bluuebunny/crossref_metadata_2025 huggingface dataset:
A Neural Topic Modeling Study Integrating SBERT and Data Augmentation
Authors: Cheng Huaqing , Liu Shengquan , Sun Weiwei , Sun Qi
Published: April 2023

Topic models can extract consistent themes from large corpora for research purposes. In recent years, the combination of pretrained language models and neural topic models has gained attention among scholars. However, this approach has some drawbacks: in short texts, the quality of the topics obtained by the models is low and incoherent, which is caused by the reduced word frequency (insufficient word co-occurrence) in short texts compared to long texts. To address these issues, we propose a neural topic model based on SBERT and data augmentation. First, our proposed easy data augmentation (EDA) method with keyword combination helps overcome the sparsity problem in short texts. Then, the attention mechanism is used to focus on keywords related to the topic and reduce the impact of noise words. Next, the SBERT model is trained on a large and diverse dataset, which can generate high-quality semantic information vectors for short texts. Finally, we perform feature fusion on the augmented data that have been weighted by an attention mechanism with the high-quality semantic information obtained. Then, the fused features are input into a neural topic model to obtain high-quality topics. The experimental results on an English public dataset show that our model generates high-quality topics, with the average scores improving by 2.5% for topic coherence and 1.2% for topic diversity compared to the baseline model.
Convolutional Neural Network-Based Automated System for Dog Tracking and Emotion Recognition in Video Surveillance
Authors: Chen Huan-Yu , Lin Chuen-Horng , Lai Jyun-Wei , Chan Yung-Kuan
Published: April 2023

This paper proposes a multi–convolutional neural network (CNN)-based system for the detection, tracking, and recognition of the emotions of dogs in surveillance videos. This system detects dogs in each frame of a video, tracks the dogs in the video, and recognizes the dogs’ emotions. The system uses a YOLOv3 model for dog detection. The dogs are tracked in real time with a deep association metric model (DeepDogTrack), which uses a Kalman filter combined with a CNN for processing. Thereafter, the dogs’ emotional behaviors are categorized into three types—angry (or aggressive), happy (or excited), and neutral (or general) behaviors—on the basis of manual judgments made by veterinary experts and custom dog breeders. The system extracts sub-images from videos of dogs, determines whether the images are sufficient to recognize the dogs’ emotions, and uses the long short-term deep features of dog memory networks model (LDFDMN) to identify the dog’s emotions. The dog detection experiments were conducted using two image datasets to verify the model’s effectiveness, and the detection accuracy rates were 97.59% and 94.62%, respectively. Detection errors occurred when the dog’s facial features were obscured, when the dog was of a special breed, when the dog’s body was covered, or when the dog region was incomplete. The dog-tracking experiments were conducted using three video datasets, each containing one or more dogs. The highest tracking accuracy rate (93.02%) was achieved when only one dog was in the video, and the highest tracking rate achieved for a video containing multiple dogs was 86.45%. Tracking errors occurred when the region covered by a dog’s body increased as the dog entered or left the screen, resulting in tracking loss. The dog emotion recognition experiments were conducted using two video datasets. The emotion recognition accuracy rates were 81.73% and 76.02%, respectively. Recognition errors occurred when the background of the image was removed, resulting in the dog region being unclear and the incorrect emotion being recognized. Of the three emotions, anger was the most prominently represented; therefore, the recognition rates for angry emotions were higher than those for happy or neutral emotions. Emotion recognition errors occurred when the dog’s movements were too subtle or too fast, the image was blurred, the shooting angle was suboptimal, or the video resolution was too low. Nevertheless, the current experiments revealed that the proposed system can correctly recognize the emotions of dogs in videos. The accuracy of the proposed system can be dramatically increased by using more images and videos for training the detection, tracking, and emotional recognition models. The system can then be applied in real-world situations to assist in the early identification of dogs that may exhibit aggressive behavior.
Addressing the Algorithm Selection Problem through an Attention-Based Meta-Learner Approach
Authors: Díaz de León-Hicks Enrique , Conant-Pablos Santiago Enrique , Ortiz-Bayliss José Carlos , Terashima-Marín Hugo
Published: April 2023

In the algorithm selection problem, where the task is to identify the most suitable solving technique for a particular situation, most methods used as performance mapping mechanisms have been relatively simple models such as logistic regression or neural networks. In the latter case, most implementations tend to have a shallow and straightforward architecture and, thus, exhibit a limited ability to extract relevant patterns. This research explores the use of attention-based neural networks as meta-learners to improve the performance mapping mechanism in the algorithm selection problem and fully take advantage of the model’s capabilities for pattern extraction. We compare the proposed use of an attention-based meta-learner method as a performance mapping mechanism against five models from the literature: multi-layer perceptron, k-nearest neighbors, softmax regression, support vector machines, and decision trees. We used a meta-data dataset obtained by solving the vehicle routing problem with time window (VRPTW) instances contained in the Solomon benchmark with three different configurations of the simulated annealing meta-heuristic for testing purposes. Overall, the attention-based meta-learner model yields better results when compared to the other benchmark methods in consistently selecting the algorithm that best solves a given VRPTW instance. Moreover, by significantly outperforming the multi-layer perceptron, our findings suggest promising potential in exploring more recent and novel advancements in neural network architectures.
Mechanics of Particle Motion in a Standing Wave Electric Curtain: A Numerical Study
Authors: Bechkoura Hana , Zouzou Noureddine , Kachi Miloud
Published: April 2023

Electrostatic curtains can be simple and yet efficient devices to manipulate micronized particles on flat surfaces. This paper aims to investigate the motion of a 60 µm dielectric particle on the surface of a standing-wave conveyor. The study is based on a numerical model that accounts for the many forces that could potentially influence the particle motion. For that purpose, a numerical calculation of electric field and particle movement was carried out. The particle position above the curtain surface is obtained by a resolution of the dynamic equations using the Runge–Kutta method. The electric field distribution in the space above the curtain is obtained by a finite element calculation of the Laplace equation. The simulation results demonstrated a net dependence of the particle trajectory and movement modes on applied voltage frequency. Overall, low frequencies, typically below 50 Hz, allow for higher levitation and better displacement of the particle over long distances. Conversely, higher frequencies significantly reduce levitation and displacement distance. Moreover, at higher frequencies (around 500 Hz), the particle can vibrate between electrodes without any displacement at all. It is then inferred that low frequency is needed to better carry particles using a standing-wave curtain.
Structural Basis of the Interaction between Human Axin2 and SIAH1 in the Wnt/β-Catenin Signaling Pathway
Authors: Chen Lianqi , Liu Yan-Ping , Tian Li-Fei , Li Mingzhou , Yang Shuyu , Wang Song , Xu Wenqing , Yan Xiao-Xue
Published: April 2023

The scaffolding protein Axin is an important regulator of the Wnt signaling pathway, and its dysfunction is closely related to carcinogenesis. Axin could affect the assembly and dissociation of the β-catenin destruction complex. It can be regulated by phosphorylation, poly-ADP-ribosylation, and ubiquitination. The E3 ubiquitin ligase SIAH1 participates in the Wnt pathway by targeting various components for degradation. SIAH1 is also implicated in the regulation of Axin2 degradation, but the specific mechanism remains unclear. Here, we verified that the Axin2-GSK3 binding domain (GBD) was sufficient for SIAH1 binding by the GST pull-down assay. Our crystal structure of the Axin2/SIAH1 complex at 2.53 Å resolution reveals that one Axin2 molecule binds to one SIAH1 molecule via its GBD. These interactions critically depend on a highly conserved peptide 361EMTPVEPA368 within the Axin2-GBD, which forms a loop and binds to a deep groove formed by β1, β2, and β3 of SIAH1 by the N-terminal hydrophilic amino acids Arg361 and Thr363 and the C-terminal VxP motif. The novel binding mode indicates a promising drug-binding site for regulating Wnt/β-catenin signaling.
Mass Spectrometry-Based Proteomic Profiling of a Silvaner White Wine
Authors: Albuquerque Wendell , Ghezellou Parviz , Seidel Leif , Burkert Johannes , Will Frank , Schweiggert Ralf , Spengler Bernhard , Zorn Holger , Gand Martin
Published: April 2023

The comprehensive identification of the proteome content from a white wine (cv. Silvaner) is described here for the first time. The wine protein composition isolated from a representative wine sample (250 L) was identified via mass spectrometry (MS)-based proteomics following in-solution and in-gel digestion methods after being submitted to size exclusion chromatographic (SEC) fractionation to gain a comprehensive insight into proteins that survive the vinification processes. In total, we identified 154 characterized (with described functional information) or so far uncharacterized proteins, mainly from Vitis vinifera L. and Saccharomyces cerevisiae. With the complementarity of the two-step purification, the digestion techniques and the high-resolution (HR)-MS analyses provided a high-score identification of proteins from low to high abundance. These proteins can be valuable for future authentication of wines by tracing proteins derived from a specific cultivar or winemaking process. The proteomics approach presented herein may also be generally helpful to understand which proteins are important for the organoleptic properties and stability of wines.
“Shadow of a Doubt”—The Pathogenic Role of Endometrial Defects in Endometriosis Development and Endometriosis-Associated Infertility: Robust Demonstration of Clinical Relevance Is Still Urgently Needed
Authors: Viganò Paola , Casalechi Maíra , Vercellini Paolo , Somigliana Edgardo
Published: April 2023

Endometriosis is an estrogen-dependent chronic inflammatory disease characterized by the presence of endometrial glands and stroma associated with fibrosis outside the uterine cavity [...]
A Longitudinal Assessment of Substance Use Treatment during the COVID-19 Pandemic Using Staff and Service Data
Authors: Carlyle Molly , Newland Grace , Morris Leith , Ellem Rhiannon , Tisdale Calvert , Quinn Catherine A. , Hides Leanne
Published: April 2023

Introduction: Alcohol and other drug (AOD) treatment services were required to rapidly adapt delivery of care in response to the coronavirus (COVID-19) pandemic. This study examined longitudinal changes in the delivery of AOD counselling in Australia over 21 months (October 2019–July 2021) before and throughout the pandemic, using both staff self-report and service data. Methods: Treatment staff from a large AOD service in Queensland, Australia provided self-report data on time spent delivering counselling via face-to-face, outreach (home visits), telephone, and virtual (video) formats. Two waves of online questionnaires were collected, with staff reporting on their time before the pandemic (retrospectively for October 2019–February 2020); during the first lockdown period (retrospectively for March–May 2020); when restrictions were initially eased (June–September 2020); and one year later (July 2021). Service records of the number of counselling episodes conducted by each treatment modality were extracted between October 2019 and July 2021, and analysed by month. Results: Staff (n = 117) and service records indicated an increase in telephone-delivered AOD counselling during the first lockdown, alongside an increase in total counselling records. Telephone-delivered counselling was still significantly higher one year later. Face-to-face counselling declined after the onset of the pandemic, but increased quickly when restrictions were eased. Outreach counselling decreased during the first lockdown. Virtual counselling remained negligible throughout. Conclusion: AOD treatment services quickly utilised telephone counselling options at the start of the pandemic, and demonstrated continued utilisation of this method one year later. Increased virtual (video) counselling was not observed and may be due to limited infrastructure, staff training, and clients lacking Internet connectivity or technology required.
Association between Immunophenotypic Parameters and Molecular Alterations in Acute Myeloid Leukemia
Authors: Pessoa Flávia Melo Cunha de Pinho , Machado Caio Bezerra , Barreto Igor Valentim , Sampaio Giulia Freire , Oliveira Deivide de Sousa , Ribeiro Rodrigo Monteiro , Lopes Germison Silva , de Moraes Maria Elisabete Amaral , de Moraes Filho Manoel Odorico , de Souza Lucas Eduardo Botelho , Khayat André Salim , Moreira-Nunes Caroline Aquino
Published: April 2023

Acute myeloid leukemia (AML) is a hematologic malignancy that occurs due to alterations such as genetic mutations, chromosomal translocations, or changes in molecular levels. These alterations can accumulate in stem cells and hematopoietic progenitors, leading to the development of AML, which has a prevalence of 80% of acute leukemias in the adult population. Recurrent cytogenetic abnormalities, in addition to mediating leukemogenesis onset, participate in its evolution and can be used as established diagnostic and prognostic markers. Most of these mutations confer resistance to the traditionally used treatments and, therefore, the aberrant protein products are also considered therapeutic targets. The surface antigens of a cell are characterized through immunophenotyping, which has the ability to identify and differentiate the degrees of maturation and the lineage of the target cell, whether benign or malignant. With this, we seek to establish a relationship according to the molecular aberrations and immunophenotypic alterations that cells with AML present.
Development of a Novel Anti-CD44 Variant 7/8 Monoclonal Antibody, C44Mab-34, for Multiple Applications against Oral Carcinomas
Authors: Suzuki Hiroyuki , Ozawa Kazuki , Tanaka Tomohiro , Kaneko Mika K. , Kato Yukinari
Published: April 2023

Cluster of differentiation 44 (CD44) has been investigated as a cancer stem cell (CSC) marker as it plays critical roles in tumor malignant progression. The splicing variants are overexpressed in many carcinomas, especially squamous cell carcinomas, and play critical roles in the promotion of tumor metastasis, the acquisition of CSC properties, and resistance to treatments. Therefore, each CD44 variant (CD44v) function and distribution in carcinomas should be clarified for the establishment of novel tumor diagnosis and therapy. In this study, we immunized mouse with a CD44 variant (CD44v3–10) ectodomain and established various anti-CD44 monoclonal antibodies (mAbs). One of the established clones (C44Mab-34; IgG1, kappa) recognized a peptide that covers both variant 7- and variant 8-encoded regions, indicating that C44Mab-34 is a specific mAb for CD44v7/8. Moreover, C44Mab-34 reacted with CD44v3–10-overexpressed Chinese hamster ovary-K1 (CHO) cells or the oral squamous cell carcinoma (OSCC) cell line (HSC-3) by flow cytometry. The apparent KD of C44Mab-34 for CHO/CD44v3–10 and HSC-3 was 1.4 × 10−9 and 3.2 × 10−9 M, respectively. C44Mab-34 could detect CD44v3–10 in Western blotting and stained the formalin-fixed paraffin-embedded OSCC in immunohistochemistry. These results indicate that C44Mab-34 is useful for detecting CD44v7/8 in various applications and is expected to be useful in the application of OSCC diagnosis and therapy.
Life Cycle Assessment of a Sustainable Prefabricated Housing System: A Cradle-to-Site Approach Based on a Small-Scale Experimental Model
Authors: Chippagiri Ravijanya , Biswal Divyajyoti , Mandavgane Sachin , Bras Ana , Ralegaonkar Rahul
Published: April 2023

India is in need of rapid construction technology with sustainability and environmentally friendly aspects. Prefabrication is a well-known technique that lowers carbon emissions and reduces environmental impacts. Life cycle assessment (LCA) evaluates these impacts of developed product/process. A new-age construction product was designed from a locally available agro-industrial waste called co-fired ash (CFA). Expanded polystyrene beads, fly ash, and crushed sand were also used in designing lightweight (LW) sustainable prefabricated panels. The effect of incorporating sustainable alternates into the mix designs is to be studied. An experimental small-scale model house was erected and LCA for the same was carried out with cradle-to-site approach. Based on the inventory, the environmental impact was assessed for four different indicators: acidification potential (AP), eutrophication potential (EP), global warming potential (GWP), and ozone depletion potential (ODP) were evaluated. Carbon emissions of the respective CFA-based concrete and LW prefabricated mix were found to be 0.162 kgCO2e/kg and 0.268 kgCO2e/kg, respectively. The impact of energy required during production, transport, and indirect emissions were found to contribute 3%, 3%, and 94%, respectively, to the proposed prefabricated system. Comprehensively, the phase involving mixing of LW mix contributed majorly towards all the impact indicators followed by mould preparation and material transport. The presented data helps the academia to quantify and recognise the possibilities to enhance their products’ performance.
miR-146a-5p Promotes Angiogenesis and Confers Trastuzumab Resistance in HER2+ Breast Cancer
Authors: Cabello Paula , Torres-Ruiz Sandra , Adam-Artigues Anna , Forés-Martos Jaume , Martínez María Teresa , Hernando Cristina , Zazo Sandra , Madoz-Gúrpide Juan , Rovira Ana , Burgués Octavio , Rojo Federico , Albanell Joan , Lluch Ana , Bermejo Begoña , Cejalvo Juan Miguel , Eroles Pilar
Published: April 2023

Trastuzumab treatment has significantly improved the prognosis of HER2-positive breast cancer patients. Despite this, resistance to therapy still remains the main clinical challenge. In order to evaluate the implication of microRNAs in the trastuzumab response, we performed a microRNA array in parental and acquired trastuzumab-resistant HER2-positive breast cancer cell lines. Our results identified miR-146a-5p as the main dysregulated microRNA. Interestingly, high miR-146a-5p expression in primary tumor tissue significantly correlated with shorter disease-free survival in HER2-positive breast cancer patients. The gain- and loss-of-function of miR-146a-5p modulated the response to trastuzumab. Furthermore, the overexpression of miR-146a-5p increased migration and angiogenesis, and promoted cell cycle progression by reducing CDKN1A expression. Exosomes from trastuzumab-resistant cells showed a high level of miR-146a-5p expression compared with the parental cells. In addition, the co-culture with resistant cells’ exosomes was able to decrease in sensitivity and increase the migration capacities in trastuzumab-sensitive cells, as well as angiogenesis in HUVEC-2 cells. Collectively, these data support the role of miR-146a-5p in resistance to trastuzumab, and demonstrate that it can be transferred by exosomes conferring resistance properties to other cells.
Intravascular Complications of Central Venous Catheterization by Insertion Site in Acute Leukemia during Remission Induction Chemotherapy Phase: Lower Risk with Peripherally Inserted Catheters in a Single-Center Retrospective Study
Authors: Picardi Marco , Giordano Claudia , Della Pepa Roberta , Pugliese Novella , Esposito Maria , Abagnale Davide Pio , Giannattasio Maria Luisa , Lisi Dario , Lamagna Martina , Grimaldi Francesco , Muccioli Casadei Giada , Ciriello Mauro , Persico Marcello , Gargiulo Gianpaolo , Pane Fabrizio
Published: April 2023

The basilic/brachial (BBV), internal jugular (IJV), and subclavian veins (SCV) are commonly used as central venous catheter (CVC) sites. A BBV approach [peripherally inserted central catheter (PICC)] is increasingly used for short- to intermediate-term CVCs for acute leukemias undergoing cytotoxic intensive regimens. In this retrospective study, the catheterization of the BBV, IJV, and SCV in patients with previously untreated acute leukemia was assessed. The primary outcome was the composite incidence of catheter-related symptomatic deep-vein thrombosis (sDVT) and bloodstream infection (BSI) from catheterization up to 30 days later. In a 10-year period, 336 CVC were inserted in the BBV (n = 115), IJV (n = 111), and SCV (n = 110) in 336 patients suffering from AML (n = 201) and ALL (n = 135) and undergoing induction chemotherapy. The primary outcome events were 8, 20, and 27 in the BBV, SCV and IJV cohorts (2.6, 6.9, and 9.6 per 1000 catheter-days, respectively; p = 0.002). The primary outcome risk was significantly higher in the IJV-cohort than in the BBV-cohort (HR, 3.6; 95% CI, 1.6 to 7.9; p = 0.001) and in the SCV-cohort than in the BBV-cohort (HR, 2.6; 95% CI, 1.2 to 5.9; p = 0.02). PICC was a valid CVC for the induction chemotherapy of acute leukemia for the lowest risk of sDVT and BSI.
Risk Classification of Bladder Cancer by Gene Expression and Molecular Subtype
Authors: Blanca Ana , Lopez-Beltran Antonio , Lopez-Porcheron Kevin , Gomez-Gomez Enrique , Cimadamore Alessia , Bilé-Silva Andreia , Gogna Rajan , Montironi Rodolfo , Cheng Liang
Published: April 2023

This study evaluated a panel including the molecular taxonomy subtype and the expression of 27 genes as a diagnostic tool to stratify bladder cancer patients at risk of aggressive behavior, using a well-characterized series of non-muscle invasive bladder cancer (NMIBC) as well as muscle-invasive bladder cancer (MIBC). The study was conducted using the novel NanoString nCounter gene expression analysis. This technology allowed us to identify the molecular subtype and to analyze the gene expression of 27 bladder-cancer-related genes selected through a recent literature search. The differential gene expression was correlated with clinicopathological variables, such as the molecular subtypes (luminal, basal, null/double negative), histological subtype (conventional urothelial carcinoma, or carcinoma with variant histology), clinical subtype (NMIBC and MIBC), tumor stage category (Ta, T1, and T2–4), tumor grade, PD-L1 expression (high vs. low expression), and clinical risk categories (low, intermediate, high and very high). The multivariate analysis of the 19 genes significant for cancer-specific survival in our cohort study series identified TP53 (p = 0.0001), CCND1 (p = 0.0001), MKI67 (p < 0.0001), and molecular subtype (p = 0.005) as independent predictors. A scoring system based on the molecular subtype and the gene expression signature of TP53, CCND1, or MKI67 was used for risk assessment. A score ranging from 0 (best prognosis) to 7 (worst prognosis) was obtained and used to stratify our patients into two (low [score 0–2] vs. high [score 3–7], model A) or three (low [score 0–2] vs. intermediate [score 3–4] vs. high [score 5–7], model B) risk categories with different survival characteristics. Mean cancer-specific survival was longer (122 + 2.7 months) in low-risk than intermediate-risk (79.4 + 9.4 months) or high-risk (6.2 + 0.9 months) categories (p < 0.0001; model A); and was longer (122 + 2.7 months) in low-risk than high-risk (58 + 8.3 months) (p < 0.0001; model B). In conclusion, the molecular risk assessment model, as reported here, might be used better to select the appropriate management for patients with bladder cancer.
Development and Evaluation of MR-Based Radiogenomic Models to Differentiate Atypical Lipomatous Tumors from Lipomas
Authors: Foreman Sarah , Llorián-Salvador Oscar , David Diana , Rösner Verena , Rischewski Jon , Feuerriegel Georg , Kramp Daniel , Luiken Ina , Lohse Ann-Kathrin , Kiefer Jurij , Mogler Carolin , Knebel Carolin , Jung Matthias , Andrade-Navarro Miguel , Rost Burkhard , Combs Stephanie , Makowski Marcus , Woertler Klaus , Peeken Jan , Gersing Alexandra
Published: April 2023

Background: The aim of this study was to develop and validate radiogenomic models to predict the MDM2 gene amplification status and differentiate between ALTs and lipomas on preoperative MR images. Methods: MR images were obtained in 257 patients diagnosed with ALTs (n = 65) or lipomas (n = 192) using histology and the MDM2 gene analysis as a reference standard. The protocols included T2-, T1-, and fat-suppressed contrast-enhanced T1-weighted sequences. Additionally, 50 patients were obtained from a different hospital for external testing. Radiomic features were selected using mRMR. Using repeated nested cross-validation, the machine-learning models were trained on radiomic features and demographic information. For comparison, the external test set was evaluated by three radiology residents and one attending radiologist. Results: A LASSO classifier trained on radiomic features from all sequences performed best, with an AUC of 0.88, 70% sensitivity, 81% specificity, and 76% accuracy. In comparison, the radiology residents achieved 60–70% accuracy, 55–80% sensitivity, and 63–77% specificity, while the attending radiologist achieved 90% accuracy, 96% sensitivity, and 87% specificity. Conclusion: A radiogenomic model combining features from multiple MR sequences showed the best performance in predicting the MDM2 gene amplification status. The model showed a higher accuracy compared to the radiology residents, though lower compared to the attending radiologist.
The Role of Surgery in Primary Chest Wall Tumors: Over 20 Years’ Experience in Resection and Reconstruction
Authors: Lo Iacono Giorgio , Mazzella Antonio , Mohamed Shehab , Petrella Francesco , Sedda Giulia , Casiraghi Monica , Girelli Lara , Bertolaccini Luca , Spaggiari Lorenzo
Published: April 2023

Background: Primary chest wall tumors comprise a heterogeneous group of neoplasms arising from soft tissues and bones. While surgical excision is the standard of care for benign tumors, the management of malignant tumors requires multimodal treatment. We conducted a predictive analysis of outcome, recurrence-free and overall survival. Methods: We retrospectively reviewed the clinical and pathological records of all patients treated in our center between 1998 and 2020. Results: 53 patients (15–85 years) were treated in our department. The average tumor diameter was 65 ± 35 mm (10–160 mm). Negative margins were obtained in 48 patients (90.6%), whereas in the remaining 5, R1 resection was accomplished. Median overall survival was 63,03 months (1–282 months). Overall survival was 90% at 1 year, 78% at 2 years, and 61% at 5 years. Our analysis identified tumor diameter, postoperative complications, and high grade of malignancy as factors that can influence prognosis. Conclusions: The treatment of primary chest wall tumors remains a very challenging process. Different histological types preclude definition of an unequivocal approach. Complete resection with healthy margins remains a definitive cornerstone in the treatment of these cancers as part of a more comprehensive approach.
Crystal-Plane-Dependent Guaiacol Hydrodeoxygenation Performance of Au on Anatase TiO2
Authors: Zhao Bin , Zhang Xiaoqiang , Mao Jingbo , Wang Yanli , Zhang Guanghui , Zhang Zongchao Conrad , Guo Xinwen
Published: April 2023

TiO2-supported catalysts have been widely used for a range of both liquid-phase and gas-phase hydrogenation reactions. However, little is known about the effect of their different crystalline surfaces on their activity during the hydrodeoxygenation process. In this work, Au supported on anatase TiO2, mainly exposing 101 or 001 facets, was investigated for the hydrodeoxygenation (HDO) of guaiacol. At 300 °C, the strong interaction between the Au and TiO2-101 surface resulted in the facile reduction of the TiO2-101 surface with concomitant formation of oxygen vacancies, as shown by the H2-TPR and H2-TPD profiles. Meanwhile, the formation of Auδ−, as determined by CO-DRIFT spectra and in situ XPS, was found to promote the demethylation of guaiacol producing methane. However, this strong interaction was absent on the Au/TiO2-001 catalyst since TiO2-001 was relatively difficult to be reduced compared with TiO2-101. The Au on TiO2-001 just served as the active site for the dissociation of hydrogen without the formation of Auδ−. The hydrogen atoms spilled over to the surface of TiO2-001 to form a small amount of oxygen vacancies, which resulted in lower activity than that over Au/TiO2-101. The catalytic activity of the Au/TiO2 catalyst for hydrodeoxygenation will be controlled by tuning the crystal plane of the TiO2 support.
Copy Number Variation in Inflammatory Breast Cancer
Authors: Hazra Aditi , O’Hara Andrea , Polyak Kornelia , Nakhlis Faina , Harrison Beth T. , Giordano Antonio , Overmoyer Beth , Lynce Filipa
Published: April 2023

Identification of a unique genomic biomarker in de novo inflammatory breast cancer (IBC) may provide an insight into the biology of this aggressive disease. The goal of our study was to elucidate biomarkers associated with IBC. We examined breast biopsies collected from Dana–Farber Cancer Institute patients with IBC prior to initiating preoperative systemic treatment (30 samples were examined, of which 14 were eligible). Patients without available biopsies (n = 1), with insufficient tumor epithelial cells (n = 10), or insufficient DNA yield (n = 5) were excluded from the analysis. Molecular subtype and tumor grade were abstracted from a medical records’ review. Ten IBC tumors were estrogen-receptor-positive (ER+) and human epidermal growth factor receptor 2 (HER2)-negative (n = 10 out of 14). Sufficient RNA and DNA were simultaneously extracted from 14 biopsy specimens using the Qiagen AllPrep Kit. RNA was amplified using the Sensation kit and profiled using the Affymetrix Human Transcriptome Array 2.0. DNA was profiled for genome-wide copy number variation (CNV) using the Affymetrix OncoScan Array and analyzed using the Nexus Chromosome Analysis Suite. Among the 14 eligible samples, we first confirmed biological concordance and quality control metrics using replicates and gene expression data. Second, we examined CNVs and gene expression change by IBC subtype. We identified significant CNVs in IBC patients after adjusting for multiple comparisons. Next, to assess whether the CNVs were unique to IBC, we compared the IBC CNV data to fresh-frozen non-IBC CNV data from The Cancer Genome Atlas (n = 388). On chromosome 7p11.2, we identified significant CN gain located at position 58,019,983-58,025,423 in 8 ER+ IBC samples compared to 338 non-IBC ER+ samples (region length: 5440 bp gain and 69,039 bp, False Discovery Rate (FDR) p-value = 3.12 × 10−10) and at position 57,950,944–58,025,423 in 3 TN-IBC samples compared to 50 non-IBC TN samples (74,479 base pair, gain, FDR p-value = 4.27 × 10−5; near the EGFR gene). We also observed significant CN loss on chromosome 21, located at position 9,648,315–9,764,385 (p-value = 4.27 × 10−5). Secondarily, differential gene expression in IBC patients with 7p11.2 CN gain compared to SUM149 were explored after FDR correction for multiple testing (p-value = 0.0016), but the results should be interpreted with caution due to the small sample size. Finally, the data presented are hypothesis-generating. Validation of CNVs that contribute to the unique presentation and biological features associated with IBC in larger datasets may lead to the optimization of treatment strategies.
Evaluating the Development Status of Fluorescence-Guided Surgery (FGS) in Pediatric Surgery Using the Idea, Development, Exploration, Assessment, and Long-Term Study (IDEAL) Framework
Authors: Preziosi Alessandra , Paraboschi Irene , Giuliani Stefano
Published: April 2023

Fluorescence-guided surgery (FGS) is used in many pediatric subspecialties but there are currently no standard guidelines or outcome data. We aimed to assess the current status of FGS in pediatrics using the Idea, Development, Exploration, Assessment, and Long-term study (IDEAL) framework. Clinical papers on FGS in children published from January 2000 to December 2022 were systematically reviewed. The stage of research development was measured considering seven fields of application: biliary tree imaging, vascular perfusion for gastrointestinal procedures, lymphatic flow imaging, tumor resection, urogenital surgery, plastic surgery, and miscellaneous procedures. Fifty-nine articles were selected. For each field of application, the overall IDEAL stage was determined to be 2a for biliary tree imaging (10 publications, 102 cases), 1 for vascular perfusion for gastrointestinal procedures (8 publications, 28 cases), 1 for lymphatic flow imaging (12 publications, 33 cases), 2a for tumor resection (20 publications, 238 cases), 2a for urogenital surgery (9 publications, 197 cases), and 1-2a for plastic surgery (4 publications, 26 cases). One report did not belong to any categories. FGS in children is still in an early phase of adoption and development. We recommend using the IDEAL framework as a guide and suggest developing multicenter studies to define the standard guidelines, effectiveness, and outcomes.
A Computational Study of Particle Mass Transport during Melting of NePCM in a Square Cavity with a Single Adiabatic Side
Authors: El Hasadi Yousef M. F.
Published: April 2023

Nanostructured phase change materials (NePCM) are phase change materials that contain different types and sizes of colloidal I removed the word sizes particles. Many investigations in the literature assess those type of phase change materials to investigate their thermal performance. However, there is a discrepancy between the experimental observations and numerical results of the melting process of the NePCM because most numerical models do not count for the mass transfer of the particles. In the current work, we will investigate the melting process of NePCM that consists of copper nanoparticles suspended in water for the geometry of a square cavity, heated from the two sides, cooled from one side, and the remaining side is thermally insulated. Our numerical model will account for the mass transfer of the particles using a one-fluid mixture and the enthalpy porosity model for accounting for the phase change process. We found that adding the particles will lead to the deceleration of the melting process, as described by the experiments, because of the reduction of the convection intensity. We found that for NePCM suspension containing 10% of nanoparticles by mass, the deceleration of melting will be about 2.2% compared to pure water. Most of the particles are convected away by the flow cells toward the bottom side of the cavity, especially near the isolated right side of the cavity. Our findings indicate that incorporating mass transport of particles leads to a significantly improved prediction of the melting behavior of the NePCM.
Algebraic Cryptanalysis with MRHS Equations
Authors: Zajac Pavol
Published: April 2023

In this work, we survey the existing research in the area of algebraic cryptanalysis based on Multiple Right-Hand Sides (MRHS) equations (MRHS cryptanalysis). MRHS equation is a formal inclusion that contains linear combinations of variables on the left-hand side, and a potential set of values for these combinations on the right-hand side. We describe MRHS equation systems in detail, including the evolution of this representation. Then we provide an overview of the methods that can be used to solve MRHS equation systems. Finally, we explore the use of MRHS equation systems in algebraic cryptanalysis and survey existing experimental results.
High-Angle Structural Color Scattering Features from Polymeric Photonic Structures
Authors: Rosetta Giselle , Tomes John J. , Butters Mike , Gunn Matthew , Finlayson Chris E.
Published: April 2023

Three-dimensional goniometric measurements of structural color from melt-sheared polymer nanoparticle composites is presented revealing high-angle features arising from Bragg scattering. These features are presented in terms of ‘scattering cones’ from full 180° hemispherical scans showing the spectroscopic and angular properties of these scattering spots. This work identifies the Miller indices of the photonic crystal planes responsible for these features and makes further observations as to the appearance of this scattering in the context of these structures as quasi-ordered systems. We probe structural color metrics such as peak wavelength and the tunability of reflectance intensities. As such, this report contributes towards an improved understanding of Bragg scattering and structural color from structures with inherent disorder. The complexity and specificity of color quality across the scattering hemisphere is an important consideration for practical uses such as in sensing applications, and we suggest that soft photonics, in particular, are strong candidates in high-angle color uses.
Seed Density as a New Predictive Index of Seed Migration in Brachytherapy for Prostate Cancer Using Iodine-125 Loose Seed
Authors: Yamaguchi Takahiro , Matsuo Masayuki , Mori Takayuki , Noda Yoshifumi , Makita Chiyoko , Hyodo Fuminori , Iinuma Koji , Nakano Masahiro , Koie Takuya , Tanaka Hidekazu
Published: April 2023

Aim: This study aimed to examine the usefulness of seed density as a predictor of seed migration in patients with prostate cancer who received brachytherapy using Iodine-125 loose seed. Methods: From May 2006 to April 2016, 320 patients with localized prostate cancer underwent transperineal brachytherapy using iodine-125 loose seeds. Among them, 202 (63.1%) patients received brachytherapy monotherapy and 118 (36.9%) received combined brachytherapy and external beam radiotherapy. Seed density was calculated using the following formula: seed density = implanted seed number/prostate volume. All patients underwent radiography of the chest, abdomen and pelvis, and computed tomography at 1 day, 1 month, and 1 year after brachytherapy to evaluate the presence of seed migration. Results: In total, the number of implanted seeds was 21,876. Seed migration was detected in 92 (28.8%) patients. Of a total of 21,876 seeds, 144 (0.66%) showed migration. The number of needles, number of seeds, and seed density were significantly higher in the group with migration than in the group without migration (p = 0.05). The ROC cutoff values for prostate volume, number of needles, number of seeds, and seed density were 20.9 cc, 21, 65, and 3.0, respectively. In the univariate analysis, prostate volume, number of needles, number of seeds, seed density, and treatment modality were all significant factors in predicting migration (p = 0.05). In the multivariate analysis, seed density and treatment modality were significant factors in predicting migration (p = 0.05). Conclusion: Seed density is useful for predicting seed migration. In cases with seed density > 3.0, it is necessary to take measures such as considering the use of stranded seeds.
2s-GATCN: Two-Stream Graph Attentional Convolutional Networks for Skeleton-Based Action Recognition
Authors: Zhou Shu-Bo , Chen Ran-Ran , Jiang Xue-Qin , Pan Feng
Published: April 2023

As human actions can be characterized by the trajectories of skeleton joints, skeleton-based action recognition techniques have gained increasing attention in the field of intelligent recognition and behavior analysis. With the emergence of large datasets, graph convolutional network (GCN) approaches have been widely applied for skeleton-based action recognition and have achieved remarkable performances. In this paper, a novel GCN-based approach is proposed by introducing a convolutional block attention module (CBAM)-based graph attention block to compute the semantic correlations between any two vertices. By considering semantic correlations, our model can effectively identify the most discriminative vertex connections associated with specific actions, even when the two vertices are physically unconnected. Experimental results demonstrate that the proposed model is effective and outperforms existing methods.
FPGA Implementation of Shack–Hartmann Wavefront Sensing Using Stream-Based Center of Gravity Method for Centroid Estimation
Authors: Kong Fanpeng , Cegarra Polo Manuel , Lambert Andrew
Published: April 2023

We present a fast and reconfigurable architecture for Shack–Hartmann wavefront sensing implemented on FPGA devices using a stream-based center of gravity to measure the spot displacements. By calculating the center of gravity around each incoming pixel with an optimal window matching the spot size, the common trade-off between noise and bias errors and dynamic range due to window size existing in conventional center of gravity methods is avoided. In addition, the accuracy of centroid estimation is not compromised when the spot moves to or even crosses the sub-aperture boundary, leading to an increased dynamic range. The calculation of the centroid begins while the pixel values are read from an image sensor and further computation such as slope and partial wavefront reconstruction follows immediately as the sub-aperture centroids are ready. The result is a real-time wavefront sensing system with very low latency and high measurement accuracy feasible for targeting on low-cost FPGA devices. This architecture provides a promising solution which can cope with multiple target objects and work in moderate scintillation.
Improving Humanization through Metaverse-Related Technologies: A Systematic Review
Authors: Gonzalez-Moreno Maria , Andrade-Pino Paula , Monfort-Vinuesa Carlos , Piñas-Mesa Antonio , Rincon Esther
Published: April 2023

While there is an increasing awareness regarding the culture of humanization, which is strongly needed in the healthcare environment, little knowledge has been provided in relation to accurate strategies to teach humanization skills to healthcare undergraduate students, as well as to healthcare professionals. Furthermore, the usefulness of new technologies to improve humanization skills has hardly been addressed so far in the scientific literature, including promising strategies such as Metaverse-related technologies. Presumably, this is the first systematic review focused on the efficacy of Metaverse-related technologies to increase the acquisition of humanization skills in the healthcare environment. The purpose of this study was to review the scientific studies published in the last decade to answer the following two questions: (1) are Metaverse-related technologies useful in enhancing humanization skills in the healthcare environment? (2) What are the advantages and disadvantages that should be addressed to successfully develop Metaverse-related technologies in the healthcare sector? We conducted a systematic review of the peer-reviewed literature from EBSCO, Ovid, PubMed, Scopus, and Web of Science (WOS), following the PRISMA statements and using the following keywords: “humanization + Metaverse”; “humanization + mixed reality”; “humanization + extended reality”; “humanization + augmented reality”; “humanization + virtual reality”; “humanization + app”; “humanization + telemedicine”; “humanization + digital health”; “humanization + eHealth”; “humanization + telehealth”; “humanization + web-based”; “humanization + website”; “humanization + digital”; “humanization + online”; and “humanization + internet”. Studies published from 2012 to the present, written in the English language, were reviewed. A total of 505 records were obtained, of which three were selected based on the inclusion and exclusion criteria. The results will be helpful in developing new strategies to improve humanization skills in the health sphere.
A New Generation of Fast and Low-Memory Smart Digital/Geometrical Beamforming MIMO Antenna
Authors: Pirapaharan Kandasamy , Prabhashana W. H. Sasinda C. , Medaranga S. P. Pramuka , Hoole Paul R. P. , Fernando Xavier
Published: April 2023

Smart multiple-input multiple-output (MIMO) antennas with advanced signal processing algorithms are necessary in future wireless networks, such as 6G and beyond, for accurate space division multiplexing and beamforming. Such a MIMO antenna will yield better network coverage and tracking. This paper presents a smart MIMO antenna configuration with a highly innovative beamforming technique using several nonlinear configurations of dipole arrays. Phase delay factors are optimized at the transmitter to form a single beam and then to steer the beam towards a particular direction. A number of phase shifters are added in order to obtain maximum directional gain. This configuration also significantly increases the power gain of the MIMO antenna at a low cost and with operational simplicity. The paper also demonstrates how the beam width and beamsteering can be effectively controlled. Wolfram Mathematica software was used to generate the three-dimensional radiated beam patterns of the transmitter antenna. There are two approaches to configure the receiver antenna. In the first approach, the received signal magnitude is maximized by aligning the contribution of all elements of the receiver antenna to the same phase. With this approach, the field gain of the proposed system is 25.52 (14.07 dBi). The signal processing gain at the receiver is 64 (18.06 dBi). Therefore, the overall power gain for this proposed new digital/geometrical smart MIMO system is 32.13 dBi. In the second approach, the receiver beam is directed towards the transmitter by optimizing the phase delay coefficients of the receiver. Here, the overall gain of the system is found to be 134.56 (21.28 dBi). Even though the system gain in the second approach is lower, it has the advantage of low interference at the receiver side.
Temporally and Spatially Resolved Simulation of the Wind Power Generation in Germany
Authors: Lehneis Reinhold , Thrän Daniela
Published: April 2023

Temporally and spatially resolved data on wind power generation are very useful for studying the technical and economic aspects of this variable renewable energy at local and regional levels. Due to the lack of disaggregated electricity data from onshore and offshore turbines in Germany, it is necessary to use numerical simulations to calculate the power generation for a given geographic area and time period. This study shows how such a simulation model, which uses freely available plant and weather data as input variables, can be developed with the help of basic atmospheric laws and specific power curves of wind turbines. The wind power model is then applied to ensembles of nearly 28,000 onshore and 1500 offshore turbines to simulate the wind power generation in Germany for the years 2019 and 2020. For both periods, the obtained and spatially aggregated time series are in good agreement with the measured feed-in patterns for the whole of Germany. Such disaggregated simulation results can be used to analyze the power generation at any spatial scale, as each turbine is simulated separately with its location and technical parameters. This paper also presents the daily resolved wind power generation and associated indicators at the federal state level.