bluuebunny/crossref_metadata_2025_split huggingface dataset:
MicroRNA-221-3p inhibits the inflammatory response of keratinocytes by regulating the DYRK1A/STAT3 signaling pathway to promote wound healing in diabetes
Authors: Hu Keyan , Liu Lei , Tang Songtao , Zhang Xin , Chang Hongfeng , Chen Wenyang , Fan Taotao , Zhang Lesha , Shen Bing , Zhang Qiu 
Published: March 2024

AbstractDiabetic foot ulcer (DFU), a serious complication of diabetes, remains a clinical challenge. MicroRNAs affect inflammation and may have therapeutic value in DFU. Here, we find that an miR-221-3p mimic reduces the inflammatory response and increases skin wound healing rates in a mouse model of diabetes, whereas miR-221-3p knockout produced the opposite result. In human keratinocytes cells, miR-221-3p suppresses the inflammatory response induced by high glucose. The gene encoding DYRK1A is a target of miR-221-3p. High glucose increases the expression of DYRK1A, but silencing DYRK1A expression decreases high glucose–induced inflammatory cytokine release via dephosphorylation of STAT3, a substrate of DYRK1A. Application of miR-221-3p mimic to human keratinocytes cells not only decreases DYRK1A expression but also inhibits high glucose–induced production of inflammatory cytokines to promote wound healing. This molecular mechanism whereby miR-221-3p regulates inflammation through the DYRK1A/STAT3 signaling pathway suggests targets and therapeutic approaches for treating DFU.
Bacteriophage therapy for the treatment of Mycobacterium tuberculosis infections in humanized mice
Authors: Yang Fan , Labani-Motlagh Alireza , Bohorquez Jose Alejandro , Moreira Josimar Dornelas , Ansari Danish , Patel Sahil , Spagnolo Fabrizio , Florence Jon , Vankayalapati Abhinav , Sakai Tsuyoshi , Sato Osamu , Ikebe Mitsuo , Vankayalapati Ramakrishna , Dennehy John J. , Samten Buka , Yi Guohua 
Published: March 2024

AbstractThe continuing emergence of new strains of antibiotic-resistant bacteria has renewed interest in phage therapy; however, there has been limited progress in applying phage therapy to multi-drug resistant Mycobacterium tuberculosis (Mtb) infections. In this study, we show that bacteriophage strains D29 and DS6A can efficiently lyse Mtb H37Rv in 7H10 agar plates. However, only phage DS6A efficiently kills H37Rv in liquid culture and in Mtb-infected human primary macrophages. We further show in subsequent experiments that, after the humanized mice were infected with aerosolized H37Rv, then treated with DS6A intravenously, the DS6A treated mice showed increased body weight and improved pulmonary function relative to control mice. Furthermore, DS6A reduces Mtb load in mouse organs with greater efficacy in the spleen. These results demonstrate the feasibility of developing phage therapy as an effective therapeutic against Mtb infection.
Calibration‐free structured‐light‐based 3D scanning system in laparoscope for robotic surgery
Authors: Furukawa Ryo , Chen Elvis , Sagawa Ryusuke , Oka Shiro , Kawasaki Hiroshi 
Published: March 2024

AbstractAccurate 3D shape measurement is crucial for surgical support and alignment in robotic surgery systems. Stereo cameras in laparoscopes offer a potential solution; however, their accuracy in stereo image matching diminishes when the target image has few textures. Although stereo matching with deep learning has gained significant attention, supervised learning requires a large dataset of images with depth annotations, which are scarce for laparoscopes. Thus, there is a strong demand to explore alternative methods for depth reconstruction or annotation for laparoscopes. Active stereo techniques are a promising approach for achieving 3D reconstruction without textures. In this study, a 3D shape reconstruction method is proposed using an ultra‐small patterned projector attached to a laparoscopic arm to address these issues. The pattern projector emits a structured light with a grid‐like pattern that features node‐wise modulation for positional encoding. To scan the target object, multiple images are taken while the projector is in motion, and the relative poses of the projector and a camera are auto‐calibrated using a differential rendering technique. In the experiment, the proposed method is evaluated by performing 3D reconstruction using images obtained from a surgical robot and comparing the results with a ground‐truth shape obtained from X‐ray CT.
Assessing temporary traffic management measures on a motorway: Lane closures vs narrow lanes for connected and autonomous vehicles in roadworks
Authors: Singh Mohit Kumar , Formosa Nicolette , Man Cheuk Ki , Morton Craig , Masera Cansu Bahar , Quddus Mohammed 
Published: March 2024

AbstractConnected and automated vehicles (CAVs) are being developed and designed to operate on existing roads. Their safe and efficient operation during roadworks, where traffic management measures are often introduced, is crucial. Two alternative measures are commonly applied during roadworks on motorways: (i) closing one or multiple lanes (ii) narrowing one or all lanes. The former can cause delays and increased emissions, while the latter can pose safety risks. This study uses a VISSIM‐based traffic microsimulation to compare the effectiveness of these two strategies on traffic efficiency and safety, considering various market penetration rates (MPR) of CAVs. The model was calibrated and validated with the data collected from M1 motorway in the United Kingdom. Results show that average delays per vehicle‐kilometre‐travelled decreased from 102.7 to 2.5 s (with lane closure) and 23.6 to 0.6 s (with narrow lanes) with 0% and 100% CAV MPR, respectively. Moreover, safety in narrow lanes improved by 4.8 times compared to 1.5 times improvement in lane closure with a 100% CAV MPR; indicating that narrow lanes would result in better safety performance. These findings could assist transport authorities in designing temporary traffic management measure that results in better CAV performance when navigating through roadworks.
Component design procedure for LCC‐S wireless power transfer systems based on genetic algorithms and sensitivity analysis
Authors: Corti Fabio , Intravaia Matteo , Reatti Alberto , Grasso Francesco , Grasso Emanuele , Cabrera Alicia Triviño 
Published: March 2024

AbstractThis paper introduces a novel approach for designing a Wireless Power Transfer (WPT) system with LCC‐S compensation. Since WPT systems operate under resonant conditions, even small deviations of the components from the nominal values can result in a significant reduction of the power transferred to the load, and in an increment of the circulating currents, reducing the system efficiency. The design techniques available today in the literature provide a unique combination of passive components capable of transferring a certain power to the load. This is a limitation, because, in practice, there are several combinations that allow reaching the desired output power, but they are usually neglected because they are extremely difficult to compute analytically. For this reason, in this paper, the authors present an innovative design procedure that enables, through a Genetic Algorithm, the identification of multiple feasible combinations of the LCC‐S components capable of achieving the desired output power. Moreover, the authors evaluate the effects of the component tolerances on the output power to determine which combinations are more robust to component variations. This task is performed by calculating the probability that a particular combination yields the desired output power, once the tolerances have been considered, following a Monte Carlo approach. This information is utilized to decide whether it is possible to reduce the component quality (worsening the tolerance) without affecting the performance. Finally, an optimal solution granting both low‐cost and robustness against component tolerances can be individuated. The proposed design procedure is applied to a case study and validated experimentally.
Compensating trigger jitter and time interval error measurement for digital sampling oscilloscopes with hardware design on FPGA
Authors: Moussa Bilal , Chaccour Kabalan , Bouyekhf Rachid , Abdallah Abdallah , Mroué Mohamad 
Published: March 2024

Abstract
This paper presents the creation and realization of a precision time base (PTB) for mitigating jitter and measuring time interval error (TIE) in digital sampling oscilloscopes (DSO), achieved through the utilization of a field programmable gate array (FPGA). Our proposed method focuses on mitigating jitter through PTB, which involves the sampling of two reference channels having a phase shift of approximately 90∘ (at quadrature) for an accurate timebase correction. Through extensive experimentation and analysis, we were able to achieve a reduction in root mean square (RMS) jitter, minimizing it to around 260 fs. This outcome demonstrates the effectiveness of our approach in enhancing the accuracy and reliability of DSO measurements. Expanding on the application of our previously proposed technique, we demonstrate that the same sampling error correction approach can be utilized for TIE measurement. By sampling a large amount of data at either the rising or falling edge of a sinusoidal signal, TIE can be accurately evaluated. This extension enhances the versatility of our FPGA-based implementation by enabling comprehensive TIE analysis alongside PTB compensation in DSOs.
Multi-organ segmentation: a progressive exploration of learning paradigms under scarce annotation
Authors: Li Shiman , Wang Haoran , Meng Yucong , Zhang Chenxi , Song Zhijian 
Published: March 2024

Abstract
Precise delineation of multiple organs or abnormal regions in the human body from medical images plays an essential role in computer-aided diagnosis, surgical simulation, image-guided interventions, and especially in radiotherapy treatment planning. Thus, it is of great significance to explore automatic segmentation approaches, among which deep learning-based approaches have evolved rapidly and witnessed remarkable progress in multi-organ segmentation. However, obtaining an appropriately sized and fine-grained annotated dataset of multiple organs is extremely hard and expensive. Such scarce annotation limits the development of high-performance multi-organ segmentation models but promotes many annotation-efficient learning paradigms. Among these, studies on transfer learning leveraging external datasets, semi-supervised learning including unannotated datasets and partially-supervised learning integrating partially-labeled datasets have led the dominant way to break such dilemmas in multi-organ segmentation. We first review the fully supervised method, then present a comprehensive and systematic elaboration of the 3 abovementioned learning paradigms in the context of multi-organ segmentation from both technical and methodological perspectives, and finally summarize their challenges and future trends.
Free vibration of the piezoelectric laminated composite beams under the elastic foundation
Authors: Zhao Lei , Zhu Dongpo , Kuang Rui , Ruan Hengjin , Wang Kelong , Shi Xiaona , Mou Di 
Published: March 2024

Abstract
Due to its self-adaptability and electric-mechanical interaction, the piezoelectric laminated composite structure has received increased attention in the engineering community, with the intricacy of the actual scenario, the structural stability based on numerous foundations has also been recognized. In this paper, a unified formulation which is based on classical laminated beam is presented to conduct free vibration analysis of piezoelectric laminated beams subjected to classical boundary conditions with the varied elastic foundations. The semi-analytical solutions of layered beams in various boundaries have been obtained based on the two-dimensional piezoelectric elastic theory and state space-differential quadrature method (SS-DQM), the solution of the general structural equation has been generated introducing the electrical boundary conditions and interlayer continuity conditions with this understanding. The different elastic foundations have been used to calculate the frequency equation of the piezoelectric laminated construction. The proposed finite element model is validated through the analysis of the piezoelectric laminated composite beam (PLCB) using the SS-DQM, and the present solutions are compared with those available in the literature to confirm their validity. A systematic parameter study for the piezoelectric laminated beams with various boundary conditions, piezoelectric parameters, lamina numbers and thickness ratios is also performed. The results of the PLCBs with various boundary constraints under the elastic foundation are presented and they may be served as a benchmark for researchers in this field.
Synthesis and characterization of Co3O4 spinel nanowall: understanding the growth mechanism and properties
Authors: Barala Sushil , Panda Sri Aurobindo , Gangopadhyay Subhashis 
Published: March 2024

Abstract
Formation of spinel tricobalt tetraoxide (Co3O4) nanostructures through a controlled thermal oxidation process is discussed here. Thin films of high purity cobalt (Co) were deposited on glass/quartz substrates using an electron beam (E-beam) evaporation technique. Thermal oxidation of the as-deposited Co thin films was carried out at various oxidation temperatures (400 °C to 600 °C) for different durations (5 h to 15 h) to grow various oxide nanostructures. Different surface characterizations techniques were used to investigate the structure, chemistry and electronic properties of the as-grown cobalt oxide nanostructures. x-ray diffraction analysis revealed the presence of the CoO phase along with the Co3O4 phases at relatively lower oxidation temperature. However, the Co3O4 phase becomes more predominant for longer oxidation durations at higher oxidation temperatures. Field emission scanning electron microscopy analysis showed a surface morphological transition from nanowalls to nanograins with an increase in the oxidation temperature. The surface electrical conductivity of the oxidized Co films is also increased for higher oxidation temperature and/or duration mainly due to the oxide phase purity and larger particle sizes. Ultraviolet–visible spectroscopy indicated two distinct optical energy bandgaps, which effectively decreased with an increase in the oxidation temperature and duration. Raman spectroscopy identified five different Raman-active modes corresponding to the Co3O4 phase, with the F2g mode dominating at higher temperatures. All these findings provide clear insights into the structural, electrical, chemical and optical properties of cobalt oxide thin films. Moreover, it provides a mechanism on how to grow 2D nanowalls morphology of Co3O4 films which can further be used in energy, sensor or catalytic applications.
Tribological impact on borosilicate glass powder reinforced Al-MMC by variation of sliding velocity and the study of its machinability
Authors: Bhowmik Abhijit , Bhattacharjee Biplab , T Arunkumar , Akinwande Abayomi Adewale , Syed Asad , Wong Ling Shing 
Published: March 2024

Abstract
Now-a-days, metal matrix composites based on pure aluminium are widely used as a replacement for a wide range of applications thanks to their high strength-to-weight ratio, ductility, and thermal conductivity. Micron-sized (10−3 mm) borosilicate (mixer of Silica (SiO2) and Boron Oxide (B2O3)) glass particles were used to create a dispersion in an aluminium matrix composite (Al7075- borosilicate glass MMC) utilizing a stir casting technique while in a liquid condition. The present study examines the effect of borosilicate glass particle content (0, 3, 6, and 9 wt%) and changes in sliding velocity (0.5, 1, 1.5, and 2 m s−1) on the wear behaviour of a composite rubbing against an EN31 steel disc at a constant load of 20N and a sliding distance of 1000 m. Analysis of wear showed that the presence of borosilicate glass increased the wear rate and countered the trend shown in the coefficient of friction. In a similar vein, the sliding velocity of the counter plate rotated faster resulted in a higher coefficient of friction and a higher wear rate. A reliable mathematical model is developed to find the best combination of machining parameters for Al7075-borosilicate glass metal matrix composite (MMC). This model will consider important performance measures like surface smoothness and material removal rate. The authors will also use a sophisticated statistical method called the Taguchi L9 orthogonal array design of experiments (DOE) to understand how different machining settings affect how easily the composite can be machined. By analyzing the results from the DOE, it can optimize the machining parameters for efficient and cost-effective processing. This work can lead to manufacturing innovation in the future.
Source engineered TFET for digital inverters application
Authors: Talukdar Jagritee , Malvika  , Das Basab , Rawat Gopal , Mummaneni Kavicharan 
Published: March 2024

Abstract
This article delves into a performance evaluation of source engineered asymmetric Tunnel Field Effect Transistors using Sentaurus TCAD. The focus of this analysis centers around Single and Double gate extended Source TFET (SG-ESTFET and DG-ESTFET) device configurations. The study emphasizes the reliability of these devices for circuit applications taking in account interface trap charges. Various digital inverters based on the aforementioned TFET devices are designed, showcasing their potential utility in terms of different delay parameters. Additionally, the article explores transient characteristics and notes the occurrence of undershoot when interface trap charges are present at oxide-semiconductor interfaces. Notably, the findings indicate that DG-ESTFET surpasses SG-ESTFET in mitigating undershoot, and the measured propagation delay is reported to be 9 ps.
Constraining decaying very heavy dark matter from galaxy clusters with 14 year Fermi-LAT data
Authors: Song Deheng , Murase Kohta , Kheirandish Ali 
Published: March 2024

Abstract
Galaxy clusters are promising targets for indirect detection of dark matter thanks to the
large dark matter content. Using 14 years of Fermi-LAT data from seven nearby galaxy
clusters, we obtain constraints on the lifetime of decaying very heavy dark matter particles with
masses ranging from 103 GeV to 1016 GeV. We consider a variety of decaying channels
and calculate prompt gamma rays and electrons/positrons from the dark matter. Furthermore, we take
into account electromagnetic cascades induced by the primary gamma rays and electrons/positrons,
and search for the resulting gamma-ray signals from the directions of the galaxy clusters. We
adopt a Navarro-Frenk-White profile of the dark matter halos, and use the profile likelihood
method to set lower limits on the dark matter lifetime at a 95% confidence level. Our results are
competitive with those obtained through other gamma-ray observations of galaxy clusters and
provide complementary constraints to existing indirect searches for decaying very heavy
dark matter.
Controllable optical bistability and multistability in a V-type three-level atomic system interacting with two broadband independent squeezed baths
Authors: Batoo Khalid Mujasam , Naeem Youssef Ali , Ibrahim Ahmed Ahmed , Zazoum Bouchaib , Mahmud Sanaa Fathy , Sattar Ruaa , Dawood Imad Ibrahim , Ramadan Montather F , Al-Tameemi Ahmed Read , Kadhum Eftikhaar Hasan , Redhee Ahmed Huseen 
Published: March 2024

Abstract
In this study, we investigate the optical bistability (OB) and optical multistability (OM) phenomena within a V-type three-level atomic system interacting with two independent broadband squeezed baths confined in a unidirectional cavity. Our analysis reveals that the transition between OB and OM is influenced by the strength of the control field and the intensity of the squeezed vacuum. Notably, the impact of each of these factors on the transition exhibits distinct characteristics. Furthermore, we explore the effects of additional system parameters, such as the incoherent pumping rate and cooperation parameter. Our findings emphasize the crucial roles played by these parameters in shaping the observed results. Specifically, we observe that variations in the incoherent pumping rate and cooperation parameter contribute significantly to the system’s OB and OM behavior, further underscoring the multifaceted nature of the studied atomic system. This comprehensive investigation not only elucidates the intricate interplay between key parameters but also unveils the sensitivity of the system to variations in control field strength, intensity of the squeezed vacuum, incoherent pumping rate, and cooperation parameter.
Individual-finger motor imagery classification: a data-driven approach with Shapley-informed augmentation
Authors: Alsuradi Haneen , Khattak Arshiya , Fakhry Ali , Eid Mohamad 
Published: March 2024

Abstract

Objective. Classifying motor imagery (MI) tasks that involve fine motor control of the individual five fingers presents unique challenges when utilizing electroencephalography (EEG) data. In this paper, we systematically assess the classification of MI functions for the individual five fingers using single-trial time-domain EEG signals. This assessment encompasses both within-subject and cross-subject scenarios, supported by data-driven analysis that provides statistical validation of the neural correlate that could potentially discriminate between the five fingers. Approach. We present Shapley-informed augmentation, an informed approach to enhance within-subject classification accuracy. This method is rooted in insights gained from our data-driven analysis, which revealed inconsistent temporal features encoding the five fingers MI across sessions of the same subject. To evaluate its impact, we compare within-subject classification performance both before and after implementing this augmentation technique. Main results. Both the data-driven approach and the model explainability analysis revealed that the parietal cortex contains neural information that helps discriminate the individual five fingers’ MI apart. Shapley-informed augmentation successfully improved classification accuracy in sessions severely affected by inconsistent temporal features. The accuracy for sessions impacted by inconsistency in their temporal features increased by an average of

26.3
%
±
6.70

, thereby enabling a broader range of subjects to benefit from brain–computer interaction (BCI) applications involving five-fingers MI classification. Conversely, non-impacted sessions experienced only a negligible average accuracy decrease of

2.01
±
5.44
%

. The average classification accuracy achieved is around 60.0% (within-session), 50.0% (within-subject) and 40.0% (leave-one-subject-out). Significance. This research offers data-driven evidence of neural correlates that could discriminate between the individual five fingers MI and introduces a novel Shapley-informed augmentation method to address temporal variability of features, ultimately contributing to the development of personalized systems.