bluuebunny/crossref_metadata_2025_split huggingface dataset:
Data correction and verification of thermal simulation experiments under the influence of bulging belly
Authors: Zheng Bing , Xu Dong , Zou Zhipeng , Wang Yiqun , Guo Longxin , Zhao Hongyang , Ju Dongying 
Published: September 2023

AbstractDuring the thermal simulation compression test, the formation of an obvious bulge in the specimen leads to a certain deviation between the calculated and actual values of the true stress. The finite element method was used to simulate the single-pass compression of specimens of 34CrNi3MoV steel and obtain the actual nonuniform deformation of the bulging belly during the compression process, and the results were applied to correct experimental flow curves. The results showed that the deformation conditions had a significant influence on the nonuniformity of the specimen deformation during the compression process, and all the modified flow curves were lower than the original ones. The size of the bulge and the metal flow line in the finite element simulation were consistent with the test results. The load value obtained by using the modified flow curve was similar to the load value measured in the test, which indicated that the modified flow curve was very close to the real flow force curve of the material. The method used to modify the flow force curve is simple and practical.
Concept of a fully-implantable system to monitor tumor recurrence
Authors: Schaufler Anna , Sanin Ahmed Y. , Sandalcioglu I. Erol , Hartmann Karl , Croner Roland S. , Perrakis Aristotelis , Wartmann Thomas , Boese Axel , Kahlert Ulf D. , Fischer Igor 
Published: September 2023

AbstractCurrent treatment for glioblastoma includes tumor resection followed by radiation, chemotherapy, and periodic post-operative examinations. Despite combination therapies, patients face a poor prognosis and eventual recurrence, which often occurs at the resection site. With standard MRI imaging surveillance, histologic changes may be overlooked or misinterpreted, leading to erroneous conclusions about the course of adjuvant therapy and subsequent interventions. To address these challenges, we propose an implantable system for accurate continuous recurrence monitoring that employs optical sensing of fluorescently labeled cancer cells and is implanted in the resection cavity during the final stage of tumor resection. We demonstrate the feasibility of the sensing principle using miniaturized system components, optical tissue phantoms, and porcine brain tissue in a series of experimental trials. Subsequently, the system electronics are extended to include circuitry for wireless energy transfer and power management and verified through electromagnetic field, circuit simulations and test of an evaluation board. Finally, a holistic conceptual system design is presented and visualized. This novel approach to monitor glioblastoma patients is intended to early detect recurrent cancerous tissue and enable personalization and optimization of therapy thus potentially improving overall prognosis.
Assessment of health risks associated with heavy metal concentration in seafood from North-Western Croatia
Authors: Traven Luka , Marinac-Pupavac Sandra , Žurga Paula , Linšak Željko , Pavičić Žeželj Sandra , Glad Marin , Vukić Lušić Darija 
Published: September 2023

AbstractThe following study aims at assessing the health risks associated with the consumption of the most commonly consumed seafood in the north-western part of Croatia due to the presence of heavy metals. Samples of seafood were collected and analysed for lead (Pb), cadmium (Cd), and mercury (Hg) content. Analyses of Cd and Pb were carried out by inductively coupled plasma mass spectrometry (ICP-MS) whereas Hg content was measured using atomic absorption spectrometry (AAS). Metal concentrations were in the following order Hg > Pb > Cd for the gilthead seabream, European hake, sardines, and tuna fish whereas in the Patagonian squid cadmium (Cd) was the heavy metal with the highest concentration, with the order of other metals being Cd > Hg > Pb. The heavy metal concentrations have been used to address the health risks using the Estimated Weekly Intake (EWI), Target Hazard Quotients (THQ), and Hazard Indices (HI). The findings revealed that the concentrations of the tested heavy metals, expressed on a per wet weight basis, did not exceed the Maximum Residue Levels (MRL) for those compounds mandated by national Croatian legislation. However, the HI for Hg was above 1, indicating a risk of adverse health effects due to the presence of this heavy metal in the consumed seafood. We conclude that the consumption of certain type of seafood such as the tuna fish should be limited when sensitive segments of the population such as children, elderly and pregnant women are concerned. Our results strongly advocate for a more stringent seafood quality control in the region.
Electron beam driven ion-acoustic solitary waves in plasmas with two kappa-distributed electrons
Authors: Hatami M. M. 
Published: September 2023

AbstractFormation and the basic features of arbitrary amplitude ion-acoustic solitary waves (IASWs) in a plasma consisting of warm positive ions, two$$\kappa$$κ-distributed electrons and an electron beam are investigated by using the Sagdeev pseudopotential approach. It is shown that the soliton existence domain (Mach number limits) sensitively depends on temperature of ions, spectral index of cool electrons and concentration of hot electron species while spectral index of hot electrons, hot-to-cool electron temperature ratio and also concentration of electron beam do not considerably affect this domain. It is also found that temperature of electron beam only affect the existence domain of rarefactive solitons. Furthermore, it is shown that considered plasma medium supports the coexistence of positive and negative IASWs. Moreover, effect of different plasma parameters such as hot-to-cool electron density ratio, ion-to-cool electron temperature ratio, beam-to-ion density ratio, hot-to-cool electron temperature ratio and superthermality index of electron species on the basic features of positive and negative IASWs is investigated numerically. Finally, the effect of plasma parameters on the parametric regime of coexistence of compressive and rarefactive IASWs is studied and, for example, effect of temperature of positive ions and number density of hot electrons on polarity of IASWs is numerically investigated.
A multimodal radiomic machine learning approach to predict the LCK expression and clinical prognosis in high-grade serous ovarian cancer
Authors: Zhan Feng , He Lidan , Yu Yuanlin , Chen Qian , Guo Yina , Wang Lili 
Published: September 2023

AbstractWe developed and validated a multimodal radiomic machine learning approach to noninvasively predict the expression of lymphocyte cell-specific protein-tyrosine kinase (LCK) expression and clinical prognosis of patients with high-grade serous ovarian cancer (HGSOC). We analyzed gene enrichment using 343 HGSOC cases extracted from The Cancer Genome Atlas. The corresponding biomedical computed tomography images accessed from The Cancer Imaging Archive were used to construct the radiomic signature (Radscore). A radiomic nomogram was built by combining the Radscore and clinical and genetic information based on multimodal analysis. We compared the model performances and clinical practicability via area under the curve (AUC), Kaplan–Meier survival, and decision curve analyses. LCK mRNA expression was associated with the prognosis of HGSOC patients, serving as a significant prognostic marker of the immune response and immune cells infiltration. Six radiomic characteristics were chosen to predict the expression of LCK and overall survival (OS) in HGSOC patients. The logistic regression (LR) radiomic model exhibited slightly better predictive abilities than the support vector machine model, as assessed by comparing combined results. The performance of the LR radiomic model for predicting the level of LCK expression with five-fold cross-validation achieved AUCs of 0.879 and 0.834, respectively, in the training and validation sets. Decision curve analysis at 60 months demonstrated the high clinical utility of our model within thresholds of 0.25 and 0.7. The radiomic nomograms were robust and displayed effective calibration. Abnormally high expression of LCK in HGSOC patients is significantly correlated with the tumor immune microenvironment and can be used as an essential indicator for predicting the prognosis of HGSOC. The multimodal radiomic machine learning approach can capture the heterogeneity of HGSOC, noninvasively predict the expression of LCK, and replace LCK for predictive analysis, providing a new idea for predicting the clinical prognosis of HGSOC and formulating a personalized treatment plan.
Skin microbiota secretomes modulate cutaneous innate immunity against Borrelia burgdorferi s.s
Authors: Baquer F. , Jaulhac B. , Barthel C. , Paz M. , Wolfgramm J. , Müller A. , Boulanger N. , Grillon A. 
Published: September 2023

AbstractIn Lyme borreliosis, the skin constitutes a major interface for the host, the bacteria and the tick. Skin immunity is provided by specialized immune cells but also by the resident cells: the keratinocytes and the fibroblasts. Discoveries on the role of the microbiome in the modulation of skin inflammation and immunity have reinforced the potential importance of the skin in vector-borne diseases. In this study, we analyzed in vitro the interaction of human primary keratinocytes and fibroblasts with Borrelia burgdorferi sensu stricto N40 in presence or absence of bacterial commensal supernatants. We aimed to highlight the role of resident skin cells and skin microbiome on the inflammation induced by B. burgdorferi s.s.. The secretomes of Staphylococcus epidermidis, Corynebacterium striatum and Cutibacterium acnes showed an overall increase in the expression of IL-8, CXCL1, MCP-1 and SOD-2 by fibroblasts, and of IL-8, CXCL1, MCP-1 and hBD-2 in the undifferentiated keratinocytes. Commensal bacteria showed a repressive effect on the expression of IL-8, CXCL1 and MCP-1 by differentiated keratinocytes. Besides the inflammatory effect observed in the presence of Borrelia on all cell types, the cutaneous microbiome appears to promote a rapid innate response of resident skin cells during the onset of Borrelia infection.
Reduced length of nodes of Ranvier and altered proteoglycan immunoreactivity in prefrontal white matter in major depressive disorder and chronically stressed rats
Authors: Miguel-Hidalgo José Javier , Hearn Erik , Moulana Mohadetheh , Saleem Khunsa , Clark Austin , Holmes Maggie , Wadhwa Kashish , Kelly Isabella , Stockmeier Craig Allen , Rajkowska Grazyna 
Published: September 2023

AbstractMajor depressive disorder (MDD) and chronic unpredictable stress (CUS) in animals feature comparable cellular and molecular disturbances that involve neurons and glial cells in gray and white matter (WM) in prefrontal brain areas. These same areas demonstrate disturbed connectivity with other brain regions in MDD and stress-related disorders. Functional connectivity ultimately depends on signal propagation along WM myelinated axons, and thus on the integrity of nodes of Ranvier (NRs) and their environment. Various glia-derived proteoglycans interact with NR axonal proteins to sustain NR function. It is unclear whether NR length and the content of associated proteoglycans is altered in prefrontal cortex (PFC) WM of human subjects with MDD and in experimentally stressed animals. The length of WM NRs in histological sections from the PFC of 10 controls and 10 MDD subjects, and from the PFC of control and CUS rats was measured. In addition, in WM of the same brain region, five proteoglycans, tenascin-R and NR protein neurofascin were immunostained or their levels measured with western blots. Analysis of covariance and t-tests were used for group comparisons. There was dramatic reduction of NR length in PFC WM in both MDD and CUS rats. Proteoglycan BRAL1 immunostaining was reduced at NRs and in overall WM of MDD subjects, as was versican in overall WM. Phosphacan immunostaining and levels were increased in both in MDD and CUS. Neurofascin immunostaining at NRs and in overall WM was significantly increased in MDD. Reduced length of NRs and increased phosphacan and neurocan in MDD and stressed animals suggest that morphological and proteoglycan changes at NRs in depression may be related to stress exposure and contribute to connectivity alterations. However, differences between MDD and CUS for some NR related markers may point to other mechanisms affecting the structure and function of NRs in MDD.
Study on development methods of different types of gas wells in tight sandstone gas reservoirs
Authors: He Jie , Liu Zhiwei , Zhang Heng , Xie Shenghong , Wang Xiqiang , Zhu Yushuang 
Published: September 2023

AbstractReasonable production allocation of tight sandstone gas reservoirs is an important basis for efficient development of gas wells. Taking Block XX in Ordos Basin as an example, the modified flowing material balance equation was established considering the variation of gas viscosity and compression coefficient, the advantages and disadvantages of the method were discussed, and a reasonable production allocation process for gas wells was developed. The results show that: ① The commonly used flow material balance method ignores the change of natural gas compression coefficient, viscosity and deviation coefficient in the production process. The slope of the relationship curve between bottom hole pressure and cumulative production and the slope of the relationship curve between average formation pressure and cumulative production are not equal After considering this change. Compared with the results calculated by the material balance method, the results calculated by the flow material balance method are smaller. ② The production of 660 gas wells in the study area during stable production period is verified. Compared with the open flow method, the dynamic reserve allocation method is better, with an error of 0.06%. ③ The new method in this paper is used to allocate production for different types of gas wells. The cumulative production of different types of gas wells shows different degrees of increase. The I, II, III and IV types of gas wells increase by 32.26%, 30.29%, 23.58% and 25.07% respectively. This study provides technical support for dynamic reserve calculation and reasonable production allocation of gas wells in the study area, and has important guiding significance for the formulation of reasonable development plan and economic and efficient development of tight sandstone gas reservoirs.
Inverse design of optical lenses enabled by generative flow-based invertible neural networks
Authors: Luo Menglong , Lee Sang-Shin 
Published: September 2023

AbstractDeveloping an optical geometric lens system in a conventional way involves substantial effort from designers to devise and assess the lens specifications. An expeditious and effortless acquisition of lens parameters satisfying the desired lens performance requirements can ease the workload by avoiding complex lens design process. In this study, we adopted the Glow, a generative flow model, which utilizes latent Gaussian variables to effectively tackle the issues of one-to-many mapping and information loss caused by dimensional disparities between high-dimensional lens structure parameters and low-dimensional performance metrics. We developed two lenses to tailor the vertical field of view and magnify the horizontal coverage range using two Glow-based invertible neural networks (INNs). By directly inputting the specified lens performance metrics into the proposed INNs, optimal inverse-designed lens specifications can be obtained efficiently with superb precision. The implementation of Glow-assisted INN approach is anticipated to significantly streamline the optical lens design workflows.
Experimental study on the axial tensile properties of polypropylene fiber reinforced concrete
Authors: Zhang Xutao , Yin Ruijie , Chen Yunjuan , Lou Chao 
Published: September 2023

AbstractIn order to study the axial tensile properties of polypropylene fiber reinforced concrete, an axial tensile test device for concrete is developed in this paper. The device is composed of three parts: rigid frame, spherical hinge and puller, and specimen fabrication part. The test device can accurately measure the tensile strength and peak tensile strain of concrete, and perfectly solves the eccentricity problem of concrete specimens under tension. It can measure the post peak segment tensile strain, such that the whole process tensile stress–strain curve can be obtained. The axial tensile test of polypropylene fiber concrete was carried out using the above test device, and the results show that the tensile strength of concrete can be clearly improved by adding polypropylene fiber, which makes the tensile failure of concrete show certain plastic characteristics. The test results show that with the increase in fiber content, the tensile strength of concrete increases first and then decreases. The effects of polypropylene fiber content and curing age on the tensile properties of concrete were studied and the optimum polypropylene fiber content was determined. When the fiber content is 0.9 kg/m3, the tensile strength of concrete reaches the maximum value. The splitting tensile test of concrete under the same condition was carried out simultaneously. The damage phenomenon and test results of the axial tensile test and splitting tensile test of concrete were compared and analyzed, and the applicability of the new developed device in the concrete axial tensile test was verified.
Anti-EGFR bioengineered bacterial outer membrane vesicles as targeted immunotherapy candidate in triple-negative breast tumor murine model
Authors: Rezaei Adriani Razieh , Mousavi Gargari Seyed Latif , Bakherad Hamid , Amani Jafar 
Published: September 2023

AbstractCancer immunotherapy employing checkpoint inhibitors holds great promise across diverse cancers; nonetheless, a substantial proportion of patients (ranging from 55 to 87%) remain unresponsive to this treatment. To amplify therapeutic efficiency, we propose a synergistic therapeutic strategy that entails the deployment of targeted nano-sized particles carrying Toll-like receptor (TLR) agonists to the tumor site. This innovative approach seeks to activate intratumoral antigen-presenting cells using bioengineered outer membrane vesicles (OMVs) derived from gram-negative bacteria. These OMVs possess inherent attributes of surface-exposed immune stimulators and TLR-activating components, rendering them intriguing candidates for investigation. These OMVs were meticulously designed to selectively target cancer cells exhibiting an overexpression of epidermal growth factor receptor (EGFR). To gauge the precision of this targeting, the conducted affinity-based assays aimed at determining the equilibrium dissociation constant of the single-chain variable fragment employed for this purpose. In vitro experiments confirmed the OMVs' proficiency in adhering to EGFR-overexpressed cancer cells. Moreover, the evaluation extended to an in vivo context, where the therapeutic effect of nanovesicles was appraised within the tumor microenvironment of the triple-negative breast cancer mouse model. Notably, both intraperitoneal and intratumoral administrations of nanovesicles exhibited the ability to activate natural killer cells and skew M2 macrophage towards an M1 phenotype. The combined scrutiny of in vitro and in vivo findings underscores the potential efficiency of OMVs as a promising strategy for future anti-tumor endeavors.
Superheated steam production from a large-scale latent heat storage system within a cogeneration plant
Authors: Johnson Maike , Fiss Michael 
Published: September 2023

AbstractDuring phase change, phase change materials absorb or release latent heat at a nearly constant temperature. Latent heat thus can be stored and integrated with evaporation/condensation systems such as steam generators within a relatively narrow range of operating temperature. Storage units and systems have been proven at pilot scale but none to-date have been integrated in industrial processes. This remains a challenge, due to the size of the systems and to hurdles in design, permission and build. Here we integrate a megawatt-scale latent heat storage into a cogeneration power plant in Wellesweiler-Neunkirchen, Saarland, Germany. The storage produced superheated steam for at least 15 min at more than 300 °C at a mass flow rate of 8 tonnes per hour. This provided thermal power at 5.46 MW and results in 1.9 MWh thermal capacity. Our study demonstrates the feasibility of using latent heat storage in the industrial production of superheated steam.
Stock index forecasting using DACLAMNN: A new intelligent highly accurate hybrid ACLSTM/Markov neural network predictor
Authors: Safari Ashkan , Badamchizadeh Mohammad Ali 
Published: September 2023

AbstractThe authors present the investigation of a new hybrid predictive model of Duplex Attention‐based Coupled LSTM Markov Averaged Neural Network, known as DACLMANN. The financial field, particularly the stock market, heavily relies on accurate predictive models. DACLMANN comprises four essential components: two LSTM blocks, an Averagiser and a Markov Neural Network block. The first LSTM block is composed of two hidden layers, each containing 50 neurons and a dense layer with 25 neurons. The second LSTM block consists of two hidden layers, each with 100 neurons, and a dense layer with 50 neurons. The Averagiser plays a crucial role by averaging the closing prices and predicted values from the first LSTM block, resulting in a 90% gain. These averaged values are then fed into the second LSTM block for further prediction. Finally, the predictions undergo evaluation using the Markov model, yielding the final prediction. To assess the performance of DACLMANN, it was tested on 22 years of stock prices for the AMZN index. The evaluation metrics used by the authors include an R2 of 0.76, mean absolute error of 6.81216, root mean square error of 8.6040, Precision of 1, Accuracy of 1, Recall of 1 and F1 of 1. Additionally, DACLMANN achieved a Mean Absolute Percentage Error of less than 0.043% and an RMSPE of less than 2.1%. These results not only demonstrate the effectiveness of the proposed model but also authenticate the prediction outcomes. DACLMANN offers several advantages over traditional predictive models in the stock market. By combining the strengths of Duplex Attention‐based Coupled LSTM, Averagiser, and Markov Neural Network, DACLMANN leverages the power of deep learning, attention mechanisms, and sequential modelling. This hybrid approach enables DACLMANN to capture intricate patterns and dependencies present in stock market data, leading to more accurate and reliable predictions. The robust evaluation metrics further validate the superiority of DACLMANN in predicting stock prices.