bluuebunny/crossref_metadata_2025 huggingface dataset:
The Na/K-ATPase α1/Src Signaling Axis Regulates Mitochondrial Metabolic Function and Redox Signaling in Human iPSC-Derived Cardiomyocytes
Authors: Cai Liquan , Pessoa Marco T. , Gao Yingnyu , Strause Sidney , Banerjee Moumita , Tian Jiang , Xie Zijian , Pierre Sandrine V.
Published: December 2023

Na/K-ATPase (NKA)-mediated regulation of Src kinase, which involves defined amino acid sequences of the NKA α1 polypeptide, has emerged as a novel regulatory mechanism of mitochondrial function in metazoans. Mitochondrial metabolism ensures adequate myocardial performance and adaptation to physiological demand. It is also a critical cellular determinant of cardiac repair and remodeling. To assess the impact of the proposed NKA/Src regulatory axis on cardiac mitochondrial metabolic function, we used a gene targeting approach in human cardiac myocytes. Human induced pluripotent stem cells (hiPSC) expressing an Src-signaling null mutant (A420P) form of the NKA α1 polypeptide were generated using CRISPR/Cas9-mediated genome editing. Total cellular Na/K-ATPase activity remained unchanged in A420P compared to the wild type (WT) hiPSC, but baseline phosphorylation levels of Src and ERK1/2 were drastically reduced. Both WT and A420P mutant hiPSC readily differentiated into cardiac myocytes (iCM), as evidenced by marker gene expression, spontaneous cell contraction, and subcellular striations. Total NKA α1-3 protein expression was comparable in WT and A420P iCM. However, live cell metabolism assessed functionally by Seahorse extracellular flux analysis revealed significant reductions in both basal and maximal rates of mitochondrial respiration, spare respiratory capacity, ATP production, and coupling efficiency. A significant reduction in ROS production was detected by fluorescence imaging in live cells, and confirmed by decreased cellular protein carbonylation levels in A420P iCM. Taken together, these data provide genetic evidence for a role of NKA α1/Src in the tonic stimulation of basal mitochondrial metabolism and ROS production in human cardiac myocytes. This signaling axis in cardiac myocytes may provide a new approach to counteract mitochondrial dysfunction in cardiometabolic diseases.
Detection and Characterization of Electrogenic Bacteria from Soils
Authors: Rumora Ana , Hopkins Liliana , Yim Kayla , Baykus Melissa F. , Martinez Luisa , Jimenez Luis
Published: December 2023

Soil microbial fuel cells (SMFCs) are bioelectrical devices powered by the oxidation of organic and inorganic compounds due to microbial activity. Seven soils were randomly selected from Bergen Community College or areas nearby, located in the state of New Jersey, USA, were used to screen for the presence of electrogenic bacteria. SMFCs were incubated at 35–37 °C. Electricity generation and electrogenic bacteria were determined using an application developed for cellular phones. Of the seven samples, five generated electricity and enriched electrogenic bacteria. Average electrical output for the seven SMFCs was 155 microwatts with the start-up time ranging from 1 to 11 days. The highest output and electrogenic bacterial numbers were found with SMFC-B1 with 143 microwatts and 2.99 × 109 electrogenic bacteria after 15 days. Optimal electrical output and electrogenic bacterial numbers ranged from 1 to 21 days. Microbial DNA was extracted from the top and bottom of the anode of SMFC-B1 using the ZR Soil Microbe DNA MiniPrep Protocol followed by PCR amplification of 16S rRNA V3-V4 region. Next-generation sequencing of 16S rRNA genes generated an average of 58 k sequences. BLAST analysis of the anode bacterial community in SMFC-B1 demonstrated that the predominant bacterial phylum was Bacillota of the class Clostridia (50%). However, bacteria belonging to the phylum Pseudomonadota (15%) such as Magnetospirillum sp. and Methylocaldum gracile were also part of the predominant electrogenic bacterial community in the anode. Unidentified uncultured bacteria accounted for 35% of the predominant bacterial community. Bioelectrical devices such as MFCs provide sustainable and clean alternatives to future applications for electricity generation, waste treatment, and biosensors.
Heart Rate Variability in Concussed College Athletes: Follow-Up Study and Biological Sex Differences
Authors: Doucet Mariane , Brisebois Hélène , McKerral Michelle
Published: December 2023

Finding reliable biomarkers to assess concussions could play a pivotal role in diagnosis, monitoring, and predicting associated risks. The present study aimed to explore the use of heart rate variability (HRV) in the follow-up of concussions among college athletes and to investigate the relationships between biological sex, symptomatology, and HRV values at baseline and after a concussion. Correlations between measures were also analyzed. A total of 169 (55 females) athletes aged 16 to 22 years old completed baseline testing, and 30 (8 females) concussion cases were followed. Baseline assessment (T1) included psychosocial and psychological questionnaires, symptoms report, and four minutes of HRV recording. In the event of a concussion, athletes underwent re-testing within 72 h (T2) and before returning to play (T3). Baseline findings revealed that girls had higher %VLF while sitting than boys, and a small negligible correlation was identified between %HF and total symptoms score as well as %HF and affective sx. Post-concussion analyses demonstrated a significant effect of time × position × biological sex for %HF, where girls exhibited higher %HF at T3. These findings suggest disruptions in HRV following a concussion and underscore biological sex as an important factor in the analysis of HRV variation in concussion recovery trajectory.
An Update on the Efficacy of Single and Serial Intravenous Ketamine Infusions and Esketamine for Bipolar Depression: A Systematic Review and Meta-Analysis
Authors: Nunez Nicolas A. , Joseph Boney , Kumar Rakesh , Douka Ioanna , Miola Alessandro , Prokop Larry J. , Mickey Brian J. , Singh Balwinder
Published: December 2023

Ketamine has shown rapid antidepressant and anti-suicidal effects in treatment-resistant depression (TRD) with single and serial intravenous (IV) infusions, but the effectiveness for depressive episodes of bipolar disorder is less clear. We conducted an updated systematic review and meta-analysis to appraise the current evidence on the efficacy and tolerability of ketamine/esketamine in bipolar depression. A search was conducted to identify randomized controlled trials (RCTs) and non-randomized studies examining single or multiple infusions of ketamine or esketamine treatments. A total of 2657 articles were screened; 11 studies were included in the systematic review of which 7 studies were included in the meta-analysis (five non-randomized, N = 159; two RCTs, N = 33) with a mean age of 42.58 ± 13.1 years and 54.5% females. Pooled analysis from two RCTs showed a significant improvement in depression symptoms measured with MADRS after receiving a single infusion of ketamine (1-day WMD = −11.07; and 2 days WMD = −12.03). Non-randomized studies showed significant response (53%, p < 0.001) and remission rates (38%, p < 0.001) at the study endpoint. The response (54% vs. 55%) and remission (30% vs. 40%) rates for single versus serial ketamine infusion studies were similar. The affective switch rate in the included studies approximated 2.4%. Esketamine data for bipolar depression are limited, based on non-randomized, small sample-sized studies. Further studies with larger sample sizes are required to strengthen the evidence.
Parametric Automated Design and Virtual Simulation of Building Machine Using BIM
Authors: Zou Yiquan , Sun Zhaocheng , Pan Han , Tu Wenlei , Dong Daode
Published: December 2023

With the continuous development of the construction technology of the main structure of high-rise buildings, traditional construction techniques have been widely used in high-rise building projects. However, these technologies have problems such as low safety, low intelligence, and poor integrity. In order to solve these challenges, the Third Engineering Bureau of China Construction independently developed a new type of construction technology—a high-rise building integrated work construction platform (referred to as a building machine). Building machines has been gradually applied to high-rise building projects due to its intelligence, integration, safety, and other advantages. However, with the increase in the number of high-rise building projects, the traditional way of designing building machine layout programs is inefficient and the design program is complicated to change. To solve these problems, this paper proposes a building machine parametric design and layout and virtual simulation method. This method uses Blender open-source software to model the building machine parametrically and quickly using its visual programming tool Geometry Nodes (GN) and simulates the building machine in the virtual scene through the Unity3D platform. The results show that, compared with the traditional design mode, the method proposed in this paper can quickly complete the scheme design in the design phase of the building machine and display it through the 3D model, which has a better visualization effect, improves the design efficiency, and reduces the design cost, and the Unity simulation platform can also provide the construction personnel with pre-shift education and simulation of the operation of the building machine. This method provides a theoretical basis and guidance for the digital construction of the building machine.
Clinical Application of ImmunoPET Targeting Checkpoint Inhibitors
Authors: Abenavoli Elisabetta Maria , Linguanti Flavia , Calabretta Raffaella , Delgado Bolton Roberto C. , Berti Valentina , Lopci Egesta
Published: December 2023

In the last decade, monoclonal antibodies (mAbs) targeting CTLA-4, PD-1, or PD-L1 have been developed and immune checkpoint inhibitors (ICIs) have become the main approach in cancer immunotherapy. However, not all patients benefit from ICI therapy and some are at risk of developing treatment-induced side-effects. These aspects, in parallel with the imaging challenges related to response assessments during immunotherapy, have driven scientific research to the discovery of new predictive biomarkers to individualize patients who could benefit from ICIs. In this context, molecular imaging using PET (positron emission tomography), which allows for whole-body tumor visualization, may be a promising non-invasive method for the determination of patients’ sensitivity to antibody drugs. Several PET tracers, diverse from 2-[18F]FDG (or 2-Deoxy-2-[18F]fluoroglucose), have been developed to image immune checkpoints (ICs) or key elements of the immune system, although most of them are still in preclinical phases. Herein, we present the current state of the ImmunoPET-targeting of IC proteins with mAbs and antibody fragments, with a main focus on the latest developments in clinical molecular imaging studies of solid tumors. Moreover, given the relevance of the immune system and of tumor-infiltrating lymphocytes in particular in the prediction of the benefit of ICIs, we dedicate a portion of this review to ImmunoPET-targeting T cells.
Computational Modeling of Thermal Ablation Zones in the Liver: A Systematic Review
Authors: van Erp Gonnie C. M. , Hendriks Pim , Broersen Alexander , Verhagen Coosje A. M. , Gholamiankhah Faeze , Dijkstra Jouke , Burgmans Mark C.
Published: December 2023

Purpose: This systematic review aims to identify, evaluate, and summarize the findings of the literature on existing computational models for radiofrequency and microwave thermal liver ablation planning and compare their accuracy. Methods: A systematic literature search was performed in the MEDLINE and Web of Science databases. Characteristics of the computational model and validation method of the included articles were retrieved. Results: The literature search identified 780 articles, of which 35 were included. A total of 19 articles focused on simulating radiofrequency ablation (RFA) zones, and 16 focused on microwave ablation (MWA) zones. Out of the 16 articles simulating MWA, only 2 used in vivo experiments to validate their simulations. Out of the 19 articles simulating RFA, 10 articles used in vivo validation. Dice similarity coefficients describing the overlap between in vivo experiments and simulated RFA zones varied between 0.418 and 0.728, with mean surface deviations varying between 1.1 mm and 8.67 mm. Conclusion: Computational models to simulate ablation zones of MWA and RFA show considerable heterogeneity in model type and validation methods. It is currently unknown which model is most accurate and best suitable for use in clinical practice.
Radiation-Induced Innate Neutrophil Response in Tumor Is Mediated by the CXCLs/CXCR2 Axis
Authors: Zhang Faya , Mulvaney Oscar , Salcedo Erica , Manna Subrata , Zhu James Z. , Wang Tao , Ahn Chul , Pop Laurentiu M. , Hannan Raquibul
Published: December 2023

The early events that lead to the inflammatory and immune-modulatory effects of radiation therapy (RT) in the tumor microenvironment (TME) after its DNA damage response activating the innate DNA-sensing pathways are largely unknown. Neutrophilic infiltration into the TME in response to RT is an early innate inflammatory response that occurs within 24–48 h. Using two different syngeneic murine tumor models (RM-9 and MC-38), we demonstrated that CXCR2 blockade significantly reduced RT-induced neutrophilic infiltration. CXCR2 blockade showed the same effects on RT-induced tumor inhibition and host survival as direct neutrophil depletion. Neutrophils highly and preferentially expressed CXCR2 compared to other immune cells. Importantly, RT induced both gene and protein expression of CXCLs in the TME within 24 h, attracting neutrophils into the tumor. Expectedly, RT also upregulated the gene expression of both cGAS and AIM2 DNA-sensing pathways in cGAS-positive MC-38 tumors but not in cGAS-negative RM-9 tumors. Activation of these pathways resulted in increased IL-1β, which is known to activate the CXCLs/CXCR2 axis. Gene ontology analysis of mRNA-Seq supported these findings. Taken together, the findings suggest that the CXCLs/CXCR2 axis mediates the RT-induced innate inflammatory response in the TME, likely translating the effects of innate DNA-sensing pathways that are activated in response to RT-induced DNA damage.
Cytogenetic Profile in Monoclonal Gammopathy of Undetermined Significance, Smoldering and Symptomatic Multiple Myeloma: A Study of 1087 Patients with Highly Purified Plasma Cells
Authors: Tang Guilin , Wu Yilin , Lin Pei , Toruner Gokce A. , Hu Shimin , Li Shaoying , Qazilbash Muzaffar H. , Orlowski Robert Z. , Ye Christine , Xu Jie , Nahmod Karen A. , Medeiros L. Jeffrey , Tang Zhenya
Published: December 2023

The aim of this study was to examine the cytogenetic profiles of plasma cell neoplasms (PCNs) at various disease stages, encompassing 1087 patients with monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), newly diagnosed multiple myeloma (NDMM), and refractory/relapsed multiple myeloma (RRMM). Fluorescence in situ hybridization (FISH) analyses were conducted on highly purified plasma cell samples, revealing that 96% of patients exhibited at least one cytogenetic abnormality. The genomic complexity escalated from MGUS to SMM and further to NDMM and RRMM, largely driven by 1q gain, del(17p), MYC-rearrangement (MYC-R), del(1p), and tetraploidy. Elevated frequencies of high-risk cytogenetics (59%), 1q gain (44%), and del(17p) (23%), as well as the presence of subclones (48%), were particularly notable in RRMM cases. IGH::CCND1 was observed in 26% of the cases, with no apparent variations across races, ages, or disease groups. Concurrent chromosomal analysis with FISH revealed that the incidence of abnormal karyotypes was strongly correlated with the extent of neoplastic plasma cell infiltration, genomic complexity, and the presence of specific abnormalities like del(17p) and MYC-R. Approximately 98% of the cases with abnormal karyotypes were complex, with most featuring five or more abnormalities. Chromosome 1 structural abnormalities were the most prevalent, found in 65% of cases. The frequent presence of subclones and composite karyotypes underscored the genomic heterogeneity and instability in this cohort.
TMEM97/Sigma 2 Receptor Increases Estrogen Receptor α Activity in Promoting Breast Cancer Cell Growth
Authors: Zhang Yuanqin , Fang Xiangwei , Wang Jiuhui , Nie Daotai
Published: December 2023

Aberrant estrogen receptor (ER) signaling is a major driver of breast tumor growth and progression. Sigma 2 receptor has long been implicated in breast carcinogenesis based on pharmacological studies, but its molecular identity had been elusive until TMEM97 was identified as the receptor. Herein, we report that the TMEM97/sigma 2 receptor is highly expressed in ER-positive breast tumors and its expression is strongly correlated with ERs and progesterone receptors (PRs) but not with HER2 status. High expression levels of TMEM97 are associated with reduced overall survival of patients. Breast cancer cells with increased expression of TMEM97 had a growth advantage over the control cells under both nutrition-limiting and sufficient conditions, while the knockdown of TMEM97 expression reduced tumor cell proliferations. When compared to their vector control cells, MCF7 and T47D cells with increased TMEM97 expression presented increased resistance to tamoxifen treatment and also grew better under estrogen-depleted conditions. The TMEM97/sigma 2 receptor enhanced the ERα transcriptional activities and increased the expression of genes responsive to estrogen treatment. Increased TMEM97 also stimulated the mTOR/S6K1 signaling pathways in the MCF7 and T47D cells. The increased level of active, phosphorylated ERα, and the enhanced resistance to tamoxifen treatment with increased TMEM97, could be blocked by an mTOR inhibitor. The knockdown of TMEM97 expression reduced the ERα and mTOR/S6K1 signaling activities, rendering the cells with an increased sensitivity to tamoxifen. The observations suggest that the TMEM97/sigma 2 receptor is a novel regulator of ERα activities in breast tumor cell growth.
Breaking Barriers: AI’s Influence on Pathology and Oncology in Resource-Scarce Medical Systems
Authors: Vigdorovits Alon , Köteles Maria Magdalena , Olteanu Gheorghe-Emilian , Pop Ovidiu
Published: December 2023

The application of artificial intelligence to improve the access of cancer patients to high-quality medical care is one of the goals of modern medicine. Pathology constitutes the foundation of modern oncologic treatment, and its role has expanded far beyond diagnosis into predicting treatment response and overall survival. However, the funding of pathology is often an afterthought in resource-scarce medical systems. The increased digitalization of pathology has paved the way towards the potential use of artificial intelligence tools for improving pathologist efficiency and extracting more information from tissues. In this review, we provide an overview of the main research directions intersecting with artificial intelligence and pathology in relation to oncology, such as tumor classification, the prediction of molecular alterations, and biomarker quantification. We then discuss examples of tools that have matured into clinical products and gained regulatory approval for clinical use. Finally, we highlight the main hurdles that stand in the way of the digitalization of pathology and the application of artificial intelligence in pathology while also discussing possible solutions.
Unveiling the Immunogenicity of Ovarian Tumors as the Crucial Catalyst for Therapeutic Success
Authors: Rodriguez Galaxia M. , Yakubovich Edward , Vanderhyden Barbara C.
Published: December 2023

Epithelial ovarian cancer (EOC) is the most lethal gynecologic cancer. The disease is often diagnosed after wide-spread dissemination, and the standard treatment combines aggressive surgery with platinum-based chemotherapy; however, most patients experience relapse in the form of peritoneal carcinomatosis, resulting in a 5-year mortality below 45%. There is clearly a need for the development of novel treatments and cancer immunotherapies offering a different approach. Immunotherapies have demonstrated their efficacy in many types of cancers; however, only <15% of EOC patients show any evidence of response. One of the main barriers behind the poor therapeutic outcome is the reduced expression of Major Histocompatibility Complexes class I (MHC I) which occurs in approximately 60% of EOC cases. This review aims to gather and enhance our current understanding of EOC, focusing on its distinct cancer characteristics related to MHC I expression, immunogenicity, antigen presentation, epithelial-to-mesenchymal transition, and various ongoing immunotherapeutic strategies designed to stimulate antitumor immunity.
Catalytic Ozonation of Ethyl Acetate with Assistance of MMn2O4 (M = Cu, Co, Ni and Mg) Catalysts through In Situ DRIFTS Experiments and Density Functional Theory Calculations
Authors: Sun Yulin , Liu Peixi , Zhang Yiwei , He Yong , Zhu Yanqun , Wang Zhihua
Published: December 2023

Catalytic ozonation, with enhanced efficiency and reduced byproduct formation at lower temperatures, proved to be efficient in ethyl acetate (EA) degradation. In this work, MMn2O4 (M = Cu, Co, Ni, Mg) catalysts were prepared via a redox-precipitation method to explore the catalytic ozonation mechanism of EA. Among all the catalysts, CuMn exhibited superior catalytic activity at 120 °C, achieving nearly 100% EA conversion and above 90% CO2 selectivity with an O3/EA molar ratio of 10. Many characterizations were conducted, such as SEM, BET and XPS, for revealing the properties of the catalysts. Plentiful active sites, abundant oxygen vacancies, more acid sites and higher reduction ability contributed to the excellent performance of CuMn. Moreover, the addition of NO induced a degree of inhibition to EA conversion due to its competition for ozone. H2O had little effect on the catalytic ozonation of CuMn, as the conversion of EA could reach a stable platform at ~89% even with 5.0 vol.% of H2O. The presence of SO2 usually caused catalyst deactivation. However, the conversion could gradually recover once SO2 was discontinued due to the reactivation of ozone. A detailed reaction mechanism for catalytic ozonation was proposed via in situ DRIFTS measurements and DFT calculations.
The Management of Data for the Banking, Qualification, and Distribution of Induced Pluripotent Stem Cells: Lessons Learned from the European Bank for Induced Pluripotent Stem Cells
Authors: Mah Nancy , Kurtz Andreas , Fuhr Antonie , Seltmann Stefanie , Chen Ying , Bultjer Nils , Dewender Johannes , Lual Ayuen , Steeg Rachel , Mueller Sabine C.
Published: December 2023

The European Bank for induced pluripotent Stem Cells (EBiSC) was established in 2014 as a non-profit project for the banking, quality control, and distribution of human iPSC lines for research around the world. EBiSC iPSCs are deposited from diverse laboratories internationally and, hence, a key activity for EBiSC is standardising not only the iPSC lines themselves but also the data associated with them. This includes enabling unique nomenclature for the cells, as well as applying uniformity to the data provided by the cell line generator versus quality control data generated by EBiSC, and providing mechanisms to share personal data in a secure and GDPR-compliant manner. A joint approach implemented by EBiSC and the human pluripotent stem cell registry (hPSCreg®) has provided a solution that enabled hPSCreg® to improve its registration platform for iPSCs and EBiSC to have a pipeline for the import, standardisation, storage, and management of data associated with EBiSC iPSCs. In this work, we describe the experience of cell line data management for iPSC banking throughout the course of EBiSC’s development as a central European banking infrastructure and present a model for how this could be implemented by other iPSC repositories to increase the FAIRness of iPSC research globally.
Promoting the Segregation of Sr2+ from the Perovskite Oxygen Catalyst La0.5Sr0.5Co3−δ via Quenching
Authors: Zheng Fa , Qian Yaozheng , Pang Shengli
Published: December 2023

The microstructure of the surface plays a crucial role in determining the efficacy of high-temperature oxygen catalysts. In this study, we conducted a comprehensive investigation into the impact of quenching on the crystal structure, surface topology, and oxygen-catalyzing capabilities of La0.5Sr0.5CoO3−δ (LSC). Our findings revealed that quenching can notably promote the segregation of SrO on the surface of the classical perovskite-based high-temperature oxygen catalyst LSC. This phenomenon can be attributed to the introduction of a significant number of chemical defects within the LSC bulk during the catalytic process, thereby endowing it with sufficient stress and electrostatic forces to drive Sr2+ toward the catalyst’s surface. This finding could simplify the removal of inert segregation layers on the surface of perovskite-based high-temperature oxygen catalysts. The electrochemical analysis results demonstrate that the quenching process can markedly improve the long-term operational stability of LSC but can bring a decrease in catalytic activity.
Impact of Solid-State Charge Injection on Spectral Photoresponse of NiO/Ga2O3 p–n Heterojunction
Authors: Schulte Alfons , Modak Sushrut , Landa Yander , Atman Atman , Li Jian-Sian , Chiang Chao-Ching , Ren Fan , Pearton Stephen J. , Chernyak Leonid
Published: December 2023

Forward bias hole injection from 10-nm-thick p-type nickel oxide layers into 10-μm-thick n-type gallium oxide in a vertical NiO/Ga2O3 p–n heterojunction leads to enhancement of photoresponse of more than a factor of 2 when measured from this junction. While it takes only 600 s to obtain such a pronounced increase in photoresponse, it persists for hours, indicating the feasibility of photovoltaic device performance control. The effect is ascribed to a charge injection-induced increase in minority carrier (hole) diffusion length (resulting in improved collection of photogenerated non-equilibrium carriers) in n-type β-Ga2O3 epitaxial layers due to trapping of injected charge (holes) on deep meta-stable levels in the material and the subsequent blocking of non-equilibrium carrier recombination through these levels. Suppressed recombination leads to increased non-equilibrium carrier lifetime, in turn determining a longer diffusion length and being the root-cause of the effect of charge injection.
Breast Imaging Physics in Mammography (Part II)
Authors: Fico Noemi , Grezia Graziella Di , Cuccurullo Vincenzo , Salvia Antonio Alessandro Helliot , Iacomino Aniello , Sciarra Antonella , La Forgia Daniele , Gatta Gianluca
Published: December 2023

One of the most frequently detected neoplasms in women in Italy is breast cancer, for which high-sensitivity diagnostic techniques are essential for early diagnosis in order to minimize mortality rates. As addressed in Part I of this work, we have seen how conditions such as high glandular density or limitations related to mammographic sensitivity have driven the optimization of technology and the use of increasingly advanced and specific diagnostic methodologies. While the first part focused on analyzing the use of a mammography machine from a physical and dosimetric perspective, in this paper, we will examine other techniques commonly used in breast imaging: contrast-enhanced mammography, digital breast tomosynthesis, radio imaging, and include some notes on image processing. We will also explore the differences between these various techniques to provide a comprehensive overview of breast lesion detection techniques. We will examine the strengths and weaknesses of different diagnostic modalities and observe how, with the implementation of improvements over time, increasingly effective diagnoses can be achieved.
Heat-Bath and Metropolis Dynamics in Ising-like Models on Directed Regular Random Graphs
Authors: Lipowski Adam , Ferreira António L. , Lipowska Dorota
Published: December 2023

Using a single-site mean-field approximation (MFA) and Monte Carlo simulations, we examine Ising-like models on directed regular random graphs. The models are directed-network implementations of the Ising model, Ising model with absorbing states, and majority voter models. When these nonequilibrium models are driven by the heat-bath dynamics, their stationary characteristics, such as magnetization, are correctly reproduced by MFA as confirmed by Monte Carlo simulations. It turns out that MFA reproduces the same result as the generating functional analysis that is expected to provide the exact description of such models. We argue that on directed regular random graphs, the neighbors of a given vertex are typically uncorrelated, and that is why MFA for models with heat-bath dynamics provides their exact description. For models with Metropolis dynamics, certain additional correlations become relevant, and MFA, which neglects these correlations, is less accurate. Models with heat-bath dynamics undergo continuous phase transition, and at the critical point, the power-law time decay of the order parameter exhibits the behavior of the Ising mean-field universality class. Analogous phase transitions for models with Metropolis dynamics are discontinuous.
A Precise Calibration Method for the Robot-Assisted Percutaneous Puncture System
Authors: Li Jinbiao , Li Minghui , Zeng Quan , Qian Cheng , Li Tao , Zhou Shoujun
Published: December 2023

The precision and stability of the Robot-Assisted Percutaneous Puncture (RAPP) system have become increasingly crucial with the widespread integration of robotic technology in the field of medicine. The accurate calibration of the RAPP system prior to surgery significantly influences target positioning performance. This study proposes a novel system calibration method that simultaneously addresses system hand–eye calibration and robot kinematic parameters calibration, thereby enhancing the surgery success rate and ensuring patient safety. Initially, a Closed-loop Hand–eye Calibration (CHC) method is employed to rapidly establish transformation relationships among system components. These CHC results are then integrated with nominal robot kinematic parameters to preliminarily determine the system calibration parameters. Subsequently, a hybrid algorithm, combining the regularized Levenberg–Marquardt (LM) algorithm and a particle filtering algorithm, is utilized to accurately estimate the system calibration parameters in stages. Numerical simulations and puncture experiments were conducted using the proposed system calibration method and other comparative methods. The experimental results revealed that, among several comparative methods, the approach presented in this paper yields the greatest improvement in the puncture accuracy of the RAPP system, demonstrating the accuracy and effectiveness of this method. In conclusion, this calibration method significantly contributes to enhancing the precision, operational capability, and safety of the RAPP system in practical applications.
Switching Capacitor Filter with Multiple Functions, Adjustable Bandwidth in the Range of 5 Hz–10 kHz
Authors: He Fan , Yuan Yubo , Xiao Jinjin , Han Zehao , Fu Yingchun , Huang Shuilong
Published: December 2023

This article proposes a second-order switch-capacitor filter that integrates low-pass, high-pass, band-pass, band-stop, and all-pass, and achieves flexible bandwidth adjustment of the filter through clock rate and capacitance ratio. The final filter design consists of two completely independent second-order switch-capacitor filter channels, and a 4-order Butterworth low-pass filter is designed through two-stage cascades. The two completely independent second-order switch-capacitor filters are integrated on a single chip and manufactured using the Huahong BCD350GE high-voltage 24 V process. The measurement results indicate that the proposed switch-capacitor filter achieves various functional filtering characteristics and achieves a bandwidth of 5 Hz to 10 kHz. The chip area is 5.1 × 3.1 mm2, powered by a dual power supply of ± 5 V, and the power consumption is 80 mW.
A Novel Unsupervised Outlier Detection Algorithm Based on Mutual Information and Reduced Spectral Clustering
Authors: Huang Yuehua , Liu Wenfen , Li Song , Guo Ying , Chen Wen
Published: December 2023

Outlier detection is an essential research field in data mining, especially in the areas of network security, credit card fraud detection, industrial flaw detection, etc. The existing outlier detection algorithms, which can be divided into supervised methods and unsupervised methods, suffer from the following problems: curse of dimensionality, lack of labeled data, and hyperparameter tuning. To address these issues, we present a novel unsupervised outlier detection algorithm based on mutual information and reduced spectral clustering, called MISC-OD (Mutual Information and reduced Spectral Clustering—Outlier Detection). MISC-OD first constructs a mutual information matrix between features, then, by applying reduced spectral clustering, divides the feature set into subsets, utilizing the LOF (Local Outlier Factor) for outlier detection within each subset and combining the outlier scores found within each subset. Finally, it outputs the outlier score. Our contributions are as follows: (1) we propose a novel outlier detection method called MISC-OD with high interpretability and scalability; (2) numerous experiments on 18 benchmark datasets demonstrate the superior performance of the MISC-OD algorithm compared with eight state-of-the-art baselines in terms of ROC (receiver operating characteristic) and AP (average precision).
KULF-TT53: A Display-Specific Turntable-Based Light Field Dataset for Subjective Quality Assessment
Authors: Javidi Kamran , Martini Maria G. , Kara Peter A.
Published: December 2023

Light field datasets enable researchers to conduct both objective and subjective quality assessments, which are particularly useful when acquisition equipment or resources are not available. Such datasets may vary in terms of capture technology and methodology, content, quality characteristics (e.g., resolution), and the availability of subjective ratings. When contents of a light field dataset are visualized on a light field display, the display system matches the received input to its output capabilities through various processes, such as interpolation. Therefore, one of the most straightforward methods to create light field contents for a specific display is to consider its visualization parameters during acquisition. In this paper, we introduce a novel display-specific light field dataset, captured using a DSLR camera and a turntable rig. The visual data of the seven static scenes were recorded twice by using two settings of angular resolution. While both were acquired uniformly within a 53-degree angle, which matches the viewing cone of the display they were captured for, one dataset consists of 70 views per content, while the other of 140. Capturing the contents twice was a more straightforward solution than downsampling, as the latter approach could either degrade the quality or make the FOV size inaccurate. The paper provides a detailed characterization of the captured contents, as well as compressed variations of the contents with various codecs, together with the calculated values of commonly-used quality metrics for the compressed light field contents. We expect that this dataset will be useful for the research community working on light field compression, processing, and quality assessment, for instance to perform subjective quality assessment tests on a display with a 53-degree display cone and to test new interpolation methods and objective quality metrics. In future work, we will also focus on subjective tests and provide relevant results. This dataset is made free to access for the research community.
Knowledge-Aware Graph Self-Supervised Learning for Recommendation
Authors: Li Shanshan , Jia Yutong , Wu You , Wei Ning , Zhang Liyan , Guo Jingfeng
Published: December 2023

Collaborative filtering (CF) based on graph neural networks (GNN) can capture higher-order relationships between nodes, which in turn improves recommendation performance. Although effective, GNN-based methods still face the challenges of sparsity and noise in real scenarios. In recent years, researchers have introduced graph self-supervised learning (SSL) techniques into CF to alleviate the sparse supervision problem. The technique first augments the data to obtain contrastive views and then utilizes the mutual information maximization to provide self-supervised signals for the contrastive views. However, the existing approaches based on graph self-supervised signals still face the following challenges: (i) Most of the works fail to effectively mine and exploit the supervised information from the item knowledge graph, resulting in suboptimal performance. (ii) Existing data augmentation methods are unable to fully exploit the potential of contrastive learning, because they primarily focus on the contrastive view of data structure changes and neglect the adjacent relationship among users and items. To address these issues, we propose a novel self-supervised learning approach, namely Knowledge-aware Graph Self-supervised Learning (KGSL). Specifically, we calculate node similarity based on semantic relations between items in the knowledge graph to generate a semantic-based item similarity graph. Then, the self-supervised learning contrast views are generated from both the user–item interaction graph and the item similarity graph, respectively. Maximization of the information from these contrastive views provides additional self-supervised signals to enhance the node representation capacity. Finally, we establish a joint training strategy for the self-supervised learning task and the recommendation task to further optimize the learning process of KGSL. Extensive comparative experiments as well as ablation experiments are conducted on three real-world datasets to verify the effectiveness of KGSL.
Improving Medical Entity Recognition in Spanish by Means of Biomedical Language Models
Authors: Villaplana Aitana , Martínez Raquel , Montalvo Soto
Published: December 2023

Named Entity Recognition (NER) is an important task used to extract relevant information from biomedical texts. Recently, pre-trained language models have made great progress in this task, particularly in English language. However, the performance of pre-trained models in the Spanish biomedical domain has not been evaluated in an experimentation framework designed specifically for the task. We present an approach for named entity recognition in Spanish medical texts that makes use of pre-trained models from the Spanish biomedical domain. We also use data augmentation techniques to improve the identification of less frequent entities in the dataset. The domain-specific models have improved the recognition of name entities in the domain, beating all the systems that were evaluated in the eHealth-KD challenge 2021. Language models from the biomedical domain seem to be more effective in characterizing the specific terminology involved in this task of named entity recognition, where most entities correspond to the "concept" type involving a great number of medical concepts. Regarding data augmentation, only back translation has slightly improved the results. Clearly, the most frequent types of entities in the dataset are better identified. Although the domain-specific language models have outperformed most of the other models, the multilingual generalist model mBERT obtained competitive results.
A Fast Reconfiguration Technique for Boost-Based DMPPT PV Systems Based on Deterministic Clustering Analysis
Authors: Balato Marco , Petrarca Carlo , Liccardo Annalisa , Botti Martina , Verolino Luigi
Published: December 2023

Mismatching operating conditions affect the energetic performance of PhotoVoltaic (PV) systems because they decrease their efficiency and reliability. The two different approaches used to overcome this problem are Distributed Maximum Power Point Tracking (DMPPT) architecture and reconfigurable PV array architecture. These techniques can be considered not only as alternatives but can be combined to reach better performance. To this aim, the present paper presents a new algorithm, based on the joint action of the DMPPT and reconfiguration approaches, applied to a reconfigurable Series-Parallel-Series architecture, which is suitable for domestic PV application. The core of the algorithm is a deterministic cluster analysis based on the shape of the current vs. voltage characteristic of a single PV module combined with its DC/DC converter to perform the DMPPT function. Experimental results are provided to validate the effectiveness of the proposed algorithm and to demonstrate evidence of its major advantages: robustness, simplicity of implementation and time-saving.
Practical Challenges in Nanofluid Convective Heat Transfer Inside Silicon Microchannels
Authors: Eneren Pinar , Aksoy Yunus Tansu , Vetrano Maria Rosaria
Published: December 2023

Despite numerous studies on nanofluids in microchannel heat sinks (MCHSs), they are not yet commercialized due to long-term stability issues and high maintenance costs. Therefore, this study explores the impact of nanofluids and nanoparticle clustering on single-phase convective heat transfer inside microchannels under laminar conditions. Water and commercially available water-based nanosuspensions, including Al2O3-water (30–60 nm), TiO2-water (5–30 nm), and polystyrene-water (50 nm), are circulated through silicon MCHS having rectangular channels integrated into a closed flow loop. To assess the in situ and real-time nanoparticle clustering during heat transfer experiments, Light Extinction Spectroscopy (LES) is applied as a non-intrusive measurement technique on nanofluids without any fluid sampling. Our findings reveal the appearance of nanofluid discoloration with no measurable increase in heat transfer coefficient. This unexpected change is attributed to the interplay of abrasion, erosion, and corrosion phenomena, likely triggered by the clustering of nanoparticles within the silicon microchannels—a novel insight into the complex dynamics of nanofluid behavior (an increase in the De Brouckere mean diameter from 11 nm to 107.3 nm over a 2.5 h period for TiO2 nanoparticles). The resulting material loss could not be mitigated by altering the nanoparticle material, which may impede heat transfer enhancement under tested conditions.
Effect of the Ground Albedo on the Estimation of Solar Radiation on Tilted Flat-Plate Surfaces: The Case of Saudi Arabia
Authors: Farahat Ashraf , Kambezidis Harry D. , Kampezidou Styliani I.
Published: December 2023

This work investigates the influence of ground albedo on the solar radiation obtained by surfaces mounted on fixed-tilt-to-south, one-axis, and two-axis systems. To do this, estimation of the solar radiation difference is performed by applying real albedo and zero albedo. This is achieved within Saudi Arabia at 82 selected sites. Annual, seasonal, and monthly mean solar energy differences are computed as a function of the site’s number, latitude, and local near-real ground albedo. The great variation in the ground-albedo values at the 82 sites (0.1–0.46) could be thought of as having a significant effect on the solar radiation levels received on the three tracking modes. This analysis shows quite the opposite; zero-albedo ground diminishes solar radiation levels by 1.43%, 3.50%, and 3.20%, respectively, for the three modes. Therefore, in most solar engineering applications, a ground albedo of 0.2 (considered a reference) can be used without losing accuracy. This is the main conclusion of the study, which must, however, be applied with caution in areas with snow cover, especially for mode-III tracking systems. In such situations, the increase in solar radiation levels may be up to 15% (but ≈3.5% for mode-I and -II systems instead).
Stability Control Technology for Surrounding Rocks in Gob-Side Entry Driving with Small Coal Pillars under Dynamic Pressure
Authors: Guo Shihao , Hu Shanchao , Huang Junhong , Gao Zhihao , Cheng Yafei , Han Jinming , Yang Lei
Published: December 2023

To address the support difficulties caused by the dynamic pressure from the adjacent working face in gob-side entry driving, this study, taking the 8103 working face of the Jinhuagong Coal Mine in Shanxi Province as an example, adopted methods such as theoretical analysis, physical experiments, numerical simulations, and field practices to explore roof-cutting and pressure-relieving techniques to control the surrounding rocks in gob-side entry driving with small coal pillars under dynamic pressure. Fractures of the lateral roof, stresses on the surrounding rock, and deformations with different cutting-roof parameters were analyzed to determine the reasonable parameters for applications. The following results have been obtained. The longer the lateral cantilever length of the roof, the greater the load borne by the surrounding rock. Therefore, the key to reducing the confining pressure in a roadway is reducing the lateral cantilever length of the roof. After roof cutting, the roof of the gob area collapsed more completely. The stress on both sides of the coal pillar and that on the ribs of the solid coal dropped by 7.72 MPa and 4.16 MPa, respectively. The key roof-cutting parameters were analyzed by the UDEC numerical software, and the reasonable roof-cutting angle and height were determined to be 12° and 14 m. A support scheme combining “steel strip + bolt + anchor cable + roof cutting” was proposed. With the scheme applied, the displacement of both sides of the coal pillar was 61 mm shorter than that in the non-test section, and the duration in which the roadway was affected by mining was 11 days shorter. Therefore, the rationality of the selected roof-cutting and support parameters in this study is verified. The proposed scheme can effectively control the stability of surrounding rocks in gob-side entry driving with small coal pillars under dynamic pressure.
Management of Fly Ash to Synthesise Geopolymers and Zeolites
Authors: Baran Paweł , Sobala Jakub , Szczurowski Jakub , Zarębska Katarzyna
Published: December 2023

The purpose of the article was to conduct an in-depth literature review on the possibilities of managing combustion by-products (mainly fly ash) in the context of a closed-loop economy. First, information on the chemical composition of fly ash in Poland was collected and compared with the composition of fly ash in other European countries. The authors concentrated on describing methods for synthesizing geopolymers and zeolites using fly ash as a substrate. By-products of zeolite synthesis, which are strongly alkaline solutions, can be used as a substrate in the synthesis of geopolymers. A concept has been proposed to combine the synthesis of zeolites and geopolymers into a single process to close the material loop. The search for comprehensive technological solutions that take into account the ideas of a closed-loop economy is essential in an era of resource depletion, and this literature review encapsulates this topic area.