bluuebunny/crossref_metadata_2025 huggingface dataset:
Process Stability Analysis during Trochoidal Milling of AZ91D Magnesium Alloy Using Different Toolholder Types
Authors: Korpysa Jarosław , Zagórski Ireneusz , Weremczuk Andrzej , Habrat Witold
Published: April 2024

Trochoidal milling is one of the solutions for increasing the efficiency of machining processes. A decreased cutting tool’s arc of contact leads to a reduction in the generated cutting forces, thus improving process stability. Vibration is an inherent part of any machining process, affecting the accuracy and quality of the manufactured components, but it can also pose a danger to machine operators. Chatter is particularly detrimental, leaving characteristic marks on shaped surfaces and potentially leading to catastrophic tool damage. Therefore, it is important to ensure the stability of machining and also reduce vibration. The primary purpose of the conducted research is to evaluate the stability of the milling process of the AZ91D magnesium alloy performed through a trochoidal strategy. An additional objective is to establish the effect of the variation in machining parameters and toolholder types on milling stability. Three types of toolholders most commonly used in industry are used in the study. The basis of the investigation is the measurement of vibration displacement and acceleration analysed in the time domain. A spectral analysis of the signals is also performed based on Fast Fourier Transform, to identify signal components and detect the susceptibility to chatter occurrence. An important part of the study is also an attempt to use the Composite Multiscale Entropy as an indicator to determine the stability of the machining processes. Entropy does not exceed the values of 1.5 for cutting speed and 2.5 for feed per tooth, respectively. Vibration acceleration does not exceed (in most cases) the value of 20 m/s2 for the peak-to-peak parameter and the shrinkfit toolholder. For vibration displacement (peak-to-peak parameter), there are oscillations around the value of 0.9 mm for all kinds of toolholders.
Distributed Consensus for Global Matrix Formation in the Principal Component Pursuit Scenario
Authors: Suárez  Gustavo , Velásquez Juan David
Published: April 2024

The aim behind principal component pursuit is to recover a low-rank matrix and a sparse matrix from a noisy signal which is the sum of both matrices. This optimization problem is a priori and non-convex and is useful in signal processing, data compression, image processing, machine learning, fluid dynamics, and more. Here, a distributed scheme described by a static undirected graph, where each agent only observes part of the noisy or corrupted matrix, is applied to achieve a consensus; then, a robust approach that can also handle missing values is applied using alternating directions to solve the convex relaxation problem, which actually solves the non-convex problem under some weak assumptions. Some examples of image recovery are shown, where the network of agents achieves consensus exponentially fast.
Geological and Geotechnical Aspects of the Most Significant Deep Landslides in the Danube Area on the Territory of Vojvodina
Authors: Djogo Mitar , Vasić Milinko , Despotović Iva , Mihajlović Stefan
Published: April 2024

The largest and the deepest landslides in Serbia occurred on the right valley side of the Danube. General conclusions about landslides along the Danube were obtained on the basis of their comprehensive, detailed investigations: the Sloboda bridge in Novi Sad, the Beška bridge, the large settlement of Bocke, and the high-speed railway viaduct in Čortanovci. These areas are actually large, unstable slopes with deep and shallow landslides. Deep landslides consist of several sliding blocks with 20–40 m in depth. All these landslides were formed in clays and sands of the Pliocene age in the decayed crust of these sediments. The general conclusions about landslides presented in this paper will be of great use for the construction of new facilities in the entire unstable area along the Danube, which is about 100 km in length.
Study on the Influence of Adjacent Double Deep Foundation Pit Excavation Sequence on Existing Tunnel Deformation Based on HSS Constitutive Model
Authors: Wang Sijun , Wang Wenting , Yang Huan , Zhao Debin , Liu Yang
Published: April 2024

With the increase in the number of buildings along the subway, the impact of building construction on the adjacent subway tunnels has gradually come to the forefront and become an important problem to be solved in the engineering field. In particular, the excavation and unloading process of deep foundation pits will trigger an additional deformation of the subway structure, which may pose a serious threat to the safety and stability of subway tunnels. This article is based on a foundation pit project in the sub-center of Beijing, focusing on the form of a connected double foundation pit. Using the HSS constitutive model for soil materials, this study simulates the deformation response of adjacent existing subway tunnels under three excavation sequences: sequential excavation, simultaneous excavation, and the comprehensive excavation of the connected double foundation pits. The study shows that, from the point of view of the total displacement of the whole construction process, the impact of a synchronized excavation of double pits on the existing tunnel line is relatively large in the process, and the impact of sequential excavation is relatively small in the construction cycle. The result of the similarity of the excavation sequence is the similarity of the impact trend. The volume of excavated earth determines the value of displacement change for each excavation scenario in each working condition and is also responsible for the convergence of changes. The trend of total tunnel displacement is more consistent with that of vertical displacement, which is dominated by vertical displacement, with horizontal displacement having a relatively small influence. The maximum value of the total tunnel displacement occurs at the side of the tunnel near the excavation area, and the direction is inclined to the excavation area. The application of supporting structures, especially the center plate and the bottom plate, can suppress the vertical deformation of the tunnel bulge.
Optimal Timing of Carrot Crop Monitoring and Yield Assessment Using Sentinel-2 Images: A Machine-Learning Approach
Authors: Madugundu Rangaswamy , Al-Gaadi Khalid A. , Tola ElKamil , Edrris Mohamed K. , Edrees Haroon F. , Alameen Ahmed A.
Published: April 2024

Remotely sensed images provide effective sources for monitoring crop growth and the early prediction of crop productivity. To monitor carrot crop growth and yield estimation, three 27 ha center-pivot irrigated fields were studied to develop yield prediction models using crop biophysical parameters and vegetation indices (VIs) extracted from Sentinel-2A (S2) multi-temporal satellite data. A machine learning (ML)-based image classification technique, the random forest (RF) algorithm, was used for carrot crop monitoring and yield analysis. The VIs (NDVI, RDVI, GNDVI, SIPI, and GLI), extracted from S2 satellite data for the crop ages of 30, 45, 60, 75, 90, 105, and 120 days after plantation (DAP), and the chlorophyll content, SPAD (Soil Plant Analysis Development) meter readings, were incorporated as predictors for the RF algorithm. The RMSE of the five RF scenarios studied ranged from 7.8 t ha−1 (R2 ≥ 0.82 with Scenario 5) to 26.2 t ha−1 (R2 ≤ 0.46 with Scenario 1). The optimal window for monitoring the carrot crop for yield prediction with the use of S2 images could be achieved between the 60 DAP and 75 DAP with an RMSE of 8.6 t ha−1 (i.e., 12.4%) and 11.4 t ha−1 (16.2%), respectively. The developed RF algorithm can be utilized in carrot crop yield monitoring and decision-making processes for the self-sustainability of carrot production.
A Segmentation-Based Optimal Seamline Generation Method for SAR Image Mosaic
Authors: Liu Rui , Zhu Jingxing , Jiao Niangang , Chen Yao , You Hongjian
Published: April 2024

In the mosaic creation of multiple high-resolution synthetic aperture radar (SAR) images, achieving an optimal seamline in overlapping areas is crucial for seamless and visually satisfactory results. Many existing seamline generation methods are designed primarily for optical remote sensing images, but due to the differing characteristics of SAR images and optical images, applying these methods directly to SAR images poses challenges in finding the optimal seamline. In response, this paper proposes a segmentation-based optimal seamline generation (SOSG) method for SAR image mosaics. The SOSG method involves a multi-step process. First, SAR image joint segmentation is performed within the overlapping areas. Subsequently, homogeneous areas are identified based on the segmentation results. Following this, a pixel cost matrix is constructed, incorporating homogeneous areas and intensity differences. Finally, the minimum path cost from the starting pixel to the end pixel is computed using the Dijkstra algorithm to determine the optimal path. To assess the feasibility and effectiveness of the proposed method, experiments are conducted using multiple SAR images from the Chinese Gaofen-3 01 satellite as datasets. The experimental results demonstrate that the proposed method yields seamless mosaic images when compared to other methods, while delivering satisfactory outcomes. This indicates the potential of the proposed method in addressing the unique challenges posed by SAR images and enhancing the quality of SAR image mosaics.
MDSEA: Knowledge Graph Entity Alignment Based on Multimodal Data Supervision
Authors: Fang Jianyong , Yan Xuefeng
Published: April 2024

With the development of social media, the internet, and sensing technologies, multimodal data are becoming increasingly common. Integrating these data into knowledge graphs can help models to better understand and utilize these rich sources of information. The basic idea of the existing methods for entity alignment in knowledge graphs is to extract different data features, such as structure, text, attributes, images, etc., and then fuse these different modal features. The entity similarity in different knowledge graphs is calculated based on the fused features. However, the structures, attribute information, image information, text descriptions, etc., of different knowledge graphs often have significant differences. Directly integrating different modal information can easily introduce noise, thus affecting the effectiveness of the entity alignment. To address the above issues, this paper proposes a knowledge graph entity alignment method based on multimodal data supervision. First, Transformer is used to obtain encoded representations of knowledge graph entities. Then, a multimodal supervised method is used for learning the entity representations in the knowledge graph so that the vector representations of the entities contain rich multimodal semantic information, thereby enhancing the generalization ability of the learned entity representations. Finally, the information from different modalities is mapped to a shared low-dimensional subspace, making similar entities closer in the subspace, thus optimizing the entity alignment effect. The experiments on the DBP15K dataset compared with methods such as MTransE, JAPE, EVA, DNCN, etc., all achieve optimal results.
Reversible Contraception in Males: An Obtainable Target?
Authors: Koilpillai Joanna Nandita , Nunan Emily , Butler Landon , Pinaffi Fabio , Butcher Joshua T.
Published: April 2024

The last few decades have brought contraception to the forefront of research, with great strides made in effectively targeting and optimizing the physiology, pharmacology, and delivery processes that prevent pregnancy. However, these advances still predominantly target female contraceptives for the prevention of contraception, whereas targeting the male sex has lagged far behind. This has led to a marked deficiency in safe and effective male contraceptive agents, resulting in a heavy dependence on female contraceptives to prevent unwanted and unplanned pregnancies. Current research in the veterinary field and in rodents highlights several promising avenues whereby novel, safe, and effective male contraceptive alternatives are being developed—with an emphasis on reduced side effects and reversibility potential. This review aims to discuss current and novel male contraceptives (both human and veterinary formulations) while highlighting their efficacy, advantages, and disadvantages.
Remapping and Reconnecting the Language Network after Stroke
Authors: Tilton-Bolowsky Victoria , Stockbridge Melissa D. , Hillis Argye E.
Published: April 2024

Here, we review the literature on neurotypical individuals and individuals with post-stroke aphasia showing that right-hemisphere regions homologous to language network and other regions, like the right cerebellum, are activated in language tasks and support language even in healthy people. We propose that language recovery in post-stroke aphasia occurs largely by potentiating the right hemisphere network homologous to the language network and other networks that previously supported language to a lesser degree and by modulating connection strength between nodes of the right-hemisphere language network and undamaged nodes of the left-hemisphere language network. Based on this premise (supported by evidence we review), we propose that interventions should be aimed at potentiating the right-hemisphere language network through Hebbian learning or by augmenting connections between network nodes through neuroplasticity, such as non-invasive brain stimulation and perhaps modulation of neurotransmitters involved in neuroplasticity. We review aphasia treatment studies that have taken this approach. We conclude that further aphasia rehabilitation with this aim is justified.
Environmental Microvibration Analysis Method for Vibration Isolation Research in High-Precision Laboratories
Authors: Cheng Yang , Lu Kangyi , Huang Qiuju , Ding Feng , Song Chunyu
Published: April 2024

Environmental microvibrations, often originating from unidentified sources, pose a significant challenge for predicting and controlling their complex wave fields, potentially leading to measurement errors of sensitive instruments in high-precision laboratories and impacting the accuracy of experimental outcomes. Therefore, investigating effective control measures for environmental microvibrations under passive conditions is key to addressing such engineering issues. This paper presents a finite element analysis method tailored to address environmental microvibrations in the absence of apparent sources. This method involves obtaining the vibration time history at specific ground surface points through field measurements and combining the Rayleigh wave velocity attenuation character with depth at the center frequencies of one-third octave bands within the 1–100 Hz frequency range; the vibration time history at any depth in the soil is calculated. These calculated vibrations are then applied as input loads to the corresponding nodes on one boundary of the foundation–soil model, serving as the source of environmental microvibrations. The predicted results are compared with measured data and the empirical point source input method, indicating that this approach is more precise and efficient, providing valuable reference for the prediction and analysis of environmental microvibrations. In addition, utilizing this method, the study examines the effects of pile foundation parameters such as the pile length, burial depth, and concrete baseplate thickness on the vibration isolation performance of environmental microvibrations, providing guidance for designing pile foundation isolation.
Increasing the Utilization of Solar Energy through the Performance Evaluation of Air-Based Photovoltaic Thermal Systems
Authors: Choi Youngjin
Published: April 2024

Photovoltaic thermal (PVT) systems are attracting a significant amount of attention in research because they can generate electricity outside of daytime hours, unlike photovoltaic (PV) systems, and can increase efficiency and collect additional energy by reducing the temperature of PVT panels. However, a somewhat lower amount of collected energy is used in the summer than in the winter, and research on this issue is lacking. In this study, first, we experimentally evaluated the performance of PV and PVT systems by season and verified the improvement in the performance of the PVT system. Second, experiments were conducted to verify the enthalpy reduction via mist cooling and dehumidification, and the temperature and humidity control effect via mist cooling and dehumidification was verified. Based on our research findings, we propose a model that can be integrated with indoor ventilation systems to increase the solar energy utilization of PVT systems. Using the PVT system, we improved the panel power generation efficiency by up to 5.89% and generated up to a 38.0% higher collection efficiency than that of the PV system. The air that passed through the PVT system was then subjected to mist cooling and dehumidification to reduce its temperature and increase its humidity, resulting in a 23.2% reduction in enthalpy.
Detection and Real-Time Surgical Assessment of Colorectal Liver Metastases Using Near-Infrared Fluorescence Imaging during Laparoscopic and Robotic-Assisted Resections
Authors: Piccolo Gaetano , Barabino Matteo , Ghilardi Giorgio , Masserano Riccardo , Lecchi Francesca , Piozzi Guglielmo Niccolò , Bianchi Paolo Pietro
Published: April 2024

Background: The European Association of Endoscopic Surgery (EAES) recommends, with strong evidence, the use of indocyanine green (ICG) fluorescence imaging combined with intraoperative ultrasound (IOUS) to improve identification of superficial liver tumors. This study reports the use of ICG for the detection of colorectal liver metastases (CRLMs) during minimally invasive liver resection. Methods: A single-center consecutive series of minimally invasive (laparoscopic and robotic) hepatic resections for CRLMs was prospectively evaluated (April 2019 and October 2023). Results: A total of 25 patients were enrolled—11 undergoing laparoscopic and 14 undergoing robotic procedures. The median age was 65 (range 50–85) years. Fifty CRLMs were detected: twenty superficial, eight exophytic, seven shallow (<8 mm from the hepatic surface), and fifteen deep (>10 mm from the hepatic surface) lesions. The detection rates of CRLMs through preoperative imaging, laparoscopic ultrasound (LUS), ICG fluorescence, and combined modalities (ICG and LUS) were 88%, 90%, 68%, and 100%, respectively. ICG fluorescence staining allowed us to detect five small additional superficial lesions (not identified with other preoperative/intraoperative techniques). However, two lesions were false positive fluorescence accumulations. All rim fluorescence pattern lesions were CRLMs. ICG fluorescence was used as a real-time guide to assess surgical margins during parenchymal-sparing liver resections. All patients with integrity of the fluorescent rim around the CRLM displayed a radical resection during histopathological analysis. Four patients (8%) with a protruding rim or residual rim patterns had positive resection margins. Conclusions: ICG fluorescence imaging can be integrated with other conventional intraoperative imaging techniques to optimize intraoperative staging. Rim fluorescence proved to be a valid indicator of the resection margins: by removing the entire fluorescent area, a tumor-negative resection (R0) is achieved.
Prostate-Specific Membrane Antigen-Targeted Therapy in Prostate Cancer: History, Combination Therapies, Trials, and Future Perspective
Authors: Mattana Francesco , Muraglia Lorenzo , Barone Antonio , Colandrea Marzia , Saker Diffalah Yasmina , Provera Silvia , Cascio Alfio Severino , Omodeo Salè Emanuela , Ceci Francesco
Published: April 2024

In the last decades, the development of PET/CT radiopharmaceuticals, targeting the Prostate-Specific Membrane Antigen (PSMA), changed the management of prostate cancer (PCa) patients thanks to its higher diagnostic accuracy in comparison with conventional imaging both in staging and in recurrence. Alongside molecular imaging, PSMA was studied as a therapeutic agent targeted with various isotopes. In 2021, results from the VISION trial led to the Food and Drug Administration (FDA) approval of [177Lu]Lu-PSMA-617 as a novel therapy for metastatic castration-resistant prostate cancer (mCRPC) and set the basis for a radical change in the future perspectives of PCa treatment and the history of Nuclear Medicine. Despite these promising results, primary resistance in patients treated with single-agent [177Lu]Lu-PSMA-617 remains a real issue. Emerging trials are investigating the use of [177Lu]Lu-PSMA-617 in combination with other PCa therapies in order to cover the multiple oncologic resistance pathways and to overcome tumor heterogeneity. In this review, our aim is to retrace the history of PSMA-targeted therapy from the first preclinical studies to its future applications in PCa.
Clinical Prediction Models for Prognosis of Colorectal Liver Metastases: A Comprehensive Review of Regression-Based and Machine Learning Models
Authors: Kokkinakis Stamatios , Ziogas Ioannis A. , Llaque Salazar Jose D. , Moris Dimitrios P. , Tsoulfas Georgios
Published: April 2024

Colorectal liver metastasis (CRLM) is a disease entity that warrants special attention due to its high frequency and potential curability. Identification of “high-risk” patients is increasingly popular for risk stratification and personalization of the management pathway. Traditional regression-based methods have been used to derive prediction models for these patients, and lately, focus has shifted to artificial intelligence-based models, with employment of variable supervised and unsupervised techniques. Multiple endpoints, like overall survival (OS), disease-free survival (DFS) and development or recurrence of postoperative complications have all been used as outcomes in these studies. This review provides an extensive overview of available clinical prediction models focusing on the prognosis of CRLM and highlights the different predictor types incorporated in each model. An overview of the modelling strategies and the outcomes chosen is provided. Specific patient and treatment characteristics included in the models are discussed in detail. Model development and validation methods are presented and critically appraised, and model performance is assessed within a proposed framework.
Inter- and Intra-Patient Repeatability of Radiomic Features from Multiparametric Whole-Body MRI in Patients with Metastatic Prostate Cancer
Authors: Donners Ricardo , Candito Antonio , Rata Mihaela , Sharp Adam , Messiou Christina , Koh Dow-Mu , Tunariu Nina , Blackledge Matthew D.
Published: April 2024

(1) Background: We assessed the test–re-test repeatability of radiomics in metastatic castration-resistant prostate cancer (mCPRC) bone disease on whole-body diffusion-weighted (DWI) and T1-weighted Dixon MRI. (2) Methods: In 10 mCRPC patients, 1.5 T MRI, including DWI and T1-weighted gradient-echo Dixon sequences, was performed twice on the same day. Apparent diffusion coefficient (ADC) and relative fat-fraction-percentage (rFF%) maps were calculated. Per study, up to 10 target bone metastases were manually delineated on DWI and Dixon images. All 106 radiomic features included in the Pyradiomics toolbox were derived for each target volume from the ADC and rFF% maps. To account for inter- and intra-patient measurement repeatability, the log-transformed individual target measurements were fitted to a hierarchical model, represented as a Bayesian network. Repeatability measurements, including the intraclass correlation coefficient (ICC), were derived. Feature ICCs were compared with mean ADC and rFF ICCs. (3) Results: A total of 65 DWI and 47 rFF% targets were analysed. There was no significant bias for any features. Pairwise correlation revealed fifteen ADC and fourteen rFF% feature sub-groups, without specific patterns between feature classes. The median intra-patient ICC was generally higher than the inter-patient ICC. Features that describe extremes in voxel values (minimum, maximum, range, skewness, and kurtosis) showed generally lower ICCs. Several mostly shape-based texture features were identified, which showed high inter- and intra-patient ICCs when compared with the mean ADC or mean rFF%, respectively. (4) Conclusions: Pyradiomics texture features of mCRPC bone metastases varied greatly in inter- and intra-patient repeatability. Several features demonstrated good repeatability, allowing for further exploration as diagnostic parameters in mCRPC bone disease.
Therapeutic Targeting of DNA Repair Pathways in Pediatric Extracranial Solid Tumors: Current State and Implications for Immunotherapy
Authors: Zhao Sophia J. , Prior Daniel , Heske Christine M. , Vasquez Juan C.
Published: April 2024

DNA damage is fundamental to tumorigenesis, and the inability to repair DNA damage is a hallmark of many human cancers. DNA is repaired via the DNA damage repair (DDR) apparatus, which includes five major pathways. DDR deficiencies in cancers give rise to potential therapeutic targets, as cancers harboring DDR deficiencies become increasingly dependent on alternative DDR pathways for survival. In this review, we summarize the DDR apparatus, and examine the current state of research efforts focused on identifying vulnerabilities in DDR pathways that can be therapeutically exploited in pediatric extracranial solid tumors. We assess the potential for synergistic combinations of different DDR inhibitors as well as combinations of DDR inhibitors with chemotherapy. Lastly, we discuss the immunomodulatory implications of targeting DDR pathways and the potential for using DDR inhibitors to enhance tumor immunogenicity, with the goal of improving the response to immune checkpoint blockade in pediatric solid tumors. We review the ongoing and future research into DDR in pediatric tumors and the subsequent pediatric clinical trials that will be critical to further elucidate the efficacy of the approaches targeting DDR.
Real-World Treatment Patterns and Survival Outcomes for Patients with Non-Metastatic Non-Small-Cell Lung Cancer in Sweden: A Nationwide Registry Analysis from the I-O Optimise Initiative
Authors: Oskarsdottir Gudrun N. , Lampa Erik , Berglund Anders , Rosengren Linda , Ulvestad Maria , Boros Miklos , Daumont Melinda J. , Rault Caroline , Emanuel Gabrielle , Leal Cátia , Schoemaker Minouk J. , Wagenius Gunnar
Published: April 2024

Non-small-cell lung cancer (NSCLC) is the leading cause of cancer-related death worldwide, with ~40–50% of patients diagnosed with non-metastatic disease (stages IA–IIIC). The treatment landscape is evolving rapidly as immunotherapies and targeted therapy are introduced in the non-metastatic setting, creating a need to assess patient outcomes prior to their introduction. This real-world study using Swedish National Lung Cancer Registry data examined outcomes (overall survival (OS) and time to next treatment or death (TTNTD)) and treatment patterns for adults diagnosed with non-metastatic NSCLC. Baseline characteristics and OS from diagnosis were described for all patients; OS, treatment patterns, and TTNTD from treatment start were described for the treatment subgroup (patients diagnosed from 2014 onwards), stratified by disease stage and initial treatment. OS and TTNTD were described using the Kaplan–Meier estimator. The overall population (2008–2019) included 17,433 patients; the treatment subgroup included 5147 patients. Median OS (interquartile range) overall ranged from 83.3 (31.6–165.3) months (stage I patients) to 10.4 (4.3–24.2) months (stage IIIB patients). Among the treatment subgroup, median OS and TTNTD were longest among patients receiving surgery versus other anticancer treatments. These findings provide a baseline upon which to evaluate the epidemiology of non-metastatic NSCLC as newer treatments are introduced.
Gastric Inhibitory Polypeptide Receptor (GIPR) Overexpression Reduces the Tumorigenic Potential of Retinoblastoma Cells
Authors: Haase André , Alefeld Emily , Yalinci Fatma , Meenen Dario Van , Busch Maike Anna , Dünker Nicole
Published: April 2024

Retinoblastoma (RB) is the most common malignant intraocular tumor in early childhood. Gene expression profiling revealed that the gastric inhibitory polypeptide receptor (GIPR) is upregulated following trefoil factor family peptide 1 (TFF1) overexpression in RB cells. In the study presented, we found this G protein-coupled transmembrane receptor to be co-expressed with TFF1, a new diagnostic and prognostic RB biomarker for advanced subtype 2 RBs. Functional analyses in two RB cell lines revealed a significant reduction in cell viability and growth and a concomitant increase in apoptosis following stable, lentiviral GIPR overexpression, matching the effects seen after TFF1 overexpression. In chicken chorioallantoic membrane (CAM) assays, GIPR-overexpressing RB cells developed significantly smaller CAM tumors. The effect of GIPR overexpression in RB cells was reversed by the GIPR inhibitor MK0893. The administration of recombinant TFF1 did not augment GIPR overexpression effects, suggesting that GIPR does not serve as a TFF1 receptor. Investigations of potential GIPR up- and downstream mediators suggest the involvement of miR-542-5p and p53 in GIPR signaling. Our results indicate a tumor suppressor role of GIPR in RB, suggesting its pathway as a new potential target for future retinoblastoma therapy.
Endoscopic Contrast-Enhanced Ultrasound and Fine-Needle Aspiration or Biopsy for the Diagnosis of Pancreatic Solid Lesions: A Systematic Review and Meta-Analysis
Authors: Esposto Giorgio , Massimiani Giuseppe , Galasso Linda , Santini Paolo , Borriello Raffaele , Mignini Irene , Ainora Maria Elena , Nicoletti Alberto , Zileri Dal Verme Lorenzo , Gasbarrini Antonio , Alfieri Sergio , Quero Giuseppe , Zocco Maria Assunta
Published: April 2024

Introduction: Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) and endoscopic ultrasound-guided fine-needle biopsy (EUS-FNB) are currently recommended for the pathologic diagnosis of pancreatic solid lesions (PSLs). The application of contrast-enhanced endoscopic ultrasound (ECEUS) could aid the endoscopist during an FNA and/or FNB procedure. CEUS is indeed able to better differentiate the pathologic tissue from the surrounding healthy pancreatic parenchyma and to detect necrotic areas and vessels. Objectives: Our objective was to evaluate if ECEUS could reduce the number of needle passes and side effects and increase the diagnostic efficacy of FNA and/or FNB. Methods: A comprehensive literature search of clinical studies was performed to explore if ECEUS-FNA or FNB could increase diagnostic accuracy and reduce the number of needle passes and adverse effects compared to standard EUS-FNA or FNB. In accordance with the study protocol, a qualitative and quantitative analysis of the evidence was planned. Results: The proportion of established diagnoses of ECEUS was 90.9% compared to 88.3% of EUS, with no statistically significant difference (p = 0.14). The diagnosis was made through a single step in 70.9% of ECEUS patients and in 65.3% of EUS patients, without statistical significance (p = 0.24). The incidence of adverse reactions was substantially comparable across both groups (p = 0.89). Conclusion: ECEUS-FNA and FNB do not appear superior to standard EUS-FNA and FNB for the diagnosis of pancreatic lesions.
A Combined Cyto- and Histopathological Diagnostic Approach Reduces Time to Diagnosis and Time to Therapy in First Manifestation of Metastatic Spinal Disease: A Cohort Study
Authors: Leonhardt Leon-Gordian , Heuer Annika , Stangenberg Martin , Schroeder Malte , Schmidt Gabriel , Welker Lutz , von Amsberg Gunhild , Strahl André , Krüger Lara , Dreimann Marc , Bokemeyer Carsten , Viezens Lennart , Asemissen Anne Marie
Published: April 2024

Malignant spinal lesions (MSLs) are frequently the first manifestation of malignant disease. Spinal care, diagnostic evaluation, and the initiation of systemic therapy are crucial for outcomes in patients (pts) with advanced cancer. However, histopathology (HP) may be time consuming. The additional evaluation of spinal lesions using cytopathology (CP) has the potential to reduce the time to diagnosis (TTD) and time to therapy (TTT). CP and HP specimens from spinal lesions were evaluated in parallel in 61 pts (CP/HP group). Furthermore, 139 pts in whom only HP was performed were analyzed (HP group). We analyzed the TTD of CP and HP within the CP/HP group. Furthermore, we compared the TTD and TTT between the groups. The mean TTD in CP was 1.7 ± 1.7 days (d) and 8.4 ± 3.6 d in HP (p < 0.001). In 13 pts in the CP/HP group (24.1%), specific therapy was initiated based on the CP findings in combination with imaging and biomarker results before completion of HP. The mean TTT in the CP/HP group was 21.0 ± 15.8 d and was significantly shorter compared to the HP group (28.6 ± 23.3 d) (p = 0.034). Concurrent CP for MSLs significantly reduces the TTD and TTT. As a result, incorporating concurrent CP for analyzing spinal lesions suspected of malignancy might have the potential to enhance pts’ quality of life and prognosis in advanced cancer. Therefore, we recommend implementing CP as a standard procedure for the evaluation of MSLs.
One-Step Production of Highly Selective Ethylbenzene and Propylbenzene from Benzene and Carbon Dioxide via Coupling Reaction
Authors: Wang Tianyun , Guan Yingjie , Wu Haidan , Su Zhaojie , Zhuang Jianguo , Yan Siyan , Zhu Xuedong , Yang Fan
Published: April 2024

Utilizing carbon dioxide as a carbon source for the synthesis of olefins and aromatics has emerged as one of the most practical methods for CO2 reduction. In this study, an improved selectivity of 85% for targeting products (ethylbenzene and propylbenzene) is achieved with a benzene conversion of 16.8% by coupling the hydrogenation of carbon dioxide to olefins over the bifunctional catalyst “Oxide-Zeolite” (OX-ZEO) and the alkylation of benzene with olefins over ZSM-5. In addition to investigating the influence of SAPO-34 and ZSM-5 zeolite acidity on product distribution, catalyst deactivation due to coke formation is addressed by modifying both molecular sieves to be hierarchical to extend the catalyst lifespan. Even after 100 h of operation at 400 °C, the catalysts maintained over 80% selectivity towards the target products, with benzene conversion over 14.2%. Furthermore, the pathway of propylbenzene formation is demonstrated through simple experimental design, revealing that the surface Brønsted acid sites of SAPO-34 serve as its primary formation sites. This provides a novel perspective for further investigation of the reaction network.
CO2 Promoting Polymorphic Transformation of Clarithromycin: Polymorph Characterization, Pathway Design, and Mechanism Study
Authors: Hou Lixin , Jing Dingding , Wang Yanfeng , Bao Ying
Published: April 2024

Carbon dioxide (CO2) has a wide range of uses such as food additives and raw materials for synthetic chemicals, while its application in the solid-state transformation of pharmaceutical crystals is rare. In this work, we report a case of using 1 atm CO2 as an accelerator to promote the polymorphic transformation of clarithromycin (CLA). Initially, crystal structures of Form 0′ and three solvates were successfully determined by single crystal X-ray diffraction (SCXRD) analysis for the first time and found to be isomorphous. Powder X-ray diffraction (PXRD) and thermal analysis indicated that the solvate desolvates and transforms into the structurally similar non-solvated Form 0′ at room temperature to ~50 °C. Form 0′ and Form II are monotropically related polymorphs with Form II being the most stable. Subsequently, the effect of CO2 on the transformation of CLA solvates to Form II was studied. The results show that CO2 can significantly facilitate the transformation of Form 0′ to Form II, despite no significant effect on the desolvation process. Finally, the molecular mechanism of CO2 promoting the polymorphic transformation was revealed by the combination of the measurement of adsorption capacity, theoretical calculations as well as crystal structure analysis. Based on the above results, a new pathway of preparing CLA Form II was designed: transform CLA solvates into Form 0′ in 1 atm air at 50 °C followed by the transformation of Form 0′ to Form II in 1 atm CO2 at 50 °C. This work provides a new idea for promoting the phase transformation of pharmaceutical crystals as well as a new scenario for the utilization of CO2.
Sensorless Speed Estimation of Induction Motors through Signal Analysis Based on Chaos Using Density of Maxima
Authors: Silva Marlio Antonio , Lucena-Junior Jose Anselmo , da Silva Julio Cesar , Belo Francisco Antonio , Lima-Filho Abel Cavalcante , Ramos Jorge Gabriel Gomes de Souza , Camara Romulo , Brito Alisson
Published: April 2024

Three-phase induction motors are widely used in various industrial sectors and are responsible for a significant portion of the total electrical energy consumed. To ensure their efficient operation, it is necessary to apply control systems with specific algorithms able to estimate rotation speed accurately and with an adequate response time. However, the angular speed sensors used in induction motors are generally expensive and unreliable, and they may be unsuitable for use in hostile environments. This paper presents an algorithm for speed estimation in three-phase induction motors using the chaotic variable of maximum density. The technique used in this work analyzes the current signals from the motor power supply without invasive sensors on its structure. The results show that speed estimation is achieved with a response time lower than that obtained by classical techniques based on the Fourier Transform. This technique allows for the provision of motor shaft speed values when operated under variable load.
Exploring the Effects of Teachers’ Practices in the Early Childhood Literacy Classroom Environment on Children’s Acquisition of Literacy Skills
Authors: Alsubaie Merfat Ayesh
Published: April 2024

The primary focus of this study is to explore the relationship between the early childhood literacy classroom environment and teachers’ practices to promote an understanding of their influence on Arabic-speaking children’s acquisition of literacy skills. This study utilizes a quantitative methodological approach, whereby null and alternative hypotheses were formulated to examine the association between Arabic-speaking children’s acquisition of literacy skills and the early childhood literacy classroom environment. Data analysis was conducted using a statistical technique known as structural equation modeling. The results of this study indicate that the literacy classroom environment, teachers’ practices, and Arabic-speaking children’s acquisition of literacy skills affect each other and have an evidence-based interrelationship. Based on this relationship, the results and recommendations of this study may be considered inspirational ideas for teachers, researchers, and decision-makers working in early childhood who seek to make positive educational changes in this field.
Enhancing ICT Literacy and Achievement: A TPACK-Based Blended Learning Model for Thai Business Administration Students
Authors: Nantha Cherisa , Siripongdee Kobchai , Siripongdee Surapong , Pimdee Paitoon , Kantathanawat Thiyaporn , Boonsomchuae Kanitphan
Published: April 2024

The COVID-19 pandemic has heightened the need for 21st century skills, particularly computer and ICT literacy (CICT) in Thailand. This study aimed to develop a TPACK (Technological Pedagogical and Content Knowledge)-based blended learning model (BLM) to enhance CICT skills and academic performance among 179 Business Administration (BA) undergraduates in the 2022 academic year Computer and Information Applications course. Research instruments were designed and evaluated by experts. Over 18 weeks, qualitative and quantitative data were collected, with the qualitative data undergoing content analysis. Descriptive statistics were used to analyze quantitative data, comparing pretests, post-tests, and 2-week retests using a repeated measure ANOVA. One-sample t-tests were used to assess the model’s impact on CICT skills. The results showed a significant score improvement between tests, with the highest mean being seen in the 2-week retest. The BA-TPACK model significantly enhanced CICT skills, exceeding 80%. The students expressed high satisfaction, with the BA-TPACK model effectively enhancing CICT skills and academic achievement, recommending its integration into future computer and information courses. This study’s contribution lies in addressing the pressing need for CICT skills in the ‘new normal’. By developing and implementing a BLM grounded in the TPACK framework, this study not only enhances students’ CICT proficiency but also fills a crucial gap in the literature regarding effective pedagogical approaches to foster 21st century skills.
AI-Driven Refactoring: A Pipeline for Identifying and Correcting Data Clumps in Git Repositories
Authors: Baumgartner Nils , Iyenghar Padma , Schoemaker Timo , Pulvermüller Elke
Published: April 2024

Data clumps, groups of variables that repeatedly appear together across different parts of a software system, are indicative of poor code structure and can lead to potential issues such as maintenance challenges, testing complexity, and scalability concerns, among others. Addressing this, our study introduces an innovative AI-driven pipeline specifically designed for the refactoring of data clumps in software repositories. This pipeline leverages the capabilities of Large Language Models (LLM), such as ChatGPT, to automate the detection and resolution of data clumps, thereby enhancing code quality and maintainability. In developing this pipeline, we have taken into consideration the new European Union (EU)-Artificial Intelligence (AI) Act, ensuring that our pipeline complies with the latest regulatory requirements and ethical standards for use of AI in software development by outsourcing decisions to a human in the loop. Preliminary experiments utilizing ChatGPT were conducted to validate the effectiveness and efficiency of our approach. These tests demonstrate promising results in identifying and refactoring data clumps, but also the challenges using LLMs.
Design and Evaluation of CPU-, GPU-, and FPGA-Based Deployment of a CNN for Motor Imagery Classification in Brain-Computer Interfaces
Authors: Pacini Federico , Pacini Tommaso , Lai Giuseppe , Zocco Alessandro Michele , Fanucci Luca
Published: April 2024

Brain–computer interfaces (BCIs) have gained popularity in recent years. Among noninvasive BCIs, EEG-based systems stand out as the primary approach, utilizing the motor imagery (MI) paradigm to discern movement intentions. Initially, BCIs were predominantly focused on nonembedded systems. However, there is now a growing momentum towards shifting computation to the edge, offering advantages such as enhanced privacy, reduced transmission bandwidth, and real-time responsiveness. Despite this trend, achieving the desired target remains a work in progress. To illustrate the feasibility of this shift and quantify the potential benefits, this paper presents a comparison of deploying a CNN for MI classification across different computing platforms, namely, CPU-, embedded GPU-, and FPGA-based. For our case study, we utilized data from 29 participants included in a dataset acquired using an EEG cap for training the models. The FPGA solution emerged as the most efficient in terms of the power consumption–inference time product. Specifically, it delivers an impressive reduction of up to 89% in power consumption compared to the CPU and 71% compared to the GPU and up to a 98% reduction in memory footprint for model inference, albeit at the cost of a 39% increase in inference time compared to the GPU. Both the embedded GPU and FPGA outperform the CPU in terms of inference time.
Static Equivalence Method of Power Grid Based on Genetic Algorithm
Authors: Jiang Xiaofeng , Pan Pengyu , Wang Hao , Liu Lei , Chen Gang , Wang Xi , Han Xiaoyan
Published: April 2024

When the electromagnetic transient simulation of a large-scale power grid is carried out, because the simulation is limited by the scale of simulation software, it is necessary to divide the grid into internal and external grids, and the external grid is modeled with equivalent simplification. Aiming at resolving the difficulties of the traditional grid equivalence method, such as a cumbersome calculation process and harsh calculation conditions, a static grid equivalence method based on the genetic algorithm is proposed in this paper. The method first constructs an external grid equivalence network, which includes coupling branches between boundary nodes, and each boundary node is connected to the external grid equivalence power supply through the branches. Then, the external grid equivalence model is used to establish an optimization model for solving the equivalence network parameters based on the information of the internal network, the difference of the power input from the external grid to the boundary nodes before and after equivalence is used as the objective function, and the genetic algorithm is used to realize the iterative optimization of the objective function to obtain a set of optimal post-equivalence network model parameters so that the state variables of the internal power grid before and after the equivalence are matched. The accuracy and effectiveness of the proposed method are verified through simulation with the CERPI36V7 node system.
Adaptive Comfort Potential in Different Climate Zones of Ecuador Considering Global Warming
Authors: Delgado-Gutierrez Evelyn , Canivell Jacinto , Bienvenido-Huertas David , Hidalgo-Sánchez Francisco M.
Published: April 2024

Ecuador is a country with several climate zones. However, their behaviour is similar throughout the year, with no peaks of extreme temperatures in the various seasons. This paper is a first approach to study the adaptive comfort behaviour in several areas and populations of the country. Considering the ASHRAE 55-2020 model, energy simulation programmes are applied not just to the current climate scenario but also to the climate change scenarios of 2050 and 2100. The results of locations are analysed and compared to determine their performance. Thanks to their climate characteristics, adaptive comfort models could be applied as a passive strategy, using natural ventilation for building indoor comfort improvement, particularly social dwellings. According to previous studies, some prototypes have not considered the climate determinants in each region. Given the geographic situation of the study areas, the adaptive comfort model could be applied in all cases. Percentages of application of natural ventilation and heating and cooling degree hours have similar behaviours according to the climatic region, with a variation greater than 30% among them.