bluuebunny/crossref_metadata_2025 huggingface dataset:
The comparative transient prediction on hydrodynamic characteristics and flow field properties of pump-jets with accelerating and decelerating ducts
Authors: Zhou Yunkai , Yuan Jianping , Cavazzini Giovanna , Fu Yanxia , Gao Quanlin
Published: March 2024

Pump-jet holds a pivotal position in various marine applications, underscoring the need for comprehending their transient behavior for the purpose of design enhancement and performance refinement. This paper employs Reynolds-averaged Navier–Stokes equations method in conjunction with Detached Eddy Simulation model. The study delves into the ramifications of accelerating and decelerating ducts, distinguished by camber f and attack angles α, on transient hydrodynamic characteristics. The hydrodynamic characteristics are investigated numerically, after the validation of the numerical methodology by comparing simulation outcomes against experimental results. Subsequently, the study delves into propulsion characteristics, followed by an exploration of time-domain and frequency-domain data transformed through fast Fourier transform to analyze thrust fluctuations and pulsating pressures. Additionally, a detailed examination of pressure distribution and velocity field is provided, aiming to dissect the mechanisms through the variations in f and α influence the flow field. Findings suggest that the outlet velocity of accelerating ducts significantly surpasses the inlet velocity, a behavior contrasted by decelerating ducts. Notably, the patterns of accelerating and decelerating ducts resulting from alterations in f exhibit consistent characteristics with those brought about by changes in α. However, several opposite characteristics surface in transient flow field due to the distinct modifications in the duct profile. Furthermore, by considering vorticity magnitude distribution and vortices, a comparative analysis elucidates the effects of varying f and α on rotor and stator trailing vortices. This contributes to understanding the flow instability mechanism under differing duct configurations. It is evident that changes in f and α exert significant influence on both performance and flow field.
Investigation of surface hardness, thermostability, tribo-corrosion, and microstructural morphological properties of microwave-synthesized high entropy alloy FeCoNiMnCu coating claddings on steel
Authors: Sharma Shubham , Dwivedi Shashi Prakash , Mohammed Kahtan A. , Kumar Abhinav , Awwad Fuad A. , Khan M. Ijaz , Ismail Emad A. A.
Published: March 2024

Deposition of high entropy alloy FeCoNiMnCu on SS-304 was carried out by microwave energy for application in “solid oxide fuel-cell (SOFC) interconnects”. The ball-milling has been performed by taking “Fe, Co, Ni, Mn, and Cu” in equal 20 wt. % of before deposited on SS-304 substrate. The deposited steel with 20% Fe 20% Co 20% Ni 20% Mn 20% Cu high entropy alloy (HEA) was exposed to thermal-exposure in the air for up to 10 weeks at 800 °C. The uniform cladding distribution of 20% Fe 20% Co 20% Ni 20% Mn 20% Cu HEA particles can be apparently observed on SS-304 substrate by utilizing Scanning Electron Microscope (SEM), and Optical microscopy analysis. Homogeneity in the interfacial layer was evident by employing Scanning Electron Microscope (SEM) characterization. Results have indicated that after the thermal exposure of deposited steel with 20% Fe 20% Co 20% Ni 20% Mn 20% Cu in the air for up to ten weeks at 800 °C, a “protective Cr2O3layer”, and “high-entropy spinel coating” of (Fe, Co, Ni, Mn, Cu)3O4have been formed. During microwave cladding, the emergence of harder-phases has contributed to the raised hardness. The wear behavior after coating of 20% Fe 20% Co 20% Ni 20% Mn 20% Cu HEA on SS-304 substrate has significantly enhanced due to the strengthened wear resistance and hardness of the coatings. Findings have exhibited that the formation of (Fe, Co, Ni, Mn, Cu)3O4phase is a potential coating material for “SOFC interconnects” applications. Moreover, the cladding of SS304 with a composition of 20% Fe, 20% Co, 20% Ni, 20% Mn, and 20% Cu has demonstrated remarkable stability under thermal expansion studies. As the findings have revealed that the composite cladding has efficiently withstand significant variations in volume when subjected to elevated temperatures for a prolonged period of time, thus, exhibiting its superior thermal stability for SOFC-interconnect applications. Furthermore, the SEM images of the cladding surface, surface hardness, and tribocorrosion behavior of the coated material have been observed to identify the 20% Fe 20% Co 20% Ni 20% Mn 20% Cu HEA coating effect on SS-304 steel-substrate.
Characterisation, prevalence and severity of skin lesions caused by ophidiomycosis in a population of wild snakes
Authors: Allain Steven J. R. , Leech David I. , Hopkins Kevin , Seilern-Moy Katharina , Rodriguez-Ramos Fernandez Julia , Griffiths Richard A. , Lawson Becki
Published: March 2024

Ophidiomycosis is an emerging infectious disease affecting wild snakes in the Northern Hemisphere. Recently confirmed in Great Britain, the prevalence, severity and significance of ophidiomycosis has yet to be characterised in free-living snakes at a population level in Europe. Therefore, a population of barred grass snakes (Natrix helvetica) in eastern England was monitored for three seasons (May 2019 to October 2021), to investigate the prevalence (25.5%; 191/750 snakes) and severity of skin lesions and their aetiology. The most frequently observed skin lesion characteristics were changes in scale colour, crusting, and scale margin erosion. The majority of such lesions (96.9%; 185/191 snakes) was observed on the ventral surface along the length of the body. The severity of skin lesions was considered mild in more than half of the cases (53.1%; 98/191 snakes). Predominantly, skin lesions were observed in adult snakes (72.8%; 139/191 snakes). Combined histological examinations and qPCR tests of skin lesions from N. helvetica sloughs and/or carcasses confirmed a diagnosis of ophidiomycosis. Further targeted surveillance, supported by molecular and histological examinations to confirm skin lesion aetiology, is required to determine the extent to which our findings reflect the occurrence of ophidiomycosis in populations within wider landscapes.
IInception-CBAM-IBiGRU based fault diagnosis method for asynchronous motors
Authors: Li Zhengting , Wang Peiliang , yang Zeyu , Li Xiangyang , Jia Ruining
Published: March 2024

Aiming at the problems of insufficient extraction of asynchronous motor fault features by traditional deep learning algorithms and poor diagnosis of asynchronous motor faults in robust noise environments, this paper proposes an end-to-end fault diagnosis method for asynchronous motors based on IInception-CBAM-IBiGRU. The method first uses a signal-to-grayscale image conversion method to convert one-dimensional vibration signals into two-dimensional images and initially extracts shallow features through two-dimensional convolution; then the Improved Inception (IInception) module is used as a residual block to learning features at different scales with a residual structure, and extracts its important feature information through the Convolutional Block Attention Module (CBAM) to extract important feature information and adjust the weight parameters; then the feature information is input to the Improved Bi-directional Gate Recurrent Unit (IBiGRU) to extract its timing features further; finally, the fault identification is achieved by the SoftMax function. The primary hyperparameters in the model are optimized by the Weighted Mean Of Vectors Algorithm (INFO). The experimental results show that the method is effective in fault diagnosis of asynchronous motors, with an accuracy rate close to 100%, and can still maintain a high accuracy rate under the condition of low noise ratio, with good robustness and generalization ability.
Jewelry rock discrimination as interpretable data using laser-induced breakdown spectroscopy and a convolutional LSTM deep learning algorithm
Authors: Khalilian Pouriya , Rezaei Fatemeh , Darkhal Nazli , Karimi Parvin , Safi Ali , Palleschi Vincenzo , Melikechi Noureddine , Tavassoli Seyed Hassan
Published: March 2024

In this study, the deep learning algorithm of Convolutional Neural Network long short-term memory (CNN–LSTM) is used to classify various jewelry rocks such as agate, turquoise, calcites, and azure from various historical periods and styles related to Shahr-e Sokhteh. Here, the CNN–LSTM architecture includes utilizing CNN layers for the extraction of features from input data mixed with LSTMs for supporting sequence forecasting. It should be mentioned that interpretable deep learning-assisted laser induced breakdown spectroscopy helped achieve excellent performance. For the first time, this paper interprets the Convolutional LSTM effectiveness layer by layer in self-adaptively obtaining LIBS features and the quantitative data of major chemical elements in jewelry rocks. Moreover, Lasso method is applied on data as a factor for investigation of interoperability. The results demonstrated that LIBS can be essentially combined with a deep learning algorithm for the classification of different jewelry songs. The proposed methodology yielded high accuracy, confirming the effectiveness and suitability of the approach in the discrimination process.
Development of high performance microwave absorption modified epoxy coatings based on nano-ferrites
Authors: Abd El-Gawad W. M. , Eldesouki E. M. , Abd El-Ghany W. A.
Published: March 2024

With the rapid spread of wireless technologies and increasing electromagnetic energy, electromagnetic waves (EMW) have become a severe threat to human health. Therefore, minimizing the harmful effects of electromagnetic wave radiation is possible through the development of high-efficiency EMW absorption coatings. The aim of this work was to generate microwave absorbance coatings containing synthesized nano-CuFe2O4 and nano-CaFe2O4. Firstly, nano-CuFe2O4 and nano-CaFe2O4 were synthesized using the sol–gel method. Then, their structure, electrical, dielectric, and magnetic properties were investigated to find out the possibility of using these materials in high-frequency applications (e.g., microwave absorbance coatings). After that, two dosages (2.5 wt% and 5 wt%) of nano-CuFe2O4 and nano-CaFe2O4 were incorporated into epoxy resin to prepare modified epoxy resin as microwave coatings. The dielectric studies show that the AC conductivity of the prepared samples is high at high frequencies. Additionally, the magnetic properties reveal a low coercivity value, making these samples suitable for high-frequency devices. The microwave results illustrate that adding nano-ferrites with high content enhances the absorption characteristics of the tested films. The results showed that the two films have two absorption bands with RL < –10 dB ranging from 10.61 to 10.97 GHz and from 10.25 to 11.2 GHz. The minimum return loss achieved for the two cases is −13 and −16 dB, respectively. Indicating that the film coated with CuFe has a better absorption value than the one coated with CaFe.
Periodic stub implementation with plasmonic waveguide as a slow-wave coupled cavity for optical refractive index sensing
Authors: Tabatabaeian Zahra Sadat , Kazemi Fatemeh , Zarrabi Ferdows B.
Published: March 2024

Optical biosensors based on plasmonic nanostructures have attracted great interest due to their ability to detect small refractive index changes with high sensitivity. In this work, a novel plasmonic coupled cavity waveguide is proposed for refractive index sensing applications. The structure consists of a metal–insulator–metal waveguide side coupled to an array of asymmetric H-shape element, designed to provide dual-band resonances. The sharp transmission dips and large field enhancements associated with dual-band resonances can enable sensitive detection of material under test. The resonator array creates a slow light effect to improve light-matter interactions. The structure was simulated using the finite integration technique as the full-wave technique, and the sensitivity and figure of merit were extracted for different ambient refractive indices. The maximum sensitivity of 1774 nm/RIU and high figure of merit of 2 × 104 RIU−1 for the basic model and 1.15 × 105 RIU−1 for the modified model were achieved, demonstrating the potential for high-performance sensing. The unique transmission characteristics also allow for combined spectral shaping and detection over a broad bandwidth. The simple, compact geometry makes the design suitable for on-chip integration. This work demonstrates a promising refractive index sensor based on coupled dual-band resonators in a plasmonic waveguide.
Rising sea levels and the increase of shoreline wave energy at American Samoa
Authors: Barnes Austin T. , Becker Janet M. , Tagarino Kelley A. , O’Reilly William C. , Siegelman Mika , Thompson Philip R. , Merrifield Mark A.
Published: March 2024

American Samoa is experiencing rapid relative sea level rise due to increases in global sea level and significant post-2009 earthquake land subsidence, endangering homes and critical infrastructure. Wave and water-level observations collected over a fringing reef at Faga‘itua Bay, American Samoa, in 2017 reveal depth-limited shoreline sea-swell wave heights over the range of conditions sampled. Using field data to calibrate a one-dimensional, phase-resolving nonhydrostatic wave model (SWASH), we examine the influence of water level on wave heights over the reef for a range of current and future sea levels. Assuming a fixed reef bathymetry, model results predict rising sea levels will escalate nearshore extreme water levels that are dominated by an increase in nearshore sea-swell wave heights. Model results provide insight into how and at what reef depths rising sea levels reduce reef capacity to dissipate wave energy, compounding shoreline threats. This study aims to bring increased attention to the immediate threats to American Samoa’s way of life, and to demonstrate the utility of SWASH for extrapolating wave transformation to future sea level.
A technique for repeated blood and cerebrospinal fluid sampling from individual rats over time without the need for repeated anesthesia
Authors: Santandrea Erin , Aliakbari Farhang , Truscott Emily , McCaig Lynda , Donison Neil S. , Graham Danielle , Strong Michael J. , Volkening Kathryn
Published: March 2024

Ethical animal use follows the 3R’s: Replacement, Reduction and Refinement. Here, we present the use of simultaneous jugular vein and cisterna magna catheterization via a port system in rats for repeated fluid sampling for 14 consecutive days without loss of catheter patency. This technique allows repeated intra-animal sampling without anesthesia and, if used with pooling samples from a cohort of animals, replaces the need for terminal collections for sufficient sample volumes.
Hypoxia suppresses glucose-induced increases in collective cell migration in vascular endothelial cell monolayers
Authors: Sone Kazuki , Sakamaki Yuka , Hirose Satomi , Inagaki Mai , Tachikawa Masanori , Yoshino Daisuke , Funamoto Kenichi
Published: March 2024

Blood glucose levels fluctuate during daily life, and the oxygen concentration is low compared to the atmosphere. Vascular endothelial cells (ECs) maintain vascular homeostasis by sensing changes in glucose and oxygen concentrations, resulting in collective migration. However, the behaviors of ECs in response to high-glucose and hypoxic environments and the underlying mechanisms remain unclear. In this study, we investigated the collective migration of ECs simultaneously stimulated by changes in glucose and oxygen concentrations. Cell migration in EC monolayer formed inside the media channels of microfluidic devices was observed while varying the glucose and oxygen concentrations. The cell migration increased with increasing glucose concentration under normoxic condition but decreased under hypoxic condition, even in the presence of high glucose levels. In addition, inhibition of mitochondrial function reduced the cell migration regardless of glucose and oxygen concentrations. Thus, oxygen had a greater impact on cell migration than glucose, and aerobic energy production in mitochondria plays an important mechanistic role. These results provide new insights regarding vascular homeostasis relative to glucose and oxygen concentration changes.
The effect of quiet eye training on golf putting performance in pressure situation
Authors: He Qiao , Liu Yunzhou , Yang Yongtao
Published: March 2024

To explores the effect and mechanism of quiet eye training on the accuracy of golfers´ putts in pressure situations and provides methods and basis for targeted attention training and control. 22 young golfers in China golf team aged from 13 to 18 were randomly assigned to the experimental group (quiet eye training group) and the control group (technical guidance group) according to gender. Both groups of participants underwent two consecutive weeks of push training (3 sets per day, 20 golf putts per set, rest for 3 min between sets) separately in accordance with the guidance of a professional psychological research group and an expert coach. Eye tracking technology, biofeedback technology, and subjective evaluation methods were used to test and analyze the push process of the two groups of participants before and after training under pressure situations (Eye movement behaviors and the heart rate were recorded by ASL Mobile Eye-XG and NeXus-2 biofeedback, pressure and state anxiety were evaluated by self-rating pressure scale and S-AI. Golf putting performance was recorded by a research graduate assistant). A higher hit ratio as well as lower pressure and SAI level was founded in quiet eye training group in the pressure situation, the quiet eye movement time and total fixation time was longer than technical group. The quiet eye training group has a better putting performance. Quiet eye training can improve the golf putting performance in pressure situations. After quiet eye training, the state anxiety decreased, the quiet eye movement time and the total fixation time increased in pressure situations.
Muscle-inspired bi-planar cable routing: a novel framework for designing cable driven lower limb rehabilitation exoskeletons (C-LREX)
Authors: Prasad Rajan , El-Rich Marwan , Awad Mohammad I. , Agrawal Sunil K. , Khalaf Kinda
Published: March 2024

There is a growing interest in the research and development of Cable Driven Rehabilitation Devices (CDRDs) due to multiple inherent features attractive to clinical applications, including low inertia, lightweight, high payload-to-weight ratio, large workspace, and modular design. However, previous CDRDs have mainly focused on modifying motor impairment in the sagittal plane, despite the fact that neurological disorders, such as stroke, often involve postural control and gait impairment in multiple planes. To address this gap, this work introduces a novel framework for designing a cable-driven lower limb rehabilitation exoskeleton which can assist with bi-planar impaired posture and gait. The framework used a lower limb model to analyze different cable routings inspired by human muscle architecture and attachment schemes to identify optimal routing and associated parameters. The selected cable routings were safeguarded for non-interference with the human body while generating bi-directional joint moments. The subsequent optimal cable routing model was then implemented in simulations of tracking reference healthy trajectory with bi-planar impaired gait (both in the sagittal and frontal planes). The results showed that controlling joints independently via cables yielded better performance compared to dependent control. Routing long cables through intermediate hinges reduced the peak tensions in the cables, however, at a cost of induced additional joint forces. Overall, this study provides a systematic and quantitative in silico approach, featured with accessible graphical user interface (GUI), for designing subject-specific, safe, and effective lower limb cable-driven exoskeletons for rehabilitation with options for multi-planar personalized impairment-specific features.
A road data assets revenue allocation model based on a modified Shapley value approach considering contribution evaluation
Authors: Li Shiwei , Chu Lei , Wang Jisen , Zhang Yuzhao
Published: March 2024

This paper constructs a two-layer road data asset revenue allocation model based on a modified Shapley value approach. The first layer allocates revenue to three roles in the data value realization process: the original data collectors, the data processors, and the data product producers. It fully considers and appropriately adjusts the revenue allocation to each role based on data risk factors. The second layer determines the correction factors for different roles to distribute revenue among the participants within those roles. Finally, the revenue values of the participants within each role are synthesized to obtain a consolidated revenue distribution for each participant. Compared to the traditional Shapley value method, this model establishes a revenue allocation evaluation index system, uses entropy weighting and rough set theory to determine the weights, and adopts a fuzzy comprehensive evaluation and numerical analysis to assess the degree of contribution of participants. It fully accounts for differences in both the qualitative and quantitative contributions of participants, enabling a fairer and more reasonable distribution of revenues. This study provides new perspectives and methodologies for the benefit distribution mechanism in road data assets, which aid in promoting the market-based use of road data assets, and it serves as an important reference for the application of data assetization in the road transportation industry.
Population characteristics and diagnosis rate of chronic kidney disease by eGFR and proteinuria in Japanese clinical practice: an observational database study
Authors: Tanaka Tetsuhiro , Maruyama Shoichi , Chishima Noriharu , Akiyama Hiroki , Shimamoto Koji , Inokuchi Shoichiro , Yokota Keiji , Ozaki Asuka
Published: March 2024

Chronic kidney disease (CKD) guidelines recommend early identification and intervention to delay the progression of CKD. The Kidney Disease: Improving Global Outcomes (KDIGO) heatmap is widely used for risk evaluation in CKD management; however, real-world evidence on clinical characteristics based on the KDIGO heatmap remains limited worldwide including Japan. In order to understand the management of CKD including its diagnostic rates in a Japanese clinical setting on the basis of KDIGO heatmap, we utilized a medical record database that contains estimated glomerular filtration rate (eGFR) and urine protein data. Adult individuals (≥ 18 years) with two eGFR results of < 90 mL/min/1.73 m2, 90–360 days apart, were included. Approximately half of patients (452,996/788,059) had proteinuria test results and 6.9% (54,073) had quantitative results. CKD diagnosis rate in patients without proteinuria data was 5.9%, with a lower rate (2.9%) in stage G2; the corresponding rates with quantitative test results were 43.5% and 31.3%, respectively. The most frequent comorbidities were hypertension, diabetes, and cardiovascular disease, and their prevalence increased as the eGFR and proteinuria stages progressed. This study revealed a low rate of proteinuria assessment, especially using quantitative methods, and diagnosis in individuals with suspected CKD. With emerging treatment options to prevent CKD progression and complication onset, there is a need for early evaluation and diagnosis of CKD.
Comparison of blood loss between intra-articular microporous polysaccharide hemospheres powder and tranexamic acid following primary total knee arthroplasty
Authors: Jeon Young-Dae , Cha Jae-Ryong , Oh Jae-Min , Kim Sang-Gon , Park Ki-Bong
Published: March 2024

Total knee arthroplasty (TKA) is associated with substantial blood loss and tranexamic acid (TXA) effectively reduces postoperative bleeding. Although it is known that there is no difference between intravenous or intra-articular (IA) injection, the general interest is directed towards topical hemostatic agents regarding thromboembolic events in high-risk patients. This study aimed to compare the blood conservation effects of IA MPH powder and TXA in patients undergoing primary TKA. We retrospectively analyzed 103 patients who underwent primary TKA between June 2020 and December 2021. MPH powder was applied to the IA space before capsule closure (MPH group, n = 51). TXA (3 g) was injected via the drain after wound closure (TXA group, n = 52). All patients underwent drain clamping for three postoperative hours. The primary outcome was the drain output, and the secondary outcomes were the postoperative hemoglobin (Hb) levels during the hospitalization period and the perioperative blood transfusion rates. An independent Student’s t-test was used to determine differences between the two groups. The drain output in the first 24 h after surgery was significantly higher in the MPH group than in the TXA group. The postoperative Hb levels were significantly lower in the MPH group than in the TXA group. In patients with simultaneous bilateral TKA, there was a significant difference in the blood transfusion volumes and the rates between groups. It is considered that IA MPH powder cannot replace IA TXA because of an inferior efficacy in reducing blood loss and maintaining postoperative Hb levels in the early postoperative period after primary TKA. Moreover, in the case of simultaneous bilateral TKA, we do not recommend the use of IA MPH powder because it was notably less effective in the field of transfusion volume and rate.
Comparative study on fatigue evaluation of suspenders by introducing actual vehicle trajectory data
Authors: Pan Yue , Dong Yiqing , Wang Dalei , Cao Sugong , Chen Airong
Published: March 2024

Suspenders play a crucial role in transmitting loads from the bridge deck to the main cable in a suspension bridge. They are susceptible to fatigue due to repeated dynamic loads, particularly traffic loads. Traffic Load Models (TLMs), typically created using Monte–Carlo simulation and Weigh-In-Motion (WIM) data, are employed to evaluate this fatigue. However, these models often overlook practical vehicle trajectories and spatio-temporal distribution, which compromises the precision of fatigue assessments. In this study, we introduce a novel 2D Intelligent Driver Model (2D-IDM) that incorporates actual vehicle trajectories, with a particular focus on transverse vehicle movement. This enhancement aims to improve the fidelity of existing TLMs. To provide a clear, qualitative, and quantitative understanding of the effects of fatigue evaluation with or without actual trajectory characteristics, we have structured this paper as a comparative study. We compare our proposed model, denoted as TLM S-3, with two observation-based models (O-1 and O-2) and two simulation-based models (S-1 and S-2). We conducted an experimental case study on a long-span suspension bridge, where the actual traffic load trajectory was obtained using a WIM-Vision integrated system. To calculate fatigue damage considering both longitudinal and transverse directions, we established a multi-scale Finite Element Model (FEM) using solid element types to simulate the bridge girder. This model can generate the stress influence surface of the bridge and has been verified in both static and dynamic aspects. Our detailed comparative analysis demonstrates the consistency of the proposed 2D-IDM with the actual measured traffic load trajectories. This indicates that our approach can enhance the fidelity and precision of fatigue evaluations for bridge suspenders.
The immune cell infiltration-associated molecular subtypes and gene signature predict prognosis for osteosarcoma patients
Authors: Liu Bin , Liu Xiang-Yang , Wang Guo-Ping , Chen Yi-Xin
Published: March 2024

Host immune dysregulation involves in the initiation and development of osteosarcoma (OS). However, the exact role of immune cells in OS remains unknown. We aimed to distinguish the molecular subtypes and establish a prognostic model in OS patients based on immunocyte infiltration. The gene expression profile and corresponding clinical feature of OS patients were obtained from TARGET and GSE21257 datasets. MCP-counter and univariate Cox regression analyses were applied to identify immune cell infiltration-related molecular subgroups. Functional enrichment analysis and immunocyte infiltration analysis were performed between two subgroups. Furthermore, Cox regression and LASSO analyses were performed to establish the prognostic model for the prediction of prognosis and metastasis in OS patients. The subgroup with low infiltration of monocytic lineage (ML) was related to bad prognosis in OS patients. 435 DEGs were screened between the two subgroups. Functional enrichment analysis revealed these DEGs were involved in immune- and inflammation-related pathways. Three important genes (including TERT, CCDC26, and IL2RA) were identified to establish the prognostic model. The risk model had good prognostic performance for the prediction of metastasis and overall survival in OS patients. A novel stratification system was established based on ML-related signature. The risk model could predict the metastasis and prognosis in OS patients. Our findings offered a novel sight for the prognosis and development of OS.
Adoption of hooped-battens in cold-formed steel built-up columns for superior axial performance
Authors: Sadid A. Jamshid. , Dar Mohammad Adil , Ghowsi A. Fayeq , Aydın A. Cüneyt
Published: March 2024

Previous research on cold-formed steel (CFS) battened columns has identified the critical factors influencing their performance and accordingly, their limiting values for improved performance have been recommended. However, these studies involved connecting battens to the chords (channels) via their flanges, leaving the slenderest component disconnected from the web. This study introduces a novel hooped-batten (tubular-element) that links both webs and flanges of the chords together, thereby improving the structural integrity of the built-up system and curtailing the half-wave buckling length in the webs. As a result, axial strength and stability in these built-up columns may improve adequately. Firstly, a numerical model of a conventional CFS battened column was developed in ABAQUS and verified against test results on the same reported in literature. Afterward, the validated model was used to simulate the behaviour of CFS built-up columns with hooped-battens. Two key parameters i.e., unbraced chord slenderness and overall column slenderness were varied to explore their influence on the axial behaviour of built-up columns in terms of peak strengths, failure modes and load-displacement characteristics. The performance of the hooped-battened columns was compared with the identical conventional battened columns, which reflects that the former exhibits superior strength and stability characteristics over the latter.
Cellular mechanisms underlying carry-over effects after magnetic stimulation
Authors: Ye Hui , Dima Maria , Hall Vincent , Hendee Jenna
Published: March 2024

Magnetic fields are widely used for neuromodulation in clinical settings. The intended effect of magnetic stimulation is that neural activity resumes its pre-stimulation state right after stimulation. Many theoretical and experimental works have focused on the cellular and molecular basis of the acute neural response to magnetic field. However, effects of magnetic stimulation can still last after the termination of the magnetic stimulation (named “carry-over effects”), which could generate profound effects to the outcome of the stimulation. However, the cellular and molecular mechanisms of carry-over effects are largely unknown, which renders the neural modulation practice using magnetic stimulation unpredictable. Here, we investigated carry-over effects at the cellular level, using the combination of micro-magnetic stimulation (µMS), electrophysiology, and computation modeling. We found that high frequency magnetic stimulation could lead to immediate neural inhibition in ganglion neurons from Aplysia californica, as well as persistent, carry-over inhibition after withdrawing the magnetic stimulus. Carry-over effects were found in the neurons that fired action potentials under a variety of conditions. The carry-over effects were also observed in the neurons when the magnetic field was applied across the ganglion sheath. The state of the neuron, specifically synaptic input and membrane potential fluctuation, plays a significant role in generating the carry-over effects after magnetic stimulation. To elucidate the cellular mechanisms of such carry-over effects under magnetic stimulation, we simulated a single neuron under magnetic stimulation with multi-compartment modeling. The model successfully replicated the carry-over effects in the neuron, and revealed that the carry-over effect was due to the dysfunction of the ion channel dynamics that were responsible for the initiation and sustaining of membrane excitability. A virtual voltage-clamp experiment revealed a compromised Na conductance and enhanced K conductance post magnetic stimulation, rendering the neurons incapable of generating action potentials and, therefore, leading to the carry over effects. Finally, both simulation and experimental results demonstrated that the carry-over effects could be controlled by disturbing the membrane potential during the post-stimulus inhibition period. Delineating the cellular and ion channel mechanisms underlying carry-over effects could provide insights to the clinical outcomes in brain stimulation using TMS and other modalities. This research incentivizes the development of novel neural engineering or pharmacological approaches to better control the carry-over effects for optimized clinical outcomes.
Deep learning solutions for smart city challenges in urban development
Authors: Wu Pengjun , Zhang Zhanzhi , Peng Xueyi , Wang Ran
Published: March 2024

In the realm of urban planning, the integration of deep learning technologies has emerged as a transformative force, promising to revolutionize the way cities are designed, managed, and optimized. This research embarks on a multifaceted exploration that combines the power of deep learning with Bayesian regularization techniques to enhance the performance and reliability of neural networks tailored for urban planning applications. Deep learning, characterized by its ability to extract complex patterns from vast urban datasets, has the potential to offer unprecedented insights into urban dynamics, transportation networks, and environmental sustainability. However, the complexity of these models often leads to challenges such as overfitting and limited interpretability. To address these issues, Bayesian regularization methods are employed to imbue neural networks with a principled framework that enhances generalization while quantifying predictive uncertainty. This research unfolds with the practical implementation of Bayesian regularization within neural networks, focusing on applications ranging from traffic prediction, urban infrastructure, data privacy, safety and security. By integrating Bayesian regularization, the aim is to, not only improve model performance in terms of accuracy and reliability but also to provide planners and decision-makers with probabilistic insights into the outcomes of various urban interventions. In tandem with quantitative assessments, graphical analysis is wielded as a crucial tool to visualize the inner workings of deep learning models in the context of urban planning. Through graphical representations, network visualizations, and decision boundary analysis, we uncover how Bayesian regularization influences neural network architecture and enhances interpretability.
Chemical disinfection as a simple and reliable method to control the amphibian chytrid fungus at breeding points of endangered amphibians
Authors: Thumsová Barbora , González-Miras Emilio , Rubio Ángel , Granados Ignacio , Bates Kieran A. , Bosch Jaime
Published: March 2024

Chytridiomycosis caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd) is pushing amphibians towards extinction. Whilst mitigation methods were suggested a decade ago, we lack field trials testing their efficacy. We used the agrochemical fungicide, tebuconazole, to treat Bd infected breeding waterbodies of an endangered species that is highly susceptible to the fungus. Just two applications of tebuconazole led to a significant reduction in infection loads in the vast majority of sites, and at six sites the disinfection remained one/two-years post-application. Tebuconazole values drastically decreased in the waterbodies within a week after application, with no significant effects on their hydrochemical and hydrobiological characteristics. Although the use of chemicals in natural populations is undesirable, the growing existential threat to amphibians all over the world indicates that effective interventions in selected populations of endangered species are urgently needed.
Prediction of lncRNA and disease associations based on residual graph convolutional networks with attention mechanism
Authors: Wang Shengchang , Qiao Jiaqing , Feng Shou
Published: March 2024

LncRNAs are non-coding RNAs with a length of more than 200 nucleotides. More and more evidence shows that lncRNAs are inextricably linked with diseases. To make up for the shortcomings of traditional methods, researchers began to collect relevant biological data in the database and used bioinformatics prediction tools to predict the associations between lncRNAs and diseases, which greatly improved the efficiency of the study. To improve the prediction accuracy of current methods, we propose a new lncRNA-disease associations prediction method with attention mechanism, called ResGCN-A. Firstly, we integrated lncRNA functional similarity, lncRNA Gaussian interaction profile kernel similarity, disease semantic similarity, and disease Gaussian interaction profile kernel similarity to obtain lncRNA comprehensive similarity and disease comprehensive similarity. Secondly, the residual graph convolutional network was used to extract the local features of lncRNAs and diseases. Thirdly, the new attention mechanism was used to assign the weight of the above features to further obtain the potential features of lncRNAs and diseases. Finally, the training set required by the Extra-Trees classifier was obtained by concatenating potential features, and the potential associations between lncRNAs and diseases were obtained by the trained Extra-Trees classifier. ResGCN-A combines the residual graph convolutional network with the attention mechanism to realize the local and global features fusion of lncRNA and diseases, which is beneficial to obtain more accurate features and improve the prediction accuracy. In the experiment, ResGCN-A was compared with five other methods through 5-fold cross-validation. The results show that the AUC value and AUPR value obtained by ResGCN-A are 0.9916 and 0.9951, which are superior to the other five methods. In addition, case studies and robustness evaluation have shown that ResGCN-A is an effective method for predicting lncRNA-disease associations. The source code for ResGCN-A will be available at https://github.com/Wangxiuxiun/ResGCN-A.
A tunable flat terahertz lens using Dirac semimetals: a simulation study
Authors: Panahianfar P. , Rezaei B. , Darafsheh A.
Published: March 2024

We propose and design a flat and tunable terahertz lens achieved through a two-dimensional photonic crystal composed of an array of rods made of a Dirac semimetal placed in air as the background medium. The structure of interest is a graded index photonic crystal, made possible by the slight variations in the rods’ radii in a direction perpendicular to the direction of the light propagation. Dirac semimetals' ability to respond to variations in their Fermi energy level manifested as a change in the refractive index provides the tunability of our proposed lens. The interaction of electromagnetic waves with the designed structure is investigated for both transverse magnetic and transverse electric polarizations using two-dimensional finite-difference time-domain method.
UV-light-responsive Ag/TiO2/PVA nanocomposite for photocatalytic degradation of Cr, Ni, Zn, and Cu heavy metal ions
Authors: Dehghani Mohammad Taha , Delnavaz Mohammad
Published: March 2024

The rapid growth of industrialization has led to the uncontrolled pollution of the environment, and rapid action is needed. This study synthesized Ag/TiO2/polyvinyl alcohol (PVA) nano photocatalyst for promising light-derived photocatalytic removal of heavy metal ions. The design of experiment (DOE) was used to study the effect of important factors (pH, reaction time, and photocatalyst dosage) to maximize the final performance of the photocatalyst. In the optimized condition, the Ag/TiO2/PVA nano-photocatalyst removed more than 94% of Cr6+ in 180 min, and the efficiency was more than 70% for Cu2+, Zn2+, and Ni2+ metal ions. The adsorption of the heavy metal ions on the photocatalyst was described well with the Langmuir isotherm, while the pseudo-second-order linear kinetic model fitted with the experimental data. The nano-photocatalyst's stability was confirmed after maintaining its performance for five successive runs. The enhanced photocatalytic activity for the heavy metal ions removal can be attributed to the presence of metallic silver nanoparticles (electron transfer and plasmonic fields mechanisms) and PVA, which delayed the recombination of electron–hole. The synthesized ternary Ag/TiO2/PVA nano-photocatalyst showed promising performance for the elimination of heavy metal ions and can be used for environmental remediation purposes.
Impact of industrial versus biomass burning aerosols on the Atlantic Meridional Overturning Circulation
Authors: Allen Robert J. , Vega Claire , Yao Eva , Liu Wei
Published: March 2024

The ocean’s major circulation system, the Atlantic Meridional Overturning Circulation (AMOC), is slowing down. Such weakening is consistent with warming associated with increasing greenhouse gases, as well as with recent decreases in industrial aerosol pollution. The impact of biomass burning aerosols on the AMOC, however, remains unexplored. Here, we use the Community Earth System Model version 1 Large Ensemble to quantify the impact of both aerosol types on the AMOC. Despite relatively small changes in North Atlantic biomass burning aerosols, significant AMOC evolution occurs, including weakening from 1920 to ~1970 followed by AMOC strengthening. These changes are largely out of phase relative to the corresponding AMOC evolution under industrial aerosols. AMOC responses are initiated by thermal changes in sea surface density flux due to altered shortwave radiation. An additional dynamical mechanism involving the North Atlantic sea-level pressure gradient is important under biomass-burning aerosols. AMOC-induced ocean salinity flux convergence acts as a positive feedback. Our results show that biomass-burning aerosols reinforce early 20th-century AMOC weakening associated with greenhouse gases and also partially mute industrial aerosol impacts on the AMOC. Recent increases in wildfires suggest biomass-burning aerosols may be an important driver of future AMOC variability.
TP53 gain-of-function mutations promote osimertinib resistance via TNF-α–NF-κB signaling in EGFR-mutated lung cancer
Authors: Ibusuki Ritsu , Iwama Eiji , Shimauchi Atsushi , Tsutsumi Hirono , Yoneshima Yasuto , Tanaka Kentaro , Okamoto Isamu
Published: March 2024

EGFR tyrosine kinase inhibitors (TKIs) are effective against EGFR-mutated lung cancer, but tumors eventually develop resistance to these drugs. Although TP53 gain-of-function (GOF) mutations promote carcinogenesis, their effect on EGFR-TKI efficacy has remained unclear. We here established EGFR-mutated lung cancer cell lines that express wild-type (WT) or various mutant p53 proteins with CRISPR-Cas9 technology and found that TP53-GOF mutations promote early development of resistance to the EGFR-TKI osimertinib associated with sustained activation of ERK and expression of c-Myc. Gene expression analysis revealed that osimertinib activates TNF-α–NF-κB signaling specifically in TP53-GOF mutant cells. In such cells, osimertinib promoted interaction of p53 with the NF-κB subunit p65, translocation of the resulting complex to the nucleus and its binding to the TNF promoter, and TNF-α production. Concurrent treatment of TP53-GOF mutant cells with the TNF-α inhibitor infliximab suppressed acquisition of osimertinib resistance as well as restored osimertinib sensitivity in resistant cells in association with attenuation of ERK activation and c-Myc expression. Our findings indicate that induction of TNF-α expression by osimertinib in TP53-GOF mutant cells contributes to the early development of osimertinib resistance, and that TNF-α inhibition may therefore be an effective strategy to overcome such resistance in EGFR-mutant lung cancer with TP53-GOF mutations.
Exceptionally strong coupling of defect emission in hexagonal boron nitride to stacking sequences
Authors: Li Song , Pershin Anton , Li Pei , Gali Adam
Published: March 2024

Van der Waals structures present a unique opportunity for tailoring material interfaces and integrating photonic functionalities. By precisely manipulating the twist angle and stacking sequences, it is possible to elegantly tune and functionalize the electronic and optical properties of layered van der Waals structures. Among these materials, two-dimensional hexagonal boron nitride (hBN) stands out for its remarkable optical properties and wide band gap, making it a promising host for solid state single photon emitters at room temperature. Previous investigations have demonstrated the observation of bright single photon emission in hBN across a wide range of wavelengths. In this study, we unveil an application of van der Waals technology in modulating their spectral shapes and brightness by carefully controlling the stacking sequences and polytypes. Our theoretical analysis reveals remarkably large variations in the Huang-Rhys factors–an indicator of the interaction between a defect and its surrounding lattice–reaching up to a factor of 3.3 for the same defect in different stacking sequences. We provide insights into the underlying mechanism behind these variations, shedding light on the design principles necessary to achieve rational and precise control of defect emission. This work paves the way for enhancing defect identification and facilitating the engineering of highly efficient single photon sources and qubits using van der Waals materials.