bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blood pressure in preterm infants with bronchopulmonary dysplasia in the first three months of life
Authors: Kiss Judit Klara , Gajda Anna , Mari Judit , Bereczki Csaba 
Published: October 2023

Abstract
Background
Neonatal hypertension is common in preterm infants with bronchopulmonary dysplasia (BPD). Our study aims to examine blood pressure variation in the first three months of life in preterm BPD patients.
Methods
We conducted a retrospective, single-centre study at the Neonatal Intensive Care Unit (NICU) of the University of Szeged, Hungary. We collected the blood pressure data of 26 preterm infants (less than 30 weeks' gestation) with moderate or severe BPD over three years (2019–2021). We calculated the BPD group's daily average blood pressure values and used previously defined normal blood pressure values as a reference. We used 19481 systolic (SBP) and diastolic blood pressure (DBP) measurement data separately to calculate daily average blood pressure.
Results
From the daily average blood pressure calculations, we found 11 patients (42%) with hypertensive blood pressure values for three or more days within the first 90 days of life. Within this group, acute kidney injury was present as a comorbidity in 54.5%. Daily blood pressure increases occurred most frequently (44%) between the 9th and 13th weeks of life. We found a statistically significant correlation between the blood pressure values of the BPD patient group and the reference data. The difference between the blood pressure curve of the patients with BPD and the reference data was also statistically significant.
Conclusion
The blood pressure of BPD patients correlates with but also significantly differs from the reference data. Calculating the daily average blood pressure can improve the diagnosis of neonatal hypertension compared to weekly average blood pressure-based investigations.
Future Work Self-Salience and Meaning of Life among College Students: The Mediating Effect of Career Adaptability and the Moderating Effect of Gender
Authors: Zang Tongtong , Zhao Xiaoyun , Liu Weidi 
Published: October 2023

Abstract
Purpose: Faced with difficult employment and fast-paced society, college students mostly face life negative and slack lives. To help college students better construct meaning in life, this study attempts to explore the mediating effect of career adaptability on the relationship between future work self-salience and meaning in life; and the moderating effect of college students' gender on the indirect effect of future work self-salience on meaning in life through career adaptability.
Methods: Questionnaires were administered to 1,337 college students using the Future Work Self-Salience Scale, the Career Adaptability Scale, and the Meaning in Life Scale.
Results: The study's findings showed that college students' meaning in life was significantly and positively influenced by their future work self-salience. Career adaptability partially mediated the relationship between future work self-salience and meaning in life. Additionally, the gender of the college students moderated the relationship between future work self-salience and meaning in life. In particular, compared to male college students, female students' career adaptability was less predicted by future work self-salience.
Conclusion: The study found that college students' future work self-salience can influence meaning in life through career adaptability; meanwhile, the mediating model has gender differences among male and female college students. The findings have important practical implications for the enhancement and intervention of meaning in life and provide additional evidence on the relationship between male and female gender and career adaptability.
A Preliminary Study on Mesothelin Expression Levels in Pancreatic Cancer Using a CT Radiomics Model
Authors: Li Xuanle , Li Qingyu , Yang XiaoHui , He Xiang , Wang ChangFu , Wang Binjie 
Published: October 2023

Abstract
Purpose
To explore the feasibility of CT radiomics model in identifying the expression level of pancreatic mesothelin.
Methods
A retrospective analysis of 37 confirmed pancreatic cancer cases was conducted via surgical pathology. These cases had well-preserved tissue blocks and underwent upper abdominal CT scans within two weeks of surgery. Images, centered on the tumor's maximum diameter with one slice above and below the lesion, were selected for each case. Using 3D Slicer software, Regions of Interest (ROIs) were defined, and Pyradiomics extracted radiomics features. The dataset was categorized into positive and negative groups based on mesothelin immunohistochemical expression levels. Random division into training and testing sets ensued. Initial feature selection reduced radiomics dimensions, followed by secondary selection using (Least Absolute Shrinkage and Selection Operator) LASSO regression, resulting in a radiomics score model. Diagnostic performance was assessed in both sets using Receiver Operating Characteristic (ROC) analysis, precision via Calibration Curve (CC) analysis, and clinical benefit through Decision Curve Analysis (DCA).
Results
A total of 1218 radiomics features were extracted from 111 slices of CT scans in pancreatic cancer patients. The constructed radiomics model, after a series of dimensionality reduction and selection methods, achieved an Area Under the ROC Curve (AUC) of 0.84, sensitivity of 80.00%, and specificity of 75.68% in the training set. In the testing set, the AUC was 0.75, sensitivity was 58.82%, and specificity was 88.24%. The Calibration Curves (CC) in both the training and testing sets indicate a strong fit, while the Decision Curve Analysis (DCA) shows good clinical benefit.
Conclusion
A CT-based radiomics model can be used to evaluate pancreatic mesothelin expression levels, providing a reference for early prediction and differential diagnosis of pancreatic cancer using imaging techniques.
A Face-Authentication Based Searchable Encryption Scheme For Mobile Device
Authors: Yue Xiaohan , Yi Gang , Yang Haibo , Bai Shi , He Yuan 
Published: October 2023

Abstract
In this paper, we introduce Face-Authentication Keyword Encryption Search (FAKES), a novel searchable encryption scheme that eliminates the requirement for clients to manage cryptographic keys by utilizing only the client’s face biometric data for authentication of outsourcing and retrieval of encrypted files. We propose two face biometric-based search-able encryption models that support single-user and multiuser scenarios, respectively. Furthermore, we propose a key recovery approach that relies exclusively on facial bio-metric data, making it easier for users to migrate across devices. Taking into account the limitations of storage and computation on the devices of users, we design a pairing-free elliptic-curve-based encryption algorithm in order to enhance the user’s experience. In order to ensure that cloud servers return the right documents, we provide correctness and security proofs. We also perform a security analysis of FAKES and demonstrate its effectiveness through a series of extensive experiments.
Glycemic Traits and Oesophageal Cancer a Two-Sample and Multivariable Mendelian Randomization Study
Authors: Chen Yuxing , Zeng Qingpeng , Li Muyu , Chen Keqin , Zhao Jun 
Published: October 2023

Abstract
Background: Observational studies indicate a potential link between increased blood glucose levels and the development of oesophageal cancer. However, the causal relationship between glycemic traits and oesophageal cancer has not been clarified yet. The aim of this research was to examine if there is a genetic link between glycemic characteristics and oesophageal cancer through the use of Mendelian randomization analysis.
Methods: We conducted a TSMR analysis and MVMR using publicly available GWAS data on the European population. The primary analysis utilized the IVW method, which was subsequently validated through comprehensive complementary and sensitivity analyses.
Results: IVW analysis revealed a substantial correlation (OR=1.612, P=0.0228) between type 2 diabetes (T2DM) and oesophageal cancer. After accounting for body mass index (BMI), this association remained to be statistically significant in multivariate MR analyses (OR=1.662, P=0.0416). There was only a small amount of evidence indicating a possible link between oesophageal cancer and other glycemic traits after excluding the outliers.
Conclusions: Our study further supports the evidence that European individuals with T2DM are at an increased risk of developing oesophageal cancer. It implies that pharmacological or lifestyle treatments for individuals with T2DM could potentially be advantageous in the prevention of oesophageal tumor development.
Intelligent Extraction of Surface Cracks on LNG Outer Tanks Based on Close-Range Image Point Clouds and Infrared Imagery
Authors: Guo Ming , Zhu Li , Zhao Youshan , Tang Xingyu , Guo Kecai , Shi Yanru , Han Liping 
Published: October 2023

Abstract

The precise detection and ongoing surveillance of surface fractures on exterior LNG storage tanks are crucial in guaranteeing the secure transit and storage of natural gas. Undetected fractures have the potential to result in the release of liquefied natural gas (LNG), hence presenting a significant risk to both public health and the environment. This paper presents a novel approach for crack identification, which involves the integration of thermal infrared pictures and point clouds derived from close-range images captured by unmanned aerial vehicles (UAV). The aim of this approach is to overcome the limitations of conventional manual detection methods, namely in terms of efficiency and safety concerns. The primary approach for acquiring two-dimensional photographs of the tank surface is the utilization of infrared technology to generate an infrared dataset capturing the presence of fractures on the storage tanks' exterior. The utilization of the attention mechanism convolutional neural network is employed during the process of model training. The UAV close-range photos were utilized in close-range photogrammetry to generate an accurate point cloud model. This was achieved by incorporating control point coordinates and matching feature points. The infrared photos that were discovered were subsequently matched with this particular model. The 3D model that was officially was employed as a point of reference on the unfolded 2D plane. To construct the depth image, a least-squares approach of least-column fitting was utilized. In order to validate the accuracy of the automated extraction process, a manual crack extraction was conducted on the original close-range image point cloud of the tank exterior. The results indicated that the extracted cracks exhibited an accuracy level of around 97.6%. The experimental findings demonstrate that the process of crack extraction exhibits a high level of accuracy, hence presenting numerous possible applications in the realms of maintenance management and intelligent monitoring. The utilization of this technology is appropriate for the purpose of monitoring the thermal conditions and structural soundness of LNG storage tanks.
Gate Mesa Terminal With Drain-Field-Plated β-Ga2O3 MOSFET With Power Figure of Merit of 1.914 GW/cm2
Authors: Zhang Yunfei , Luan Suzhen , Cheng Xuepei 
Published: October 2023

Abstract
In this article, we propose a novel device structure for a Gate Mesa Terminal (GMT) with a drain field plate, aimed at improving the breakdown voltage (Vbr) and reducing the on-resistance (Ron) of lateral β-Ga2O3 metal-oxide-semiconductor field-effect transistor (MOSFET). Through the design of the GMT structure, the peak electric field of the β-Ga2O3 MOSFET is directed towards the passivation layer, effectively suppressing the electric field in the channel, resulting in a higher Vbr. The optimal Vbr, specific on-resistance (Ron,sp) and maximum transconductance (gm) of various GMT structures are 4827 V, 9.9 mΩ·cm2 and 15.32 mS/mm, respectively. These values are 2.63 times, 0.88 times and 1.25 times higher than those of the non-GMT structure. Furthermore, with a channel doping concentration is 1×1016 cm−3 , the GMT achieves an enhanced threshold voltage of +0.26 V. The optimal power figure of merit (PFOM) of 1.914 GW/cm2 is obtained by simulating the electrical properties of different bevel Angles, field plate parameters, epitaxial layer doping concentration and mesa thickness. This innovative structure presents a new design concept for the next generation of high voltage and high-power devices rated above 4 KV.
Optimization and Characterization of Nori-Like Product Made from Ulva lactuca and Gracilaria changii using Mixture Design Methode
Authors: Sinurat Ellya , Sihono Sihono , Fateha Fateha , Supriyanto Agus , Suryaningrum Theresia Dwi , Nurhayati Nurhayati , Fransiska Dina , Utomo Bagus S.B. , Sedayu Bakti Berlyanto , Subaryono Subaryono , Waryanto Waryanto 
Published: October 2023

Abstract

Nori is a dried edible seaweed sheet made from Porphyra, a genus of red algae that thrives primarily in subtropical waters. Nori-like products have been developed from tropical seaweed species, but they are still considered undesirable due to their astringent taste and lower protein content compared to the original nori. This investigation aimed to produce a nori-like product by utilizing a combination of locally sourced seaweeds Ulva lactuca and Gracilaria changii with the addition of anchovy flour to enhance its protein content. To obtain the optimal formulation of the product, we employed a design expert software application to analyze sensory data collected from a hedonic scale assessment involving 25 trained panelists. We evaluated sensory characteristics, including appearance, aroma, texture, taste, and overall satisfaction. Additionally, we considered parameters such as crispness and colour to determine the nori-like product quality. The best-selected product, determined through sensory evaluation, underwent further analysis of its proximate and amino acids profile, as well as mineral content. The results were compared to those of commercial nori from Porphyra. The highest-quality product was found to be the nori-like product with a formula consisting of 25.40% Ulva lactuca, 7.98% Gracilaria changii, 1.50% glycerol, and 4.12% anchovy.
C-reactive protein is not a reliable marker for ruling out infection after cesarean section: a retrospective analysis
Authors: Enengl S , Oppelt P , Mayer RB , Brandlmayr E , Trautner PS 
Published: October 2023

Abstract

Purpose Infection after cesarean section is a major contributor to maternal morbidity. Measurement of C-reactive protein (CRP) is a laboratory test frequently conducted to rule out or confirm postoperative infection. The present study aimed to evaluate whether CRP is a suitable tool for ruling out infection after cesarean section and whether there are any reliable cut-off values.Methods 2056 patients with cesarean section (CS) over a 3-year period were included in a retrospective analysis. Outcome parameters and risk factors for postoperative infection were collected. CRP values from preoperative and postoperative tests were compared. Cut-offs for ruling out infection were assessed.Results Among 2056 CSs, postoperative infection occurred in 78 cases (3.8%). The prevalence of infection in emergency CS was lowest, at four out of 134 (2.9%), and the highest prevalence was seen in secondary CS, at 42 of 903 (4.6%; P = 0.35). CRP values in the infection group were significantly higher (preoperative, 1.01 mg/dl vs. 0.62 mg/dl; day 1 postoperative, 7.91 mg/dl vs. 6.44 mg/dl; day 4 postoperative, 8.44 mg/dl vs. 4.09 mg/dl; P = 0.01). A suitable cut-off value for ruling out infection was not identified.Conclusions Although CRP values were significantly higher in the infection group, the clinical relevance of this appears to be negligible. CRP testing does not appear to be a reliable tool for diagnosing or ruling out postoperative infection.
Paternal postpartum depression and associated factors among partners of women who gave birth in the last 12 months in Dessie Town, Northeast Ethiopia, 2023: community based cross sectional study
Authors: Assefa Abdulaziz , Werkie Amare , Assefa Mandefiro , Belay Aynalem 
Published: October 2023

Abstract
Background Paternal depression among fathers of new-borns is a new concept in Ethiopia. It is an emerging public health concern because; it produces insidious effects on the well-being of new-borns as well as on the whole family, which is currently under screened, under diagnosed and undertreated. However, there is limited evidence on the prevalence of paternal postpartum depression and its predictors among partners of women in Ethiopia.Methods A community based cross-sectional study was conducted among 634 partners of postpartum women in Dessie town from January10-Feburary10, 2023 to assess the prevalence of paternal postpartum depression and associated factors among partners of women who gave birth in the last 12 months. The data were collected using a structured and pretested questionnaire though face-to-face interviews and the data were cleaned, edited, and entered into Epi-data version 4.6, and analysed SPSS Version 26.The Edinburgh Postpartum Depression Scale was considered at a cutoff point ≥ 10 to detect depression.Result A total of 610 fathers were interviewed with a response rate of 96.2% and the prevalence of paternal postpartum depression was 19%, (95%CI: 16.0, 22.3). This study showed that; not comfortable with family income [AOR = 2.32(95% CI: 1.16, 4.66)], substance use [AOR = 2.48(95% CI: 1.22, 5.05)], experience of childbirth[AOR = 1.89(95% CI: 1.02, 3.50)], unplanned pregnancy [AOR = 2.81(95%CI: 1.50, 5.25)] and infant sleep problem [AOR = 3.59(95% CI: 1.80, 7.18)], were significantly associated with paternal depression.Conclusion and recommendations: This study revealed that almost one-fifth of fathers had paternal postpartum depression. Not comfortable with family income, substance use, experience of childbirth, unplanned pregnancy and infant sleeping problem were significantly associated with paternal postpartum depression. This suggests the need to provide health education to decrease substance use and counselling to the utilization of family planning to minimize unplanned pregnancy and supports offer to multiparous fathers.
Prediksi Penjualan Bisnis Rumah Properti Dengan Menggunakan Metode Autoregressive Integrated Moving Average (ARIMA)
Authors: Pangaribuan Jefri Junifer , Fanny Fanny , Barus Okky Putra , Romindo Romindo 
Published: October 2023

Abstract - Sales forecasting plays an important role in determining the company's strategy in the future because it allows control of planning and availability of home production according to consumer needs. Forecasting accuracy provides significant advantages for companies, including production cost savings and avoidance of unnecessary costs. Without accurate forecasting, a company will face difficulties in determining the quantity of house production, which can have a negative impact on the company's financial balance if the houses do not sell. This research implements the Autoregressive Integrated Moving Average (ARIMA) model to forecast property business house sales with a high level of accuracy to support future business decisions. The results of the research on the application of the Autoregressive Integrated Moving Average algorithm show that the ARIMA model (9,1,10) provides good forecasting results measured by the lowest AIC and BIC values compared to the other 4 models, namely ARIMA (10,1,9); ARIMA(8,1,9); ARIMA(10,1,10); and ARIMA (12,1,12) accompanied by an evaluation of measuring the accuracy of the model using RMSE, MSE, and MAPE with each value of 0.281409; 0.079191 and MAPE of 3.4% so that it can be said that sales forecasting provides a good level of accuracy.Abstrak - Prediksi penjualan memegang peran penting dalam menentukan strategi perusahaan di masa depan karena memungkinkan pengendalian perencanaan dan ketersediaan produksi rumah sesuai dengan kebutuhan konsumen. Keakuratan prediksi memberikan keuntungan signifikan bagi perusahaan, termasuk penghematan biaya produksi dan menghindari biaya yang tidak perlu. Kesulitan dalam menentukan jumlah produksi rumah tanpa prediksi yang tepat dapat berdampak negatif pada keseimbangan keuangan perusahaan jika rumah tidak terjual. Penelitian ini mengimplementasikan model Autoregressive Integrated Moving Average untuk melakukan prediksi penjualan bisnis rumah properti dengan tingkat akurasi yang baik untuk dapat mendukung keputusan bisnis kedepannya. Hasil penelitian pada pengaplikasian algoritma Autoregressive Integrated Moving Average menunjukkan bahwa model ARIMA (9,1,10) memberikan hasil nilai prediksi yang baik diukur dari nilai AIC dan BIC yang paling rendah dibandingkan 4 model lainnya yaitu ARIMA (10,1,9); ARIMA (8,1,9); ARIMA (10,1,10); dan ARIMA (12,1,12) disertai evaluasi pengukuran keakuratan model dengan menggunakan RMSE, MSE, dan MAPE dengan masing-masing nilai yaitu 0.281409; 0.079191 dan MAPE sebesar 3.4% sehingga dapat dikatakan prediksi penjualan memberikan tingkat akurasi yang baik.
Research and development of data compression methods for technical monitoring systems
Authors: Yakunin A. G. 
Published: October 2023

Objective. The aim of the study is to develop methods for data compression in relation to monitoring systems.Method. The studies were carried out mainly experimentally, by processing data generated by the information-measuring system of the Altai State Technical University in the process of meteorological observations, temperature control and control of the consumption of such energy resources as hot and cold water, heat supply. However, when it was proposed to change their structure and presentation form to compact the stored data, the degree of compression was found theoretically.Result. The results of studies conducted with the participation of the author of the publication in the field of data processing, transmission and storage are presented. Methods for streaming data compression “on the fly” as it arrives, both lossy and lossless, as well as methods based on optimizing the structure of databases designed to store information collected during monitoring, are considered. The main attention is paid to the consideration of data compression created in the process of temperature monitoring, since it is the control and monitoring of temperature processes that is most common in various technical process control systems, heat metering systems both on the consumer side (housing and communal services) and on the side of the heat supply organization.Conclusion. In the vast majority of cases, lossless compression allows you to compress the information received from the monitoring system by more than 10 times, and lossy compression is much stronger, and without losing the pragmatic value of the stored information.