due to its structural stability and anisotropic ionic pathways.
ML-AKA: An Authentication Protocol for Non-Standalone 5G-Based C-IoT Networks
Authors: Mahapatra Byomakesh , Singh Vikash , Bhattacharjee Rituraj , Srinivasan C. R.
Published: December 2024

When it comes to the development of 4G and 5G technologies, long-range IoT or machine-to-machine (M2M) communication can be achieved with the help of cellular infrastructure. In non-standalone (NSA) 5G infrastructure, cellular-IoT (C-IoT) devices are attached and authenticated by a 4G core network even if it is connected to a 5G base station. In an NSA-based 5G network, the presence of dual connectivity sometimes raises interoperability and authentication issues due to technological differences between LTE and 5G. An attacker explores these technological differences, introduces the threats, and performs various types of attacks like session hijacking at the interfaces and Man-in-the-Middle (MITM) attacks. With the introduction of these attacks, the attackers exploit the network resources and pinch out various critical information sources. To resolve this issue, the NSA-based C-IoT network must incorporate robust and seamless authentication and authorization mechanisms. This article presents the ML-AKA protocol that is used to enhance interoperability and trust between 4G and 5G networks by using a uniform key-sharing (UKS) mechanism. The proposed ML-AKA protocol is analyzed with the help of the AVISPA tool and validated with the use of Proverif. Further, the proposed protocol is compared with other existing protocols like EPS-AKA and UAKA-D2D, and the outcome shows that the proposed protocol significantly reduces the chances of MITM, DDOS and Spoofing attacks during the interoperability in the NSA-C-IoT network.
Smartphone-Based Pupillometry Using Machine Learning for the Diagnosis of Sports-Related Concussion
Authors: Maxin Anthony J. , Whelan Bridget M. , Levitt Michael R. , McGrath Lynn B. , Harmon Kimberly G.
Published: December 2024

Background: Quantitative pupillometry has been proposed as an objective means to diagnose acute sports-related concussion (SRC). Objective: To assess the diagnostic accuracy of a smartphone-based quantitative pupillometer in the acute diagnosis of SRC. Methods: Division I college football players had baseline pupillometry including pupillary light reflex (PLR) parameters of maximum resting diameter, minimum diameter after light stimulus, percent change in pupil diameter, latency of pupil constriction onset, mean constriction velocity, maximum constriction velocity, and mean dilation velocity using a smartphone-based app. When an SRC occurred, athletes had the smartphone pupillometry repeated as part of their concussion testing. All combinations of the seven PLR parameters were tested in machine learning binary classification models to determine the optimal combination for differentiating between non-concussed and concussed athletes. Results: 93 football athletes underwent baseline pupillometry testing. Among these athletes, 11 suffered future SRC and had pupillometry recordings repeated at the time of diagnosis. In the machine learning pupillometry analysis that used the synthetic minority oversampling technique to account for the significant class imbalance in our dataset, the best-performing model was a random forest algorithm with the combination of latency, maximum diameter, minimum diameter, mean constriction velocity, and maximum constriction velocity PLR parameters as feature inputs. This model produced 91% overall accuracy, 98% sensitivity, 84.2% specificity, area under the curve (AUC) of 0.91, and an F1 score of 91.6% in differentiating between baseline and SRC recordings. In the machine learning analysis prior to oversampling of our imbalanced dataset, the best-performing model was k-nearest neighbors using latency, maximum diameter, maximum constriction velocity, and mean dilation velocity to produce 82% accuracy, 40% sensitivity, 87% specificity, AUC of 0.64, and F1 score of 24%. Conclusions: Smartphone pupillometry in combination with machine learning may provide fast and objective SRC diagnosis in football athletes.
Helicobacter pylori: Routes of Infection, Antimicrobial Resistance, and Alternative Therapies as a Means to Develop Infection Control
Authors: Elbehiry Ayman , Abalkhail Adil , Anajirih Nuha , Alkhamisi Fahad , Aldamegh Mohammed , Alramzi Abdullah , AlShaqi Riyad , Alotaibi Naif , Aljuaid Abdullah , Alzahrani Hilal , Alzaben Feras , Rawway Mohammed , Ibrahem Mai , Abdelsalam Moustafa H. , Rizk Nermin I. , Mostafa Mohamed E. A. , Alfaqir Moneef Rohail , Edrees Husam M. , Alqahtani Mubarak
Published: December 2024

Helicobacter pylori (H. pylori) is a Gram-negative, spiral-shaped bacterium that colonizes the gastric epithelium and is associated with a range of gastrointestinal disorders, exhibiting a global prevalence of approximately 50%. Despite the availability of treatment options, H. pylori frequently reemerges and demonstrates increasing antibiotic resistance, which diminishes the efficacy of conventional therapies. Consequently, it is imperative to explore non-antibiotic treatment alternatives to mitigate the inappropriate use of antibiotics. This review examines H. pylori infection, encompassing transmission pathways, treatment modalities, antibiotic resistance, and eradication strategies. Additionally, it discusses alternative therapeutic approaches such as probiotics, anti-biofilm agents, phytotherapy, phototherapy, phage therapy, lactoferrin therapy, and vaccine development. These strategies aim to reduce antimicrobial resistance and enhance treatment outcomes for H. pylori infections. While alternative therapies can maintain low bacterial levels, they do not achieve complete eradication of H. pylori. These therapies are designed to bolster the immune response, minimize side effects, and provide gastroprotective benefits, rendering them suitable for adjunctive use alongside conventional treatments. Probiotics may serve as adjunctive therapy for H. pylori; however, their effectiveness as a monotherapy is limited. Photodynamic and phage therapies exhibit potential in targeting H. pylori infections, including those caused by drug-resistant strains, without the use of antibiotics. The development of a reliable vaccine is also critical for the eradication of H. pylori. This review identifies candidate antigens such as VacA, CagA, and HspA, along with various vaccine formulations, including vector-based and subunit vaccines. Some vaccines have demonstrated efficacy in clinical trials, while others have shown robust immune protection in preclinical studies. Nevertheless, each of the aforementioned alternative therapies requires thorough preclinical and clinical evaluation to ascertain their efficacy, side effects, cost-effectiveness, and patient compliance.
Evaluation of the Effects of Thermal Aging on the Surface Roughness of Novel Tooth-Colored Restorative Materials
Authors: Galbraith Austin , Abubakr Neamat Hassan
Published: December 2024

Background: The development of composite resins has led to novel materials aimed at improving restoration longevity. This study evaluates the surface roughness of four tooth-colored restorative materials after thermal aging. Methods: Eighty Class V preparations were restored with Admira Fusion, Beautifil II, Equia Forte HT, and Filtek. The samples underwent thermocycling, and their surface roughness was measured with a 3D non-contact profilometer at 24 h post-restoration and after simulation for 1, 3, and 5 clinical years. Results: Equia Forte HT showed the highest surface roughness and significant surface deterioration over time, while Admira Fusion maintained the lowest roughness across all intervals. Conclusions: Admira Fusion, Filtek, and Beautifil II demonstrated superior surface stability, with Equia Forte HT showing the least favorable performance.
DTPPO: Dual-Transformer Encoder-Based Proximal Policy Optimization for Multi-UAV Navigation in Unseen Complex Environments
Authors: Wei Anning , Liang Jintao , Lin Kaiyuan , Li Ziyue , Zhao Rui
Published: December 2024

Existing multi-agent deep reinforcement learning (MADRL) methods for multi-UAV navigation face challenges in generalization, particularly when applied to unseen complex environments. To address these limitations, we propose a Dual-Transformer Encoder-Based Proximal Policy Optimization (DTPPO) method. DTPPO enhances multi-UAV collaboration through a Spatial Transformer, which models inter-agent dynamics, and a Temporal Transformer, which captures temporal dependencies to improve generalization across diverse environments. This architecture allows UAVs to navigate new, unseen environments without retraining. Extensive simulations demonstrate that DTPPO outperforms current MADRL methods in terms of transferability, obstacle avoidance, and navigation efficiency across environments with varying obstacle densities. The results confirm DTPPO’s effectiveness as a robust solution for multi-UAV navigation in both known and unseen scenarios.
Research on Cooperative Arrival and Energy Consumption Optimization Strategies of UAV Formations
Authors: Liu Hao , Chen Renwen , Yan Xiaohong , Zhang Junyi , Nian Yongjia
Published: December 2024

The formation operation of unmanned aerial vehicles (UAVs) is a current research hotspot, particularly in specific mission scenarios where UAV formations are required to cooperatively arrive at designated task areas to meet the needs of coordinated operations. This paper investigates the issues of cooperative arrival and energy consumption optimization for UAV formations in such scenarios. First, focusing on rotorcraft UAVs, the flight energy consumption optimization model and cooperative arrival model are derived and constructed. Next, to address the challenges in solving these models, the multi-objective non-convex functions are transformed into single-objective continuous functions, thereby reducing computational complexity. Furthermore, an interior-point-method-based solving strategy is designed by estimating the initial values of the solving parameters. Finally, simulation experiments validate the feasibility and effectiveness of the proposed method. The experimental results show that when optimizing the energy consumption of a formation of five UAVs, the algorithm converges in just 16 iterations, demonstrating its suitability for practical applications.
Neural Network Design and Training for Longitudinal Flight Control of a Tilt-Rotor Hybrid Vertical Takeoff and Landing Unmanned Aerial Vehicle
Authors: Ducard Guillaume , Carughi Gregorio
Published: December 2024

This paper considers a hybrid vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV). By tilting its propellers, the aircraft can transition from rotary-wing (RW) multirotor mode to fixed-wing (FW) mode and vice versa. A novel architecture of a neural network-based controller (NNC) is presented. An “imitative learning” approach is employed to train the NNC to mimic the response of an expert but computationally expensive model predictive controller (MPC). The resulting NNC approximates the MPC’s solution while significantly decreasing the computational cost. The NNC is trained on the longitudinal axis. Successful simulations and real flight tests prove that the NNC is suitable for the longitudinal axis control of a complex nonlinear system such as the tilt-rotor VTOL UAV through a sequence of transitions between the RW mode to the FW mode, and vice versa, in a forward flight.
A Novel Parameter Estimation Scheme for Supercapacitors
Authors: Brydon Keelan , Laha Arpan , Kalathy Abirami , Pahlevani Majid
Published: December 2024

As reliance on sustainable energy grows, the demand for efficient, high-performance energy storage systems becomes increasingly critical, especially in uninterruptible power supplies (UPS), where reliability and fast transitions are essential. Supercapacitors, with their high power density and rapid charging capabilities, are emerging as strong alternatives to lithium-ion batteries in UPS systems. This paper presents a novel real-time estimation technique for monitoring supercapacitor parameters within a UPS, focusing on the dynamic behavior of these parameters and their evolution over the system’s lifecycle. The proposed estimator demonstrates exceptional accuracy, achieving less than 1% error within 120 ms of startup and nearly zero error thereafter. The estimator’s performance remains robust even as supercapacitor parameters change due to aging effects over the lifespan. The UPS system features a modular design, enabling scalability to accommodate higher power requirements or longer backup durations and adaptability to various supercapacitor types. Experimental results highlight the system’s robustness in both charging and backup modes, emphasizing the potential of supercapacitors as key components in future UPS systems.
A Novel Hybrid Intelligent Approach to Assess Blasting-Induced Overbreak Incorporating Geological Conditions in Different Tunnel Sections
Authors: Yuan Jiang , Wang Qing , Wang Jianglu , Fan Yongqiang , Jiao Weining , Li Ang
Published: December 2024

Overbreak induced by tunnel blasting is a harmful phenomenon. Accurate assessment of overbreak can effectively reduce investment and ensure operational safety. In this study, a hybrid intelligent model for assessing blasting-induced overbreak is proposed which can accurately predict overbreak and effectively evaluate the importance of feature parameters. To ensure accurate prediction of overbreak, hyperparameters of four machine learning algorithms are optimized using a whale optimization algorithm. Their performance is compared based on three regression metrics: R2, RMSE, and VAF. Given the limitations of traditional feature importance analysis methods, the Shapley Additive Explanation method is used in conjunction with the random forest algorithm. After accurately predicting overbreak caused by different sections of the tunnel, the impact of each input parameter on overbreak is analyzed, and recommendations for design values of certain significant parameters are provided. The research indicates that the proposed method can accurately predict overbreak caused by actual engineering blasts and provide insights into the selection of design parameter values.
Model Order Reduction and Stability Enhancement Control for AC/DC Converters Through State Feedback Method
Authors: Lu Yi , Bu Wenqiang , Chen Qian , Qiu Peng , Tian Yanjun
Published: December 2024

In the DC distribution networks, DC bus voltage is maintained by the grid-connected converter; the controllability and reliability of the grid-connected converter significantly affect the bus voltage characteristic. To address the problem of limited stability and frequent oscillations, this paper proposes a state feedback control method for the AC/DC converter. Conventional AC/DC converter adopts the voltage-current double-closed-loop control structure with the proportional-integral (PI) controllers, which is the equivalent of the typical type II control system, but the typical type II control system cannot fully settle the stability and immunity problems. In contrast, the state feedback control strategy not only achieves the control objectives of the traditional double-closed-loop control but also reduces the AC/DC converter system model to a typical Type I system, which improves stability and thus enhances the oscillation suppression capability of the bus voltage. By selecting multiple state variables and designing the converter pole configuration range, the proposed single-loop state feedback control method manages to optimize both the dynamic and steady-state performances of the grid-connected AC/DC converter. Finally, the effectiveness of the proposed single-loop state feedback control strategy is verified through MATLAB (2018b)/Simulink software simulation and experiments on a DC distribution network platform.