bluuebunny/crossref_metadata_2025_split huggingface dataset:
AI-based FPGA Accelerator for EVs Battery Management System
Authors: Nagarale Satyashil D. , Patil B. P. 
Published: May 2023

Abstract
The swift progress of Electric Vehicles (EVs) and Hybrid-Electric Vehicles (HEVs) has driven advancements in Battery Management Systems (BMS). However, optimizing the algorithms that drive these systems remains a challenge. Recent breakthroughs in data science, particularly in deep learning networks, have introduced the Long Short-Term Memory (LSTM) network as a solution for sequence problems. While GPUs and ASICs have been used to improve performance in AI-based applications, Field Programmable Gate Arrays (FPGAs) have gained popularity due to their low power consumption and high-speed acceleration, making them ideal for AI implementation. One of the critical components of EVs and HEVs is the BMS, which performs operations to optimize the use of energy stored in lithium-ion (LiB) batteries. Due to the nonlinear electrochemical nature of these batteries, estimating States of Charge, States of Health (SOH), and Remaining Useful Life (RUL) is challenging. This paper proposes an advanced AI-based BMS that uses LSTM to accurately estimate Lithium-ion Battery states, providing crucial information for battery performance optimization. The proposed design is implemented in Python for training and validation. The hardware prototype is synthesized using Xilinx Vitis High-Level Synthesis (HLS) and implemented on Xilinx Zynq System-on-Chip (SoC) PYNQ Z2 board, achieving low RMSE values of 0.3438 and 0.3681 in training and validation, respectively.
Research on Thermal Aging Properties of Modified E-51 Epoxy Resin for Power-on Warning Helmet
Authors: Shu Shi , Zhang Xudong , Yang Jiaquan , Yang Yang , Li Mengyang , Hu Nannan 
Published: May 2023

Abstract
The power-on warning helmet was used to detect the three- dimensional electrical field near electrical equipment with high voltage. However, the power-on warning helmet will be used in low temperature (-40℃) and high temperature (50℃) environment, E-51 epoxy resin with medium viscosity will be chosen to insulate the joint of conducting wire and fill the seam between two neighboring insulating plates of housing shell. Due to brittleness, the unmodified E-51 epoxy resin system can’t absorb huge internal stress at cryogenic temperature, so the modified E-51 epoxy resin system was developed to investigate the thermal aging properties, which aims at revealing the influence of heating temperature and heating time on the evolution of micro structure, thermo stability of micro structure and mechanical properties. The testing results indicate the micro structure of modified E-51 epoxy resin system is stable after 50 thermal cycling, and the micro structure of modified E-51 epoxy resin system is stable after 50 thermal cycling & heating 105 ℃ & 120 h too. Compared with the mechanical tensile strength of modified E-51 epoxy resin system after 50 thermal cycling & heating 105 ℃ & 120 h, the mechanical tensile strength of modified E-51 epoxy resin system after 50 thermal cycling & heating 105 ℃ & 240 h declines about 13.63%. However, the modified E-51 epoxy resin system after heating for 480 h can lead to significant change of micro structure. The mechanical tensile tests indicate the defects in cured system can lead to dramatically decrease of tensile strength. Consequently, in order to obtain high performance, modification and micro homogeneity of E-51 epoxy resin system are necessary.
Association between exposure to Occupational hazard factors and multimorbidity in steelworkers: A Cross-Sectional Study
Authors: Lu Haipeng , Xu Xianghui , Hu Jiaqi , Zhao Zekun , Si Zhikang , Wang Xuelin , Wang Hui , Meng Rui , Wang Huan , Zheng Yizhan , Chen Jiaqi , Wu Jianhui , Xue Ling , Jing Liwei , Li Xiaoming 
Published: May 2023

AbstractMultimorbidity is a huge public health issue that affects people's health significantly on a global scale. Many chronic diseases have been linked to exposure to workplace dangers. The goal of this study was to comprehend the existing degree of multimorbidity among steel workers, the connection between cumulative occupational hazard exposure and multimorbidity, and to build the groundwork for the creation of preventative and control strategies for multimorbidity among steelworkers. This cross-sectional study included 3577 steel workers who had occupational health examinations in 2017. The relationship between occupational risks and the prevalence of multimorbidity in steel workers was examined using multiple logistic regression. We discovered that the rate of multimorbidity was 61.3%. The risk of multimorbidity among employees exposed to high levels of shift work, heat, noise, and dust was 1.520 (95% CI: 1.147 to 2.014), 3.376 (95% CI: 2.583 to 4.413), 2.069 (95% CI: 1.653 to 2.590), and 1.509 (95% CI: 1.1262.023) respectively in a multifactorial logistic regression analysis. Steelworkers need stronger protection against each occupational hazard since multimorbidity is highly common within the steel sector as a whole and is made more likely by occupational hazard exposure.
Cuproptosis-related lncRNAs as a novel biomarker to predict prognosis and explore biological function in cervical cancer
Authors: Fu Liye , Wang Yang , Jiang Tao , Guan Chao , Li Yan 
Published: May 2023

Abstract
We aim to investigate a prognostic signature of cuproptosis-related long non-coding RNAs (lncRNAs) and to search for effective individualized clinical treatment strategies. Transcription profiles and clinical follow-up data of CC were retrieved from TCGA database. Three cuproptosis-related lncRNAs closely related to the prognosis of patients with CC were identified and used to construct a prognostic signature via LASSO Cox regression. The predictive performance of the signature was evaluated by K-M analysis and ROC analysis. The expression and biological function of the three lncRNAs in CC were verified by CCK-8, wound healing assay, transwell assay, qRT-PCR and WB blot. The ROC curves confirmed the superior predictive performance of the signature compared with conventional clinicopathological characteristics in CC. Furthermore, HIF-1 signaling pathway and TGF-β signaling pathway differed significantly between the two risk groups according to functional enrichment analysis. Finally, the results showed that CDKN2B-AS1 interference, SGMS1-AS1 and LINC02356 overexpression inhibited the proliferation activity of Hela cells. The invasion of Hela cells was remarkably inhibited, significantly attenuated migration functions and also the expressions of TGF-β, Smad2, Smad3 and Smad4 were decreased. The three cuproptosis-related lncRNAs may help predict CC patients' OS and thus could assist clinicians in making personalized treatment plans for CC patients.
DDETR-SLAM: A Transformer-Based Approach to Pose Optimization in Dynamic Environments
Authors: Li Feng , Liu Yuanyuan , Wang Guodong , Li Chunguang 
Published: May 2023

Abstract
Simultaneous Localization and Mapping (SLAM) is a critical technology for accurate robot localization and path planning. It has been an important area of research to improve localization accuracy. In this paper, we propose a Transformer-based visual semantic SLAM algorithm (DDETR-SLAM) to address the shortcomings of traditional visual SLAM frameworks, such as large localization errors in dynamic scenes and “ghosting” in 3D mapping. First, by incorporating the Deformable DETR (DEtection TRansformer) network as an object detection thread, the pose estimation accuracy of the system is improved compared to ORB-SLAM2. Furthermore, a dynamic feature point culling algorithm that combines the semantic information is designed to eliminate outlier points generated by dynamic objects, thereby improving the accuracy and robustness of SLAM localization and mapping. Experiments are conducted on the public TUM datasets to verify the localization accuracy, computational efficiency, and readability of the point cloud map of DDETR-SLAM. The results show that in highly dynamic environments, the ATE (Absolute Trajectory Error), translation error, and rotation error are reduced by 98.45%, 95.34%, and 92.67%, respectively, when compared to ORB-SLAM2. In most cases, our proposed system outperforms DS-SLAM, DynaSLAM, Detect-SLAM, RGB-D SLAM, and YOLOv5 + ORB-SLAM2, and our methodology improves location accuracy. The dense mapping also has better readability. The RPE (Relative Trajectory Error) is only 0.0076 m, and the ATE is only 0.0063 m.
Integrating nitrogen fertilization with crop residue management to improve nitrogen-use efficiency of crops
Authors: Jahangir M.M.R. , Kamruzzaman M. , Ferdous J. , Rahman M. S. , Islam K. R. 
Published: May 2023

Abstract
Nitrogen-use efficiency (NUE) of crops is critical for addressing global food security in response to climate change effects. The objective of our study was to evaluate the effects of N fertilization integrated with crop residue management to optimize NUE of crops. A replicated 2 x 4 split-plot experiment in randomized complete block design was conducted during the 2020–2022 on farmers’ fields at Bogura, Cumilla, and Mymensingh sites of Bangladesh. The main plots were two levels of crop residues (no residue, NR vs. 30% residue, CR) combined with sub-plots of four levels of N fertilizers (control, CL; farmers’ practice, FP; national recommended dose, RD, and 125% of RD, 125RD) on potato (Solanum tuberosum, L.), maize (Zea mays, L.), and rice (Oryza sativa, L.) systems. N fertilization when interacted with residue retention progressively increased crop yield. Residue alone contributed significantly to increase NUE of potato and maize by 9 and 6%, respectively. The NUE of rice increased significantly, while the NUE of maize decreased with N fertilization. The comparison of NUE models suggested that the nationally recommended N fertilization should be adjusted to 169, 152, 187, 92, and 112 kg/ha for potato, maize, Boro, Aus, and Aman rice, respectively. For potato and Aman rice, the SNMI showed better results, whereas for Boro, Aus, and maize, utilizing both NUE and SNMI provided maximum benefit from N management.
Rivaroxaban: A New Hope for Anticoagulation in LDLT Recipients
Authors: Khan Bilal Ahmed , Khalid Abdullah , Saeed Zubair , Haq Ihsan , Khan Muhammad Yasir , Rashid Sohail , Naveed Ammara , Dar Faisal Saud 
Published: May 2023

Abstract
Purpose:
Thromboembolic complications remain a significant concern in postoperative patients, particularly those who have undergone liver transplantation. Warfarin has been the standard oral anticoagulant. Direct oral anticoagulants (DOACs) have several advantages over warfarin, including rapid onset of action and standardized dose guidelines. However, their use in the liver transplant population remains poorly studied. We aimed to assess the safety of rivaroxaban in living donor liver transplantation (LDLT) recipients.
Methods:
This study was a single-center, retrospective descriptive analysis of LDLT recipients who received rivaroxaban between December 2020 and April 2022. A total of 27 recipients received rivaroxaban postoperatively. Liver function tests and immunosuppression levels were recorded before the initiation of rivaroxaban & then on post-therapy days 1, 7, 14, 28, 90, and 180.
Results:
Among the 27 recipients receiving rivaroxaban postoperatively, portal venous thrombosis was the most prevalent indication for anticoagulation (44.4%), followed by Budd-Chiari Syndrome (29.6%). Nine patients had a twofold increase in either ALT or AST values, two of whom were treated for biliary strictures and the others for rejection. Eighteen patients were given tacrolimus, and eight were on cyclosporine, with one patient switched from tacrolimus to cyclosporine due to insufficient therapeutic levels. There were no incidents of bleeding or re-thrombosis during the 180-day follow-up period.
Conclusion:
Rivaroxaban may be a safe and effective alternative in LDLT recipients with no significant adverse incidents. Further studies with larger sample sizes are needed to confirm these findings and determine this population's optimal dose and duration of rivaroxaban therapy.
Optimal Temporal Decay Rates of the Solution for Combustion of Compressible Fluids
Authors: Fu Shengbin , Huang Wenting , Wang Weiwei 
Published: May 2023

Abstract
This paper explores the Cauchy problem and temporal decay rates associated with the Navier-Stokes equations featuring reaction diffusion. Suppose that the initial data is a small perturbation near the equilibrium state ρ∞, 0, θ∞,ζ), where ρ∞> 0, θ∞ < θI(the ignition temperature), and 0 < ζ≤ 1, we first establish the global-in-time existence of the strong solutions via a standard continued argument. With the additional L1-integrability of the initial perturbation, we then employ the Fourier theory and the cancellation mechanism of low-medium frequent part to derive the optimal temporal decay rates of the all-order derivatives of the strong solution. The work of this paper can be considered as the further investigation to [Wang-Wen, Sci. China Math. 65, 2022, 1199-1228].
Affordable Combustion Synthesis of V2AlC Precursor for V2CTx MXene
Authors: Vorotilo Stepan , Shuck Christopher E. , Anayee Mark , Shekhirev Mikhail , Matthews Kyle , Lord Robert W. , Roslyk Iryna , Balitskiy Vitalii , Zahorodna Veronika , Gogotsi Oleksiy , Gogotsi Yury , Wang Ruocun (John) 
Published: May 2023

Abstract
Two-dimensional (2D) transition metal carbides and nitrides (MXenes) possess a unique combination of properties, such as metallic conductivity combined with hydrophilicity and surface redox activity, that are important for energy storage, printed electronics, biomedical, catalytic and other applications. However, the use of many MXene chemistries beyond titanium carbides is limited by the cost of MAX phase precursors, which are usually produced from pure elements, involving expensive transition metals. Herein, we demonstrate a low-cost rapid aluminothermic combustion synthesis of MAX phases from an inexpensive oxide precursor, producing V2AlC in seconds, with low energy input. A reactor for self-propagating high-temperature synthesis (SHS) was designed and manufactured for this study. The V2CTx MXene produced from the SHS MAX is similar to MXene from conventional pressureless sintered MAX in terms of oxidation resistance, environmental stability, conductivity, and electrochemical performance, but has a larger flake size. This work demonstrates an alternative, low-cost and scalable approach to the synthesis of MAX phases and, subsequently, MXenes without sacrificing their properties.
Application of a hybrid ANFIS with metaheuristic algorithms to estimate the aeration design parameters
Authors: Hekmat Mohsen , Sarkardeh Hamed , Jabbari Ebrahim , Samadi Mehrshad 
Published: May 2023

Abstract
Cavitation is a common and complex hydraulic phenomenon on the chute spillways and may cause damage to the structure. Aeration in the water flow is one of the best ways to prevent cavitation. To design an aerator, estimation of aeration coefficient (β), jet length (L/h0), and jet impact angle on chute (tanγ) are important in this study. The potential of a hybrid adaptive neuro-fuzzy interface system (ANFIS) with metaheuristic algorithms was investigated to estimate the required parameters to design an aerator. The ANFIS was combined with four metaheuristic algorithms, including differential evolution (DE), ant colony optimization (ACO), genetic algorithm (GA), and particle swarm optimization (PSO). Experimental data and dimensionless parameters were used to develop the proposed hybrid ANFIS models. Three statistical indicators, including root mean square error (RMSE), mean average error (MAE), and coefficient of determination (R2), were employed to compare the proposed methods with empirical relations. According to the statistical indicators, among the data-driven methods, the ANFIS–DE method had the best prediction in estimating β (RMSE = 0.018, R2 = 0.984, MAE = 0.013), L/h0 (RMSE = 1.293, R2 = 0.963, MAE = 1.082), and tanγ (RMSE = 0.009, R2 = 0.939, MAE = 0.007).
Optimization of water reuse and modelling by saline composition with nanoparticles based on machine learning architectures
Authors: Rao Koppula Srinivas , Tirth Vineet , Almujibah Hamad , Alshahri Abdullah H. , Hariprasad V. , Senthilkumar N. 
Published: May 2023

Abstract
Water is a necessary resource that enables the existence of all life forms, including humans. Freshwater usage has become increasingly necessary in recent years. Facilities for treating seawater are less dependable and effective. Deep learning methods have the ability to improve salt particle analysis in saltwater's accuracy and efficiency, which will enhance the performance of water treatment plants. This research proposes a novel technique in optimization of water reuse with nanoparticle analysis based on machine learning architecture. Here, the optimization of water reuse is carried out based on nanoparticle solar cell for saline water treatment and the saline composition has been analyzed using a gradient discriminant random field. Experimental analysis is carried out in terms of specificity, computational cost, kappa coefficient, training accuracy, and mean average precision for various tunnelling electron microscope (TEM) image datasets. The bright-field TEM (BF-TEM) dataset attained a specificity of 75%, kappa coefficient of 44%, training accuracy of 81%, and mean average precision of 61%, whereas the annular dark-field scanning TEM (ADF-STEM) dataset produced specificity of 79%, kappa coefficient of 49%, training accuracy of 85%, and mean average precision of 66% as compared with the existing artificial neural network (ANN) approach.
Network Analysis and Basic Experiments on the Inhibition of Renal
Cancer Proliferation and Migration by Alpinetin through PI3K/AKT/
mTOR Pathway
Authors: Guo Yu , Jiang Li , Luo Shengjun , Hu Daixing , Zhao Xin , Zhao Guozhi , Tang Wei 
Published: May 2023

Background:
Alpinetin, a natural flavonoid, has been shown to have
anticancer effects on many tumors. This study investigated the antitumor effect of
alpinetin on renal clear cell carcinoma (ccRCC).

Methods:
Network Pharmacology analysis was carried out on the targets and molecular
mechanisms of alpinetin treating ccRCC. The Annexin V PE/7-AAD kit was used to
detect apoptosis. Flow cytometry and Cell Counting Kit-8 (CCK-8) were used to detect
cell proliferation and cycle. A 24-well transwell chamber and the ibidi scratch insertion
performed cell migration analysis. The protein expression of the target molecule was
detected by Western blotting. Nude mouse tumorigenesis assays were used to
determine the in vivo antitumor effects of alpinetin.

Results:
The network pharmacology revealed that GAPDH, HRAS, SRC, EGFR, and
AKT1 are the main targets of alpinetin in treating ccRCC, with the PI3K/AKT signaling
pathway being the main pathway of action. We found that alpinetin could significantly
inhibit the proliferation and migration of ccRCC cells by inducing apoptosis. In addition,
alpinetin also inhibited the cycle progression of ccRCC cells by blocking them in the G1
phase. Furthermore, in vivo and in vitro, alpinetin could inhibit the activation of an
important pathway involved in the proliferation and migration of ccRCC cells, namely the
PI3K/Akt pathway.

Conclusion:
Alpinetin can inhibit the growth of ccRCC cells by inhibiting the activation
of the PI3K/Akt pathway and can be a potential anti-cancer drug for ccRCC.
DDX3X Deficiency Attenuates Pyroptosis Induced by Oxygen-glucose
Deprivation/Reoxygenation in N2a Cells
Authors: Liu Yong , Gui Yanlin , Tang Hao , Yu Jianping , Yuan Zhengzhou , Liu Lei , Ma Xuntai , Li Changqing 
Published: May 2023

Background:
NOD‑like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis
is strongly related to cerebral ischemia/reperfusion (I/R) injury. DDX3X, the DEAD-box family's
ATPase/RNA helicase, promotes NLRP3 inflammasome activation. However, whether
DDX3X deficiency attenuates NLRP3 inflammasome-mediated pyroptosis induced by cerebral I/R
injury.

Objectives:
This study investigated whether DDX3X deficiency attenuates NLRP3 inflammasomemediated
pyroptosis in N2a cells after oxygen-glucose deprivation/ reoxygenation (OGD/R) treatment.

Methods:
In vitro model of cerebral I/R injury, mouse neuro2a (N2a) cells subjected to OGD/R
were treated with the knockdown of DDX3X. Cell counting kit-8 (CCK-8) assay and Lactate dehydrogenase
(LDH) cytotoxicity assay were conducted to measure cell viability and membrane
permeability. Double immunofluorescence was performed to determine the pyroptotic cells.
Transmission electron microscopy (TEM) was used to observe morphological changes of pyroptosis.
Pyroptosis-associated proteins were analyzed by Western blotting.

Results:
The OGD/R treatment reduced cell viability, increased pyroptotic cells and released LDH
compared to the control group. TEM showed membrane pore formation of pyroptosis. Immunofluorescence
showed that GSDMD was translocated from the cytoplasm to the membrane after
OGD/R treatment. Western blotting showed that the expression of DDX3X, and pyroptosis-related
proteins (NLRP3, cleaved-Caspase1, and GSDMD-N) were increased after OGD/R treatment.
Nevertheless, DDX3X knockdown markedly improved cell viability and reduced LDH release,
expression of pyroptosis-related proteins, and N2a cells pyroptosis. DDX3X knockdown significantly
inhibited membrane pore formation and GSDMD translocation from cytoplasm to membrane.

Conclusion:
This research demonstrates for the first time that DDX3X knockdown attenuates
OGD/R‑induced NLRP3 inflammasome activation and pyroptosis, which implies that DDX3X
may become a potential therapeutic target for cerebral I/R injury.
2D-QSAR Modeling, Docking, Synthesis and In-Vitro Evaluation of Novel
Flavone Derivatives as Anticancer Agents
Authors: Surajambika Remya Ramachandran , Palanikarasu Pavithra 
Published: May 2023

Background:
Cancer is the second leading cause of death globally and is responsible for
10 million deaths in 2020 (2.26 million breast cancer deaths). Due to the problems like drug resistance,
toxicities and economic burden, there is a need for the development of novel anticancer
agents.

Objectives:
To design novel flavone derivatives by 2D QSAR studies and docking studies and to
evaluate the compounds as potential anticancer agents against MCF7 cell line by MTT assay.

Methods:
We designed a series of novel flavone derivatives by 2D QSAR modelling using the
software QSARINS.The molecular docking studies were carried out to study the molecular interaction
and binding affinitiesof the designed compounds against tyrosine protein kinase (PDB ID:
2SRC) by Auto DockVina software. ADMET profiles were calculated for all the designed compounds
and five compounds were chosen for synthesis.The synthesized compounds were characterized
and evaluated in vitro for anticancer activity against MCF7 cell line by MTT assay. Based on
2D QSAR and molecular docking studies, compounds 3c, 3f, 3i and 3m were synthesized and evaluated
for anticancer activity against MCF-7 cell lines.

Results:
Molecular docking studies of the compounds showed good binding affinity against tyrosine-
protein kinase (2SRC). The synthesized flavone derivatives were evaluated for anti-cancer activity
against human breast cancer cell line MCF-7 by MTT assay using cisplatin as a positive control.
The novel flavone derivative (3c) exhibits more cytotoxicity effect, and the IC50 value of the
compound was found to be 52.03 μg/ml. Optimization of these novel scaffolds requires extensive
studies on more derivatives.

Conclusion:
The novel flavone derivatives will be good lead compounds targeting breast cancer.