bluuebunny/crossref_metadata_2025_split huggingface dataset:
Establishment of a thermal compensation model for a turning–milling compound machine
Authors: Chuang Chia-Chin , Kuo Tzu-Chien , Jhang Yu-Hao , Peng Chuan , Hsieh Wen-Hsin 
Published: April 2024

Abstract
Thermal errors are considered the most significant errors in precision machining. The heat sources of a turning– milling compound machine (TMCM) are diverse and complex. This study proposes a new thermal compensation model in a TMCM to compensate for thermal errors. First, the relationship between the tool tip deformation direction and the temperature increase trend is considered. The temperature points that have a pronounced influence on the tool tip deformation are selected from 76 measured temperature points. Temperature sensitive points are then identified through F-test feature engineering. The temperature increases and thermal deformation data of the temperature sensitive points under the characteristic and training conditions are used as the input and output in training a recurrent neural network model. When the recurrent neural network model was trained, the automatic parameter adjustment method of the RandomSearch in the Keras tuner toolbox was used. The minimum mean-square error (MSE) of the verified operating conditions was taken as the evaluation index, and a thermal compensation model was established. Compared with the average root-mean-square errors (RMSE) of the validation and test conditions along the six axes, the maximum difference in the average RMSE (only 2.12 μm) occurred in the direction of the spindle Y-axis. Noticeably, the thermal compensation model established in this study has high robustness and good universality. In addition, the average accuracy of the validation and testing conditions along the six axes improved by 84.3%. The proposed thermal compensation model is highly reliable and can effectively improve the thermal compensation accuracy.
HRI Inhibition by Hemin as a Novel Targeted Therapy for Glioblastoma via the Integrated Stress Response
Authors: Ma Xingchuan 
Published: April 2024

Abstract
The treatment of glioblastoma (GBM), a highly malignant brain tumor, is critically hindered by the ineffectiveness of current modalities such as surgery, radiation, and chemotherapy. These traditional methods fail to completely remove the tumor mass and lack the ability to discriminate between cancerous and normal brain cells, often resulting in collateral damage to healthy tissue and recurrence of the disease. This underscores an urgent necessity to develop novel therapeutic strategies that can target tumor cells with precision, offering hope for improved survival rates and quality of life for GBM patients. This study investigates targeted therapy, focusing on the Integrated Stress Response (ISR) that cancer cells harness to survive hypoxic stress. Specifically, it demonstrates that EIF2AK1, which encodes Heme-regulated eIF2α kinase (HRI), is activated under hypoxia and co-expressed with the glioma stem cell marker SOX2, which specifically happens in glioma cells, increasing the targeted accuracy of the repurposing drug. This correlation, indicating hypoxia-driven stemness, is confirmed at both the genetic level and through Gene Set Enrichment Analysis (GSEA). Furthermore, GSEA in Spatial Transcriptomics shows hypoxia-induced glycolysis, disrupting the tumor microenvironment and causing necrotic cell death. Stemness phenotype is induced in the peripheral cells due to the unfavorable hypoxic environment. Hemin, an HRI inhibitor, has been repurposed to inhibit ISR and mitigate hypoxia. Treatment with Hemin on the U87 cell line resulted in IC50 values of 23.50 µM and 52.46 µM at 24 and 48 hours, respectively, surpassing Temozolomide's efficacy. A decrease in HRI expression after the Hemin treatment suggests the and ISR activity and, potentially, hypoxia. This would reverse the unfavorable microenvironment so that the stemness phenotype doesn’t spread. Potentially, invasiveness and recurrences of GBM in clinic situation would decrease, thus potentially improving patient prognosis. The therapeutic potential of Hemin is enhanced by its ability to kill glioma cells directly and accurately in the glioma cell in original TME when cells are proliferating with adequate oxygen. Therefore, this study demonstrates the therapeutic potential of repurposing Hemin, an HRI inhibitor, to precisely target hypoxia-induced glioma stem cells in glioblastomas, disrupting the aggressive tumor microenvironment to potentially improve patient prognosis.
Finite-time Neural Network Adaptive Sliding Mode Control of Fractional-Order Chaotic Systems With Disturbance Observer And Fractional Robust Differentiator
Authors: Cui JinWei , Zhao XiaoShan 
Published: April 2024

Abstract
This paper proposes a neural network adaptive sliding mode control scheme with a fractional-order disturbance observer and a robust differentiator for fractional-order chaotic systems with uncertain functions and random noise. The solution combines fractional-order differential controllers, gradient descent neural networks, and fractional-order disturbance observer techniques. A gradient descent neural network handles uncertain nonlinear functions, while fractional-order disturbance observers are presented to solve unexpected noise problems. On the premise that the above problems are solved, the state vector is used as the original signal, the ideal function as the tracking signal, and the design error function as the sliding mode surface. Meanwhile, in order to eliminate the vibration caused by the sliding mode functions, a fractional order robust differential observer is introduced in the estimation error. Adaptive rates are introduced in the design of the controller so that the control converges to a small interval in a finite time.
Long-Term Cardiopulmonary Outcomes and Quality of Life: A Comparative Study Among Cigarette, Electronic Cigarette and Dual use Consumers.
Authors: Krishna Gokul , Jose Ann Mary , Rahali Weaam , Alyamani Wejdan , Mohammed Manahel , Alghamdi Basmah , Homoud Mazen , AlAhmari Mohammed , Alwadeai Khalid , Alkhathami Saleh , Sreedha Jithin , Alahmari Ayedh 
Published: April 2024

Abstract

Background: Smoking is a leading cause of heart and lung diseases worldwide. Though there is a decline in tobacco smoking the use of e-cigarettes is growing in popularity.Objective:To assess the long-term effects of smoking, vaping, and dual use on cardiopulmonary function capacity and quality of life.Methods:The study participants were classified into five groups: Control, Individuals who use cigarettes only, Individuals who only use e-cigarettes, Individuals who previously smoked and currently use only e-cigarettes and Individuals who use both cigarettes and e-cigarettes. Participants performed PFT, 6MWT and completed HRQoL questionnaire.Results:A total of 175(85.7% male) participants with an average age of mean(±SD)27.38(±5.75) enrolled in the study. PFT results showed significant difference in FEV1(L/Sec) [F (4,170) = 7.73, p≤ 0.001] η²=0.15; FEV1(%predicted) [F (4,170) =24.63, p≤0.001] η²=0.36; and FEV1/FVC (%) [F (4,170) =16.85, p≤0.001] η² = 0.28 values across the five groups. On further analysis, FEV1and FEV1(%predicted) significantly decreased in all user groups. Similarly, in FEV1/FVC (%) significant difference was observed with user groups except those who only use e-cigarettes. 6MWT showed a significant difference in walking distance [F (4,170) = 19.93, p≤0.001] η² =0.31. HRQoL reported a significant difference in physical function [H (4) =20.55, p≤0.001], emotional well-being [H (4) =19.21, p=0.001], and social function [H (4) =29.63, p≤0.001] domains. Individuals who use both cigarettes and e-cigarettes reported a significant decline in lung function [(FEV12.96±0.41, FEV1(% predicted) 72.6±6.07 and FEV1/FVC (%) 73.65±11], 6MWT walking distance(m) (mean ±SD) 416.26±53.49.Conclusion: Weobserved a significant long-term impairment in lung function, cardiopulmonary capacity, and quality of life among individuals who use cigarettes and e-cigarettes compared to those who never smoked or vaped. Also, individuals who use both cigarettes and e-cigarettes showed the worst health outcomes.
Energy Forecasting In LED Video Display Panels Using Deep Learning
Authors: R RAMESH , A Bazilabanu 
Published: April 2024

Abstract
In recent years, energy usage in LED Video Wall Display Panels (LED-VWDPs) has increased massively; Predicting energy consumption is a challenging and crucial task for LED-VWDPs. Hence Real-time energy usage issues can be resolved by predicting future energy demand. Deep learning plays an important role in more accurate prediction in energy forecasting. In this article, two approaches are presented: the first makes use of a recurrent neural network (RNN), and the other utilizes a long short-term memory (LSTM) network.In comparison to other existing machine learning techniques, such as ARIMA and Facebook Prophet, Long Short-Term Memory (LSTM) in deep learning is better at handling time-series datasets and projecting future energy demand. It predicts the actual energy usage of LED-VWDP and forecasts the futureenergydemandofLED-VWDP. A vast dataset of LED-VWDP energy consumption is utilized in this paper. Through the proposed RNN and LSTM methods, users can identify the individual energy usage of LED-VWDP and predict its future energy demand.The results of the proposed methods are evaluated alongside those of the existing methods in order to forecast energy usage. The results are used to evaluate the performance of forecasting future energy demands, depending on the number of epochs. The accuracy of RNN and LSTM ranges from 82.02–95.86%. The predictions have been made for a period of two months, encompassing short-and mid-term forecasts.In evaluating the comparison of various machine and deep learning models, LSTM is found to be accurate with an average root mean square error of 0.5 in forecasting energy consumption.
Analysis of Radiological Findings and Pathological Correlation in Secondary Intracranial Hypertension
Authors: Kuzan Beyza Nur , Şahin Yener , Çiftçi Tufan , Günbey Hediye Pınar 
Published: April 2024

Abstract
Background
Intracranial hypertension is a potentially fatal entity that can occur due to idiopathic or secondary causes and can be detected by radiological methods. To determine radiological findings of intracranial hypertension secondary to primary intracranial tumors and to reveal the relationship between tumor pathology and radiological findings.
Methods
This retrospective study included 105 adult patients with a histopathologically confirmed primary intracranial tumor. Tumor characteristics and MRI findings associated with intracranial hypertension were noted. The relationship between tumor type and radiological findings was evaluated.
Results
Glioblastoma (41.0%) followed by meningioma (29.5%) was the most common primary brain tumor. There was a statistically significant difference between intraaxial tumors and extraaxial tumors in terms of pituitary gland height (p = 0.016) and sinus invasion area of the tumor (p = 0.010). In the subgroup analysis, there was a significant difference between meningioma, the most common extraaxial tumor, and other tumors in terms of pituitary gland height and dural sinus invasion area (p = 0.008 and p = 0.029, respectively).
Conclusion
It is important to know the radiological findings of secondary intracranial hypertension caused by intracranial masses and to keep in mind that it may be associated with tumor pathology and some secondary intracranial hypertension findings may be detected more frequently in extraaxial tumors.
Predictive factors for developing acute cholangitis due to choledocholithiasis
Authors: Li Feifan , Dai Meiqing , Xu Min , Cui Qidong , Shen Rongwei , Zhou Xulin , Wang Zhihua 
Published: April 2024

Abstract
Background
Acute cholangitis, an acute and severe disease in the clinic, is mostly caused by choledocholithiasis. This study aimed to identify the predictive factors for developing acute cholangitis due to choledocholithiasis.
Methods
A total of 558 patients with choledocholithiasis were enrolled. The patients were divided into a choledocholithiasis group (n = 399) and an acute cholangitis group (n = 159) according to whether they had acute cholangitis. The clinical data were analyzed, and logistic regression was used to predict acute cholangitis. Receiver operating characteristic (ROC) curves were generated to identify predictive factors for acute cholangitis.
Results
The acute cholangitis group had a greater prevalence of male sex, age ≥ 70 years, smoking history, hypertension, fever (> 38°C) and/or shaking chills, duodenal peripapillary diverticulum, and maximum diameter of choledocholithiasis (≥ 10 mm). Furthermore, the acute cholangitis group had higher WBC, CRP, T-Bil, ALT, AST, ALP, GGT, serum creatinine (Scr), prothrombin time (PT) and D-dimer (D-D) levels and lower albumin levels. Logistic regression analysis revealed that the maximum diameter of choledocholithiasis (≥ 10 mm), T-Bil, CRP, WBC, fever (> 38°C) and/or shaking chills, male sex, AST, and ALP were independent risk factors for developing acute cholangitis, with an area under the ROC curve (AUC) of 0.869 for CRP, 0.858 for T-Bil, 0.835 for WBC, 0.765 for AST and 0.743 for ALP.
Conclusions
Attention should be given to choledocholithiasis patients who have a maximum diameter of choledocholithiasis (≥ 10 mm), T-Bil > 34.25 µmol/L, CRP > 10.85 mg/L, WBC > 9.95×109/L, fever (> 38℃) and/or shaking chills, male sex, ALP > 162.5 U/L and AST > 57.8 U/L. Interventions may be taken to prevent acute cholangitis.
Impact of Frailty on Outcomes Following Emergency Laparotomy: A Retrospective Analysis Across Diverse Clinical Conditions
Authors: Isand Karl Gunnar , Hussain Shoaib Fahad , Sadiqi Maseh , Kirsimägi Ülle , Bond-Smith Giles , Kolk Helgi , Saar Sten , Lepner Urmas , Talving Peep 
Published: April 2024

Abstract

Purpose
Emergency laparotomy (EL) encompasses procedures of varying complexity and urgency, undertaken in different clinical scenarios, leading to different risks of morbidity and mortality. We hypothesized that the increased mortality and longer postoperative length of stay (LoS) observed in frail patients are related to differences in indication for operation, a higher rate of sepsis, worse intraperitoneal soiling, and more advanced malignancy in this group.
Methods
This retrospective cohort study analysed patients entered into the National Emergency Laparotomy Audit database between January 1, 2018, and June 15, 2021, in Oxford. The primary outcome was 180-day survival analysed using multivariable Cox regression. The secondary outcomes, delay to surgery (DtS) and postoperative LoS, were analysed using logarithmically transformed multivariable linear regression.
Results
Of the 803 patients analysed, 396 (49.3%) were male. The median age was 66, and 337 (42%) were living with at least very mild frailty. Mortality hazard ratios for Clinical Frailty Scale grades 4 (3.93, 95% CI 1.89–8.20), 5 (5.86, 95% CI 2.87–11.97), and 6–7 (14.17, 95% CI 7.33–27.40) were not confounded by indication, sepsis, intraperitoneal soiling, or malignancy status. Frail patients experienced a 1.38-fold longer DtS and a 1.24-fold longer postoperative LoS, even after adjusting for indication, sepsis, intraperitoneal soiling, malignancy status, and DtS.
Conclusion
Our results indicate that frail patients have a poorer prognosis and longer postoperative LoS, independent of DtS, indication, sepsis, intraperitoneal soiling, and malignancy status. Patient frailty is also associated with longer DtS.
Assessment of genetic alterations found in type 2 diabetes mellitus patients with pancreatic adenocarcinoma
Authors: Calderon-Martinez Evelyn , Zevallos-Delgado Christian , Gavilanes Diana , Landazuri-Navas Samanta , Guzman Adalberto , Ng Wern , Marquez Luis , Atrash Anas 
Published: April 2024

Abstract
Purpose In this study, we aim to determine the prognostic effects of genetic mutations identified in pancreatic adenocarcinoma (PAAD) patients with type 2 diabetes mellitus.Method Gepia and cBioPortal were used to assess the TCGA data and other PAAD studies. CBioPortal showed 2963 patients in 14 related studies. Among these participants, 37 had a positive medical history of type 2 diabetes mellitus, while 104 did not.Results Fifteen genes (HTRA3, FANCA, IL4R, NRXN2, GRPEL1, KIAA0232, TTK, WFS1, TBC1D14, CCDC96, USP25, STOML2, TPI1, PLAA, and FASTKD2) have been identified to be involved in the prognosis of the disease based on the number of mutations and survival prognosis in this study. Furthermore, the adverse impact of diabetes mellitus and PAAD are linked to single nucleotide polymorphisms.Conclusion Several genetic alterations found in patients with PAAD and type 2 diabetes mellitus have an impact on the prognosis of PAAD patients.
Errorless Robust JPEG Steganography Using Steganographic Polar Codes
Authors: Zhang Jimin , Cao Yun , He Xiaolei 
Published: April 2024

Abstract
Recently, a robust steganographic algorithm that achieves errorless robustness against JPEG recompression has been proposed. The method employs a lattice embedding scheme and utilizes the syndrome-trellis code (STC) for practical embedding. However, we have noticed that errorless robust embedding with STC may encounter failures due to modifications on wet coefficients, especially when a high quality factor is used by the compression channel. To solve this problem, we have discovered that using steganographic polar code (SPC) for embedding has better performance in avoiding modifications on wet coefficients.In this paper, we conduct theoretical analysis to prove the better performance of SPC in wet paper embedding.We establish the condition of avoiding modifications on wet coefficients, followed by presenting a recursive calculation method for determining the distribution of columns in the generator matrix of SPC. The findings reveal that SPC can avoid modifications on wet coefficients under a larger number of wet coefficients compared with STC, and therefore we propose a better errorless robust embedding method employing SPC. The experimental results demonstrate that under close security performance, the proposed method achieves a higher success rate compared with embedding with STC.Specifically, when the quality factor of the compressor is 95, our method achieves a success rate of 99.85%, surpassing the 91.95% success rate of the embedding with STC.
Massive MIMO-FDD Self-Attention CSI Feedback Networkfor Outdoor Environments
Authors: Wang Linyu , Cao Yi , Xiang Jianhong , Jiang Hanyu , Zhong Yu 
Published: April 2024

Abstract
In situations where traditional feedback methods face high complexity and rely on channel sparsity,many deep learning-based CSI compression feedback methods have shown the potential to fullycapture the diversity and multiplexing gains of Massive MIMO technology in Frequency DivisionDuplex (FDD) mode. In order to further enhance the accuracy of obtaining downlink channel stateinformation at the base station side, this paper proposes a novel neural network, SfNet. Basedon visual analysis, the convolutional layers in the encoder are designed to extract long-distancetime-delay correlations of the same antenna across different subcarriers. The SimAM module isintroduced to mitigate clustering effects. In the decoder, a spatial-temporal joint modeling approachis presented, utilizing the CBAM module to preserve the original spatial structure features lostduring the dimension reduction of the CSI matrix to sequence data. Subsequently, two layers ofTransformer multi-head attention are employed to achieve more global time-series modeling.Theexperimental results indicate that, compared to CLNet, the average complexity of SfNet’s encoder isreduced by 3.4%. It meets the demand for lightweight devices on the user side. In terms of accuracy,SfNet exhibits an average improvement of 30.17% compared to TransNet in outdoor environments.
Effects of juniperus root extract on wound healing, gene expression and biochemical response in yellowtail acei Pseudotropheus sp. fish
Authors: Önalan Şükrü , Kankaya Ertuğrul 
Published: April 2024

Abstract
Injuries are an undesirable situation in fish kept in aquariums. The use of antibiotics in wound healing is not preferred due to the development of antibiotic resistance in bacteria and for economic reasons. This study was conducted to demonstrate the efficacy of Juniperus root extract in healing experimentally induced incised wounds in yellowtail acei. Wound closure time, morphology, malondialdehyde content, glutathione s-transferase activity, changes in gene expression levels, non-dispersibility of the extract in aqueous environment, and retention on the wound were analyzed. In the antibiotic group, the scarring of the wound was observed on the sixth day. On the other hand, in the root extract group, wound healing was completed on the second day. In addition, a significant decrease in malondialdehyde and glutathione s-transferase levels was observed in the extract group compared to the control group. It was found that SWS2a, RH2B and LWS gene expression levels started to decrease during wound healing at the end of the second day in the extract-treated group. In the antibiotic group, the same effect was observed on the seventh day. Important properties of the extract used, such as not dispersing in the water environment and remaining on the wound, were also determined. It would be useful to continue the experiments with Juniperus root extract, which has been shown to be effective on wound healing, with microscopic studies on aquaculture and diseases.
Gene trail of polarized M2 macrophage decodes tumor heterogeneity and recommendation for therapy of hepatocellular carcinoma
Authors: Zhao Minjie , Tang Changlin , Liang Hang , Sun Xinyu , Wu Kun 
Published: April 2024

Abstract
M2 macrophages are known to substantially influent tumor invasion and metastasis, leading to diverse clinical outcomes. This study aimed to identify a novel biomarker associated with M2 macrophages and assess its prognostic significance in hepatocellular carcinoma. Genes exhibiting a significant correlation with M2 cells were identified using single-cell RNA sequencing (scRNA-Seq) and WGCNA analysis. Subsequently, patients were stratified into two distinct groups using the consistency clustering method. Following this categorization, an in-depth investigation was conducted to explore the prognostic implications, biological attributes, genomic variations, and the immune landscape within each cluster. Moreover, the potential efficacy of drug treatment and the anticipated impact of immunotherapy were also assessed.Based on the analysis of M2 cell development trace genes and the findings from WGCNA, a total of 17 target genes were identified, leading to the identification of two distinct clusters with varying clinical outcomes. Group C1 was characterized as cell proliferative liver cancer, whereas Group C2 was classified as lipid metabolic liver cancer. Furthermore, two anticancer drugs were analyzed. Patients in group C1 exhibited a higher sensitivity to erlotinib, whereas patients in group C2 demonstrated a greater sensitivity to rapamycin. Moreover, immunotherapy appeared to be more suitable for patients in group C1. This study significantly enhances the existing understanding of the involvement of M2 cells in the biological and prognostic prediction of hepatocellular carcinoma, thereby offering potential benefits in terms of enhancing clinical management and ultimately improving clinical outcomes.