bluuebunny/crossref_metadata_2025 huggingface dataset:
Phase 2 Trial of Regorafenib in Recurrent/Metastatic Adenoid Cystic Carcinoma
Authors: Desilets Antoine , Vos Joris L. , Katabi Nora , Kuo Fengshen , Nadeem Zaineb , Linxweiler Maximilian , Ostrovnaya Irina , Baxi Shrujal , Dunn Lara A. , Sherman Eric J. , Pfister David G. , Morris Luc G.T. , Ho Alan L.
Published: October 2024

Purpose:

There is a significant need for effective therapies to treat recurrent/metastatic (R/M) adenoid cystic carcinoma (ACC). This study evaluated the multitargeted VEGFR tyrosine kinase inhibitor (TKI) regorafenib in patients with R/M ACC.

Patients and Methods:

Patients with progressive R/M ACC were treated with regorafenib until disease progression, consent withdrawal, or excessive toxicity. The co-primary endpoints were best overall response and 6-month progression-free survival (PFS). Genomic and transcriptomic biomarker analyses were performed in tumors from trial participants.

Results:

Thirty-eight patients were enrolled, including 7 (18%) patients with prior VEGFR TKIs. No objective responses were observed. The 6-month PFS was 45%, and the median PFS was 7.2 months (95% confidence interval, 5.2–11.9 months). The presence of either activating NOTCH1 (22%) or KDM6A alterations (24%) was associated with decreased PFS [HR 2.6; 95% confidence interval (CI), 1.1–6.1; P = 0.03]. Bulk RNA sequencing of pretreatment tumors revealed that regorafenib clinical benefit (CB; PFS ≥ 6 months; n = 11) was associated with the native enrichment of immune-related signatures. Immune deconvolution revealed a greater degree of macrophage and T-cell infiltration in CB tumors. Tumors from patients with no clinical benefit (NCB; PFS < 6 months; n = 9) had greater expression of signatures related to cell-cycle progression (E2F targets, G2–M checkpoint).

Conclusions:

The trial failed to meet the prespecified 6-month PFS and best overall response targets. We hypothesize that TKI efficacy may be reliant upon an interplay between kinase inhibition and the ACC immune microenvironment, whereas programs promoting cell-cycle progression may contribute to TKI resistance. These observations suggest that trials evaluating CDK4/6 inhibition plus a VEGFR TKI should be considered.
Safety, Efficacy, and Biomarker Analysis of Crizotinib in MET-Mutated Non–Small Cell Lung Cancer—Results from the Drug Rediscovery Protocol
Authors: Verkerk Karlijn , van der Wel Tijmen J.W.T. , Zeverijn Laurien J. , Geurts Birgit S. , Spiekman Ilse A.C. , de Wit Gijs F. , Roepman Paul , Jansen Anne M.L. , van der Noort Vincent , Smit Egbert F. , Hoeben Ann , Hendriks Lizza E.L. , van den Heuvel Michel M. , Piet Berber , Herder Gerarda J.M. , Hashemi Sayed M.S. , Gelderblom Hans , Verheul Henk M.W. , Voest Emile E. , de Langen Adrianus J.
Published: October 2024

Purpose:

To provide patients with MET-mutated advanced non–small cell lung cancer (METmut aNSCLC) access to crizotinib, further substantiate evidence of its efficacy and safety in this setting, and find potential biomarkers for nonresponse.

Patients and Methods:

In the Drug Rediscovery Protocol (NCT0295234), patients with an actionable molecular profile are treated with off-label registered drugs. Both treated and untreated patients with aNSCLC harboring MET exon 14 skipping or other MET mutations received crizotinib 250 mg BID until disease progression or intolerable toxicity. Primary endpoints were clinical benefit [CB: RECIST v1.1 confirmed partial response, complete response (CR), or stable disease ≥16 weeks] and safety. Patients were enrolled using a Simon-like two-stage design, with eight patients in stage I and if ≥1/8 patients had CB, 24 patients in stage II. Whole-genome sequencing and RNA sequencing were performed on baseline biopsies.

Results:

Between September 2018 and October 2022, 30 patients started treatment, and 24 were response-evaluable after completing ≥1 full treatment cycle. Two patients (8.3%) achieved CR, 13 (54.2%) partial response, and two (8.3%) stable disease. The CB rate was 70.8% [95% confidence interval (CI), 48.9–87.4], and the objective response rate was 62.5% (95% CI, 40.6–81.2). After 21.2-month median follow-up, median duration of response, progression-free survival, and overall survival were 9.3 (95% CI, 6.5–not available), 10.2 (95% CI, 6.0–20.1), and 13.0 months (95% CI, 9.0–not available), respectively. Twenty-three treatment-related grade ≥ 3 adverse events occurred in 12/30 patients (40%), causing treatment discontinuation in three (10%). One patient (achieving CR) had a tyrosine kinase domain mutation (p.H1094Y), and all other patients had MET exon 14 skipping mutations.

Conclusions:

Crizotinib is a valuable treatment option in METmut aNSCLC.
Supplementary Figure S9 from Anti-Claudin-2 Antibody–Drug Conjugates for the Treatment of Colorectal Cancer Liver Metastasis
Authors: Tabariès Sébastien , Robert Alma , Marcil Anne , Ling Binbing , Acchione Mauro , Lippens Julie , Pagé Martine , Fortin Annie , Meury Luc , Coutu Mathieu , Annis Matthew G. , Girondel Charlotte , Navarre Julie , Jaramillo Maria , Moraitis Anna N. , Siegel Peter M.
Published: October 2024

Supplementary Figure S9
Figure S6 from Characterization of AB598, a CD39 Enzymatic Inhibitory Antibody for the Treatment of Solid Tumors
Authors: Anderson Amy E. , Parashar Kaustubh , Jin Ke , Clor Julie , Stagnaro Carlo E. , Vani Urvi , Singh Jaskirat , Chen Ada , Guan Yihong , Talukdar Priyanka , Sathishkumar Pavithra , Juat Damie J. , Singh Hema , Kushwaha Ritu , Zhao Xiaoning , Kaplan Angelo , Seitz Lisa , Walters Matthew J. , Fernandez-Salas Ester , Walker Nigel P.C. , Bowman Christine E.
Published: October 2024

Figure S6
Figure S4 from Characterization of AB598, a CD39 Enzymatic Inhibitory Antibody for the Treatment of Solid Tumors
Authors: Anderson Amy E. , Parashar Kaustubh , Jin Ke , Clor Julie , Stagnaro Carlo E. , Vani Urvi , Singh Jaskirat , Chen Ada , Guan Yihong , Talukdar Priyanka , Sathishkumar Pavithra , Juat Damie J. , Singh Hema , Kushwaha Ritu , Zhao Xiaoning , Kaplan Angelo , Seitz Lisa , Walters Matthew J. , Fernandez-Salas Ester , Walker Nigel P.C. , Bowman Christine E.
Published: October 2024

Figure S4
Figure S6 from FZ-AD005, a Novel DLL3-Targeted Antibody–Drug Conjugate with Topoisomerase I Inhibitor, Shows Potent Antitumor Activity in Preclinical Models
Authors: Guo Qingsong , Gao Bei , Song Ruiwen , Li Weinan , Zhu Shulei , Xie Qian , Lou Sensen , Wang Lei , Shen Jiafei , Zhao Teng , Zhang Yifan , Wu Jinsong , Lu Wei , Yang Tong
Published: October 2024

Supplementary Fig.S6
Figure S2 from PKMYT1 Is a Marker of Treatment Response and a Therapeutic Target for CDK4/6 Inhibitor-Resistance in ER+ Breast Cancer
Authors: Chen Anran , Kim Beom-Jun , Mitra Aparna , Vollert Craig T. , Lei Jonathan T. , Fandino Diana , Anurag Meenakshi , Holt Matthew V. , Gou Xuxu , Pilcher Jacob B. , Goetz Matthew P. , Northfelt Donald W. , Hilsenbeck Susan G. , Marshall C. Gary , Hyer Marc L. , Papp Robert , Yin Shou-Yun , De Angelis Carmine , Schiff Rachel , Fuqua Suzanne A.W. , Ma Cynthia X. , Foulds Charles E. , Ellis Matthew J.
Published: October 2024

A model of PKMYT1 gene transcription regulated by ERα and E2F transcription factors
Figure S13 from PKMYT1 Is a Marker of Treatment Response and a Therapeutic Target for CDK4/6 Inhibitor-Resistance in ER+ Breast Cancer
Authors: Chen Anran , Kim Beom-Jun , Mitra Aparna , Vollert Craig T. , Lei Jonathan T. , Fandino Diana , Anurag Meenakshi , Holt Matthew V. , Gou Xuxu , Pilcher Jacob B. , Goetz Matthew P. , Northfelt Donald W. , Hilsenbeck Susan G. , Marshall C. Gary , Hyer Marc L. , Papp Robert , Yin Shou-Yun , De Angelis Carmine , Schiff Rachel , Fuqua Suzanne A.W. , Ma Cynthia X. , Foulds Charles E. , Ellis Matthew J.
Published: October 2024

Synergy and viability analysis of RP-6306 and 5-FU combination in T47D parental and Palbo-R cells
Supplementary Figure 2 from The Vedotin Antibody–Drug Conjugate Payload Drives Platform-Based Nonclinical Safety and Pharmacokinetic Profiles
Authors: Neff-LaFord Haley D. , Carratt Sarah A. , Carosino Christopher , Everds Nancy , Cardinal Kristen A. , Duniho Steven , Schutten Melissa M. , Frantz Christopher , Zuch de Zafra Christina , Harstad Eric B.
Published: October 2024

Supplementary Figure 2. Reproductive toxicity with vedotin ADCs in cynomolgus monkeys.
Supplementary Figure S11 from Blocking M2-Like Macrophage Polarization Using Decoy Oligodeoxynucleotide-Based Gene Therapy Prevents Immune Evasion for Pancreatic Cancer Treatment
Authors: Chen Chang-Jung , Wang Hao-Chen , Hou Ya-Chin , Wu Yi-Ying , Shieh Chi-Chang , Shan Yan-Shen
Published: October 2024

Supplementary Figure S11. STAT6-CYBB ODN-treated macrophages can activate the proliferation of Jurkat cells and αCD3-PBMC cells. A, and B, After scrambled ODN (SC-ODN) and STAT6-CYBB ODN treatment, U937 cells were cocultured with PANC-1 cells for 72h. After coculture with PANC-1 cells, SC-ODN treated macrophages or STAT6-CYBB ODN treated macrophages were cocultured with CFSE-staining Jurkat cells or CFSE-staining αCD3-PBMC cells for 72h. Flow cytometry analysis of cell proliferation in Jurkat cells and αCD3-PBMC was performed. C, and D, The bar graphs indicate the relative percentages of CFSE-labeled Jurkat cells or αCD3-PBMC cells as proliferative index. *, p < 0.05; ***, p < 0.001, compared to the Jurkat cell or αCD3-PBMC cell only group. Data represent the mean of 3 independent experiments.
Table S3 from AKT Inhibition Sensitizes to Polo-Like Kinase 1 Inhibitor Onvansertib in Prostate Cancer
Authors: Nouri Mannan , Varkaris Andreas , Ridinger Maya , Dalrymple Susan L. , Dennehy Christopher M. , Isaacs John T. , Einstein David J. , Brennen W.N. , Balk Steven P.
Published: October 2024

Table S3 (% Control hits)
Figure S3 from AKT Inhibition Sensitizes to Polo-Like Kinase 1 Inhibitor Onvansertib in Prostate Cancer
Authors: Nouri Mannan , Varkaris Andreas , Ridinger Maya , Dalrymple Susan L. , Dennehy Christopher M. , Isaacs John T. , Einstein David J. , Brennen W.N. , Balk Steven P.
Published: October 2024

Olaparib and onvansertib treatment in vivo models demonstrate modest toxicity.
Figure S2 from AKT Inhibition Sensitizes to Polo-Like Kinase 1 Inhibitor Onvansertib in Prostate Cancer
Authors: Nouri Mannan , Varkaris Andreas , Ridinger Maya , Dalrymple Susan L. , Dennehy Christopher M. , Isaacs John T. , Einstein David J. , Brennen W.N. , Balk Steven P.
Published: October 2024

Prostate cancer cell sensitivity to PLK1 inhibitors.
Supplementary Tables S1-S13 from Atypical B Cells Promote Cancer Progression and Poor Response to Bacillus Calmette-Guérin in Non–Muscle Invasive Bladder Cancer
Authors: Yolmo Priyanka , Rahimi Sadaf , Chenard Stephen , Conseil Gwenaëlle , Jenkins Danielle , Sachdeva Kartik , Emon Isaac , Hamilton Jake , Xu Minqi , Rangachari Manu , Michaud Eva , Mansure Jose J. , Kassouf Wassim , Berman David M. , Siemens David R. , Koti Madhuri
Published: October 2024

Data from Atypical B cells promote cancer progression and poor response to Bacillus Calmette Guérin in non-muscle invasive bladder cancer
Figure S11 from Atypical B Cells Promote Cancer Progression and Poor Response to Bacillus Calmette-Guérin in Non–Muscle Invasive Bladder Cancer
Authors: Yolmo Priyanka , Rahimi Sadaf , Chenard Stephen , Conseil Gwenaëlle , Jenkins Danielle , Sachdeva Kartik , Emon Isaac , Hamilton Jake , Xu Minqi , Rangachari Manu , Michaud Eva , Mansure Jose J. , Kassouf Wassim , Berman David M. , Siemens David R. , Koti Madhuri
Published: October 2024

BBN exposure and BCG treatment alters plasma immunoglobulin profiles in a sex differential manner.
Supplemental Table S14 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

Top 20 CFDs for conversion of murine GBM to myeloid cells (supporting Main Figure 1)
Supplemental Figure S4 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

nSCORE Validation (Supporting the Materials and Methods Section)
Supplemental Figure S21 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

Human PU.1/IKZF1 (hPI) is 50%-100% more efficient at inducing CD45+ and CD45+MHCII+ cells compared to hP-hF3 and hPIB in U87 GBM cells. (Supporting Main Figure 7)
Supplementary Figure 7 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 7. Intermittent CKI27 treatment and GITR co-stimulation relieves expression of co-stimulatory markers. Representative dot plot data for FACS analysis of co-stimulatory markers expressed by CD8+ T cells.
Table S2 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

Primer list for quantitative PCR & ChIP.
Supplemental Figure 4 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) Violin plots showing quality metrics of single cells included in downstream analysis. nCount RNA: number of RNA unique molecular identifiers (UMI); nFeature RNA: number of detected genes; nCount_ADT: number of antibody UMI; nFeature_ADT: number of detected antibodies; percent.mt: percentage of mitochondrial gene expression; HTO_margin: difference between signals for the hashtag with the highest signal and the hashtag with the second highest signal. (B) (C) Weighted-nearest neighbor (WNN) UMAP of single cells colored by condition (CAR T cell construct and timepoint) (top) and CD4+ vs CD8+ cell type (bottom). Expression of T cell markers (CD3, CD4, and CD8) at the RNA (top) and antibody-derived tag (ADT) level projected on WNN UMAPs. (D) Expression of the RNA (top) and ADT (bottom) markers of T cell type, proliferation, activation, cytotoxicity, and cytokines support CITE-seq cluster annotation. Blue is control CAR T cell and Red is LIGHT-CAR T cell.
Data 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

Abstract
Immunotherapy has limited efficacy in glioblastoma (GBM) due to the blood–brain barrier and the immunosuppressed or “cold” tumor microenvironment (TME) of GBM, which is dominated by immune-inhibitory cells and depleted of CTL and dendritic cells (DC). Here, we report the development and application of a machine learning precision method to identify cell fate determinants (CFD) that specifically reprogram GBM cells into induced antigen-presenting cells with DC-like functions (iDC-APC). In murine GBM models, iDC-APCs acquired DC-like morphology, regulatory gene expression profile, and functions comparable to natural DCs. Among these acquired functions were phagocytosis, direct presentation of endogenous antigens, and cross-presentation of exogenous antigens. The latter endowed the iDC-APCs with the ability to prime naïve CD8+ CTLs, a hallmark DC function critical for antitumor immunity. Intratumor iDC-APCs reduced tumor growth and improved survival only in immunocompetent animals, which coincided with extensive infiltration of CD4+ T cells and activated CD8+ CTLs in the TME. The reactivated TME synergized with an intratumor soluble PD1 decoy immunotherapy and a DC-based GBM vaccine, resulting in robust killing of highly resistant GBM cells by tumor-specific CD8+ CTLs and significantly extended survival. Lastly, we defined a unique CFD combination specifically for the human GBM to iDC-APC conversion of both glioma stem-like cells and non–stem-like cell GBM cells, confirming the clinical utility of a computationally directed, tumor-specific conversion immunotherapy for GBM and potentially other solid tumors.
Data 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

Abstract
Interleukin 2 (IL-2) is a crucial cytokine in T-cell immunity, with a promising potential in cancer vaccines. However, therapeutic application of IL-2 is hampered by its short half-life and substantial toxicity. This study reports preclinical characterization of a mouse serum albumin–IL-2 fusion protein (Alb–IL2) encoded on nucleoside-modified RNA that is delivered via a nanoparticle formulation (Alb–IL2 RNA-NP) mediating prolonged cytokine availability. Alb–IL2 RNA-NP was combined with RNA-lipoplex (RNA-LPX) vaccines to evaluate its effect on the expansion of vaccine-induced antigen specific T-cell immunity. In mice dosed with Alb–IL2 RNA-NP, translated protein was shown to be systemically available up to 2 days, with an albumin-dependent preferred presence in the tumor and tumor-draining lymph node. Alb–IL2 RNA-NP administration prolonged serum availability of the cytokine compared with murine recombinant IL-2. In combination with RNA-LPX vaccines, Alb-IL2 RNA-NP administration highly increased the expansion of RNA-LPX vaccine–induced CD8+ T cells in the spleen and blood. The combination enhanced and sustained the fraction of IL-2 receptor (IL-2R) α-positive antigen-specific CD8+ T cells and ameliorated the functional capacity of the CD8+ T-cell population. Alb–IL2 RNA-NP strongly improved the antitumor activity and survival of concomitant RNA-LPX vaccination and PD-L1 blockade in a subcutaneous mouse tumor model. The favorable pharmacokinetic properties of Alb–IL2 RNA-NP render it an attractive modality for rationally designed combination immunotherapy. RNA vaccines that induce tumor-specific T-cell immunity for Alb–IL2 RNA-NP to further amplify are particularly attractive combination partners.
Investigation and Characterization of the RAS/RAF/MEK/ERK Pathway and Other Signaling Pathways in Chronic Sinusitis with Nasal Polyps
Authors: Niu Zhipu , Sha Jichao , Zhu Dongdong , Meng Cuida
Published: October 2024

Background: The clinical outcomes of drug treatments and surgical interventions for chronic sinusitis with nasal polyps (CRSwNPs) are suboptimal, and the high recurrence rate remains a significant challenge in clinical practice. Targeted therapies such as biologics provide new perspectives and directions for treating CRSwNP. Summary: With the continuous investigation of signaling pathways, RAS/RAF/MEK/ERK signaling pathway and other signaling pathways including Hippo, JAK-STAT, Wnt, TGF-β, PI3K, Notch, and NF-κB were confirmed to play an important role in the progression of CRSwNP. Among them, the abnormality of RAS/RAF/MEK/ERK signaling pathway is accompanied by the abnormality of this apoptotic component, which may provide new research directions for targeting the components of signaling pathways to mediate apoptosis. Key Messages: Abnormalities in signaling pathways are particularly important in studying the pathogenesis and treatment of CRSwNP. Therefore, this review summarizes the ongoing investigation and characterization of RAS/RAF/MEK/ERK signaling pathway and other signaling pathways in CRSwNP, which provides constructive ideas and directions for improving the treatment of CRSwNP.
Impacts of electric vehicle charging stations and DGs on RDS for improving voltage stability using honey badger algorithm
Authors: Thiruveedula Madhubabu , Asokan K. , Subrahmanyam JBV
Published: October 2024

The intelligent computational technique used in this research handles the multi-objective voltage stability optimization (MOVSO) problem in radial distribution systems (RDS). The objectives of the proposed research are to minimize network loss, lower the average voltage deviation index (AVDI), and improve the voltage stability index (VSI) of RDS by taking into account the recently created distributed generators (DGs) and electric vehicle charging stations (EVCSs). To address the MOVSO problem, a novel and innovative honey badger algorithm (HBA) optimization technique is put forth. The two stages of HBA, known as the "digging" and "honey" phases, are responsible for effectively identifying the ideal position and appropriate quantity of EVCSs and DGs. The standard IEEE 33 node test system with different case studies is considered to validate the performance of HBA. The simulation results of improved voltage profile, minimized power loss, AVDI and improved VSI are tabulated. The proposed HBA fine-tunes the ideal position and size of the EVCSs to significantly enhance RDS performance under higher loading circumstances. To demonstrate the efficacy and originality of the suggested HBA, the numerical results are contrasted with those of earlier soft computing techniques.
Advanced control and optimization strategies for a 2-phase interleaved boost converter
Authors: Samad Muhammad Adnan , Yulbarsovich Usmonov Shukurillo , Anvarjon Ugli Sultonov Ruzimatjon , Siddiqui Saima
Published: October 2024

Renowned for their adeptness in smoothing current flow and maintaining balanced operation, 2-phase interleaved boost converters (IBC) demonstrate remarkable efficiency, especially when confronted with demanding loads. This makes them a preferred choice for high-power applications such as renewable energy systems, high-power supplies, and electric vehicle power trains. In contrast, standard boost converters are typically favored in low-power, low-demand scenarios. The control of a 2-phase IBC involves running two boost converters in parallel but with a phase shift to reduce ripple currents, improve efficiency, and increase power handling capabilities. To ensure stability and optimal performance, the control strategies for these converters focus on achieving balanced operation between the phases. Hence, the control of 2-phase IBC presents a significant challenge due to their non-minimum phase behavior. The core focus of this article is the implementation of a composite model predictive control (MPC) technique to regulate a 2-phase interleaved boost converter. It introduces a novel approach, model predictive sliding mode control (MPSMC), which leverages the strengths of both MPC and sliding mode control (SMC). The benefits of this hybrid method, termed MPSMC, are thoroughly developed and simulated using MATLAB/Simulink. The results, as discussed in the respective section, provide an in-depth understanding of its effectiveness in practical applications.
Improve fractal interpolation function with Sierspinski triangle
Authors: Susanti Eka , Puspita Fitri Maya , Supadi Siti Suzlin , Yuliza Evi , Fadhila Chaniago Redina An
Published: October 2024

Interpolation techniques can be used to determine the approximate value of a parameter if it is known that two values are bound to a certain interval. Interpolation can be done numerically or fractal. The fractal interpolation value is influenced by the vertical scale factor and the fractal interpolation function (FIF). This research introduces fractal interpolation technique with FIF which is constructed from Sierspinski triangles. As an example of application, the interpolation technique is applied to determine the approximate value of the rice demand parameter in the inventory model. The accuracy of the interpolation results is determined using the mean absolute percentage error (MAPE). The number of triangles obtained and the interpolation values for each successive iteration are 3𝑛 and 3𝑛+1. MAPE values from 6 to 9 iteration were 24.603%, 24.603%, 23.858%, 23.772% respectively. There is a decrease in the value of MAPE, this indicates an increase in the value of the accuracy of the interpolation results. It can be concluded that the MAPE value is also influenced by the number of iterations of the interpolation technique.
Plant disease classification using novel integration of deep learning CNN and graph convolutional networks
Authors: Maheswara Rao Saka Uma , Sreekala Keshetti , Rao Pulluri Srinivas , Shirisha Nalla , Srinivas Gunnam , Sreedevi Erry
Published: October 2024

Plant diseases present substantial challenges to global agriculture, significantly affecting crop yields and jeopardizing food security. Accurate and timely detection of these diseases is paramount for mitigating their adverse effects. This paper proposes a novel approach for plant disease classification by integrating convolutional neural networks (CNNs) and graph convolutional networks (GCNs). The model aims to enhance classification accuracy by leveraging both visual features extracted by CNNs and relational information captured by GCNs. Using a Kaggle dataset containing images of diseased and healthy plant leaves from 31 classes, including apple, corn, grape, peach, pepper bell, potato, strawberry, and tomato. Standalone CNN models were trained on image data from each plant type, while standalone GCN models utilized graph-structured data representing plant relationships within each subset. The proposed integrated CNN-GCN model capitalizes on the complementary strengths of CNNs and GCNs to achieve improved classification performance. Through rigorous experimentation and comparative analysis, the effectiveness of the integrated CNN-GCN approach was evaluated alongside standalone CNN and GCN models across all plant types. Results demonstrated the superiority of the integrated model, highlighting its potential for enhancing plant disease classification accuracy.
An efficient convolutional neural network for adversarial training against adversarial attack
Authors: Vaddadi Srinivas A. , Somanathan Pillai Sanjaikanth E. Vadakkethil , Addula Santosh Reddy , Vallabhaneni Rohith , Ananthan Bhuvanesh
Published: October 2024

Convolutional neural networks (CNN) are widely used by researchers due to their extensive advantages over various applications. However, images are highly susceptible to malicious attacks using perturbations that are unrecognized even under human intervention. This causes significant security perils and challenges to CNN-related applications. In this article, an efficient adversarial training model against malevolent attacks is demonstrated. This model is highly robust to black-box malicious examples, it is processed with different malicious samples. Initially, malicious training models like fast gradient descent (FGS), recursive-FGSM (I-FGS), Deep-Fool, and Carlini and Wagner (CW) techniques are utilized that generate adversarial input by means of the CNN acknowledged to the attacker. In the experimentation process, the MNIST dataset comprising 60K and 10K training and testing grey-scale images are utilized. In the experimental section, the adversarial training model reduces the attack accuracy rate (ASR) by an average of 29.2% for different malicious inputs, when preserving the accuracy of 98.9% concerning actual images in the MNIST database. The simulation outcomes show the preeminence of the model against adversarial attacks.
Pneumonia stage analyzes through image processing
Authors: Chowdhury Nishu , Choudhury Pranto Protim , Moon Shatabdi Roy
Published: October 2024

A physical examination and diagnostic imaging techniques including lung biopsies, ultrasounds, and chest X-rays are typically used to make the diagnosis of pneumonia infection, an infectious disease that has the potential to be life-threatening. The objective of this research is to categorize the stages of pneumonia through image processing methods. Before that, an ensemble model for diagnosing pneumonia infections is created utilizing the transfer learning algorithms ResNet50V2 and DenseNet201. The 5,857 images were taken from the PAUL MOONEY dataset for this research. The proposed ensemble averaging model recognizes lung infection appropriately and accurately. By applying a contour detection approach, the left and right chests are separated and the affected pixels from there to analyze the stage of pneumonia. It is very crucial to identify the stage for treatment purposes.
Dynamic long short-term memory model for enhanced product recommendations in e-commerce
Authors: Bhogan Snehal , Rajpurohit Vijay S. , Sannakki Sanjeev S.
Published: October 2024

Recommendation systems are pivotal for personalized user experiences, employing algorithms to predict and suggest items aligned with user preferences. Deep learning (DL) models, such as recurrent neural networks (RNNs) and long short-term memory networks (LSTMs), excel in capturing sequential dependencies, enhancing recommendation accuracy. However, challenges persist in session-based recommendation systems, particularly with gradient descent and class imbalances. Addressing these challenges, this work introduces dynamic LSTM (D-LSTM), a novel DL-based recommendation system tailored for dynamic E-commerce environments. The primary objective is to optimize recommendation accuracy by effectively capturing temporal dependencies within user sessions. The methodology involves the integration of D-LSTM with weight matrix optimization and a Bayesian personalized ranking (BPR) adaptable learning rate optimizer to enhance learning efficiency. Experimental results demonstrate the efficacy of D-LSTM, showing significant improvements over existing models. Specifically, comparisons with the hybrid time-centric prediction (HTCP) model reveal a performance enhancement of 19.4%, 17.2%, 35.41%, and 21.99% for hit-rate (HR) and mean reciprocal rank (MRR) in 10k and 20k recommendation sets using the Tmall dataset. These findings underscore the superior performance of D-LSTM, highlighting its potential to advance personalized recommendations in dynamic E-commerce settings.
A multi-criteria trust-enhanced collaborative filtering algorithm for personalized tourism recommendations
Authors: Shambour Qusai Y. , Al-Zyoud Mahran M. , Alsaaidah Adeeb M. , Abualhaj Mosleh M. , Abu-Shareha Ahmad A.
Published: October 2024

The exponential growth of online information has LED to significant challenges in navigating data overload, particularly in the tourism industry. Travelers are overwhelmed with choices regarding destinations, accommodations, dining, and attractions, making it difficult to select options that best meet their needs. Recommender systems have emerged as a promising solution to this problem, aiding users in decision-making by providing personalized suggestions based on their preferences. Traditional collaborative filtering (CF) methods, however, face limitations, such as data sparsity and reliance on single rating scores, which do not fully capture the complexity of user preferences. This study proposes a hybrid multi-criteria trust-enhanced CF (HMCTeCF) algorithm to improve the accuracy and robustness of tourism recommendations. HMCTeCF improves the quality of recommendations by integrating multi-criteria user preferences with trust relationships among users and between items. Experimental results using real-world datasets, including Restaurants-TripAdvisor and Hotels-TripAdvisor, demonstrate that HMCTeCF outperforms benchmark CF-based recommendation methods. It achieves higher prediction accuracy and coverage rate, effectively addressing the data sparsity problem. This innovative algorithm facilitates a more personalized and enriching travel experience, particularly in scenarios with limited user data. The findings highlight the importance of considering multiple criteria and trust relationships in developing robust recommendation systems for the tourism industry.
Data mining implementation: a survey
Authors: Widayat Wisnu , Assiroj Priati , Sohirin Sohirin , Prabadhi Isidorus Anung , Kautsar Pasha Adelia
Published: October 2024

In the current era, the relentless advancement of information technology necessitates efficient information acquisition, which relies on proper data processing. To address the challenges in data organization, data mining emerges as a pivotal solution. This study aims to delve into various methodologies for data grouping. Employing a survey approach, the research scrutinizes journals published from 2020 to 2024. The findings illuminate prevalent techniques, algorithms, and software tools utilized in similar research domains. Notably, the study reveals that the predominant approach entails clustering via K-Means leveraging RapidMiner. This insight underscores the significance of employing robust methodologies and tools to streamline data processing and analysis in the contemporary information landscape. By elucidating the prevalent techniques and tools, this study contributes to enhancing understanding and fostering advancements in data mining practices, thereby facilitating more efficient data utilization and decision-making processes.
INVESTIGATION OF BLUE ECONOMY AND ITS IMPACT ON GLOBAL MARITIME TRANSPORTATION
Authors: Usluer Hasan Bora
Published: October 2024

According to sustainability, the Strategy to protect the oceans, water surfaces, and water resources that constitute 70% of the world is generally called a Blue Economy (BE). This Strategy maximizes the return from the aquatic environment, which can only be achieved when economic activity is perfectly balanced with the long-term activity of ocean ecosystems. Threats arising during and after studies and activities should be anticipated and actively reduced. This proactive stance is fundamental to the Blue Economy philosophy and allows us to reap its benefits while protecting our oceans. One of the most essential elements of the Blue Economy philosophy is maritime transportation, Ships, and Ports. The maritime industry should remain sustainable and green as it develops. The study investigated the impact of the Blue Economy on maritime transportation and how maritime transportation affects world trade.
The Ethiopian State, Foreign Policy and Participation in International Peacekeeping: Continuities and Changes
Authors: Belay Yeshiwas Degu
Published: October 2024

This article examines the continuities and changes in Ethiopian peacekeeping practices since its inception in the early 1950s to the present. It focuses on how international operations have interacted with historical, structural and ideational factors to shape Ethiopia’s involvement. Drawing on archival sources, policy papers, and media material as well as interviews with officials in Ethiopia, it singles out four distinct periods that have influenced Ethiopia’s participation in peacekeeping mission. It shows that all were characterised by the interplay between geopolitical factors, regional developments in Africa and domestic political changes. By identifying the major shifts in Ethiopia’s foreign policy orientation and involvement in peacekeeping, the article seeks to explain the rise of Ethiopia as a major actor in international peacekeeping since the early 2000s. It concludes by highlighting uncertainties facing Ethiopian peacekeeping due to regional complexities and political constraints resulting from internal conflicts.
Improving the Safety of UN Peacekeepers through Data-Driven Training
Authors: Garinther Alexander , Meehan Nathan
Published: October 2024

Peace operations personnel are often targeted while on mission by armed groups and individual actors seeking to cause harm. This paper outlines recent events driving force-protection concerns, analyzes trends in peacekeeper fatalities, and proposes steps for improving force-protection research and training in the future. Among our recommendations are continued efforts to monitor and evaluate the experiences of peacekeeping personnel, including but not limited to violent incidents on mission that result in fatalities to peacekeepers or civilians. With that, broadening access to anonymized incident data from the field would facilitate both research and training teams and ultimately allow troop contributing countries (tcc s) to better target the specific needs of their deployed units. Our recommendations are built upon a decade of experience providing pre-deployment force protection training to tcc s through the Identifying Threats in Peacekeeping Environments program. The best way to help personnel stay safe on mission is through an understanding of current trends in the field; improving access to incident data would dramatically help stakeholders understand the points of impact for peacekeeper safety so they can ultimately help deployed personnel stay safe.
First record of the genus Palpostilpnus Aubert (Ichneumonidae: Phygadeuontinae) from Vietnam, with descriptions of eight new species
Authors: PHAM NHI THI , SHENG MAO-LING , PARK CLARA , TRAN DUONG DINH , RESHCHIKOV ALEXEY
Published: October 2024

Palpostilpnus Aubert, 1961 is a genus of the subfamily Phygadeuontinae (Hymenoptera: Ichneumonidae) with 17 currently recognized species from the Oriental and Australasian regions. In this paper, this genus is reported for the first time from Vietnam. Eight new species are described, comprising: P. cattienensis, P. hoanglienensis, P. incompletus, P. melanothoracicus, P. melinhensis, P. meovacensis, P. ngoclinhensis and P. taynguyenensis. Three species, P. maculata Sheng & Sun, 2013, P. pterodactylus Reshchikov, Santos, Liu, Barthélémy, 2019 and P. tamasek Reshchikov, Santos, Liu, Barthélémy, 2019 are recorded as new from the country. The key to the world species of Palpostilpnus by Reshchikov et al. (2019) is modified to include eight new species from Vietnam.
“I’m Going to Vote for the First Time in My Life this Year”: Native American Political Engagement in the Trump Era
Authors: Hrabik Lynette , Horsting Trudy , Ignacio Matt , Gresenz Kyle , Gonzales Angela A.
Published: October 2024

During the 2020 election, Arizona voted Democratic for the first time in decades and contributed to Joe Biden’s presidential win. Native Americans, predominantly young adults, turned out in record numbers and were credited as one of the key demographic groups that “flipped” Arizona blue. What drove young Native voters to engage during this election cycle? Using data from the Arizona Youth Identity Project, a multi-wave mixed-methods study, we analyzed interviews with 38 self-identified Native American participants ages 18–29 to understand the factors motivating their political engagement in the 2020 Presidential election. Findings reveal that young Native adults in Arizona were motivated by (1) targeted political organizing, outreach, and advocacy efforts, (2) increased positive attitudes toward voting, and (3) a desire for political and social change. These findings enhance our collective understanding of the motivations behind Native American voter engagement.
Enhancing Precision in Predicting Magnitude of Differential Item Functioning: An M-DIF Pretrained Model Approach
Authors: Huang Shan , Ishii Hidetoki
Published: October 2024

Despite numerous studies on the magnitude of differential item functioning (DIF), different DIF detection methods often define effect sizes inconsistently and fail to adequately account for testing conditions. To address these limitations, this study introduces the unified M-DIF model, which defines the magnitude of DIF as the difference in item difficulty parameters between reference and focal groups. The M-DIF model can incorporate various DIF detection methods and test conditions to form a quantitative model. The pretrained approach was employed to leverage a sufficiently representative large sample as the training set and ensure the model’s generalizability. Once the pretrained model is constructed, it can be directly applied to new data. Specifically, a training dataset comprising 144 combinations of test conditions and 144,000 potential DIF items, each equipped with 29 statistical metrics, was used. We adopt the XGBoost method for modeling. Results show that, based on root mean square error (RMSE) and BIAS metrics, the M-DIF model outperforms the baseline model in both validation sets: under consistent and inconsistent test conditions. Across all 360 combinations of test conditions (144 consistent and 216 inconsistent with the training set), the M-DIF model demonstrates lower RMSE in 357 cases (99.2%), illustrating its robustness. Finally, we provided an empirical example to showcase the practical feasibility of implementing the M-DIF model.
Naming Jesus in Matthew 28
Authors: O’Collins Gerald
Published: October 2024

The Easter narrative of Matthew 28, unlike those of Luke 24 and John 20 and 21, does not refer to the Risen One as ‘Lord’. Unlike Luke 24, it does not call him ‘Son of Man’. While once naming him as Son (in a baptismal formula), Matthew 28 five times calls him ‘Jesus’. This is the personal name which the evangelist explained in his opening chapter, the name which held together the teaching, healing, and other activity of Jesus’ ministry, and which unified the final Easter chapter. Up to Chapter 27, Matthew has cited the Scriptures to illuminate the ministry of Jesus. Now the Scriptures fall silent; the risen Jesus speaks for himself, the divine Emmanuel (Matt 1:23) who accompanies the Church on her universal mission. He will be ‘with’ his community until the end of history (Matt 28:20).
The Effects of Telerehabilitation-Based Exercise Therapy on Motor and Non-Motor Clinical Outcomes in Adults With Facial Palsy: A Randomized Controlled Trial
Authors: Özden Fatih , Golcuk Yalcin , Tümtürk İsmet , Özkeskin Mehmet
Published: October 2024

Recent case reports have emphasized the essential clinical contribution of telerehabilitation in the treatment of facial palsy. However, no randomized controlled trial has yet demonstrated the effects of telerehabilitation-based facial exercise therapy. Thus, we aimed to investigate the effectiveness of video exercise-based telerehabilitation on motor and non-motor clinical outcomes in adults with facial palsy. We conducted a randomized controlled trial with 40 peripheral facial palsy patients. Those in the experimental group (EG) received four weeks of telerehabilitation-based video exercises and routine care. Those in the control group (CG) received only routine care. All participants were evaluated with the Facial Disability Index (FDI), the Facial Clinimetric Evaluation Scale (FaCE), Short Form-12 (SF-12), the Hospital Anxiety and Depression Scale (HADS), the House-Brackmann Scale (H-B) and the Telemedicine Satisfaction and Usefulness Questionnaire (TSUQ), both before and after the interventions. Both groups demonstrated a significant improvement in FDI, FaCE, and SF-12 PCS scores ( p < .05). In addition, there was a significant improvement only in EG on the SF-12 MCS score ( p < .05), and there was a significant gain only in CG on the HADS-Depression score ( p < .05). While these results provide a further contribution to our understanding of telerehabilitation benefits in mental health variables related to quality of life for facial palsy patients, we found no EG and CG differences on the physical components of treatment.
Meeting practitioners where they are: A conversation on engaged learning in policy and management
Authors: Macaulay Michael , Ormston Christianne
Published: October 2024

Our paper is a practitioner reflection that explores the concepts of engaged learning as a means of erasing the specious divide between academia and policy/management practice. It takes the form of a conversation between the two authors, each of whom have significant experience in both camps, but who also would seem to fall more neatly into one than the other. The paper outlines our experiences in professional development, with an emphasis on a specific series of organisational trust workshops, which use an ‘embodied values’ approach so that learning outcomes are built into the structure and process of the session rather than just in content. We utilise a conversational approach as this enables us to expand on broader themes as well as draw on our experiences. More importantly, it also is redolent of the embodied values approach and demonstrates the types of shared learning we seek to promote as useful for the future.
Driving Difficulties and Coping Strategies in Persons With Homonymous Quadrantanopia or Homonymous Scotoma
Authors: Wallace-Carrete Chris , Baker Patrick , Bowers Alex R. , Xu Jing
Published: October 2024

Introduction: This study, conducted in the United States, investigated the challenges faced by drivers with homonymous visual field loss and their coping strategies, including the use of in-vehicle Advanced Driver Assistance Systems (ADAS). Methods: Four current drivers with either homonymous quadrantanopia or homonymous scotoma caused by a stroke completed an in-depth semi-structured telephone interview. Using mostly open-ended questions, the interview addressed the difficulties encountered while driving, strategies used to cope with the difficulties, and the use of ADAS. Results: The main difficulties related to seeing objects on the side of the field loss, especially at intersections and when merging or changing lanes. Individuals with left-sided field loss reported problems with left turns and seeing oncoming cars at intersections. Those who had homonymous scotomas described how cars disappeared in and out of the scotoma. Two participants reported many driving difficulties at first, but fewer difficulties as they became used to driving with the field loss. The most common coping strategies included scanning to the side of the field loss (including large scans with head movements), use of rearview and side mirrors, adding mirrors to the car, leaving more space on the side of the field loss, avoiding difficult driving situations and the use of ADAS (blind spot warning, GPS navigation, and rearview camera). Discussion: All participants reported some difficulties consistent with those found in on-road and driving simulator studies of individuals with homonymous visual field loss. Over time they each reported developing a set of strategies, including the use of ADAS, for coping with the field loss that enabled them to be active drivers with relatively few self-imposed restrictions. Implications for Practitioners: Advising drivers with stroke-related field loss about potential difficulties and compensatory strategies is an important part of preparation for return to driving. This article provides examples of problem situations, coping strategies, and ADAS use which can be used to guide discussion.