bluuebunny/crossref_metadata_2025 huggingface dataset:
Figure S3 from NK Receptor Signaling Lowers TCR Activation Threshold, Enhancing Selective Recognition of Cancer Cells by TAA-Specific CTLs
Authors: Dong Bowen , Obermajer Nataša , Tsuji Takemasa , Matsuzaki Junko , Bonura Cindy M. , Sander Cindy , Withers Henry , Long Mark D. , Chavel Colin , Olejniczak Scott H. , Minderman Hans , Kirkwood John M. , Edwards Robert P. , Storkus Walter J. , Romero Pedro , Kalinski Pawel
Published: October 2024

DC-primed MART-1-specific CTLs express high levels of NKRs, but recognize and kill cancer cells in a strictly TCR-dependent manner.
Figure S1 from NK Receptor Signaling Lowers TCR Activation Threshold, Enhancing Selective Recognition of Cancer Cells by TAA-Specific CTLs
Authors: Dong Bowen , Obermajer Nataša , Tsuji Takemasa , Matsuzaki Junko , Bonura Cindy M. , Sander Cindy , Withers Henry , Long Mark D. , Chavel Colin , Olejniczak Scott H. , Minderman Hans , Kirkwood John M. , Edwards Robert P. , Storkus Walter J. , Romero Pedro , Kalinski Pawel
Published: October 2024

DNAM-1 and NKG2D expression is correlated with long term survival and cytotoxic genes in tumor samples from melanoma patients (TCGA).
Figure S10 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

Contour plots showing myeloid and T cell populations.
Figure S10 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

Representative dot plots corresponding to flow cytometry data displayed in Figure 5.
Supplemental Table S1 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

False discovery rate (FDR) of 3 filtration methods employed by GeneRep compared to ARACNe to 6 cancer types in TCGA (Supporting the Materials and Methods Section)
Supplemental Figure S7 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

Morphological changes of the murine GBM cells GL261 reprogrammed with dP-mF3. (Supporting Main Figure 1E)
Supplemental Figure S23 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 iDC-APCs induced by PU.1 plus IKZF1 (PI) exhibit DC-like phenotypes. (Supporting Main Figure 7)
Supplemental Figure S18 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

PI expression did not induce expression B and T cell markers in LN428, LN827 and LN308 GBM cells. (Supporting Main Figure 7)
Figure S8 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

Representative images of HIF-1α, HLA-ABC, and HIF1A-AS2 in the stroma, epithelium, and tumor part of a HNSCC sample.
Supplementary Figure 14 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 14. The triple combination increases activation of CD8+ T cells and CD4+ Teffs while destabilizing Tregs in CT26 tumor. (A) Schema of CT26 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) Tumor weights, numbers of cells/mg, and CD8:Treg ratio 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).
Supplementary Figure S8 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 S8. NK-92 cells with FBXO38 overexpression show enhanced antitumor activity in vivo
Data 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

Abstract
MEK inhibitors (MEKi) have shown limited success as a treatment for MAPK/ERK pathway–dependent cancers due to various resistance mechanisms tumor cells can employ. CH5126766 (CKI27) is an inhibitor that binds to MEK and prevents release of RAF, reducing the relief of negative feedback commonly observed with other MEKis. We observed that CKI27 increased MHC expression in tumor cells and improved T cell–mediated killing. Yet, CKI27 also decreased T-cell proliferation, activation, and cytolytic activity by inhibiting the MAPK/ERK pathway that is activated downstream of T-cell receptor signaling. Therefore, we aimed to balance the positive and negative immunomodulatory effects of MEKis for optimal combination with immunotherapy. Intermittent administration of CKI27 allowed T cells to partially recover and costimulation via GITR and OX-40 agonist antibodies completely alleviated inhibition of function. In Kras mutant lung and colon tumor mouse models, intermittent CKI27 and anti-GITR significantly decreased tumor growth and prolonged survival when further combined with CTLA-4 immune checkpoint blockade. Moreover, this triple combination increased CD8+ and CD4+ T-cell proliferation, activation, and effector/memory subsets in the tumor-draining lymph nodes and tumors and led to intratumoral regulatory T-cell destabilization. These data, collectively, will allow for more informed decisions when optimizing combination regimens by overcoming resistance, reducing toxicity, and generating long-term immune responses.
Supplementary Figure S5 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 S5 compares the natural history growth of Calu6 and U87 xenografts.
Supplementary Figure S4 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 Figure S4. Repeatability and reproducibility of SPR assay in detecting exosomal TF-Ag-α. The levels of exosomal TF-Ag-α in serum samples from one normal control, one lung cancer patient and one breast cancer patient were measured by operator 1 (a) and operator 2 (b) on 3 different days, 3 replicates per day. The mean, standard deviation, and coefficient of variation (CV) were reported. (c) Pearson correlation of results from operator 1 and operator 2.
Battery charging system for electric vehicle
Authors: Kotmire Nayan J. , Kakade Anandrao B.
Published: October 2024

Selecting the appropriate charger for electric vehicles (EVs) is crucial for enhancing performance, with non-isolated DC-DC converters playing a significant role in charging EV batteries. The efficient conversion of input power into output as per the requirement is main perspective in the design of DC-DC converters. This paper delves into the landscape of non-isolated DC-DC converters utilized in EV charging, emphasizing their pivotal role. Additionally, it introduces a novel approach by incorporating machine learning-based pulse width modulation (PWM) control for the buck DC-DC converter. By integrating machine learning algorithms into the control scheme, the efficiency and performance of the charging system can be greatly enhanced, resulting in improved overall EV operation. This innovative application of machine learning not only optimizes charging efficiency but also enables adaptability to varying input/output conditions, ultimately leading to more efficient and effective charging processes for EVs.
Efficient deep learning models for Telugu handwritten text recognition
Authors: Revathi Buddaraju , Raju B. N. V. Narasimha , Rama Krishna Boddu L. V. Siva , Kumar Marapatla Ajay Dilip , Saripalle S. Suryanarayanaraju
Published: October 2024

Optical character recognition (OCR) technology is indispensable for converting and analyzing text from various sources into a format that is editable and searchable. Telugu handwriting presents notable challenges due to the resemblance of characters, the extensive character set, and the need to segment overlapping characters. To segment the overlapping characters, we assess the width of small characters within a word and segment the overlapping characters accordingly. This method is well suited for the segmentation of overlapping compound characters. To address the recognition of similar characters with less training periods we have used ResNet 18 and SqueezeNet models which have achieved character recognition rates of 95% and 94% respectively.
Identification and characterisation of earthquake clusters from seismic historical data
Authors: Markhaba Karmenova , Aizhan Tlebaldinova , Karlygash Alibekkyzy , Zheniskul Zhantassova , Indira Karymsakova
Published: October 2024

New approaches and methods based on machine learning technologies make it possible to identify not only the spread of earthquakes, but also to establish hidden patterns that allow further assessment of any risks associated with their occurrence. In this article, the clustering algorithms of K-means and K-medoids are applied for the analysis of seismic data recorded on the territory of the Republic of Kazakhstan. Using the Elbow and Silhouette methods, the optimal value of K clusters was determined, which was later used in classifying a data set using cluster analysis methods. The results of seismic data classification by clustering algorithms are in line with expectations. However, when measuring the quality of clustering, the accuracy of the model by the K-means method exceeded the accuracy of the K-medoids model, and the scoring value by the K-means method is ahead of the value by the K-medoids method. In addition, the presented results of descriptive statistics allowed to carry out a more in-depth analysis of the characteristics of each cluster.
Developed improved lion optimization for breast cancer classification using histopathology images
Authors: Ali Khan Pattan M. D. , Rathina Xavier Arputha
Published: October 2024

Breast cancer, a prevalent kind of cancer, is a major health problem among women. Researchers recently achieved categorization effectiveness of breast cancer (BC) detection in histopathology picture database using convolutional neural networks (CNNs) of medical image processing. Although CNN method parameter settings were complex, employing breast cancer histopathological database (BCHD) data for categorization was valued as expensive. This research used uniform experimental design (UED) to solve these issues and improved lion optimization (ILO) breast cancer histopathology image categorization. To optimize the variables at UED-ILO, a regression method was employed. According to the experimental data, the proposed approach of UED-ILO (uniform experimental design based improved lion optimization) variable optimization provided a categorization accuracy rate of 84.41%. Finally, the proposed approach can effectively increase classification accuracy, with results that outperform others of an equivalent nature.
Transfer learning based leaf disease detection model using convolution neural network
Authors: Raut Rahul , Bidve Vijaykumar , Sarasu Pakiriswamy , Kakade Kiran Shrimant , Shaikh Ashfaq , Kediya Shailesh , Borde Santosh , Pakle Ganesh
Published: October 2024

The plants are attacked from various micro-organisms, bacterial illnesses, and pests. The signs are normally identified via leaves, stem, or fruit inspection. Illnesses that generally appeared on vegetation are from leaves and causes big harm if not managed in the early ranges. To stop this huge harm and manipulate the unfold of disorder this work implements a software system. This research work customs deep neural network to gain knowledge of probable illnesses on leaves within the early phases so it can be stopped early. Deep neural network (DNN) used for image classification. This work mainly focuses a neural network model of leaves ailment detection. The commonly available plant leaves dataset is undertaken with a dataset having special training of disease detection. In this work VGG16, ResNet50, Inception V3 and Inception ResNetV2 architectural techniques are implemented to generate and compare the results. Results are compared on the factors like precision, accuracy, recall and F1-Score. The results lead to the conclusion, that the convolution neural network (CNN) is more impactful technique to perceive and predict plant diseases.
Hybrid feature selection of microarray prostate cancer diagnostic system
Authors: Ali Nursabillilah Mohd , Hanafi Ainain Nur , Karis Mohd Safirin , Shamsudin Nur Hazahsha , Shair Ezreen Farina , Abdul Aziz Nor Hidayati
Published: October 2024

DNA microarray prostate cancer diagnosis systems are widely used, and hybrid feature selection methods are applied to select optimal features to address the high dimensionality of the dataset. This work proposes a new hybrid feature selection method, namely the relief-F (RF)-genetic algorithm (GA) with support vector machine (SVM) classification method. The aim is to evaluate the performance of the proposed method in terms of accuracy, computation time, and the number of selected features. The method is implemented using Python in PyCharm and is evaluated on a DNA microarray prostate cancer. The outcome of this work is a performance comparison table for the proposed methods on the dataset. The performance of GA, particle swarm optimization (PSO), and whale optimization algorithm (WOA) is compared in terms of accuracy, computation time, and the number of selected features. Results show that GA has the highest average accuracy (91.17%) compared to PSO (90.52%) and WOA (85.74%). GA outperforms PSO and WOA due to its superior convergence properties and better alignment with complex problems.
Utilizing minimum spanning trees for effective mobile sink routing in wireless sensor networks
Authors: Taleb Anas Abu , Odeh Ammar
Published: October 2024

With many practical applications, wireless sensor networks (WSNs) represent an important field of study. Real-world applications of WSNs include smart home automation, healthcare, agriculture, industrial automation, and environmental monitoring. WSNs present countless chances for creative solutions across various industries as they develop and become more sophisticated. But because they are unattended, we must devise ways to make them work better without using the sensor nodes’ most important resource—battery power. A unique sink mobility model from a deployed WSN is proposed in this paper, based on constructing a minimal Spanning tree. The proposed approach derives a controlled movement model for the mobile sink based on minimal spanning tree (MST) features. Consequently, fixed nodes will be scheduled and visited to save routing overhead and improve network efficiency. Using the properties of the minimal spanning tree, the moving sink node can visit immobile sensor nodes, which is the most effective approach to gather data and send it to the base station. The effectiveness of WSNs was examined when implementing this mobility model, and we used the NS-2 simulator to run simulations to assess how efficiently the suggested strategy performed. Our findings demonstrate that WSN performance can be significantly enhanced by implementing the proposed method.
Optimized deep neural network based vulnerability detection enabled secured testing for cloud SaaS
Authors: Vallabhaneni Rohith , Somanathan Pillai Sanjaikanth E. Vadakkethil , Vaddadi Srinivas A. , Addula Santosh Reddy , Ananthan Bhuvanesh
Published: October 2024

Based on the information technology service model, an on-demand services towards user becomes cost effective, which is provided with cloud computing. The network attack is detected with research community that pays huge interest. The novel proposed framework is intended with the combination of mitigation and detection of attack. While enormous traffic is obtainable, extract the relevant fields decide with Software-as-a-service (SaaS) provider. According to the network vulnerability and mitigation procedure, perform deep learning-based attack detection model. The golf optimization algorithm (GOA) done the selection of features followed by deep neural network (DNN) detect the attacks from the selected features. The correntropy variational features validates the level of risk and performs vulnerability assessment. Perform the process of bait-oriented mitigation during the phase of attack mitigation. The proposed approach demonstrates 0.97kbps throughput with 0.2% packet loss ratio than traditional methods.
Advancing elderly care through big data analytics and machine learning for daily activity characterization
Authors: Allali Ayoub , Bouanani Nouama , Abouchabaka Ibtihal , Rafalia Najat
Published: October 2024

Confronted with the ongoing demographic shift characterized by an aging population, society grapples with emerging challenges that extend beyond the provision of targeted health services for the elderly. The focus has broadened to encompass the promotion of well-being and vitality throughout the aging process. Addressing these multifaceted issues demands a comprehensive approach that integrates biomedical components with physical, psychological, and social interventions. In the context of my project, a unique strategy is employed, placing significant emphasis on leveraging big data analytics and machine learning. The primary objective is to systematically observe and characterize the physiological conditions of the elderly, facilitating healthcare professionals in monitoring behaviors and promoting active aging. This undertaking involves meticulous data collection and analysis, employing machine learning algorithms (support vector machine (SVM), gradient boosting) within a framework that harnesses extensive data analytics. Ultimately, this approach enables the identification and characterization of daily routines and physiological states of individuals, contributing to a holistic understanding of aging.
Comparison of Ultrathin- Versus Thin-Strut Stents in Patients With High Bleeding Risk PCI: Results From the COMPARE 60/80 HBR Trial: An Open-Label, Randomized, Controlled Trial
Authors: Smits Pieter C. , Tonino Pim A.L. , Hofma Sjoerd H. , van Kuijk Jan-Peter , Spano Fabrizio , Al Mafragi Amar , Pisters Ron , Polad Jawed , Bogaerts Kris , Oemrawsingh Rohit M. , Paradies Valeria
Published: October 2024

BACKGROUND:

No randomized data exist on ultrathin-strut stents in patients at high bleeding risk (HBR) undergoing an abbreviated dual antiplatelet therapy after coronary stenting. The aim of this study was to compare the safety and effectiveness of the ultrathin-strut biodegradable-polymer sirolimus-eluting Supraflex Cruz stent with the thin-strut biodegradable-polymer sirolimus-eluting Ultimaster Tansei stent in patients at HBR with abbreviated dual antiplatelet therapy after stenting.

METHODS:

In the investigator-initiated, randomized, open-label COMPARE 60/80 HBR trial (Comparison of the Supraflex Cruz 60 Micron Stent Strut Versus the Ultimaster Tansei 80 Micron Stent Strut in HBR Percutaneous Coronary Intervention Population), 741 patients at HBR according to the Academic Research Consortium HBR criteria were randomized to receive either the ultrathin-strut biodegradable-polymer sirolimus-eluting Supraflex Cruz stent or thin-strut biodegradable-polymer sirolimus-eluting Ultimaster Tansei stent. Dual antiplatelet therapy was recommended according to the applicable guidelines and trial data for patients at HBR. The primary outcome was net adverse clinical events, the composite of cardiovascular death, myocardial infarction, target vessel revascularization, stroke, and major bleeding, and was powered for noninferiority with an absolute margin of 4.0% at 1-sided 2.5% alpha.

RESULTS:

Between September 2020 and August 2022, 371 patients were randomized to the ultrathin-strut biodegradable-polymer sirolimus-eluting Supraflex Cruz stent and 370 patients to the thin-strut biodegradable-polymer sirolimus-eluting Ultimaster Tansei stent at 11 sites in the Netherlands. At 1 year, the primary outcome was observed in 56 (15.4%) patients in the ultrathin-strut biodegradable-polymer sirolimus-eluting Supraflex Cruz stent group and 61 (17.1%) in the thin-strut biodegradable-polymer sirolimus-eluting Ultimaster Tansei stent group (risk difference, −1.65%; upper boundary of the 1-sided 95% CI, 3.74;
P
=0.02 for noninferiority at a 0.025 significance level and
P
=0.55 for 2-sided superiority at a 0.05 significance level).

CONCLUSIONS:

Among patients at HBR with abbreviated dual antiplatelet therapy post-stenting, the use of an ultrathin-strut biodegradable-polymer sirolimus-eluting Supraflex Cruz stent was noninferior compared with the use of a thin-strut biodegradable-polymer sirolimus-eluting Ultimaster Tansei stent.

REGISTRATION:

URL:
https://www.clinicaltrials.gov
; Unique identifier: NCT04500912.
Determinants of Timely Access to Recanalization Treatments and Outcomes in Pediatric Ischemic Stroke
Authors: Tudorache Raluca , Kossorotoff Manoëlle , Kerleroux Basile , Denier Christian , Naggara Olivier , Boulouis Grégoire ,   the KID-CLOT Group
Published: October 2024

BACKGROUND:

Timely revascularization in acute arterial ischemic stroke (AIS) is paramount for optimal outcomes. However, factors causing treatment delays in pediatric AIS remain understudied. We investigated determinants affecting the time from symptom onset or last-known-well to the start of recanalization treatment in pediatric AIS.

METHODS:

We conducted an ancillary analysis of the French KID-CLOT study (The National Retrospective Study of Recanalization Treatments in Pediatric Arterial Ischemic Stroke), considering patients with pediatric AIS receiving recanalization treatments (IV thrombolysis IVT and mechanical thrombectomy) from 2015 to 2018. The study assessed prehospital triage’s impact, direct versus transferred admissions, and unit type (pediatric versus adult) on treatment delay and clinical outcomes using modified Rankin Scale at 1 year.

RESULTS:

Among 68 patients (median age, 11 [IQR, 4–16]; initial PedNIHSS, 13 [IQR, 7–19]), treatment modalities were IVT (n=31), and mechanical thrombectomy (n=23), and IVT+mechanical thrombectomy (n=14). Prehospital triage significantly reduced last-known-well to treatment delay (overall, 229 versus 270 minutes;
P
=0.01), most notably for and mechanical thrombectomy (
P
<0.001). There was no substantial delay difference between direct and transferred admissions, or between unit types, although a trend favored adult units (370.3 versus 436.73 minutes;
P
=0.06). Prehospital triage correlated with improved outcomes, with a shift to lower modified Rankin Scale scores (
P
=0.021).

CONCLUSIONS:

For pediatric AIS treated with reperfusion therapy, prehospital triage emerges as a pivotal factor in reducing treatment delays and enhancing outcomes. These findings underscore the need for a dedicated prehospital stroke protocol for children.

REGISTRATION:

URL:
https://www.clinicaltrials.gov
; Unique identifier: NCT03887143.
ANALYSIS OF BUBBLES ASSETS FOR WEIGHTED AVERAGE INTEREST RATES APPLIED TO BANK LOANS
Authors: Tarkun Savaş , Işığıçok Erkan
Published: October 2024

This study examines the existence of the "bubble effect" in the average interest rates of loans applied by banks to various types of loans for consumers. The purpose of this article is the research of the bubble formations in the average interest rates applied by the banks to consumer, housing (home), vehicle, and commercial loan types. This article examines the existence of bubbles in the average loan interest rates of banks in Turkey using the GSADF unit root test developed by Phillips et al. (2015). Bubble assets are analyzed with weekly data for the period June 2019–March 2023. Monte Carlo simulations performed obtained critical values for the GSADF unit root test. The results show that the bubble effect on housing loan interest rates is statistically significant at the 0.05 level. Against this, although the existence of a bubble effect in consumer, vehicle, and commercial loan interest rates has been determined, these bubbles are statistically insignificant.
MEASURING CAREER EXPECTATIONS OF GENERATION Z: KARABUK UNIVERSITY EXAMPLE
Authors: Kurter Osman , Aydan Ümmet
Published: October 2024

This study aims to ascertain the career expectations of Generation Z. To achieve this objective, it analyzes the concepts and characteristics of Traditionalists, Baby Boomers, Generation X, Generation Y, and Generation Z, with the underlying reasons for their distinctions. The research comprises 551 male and 253 female students currently enrolled at Karabük University in Türkiye. This study utilizes a descriptive research model, employing online survey forms as the primary data collection methodology. The gathered data analysis was done using t-tests and ANOVA statistical measurements. After a thorough evaluation, the findings revealed significant differences in the responses between participants from Generation Z and Generation X. While the majority of the respondents expressed confidence in possessing adequate knowledge about their future job prospects and expectations, most respondents expressed the need for assistance with career services. Therefore, the findings recommend that employers should be prepared to address the unique needs and work styles of Gen Z.
Post-Cold War Era UN Collaboration with Non-UN Military for Conflict Management in Africa
Authors: Arai Nobuhiro
Published: October 2024

This research explores the factors associated with the success or failure of European Union (EU) military bridging operations supporting United Nations (UN) peacekeeping in Africa. This study defines the success of eufor bridging operations as those in which a subsequent UN mission was able to continue operations after assuming responsibilities from eufor. This raises two factors associated with success and failure: integration and adaptation. Two hypotheses are formulated regarding the respective parameters for achieving bridging operations goals that lead to their success. To examine the hypotheses, this study conducts a comparative analysis with two EU bridging operations, one in the Democratic Republic of Congo as a success case and the other in Chad and the Central African Republic as a failure. This study aims to produce new knowledge in the field of peacekeeping operations, practical policies, and general considerations on the ground. It also seeks to further understanding of bridging operations and develop better opportunities for designing future operations.
A new species of treefrog (Litoria: Pelodryadidae) from the karstic South-fold Mountains of New Guinea
Authors: OLIVER PAUL M. , MCDONALD PETER J. , DAHL GEORGE , NAGOMBI ELIZAH , RICHARDS STEPHEN J.
Published: October 2024

Despite recent advances in the systematics and taxonomy of the relictual family Scolebythidae, the type genus Scolebythus Evans, 1963 remained monospecific for more than sixty years. Here, I describe and illustrate Scolebythus bekilyensis sp. nov. from a female specimen collected in southern Madagascar. This discovery emphasizes on the endemism of this genus, which is unique within the Scolebythidae for being restricted to one biogeographic realm, and suggests that potential new species are yet to be discovered in this megadiverse region.
An illustrated key to the Afrotropical bark beetle species of Cladoctonus Strohmeyer (Curculionidae, Scolytinae)—a genus of rare cossonine look-alikes
Authors: JORDAL BJARTE H.
Published: October 2024

The Afrotropical species of Cladoctonus Strohmeyer, 1911 is revised. A key to species is provided with all species illustrated with photos. Five species are currently recognized as valid. Variation between species is limited and samples are few, not yet allowing for assessment of potential intraspecific variation. One synonym is suggested for Cladoctonus affinis Strohmeyer, 1911 (=Cladoctonus eggersi Wichmann, 1911, syn. nov.)
New species and records of Paraphloeostiba Steel, 1960 and Xanthonomus Bernhauer, 1926 from the eastern Palaearctic, Oriental and Papuan regions (Coleoptera: Staphylinidae: Omaliinae)
Authors: SHAVRIN ALEXEY V.
Published: October 2024

New taxonomic and faunistic data for nine species of Paraphloeostiba Steel, 1960 and one species of Xanthonomus Bernhauer, 1926 (X. guineensis Shavrin, 2024) from the eastern Palaearctic, Oriental and Papuan regions are provided. Three new species of Paraphloeostiba are described and illustrated: P. acrolochaoides sp. nov. and P. brevicula sp. nov. from Papua New Guinea, and P. zingiberiphila sp. nov. from Malaysia (Sabah). Four species are recorded for the first time: P. gayndanensis (MacLeay, 1873) from Guangxi Province of China, Laos and Japan (Amami-Ōshima), P. papuana (Cameron, 1931) and P. riedeli Shavrin, 2024 from Papua New Guinea, and P. steeli Shavrin, 2024 from Indonesia (Sulawesi).
Moulding of SS316L surgical component using palm-stearin feedstock: Rheological analysis, process window and parametric optimisation
Authors: Rezaei Sina , Askari Ali
Published: October 2024

Metal injection moulding of a thin surgical component using a palm-stearin based SS316L feedstock was investigated. The study first determined the optimal solids loading of the feedstock, followed by examining its sensitivity to the shear rate and temperature, to ensure its pseudo-plastic behaviour. After developing the Mouldability index, a process window was established based on the experiments to present appropriate injection parameters. Using the analysis of variance, the significance and mutual coupling of each parameter was evaluated. The study found that the impact of injection speed was greater than other parameters, while holding pressure showed little effect. The verified optimised injection parameters to maximise the green density were found to be an injection temperature of 155 °C, an injection speed of 80 mm/s, a holding pressure of 83 bar, a holding time of 9 s, and an injection pressure of 132 bar, resulting in a green part density of 4.892 g/cm3.
Experimental analysis of tensile strength of 6-layer carbon/kevlar/epoxy hybrid composite reinforced with nano-graphene/silica nanoparticles
Authors: Voghofi Iman , Ashenai Ghasemi Faramarz , Reza Kashyzadeh Kazem
Published: October 2024

The main aim of the present research is to improve the static tensile strength of Carbon/Kevlar/Epoxy hybrid composite by adding different nanoparticles. To this end, two well-known nanoparticles namely Nano-Silica and Nano-Graphene were considered. Also, the total percentage of adding nanoparticle reinforcing elements to the hybrid composite was considered equal to 1.5%. In this way, five categories of reinforced hybrid composites, including 0%Nano-Silica+0%Nano-Graphene, 1.5%Nano-Silica+0%Nano-Graphene, 1.2%Nano-Silica+0.3%Nano-Graphene, 1.0%Nano-Silica+0.5%Nano-Graphene, and 0.75%Nano-Silica+0.75%Nano-Graphene, were studied. Composite samples were prepared using manual layout technique and tensile tests were performed according to the ASTM standard. It was found that the tensile strength increases with the addition of nanoparticles to the Carbon/Kevlar/Epoxy hybrid composite, but these two do not always have a direct and linear relationship with each other. Moreover, it was shown that the addition of 1.2% silica nanoparticles and 0.3% nanographene leads to an increase of tensile strength up to 36%, and this is the best optimal percentage of additive nanoparticles in this research.
Efficacy of a Culturally Adapted Emotion Recognition Training Program in Improving Facial Emotion Recognition in Persons with Schizophrenia
Authors: Thonse Umesh , Behere Rishikesh V. , Frommann Nicole , Praharaj Samir Kumar , Sharma Podila Sathya Venkata Narasimha
Published: October 2024

Background:

Facial emotion recognition (FER) deficits are being considered as core features of social cognitive deficits in schizophrenia, associated with socio-occupational dysfunction. Social cognition intervention programs have been shown to improve these deficits; however, there are no such intervention strategies in India. In this study, we aim to examine the efficacy of Training of Affect Recognition – Indian Version (TAR-IV) to enhance the FER abilities of people with schizophrenia.

Methods:

In an open-label experimental design, 36 participants with schizophrenia underwent 12 sessions of TAR-IV as an add-on to treatment as usual (TAU), while 29 participants with schizophrenia continued TAU (pharmacological treatment with or without occupational therapy and vocational rehabilitation services). Clinical and functional assessments were done using the positive and negative syndrome scale (PANSS) and socio-occupational functioning scale. Emotion recognition abilities were assessed on the tool for recognition of emotions in neuropsychiatric disorders at baseline, post-intervention, and follow-up (two to three months post-intervention).

Results:

The intervention group showed significant improvements in FER ( P = .001) and socio-occupational functioning ( P = .008) after receiving the TAR-IV, which remained significant at two months follow-up. A lower age of onset and poorer neurocognitive function at baseline predicted greater changes in emotion recognition ability following the intervention.

Conclusions:

This study demonstrated the efficacy of TAR-IV, the Indian adaptation of social cognition intervention, in improving emotion recognition abilities and socio-occupational functioning in patients with schizophrenia. These findings need to be replicated in randomized controlled trials.
Comparison of microstructure and tribological behavior for ductile iron with quench-tempered and intensive quench-tempered
Authors: Xiao Shichen , Zhu Xiaoshuo , Fu Yudong , Su Xiyang , Dong Ning , Wang Juncheng
Published: October 2024

In recent years, the intensive quenched process has gained significant attention due to its low energy consumption and absence of pollution. The tribological behavior of traditional quenched and tempered ductile iron (DI_QAT) and an innovative intensive quenched and tempered ductile iron (DI_IQAT) was investigated. Both DI_QAT and DI_IQAT consist of graphite, ferrite and cementite particles. Compared to DI_QAT, DI_IQAT exhibits higher hardness, impact toughness, and yield strength. Wear tests indicate that the friction coefficient of DI_IQAT is lower and the wear resistance of DI_IQAT surpasses that of DI_QAT, it is mainly related to its enhanced wear-resistant structure. Examination of the wear surface morphology reveals that the primary wear mechanisms for DI_QAT and DI_IQAT involve adhesive and abrasive wear.
Effect of eco-friendly organic additives on copper electropolishing and process parameter optimization
Authors: Zhan Q. F. , Li H. L. , Wang Y. , Wang Z. W.
Published: October 2024

The type of organic additives significantly affects copper electropolishing performance, including glossiness and surface smoothness. Therefore, developing efficient and eco-friendly additives is crucial for advancing this technology. This study investigates the effects of glycerol and ascorbic acid on copper electrochemical properties and surface morphology. Using the Box- Behnken Design (BBD), we examined the interaction effects of polishing time (A), current density (B), and polishing temperature (C) while optimizing the process parameters. The results demonstrate that glycerol and ascorbic acid additives effectively reduce the critical current density and limiting current density, synergistically enhancing copper surface glossiness and smoothness while slowing down the dissolution rate of the copper. Interaction analysis revealed a prioritized sequence of effects: AB > BC > AC. Under optimal conditions (1.5 min of polishing time, 12 A dm−2 of current density, and 27 °C of polishing temperature), copper surface roughness decreases from 1.2 μm to 37 nm, representing a 97% reduction, along with enhanced corrosion resistance.
Positioning method of track irregularities in high-speed turnout area based on multi-resolution analysis
Authors: Sun Xu , Qin Lusheng , Wang Ping
Published: October 2024

The assessment and evaluation of complex track geometry parameters (TGP) in turnout areas present challenges for track recording cars due to uncertainties in their positioning on short sections. To obtain precise and reliable measured TGP in the turnout area, a multi-resolution technology based on maximal overlap discrete wavelet transform (MODWT) is used to perform multi-layer decomposition of the longitudinal level. By utilizing the zero-phase characteristic of MODWT, the TGP can be determined by aligning the decomposed weld spacings with their corresponding theoretical lengths. The positioning error is assessed through statistical analysis of measured TGP and numerical simulation using a virtual track inspection method. Finally, a 70 m length of TGP, including the entire turnout section, was extracted with a positioning error of no more than 1.5 m.
Vibration control of nonlinear viscoelastic systems with displacement delay feedback
Authors: Wang Daohang , Sun Bo , Liu Chunxia , Jia Ke
Published: October 2024

In this study, the nonlinear vibration characteristics of a nonlinear Zener model under harmonic excitation, equipped with linear and nonlinear displacement delay feedback control, were investigated. The amplitude–frequency curve of the system’s main resonance was computed using the multi-scale method. Stability conditions for the system were then established based on the Lyapunov stability theory. The influence of several parameters on the system’s dynamic behavior was also analyzed, including time delay, displacement feedback gain coefficient, nonlinear term coefficient, damping coefficient, and external excitation. The findings revealed that the nonlinear displacement feedback gain coefficient was observed to exert a more substantial effect on the system’s amplitude than other factors. Further, the nonlinear displacement delay feedback gain coefficient and time-delay value diminish the amplitude of the vibration, leading all solutions to achieve a stable state. In instances with time-delay control, the impact of the main system parameters on system vibration was significantly diminished. The aim of this study is to provide a theoretical basis for the implementation of displacement delay controllers in nonlinear viscoelastic systems.
The Effects of Policy-Interested Bureaucrats on State and Local Policymaking
Authors: Watson Henry
Published: October 2024

From 1971 to 2023, 19 states, 24 counties, and 105 cities passed Source-of-Income Anti-Discrimination (SOI) laws, outlawing landlord discrimination against tenants receiving rental assistance. I present a theory of bureaucratic involvement in state and local policymaking, arguing that policy-interested local bureaucratic agencies—signaled by participation in a national membership organization—elevate mission-relevant policy problem definitions to the legislative agenda and motivate the passage of legislation. I present results from a Cox Proportional Hazards Model which demonstrates that SOI laws are significantly more likely to be enacted in cities, counties, and states associated with a public agency which is a member of the Council of Large Public Housing Authorities, even compared to jurisdictions associated with non-member Public Housing Authorities of similar sizes.
Advancements in Tissue Engineering: A Review of Bioprinting Techniques, Scaffolds, and Bioinks
Authors: Zoghi Shervin
Published: October 2024

Tissue engineering is a multidisciplinary field that uses biomaterials to restore tissue function and assist with drug development. Over the last decade, the fabrication of three-dimensional (3D) multifunctional scaffolds has become commonplace in tissue engineering and regenerative medicine. Thanks to the development of 3D bioprinting technologies, these scaffolds more accurately recapitulate in vivo conditions and provide the support structure necessary for microenvironments conducive to cell growth and function. The purpose of this review is to provide a background on the leading 3D bioprinting methods and bioink selections for tissue engineering applications, with a specific focus on the growing field of developing multifunctional bioinks and possible future applications.
Interpretable machine learning models for predicting probabilistic axial buckling strength of steel circular hollow section members considering discreteness of geometries and material
Authors: Hou Zhengyang , Hu Shuling , Wang Wei
Published: October 2024

Steel circular hollow section (CHS) members are widely utilized as axial force-resisting structural members in civil engineering structures. The buckling strength under axial loads is one of the critical parameters to determine the performance of the steel CHS members, which is significantly affected by the discreteness introduced by geometries, material, and initial imperfections. However, the reduction factor employed in the modern design codes (i.e. Chinese codes and EC3) only accounts for the reduction caused by all kinds of discreteness and does not reflect the impacts of every single discreteness and imperfection. To fill the gap, this paper proposed an interpretable machine-learning method to provide the probabilistic axial buckling strength of steel CHS members prediction result in a distribution form with the consideration of detailed discreteness. The model to predict the nominal axial buckling strength of steel CHS members was first developed utilizing ten machine learning algorithms after sufficient numerical simulations, where the numerical model was verified using test results. The artificial neural network (ANN) was selected for developing the prediction model due to its highly reliable performance in testing. The developed ANN models were further interpreted utilizing Shapley Additive exPlanations (SHAP) to determine the interrelationship of different parameters. Then, the probabilistic axial bucking strength prediction model was established based on the developed ANN models, where the Latin hypercube sampling method was applied to address the discreteness of geometries, material, and initial imperfections. The generated probabilistic axial bucking strength prediction model’s effectiveness was verified by the evidence that the machine learning prediction results can highly match the numerical results' probability density function and the result from codes while significantly reducing the computation time. Finally, the design parameters’ impact on the axial buckling strength’s discreteness was evaluated using the global sensitivity analysis (GSA) method. The result shows that the discreteness of design parameters substantially influences the distribution of the axial buckling strength of the steel CHS members and the proposed prediction model can provide an accurate probabilistic distribution prediction.
Non-contact measurement of structural dynamic displacement based on improved edge detection and video interpolation
Authors: Yang Kechao , Luo Yongpeng , Pan Shuang , Li Lin
Published: October 2024

In structural health monitoring (SHM), smartphones are increasingly used for non-contact dynamic displacement measurement using computer vision. To overcome limitations in capturing high-frame-rate data, a non-contact measurement method of structural dynamic displacement based on an improved edge detection algorithm and video frame interpolation is proposed. Initially, a smartphone is employed to capture the structure’s vibration video and then generates intermediary frames between adjacent frames that match the structure’s motion state by using a video frame interpolation algorithm to obtain a video with a high frame rate. Subsequently, the improved edge detection algorithm is applied to measure the displacement within the interpolated video. In order to address the problem that traditional edge detection may have false edges leading to the degradation of measurement accuracy, a feature point tracking technique is proposed based on the traditional edge detection technique, which effectively excludes the interference of false edges in ROI and improves the accuracy of displacement monitoring. Experimental validation on a cantilever beam and steel frame bridge demonstrates the method’s viability and precision, highlighting its effectiveness in improving displacement measurement accuracy compared to traditional methods.
You fold the robes to perfection! A story from doing working participant observation
Authors: Thulemark Maria , Cassel Susanna Heldt , Duncan Tara
Published: October 2024

This note tells a story of working participant observation. It shares a narrative of how working as a housekeeper, as part of a project about dignity and decent work, opened up the researchers to stories beyond the work tasks. The note weaves a tale around one particular worker, and highlights how as researchers, being embedded, and embodied within their research allowed for insights and reflections that a “common” interview would not have gained. It highlighted the positives and tensions of being “in between” an insider and an outsider as a researcher. The note concludes with a reminder or perhaps a caution that we are all, bodies, minds, our “selves,” part of the research process and the necessity to be reflexive, thoughtful, and engaged with our research remains essential as we look to expand how we gain knowledge into (service) work and employment.