bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence of anxiety and depression among pregnant women with diabetes and their predictors in Qazvin province, Iran
Authors: Salimi Hamid Reza , Griffiths Mark D. , Alimoradi Zainab 
Published: September 2023

Abstract
Background: Addressing mental health of diabetic pregnant women is important as it might increase the chance of obstetric complications, preterm birth, and neonatal complications.
Aim: The present study investigated the prevalence of anxiety and depression among pregnant women with diabetes and their predictors.
Methods: A cross-sectional study was conducted in 2023. The sample comprised 350 pregnant women with diabetes (pre-pregnancy or gestational) referred to comprehensive health centers in Qazvin Province, Iran. Fertility and demographic characteristics, anxiety, depression, partner social support, self-efficacy, medication adherence and fear of hypoglycemia were assessed.
Results: Among the sample, 28.9% had pre-pregnancy diabetes and 71.1% had gestational diabetes. Anxiety and depression were reported by 74.9% and 79.4% of all participants (significantly higher among those with pre-existing diabetes compared to gestational diabetes). Self-efficacy (OR: 0.91 [95% CI: 0.86; 0.96]) and spouse's social support (OR: 0.68 [95% CI: 0.56; 0.82]) were significant predictors of abnormal anxiety. Fear of hypoglycemia (OR: 1.06 [95% CI: 1.02; 1.09]), medication adherence (OR: 1.05 [95% CI: 1.01; 1.09]), self-efficacy (OR: 0.86 [95% CI: 0.82; 0.91]), partner social support (OR: 0.62 [95% CI: 0.49; 0.78]), diabetes type (pregnancy vs. pre-pregnancy diabetes; OR: 0.26 [95% CI: 0.09; 0.77]), perceived family economic status (fair vs. good; OR: 3.08 [95% CI: 1.12; 8.49]), and diabetes treatment (insulin vs. diet; OR: 0.21 [95% CI: 0.08; 0.55]) were significant predictors of abnormal depression.
Conclusion: Diabetic pregnant women should be evaluated for anxiety and depression during their prenatal visit. Improving self-efficacy, increasing medication adherence, reducing the fear of hypoglycemia, and improving the spouse’s social support might all be helpful in reducing anxiety and depression among pregnant women with diabetes.
Diffusion Behavior of Free Water and Bound Water in Insulation Paper Based on Langmuir Model
Authors: Kang Meicun , Yang Lijun , Lv Xiaolu , Wang Ke , He Yuxin 
Published: September 2023

Abstract
Moisture in oil–paper insulation is a threat to the safe operation of transformers. Consequently, the diffusion, migration, and equilibrium behavior of water molecules in oil–paper insulation has always been a research hotspot in this field. Water molecules exist in both free and bound states in oil–paper insulation. Currently, the Fick model is commonly used to describe the diffusion behavior of free water molecules in oil–paper, without considering the behavior of bound water molecules, resulting in significant deviations between the calculated and measured results. In this study, the Langmuir model was introduced to investigate the diffusion behavior of free and bound water during the drying process of insulation paper, revealing that the adsorption and desorption coefficients in the model could characterize the conversion process of free and bound water molecules in cellulose under different conditions, predict the drying behavior of insulation paper at a given temperature and pressure, and guide the drying process conditions of active part insulation in transformers.
Heteroclinic for a 6-dimensional reversible system - Domain walls in convection Gérard Iooss
Authors: Iooss Gerard 
Published: September 2023

Abstract

A six-dimensional reversible normal form system occurs in Bénard-Rayleigh convection between parallel planes, when we look for domain walls intersecting orthogonally (see Buffoni et al [1]). We prove analytically the existence, local uniqueness, and analyticity in parameters, of a heteroclinic connection between two equilibria, each corresponding to a system of convective rolls. We prove that the 3-dimensional unstable manifold of one equilibrium, intersects transversally the 3-dimensional stable manifold of the other equilibrium, both manifolds lying on a 5-dimensional invariant manifold. We also study the linearized operator along the het-eroclinic, allowing to prove the persistence under perturbation, of the heteroclinic obtained in [1]. This provides a complete mathematical proof of existence of orthogonal domain walls in Bénard-Rayleigh convection.
In-plane synthesis of silicon microwires array for optoelectronic and microelectronic applications; a TCAD study
Authors: Jahromi Hamed Dehdashti , Sanaei Ali 
Published: September 2023

Abstract

Silicon microwires have been used in various applications such as sensors, solar cells, and lithium-ion batteries due to their high surface area-to-volume ratio and good electrical conductivity. One of the interesting challenges in microelectronics and photovoltaics is the creation of interspacing, laterally oriented silicon arrays on SiO2 substrate for semiconductor devices with multi-function. Silicon microwires array is a type of microstructure with unique optical and electrical properties that makes it useful for various applications. The fabrication of such structures is still a serious technological problem and requires searching for new approaches and techniques. In this work, we report a CMOS compatible approach for synthesis of in-plane Si microwires array on SiO2 substrate. The approach is a combination of micro-photolithography, oxidation, and etching techniques that are all compatible with standard CMOS fabrication processes. We found that dray oxidation leads to desirable results, and the process will be successful at 1575 degree Celsius after 120 minutes. The resulted Si microwires array are then processed to be used in the channel of a MOSFET for microelectronic application as a sensor. The excellent performance of the designed MOSFET proves formation of the desired Si microwires array which can be used in the structure of any microelectronic devices and sensors. All simulations were performed using TCAD Silvaco software.
Prediction of neurological diseases using data mining
Authors: Shirdel Gholam Hassan , Ghanbari Mojtaba , Zarghami Shabnam 
Published: September 2023

Abstract
Background and Aim: Data mining is one of the stages of acquiring knowledge in a database to collect useful information. Data mining is a new field that has various applications and it is known as one of the top ten sciences affecting technology. Data mining analyzes databases and massive data sets in order to discover and extract knowledge, and machine (and semi-machine) mines. Such studies and explorations can actually be considered the extension and continuation of the ancient and ubiquitous knowledge of statistics. The major difference is the scale, breadth and variety of fields and applications, as well as the dimensions and sizes of today's data, which require machine learning, modeling, and training methods. In the 1960s, statisticians used the term "Data Fishing" or "Data Dredging" to discover any relationship in a very large volume of data without considering any assumptions. After thirty years and with the accumulation of data in databases, the term "Data Mining" became more popular around 1990. The purpose of this research is to predict brain and nerve diseases using data mining algorithms. The purpose of this research is to help medical professionals to predict disease.
Materials and Methods: In this research, after data preparation, disease prediction has been attempted using large matrix methods and data mining techniques. By examining the new vector, we can find out which of the diseases in the matrix will be closer to this new disease with new symptoms using the rows of the matrix. The conducted research is one of descriptive-analytical and applied studies.
Results: In this research, we used different meters such as Jacquard distance, cosine similarity L1-norm and cosine similarity L2-norm implemented a program using Python software to predict brain and neurological diseases.
Conclusion: The algorithm implemented by Python software, the doctor enters the symptoms of the patient and the output of the program shows three diseases close to the input symptoms for each meter, and finally all the meters are compared and the meter that has a weaker result is determined each time it is run. The advantages of each of these meters are explained below.
Multiple Fault Detection in Taper Roller Bearings Based on Sensor Fusion of Acoustic Emission and Vibration Data Using Deep Learning Techniques
Authors: Mahajan Pavan , Vasu V , Srin K V S , Pal Anuj 
Published: September 2023

Abstract

In rotating machinery, taper roller bearings are essential parts whose failure can have fatal consequences. To ensure safe and effective operation, these bearings must undergo condition monitoring and fault diagnosis. This study uses sensor fusion of vibration and acoustic emission data to demonstrate an integrated approach for multiple fault detection in taper roller bearings. Most of the literature classified bearing faults in 3 or 4 classes. Classification for lesser faults is an easy task as compared to classification of multiple faults. The proposed experiment demonstrate that the suggested method is highly accurate in detecting multiple bearing faults, and the integration of acoustic emission and vibration data improves the fault detection performance compared to using either data source alone. The proposed method involves collecting acoustic and vibration data using a DAQ system for multiple bearing faults and converting that data into scalogram images. This study also focused on importance of data denoising and use of optimal hyperparameter. As per proposed method data pre-processing and setting ideal hyperparameter have significantly increased the accuracy of bearing fault classification. This study uses deep learning CNN model to classify the scalogram images of bearing faults. CNN automatically extract features from scalogram images and classify images based on their similarities. The proposed approach can be used to monitorthe conditions and diagnose various faults of taper roller bearings in various industrial applications.
TLIS: Two-stage low-light image instance segmentation
Authors: Li Wei , Huang Ya , Zhang Xinyuan , Han Guijin 
Published: September 2023

Abstract
Current instance segmentation models perform adequately under normal light conditions, but encounter significant challenges in low-light scenarios, where the feature information of objects becomes less discernible, thus impeding accurate segmentation. The present study proposes a two-stage methodology for instance segmentation in low-light images. In stage-I, we enhance the low-light images while denoising and enhancing the detail information. To mitigate degradation phenomena such as noise and loss of details caused by low-light image enhancement (LLIE), we propose a post-processing module for enhancing details while reducing noise. This module uses a diffusion approach with an attention mechanism to model the conditional distribution between under-enhanced and naturally illuminated images. The enhancement results from the first stage are used as input to the segmentation network in the second stage, and we observe that incorporating fine-grained features into the mask branch of the segmentation network positively affects the accurate delineation of finer masks. To achieve this objective, we devise a wavelet feature fusion module to effectively integrate the high-resolution and low-resolution features within the feature pyramid, thereby preserving more intricate details. We achieve great segmentation results on LIS, an extremely low-light instance segmentation dataset. Detailed Comparative experiments and ablation studies show the advantages and excellent generalization ability of our model.
Light-Trans YOLO: A Lightweight Network Based on Transformer for Defect Detection of Industrial Lace Surface
Authors: Wang Yafei , Jing Junfeng , Sheng Siyu 
Published: September 2023

Abstract
Lace surface Defect detection has always been a crucial step in the industrial production of lace products. However, due to the complex texture and deforma-bility of lace, as well as the difficulty of distinguishing minor defects from normal images. Therefore, the detection of defects on lace surfaces is a challenging but rarely studied task. In this paper, we propose a new lightweight detection framework , Light-Trans YOLO, to detect lace surface defects. First, our backbone network uses the lightweight network C3 GhostNet. In addition, to obtain more complete global information, we add the lightweight Mobile Transformer Block (MTB) to the backbone network. Then we use the proposed standard deep-wise separable convolution (SDSConv) and SDSBottleneck to design a new neck and add Coordinate Attention (CA) at the end, which overcomes the problem of information loss of deep separable convolution and extracts more effective information. In the training, we propose the loss function ϵSIoU, which can improve the separability of defective and normal samples. We conduct experiments on the industrial lace surface defect dataset collected in lace production sites, and the experiments prove that the mAP of our model is 96.6%, which is 7.7% higher than YOLOV5s, and the FPS and F1-score of the model reaches 50.3 and 0.93, which indicates that our model has a great trade-off between detection accuracy and speed.
Lattice simulations of non-minimally coupled scalar fields in the Jordan frame
Authors: Figueroa Daniel , Florio Adrien , Opferkuch Toby , Stefanek Benjamin 
Published: September 2023

The presence of scalar fields with non-minimal gravitational interactions of the form \xi |\phi|^2 Rξ|ϕ|2R may have important implications for the physics of the early universe. We propose a procedure to solve the dynamics of non-minimally coupled scalar fields directly in the Jordan frame, where the non-minimal couplings are maintained explicitly. Our algorithm can be applied to lattice simulations that include minimally coupled fields and an arbitrary number of non-minimally coupled scalars, with the expansion of the universe sourced by all fields present. This includes situations when the dynamics become fully inhomogeneous, fully non-linear (due to e.g. backreaction or mode rescattering effects), and/or when the expansion of the universe is dominated by non-minimally coupled species. As an example, we study geometric preheating with a non-minimally coupled scalar spectator field when the inflaton oscillates following the end of inflation.
The Impact of Health Education Utilizing Online QR Code on Hospital Stay in Patients Undergoing Day Surgery: A Retrospective Observational Study (Preprint)
Authors: Ma Guozhen , Jiang Pengjun , Zhao Yongling , Huang Yanhui , Luo Yijun 
Published: September 2023

BACKGROUND

Day care surgery is required early recovery and discharge. To safely shorten hospital stay represents future direction of day surgery. The use of specific nursing interventions before surgery can reduce anxiety as well as speed up post-operative recovery. To provide effective preoperative health education may reduce post-operative fasting time and early ambulate, thereby shorten hospital stay. Specifically, to select a health belief model (HBM) for theoretical guidance to improve patients' compliance with health education for first ambulation, thereby shorten hospital stay in patients undergoing day surgery.

OBJECTIVE

The aim is to distribute online QR code to pre-hospitalized patients for health education and to improve compliance with early eating and ambulating after surgery, thereby shortening the hospital stay.

METHODS

The study was retrospective and observational. The relationship between health education-based utilizing online QR code and hospital stay in patients with inguinal hernia repair under general anesthesia following day surgery between from August 2022 to June 2023 was reviewed and analyzed.The t-tests or Mann-Whitney U-tests was used to compare the means of two groups (viewed online QR code and non-viewed).The chi-square test was used to compare the rates between the two groups. To explore the factors associated with these factors, regression and correlation analyses were performed.

RESULTS

There were significant differences in the participant's hospital stay, the time to postoperative first ambulation and dietary, Self-rating Anxiety Scale(SAS), and patient satisfaction (P<0.05). The analyses revealed statistically significant correlations between hospital stay and viewed online QR code,the time to postoperative first ambulation and dietary, SAS as well as pain scores(P<0.05). This fully adjusted linear regression analyses observed a negative relationship between viewed online QR code and hospital stay (β = −4.06, 95%CI: −6.43, −1.70; P =0.002), the time to postoperative first ambulation(β = −0.71, 95%CI: −1.25, −0.17; P =0.015) as well as the time to postoperative first dietary(β = −1.20, 95%CI: −1.71, −0.34; P =0.006) after adjusting for confounders.

CONCLUSIONS

Providing effective preoperative health education-based utilizing online QR code during pre-hospitalized may shorten hospital stay as well as improve the experience for patients with day surgery.
Literasi Hukum Terkait Pembatasan Penggunaan Kantong Plastik Bagi Siswa-Siswa SMAN 1 di Kota Blitar
Authors: Masnun Muh. Ali , Sulistyowati Eny , Nugroho Arinto , Hermono Budi , Nur Azizah Siti , Hassyati Astrid Amidiaputri 
Published: September 2023

Sampah plastik merupakan sampah anorganik yang sulit terurai dan dapat memiliki dampak negatif bagi lingkungan. Bertambahnya jumlah penduduk berimplikasi pada jumlah penggunaan plastik. Tujuan dari pengabdian masyarakan ini untuk memberikan literasi hukum mengenai kesadaran hukum khususnya bagaimana regulasi terkait pembatasan penggunaan kantong plastic khususnya di SMAN 1 Kota Blitar. Metode yang digunakan dalam pengabdian ini berupa sosialisasi dengan melakukan tiga tahapan utama yakni, pretest, sosialisasi dalam bentuk pemaparan materi, dan posttest. Berdasarkan hasil pelaksanaan kegiatan tersebut tampak bahwa adanya kenaikan signifikan terkait pengetahuan hukum, pemahaman hukum, dan sikap hukum para siswa siswi tentang peraturan perundang-undangan terkait pembatasan kemasan sekali pakai dan kantung plastik. Meski demikian, perilaku hukumnya masih menunjukkan siswa siswi yang tidak peduli pada pembatasan kemasan plastik. Para siswa siswi masih memilih snack yang menggunakan kemasan plastik.

Abstract
Legal Literacy Related to Restricting the Use of Plastic Bags for Students of SMAN 1 in Blitar City.
Plastic waste is anorganic waste that is difficult to decompose and can have a negative impact on the environment. The increase in population has implications for the amount of plastic use. The purpose of this community service is to provide legal literacy regarding legal awareness, especially regarding regulations related to restrictions on the use of plastic bags, especially at SMAN 1 Kota Blitar. The method used in this service is in the form of socialization by carrying out three main stages namely, pretest, socialization in the form of material presentation, and posttest. Based on the results of the implementation of these activities it appears that there was a significant increase in legal knowledge, legal understanding, and legal attitudes of students regarding laws and regulations related to restrictions on single-use packaging and plastic bags. However, his legal behavior still shows students who do not care about restrictions on plastic packaging. The students still choose snacks that use plastic packaging.
Pemanfaatan Inokulum Feses Sapi Dalam Uji Kecernaan In Vitro ADF dan NDF Rumput Gajah (Pennisetum purpureum)
Authors: Alwi Yun 
Published: September 2023

The aim of this study was to reveal the effect of faecal inoculum on the in vitro digestibility of acid detergent fibre (ADF) and neutral detergent fibre (NDF) of Napier grass(Pennisetum purpureum). The design of this reserach was Completely Randomized Design (5 x 4) with five treatments and fourreplications. The treatments were rumen liquor inoculum, faecal inoculum (FI), FI added with sugar of 2.5 % (w/v), FI added with sugar of 2.5 % (w/v) and urea of 2.5 % (w/v) and FI added with urea of 2.5 % (w/v) for treatment A, B, C, D and E respectively. Samples of Napier grass were tested by the two stepin vitro technique of Tilley and Terry (1963). Results of this study showed that faecal inoculum significantly (P<0.05) decreased the digestibility of ADF and NDF of Napier grass. The use of faecal inoculum (treatment B, C, D and E) showed the lower digestibility of ADF and NDF than using therumen liquor. In conclusion, the addition of sugar or and urea in the faecal inoculum could not increase the digestibility of ADF, NDF and gas profile of Napier grass.
Pengaruh Dosis Inokulum Marasmius sp. dan Lama Inkubasi terhadap Kandungan Komponen Serat dan Protein Murni pada Sabut Kelapa Sawit untuk Bahan Pakan Ternak
Authors: Musnandar Endri 
Published: September 2023

The objective of the experiment was to find out the best inoculum dosage and incubation time for fiber component percentage and true protein percentage. The experiment was arranged by a Completely Randomized Design with factorial pattern 4x4, which the first factor was inoculum dosage (D2,5=2,5%; D5=5%; D7,5=7,5%; and D10=10%) and the second factor was incubation time (W1=1 week, W2= 2 week, W3 = 3 week, and W4= 4 week), the treatment combination were replicated 3 times which component fiber percentage and true protein percentage as parameters. All data were analyzed by analysis of variance followed DMRT. The results of experiment showed that there was significant interaction between inoculum dosage and incubation time on fiber component and true protein percentage. The lowest of fiber component especialy lignin and highest true protein percentage were found at D3W3 combination treatment, which the fiber componen percentage was NDF (67.63%), ADF (60.50%), selulosa (45.27%), lignin (9.93%), and True protein (8.957%).
Faktor-Faktor yang Mempengaruhi Lama Kebuntingan pada Sapi Hissar Sumbawa
Authors: Arman Chairusyuhur 
Published: September 2023

A study of factors affecting gestation period was made by statistically analyzing the data relating to 38 calvings of Hissar cattle in BPT & HMT Serading Sumbawa. The average length of gestation period was found to be 289.87 ± 6.42 for all calves, 289.38 ± 6.48 days for males dan 290.71 ± 6.24 for females. Females calves were carried 1.33 days longer than males, the difference, however, tended not to be significant. Calvings were distributed throughout the year, the percentage of calvings was lower (28.95%) during wet season than that of dry season (71.05%). The percentage of calvings both in males and females were found to be higher during dry than wet seasons. It is concluded, therefore, that sex does not appear to influence gestation period, while season of calving was found to be responsible in causing variation in the length of gestation period.
Korelasi Motilitas Progresif dan Keutuhan Membran Sperma dalam Semen Beku Sapi Ongole Terhadap Keberhasilan Inseminasi
Authors: Jalius Jalius , Depison Depison 
Published: September 2023

The correlation between the progressive motility and sperm membrane totality in frozen semen of Ongole with artificial insemination success. This experiment was aimed to evaluated the characteristics of progressive motility and spermatozoa membrane totality of Ongole cattle in frozen semen and their correlation to the successful of artificial insemination. The parameters were progressive motility and membrane totality (MT) successful of artificial insemination was measured by non return rate (NR) and conception rate (CR). Result of this experiment showed that PM = 38.14%, MT = 69.86%, NR = 64.49% and CR = 53.47%. Progressive mortality significantly influenced (P<0.05) NR. Mortality and membrane totality significantly determine (P<0.05) the successful of artificial insemination (CR) of Ongole cattle