bluuebunny/crossref_metadata_2025 huggingface dataset:
Supplemental Table S5 from Machine Learning–Directed Conversion of Glioblastoma Cells to Dendritic Cell–Like Antigen-Presenting Cells as Cancer Immunotherapy
Authors: Liu Tianyi , Jin Dan , Le Son B. , Chen Dongjiang , Sebastian Mathew , Riva Alberto , Liu Ruixuan , Tran David D.
Published: October 2024

List of cellular molecular perturbations curated for nSCORE validation (Supporting the Materials and Methods Section)
Supplemental Table S2 from Machine Learning–Directed Conversion of Glioblastoma Cells to Dendritic Cell–Like Antigen-Presenting Cells as Cancer Immunotherapy
Authors: Liu Tianyi , Jin Dan , Le Son B. , Chen Dongjiang , Sebastian Mathew , Riva Alberto , Liu Ruixuan , Tran David D.
Published: October 2024

Network statistics for the 3 filtration methods of GeneRep in 6 cancer types in TCGA (Supporting the Materials and Methods Section)
Figure S4 from RNA-encoded Interleukin 2 with Extended Bioavailability Amplifies RNA Vaccine–Induced Antitumor T-cell Immunity
Authors: Peters Daniel , Kranz Lena M. , Eisel David , Diken Mustafa , Kreiter Sebastian , Türeci Özlem , Sahin Ugur , Vormehr Mathias
Published: October 2024

Antitumor immunity in response to RNA-LPX and Alb-IL2 RNA-NP. Absolute number of vaccine antigen-specific and nonvaccine antigen-specific CD8+ T cells, Tregs, and NK cells in the tumor (n=6 mice/group; A), tumor-draining lymph node (n=6 mice/group; B), and spleen (Alb RNA-NP: n=5 mice/group; Alb-IL2 RNA-NP: n=6 mice/group; C) of CT26 tumor-bearing BALB/c mice 5 days after i.v. administration of gp70 RNA-LPX combined with Alb-IL2 RNA-NP or Alb RNA-NP on day 12 after tumor cell inoculation. Mean + SEM. Two-tailed Student t-test. *P≤0.05.
Figure S3 from RNA-encoded Interleukin 2 with Extended Bioavailability Amplifies RNA Vaccine–Induced Antitumor T-cell Immunity
Authors: Peters Daniel , Kranz Lena M. , Eisel David , Diken Mustafa , Kreiter Sebastian , Türeci Özlem , Sahin Ugur , Vormehr Mathias
Published: October 2024

Expansion of Tregs in response to RNA-LPX and Alb-IL2 RNA-NP. Number of regulatory CD4+ T cells per spleen 7 days after the last of three weekly i.v. vaccinations with gp70 RNA-LPX (A) or OVA RNA-LPX (B) combined with Alb-IL2 RNA-NP or Alb RNA-NP (gp70: n=7 mice/group; OVA: n=5 mice/group). Mean + SEM.
Supplemental Table S15 from Machine Learning–Directed Conversion of Glioblastoma Cells to Dendritic Cell–Like Antigen-Presenting Cells as Cancer Immunotherapy
Authors: Liu Tianyi , Jin Dan , Le Son B. , Chen Dongjiang , Sebastian Mathew , Riva Alberto , Liu Ruixuan , Tran David D.
Published: October 2024

CFDs for murine GBM → iDC-APC conversion (Supporting Main Figure 1)
Supplemental Figure S9 from Machine Learning–Directed Conversion of Glioblastoma Cells to Dendritic Cell–Like Antigen-Presenting Cells as Cancer Immunotherapy
Authors: Liu Tianyi , Jin Dan , Le Son B. , Chen Dongjiang , Sebastian Mathew , Riva Alberto , Liu Ruixuan , Tran David D.
Published: October 2024

Murine DCs and myeloid markers (Supporting Main Figure 2A)
Supplemental Figure S8 from Machine Learning–Directed Conversion of Glioblastoma Cells to Dendritic Cell–Like Antigen-Presenting Cells as Cancer Immunotherapy
Authors: Liu Tianyi , Jin Dan , Le Son B. , Chen Dongjiang , Sebastian Mathew , Riva Alberto , Liu Ruixuan , Tran David D.
Published: October 2024

iDC-APCs upregulate the immune checkpoint PD-L1 (Supporting Main Figure 1F).
Figure S3 from Targeting Tumor-Associated Sialic Acids Using Chimeric Switch Receptors Based on Siglec-9 Enhances the Antitumor Efficacy of Engineered T Cells
Authors: Eisenberg Vasyl , Hoogi Shiran , Katzman Erel , Ben Haim Nimrod , Zur-Toledano Raphaelle , Radman Maria , Reboh Yishai , Zadok Oranit , Kamer Iris , Bar Jair , Sagi Irit , Hendel Ayal , Cohen Cyrille J.
Published: October 2024

Figure S3
Figure S2 from Targeting Tumor-Associated Sialic Acids Using Chimeric Switch Receptors Based on Siglec-9 Enhances the Antitumor Efficacy of Engineered T Cells
Authors: Eisenberg Vasyl , Hoogi Shiran , Katzman Erel , Ben Haim Nimrod , Zur-Toledano Raphaelle , Radman Maria , Reboh Yishai , Zadok Oranit , Kamer Iris , Bar Jair , Sagi Irit , Hendel Ayal , Cohen Cyrille J.
Published: October 2024

Figure S2
Supplemental Figure S15 from Machine Learning–Directed Conversion of Glioblastoma Cells to Dendritic Cell–Like Antigen-Presenting Cells as Cancer Immunotherapy
Authors: Liu Tianyi , Jin Dan , Le Son B. , Chen Dongjiang , Sebastian Mathew , Riva Alberto , Liu Ruixuan , Tran David D.
Published: October 2024

scRNA-seq analysis of fresh GBM tumors reveals the absence of a significant population of tumor-derived APCs with DC-like markers. (Supporting Main Figures 7)
Figure S1 from Targeting Tumor-Associated Sialic Acids Using Chimeric Switch Receptors Based on Siglec-9 Enhances the Antitumor Efficacy of Engineered T Cells
Authors: Eisenberg Vasyl , Hoogi Shiran , Katzman Erel , Ben Haim Nimrod , Zur-Toledano Raphaelle , Radman Maria , Reboh Yishai , Zadok Oranit , Kamer Iris , Bar Jair , Sagi Irit , Hendel Ayal , Cohen Cyrille J.
Published: October 2024

Figure S1
Supplemental Figure S10 from Machine Learning–Directed Conversion of Glioblastoma Cells to Dendritic Cell–Like Antigen-Presenting Cells as Cancer Immunotherapy
Authors: Liu Tianyi , Jin Dan , Le Son B. , Chen Dongjiang , Sebastian Mathew , Riva Alberto , Liu Ruixuan , Tran David D.
Published: October 2024

Murine iDCs-APCs share overlaps with murine DCs. (Supporting Main Figure 2A)
Supplementary Figure 9 from Intermittent MEK Inhibition with GITR Costimulation Rescues T-cell Function for Increased Efficacy with CTLA-4 Blockade in Solid Tumor Models
Authors: Dong Lauren , Choi Hyejin , Budhu Sadna , Schulze Isabell , Verma Svena , Mangarin Levi M. , Estrada Nevarro Valeria , Mehanna Nezar , Khan Jonathan F. , Venkatesh Divya , Thach Daniel , Rosen Neal , Wolchok Jedd D. , Merghoub Taha
Published: October 2024

Supplementary Figure 9. Intermittent CKI27 treatment and GITR engagement relieves suppressive effects of MEK inhibition on T cell proliferation, cytokine production, and effector function. (A-C) Human PBMCs were labelled with CTV, sub-optimally stimulated with 1:25 or 1:100 CD3/CD28 Dynabeads, and treated with DMSO, continuous CKI27 (96hr), washout CKI27 (24hr on, 72hr off), and/or GITR-L; n=2-3. (A) % proliferation of CTVlow CD8+ and CD4+ T cells. (B) FACS analysis of co-inhibitory, co-stimulatory, and activation markers on CD8+ and CD4+ T cells. Heatmaps represent fold changes of positive percentages of each marker normalized to DMSO. (C) Cytokine analysis of supernatants collected from all PBMCs. Heatmap represents fold changes of concentrations (pg/mL) of proteins normalized to DMSO. Two-way ANOVA test with Bonferroni’s correction for multiple comparisons was used. Significance levels are indicated by asterisks (*p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001; ****p ≤ 0.0001)
Table S4 from Hypoxia-Induced Long Noncoding RNA HIF1A-AS2 Regulates Stability of MHC Class I Protein in Head and Neck Cancer
Authors: Liao Tsai-Tsen , Chen Yu-Hsien , Li Zih-Yu , Hsiao An-Ching , Huang Ya-Li , Hao Ruo-Xin , Tai Shyh-Kuan , Chu Pen-Yuan , Shih Jing-Wen , Kung Hsing-Jien , Yang Muh-Hwa
Published: October 2024

Characteristics of the HNSCC patients for in situ hybridization and immunohistochemistry analysis (n = 29).
Figure S6 from Hypoxia-Induced Long Noncoding RNA HIF1A-AS2 Regulates Stability of MHC Class I Protein in Head and Neck Cancer
Authors: Liao Tsai-Tsen , Chen Yu-Hsien , Li Zih-Yu , Hsiao An-Ching , Huang Ya-Li , Hao Ruo-Xin , Tai Shyh-Kuan , Chu Pen-Yuan , Shih Jing-Wen , Kung Hsing-Jien , Yang Muh-Hwa
Published: October 2024

The representative images of manual IHC scoring and quantification of tumor-infiltrated CD8+ cells in HNSCC samples.
Figure S5 from Hypoxia-Induced Long Noncoding RNA HIF1A-AS2 Regulates Stability of MHC Class I Protein in Head and Neck Cancer
Authors: Liao Tsai-Tsen , Chen Yu-Hsien , Li Zih-Yu , Hsiao An-Ching , Huang Ya-Li , Hao Ruo-Xin , Tai Shyh-Kuan , Chu Pen-Yuan , Shih Jing-Wen , Kung Hsing-Jien , Yang Muh-Hwa
Published: October 2024

HIF1A-AS2 does not affect the expression of autophagy-related genes.
Supplementary Figure 13 from Intermittent MEK Inhibition with GITR Costimulation Rescues T-cell Function for Increased Efficacy with CTLA-4 Blockade in Solid Tumor Models
Authors: Dong Lauren , Choi Hyejin , Budhu Sadna , Schulze Isabell , Verma Svena , Mangarin Levi M. , Estrada Nevarro Valeria , Mehanna Nezar , Khan Jonathan F. , Venkatesh Divya , Thach Daniel , Rosen Neal , Wolchok Jedd D. , Merghoub Taha
Published: October 2024

Supplementary Figure 13. The triple combination increases activation of CD8+ T cells and CD4+ Teffs while destabilizing Tregs in LLC tumor. (A) Schema of LLC tumor bearing mice treated with vehicle, CKI27, isotypes, GITR, and/or CTLA-4. All timepoints were harvested on day 21 (7 days post treatment). (B) Numbers of cells/mg of TILs; n=4-5. (C) Phenotypes of TILs; n=4-5. Data are shown as mean±SEM. One-way ANOVA test with Bonferroni’s correction for multiple comparisons was used in all panels. Significance levels are indicated by asterisks (*p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001; ****p ≤ 0.0001).
Supplemental Figure 6 from Augmenting CAR T-cell Functions with LIGHT
Authors: Cai Winson , Tanaka Kento , Mi Xiaoli , Rajasekhar Vinagolu K. , Khan Jonathan F. , Yoo Sarah , de Stanchina Elisa , Rahman Jahan , Mathew Serena , Abrahimi Parwiz , Souness Sydney , Purdon Terence J. , McDowell James R. , Meyerberg Jeremy , Fujino Takeshi , Healey John H. , Abdel-Wahab Omar , Scheinberg David A. , Brentjens Renier J. , Daniyan Anthony F.
Published: October 2024

(A) Histopathological analysis images of certain organs in the 3 CAR-treated groups following full necropsy on day 30. Representative regions displaying lesion or absence of lesion at 20magnification are stained with H&E. Scale bar 100 microns. (B) Histologic examination of various organs and tissues on day 30 after CAR T cell treatment. (C) Serum chemistry values of mice on day 30 after CAR T cell treatment. Red represents higher than reference range and blue represents lower than reference range.
Supplemental Figure 5 from Augmenting CAR T-cell Functions with LIGHT
Authors: Cai Winson , Tanaka Kento , Mi Xiaoli , Rajasekhar Vinagolu K. , Khan Jonathan F. , Yoo Sarah , de Stanchina Elisa , Rahman Jahan , Mathew Serena , Abrahimi Parwiz , Souness Sydney , Purdon Terence J. , McDowell James R. , Meyerberg Jeremy , Fujino Takeshi , Healey John H. , Abdel-Wahab Omar , Scheinberg David A. , Brentjens Renier J. , Daniyan Anthony F.
Published: October 2024

(A) CAR T cells infiltration and expression of LIGHT at the tumor site was quantified by flow cytometric analysis on day 14 post CAR T cell treatment. (B) (C) Quantification of CAR T cells per gram of AsPC1 tumor mass on day 14 post CAR T cell treatment. Plot is representative of 4 to 5 mice per treatment group. Immunohistochemistry staining of mesothelin-negative cancer cell line, Panc1. Negative control. (D) Immunohistochemistry staining of mesothelin-positive cancer cell line, MDA-MB-231. Positive control. (E) Immunohistochemistry staining of various PDX slides samples to validate their mesothelin expression. (F) Flow cytometric analysis of mesothelin expression in PDAC2, one of the PDX selected for in vivo model. (G) In vitro cytotoxicity assay of PDX PDAC2 cocultured with various CAR T cell constructs. Plot represents 2 independent experiments of separate donor T cells.
Supplementary Figure S4 from MR1 Gene and Protein Expression Are Enhanced by Inhibition of the Extracellular Signal-Regulated Kinase ERK
Authors: Constantin Daniel , Nosi Vladimir , Kehrer Natalie , Vacchini Alessandro , Chancellor Andrew , Contassot Emmanuel , Beshirova Aisha , Prota Gennaro , Navarini Alexander , Mori Lucia , De Libero Gennaro
Published: October 2024

Supplementary Figure S4
Supplementary Figure S7 from The E3 Ubiquitin Ligase FBXO38 Maintains the Antitumor Function of Natural Killer Cells by Sustaining IL15R Signaling
Authors: Shi Yongjing , Zheng Xiaodong , Peng Hui , Xu Chenqi , Sun Rui , Tian Zhigang , Sun Haoyu , Wang Xianwei
Published: October 2024

Supplementary Figure S7. FBXO38 promotes human NK-92 cell proliferation in vitro
Supplementary Figure S4 from The E3 Ubiquitin Ligase FBXO38 Maintains the Antitumor Function of Natural Killer Cells by Sustaining IL15R Signaling
Authors: Shi Yongjing , Zheng Xiaodong , Peng Hui , Xu Chenqi , Sun Rui , Tian Zhigang , Sun Haoyu , Wang Xianwei
Published: October 2024

Supplementary Figure S4. FBXO38 does not affect NK cell trafficking
Data from MR1 Gene and Protein Expression Are Enhanced by Inhibition of the Extracellular Signal-Regulated Kinase ERK
Authors: Constantin Daniel , Nosi Vladimir , Kehrer Natalie , Vacchini Alessandro , Chancellor Andrew , Contassot Emmanuel , Beshirova Aisha , Prota Gennaro , Navarini Alexander , Mori Lucia , De Libero Gennaro
Published: October 2024

Abstract
The MHC class I–related molecule MR1 is ubiquitously expressed, is highly conserved among mammals, and presents bacterial and endogenous antigens in tumor cells. These features indicate that tumor-specific T cells restricted to MR1 may represent ideal candidates for novel cancer-directed T-cell immunotherapy. The very low expression of the MR1 protein at the cell surface is a potential challenge limiting the possible use of MR1-directed immunotherapies. To overcome this challenge, it is important that understanding of the mechanisms regulating MR1 expression is increased, as little is known about this currently. This study identified ERK1/2 as negative regulators of the MR1 gene and protein expression. Inhibition of ERK1/2 in tumor cells or treatment of BRAF-mutant tumor cells with drugs specific for mutated BRAF increased MR1 protein expression and recognition by tumor-reactive and MR1-restricted T cells. The ERK1/2 inhibition of MR1 was mediated by the ELF1 transcription factor, which was required for MR1 gene expression. The effects of ERK1/2 inhibition also occurred in cancer cell lines of different tissue origins, cancer cell lines resistant to drugs that inhibit mutated BRAF, and primary cancer cells, making them potential targets of specific T cells. In contrast to tumor cells, the recognition of healthy cells was very poor or absent after ERK1/2 inhibition. These findings suggest a pharmaceutical approach to increase MR1 protein expression in tumor cells and the subsequent activation of MR1-restricted T cells, and they have potential therapeutic implications.
Supplementary Figure S1 from Combined Oxygen-Enhanced MRI and Perfusion Imaging Detect Hypoxia Modification from Banoxantrone and Atovaquone and Track Their Differential Mechanisms of Action
Authors: O’Connor James P.B. , Tessyman Victoria , Little Ross A. , Babur Muhammad , Forster Duncan , Latif Ayşe , Cheung Susan , Lipowska-Bhalla Grazyna , Higgins Geoff S. , Asselin Marie-Claude , Parker Geoff J.M. , Williams Kaye J.
Published: October 2024

Supplementary Figure S1 shows a summary of the cohorts of xenografts used in each experiment.
Figure 3 from Combined Oxygen-Enhanced MRI and Perfusion Imaging Detect Hypoxia Modification from Banoxantrone and Atovaquone and Track Their Differential Mechanisms of Action
Authors: O’Connor James P.B. , Tessyman Victoria , Little Ross A. , Babur Muhammad , Forster Duncan , Latif Ayşe , Cheung Susan , Lipowska-Bhalla Grazyna , Higgins Geoff S. , Asselin Marie-Claude , Parker Geoff J.M. , Williams Kaye J.
Published: October 2024

Atovaquone (ATQ) induces modification of tumor hypoxia in Calu6 xenografts. A, TMR [18F] FAZA uptake is increased from baseline at day 7 in control tumors (Cn; white bars) but was reduced in drug-treated tumors. B, Example [18F] FAZA PET images, with greatest hypoxia represented by orange and red. C, Tumor MRI hypoxic fraction showed similar relative reduction at day 3 and 7, relative to control tumors. D, Example segmented MRI images showing hypoxic (blue), normoxic (yellow), and necrotic (gray) tumor. E, Lower percentage of pimonidazole staining was detected in drug-treated tumors at day 7, compared to controls. F, Example pimonidazole adduct formation images (×40 magnification).
Table S1 from Exosomal Thomsen–Friedenreich Glycoantigen: A New Liquid Biopsy Biomarker for Lung and Breast Cancer Diagnoses
Authors: Hsu Chang-Chieh , Su Yafei , Rittenhouse-Olson Kate , Attwood Kristopher M. , Mojica Wilfrido , Reid Mary E. , Dy Grace K. , Wu Yun
Published: October 2024

Supplementary Table S1. Characteristics of Lung Cancer Patients and Controls.
Supplementary Figure 7 from SREBP-Dependent Regulation of Lipid Homeostasis Is Required for Progression and Growth of Pancreatic Ductal Adenocarcinoma
Authors: Ishida Chiaki T. , Myers Stephanie L. , Kubota Casie S. , Shao Wei , McGuire Meredith R. , Liu Chune , Ewachiw Theodore E. , Mukhopadhyay Debaditya , Ke Suqi , Wang Hao , Rasheed Zeshaan A. , Anders Robert A. , Espenshade Peter J.
Published: October 2024

FIGURE S7 – SREBP pathway activation is required for PDAC cell growth in low serum conditions.
Improving Access to Mental Health Care through a Stepped Care Approach: Preliminary Results from a University Students’ Sample
Authors: Marques Marisa , Caetano Sofia , Xavier Sandra , Melo Ana , Ferreira Andreia , Martins Joana , Lavaredas Célia , Silva Bruno , Morais Sofia , Moura Diana , Madeira Nuno , Queirós António , Martins Maria João
Published: October 2024

Introduction: Recently, university counseling services have been faced with an increasing number of students seeking psychological support. However, human resources and time constraints limit the services to respond adequately. Recently, national guidelines for Mental Health Services in Higher Education recommended the stepped care approach to increase efficiency. The present study aimed to explore the implementation of a stepped care model in a Portuguese public university, analyzing students’ sociodemographic and clinical characteristics, and presenting the flow of the stepped care approach and the students’ waiting periods in each step. Methods: An observational study was conducted in the University of Coimbra’s health services between May 2019 and June 2021. Descriptive statistics were performed to describe the sociodemographic and clinical characteristics of the sample, the flow of the stepped care approach, and students’ waiting periods. Results: We enrolled 295 students in the present study. The findings of this study revealed that over 40% had a clinical diagnosis of anxiety or depressive disorders. In terms of students’ flow within the stepped care model, 82% of students sought psychological help through self-referral. Concerning the implementation of the stepped care model, results have shown that most students wait less than a month to access each step. Discussion/Conclusions: Although preliminary, our results suggest that the stepped care model might be a useful service organization, mainly in a community in which accessibility to services and speed of response are particularly important. Most students being self-referred highlight the importance of direct contact between the university community and the health services. Additionally, anxiety and mood disorders were the most prevalent diagnoses in our sample, which also points to the relevance of a stepped care approach, since other studies have highlighted its advantages for this kind of clinical population.
No-reference image quality assessment based on visual explanation images and deep transfer learning
Authors: Ahmed Basma , Omer Osama A. , Singh Vivek Kumar , Rashed Amal , Abdel-Nasser Mohamed
Published: October 2024

Quantifying image quality in the absence of a reference image continues to be a challenge despite the introduction of numerous no-reference image quality assessments (NR-IQA) in recent years. Unlike most existing NRIQA methods, this paper proposes an efficient NR-IQA method based on deep visual interpretations. Specifically, the main components of the proposed method are: i) generating a pseudo-reference image (PRI) for the input distorted images, ii) employing a pretrained convolutional network to extract feature maps from the distorted image and the corresponding PRI, iii) producing visual explanation images (VEIs) by using the feature maps of the distorted image and the corresponding PRI, iv) measuring the similarity between the two VEIs using an image similarity metric, and v) employing a non-linear mapping function for quality score alignment. In our experiments, we evaluated the efficacy of the proposed method across various forms of distortion using four benchmark datasets (LIVE, SIQAD, CSIQ, and TID2013). The proposed approach demonstrates parity with the latest methods, as evidenced by comparisons with both hand-crafted NR-IQA and deep learning-based approaches.
Enhanced driving assistance: automated day and night vehicle detection system utilizing convolutional neural networks
Authors: Zaarane Abdelmoghit , Slimani Ibtissam , Elhabchi Mourad , Atouf Issam
Published: October 2024

This paper presents an enhanced real-time vehicle detection system using convolutional neural networks (CNNs) for both daytime and night-time conditions. Initially, the system determines the time of capture by analyzing the upper part of input images. For daytime detection, it uses normalized cross-correlation and two-dimensional discrete wavelet transform (2D-DWT) techniques. Night-time detection involves identifying vehicle lamps through color thresholding and connected component techniques, followed by symmetry analysis and CNN classification. The dataset for training includes images from the Caltech Cars, AOLP, KITTI Vision, and night-time vehicle detection datasets, ensuring robust performance across various lighting conditions. Experiments demonstrate the system's high accuracy, achieving 99.2% during the day and 98.27% at night, meeting real-time requirements and enhancing driving assistance systems' reliability.
Outage analysis of a single-threshold hard-switching hybrid FSO/RF system for reliable pico-macrocell backhauling
Authors: Kassim Abduljalal Yusha’u , Oduol Vitalice Kalecha , Usman Aliyu Danjuma
Published: October 2024

In the quest for high-speed, reliable and cost-effective backhaul solutions for modern cellular networks, the hybrid free space optical (FSO) and radio frequency (RF) communication system is envisaged to be a promising technology. The hybrid system merges the benefits of both RF and FSO subsystems, delivering high data rates and reliability. The integration of both technologies improves the communication system's performance by addressing the inherent limitations of each. This study proposes a single-threshold hard-switching hybrid FSO/RF system for reliable pico-macrocell backhauling applications. We formulated closed-form expressions for the cumulative density functions (CDFs), probability density functions (PDFs), and outage probability (OP) for RF-only, FSO-only and hybrid FSO/RF links. The rician fading and gamma-gamma (G-G) channel distributions were utilized, respectively. The average received signal-to-noise ratio (SNR) determines the switching mechanism based on the defined threshold and atmospheric condition. Simulation results and analysis demonstrated that, at any average SNR above the defined threshold, the hybrid system’s OP outperforms that of the RF-only and FSO-only links under most conditions. The analysis illustrates that employing the hybrid FSO/RF system enhances reliability and boosts overall system performance in pico-macrocell backhauling scenarios, surpassing the performance of standalone FSO-only or RF-only links.
Predictive analytics on crop yield using supervised learning techniques
Authors: Okesola Julius Olatunji , Ifeoluwa Olaniyi , Ajagbe Sunday Adeola , Okesola Olubunmi , Abiodun Adeyinka O. , Osang Francis Bukie , Solanke Olakunle O.
Published: October 2024

Agriculture is one of Nigeria’s most important economic activities but with climate change is a threat to crop production and a significant impact on the national economy as unforeseen scenarios can cause a drop in crop yield. Machine learning algorithms are now being considered as decision support tools for crop yields prediction and weather forecasting. Maize is the crop selected in this study, and a stochastic gradient model of five popular regression algorithms was evaluated. The prediction system is written in Python programming language and linked to a web-based interface for ease of use and effectiveness. Using performance metrics, the result shows that stochastic gradient descent (SGD) performed best with lower error rates and better R2_score value of 0.98505036. This crop yield prediction system (CYPS) is able to predict the yield of the crop which will help farmers and analysts in decision-making. It will also help industries that make use of the agricultural product in strategizing the logistics of their business.
Stacking-based ensemble learning for identifying artist signatures on paintings
Authors: Hidayati Shintami Chusnul , Irawan Rahardja Agustinus Aldi , Suciati Nanik
Published: October 2024

Identifying artist signatures on paintings is essential for authenticating artworks and advancing digital humanities. An artist’s signature is a consistent element included in each painting that the artist creates, providing a unique identifier for their work. Traditional methods that rely on expert analysis and manual comparison are time-consuming and are prone to human error. Although convolutional neural networks (CNNs) have shown promise in automating this process, existing single-model approaches struggle with the diversity and complexity of artistic styles, leading to limitations in their performance and generalizability. Therefore, this study proposes an ensemble learning approach that integrates the predictive power of multiple CNN-based models. The proposed framework leverages the strengths of three state-of-the-art CNNs: EfficientNetB4, ResNet-50, and Xception. These models were independently trained, and the predictions were combined using a meta-learning strategy. To address class imbalance, data augmentation techniques and weighted loss functions were employed. The experimental results obtained on a dataset of more than 8,000 paintings from 50 artists demonstrate significant improvements over individual CNN architectures and other ensemble methods, thereby effectively capturing complex features and improving generalizability.
Leveraging transformer models for enhanced temperature forecasting: a comparative analysis in the Beni Mellal region
Authors: Jdi Hamza , Falih Noureddine
Published: October 2024

The remarkable impact of transformers in artificial intelligence, exemplified by applications like GPT-3 in language processing, has sparked interest in their potential for time series analysis. This study aims to explore whether transformers, specifically temporal fusion transformers (TFT), can outperform conventional methods in this domain. The research question is whether TFT exhibits superior performance compared to conventional recurrent neural network (RNN) methods, specifically gated recurrent unit (GRU), and traditional machine learning approaches, notably autoregressive integrated moving average (ARIMA), in the context of time series analysis and temperature prediction. A comparative analysis is conducted among three models: ARIMA, GRU, and TFT. The study utilizes time series data spanning from 1984 to the end of 2022. The models’ performances are evaluated using multiple metrics: mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and the coefficient of determination (R2). The TFT model achieves the lowest MAE, indicating high accuracy in its predictions. It outperforms both the RNN and traditional machine learning in temperature prediction tasks. Integrating the TFT model with the FAO penman-monteith method could improve irrigation scheduling due to more accurate temperature predictions, potentially enhancing water efficiency and crop yields.
Risk disclosure and financial performance of Islamic banks in Jordan: the moderating role of financial technology
Authors: Almomani Mohammed Abd-Akarim , Al-Momani Adai
Published: October 2024

Risk disclosure (RD) is important to inform investors. However, few studies examined this variable in developing countries and in Islamic bank context. This research investigates how RD affect financial performance (FP) of Islamic banks in Jordan. It also examines the moderating role of financial technology (FinTech). We use a quantitative method to examine how mandatory risk disclosure (MRD) and voluntary risk disclosure (VRD) impact return on assets (ROA) and return on equity (ROE) in Islamic banks operating in Jordan. Our results show that both MRD and VRD have a significant effect on FP of Islamic banks. Moreover, FinTech acts as a moderator in the connection between risk disclosure (MRD and VRD) and FP performance. The effect was compared before and after coronaviruses disease 2019 (COVID-19) and it shows that the COVID-19 has increased the effect of MRD and VRD on FP of Islamic banks. More focus on VRD and MRD will enhance the FP of Islamic banks in Jordan.
A low-cost localization method in autonomous vehicle by applying light detection and ranging technology
Authors: Kannan Raju Jagadeesh , Amru Malothu , Muthumarilakshmi Surulivelu , Jeyapriya Jeyaprakash , Aghalya Stalin , Muthukumaran Dhakshnamoorthy , Murugan Subbiah
Published: October 2024

The autonomous platform uses global positioning system (GPS) to localize the vehicle. In addition, light detection and ranging (LIDAR) and the high precision camera help to identify the turns in the road. The proposed system can help to determine the road turns with higher accuracy without utilizing LIDAR and high-precision camera technology. This research aims to implement a cost-effective simultaneous localization system that can reduce the cost by half for any autonomous vehicle. The existing system is more complex due to the inclusion of LIDAR technology. In contrast, the proposed approach uses beacon communication between vehicles and infrastructure and long-range (LoRa) for vehicle-to-vehicle (V2V) and vehicle to infrastructure (V2I) communication. The simulation result illustrates that the proposed approach provides better performance.
Building Political Agreements: Pragmatic and Responsive Decision-Makers
Authors: del Río Adrián , Coller Xavier
Published: October 2024

Are politicians willing to betray their ideology, party, voters, and/or own principles to reach agreements with rivals? Focusing on the case of Spain, this article shows that there are two types of parliamentarians: those who are purely practical when making decisions (pragmatic) and those who consider their voters and electoral program in that process (responsive). We use latent class analyses to identify such profiles and conduct multinomial regression analyses to examine who are the most likely to be responsive or pragmatic parliamentarians. Our findings suggest that the former tend to have populist attitudes, support citizen involvement in decision-making, reject expert involvement in the political process, and show high levels of affective polarization. In the concluding section, we discuss how the profile of decision-makers exposes tensions in the functioning of democracy.
Stop the Bleed—Wait for the Ambulance or Get in the Car and Drive? A Post Hoc Analysis of an EAST Multicenter Trial
Authors: Simpson John T. , Nordham Kristen D. , Tatum Danielle , Haut Elliot R. , Ali Ayman , Maher Zoe , Goldberg Amy J. , Tatebe Leah C. , Chang Grace , Taghavi Sharven , Raza Shariq , Toraih Eman , Mendiola Plá Michelle , Ninokawa Scott , Anderson Christofer , Maluso Patrick , Keating Jane , Burruss Sigrid , Reeves Matthew , Craugh Lauren E. , Shatz David V. , Bhupathi Apoorva , Spalding M. Chance , LaRiccia Aimee , Bird Emily , Noorbakhsh Matthew R. , Babowice James , Nelson Marsha C. , Jacobson Lewis E. , Williams Jamie , Vella Michael , Dellonte Kate , Hayward Thomas Z. , Holler Emma , Lieser Mark J. , Berne John D. , Mederos Dalier R. , Askari Reza , Okafor Barbara , Etchill Eric , Fang Raymond , Roche Samantha L. , Whittenburg Laura , Bernard Andrew C. , Haan James M. , Lightwine Kelly L. , Norwood Scott H. , Murry Jason , Gamber Mark A. , Carrick Matthew M. , Bugaev Nikolay , Tatar Antony
Published: October 2024

Background: The Stop the Bleed campaign gives bystanders an active role in prehospital hemorrhage control. Whether extending bystanders’ role to private vehicle transport (PVT) for urban penetrating trauma improves survival is unknown, but past research has found benefit to police and PVT. We hypothesized that for penetrating trauma in an urban environment, where prehospital procedures have been proven harmful, PVT improves outcomes compared to any EMS or advanced life support (ALS) transport.

Methods: Post-hoc analysis of an EAST multicenter trial was performed on adult patients with penetrating torso/proximal extremity trauma at 25 urban trauma centers from 5/2019-5/2020. Patients were allocated to PVT and any EMS or ALS transport using nearest neighbor propensity score matching. Univariate analyses included Wilcoxon signed rank or McNemar’s Test and logistic regression.

Results: Of 1999 penetrating trauma patients in urban settings, 397 (19.9%) had PVT, 1433 (71.7%) ALS transport, and 169 (8.5%) basic life support (BLS) transport. Propensity matching yielded 778 patients, distributed equally into balanced groups. PVT patients were primarily male (90.5%), Black (71.2%), and sustained gunshot wounds (68.9%). ALS transport had significantly higher ED mortality (3.9% vs 1.9%, P = 0.03). There was no difference in in-hospital mortality rate, hospital LOS, or complications for all EMS or ALS only transport patients.

Conclusion: Compared to PVT, ALS, which provides more prehospital procedures than BLS, provided no survival benefit for penetrating trauma patients in urban settings. Bystander education incorporating PVT for early arrival of penetrating trauma patients in urban settings to definitive care merits further investigation.
Influence of intra-ply discontinuities on the mechanical behavior of continuous E-glass fiber reinforced composites
Authors: Kiliçoğlu Ahmet Süha , Tanoğlu Metin , Bilmez Sinan Ali , Güneş Mehmet Deniz , Erdoğan Hakan Salih
Published: October 2024

This study examines how structural discontinuities created during production affect glass fiber-reinforced composite plates. Due to geometrical constraints, the composite microstructure’s discontinuities can be categorized as inter-ply and intra-ply. Material testing was conducted at the coupon level as an initial step to ascertain material characteristics. Two full-scale models of intra-ply composite samples were manufactured by employing layers of glass fiber-reinforced prepregs. Discontinuities were generated in the samples using a computer numeric control cutter and then manually applied. The discontinuities’ impact on the composite laminate’s mechanical properties was assessed through full-scale pieces using three-point bending quasi-static tests. Servo-hydraulic actuators were used to conduct tests on the items. The experimental test results were compared with CAE analysis predictions by evaluating sectional fiber volume fraction. The characteristics of local discontinuities were analyzed using a microscope to enhance the findings of the CAE model. This comprehensive approach offers insights into the intricate connection between internal structural inconsistencies and the mechanical properties of continuous glass fiber-reinforced materials. It supports optimizing composite manufacturing processes and improves composite parts’ structural reliability. Dislocation areas were found to result in the formation of resin-rich zones in this investigation. The exothermic curing process in the component’s zones results in elevated temperatures, leading to a color change in the resin from clear to yellow. The yellow areas are easily recognizable and show decreased mechanical durability.
Multi-scale modeling: Finite element analysis of the thermophysical properties of carbon/carbon composites considering manufacturing defects and porosity at high temperature
Authors: Liu Yang , Zhao Haitao , Liu Kai , Zhao Zhongjie , Feng Min , Peng Yahui , Zhang Cheng-cheng , Chen Ji’an
Published: October 2024

Carbon/carbon (C/C) composites have strict requirements for their thermal properties in extreme environments, especially at high temperature, where their properties are crucial for long-term life. The structure of C/C composites is exceptionally complex and exhibits multi-scale characteristics, and their thermophysical properties are closely related to temperature. Therefore, exploring their thermal response and heat transfer mechanisms through experimental method is relatively costly. This paper constructs a multi-scale finite element model to investigate the influence of structure and manufacturing defects on performance, and analyzes the thermophysical properties of the composites at High-temperature. By constructing a micro-representative volume element (Micro-RVE) that includes fibers, matrix, and pores, and using a steady-state heat transfer analysis method, the influence of material phase distribution on performance is studied. At the same time, a Meso-RVE reflecting the layering form, needle punching effect and manufacturing defects is established, and the transient heat transfer analysis method is used to investigate the influence of the structural form on performance. Finite element analysis shows that, the simulation values of the three C/C composites of unidirectional fiber bundles, short-chopped fiber felts, and needle punched C/C composites show good consistency with the experimental results in the published literature. This paper uses numerical methods to calculate the thermophysical properties of C/C composites from room temperature to 900°C and explores their variation with temperature. The constructed multi-scale model provides an accurate and effective method for predicting the thermophysical properties of C/C composites and also provides new perspectives and insights for thermal-mechanical coupling analysis and structural design.
Spoofing attack recognition for GNSS-based train positioning using a BO-LightGBM method
Authors: Bi Jiaqi , Liu Jiang , Cai Baigen , Wang Jian
Published: October 2024

Trustworthy positioning is critical in the operational control and management of trains. For a train positioning system (TPS) based on a global navigation satellite system (GNSS), a spoofing attack significantly threatens the trustworthiness of positioning. However, the influence and recognition of GNSS spoofing attacks are not considered in the existing research on GNSS-enabled TPS. Spoofing attacks affect the performance of GNSS observations and the positioning results, allowing the development of data-driven spoofing recognition solutions. This study aims to achieve effective spoofing recognition for active security protection in TPS. Different features were designed to reflect the effects of a spoofing attack, including GNSS observation-related indicators and odometer-enabled parameters, and a novel Bayesian optimization-light gradient boosting machine (BO-LightGBM) solution was proposed. In particular, a Bayesian optimization technique was introduced into the LightGBM framework to improve the hyperparameter determination capability for recognition model training. Using a GNSS spoofing test platform with a specific GNSS signal generator and the SimSAFE spoofing test tool, different spoofing attack modes were tested to collect sample datasets for model training and evaluation. The results of model establishment and comparison of the model performance indicators illustrated the advantages of the proposed solution, its adaptability to different spoofing attack situations, and its superiority over state-of-the-art modeling strategies.
Linkages between industry, agriculture, growth, renewable energy and the environment and the role of institutional quality, evidence from selected South and East Asian economies
Authors: Lao Guo Chun , Luo Guang Qiang
Published: October 2024

This study aims to reveal the influence of industrial progress and agricultural value addition on environmental harm and explores how the unique moderating role of institutional quality handles this association; using the panel ARDL approach on a panel of South and East Asian economies from 1980 to 2020. The baseline model proposes that for each 1% increase in agricultural added value and industrial progress, carbon dioxide emissions may fluctuate considerably positively by 0.563% and 0.758% respectively. In the long term, the plausibility of the upturned U-shaped association between economic growth and carbon dioxide emissions in South and East Asian economies has been confirmed in the analysis. The use of renewable energy considerably condenses long-term emission levels. Institutional quality is found to have a strong moderating effect on the link between the main model regressors (renewable energy use, industrial growth, GDP per capita, and agricultural value addition) and CO2 emissions. Institutional quality supports the enhancement of industrial and agricultural capabilities and the improvement of environmental worth. Finally, the threshold results indicate that the influence of the main regression variables of the model (renewable energy utilization, industrial growth, per capita GDP, and agricultural added value) on carbon dioxide emissions has fully penetrated the institutional quality level. Strong, high-quality institutions, rather than weak institutions, can improve the aptitude of industry and agriculture to mitigate environmental degradation. In this pursuit, it becomes increasingly important to develop policies that support renewable energy based on institutional values.
Career Choice and Family Expectations of Individuals With Visual Impairments in Turkey: A Qualitative Study
Authors: Avcı Özlem Haskan
Published: October 2024

Introduction: This study aimed to explore the career choice of individuals with blindness or low vision (i.e., visual impairments) and their experiences with the expectations of their families. In societies where family is important, family members can influence the career choices of individuals with visual impairments. Method: This study was carried out in 2022. The online interview method was chosen to collect data due to the difficulties in conducting face-to-face interviews during the COVID-19 pandemic. The participants were 18 adults with visual impairments. Their ages ranged from 22 to 36 years. Participants were asked about the role of their families in their career choices. They were also asked about their expectations from effective career counseling. The researcher used deductive thematic analysis. Results: Four themes emerged from these data: (a) work not school, (b) guaranteed jobs are good enough, (c) daughters should marry, and (d) discrepancies in expectations based on household income. Discussion: As in many low- and middle-income countries, people with visual impairments in Turkey are discouraged from continuing their education. With the exception of affluent families, participants were generally directed to guaranteed or low-skill jobs. Gender stereotypes of families were a career barrier for women with visual impairments. Implications for Practitioners: Because of the essential role played by family members of people with visual impairments in Turkey, career counselors should work with families for effective practice. It is also essential for career counselors to inform families about the education and employment rights of individuals with visual impairments.
Digital inequalities among smallholder farmers in Benin: Determinants of attitude, material access, skills and usage
Authors: Gouthon Morrisson , Gouroubera Mori W. , Tama-Imorou Clarisse , Moumouni-Moussa Ismail
Published: October 2024

Digital inequalities in the agricultural sector have become a prominent concern since the advent of digital technologies. To address these inequalities among farmers, it is essential to gain a comprehensive understanding of their nature and underlying determinants. Drawing upon Van Dijk's theory of resources and appropriation, this study was conducted in Benin, a West African country, involving a sample of 307 smallholder farmers. Structural equation models are used to analyze the data. Firstly, the results reveal that the attitude of farmers is positively associated with their material access to digital technology, which, in turn, fosters the development of their digital skills encompassing both formal and strategic skills. These skills propel the integration of digital technology into agricultural practices. Farmers’ attitudes not only influence their access to digital tools but also significantly shape the development of their skill sets and the effective use of digital technologies in agriculture. Consequently, attitude emerges as an important factor in appropriating digital technology. Furthermore, this study identifies personal characteristics of farmers, including gender, age, income, level of education, and the presence of school-going children in their households, as factors influencing digital inequalities. Policies should foster positive attitudes, enhance digital skills, ensure equitable access, and address gender-specific barriers to reduce digital inequalities among smallholder farmers in agriculture.
Managing the Twin Faces of AI: A Commentary on “Is AI Changing the World for Better or Worse?”
Authors: Shankar Venkatesh
Published: October 2024

This commentary explores the transformative potential and inherent risks associated with artificial intelligence (AI), particularly generative AI. It focuses on the dual nature of AI, where it offers substantial benefits in industries like retailing, and social media, while also presenting challenges related to ethics, privacy, and job displacement. The article introduces a framework to analyze AI's organizational impact, categorizing outcomes based on how AI supports or disrupts the status quo. It discusses AI's contribution to operational efficiency, demand expansion, and business transformation, acknowledging both the promise of enhanced customer experiences and the peril of ethical dilemmas such as algorithmic bias and data privacy concerns. It explores real-world applications of AI, such as personalized customer engagement and healthcare diagnostics. At the same time, the article critically examines negative implications, including job displacement, wage polarization, and the erosion of human connection in customer service. The commentary offers a balanced perspective, urging businesses and policymakers to embrace Responsible AI principles like fairness, reliability, and accountability. The article projects the future of AI, particularly advancements in agentic AI, artificial general intelligence (AGI), and artificial superintelligence (ASI), as holding both enormous potential and severe risks. It concludes by calling for a thoughtful, regulated approach to AI development to ensure it serves the greater good while mitigating its risks.