bluuebunny/crossref_metadata_2025 huggingface dataset:
Cancer-Therapy-Induced Cardiotoxicity: Results of the Analysis of the UK Yellow Card Adverse Drug Reaction (ADR) Reporting
Authors: Chan Stefanie Ho Yi , Layton Deborah , Webley Sherael , Salek Sam
Published: December 2024

Background: Non-small cell lung cancer (NSCLC) is a predominant cause of oncological mortality in the United Kingdom. There is a diverse spectrum of therapeutic options available, such as chemotherapies, targeted therapies and immunotherapies, which have significantly advanced patient prognoses. However, despite these advancements, there is an escalating concern regarding the potential cardiotoxic effects associated with these treatments. Objectives: This study aimed to explore the association between non-small cell lung cancer treatments and cardiotoxicity. Methods: A pharmacovigilance study was conducted utilising the UK Yellow Card System. The proportional reporting ratio (PRR) and reporting odds ratio (ROR) were calculated to detect signals. Results: Among the 56 shortlisted NSCLC drugs, the total number of adverse events reported was 128,214 with 6133 reports being cardiovascular adverse reactions. Among all the drugs analysed, alectinib demonstrated the highest ROR and PRR values, indicating the strongest signal for potential cardiovascular adverse events. Conclusions: This result was comparable to previous studies which also detected a signal of alectinib related to cardiovascular events using the WHO pharmacovigilance database, VigiBase. However, clinical studies demonstrated that alectinib largely improved progression-free survival (PFS) and overall survival in patients. Therefore, it is important to continue monitoring the real-world use of alectinib, so that a benefit–risk balance can be maintained.
Targeted Directed Evolution of an α-L-Rhamnosidase on Hesperidin Through Six-Codon Combinatorial Mutagenesis
Authors: Wu Bingbing , Hou Xueting , Han Na , Li Xinfeng , Li Bin-Chun , Ding Guo-Bin
Published: December 2024

Targeted saturation mutagenesis at the residues located at the substrate-binding pocket for generating focused libraries has emerged as the technique of choice for enzyme engineering, but choosing the optimal residue number of the randomization site and the reduced amino acid alphabet to minimize the labor-determining screening effort remains a challenge. Herein, we propose the six-codon combinatorial mutagenesis (SCCM) strategy by using the BMT degeneracy codons encoding six amino acids with different chemical properties as the building blocks for the randomization of the amnio acid motif. SCCM requires only a small library of 646 clones for 95% coverage at the three-residue motif compared to conventional NNK degeneracy codons encoding all 20 canonical amino acids and requiring the screening of nearly 100,000 clones. SCCM generates a suitable number of mutant libraries, providing a new strategy for reducing the screening workload of saturated combination mutations in enzyme engineering. Using this approach, the α-L-rhamnosidase BtRha78A from Bacteroides thetaiotaomicron had been successfully engineered for improving the hydrolytic activity on natural flavonoid diglycoside hesperidin via targeted directed evolution at the motifs positioning the entrance of the substrate-binding pocket. The results indicate that the conversion rates of the four mutants on hesperidin were increased by more than 30% compared with the wild type using whole-cell biotransformation. Moreover, the catalytic efficiency kcat/KM value of the mutant TM1-6-F5 was 1.4-fold higher than that of the wild type.
Molecular Markers in Embryo Non-Development: Analysis of Gene Expressions (Ki-67, hTERT, HIF-1α) in Spent Embryo Culture Medium
Authors: Kılıç Nergis Özlem , Kütük Duygu , Öner Çağrı , Öztürk Senem Aslan , Selam Belgin , Çolak Ertuğrul
Published: December 2024

An embryo culture medium is a specialized set of ambient conditions, technological equipment, and nutrients that embryos require to grow properly. We aimed to investigate the Ki-67, hTERT, and HIF-1α gene expression differences between developing and non-developing embryos in spent embryo culture medium. Ki-67, hTERT, and HIF-1α gene expressions were determined from the spent embryo culture medium containing developing and non-developing embryos of 20 normoresponder patients admitted to the Bahçeci Umut IVF Center. An increase in hTERT gene expression (p < 0.05) and a decrease in HIF-1α gene expression (p < 0.001) were observed in mediums of developing compared to the non-developing embryos. No difference was observed in Ki-67 gene expression (p > 0.05). While there was a correlation between Ki-67 and HIF-1α genes in the non-growing group (r < 0.01); no correlation was observed in the developing group (r > 0.05). Both normoresponder groups will be similar in terms of proliferation rate. The low HIF-1α expression that observed high telomerase activity in embryo development maintains continuity and avoids mechanisms that result in cell death. A molecular study of the embryo development in patients with similar characteristics may help to understand the pathogenesis of the disease and establish a diagnosis and specific treatment.
The Biomechanics of Fibrillin Microfibrils: Lessons from the Ciliary Zonule
Authors: Rathaur Pooja , Rodriguez Juan , Kuchtey John , Insignares Samuel , Jones Wendell B. , Kuchtey Rachel W. , Bassnett Steven
Published: December 2024

Marfan syndrome is an inherited connective tissue disorder that affects the cardiovascular, musculoskeletal, and ocular systems. It is caused by pathogenic variants in the fibrillin-1 gene (FBN1). Fibrillin is a primary component of microfibrils, which are found throughout the extracellular matrix (ECM) and provide elasticity and resilience to connective tissue. Microfibrils also play a role in signaling by sequestering growth factors and interacting with cell surface receptors. In many tissues, microfibrils are interwoven with elastin, collagens, and other elements of the ECM. However, uniquely in the ciliary zonule of the eye, microfibrils exist in cell-free bundles largely devoid of other components. This structure offers a rare opportunity to study a pure population of fibrillin microfibrils in a relatively native state. Here, we briefly review the organization of the zonule and describe recent experiments in which we measure zonular biomechanics, providing insights into microfibril dynamics that would be challenging to obtain in other contexts.
The Intricate Relationship Between Pulmonary Fibrosis and Thrombotic Pathology: A Narrative Review
Authors: Cenerini Giovanni , Chimera Davide , Pagnini Marta , Bazzan Erica , Conti Maria , Turato Graziella , Celi Alessandro , Neri Tommaso
Published: December 2024

Idiopathic pulmonary fibrosis (IPF) is associated with a significantly increased risk of thrombotic events and mortality. This review explores the complex bidirectional relationship between pulmonary fibrosis and thrombosis, discussing epidemiological evidence, pathogenetic mechanisms, and therapeutic implications, with a particular focus on the emerging role of extracellular vesicles (EVs) as crucial mediators linking fibrosis and coagulation. Coagulation factors directly promote fibrosis, while fibrosis itself activates thrombotic pathways. Retrospective studies suggest the benefits of anticoagulants in IPF, but prospective trials have faced challenges. Novel anticoagulants, profibrinolytic therapies, and agents targeting protease-activated receptors (PARs) show promise in preclinical studies and early clinical trials. EVs have emerged as key players in the pathogenesis of interstitial lung diseases (ILDs), serving as vehicles for intercellular communication and contributing to both fibrosis and coagulation. EV-based approaches, such as EV modulation, engineered EVs as drug delivery vehicles, and mesenchymal stem cell-derived EVs, represent promising therapeutic strategies. Ongoing research should focus on optimizing risk–benefit profiles, identifying predictive biomarkers, evaluating combination strategies targeting thrombotic, fibrotic, and inflammatory pathways, and advancing the understanding of EVs in ILDs to develop targeted interventions.
Integrating Experimental and Computational Insights: A Dual Approach to Ba2CoWO6 Double Perovskites
Authors: Raji Ramesh Kumar , Ramachandran Tholkappiyan , Dhilip Muthu , Aravindan Vivekanandan , Punitha Joseph Stella , Hamed Fathalla
Published: December 2024

Double perovskite materials have emerged as key players in the realm of advanced materials due to their unique structural and functional properties. This research mainly focuses on the synthesis and comprehensive characterization of Ba2CoWO6 double perovskite nanopowders utilizing a high-temperature conventional solid-state reaction technique. The successful formation of Ba2CoWO6 powders was confirmed through detailed analysis employing advanced characterization techniques. Rietveld refinement of X-ray diffraction (XRD) and Raman data established that Ba2CoWO6 crystallizes in a cubic crystal structure with the space group Fm-3m, indicative of a highly ordered perovskite lattice. The typical crystallite size, approximately 65 nm, highlights the nanocrystalline nature of the material. Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM) discovered a distinctive morphology characterized by spherical shaped particles, suggesting a complex particle formation process influenced by synthesis conditions. To probe the electronic structure, X-ray Photoelectron Spectroscopy (XPS) identified cobalt and tungsten valence states, critical for understanding dielectric properties associated with localized charge carriers. The semiconducting character of the synthesized Ba2CoWO6 nanocrystalline material was confirmed through UV-Visible analysis, which revealed an energy bandgap value of 3.3 eV, which aligns well with the theoretical predictions, indicating the accuracy and reliability of the experimental results. The photoluminescence spectrum exhibited two distinct emissions in the blue-green region. These emissions were attributed to the transitions 3P0→3H4, 3P0→3H5, and 3P0→3H6, primarily resulting from the contributions of Ba2+ ions. The dielectric characteristics of the compound were analyzed across a different range of frequencies, spanning from 1 kHz to 1 MHz. Magnetic characterization using Vibrating Sample Magnetometry (VSM) revealed antiferromagnetic behavior of Ba2CoWO6 ceramics at room temperature, attributed to super-exchange interactions between Co3+ and W5+ ions mediated by oxygen ions in the perovskite lattice. Additionally, first-principles calculations based on the Generalized Gradient Approximation (GGA+U) with a modified Becke–Johnson (mBJ) potential were employed to gain a deeper understanding of the structural and electronic properties of the materials. This approach involved systematically varying the Hubbard U parameter to optimize the description of electron correlation effects. These results deliver an extensive understanding of the structural, optical, morphological, electronic, and magnetic properties of Ba2CoWO6 ceramics, underscoring their potential for electronic and magnetic device applications.
Sulfide, Sulfoxide, and Sulfone Derivatives of Usnic Acid as Inhibitors of Human TDP1 and TDP2 Enzymes
Authors: Filimonov Aleksandr S. , Mikhailova Marina A. , Dyrkheeva Nadezhda S. , Chernyshova Irina A. , Kornienko Tatyana E. , Naumenko Konstantin A. , Anarbaev Rashid O. , Nefedov Andrey A. , Achara Chigozie , Curtis Anthony D. M. , Luzina Olga A. , Volcho Konstantin P. , Salakhutdinov Nariman F. , Lavrik Olga I. , Reynisson Jóhannes
Published: December 2024

Tyrosyl-DNA phosphodiesterases 1 and 2 (TDP1 and TDP2) are important DNA repair enzymes that remove various adducts from the 3′- and 5′-ends of DNA, respectively. The suppression of the activity of these enzymes is considered as a promising adjuvant therapy for oncological diseases in combination with topoisomerase inhibitors. The simultaneous inhibition of TDP1 and TDP2 may result in greater antitumor effects, as these enzymes can mimic each other’s functions. We have previously shown that usnic acid-based sulfides can act as dual inhibitors, with TDP1 activity in the low micromolar range and their TDP2 at 1 mM. The oxidation of their sulfide moieties to sulfoxides led to an order of magnitude decrease in their cytotoxicity potential, while their TDP1 and TDP2 activity was preserved. In this work, we synthesized new series of usnic acid-based sulfides and their oxidized analogues, i.e., sulfoxides and sulfones, to systematically study these irregularities. The new compounds inhibit TDP1 with IC50 values (the concentration of inhibitor required to reduce enzyme activity by half) in the 0.33–25 μM range. Most sulfides and some sulfoxides and sulfones inhibit TDP2 with an IC50 = 138−421 μM. In addition, the most active compounds synergized (×4) with topotecan on the HeLa cell line as well as causing dose-dependent DNA damage, as confirmed by Comet assay. Sulfides with the 6-methylbenzoimidazol-2-yl substituent (8f, IC50 = 0.33/138 μM, TDP1/2) and sulfones containing a pyridine-2-yl fragment (12k, IC50 = 2/228 μM, TDP1/2) are the most potent derivatives and, therefore, are promising for further development.
On the Proof of Ownership of Digital Wallets
Authors: Wang Chen , Liu Zi-Yuan , Mambo Masahiro
Published: December 2024

With the widespread adoption and increasing application of blockchain technology, cryptocurrency wallets used in Bitcoin and Ethereum play a crucial role in facilitating decentralized asset management and secure transactions. However, wallet security relies heavily on private keys, with insufficient attention to the risks of theft and exposure. To address this issue, Chaum et al. (ACNS’21) proposed a “proof of ownership” method using a “backup key” to prove ownership of private keys even when exposed. However, their interactive proof approach is inefficient in large-scale systems and vulnerable to side-channel attacks due to the long key generation time. Other related schemes also suffer from low efficiency and complex key management, increasing the difficulty of securely storing backup keys. In this paper, we present an efficient, non-interactive proof generation approach for ownership of secret keys using a single backup key. Our approach leverages non-interactive zero-knowledge proofs and symmetric encryption, allowing users to generate multiple proofs with one fixed backup key, simplifying key management. Additionally, our scheme resists quantum attacks and provides a fallback signature. Our new scheme can be proved to capture unforgeability under the computational indistinguishability from the Uniformly Random Distribution property of a proper hash function and soundness in the quantum random oracle model. Experimental results indicate that our approach achieves a short key generation time and enables an efficient proof generation scheme in large-scale decentralized systems. Compared with state-of-the-art schemes, our approach is applicable to a broader range of scenarios due to its non-interactive nature, short key generation time, high efficiency, and simplified key management system.
Artificial Intelligence for Tooth Detection in Cleft Lip and Palate Patients
Authors: Arslan Can , Yucel Nesli Ozum , Kahya Kaan , Sunal Akturk Ezgi , Germec Cakan Derya
Published: December 2024

Introduction: Cleft lip and palate patients often present with unique anatomical challenges, making dental anomaly detection and numbering particularly complex. The accurate identification of teeth in these patients is crucial for effective treatment planning and long-term management. Artificial intelligence (AI) has emerged as a promising tool for enhancing diagnostic precision, yet its application in this specific patient population remains underexplored. Objectives: This study aimed to evaluate the performance of an AI-based software in detecting and numbering teeth in cleft lip and palate patients. The research focused on assessing the system’s sensitivity, precision, and specificity, while identifying potential limitations in specific anatomical regions and demographic groups. Methods: A total of 100 panoramic radiographs (52 males, 48 females) from patients aged 6 to 15 years were analyzed using AI software. Sensitivity, precision, and specificity were calculated, with ground truth annotations provided by four experienced orthodontists. The AI system’s performance was compared across age and gender groups, with particular attention to areas prone to misidentification. Results: The AI system demonstrated high overall sensitivity (0.98 ± 0.03) and precision (0.96 ± 0.04). No statistically significant differences were found between age groups (p > 0.05), but challenges were observed in the maxillary left region, which exhibited higher false positive and false negative rates. These findings were consistent with the prevalence of unilateral left clefts in the study population. Conclusions: The AI system was effective in detecting and numbering teeth in cleft lip and palate patients, but further refinement is required for improved accuracy in the cleft region, particularly on the left side. Addressing these limitations could enhance the clinical utility of AI in managing complex craniofacial cases.
The Impact of Vaccination on COVID-19 Outcomes in Vietnam
Authors: Nguyen Ngoc-Lan Thi , Nguyen Hien Thi Thu , Le-Quy Vang , To Thu-Ba , Tran Huy Thinh , Nguyen Tuan Duc , Hoang Yen , Nguyen Anh-Thu , Dam Lan Thi Phuong , Nguyen Nhat-Linh , Dinh-Xuan Anh Tuan , Ta Thanh-Van
Published: December 2024

Objectives: This study aimed to assess the effectiveness of the COVID-19 vaccine on the outcomes of patients in three hospitals in Vietnam. Methods: An observational study involved 3102 confirmed COVID-19 patients from Vietnam. Participants were classified into unvaccinated, partially vaccinated (one dose) (PV), fully vaccinated (two doses) (FV), and boosted (three doses) groups. We used a regression model to assess the relationship between vaccine status and disease outcome, including mortality, persistent symptoms after treatment, and hospital duration. Results: The proportions of unvaccinated, PV, FV, and boosted groups were 43.39%, 4.63%, 43.93%, and 8.05%, respectively, and 48% of the participants had at least one comorbidity. The proportion of severe clinical disease was significantly higher in the unvaccinated compared with the vaccinated. Biomarkers of cellular injury and organ failure, e.g., aspartate aminotransferase (AST), ferritin, troponin T, proBNP, D-dimer, and urea plasma concentration were significantly higher in unvaccinated and PV patients compared with FV and boosted patients. Age was the most crucial predictor of critical illness, followed by vaccine status, hypertension, diabetes, heart disease, and chronic kidney disease. The unvaccinated group had the highest proportion of deaths (5.2% vs. 1.4% and 0.3% in FV and boosted groups, respectively). Conclusions: Vaccination reduced mortality and both hospitalization length and disease severity in COVID-19 survivors, especially the older and patients with chronic comorbidities.
Lumen-Apposing Metal Stents in the Management of Complex Pelvic Abscesses
Authors: Chow Kenneth W. , Cumpian Nicholas A. , Makar Ranjit , Zargar Pejman , Oza Fouzia , Suliman Idrees , Eysselein Viktor , Reicher Sofiya
Published: December 2024

Background: Lumen-apposing metal stents (LAMS) are utilized in a wide range of therapeutic gastrointestinal applications. We present our experience with LAMS-assisted drainage of complex pelvic abscesses at a large safety-net hospital. Methods: EUS-guided LAMS placements for pelvic abscesses from July 2020 to June 2024 were analyzed. Data were collected on patient demographics, procedure indications, fluid collection size, stent characteristics, stent dwell time, and complications. All cases underwent multidisciplinary review with Surgery and Interventional Radiology (IR) prior to LAMS-assisted drainage; all were deemed not amenable to drainage by IR. Results: Eleven patients underwent EUS-guided drainage of complex pelvic abscesses with cautery-enhanced LAMS. Diverticulitis was the most common cause of abscesses (n = 6; 55%). The average time from presentation to drainage was 7 days (1–18). The average abscess size was 7.2 cm (3.9–12.0 cm). The most common LAMS size was 15 mm × 10 mm; each was placed through the left colon and rectum with both technical and clinical success. All abscesses completely resolved with a mean stent dwell time of 28 days (17–42 days). After stent removal, the fistula was not routinely closed. No complications such as stent migration, bleeding, or perforation occurred. There were no recurrences and no patients required additional surgical or IR procedures with a mean follow-up of 25 weeks (SD 35.6). Conclusions: Adequate drainage is the cornerstone of pelvic abscess management, but IR or surgical access can be challenging, with inadequate drainage and prolonged hospitalization leading to significant morbidity. In our experience, EUS-guided, LAMS-assisted drainage provides a safe and effective alternative for managing pelvic abscesses.
Application of CAD-CAM 3D Technology in Designing a Molar Distalization Device with Skeletal Anchorage: A Case Report
Authors: Mezio Martina , Putrino Alessandra , Barbato Ersilia , Pandolfi Stefano , Cassetta Michele
Published: December 2024

Objectives: Mandibular molar distalization is a complex orthodontic movement due to anatomic and biomechanical limitations. The opportunity to use a custom-made appliance with skeletal anchorage should be an advantageous alternative to traditional solutions: multiple extractions, interproximal reductions, vestibular inclination of incisal group. Methods: A 14-year-old female patient with Class II malocclusion and ectopic upper and lower canines was treated in the lower arch with a custom-made appliance anchored on a mini-screw in the right buccal-shelf where the ectopy and crowding was severe. The miniscrew was connected to a rigid arm with a rail equipped with a coil that activated promoted the distalization of first and second molars bonded with metallic bands. Results: After 8 months of treatment with activations repeated every 4 weeks, an effective distalization has been reached. Conclusions: Mandibular molars’ distalization is a challenging orthodontic result to achieve. When the need to obtain space cannot be beneficially obtained with conventional approaches, and distalization of the lower molars could be desirable, a custom distalization device with skeletal anchorage and biomechanics based on a pressed coil sliding on a rigid arm is an efficient solution.
Partnership Development of Smallholder Coffee Cultivation: A Model for Social Capital in the Global Value Chain
Authors: Haryono Adi , Juniarti Ina , Matajat Karjo , Suroso Arif Imam , Soesilo Moelyono
Published: December 2024

The productivity of smallholder coffee cultivation is declining due to ageing trees, making the rejuvenation of coffee trees with superior seeds essential. This rejuvenation process requires the support and participation of various stakeholders, including the government, banks, investors, universities, community leaders, experts, extension workers, and other parties. The nature of an incomplete contract in building partnership with farmers requires confidence building to avoid higher costs in enforcing a new behavior. However, this study shows that the accumulation of social capital also leads to higher expenses in maintaining these relationships. This study aimed to develop a social capital model to enhance partnerships between coffee farmers and relevant stakeholders. The analysis used a system dynamics model for coffee production and farmer income. The data collection involved the gathering of data and information from 17 actors in the coffee industry in Lampung, particularly in Kopista community. The study reveals that the social capital model must be constructed from four components: (1) trust, (2) ongoing cooperative activities, (3) social capital connections, and (4) memories of successful cooperative actions. Active involvement and instruction from specialists on the concept of social capital and partnership models can enhance cooperation by maintaining social connections. The policy implication of this study is that the development of a social capital model and partnership must be constructed by mentoring for economic benefits and must be continuously supported.
Evaluating the Effectiveness of an Extracurricular Teacher Education Training Program for DigCompEdu Competences
Authors: Johnson Frederick , Schmit Joline , Schneider Christoph , Rossa Henning , Müller Lothar
Published: December 2024

In the ongoing era of digital transformation, it is imperative for teachers to equip learners with essential digital competences to navigate the intricacies of the digital landscape successfully. As future in-service teachers function as role models and educators for the proper use of digital technology, pre-service teachers must develop adequate digital proficiency. This holds particularly true in Germany, where the prevailing competence levels of pre-service teachers are reportedly suboptimal. To this end, an extracurricular training program for pre-service teachers, based on the DigCompEdu framework, was implemented from 2021 to 2024, coinciding with COVID-19 pandemic-related limitations. A total of 242 pre-service teachers registered for the program, and 40 completed it. Employing a pre–post design, we assessed (1) attitudes towards digital technology and digital learning, (2) competence beliefs, and (3) test-based competences. Pre–post comparisons show an improvement only in participants’ confidence in deploying digital technologies for subject-specific purposes. Unexpectedly, no other statistically significant differences were observed. These findings point at shortcomings in the program, which are discussed to highlight potential areas for refinement and improvement in future programs and curricular implementation.
Small-Sample Target Detection Across Domains Based on Supervision and Distillation
Authors: Sun Fusheng , Jia Jianli , Han Xie , Kuang Liqun , Han Huiyan
Published: December 2024

To address the issues of significant object discrepancies, low similarity, and image noise interference between source and target domains in object detection, we propose a supervised learning approach combined with knowledge distillation. Initially, student and teacher models are jointly trained through supervised and distillation-based approaches, iteratively refining the inter-model weights to mitigate the issue of model overfitting. Secondly, a combined convolutional module is integrated into the feature extraction network of the student model, to minimize redundant computational effort; an explicit visual center module is embedded within the feature pyramid network, to bolster feature representation; and a spatial grouping enhancement module is incorporated into the region proposal network, to mitigate the adverse effects of noise on the outcomes. Ultimately, the model undergoes a comprehensive optimization process that leverages the loss functions originating from both the supervised and knowledge distillation phases. The experimental results demonstrate that this strategy significantly boosts classification and identification accuracy on cross-domain datasets; when compared to the TFA (Task-agnostic Fine-tuning and Adapter), CD-FSOD (Cross-Domain Few-Shot Object Detection) and DeFRCN (Decoupled Faster R-CNN for Few-Shot Object Detection), with sample orders of magnitude 1 and 5, increased the detection accuracy by 1.67% and 1.87%, respectively.
A Broadband and Wide-Scanning Dual-Polarized Dipole Array with Low Profile
Authors: Peng Yunfan , Liu Chang
Published: December 2024

This study presents a novel methodology for designing a planar broadband wide-scanning dual-polarized array using tightly-coupled dipoles and wide-angle impedance matching. By etching the S-shaped gaps between the dipoles and incorporating shorting vias with defected ground structures, we demonstrated that all radiation elements can be arranged on a single-layer substrate. Additionally, we introduced a thin printed circuit board (PCB) layer with two-dimensional periodic structures for impedance matching at wide scan angles. Leveraging high permittivity and constrained electromagnetic waves, we realized zero-scan blindness within this band. The aperture consisted of only two PCB layers, with a total profile of approximately 0.091λlow, where λlow represented the free-space wavelength at 6 GHz. A 3 × 4 dual-polarized array was fabricated and measured to validate the proposed approach. The measured active voltage standing wave ratio for one embedded array element surpassed 2.2 over 6–18 GHz. By enabling the orthogonal dipoles at the edge of the array to be mutually coupled using an additional metal patch, the active S11 for the edge cells exceeded −8.8 dB over 6.9–18 GHz. The measured patterns were in good agreement with simulations over 6–18 GHz, with the array exhibiting good radiation performance over ±60° in the E- and H-planes.
Data-Driven Maturity Level Evaluation for Cardiomyocytes Derived from Human Pluripotent Stem Cells (Invited Paper)
Authors: Hong Yan , Huang Xueqing , Li Fang , Huang Siqi , Weng Qibiao , Fraidenraich Diego , Voiculescu Ioana
Published: December 2024

Cardiovascular disease is a leading cause of death worldwide. The differentiation of human pluripotent stem cells (hPSCs) into functional cardiomyocytes offers significant potential for disease modeling and cell-based cardiac therapies. However, hPSC-derived cardiomyocytes (hPSC-CMs) remain largely immature, limiting their experimental and clinical applications. A critical challenge in current in vitro culture systems is the absence of standardized metrics to quantify maturity. This study presents a data-driven pipeline to quantify hPSC-CM maturity using gene expression data across various stages of cardiac development. We determined that culture time serves as a feasible proxy for maturity. To improve prediction accuracy, machine learning algorithms were employed to identify heart-related genes whose expression strongly correlates with culture time. Our results reduced the average discrepancy between predicted and observed culture time to 4.461 days and CASQ2 (Calsequestrin 2), a gene involved in calcium ion storage and transport, was identified as the most critical cardiac gene associated with culture duration. This novel framework for maturity assessment moves beyond traditional qualitative methods, providing deeper insights into hPSC-CM maturation dynamics. It establishes a foundation for developing advanced lab-on-chip devices capable of real-time maturity monitoring and adaptive stimulus selection, paving the way for improved maturation strategies and broader experimental/clinical applications.
Redefining Contextual and Boundary Synergy: A Boundary-Guided Fusion Network for Medical Image Segmentation
Authors: Chen Yu , Wu Yun , Wu Jiahua , Zhang Xinxin , Wang Dahan , Zhu Shunzhi
Published: December 2024

Medical image segmentation plays a crucial role in medical image processing, focusing on the automated extraction of regions of interest (such as organs, lesions, etc.) from medical images. This process supports various clinical applications, including diagnosis, surgical planning, and treatment. In this paper, we introduce a Boundary-guided Context Fusion U-Net (BCF-UNet), a novel approach designed to tackle a critical shortcoming in current methods: the inability to effectively integrate boundary information with semantic context. The BCF-UNet introduces a Adaptive Multi-Frequency Encoder (AMFE), which uses multi-frequency analysis inspired by the Wavelet Transform (WT) to capture both local and global features efficiently. The Adaptive Multi-Frequency Encoder (AMFE) decomposes images into different frequency components and adapts more effectively to boundary texture information through a learnable activation function. Additionally, we introduce a new multi-scale feature fusion module, the Atten-kernel Adaptive Fusion Module (AKAFM), designed to integrate deep semantic information with shallow texture details, significantly bridging the gap between features at different scales. Furthermore, each layer of the encoder sub-network integrates a Boundary-aware Pyramid Module (BAPM), which utilizes a simple and effective method and combines it with a priori knowledge to extract multi-scale edge features to improve the accuracy of boundary segmentation. In BCF-UNet, semantic context is used to guide edge information extraction, enabling the model to more effectively comprehend and identify relationships among various organizational structures. Comprehensive experimental evaluations on two datasets demonstrate that the proposed BCF-UNet achieves superior performance compared to existing state-of-the-art methods.
PMDRSpell: Dynamic Residual Chinese Spelling Check Method Guided by Phonological and Morphological Knowledge
Authors: Chang Guanguang , Zhang Yangsen , Yu Youren , Song Jiayuan
Published: December 2024

Since the errors in Chinese Spell Correction (CSC) involve phonetically or morphologically confusing Chinese characters, mainstream models have made numerous attempts to fuse phonological and morphological knowledge. We observe that in erroneous sentences where the vast majority of Chinese characters are correctly written, mainstream models may unintentionally increase the difficulty of predicting these correct characters when integrating multi-modal knowledge across all characters. Additionally, these models often overlook the potential relationship between the phonological and morphological modalities of a Chinese character when utilizing multi-modal information. In this paper, we propose an end-to-end model called PMDRSpell, which models erroneous Chinese characters in sentences using their multi-modal knowledge and reduces the use of multi-modal information for correct Chinese characters. Additionally, it uncovers the relationship between phonological and morphological features based on the characteristics of phonograms, enhancing the similarity between similar Chinese characters. Specifically, coarse-grained and hierarchical detection is first employed to localize and mask error locations within sentences, using the original embedding information as residual features. Next, correlation information in the phonological and morphological modalities of the erroneous characters is extracted to construct new representational features, which are then used to update the erroneous Chinese character information within the residual features. Finally, the masked sentences are predicted using the MLM model and classified to generate correct sentences by combining the residual features with the updated multi-modal information. Our model effectively reduces the interference from correct Chinese characters during the inspection process and leverages multi-modal information to accurately correct incorrect Chinese characters. In our comparison experiments with recent state-of-the-art models, PMDRSpell outperforms the optimal baseline in terms of error-corrected F1 scores for Sighan14 and Sighan15 by 1.2 and 1.0 percentage points, respectively.
A Comprehensive Review of AI Advancement Using testFAILS and testFAILS-2 for the Pursuit of AGI
Authors: Kumar Yulia , Lin Mengtian , Paredes Christopher , Li Dan , Yang Guohao , Kruger Dov , Li J. Jenny , Morreale Patricia
Published: December 2024

In a previous paper we defined testFAILS, a set of benchmarks for measuring the efficacy of Large Language Models in various domains. This paper defines a second-generation framework, testFAILS-2 to measure how current AI engines are progressing towards Artificial General Intelligence (AGI). The testFAILS-2 framework offers enhanced evaluation metrics that address the latest developments in Artificial Intelligence Linguistic Systems (AILS). A key feature of this re-view is the “Chat with Alan” project, a Retrieval-Augmented Generation (RAG)-based AI bot inspired by Alan Turing, designed to distinguish between human and AI generated interactions, thereby emulating Turing’s original vision. We assess a variety of models, including ChatGPT-4o-mini and other Small Language Models (SLMs), as well as prominent Large Language Models (LLMs), utilizing expanded criteria that encompass result relevance, accessibility, cost, multimodality, agent creation capabilities, emotional AI attributes, AI search capacity, and LLM-robot integration. The analysis reveals that testFAILS-2 significantly enhances the evaluation of model robustness and user productivity, while also identifying critical areas for improvement in multimodal processing and emotional reasoning. By integrating rigorous evaluation standards and novel testing methodologies, testFAILS-2 advances the assessment of AILS, providing essential insights that contribute to the ongoing development of more effective and resilient AI systems towards achieving AGI.
Thin-Film Technologies for Sustainable Building-Integrated Photovoltaics
Authors: Smith Andrew R. , Ghamari Mehrdad , Velusamy Sasireka , Sundaram Senthilarasu
Published: December 2024

This study investigates the incorporation of thin-film photovoltaic (TFPV) technologies in building-integrated photovoltaics (BIPV) and their contribution to sustainable architecture. The research focuses on three key TFPV materials: amorphous silicon (a-Si), cadmium telluride (CdTe), and copper indium gallium selenide (CIGS), examining their composition, efficiency, and BIPV applications. Recent advancements have yielded impressive results, with CdTe and CIGS achieving laboratory efficiencies of 22.10% and 23.35%, respectively. The study also explores the implementation of building energy management systems (BEMS) for optimizing energy use in BIPV-equipped buildings. Financial analysis indicates that despite 10.00–30.00% higher initial costs compared to conventional materials, BIPV systems can generate 50–150 kWh/m2 annually, with simple payback periods of 5–15 years. The research emphasizes the role of government incentives and innovative financing in promoting BIPV adoption. As BIPV technology progresses, it offers a promising solution for transforming buildings from energy consumers to producers, significantly contributing to sustainable urban development and climate change mitigation.
Review of Thermal Calculation Methods for Boilers—Perspectives on Thermal Optimization for Improving Ecological Parameters
Authors: Ciupek Bartosz , Frąckowiak Andrzej
Published: December 2024

This article presents an overview of thermal calculation methods used in boilers powered by fossil fuels (solid, liquid or gas). The analysis was carried out mainly in terms of combustion chamber calculation methods. Changing standards and legal regulations regarding the use of fossil fuels in Europe and the world make it necessary to adapt calculation methods and boiler design to current requirements, and many of them are related to outdated boiler models or for fuels that are no longer so heavily used in industrial solutions. Current research and development trends implemented in the EU and in the world related to the issues of the European Green Deal, the Fit for 55 directive and other ecological trends in the energy sector make it necessary to verify and remodel the calculation methods used so far in terms of the thermal efficiency of the device, fuel consumption or the use of fuels not previously used in their wide range in a wider application. Hence, the knowledge and updating of the state of knowledge in the field of the thermal calculation of boilers in terms of their environmental performance is necessary and strongly sought after by researchers. It is undoubted that in the next few years, boilers will continue to be the main source of thermal energy, especially in the power industry or industry. A reasonable energy transition should be based on the direction of the thermal optimization of already functioning structures and adaptation of their operating parameters to the planned new ecological fuels in the sense of the intensification of energy converted from primary form to thermal energy, and in the last step, it should reorganize the energy and industrial sectors, leaving only these groups of devices treated as a stable and necessary source of energy. Therefore, it should be recognized that activities aimed at improving the thermal parameters of boilers should directly improve the thermal efficiency of the device, and this will translate into fuel savings and reduce their negative impact on the environment.
Global, Regional, and National Burden of Tracheal, Bronchus, and Lung Cancer in 2022: Evidence from the GLOBOCAN Study
Authors: Sharma Rajesh , Khubchandani Jagdish
Published: December 2024

Background: Tracheal Bronchus and Lung cancers (TBL) represent one of the leading causes of cancer deaths worldwide. This study aimed to examine the disease and economic burden of TBL cancers in 185 countries worldwide in 2022. Methods: The estimates of TBL cancer incidence and mortality (counts and age-standardized rates) were obtained from the GLOBOCAN 2022 data produced by the International Agency for Research on Cancer. Mortality-to-incidence ratios (MIR) were utilized as a proxy of 5-year survival rates. Multivariate regression was utilized to examine the association between TBL cancer burden and tobacco use prevalence. Results: Globally, there were 2.48 million incident cases and 1.82 million deaths due to TBL cancers in 2022. Males accounted for 63.4% of incident cases (1.57 million) and 67.85% of TBL deaths (1.23 million) in 2022. For both sexes combined, the age-standardized rate was 23.1 per 100,000, and the age-standardized mortality rate was 16.8/100,000. The Mortality-to-incidence ratio (MIR) at the global level stood at 0.71. Eastern Asia had the largest burden of TBL cancers among the 21 UN-defined regions, with around 51% of incident cases (1.24 million) and 46.9% of global deaths (851,876), followed by Northern America (incidence: 257,284; deaths: 150,675) and Eastern Europe (incidence: 158,141; deaths: 126,840). At the country level, human development index (HDI) and adult tobacco use prevalence could explain 67% and 64% variation in ASIR and ASMR, respectively. HDI was statistically significantly related to MIR, explaining a 48% variation in MIR. Conclusions: With 1.9 million deaths in 2022, TBL cancer is a significant global cause of mortality. Despite the knowledge and awareness of smoking and lung cancer, adult smoking rates remain high in many countries, including the United States and China. Renewed and sustained global efforts are needed to reduce smoking prevalence and PM2.5 levels, particularly in China and low- and middle-income countries.
Machine Learning and Deep Learning for Wildfire Spread Prediction: A Review
Authors: Andrianarivony Henintsoa S. , Akhloufi Moulay A.
Published: December 2024

The increasing frequency and intensity of wildfires highlight the need to develop more efficient tools for firefighting and management, particularly in the field of wildfire spread prediction. Classical wildfire spread models have relied on mathematical and empirical approaches, which have trouble capturing the complexity of fire dynamics and suffer from poor flexibility and static assumptions. The emergence of machine learning (ML) and, more specifically, deep learning (DL) has introduced new techniques that significantly enhance prediction accuracy. ML models, such as support vector machines and ensemble models, use tabular data points to identify patterns and predict fire behavior. However, these models often struggle with the dynamic nature of wildfires. In contrast, DL approaches, such as convolutional neural networks (CNNs) and convolutional recurrent networks (CRNs), excel at handling the spatiotemporal complexities of wildfire data. CNNs are particularly effective at analyzing spatial data from satellite imagery, while CRNs are suited for both spatial and sequential data, making them highly performant in predicting fire behavior. This paper presents a systematic review of recent ML and DL techniques developed for wildfire spread prediction, detailing the commonly used datasets, the improvements achieved, and the limitations of current methods. It also outlines future research directions to address these challenges, emphasizing the potential for DL to play an important role in wildfire management and mitigation strategies.
Optimization of the Frying Process for Maximizing Crispiness of Scallop (Patinopecten yessoensis) Adductor Muscle Snacks Using Vacuum Low-Temperature Frying
Authors: Park Sun-Young , Kang Sang-In , Kim Jin , An Young-Hyun , Lee Ga-Bin , Park Si-Hyeong , Lee Jung-Suck
Published: December 2024

Scallops, an economically important seafood, are popular as fried snacks. Vacuum low-temperature frying creates crispy, healthier foods that meet consumer demand for nutritious snacks with excellent texture. However, research on vacuum frying for shellfish products remains limited. This study aimed to optimize the process for developing a healthy, crispy snack that retains the original shape of the Yesso scallop (Patinopecten yessoensis) adductor muscle using vacuum low-temperature frying technology. The effects of various frying methods on the scallops were analyzed. The vacuum low-temperature frying process was optimized based on evaluations of physical, chemical, and sensory properties. Frying conditions were optimized using response surface methodology, with temperature (X1: 90.1–109.9 °C) and time (X2: 186–774 s) as variables. Based on moisture (5.6 ± 0.1 g/100 g), hardness (1470 ± 5.0 g/cm2), and sensory chewiness (7.6 ± 0.2 points) analyses, 99.9 °C and 480 s were identified as the optimal conditions. Validation was conducted through sensory evaluation by 30 trained panelists. Scallops produced under these optimal frying conditions exhibited low water activity (aw) (0.46), desirable texture (1428 g/cm2), palatability (7.9 points), and high protein content (45.6 g/100 g). The predicted and experimental values for frying temperature and time showed strong agreement, validating the reliability of the optimization model.
Effects of Lactic Acid Bacteria Fermentation and In Vitro Simulated Digestion on the Bioactivities of Purple Sweet Potato Juice
Authors: Tong Yingjia , Wang Zeqing , Tong Qunyi , Liu Yutong
Published: December 2024

The effects of lactic acid bacteria fermentation and in vitro simulated digestion on phenolic bioavailability, phenolic bioavailability, and antioxidant activity of purple sweet potato juice (PSPJ) were investigated. The PSPJ was fermented by Lactobacillus rhamnosus and Streptococcus thermophilus. The viable bacterial count, phenolic components, antioxidant activity, phenolic bioaccessibility, and phenolic bioavailability of PSPJ were analyzed during the simulated digestion process in vitro. The data displayed that lactic acid bacteria fermentation increased total α-glucosidase inhibition, total flavonoid content, and ratephenolic content. The antioxidant activities were improved after in vitro simulated digestion due to the biotransformation of phenolic substances by lactic acid bacteria fermentation. The bioaccessibility and bioavailability of phenols in PSPJ were improved with fermentation of lactic acid bacteria. Furthermore, the viable bacteria count of the two strains was significantly improved (>7 log CFU/mL) after simulated digestion in vitro.