bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of the COVID-19 Pandemic on Brief Resolved Unexplained Events (BRUEs) in Children: A Comparative Analysis of Pre-Pandemic and Pandemic Periods
Authors: Nosetti Luana , Zaffanello Marco , Piacentini Giorgio , De Bernardi Francesca , Cappelluti Cristina , Sangiorgio Camilla , Agosti Massimo
Published: January 2024

Background: Brief Resolved Unexplained Events (BRUEs), formerly known as Apparent Life-Threatening Events (ALTE), are concerning episodes of short duration (typically < 1 min) characterized by a change in breathing, consciousness, muscle tone, and/or skin color. In some cases, SARS-CoV-2 infection has been associated with episodes of BRUEs in previously healthy children.This study aimed to compare the demographic, respiratory, perinatal, and infectious characteristics in children affected by BRUE before the COVID-19 pandemic and after the spread of SARS-CoV-2. Methods: We conducted a retrospective observational study covering January 2018 to March 2020 (pre-COVID-19) and April 2023 (during the ongoing COVID-19 pandemic). Collected variables included clinical information during pregnancy and neonatal details of children with BRUE. Results: The number of children in the pre-COVID-19 period was 186 (41%); after the emergence and spread of SARS-CoV-2, it was 268 (59%). The risk of infection at birth for children developing BRUE was higher during the pandemic. Children were less likely to have ongoing symptomatic infection during BRUE during the pandemic (coefficient B = 0.783; p=0.009). Respiratory symptoms during BRUE were more frequent during the pandemic (coefficient B = 0.654; p=0.052). Fever during BRUE was less likely during the pandemic (coefficient B = -0.465, p=0.046). Conclusions: The study suggests that the COVID-19 pandemic has significantly impacted children with BRUE, potentially due to changes in hygiene practices and maternal-fetal infections.
ANALISA KEBUTUHAN MATERIAL DAN RANTAI PADA PROSES PRODUKSI MESIN TEKUK PLAT HIDROLIK
Authors: Eka Putra Ismet , Wardianto Dedi , Juliantoni Juliantoni
Published: January 2024

Mesin penekuk plat atau yang disebut mesin bending, adalah pengerjaan membentuk logam lembaran (plat) sehingga sesuai dengan bentuk dan ukuran yang sudah direncanakan. Penelitian ini menerapkan teknologi hidrolik pada proses pembentukan dan penekukan plat. Mesin bending ini menerapkan mekanisme penjepitan pada plat dan melakukan pembebanan dengan menggunakan tenaga hidrolik untuk menekuk plat. Dalam pembuatan mesin bending ini perlu di analisisa apa saja kebutuhan material dan rantai proses produksi dari mesin penekuk plat hidrolik yang tepat guna. Pembuatan mesin tekuk plat hidrolik terbagi menjadi beberapa langkah yang harus dikerjakan dan dipersiapkan terlebih dahulu yaitu: Identifikasi gambar kerja, perencanaan pemilihan material, persiapan bahan, persiapan alat dan mesin, melakukan proses pengerjaan dan finishing. Bahan yang digunakan untuk membuat komponen dari mesin tekuk plat hidrolik yaitu dengan plat ST37 tebal 0,6 mm dengan komponen berupa part penjepit dengan ukuran 1400mm X 196mm X 307mm, part meja landasan dengan ukuran 1412mm x 156mm x 503mm, part penekuk dengan ukuran 1400mm x 250mm x 95mm, part Frame dengan ukuran 1000mm x 600mm. Sistem transmisi yang digunakan adalah sistem hidrolik untuk mendorong part penekuk. Lalu untuk mengangkat part penjepit plat dengan menggunakan sistem pengungkit pada kiri dan kanan mesin tekuk plat hidrolik. Mesin dan peralatan yang digunakan dalam pembuatan mesin tekuk plat hidrolik yaitu peralatan pengukuran, peralatan pengurangan volume, peralatan pengelasan, peralatan perakitan dan peralatan finishing.
Trends of Tribal Migration: A Study on Bastar Region in Chhattisgarh
Authors:   Professor and Head, Shaheed Mahendra Karma Vishwavidyalay, Jagdalpur, Bastar 494001, Chhattisgarh, India., Kolay Swapan Kumar , Srivastava Manoj Kumar ,   Vice- Chancellor, Shaheed Mahendra Karma Vishwavidyalay, Jagdalpur, Bastar 494001, Chhattisgarh, India.
Published: January 2024

This paper is an attempt to understand the emerging tribal migration patterns in five districts of Chhattisgarh and its impact on our society, culture, economic development and education. In this context, the present paper attempts to examine and it helps us to understand the current migration trend. Majority of the tribals migrate to others states due to better job opportunities, higher wages and good payment systems. The study found that economic and social factors significantly influence tribal migration. The elaboration of both primary and secondary data on tribal people migration helps us to understand the dynamics of present day mobility of tribals in Chhattisgarh.
USE OF ARTIFICIAL INTELLIGENCE IN ENGLISH LANGUAGE TEACHING
Authors: Akbarani Rizqi
Published: January 2024

In recent years, there has been a growing interest in the integration of artificial intelligence (AI) into various fields. Artificial Intelligence (AI) also has become a prominent technology in various fields, including education. One area where Artificial Intelligent (AI) has shown great potential is in English Language Teaching (ELT). With the rapid development of technology, Artificial Intelligent (AI) tools and applications have been integrated into language learning platforms, classrooms, and online resources, transforming the way English is taught and learned. In the realm of language teaching, Artificial Intelligent offers significant potential for enhancing the learning process and improving outcomes. English language teaching is no exception, as educators are exploring the potential of Artificial Intelligent (AI) to enhance language learning experiences. English language teaching is no exception, as Artificial Intelligent (AI) can enhance the learning experience for English language learners by providing personalized instruction, immediate feedback, and immersive language practice. This research addresses the extent to use artificial intelligence in English language teaching. Researcher used descriptive qualitative approach with questionnaire as technique of data collection. The results of this research are the Artificial Intelligence is needed in English language teaching. Artificial Intelligence also has negative and positive impact in English language teaching depend on utilized correctly and at the appropriate timing. Besides that, Artificial Intelligence also help students in improving their English skill like speaking, writing, and reading using product of Artificial Intelligence like Chat GPT, Quillbot, Grammarly, Plagiarism Checker, Paraphrasingtool.com. So, the use of Artificial Intelligent in English language teaching is very important or useful and also reducing the burden of teachers and improving teaching quality.
NEEDS ANALYSIS OF ENGLISH ON INFORMATION SYSTEMS DEPARTMENT STUDENTS USING AN INTEGRATED APPROACH
Authors: Fa'adhilah Wafiyah Asyifah , Jannah Izzatul , Zamhir Nabila , Azhar Nurhumaida , Musafar Muh. Aqil
Published: January 2024

In order to further comprehend the demands of students studying information systems while learning English, this study presents relevant facts. The focus of this research is investigating the students’ responses to the questions in sections 1) present situation analysis, 2) target situation analysis, and 3) learning needs. The design of this research is a survey using an integrated method. The sample of this research was 10 out of 53 second-year information systems students selected randomly. An online questionnaire survey was used in this study to gather data. Using a quantitative methodology, outcomes analysis was completed. The study's findings demonstrate the importance of English for future career support and competency enhancement. Students require more cutting-edge and visible audio-visual teaching techniques because of this.
POINTS OF LINGUISTIC STUDIES AND LANGUAGE TEACHING PERTINENT TO ISLAMIC VALUES
Authors: Milal A. Dzo'ul , Swasono Endratno Pilih
Published: January 2024

Purpose: This paper reveals the points of linguistic studies and that of language teaching which are relevant to Islamic values. Introduction: Interdisciplinary discussions on linguistic underpinnings including functional linguistics and language teaching principles, and Islamic perspectives have insufficiently been explored. Hence, the study focusing on such a relation gains significance. Method: Using an exploratory descriptive method, the data of this study were collected by exploring the linguistic axioms and language instructional principles which are relevant to Islamic knowledge conveyed in Qur’anic verses and Hadits. Having been collected, they were analyzed by thematic scrutiny, described, and concluded. The findings show that the linguistic points that are associated with Islamic values are the Divine source of language origin, the endowment of language acquisition devices, the compliance with maxims of quality and quantity in cooperative principles, that of politeness rules, and the existence of language variants. Conclusion: Concerning language teaching, the ideas that are appropriate to Islamic values include the importance of communicativeness and collaboration, the comprehensibility of instructional language, content-bound materials, and effective and efficient strategies.
Analisis Kesulitan Belajar Siswa Materi Indahnya Kebersamaan
Authors: Rahmawati Ari , Sunarsih Eti , Mertika Mertika
Published: January 2024

Tujuan penelitian ini adalah untuk mengetahui: (1) kesulitan belajar siswa pada mapel IPS pada siswa kelas IV di SDN 89 Singkawang (2) upaya guru mengatasi kesulitan belajar IPS pada siswa kelas IV di SDN 89 Singkawang.  Penelitian ini merupakan penelitian deskriptif kualitatif. Teknik pengumpulan data yaitu wawancara, angket, dan dokumentasi. Lokasi penelitian di SDN 89 Singkawang dengan subjek siswa kelas IV berjumlah lima siswa dan guru. Hasil analisis data menunjukkan dari lima siswa terdapat dua siswa mengalami kesulitan belajar berat sedangkan tiga yang lain mengalami kesulitan belajar ringan. Upaya guru dalam mengatasi kesulitan belajar siswa pada mapel IPS diketahui (1) memberikan pertanyaan agar dapat merangsang keaktifan siswa (2) menggunakan media pembelajaran berupa gambar agar fokus siswa dalam belajar dapat diarahkan (3) menerapkan dialog interaktif antar siswa dan guru. Kesulitan belajar yang dialami oleh siswa juga diantisipasi dengan menghadirkan orangtua siswa pada akhir semester dilakukan pertemuan antar pihak sekolah dengan orangtua siswa sebagai kegiatan evalluasi bersama demi kemajuan siswa dalam memperoleh hasil belajar yang maksimal.
Keaktifan Belajar Siswa SD pada Pembelajaran IPA Menggunakan Model Pembelajaran Make A Match
Authors: Anisah Siti , Erviana Lina , Purnamasari Mega Isvandiana
Published: January 2024

Tujuan penelitian ini untuk mengetahui (1) penggunaan model pembelajaran Make A Match pada pembelajaran IPA kelas V SDN 2 Gunungsari. (2) keaktifan belajar siswa setelah menggunkan model pembelajaran Make A Match pada pembelajaran IPA kelas V SDN 2 Gunungsari. (3) faktor pendukung dan penghambat kekatifan siswa dalam pembelajaran IPA menggunakan model pembelajaran Make A Match kelas V SDN 2 Gunungsari. Penelitian ini menggunakan jenis penelitian deskriptif kualitatif. Teknik pengumpulan data dengan teknik observasi, wawancara, angket dan dokumentasi. Teknik analisis data menggunakan teknik reduksi data, penyajian data, dan penarikan kesimpulan. Hasil analisis data memperoleh 1. Pembelajaran menggunakan model pembelajaran Make A Match dengan media kartu berpasangan mampu menarik perhatian, semangat siswa sehingga pembelajaran tidak merasa bosan dan jenuh. 2. Siswa aktif mengikuti pembelajaran IPA menggunakan model pembelajaran Make A Match. Dapat  membuat siswa lebih aktif bertanya, berpendapat, berdiskusi saling bertukar informasi dan dapat memecahkan masalah yang diberikan guru. 3. Faktor  pendukung pembelajaran menggunakan model pembelajaran Make A Match yaitu pembelajaran serta materi terarah, tidak kaku, interaksi siswa, tanggung jawab, dan pengetahuan siswa. faktor penghambat pembelajaran menggunakan model pembelajaran Make A Match yaitu ketidak tertiban siswa.
A week in the life of the human brain: stable states punctuated by chaotic transitions
Authors: Wang Maxwell , G'Sell Max , Castellano James F. , Richardson R. Mark , Ghuman Avniel
Published: January 2024

Many important neurocognitive states, such as performing natural activities and fluctuations of arousal, shift over minutes-to-hours in the real-world. We harnessed 3–12 days of continuous multi-electrode intracranial recordings in twenty humans during natural behavior (socializing, using digital devices, sleeping, etc.) to study real-world neurodynamics. Applying deep learning with dynamical systems approaches revealed that brain networks formed consistent stable states that predicted behavior and physiology. Changes in behavior were associated with bursts of rapid neural fluctuations where brain networks chaotically explored many configurations before settling into new states. These trajectories traversed an hourglass-shaped structure anchored around a set of networks that slowly tracked levels of outward awareness related to wake-sleep stages, and a central attractor corresponding to default mode network activation. These findings indicate ways our brains use rapid, chaotic transitions that coalesce into neurocognitive states slowly fluctuating around a stabilizing central equilibrium to balance flexibility and stability during real-world behavior.
Electron Paramagnetic Resonance Studies of Iron ions (Fe3+ - VO) as nanomaterials in Strontium Titanate Oxide (SrTiO3) Crystals at 80K
Authors: Booq Zainab Ibrahim Yousef
Published: January 2024

This work presents the structure of the phase transition of Fe3+ - V0 ions in SrTiO3 Crystals using Bruker EMX EPR spectrometer with an X-band (9.1–9.9 GHz) under nitrogen gas preserved. In the low magnetic field (300 mT) the structure is tetragonal (C4v)-orthorambic (C2v) but in high magnetic field (800 mT-1700 mT), it becomes tetragonal (C2v) only.The spectra exhibit sixteen lines originating from defect centers laying on three original direction equivalent to < 100>, others tilted a way from these directions by orthorambic angle\(\stackrel{-}{\varvec{\varnothing }}\)=±0.8, in addition to a tetragonal angle \(\varvec{\varnothing }\)=±1.2. The observed transition lines occur between the energy levels − 5/2↔-3/2,-5/2↔-1/2, -1/2↔+1/2, -3/2 ↔-1/2.
The spin Hamiltonian parameters are investigated by mathematical model (SM) and simulation programme written in this research. The position of defects Fe3+ - V0 are determined, showing that the paramagnetic Fe3+ ions moves toward the vacancy by 11 pm with a contraction of 10.55%.
Bioconversion of Eel Skin Waste into Valuable Collagen: Isolation, Spectral Characterization, and Biocompatibility Assessment
Authors: Asharaf Fathima , Rajasree Radhika , Rajan Roopa
Published: January 2024

The current investigation was carried out to evaluate the structural and cell proliferation capability of pike conger eel collagen derived by acid and enzymatic extraction methods. The recovery yield of pepsin-soluble collagen (PSC) (40.65%) was significantly higher (p<0.05) than acid-soluble collagen (ASC) (29.9%) on a dry weight basis. In terms of molecular weight pattern, α1 and α2 bands of extracted collagen occurred to be 130KDa and 112KDa, respectively, and were confirmed to have a Type 1 structure. The presence of characteristic peaks of amide bands in Fourier transform infrared spectra (FTIR) and the d value of 12.28 Å and 11.37 Å in X-ray diffraction (XRD) revealed no significant changes in the highly ordered, intact triple helical structure of collagen through pepsin digestion. The higher thermal stability with a denaturation temperature of 33.3°C for ASC and 35.1°C for PSC was well documented in the differential scanning calorimetry (DSC) curve, which showed a substantial correlation with the findings of the imino acid content of both ASC and PSC collagen (203.5 ± 1.06 and 216.81 ± 0.32 residues/1000g respectively). In addition, the nontoxic behavior of isolated collagen samples to L929 fibroblast cell lines emphasized the possible utilization of pike conger eel skin as a safe source of thermally stable collagen.
Deep-Learning-Based Survival Prediction of Patients with Thyroid Cancer
Authors: Zhang Jinrong , Li Li , Zheng Xinkai , He Yong , Wu Shuai , Jiang Yuzhen , Ming Wai-kit , Cheng Leong Nga , Lyu Jun , Deng Liehua
Published: January 2024

Background
This study acquired data pertaining to individuals diagnosed with Thyroid Cancer (TC) from the Surveillance, Epidemiology, and End Results (SEER) database. Subsequently, a deep learning and neural network model known as DeepSurv was employed to forecast the survival rate of TC patients and assess its efficacy.
Methods
Information on individuals diagnosed with TC from the years 2000 to 2019 was collected from the SEER database. The individuals in question were subsequently allocated into training and testing cohorts through a random selection process, maintaining a ratio of 7:3. The outcomes of the DeepSurv model were compared to those of the Cox proportional-hazards (CoxPH) model in order to estimate the chances of survival for TC patients. The accuracy of the model's predictions was evaluated through the examination of calibration curves, the time-dependent area under the receiver operating characteristic curve (AUC), and the concordance index (C-index).
Results
A total of 25,797 individuals diagnosed with TC were included in this study, with 18,057 comprising the training group and 7,740 forming the testing cohort. The CoxPH model exhibited robust correlations between age, gender, marital status, surgical intervention, radiation therapy, tumor extension, and the survival outcomes of TC patients. Notably, the C-index for the CoxPH model was 0.884, indicating a high level of predictive accuracy. Additionally, the training cohort data were used to create the DeepSurv model, which produced a higher C-index of 0.904. The predictive performance of both models was assessed, and the 3-, 5-, and 8-year AUC values were calculated. Regarding the CoxPH model, the corresponding area under the receiver operating characteristic curve (AUC) values were determined to be 0.835, 0.797, and 0.756, respectively. In comparison, the DeepSurv model achieved higher AUC values of 0.942, 0.918, and 0.906. The DeepSurv model demonstrated superior predictive ability for TC patients, as indicated by both the AUC values and the calibration curve, suggesting higher reliability compared to the CoxPH model.
Conclusion
Using TC patient data from the SEER database for research, we built the DeepSurv model, which performed better than the CoxPH model in estimating the survival time of TC patients.
A case of explosive community-acquired pneumonia and septic shock caused by Acinetobacter pitti
Authors: zhan xiaoying , Tian Xin , Zhang Cangjian
Published: January 2024

Acinetobacter pitti, a species of acinetobacter, has a special pathogenesis and is commonly known as nosocomial infection, but community infection is rare.We present a case of an outbreak of community-acquired pneumonia caused by Acinetobacter pitti, which was followed by convulsions and cavitation pneumonia with high virulence manifestations.Pneumonia infected by this bacterium is relatively rare, often manifested as acute onset, severe illness, high fever, shock, multiple organ failure and other manifestations, the mortality rate is very high, as early as possible to identify the infectious pathogen, early treatment can improve the success rate of treatment, significantly improve the prognosis of patients.
Risk Factors of Combined Spinal Epidural Analgesia on Maternal Intrapartum Fever
Authors: Zhao Hanzhen , Wang Cheng , Shi Lu , Tang Lian , Li Jingjing , Yu Yanxia
Published: January 2024

Objective
Combined spinal epidural analgesia (CSEA) has been commonly used as clinical labor anesthesia. Intrapartum fever induced by CSEA frequently occurs and seriously endangers maternal and fetal health. The aim of this study is to explore the risk factors of CSEA on maternal intrapartum fever.
Methods
A total of 200 parturient women from Suzhou Municipal Hospital were included in this study.74 parturient women with intrapartum fever during combined spinal epidural analgesia were included in fever group and 126 parturient women with normal body temperature in control group. The maternal demographic characteristics, details of labor and delivery, anesthetic scheme, fetal weight and Apgar score were collected. Logistic regression and receiver operating characteristic (ROC) curve were used to analyze the related factors of intrapartum fever during labor analgesia. Nomogram and decision curve analysis (DCA) were used to apply and evaluate the predictive model.
Results
Logistic multivariate analysis indicated that the times of vaginal examinations (OR 2.069,95%CI 1.587–2.696), duration of analgesia (OR 2.466,95%CI 1.741–3.492), time from rupture of membrane to delivery (OR 0.909,95%CI 0.855–0.967) and labor induced by water sac(OR 10.806,95%CI 1.384–84.035)were independent risk factors for intrapartum fever. More than 7 times of vaginal examinations, 3.35h of CSEA and 5.26h from rupture of membrane to delivery prompt for higher risk of maternal intrapartum fever.
Conclusion
The times of vaginal examinations, duration of analgesia, time from rupture of membrane to delivery and water sac induced labor are identified as risk factors of CESA-induced intrapartum fever. The predictive model and the nomogram based on the above risk factors contribute to evaluate and restraint intrapartum fever during labor anesthesia.
A fast numerical algorithm for finding all real solutions to a system of N nonlinear equations in a finite domain
Authors: Chueca-Díez Fernando , Gañán-Calvo Alfonso M.
Published: January 2024

A highly recurrent traditional bottleneck in applied mathematics, for which the most popular codes (Mathematica and Matlab) do not offer a solution, is to find all the real solutions of a system of N nonlinear equations in a certain finite domain of the N-dimensional space of variables. We present an algorithm of minimum length and computational weight to solve this problem, resembling a graphical tool of edge detection in an image extended to N dimensions. Once the hypersurfaces (edges) defined by each nonlinear equation have been identified in a single, simultaneous step, the coincidence of the hypersurfaces in the vicinity of all the hyperpoints that constitute the solutions makes the final Newton-Raphson step rapidly convergent to all the solutions with the desired degree of accuracy. As long as N remains smaller than about five, which is often the case for physical systems that depend on fewer than five parameters, this approach demonstrates excellent effectiveness.
Reappraisal on the Diversity of Ticks and Their Endosymbiont Prevalent in Indo-myanmar Border
Authors: Lalawmpuii Khawlhring , Biakzuala Lal , Jacob Siju Susan , Lalmuanpuia Joy , Behera Parthasarathi , Lalrintluanga Khawlhring , Tolenkhomba Thingujam Chaa , Lalremsanga Hmar Tlawmte , Lalchhandama Chhakchhuak , Lalrinkima Hmar
Published: January 2024

In this study, we explored the genetic diversity of ixodid ticks for the first time from Myanmar border of India, Mizoram and investigate their genetic affinities with other Indian isolates as well as with different populations from other countries. For genetic analyses, we employed phylogenetic inferences, genetic divergence, and haplotype networks based on the mitochondrial 16S rRNA, nuclear ITS-2, and 18S rRNA markers. We also implement multivariate principal coordinate analysis to visualize the genetic differentiation across ixodid ticks. Our genetic analyses affirm the identity of the ticks infesting bovine livestock in Mizoram as Rhipicephalus microplus, Haemaphysalis bispinosa, and Amblyomma habraeum. The phylogenetic inferences drawn in this study reveal instances of polytomies within Rhipicephalus species complex which could potentially arise from incomplete lineage sorting as a consequence of rapid diversification. Moreover, the genetic analysis also dictated R. microplus s.l. populations in India, China, and Pakistan constitute a closely related matrilineal lineage and form a distinct cluster of haplotypes with respect to R. microplus s.s. Despite the study, population of R. microplus from Mizoram nested within a single haplotype, our study signified a noticeable intraspecies divergence within R. microplus s.l. across India revealing the recovery of seven distinct matrilineal haplotypes based on the mitochondrial 16S rRNA marker, while a single and three distinct haplotypes are seen in the nuclear 18S rRNA and ITS-2 markers, respectively. This study also unveiled an infection rate of 5% for bovine haemoparasites and 97% for Coxiella-like-endosymbionts among the studied tick population. In conclusion, this study addresses a significant knowledge gap by providing the first documentation report on tick diversity within Myanmar border of India, Mizoram state.
The development of a dietary nutrient density educational tool and the investigation of its acceptance by Chinese residents from Henan province
Authors: Zhai Junya , Zhang Xu , Khatun Pipasha , Wang Saiqi , Cong Minghua , Liang Rui , Yao Fangfang , Liu Huan , Qin Jin , Guo Lijun , Kong Yongxia , Wu Hongbo , Ma Baihui
Published: January 2024

Objectives
Helping consumers select nutrient-dense foods is a strategy to improve their diet quality. However, communications based on the nutrient-dense foods as a positive attribution have not been used widely in nutritional education. This study aimed to develop an educational tool based on the picture and guidance of “Chinese Food Guide Pagoda (2022)", and extend it with the concept of nutrient density, and to investigate its acceptance by Chinese residents.
Methods
Three examples (recipes with high, medium, and low nutrient-rich foods (NRF) 9.2 ratings, an indicator for measuring dietary nutrient density) served as the basis for creating the dietary nutrient density educational tool. A self-designed questionnaire was designed to investigate the acceptance of the "dietary nutrient density educational tool" among college students from Henan province based on the theory of planned behavior.
Results
From three recipes used in the tool, with the decrease in the NRF9.2 score of the recipes, the energy intake was increased from 1686 kcal to 2363 kcal, the dietary fat-to-energy ratio was increased from 28–42%, and the mean adequacy ratio (MAR) was decreased from 0.96 to 0.87. A total of 851 college students completed the acceptance questionnaire. The average score of acceptance was 4.07, with the total score was 5. The results showed that behavior intention to use the tool positively correlated with family residence, subjective norms, and perceptual behavior control, with the latter playing the most substantial role. These three factors can account for 83.5% of the variation in behavior intention.
Conclusion
To encourage customers to choose healthier foods, we were the first to design the dietary nutrient density educational tool, expanding the current instructional tools—the Chinese Food Guide Pagoda (2022). The acceptance questionnaire survey showed that residents had a good acceptance of the tool and family residence, subjective norms, perceptual behavior control may strongly contribute to resident's acceptance for using the educational tool.
Analysis of Parasitic Capacitance of Wireless Power Transfer Coil and its Reduction Technique
Authors: He Qing , Chen Qingbin , Yang Fenggang
Published: January 2024

Wireless power transfer (WPT) technology has been widely investigated and applied in recent times. Increasing operation frequency proves to be effective in enhancing power transfer distance and reducing the volume of the magnetic coupling system (MCS) in the WPT system. However, once the frequency reaches MHz, the capacitive parasitic parameters of the coil in MCS can not be ignored, as it adversely affects the output characteristics in a series/series (S/S) compensation wireless power transfer system. This paper presents a method for parasitic capacitance modelling method and introduces a technique for its reduction in MCS. The parasitic capacitance is not only determined by the coil structure, including capacitance between adjacent and nonadjacent turns, but also by the electrical potential distribution of the winding turns. Based on the mathematical model of parasitic capacitances in MCS, a distributed capacitance compensation structure is adopted, and the capacitance parameters determination method is proposed. With the method, the coil parasitic capacitance can be reduced by changing the voltage potential distribution of the coil in MCS to minimize the impact of parasitic capacitances. Experimental results verify the accuracy and effectiveness of the theoretical analysis.
Riboflavin Intake and Mortality of Patients with Chronic Kidney Disease
Authors: Ren Xiaoxu , Wang Rong , Liu Xiangchun , Liu Fen , Wang Quanzhen , Sun Dehua , Jiang Zhiming , Chen Hairong
Published: January 2024

Background
Current studies have not reported the association between riboflavin intake and all-cause mortality of patients with chronic kidney disease (CKD). The aim of this study is to explore whether riboflavin intake is associated with the risk of all-cause mortality of patients with CKD.
Methods
This was a retrospective cohort study, and data extraction was performed in the National Health and Nutrition Examination Survey (NHANES). Cox regression analysis was used to calculate the hazard ratio (HR) and 95% confidence interval (CI) to assess the association between riboflavin intake and the risk of all-cause mortality. Subgroup analysis was carried out according to gender, CKD stage, hypertension, hyperlipidemia, and cardiovascular disease (CVD).
Results
A total of 3,750 patients were finally included for analysis. After potential confounders, lower intake of riboflavin was associated with the higher risk of all-cause mortality (Q1: HR = 1.33, 95% CI: 1.05–1.69). The similar association was also found in patients at mild/moderate stage (HR = 1.32, 95% CI: 1.05–1.66), in female (HR = 1.35, 95% CI: 1.01–1.81), with hypertension (HR = 1.37, 95% CI: 1.07–1.75), CVD (HR = 1.48, 95% CI: 1.08–2.03), and dyslipidemia (HR = 1.29, 95% CI: 1.01–1.66).
Conclusions
This study found the association between low riboflavin intake and high risk of all-cause mortality, indicating a potential beneficial role of riboflavin in CKD patients.
Estimates of lithium mass yields from produced water sourced from the Devonian-aged Marcellus Shale
Authors: Mackey Justin , Bain Daniel J. , Lackey Greg , Gardiner James , Gulliver Djuna , Kutchko Barbara
Published: January 2024

Decarbonatization initiatives have rapidly increased the demand for lithium. This study uses public waste compliance reports and Monte Carlo approaches to estimate total lithium mass yields from produced water (PW) sourced from the Marcellus Shale in Pennsylvania (PA). Statewide, Marcellus Shale PW has substantial extractable lithium, however, concentrations, production volumes and extraction efficiencies vary between the northeast and southwest operating zones. Annual estimates suggest statewide lithium mass yields of approximately 1,159 (95% CI: 1139–1178) metric tons per year. Production decline curve analysis on PW volumes reveal cumulative volumetric disparities between the northeast (median = 2.89 X 107 L/10-yr) and southwest (median = 5.56 x 107 L/10-yr) regions of the state, influencing estimates for ultimate lithium yields from wells in southwest [2.90 (95% CI: 2.80–2.99) mt/ 10-yr] and northeast [1.96 (CI: 1.86–2.07) mt/10-yr] PA. Moreover, Mg/Li mass ratios vary regionally, where NE PA are low Mg/Li fluids, having a median Mg/Li mass ratio of 5.39 (IQR, 2.66–7.26) and SW PA PW is higher with a median Mg/Li mass ratio of 17.8 (IQR, 14.3–20.7). These estimates indicate lithium mass yields from Marcellus PW are substantial, though regional variability in chemistry and production may impact recovery efficiencies.
Protein Features Fusion using Attributed Network Embedding for Predicting Protein-Protein Interaction
Authors: Cao Mei-Yuan , Zainudin Suhaila , Daud Kauthar Mohd
Published: January 2024

Background: Protein-protein interactions (PPIs) hold significant importance in biology, with precise PPI prediction as a pivotal factor in comprehending cellular processes and facilitating drug design. However, experimental determination of PPIs is laborious, time-consuming, and often constrained by technical limitations.Methods:We introduce a novel methodology, called FFANE, amalgamates PPI networks and protein sequence data to enhance the precision of protein interactions predictions. A Gaussian kernel similarity matrix is initially established by leveraging protein structural and functional resemblances. Concurrently, protein sequence similarities are gauged using the Levenshtein distance, enabling the capture of diverse protein attributes. Subsequently, these two feature matrices are merged by employing weighted fusion to achieve an organic amalgamation of structural and sequence details. To gain a more profound understanding of the amalgamated features, a Stacked Autoencoder (SAE) is employed for encoding learning, thereby yielding more representative feature representations. Ultimately, machine-learning methodologies use harnessed features to predict protein-protein interactions.Results:When employing 5-fold cross-validation experiments, our proposed method achieved average accuracies of 94.28%, 97.69% and 84.05% in terms of Saccharomyces cerevisiae, Homo sapiens and Helicobacter pylori datasets, respectively.Conclusion:Experimental findings across various authentic datasets validate the efficacy and superiority of this approach, underscoring its potential value in bioinformatics.
Support preferences among women with and without postpartum depression and anxiety disorder
Authors: Zieß Vanessa , Seefeld Lara , Mojahed Amera , Martini Julia , Asselmann Eva , Schellong Julia , Garthus-Niegel Susan
Published: January 2024

Background Some women struggle with mental health problems such as postpartum depression (PPD) or postpartum anxiety disorder (PAD) after giving birth. This can have a negative impact on the new mother, the infant, and the whole family. However, many women experiencing PPD and/or PAD go unrecognized and untreated. Since appropriate support is essential, efforts should be made to facilitate women’s help-seeking behavior. The purpose of this study was to improve the mental health of postpartum women by understanding their specific support preferences. To this end, the preferences for counseling and treatment services, as well as the service delivery mode among women with PPD, PAD, comorbid PPD and PAD, and women with neither PPD nor PAD were examined. Methods In the cross-sectional study INVITE, mothers (n = 2,031) were interviewed via telephone about three to four months after birth. PPD was assessed using the Edinburgh Postnatal Depression Scale (EPDS), PAD was assessed using the anxiety scale of the Symptom-Checklist-90-Revised (SCL-90-R), and preferences for services and delivery modes were assessed using self-generated questionnaires. Analyses of variance were performed to examine differences between the symptom groups. Results All women preferred the support of(family) midwivesandfamily, friends, or colleaguesand to talk to someonein person. Analyses of variance showed that, overall, women with PPD preferred all services less than women with neither PPD nor PAD. Furthermore, women with PPD preferred psychotherapeutic services (e.g.,inpatient clinicandoutpatient clinic/treatment) less, and women with comorbid PPD and PAD preferred professional and personal confidants (e.g.,midwifeandwomen in the same situation) less than all other women. Women did not differ in their preferences for service delivery mode. Conclusions This study provides unique insight into postpartum women’s preferences for various services and delivery modes. Results showed that women differ in their preferences for services depending on their symptoms. This should be considered when making referrals, and postpartum support should be better tailored to mothers' wishes and needs to improve help-seeking behavior and ultimately postpartum mental health.
A deep learning algorithm for KOL segmentation on social media videos
Authors: Yang Cheng , Zheng Fucheng , Al-Hamid Duaa Zuhair , Chong Peter han Joo , Lam Patrick
Published: January 2024

Nowadays, there is high commercial demand in advertising for KOL (Key Opinion Leader) to advertise commercial products in their social media videos. One effective technique is the product replacement which places the products virtually in the videos. However, one of the challenges of placing the products virtually is the KOL segmentation. Because KOLs often hold products in front of them, which requires the segmentation to segment not only human but also different products. This paper introduces the state-of-the-art deep learning method, namely RSUDISNet, for KOL segmentation on social media video. The proposed deep convolutional neural network (CNN) can segment both KOL and different products which block the KOLs. The proposed technique integrates two CNN technologies. One is the matting objective decomposition network (MODNet), which segments KOLs well but not the products blocking the KOLs. The other one is the two-level nested U-structure network (U2Net) based on salient object detection method to segment the objects well, but not the KOL. The key technique of U2Net is the residual U-block (RSU), which can build neural network architecture deeper, while saving computing. This research employs the RSU block to embed the MODNet to overcome the problem of KOL segmentation from U2Net. Since both MODNet and U2Net are lightweights, the combined network can be used for real-time scenario. After that, the intermediate supervision (IS) training strategy is utilized to overcome the overfitting, which increases the accuracy to a higher level. The experimental results show that our proposed method outperforms the MODNet and U2Net.
Pan-cancer landscape analysis of NOP58 and its oncogenic driving role in lung adenocarcinoma
Authors: Qian Shushu , Liu huafeng , Zhang Min , Zhang Li , Dai yunlan , Ye xiangming , Wen Wanshun , Cheng Ruidong
Published: January 2024

Even with improvements in treatment in recent years, lung adenocarcinoma (LUAD) patients still face poor prognoses. In this study, we elucidated the possible activities of NOP58 ribonucleoprotein in pan-cancer and validated its oncogenic significance in LUAD using bioinformatics and in vitro functional tests. NOP58 was shown to be overexpressed in several kinds of tumors. It had great precision for predicting 20 distinct cancer types using receiver operating characteristic curve (ROC) as well as significant connections with the prognoses in particular cancers. NOP58 was correlated substantially with the TNM stage, pathologic stage, smoking status, and effectiveness endpoints in LUAD when we analyzed its association with clinical characteristics in LUAD. Elevated NOP58 expression was shown as connected with Th2 cell infiltration while also negatively linked with infiltrating other immune cells, such as CD8 T, cytotoxic, and Th1. By inhibiting NOP58 within the LUAD cells, we found a decrease in cells’ capability to proliferate, migrate, and invade. The tissue microarray study indicated that there was a greater expression of NOP58 in the tumor tissues of LUAD than in paracarcinoma tissues. Our findings revealed that NOP58 could be an outstanding bio-index for pan-cancer diagnosis and prognosis and an independent prognostic risk factor of LUAD.
Association between nontraditional lipid parameters and cardiovascular outcomes in patients undergoing percutaneous coronary intervention: a retrospective study
Authors: Wang Baiqiang , Mei Zeyuan , Li Yunyi , Dai Honggang , Meng Xiao , An Guipeng
Published: January 2024

Background Nontraditional lipid parameters, such as the atherogenic index of plasma (AIP), triglycerides to high-density lipoprotein cholesterol ratio (TG/HDL ratio), Castelli Risk Index I (CRI-I), Castelli Risk Index II (CRI-II), fasting blood glucose to high-density lipoprotein cholesterol ratio (GHR), and lipoprotein combine index (LCI), have been implicated in cardiovascular disease. This study aims to explore the correlation between nontraditional lipid parameters and cardiovascular outcomes in patients with coronary artery disease (CAD) undergoing percutaneous coronary intervention (PCI), while also evaluating their predictive capabilities. Methods The study included 2533 consecutive patients who underwent PCI. Data from 2006 patients were analyzed using multivariate logistic models to analyze the association between nontraditional lipid parameters and major adverse cardiac and cerebrovascular events (MACCEs). Results Over a 34-month follow-up, 338 patients (16.8%) experienced MACCEs. The multivariate logistic regression analysis revealed a significant association, showing that a 1.0-SD increment in CRI-I (OR: 1.15, 95% CI: 1.03–1.30), CRI-II (OR: 1.20, 95% CI: 1.07–1.35), and LCI (OR: 1.19, 95% CI: 1.06–1.34) was significantly related to MACCEs in the overall population (all P < 0.01). Subgroup analyses revealed significant interactions between AIP, TG/HDL ratio, and GHR with sex subgroups. In female patients, after adjusting for other risk factors, AIP (OR: 1.26, 95% CI: 1.00-1.60), TG/HDL ratio (OR: 1.34, 95% CI: 1.03–1.74), and GHR (OR: 1.25, 95% CI: 1.00-1.56) were significantly associated with MACCEs (all P < 0.05). Multivariable-adjusted RCS curves illustrated a linear correlation between CRI-I, CRI-II, and LCI with MACCEs, and a nonlinear relationship between GHR and MACCEs in overall population. When CRI-II is added to the model with fully adjusting variables, its predictive performance may be enhanced (NRI = 0.158, P = 0.009; IDI = 0.005, P = 0.017). Conclusion There was a significant correlation between nontraditional lipid parameters and the risk of MACCEs in patients undergoing PCI. The CRI-II has the potential to enhance the predictive performance of traditional risk models and emerges as the most valuable among nontraditional lipid parameters.
WITHDRAWN: Spirulina C-phycocyanin: extraction, purification, stabilization, and inhibitory potential of key enzymes rRelated to pancreas inflammation, carbohydrate digestion, and glucose metabolism
Authors: Saїdi Saber Abdelkader , Al-Shaikh Turki M. , Hamden Khaled
Published: January 2024

Background
in recent years, it has become necessary to use natural food colorants to protect against different diseases and disorders. The present study aimed to purify, evaluate the stability, and investigate the effect of purified Spirulina C-Phycocyanin (CPC) on digestive and metabolic enzymes linked to hyperglycemia.
Methods
the purification of CPC was performed using column chromatography to isolate compounds and reversed-phase high performance liquid chromatography combined with diode array detector (DAD) and ultraviolet spectroscopy (DAD-HPLC-UV) and infrared Fourier transform (FTIR).
Results
the findings of this study indicate that CPC is stable at temperatures below 45°C and at a pH range of 5 to 7, as well as during storage at 4°C. In diabetic rats, the ingestion of CPC by diabetic rats suppressed key enzymes related to inflammation in pancreas, such as 5-Lipoxygenase (5-LO), hyaluronidase (HAase), myeloperoxidase (MPO), and NADPH oxidase (NOX2 activities) by 48, 41, 75, and 47%, respectively. Additionally, it reduced the pancreas thiobarbituric acid reactive substance rates (TBARS) by 59%, and stimulated the level of nitric oxide (NO) by approximately 164%. Moreover, CPC powerfully suppressed intestinal lipase, α-amylase, maltase, and sucrose activities, and significantly decreased glycosylated hemoglobin (HbA1c). Furthermore, CPC ingestion by diabetic rats suppressed glycogen phosphorylase (GP), stimulated Glycogen synthase (GS) activities, and regulated glycogen content in the liver of diabetic rats. In addition, CPC supplementation to diabetic rats modulated hepatic key enzymes of carbohydrate metabolism in the liver, such as hexokinase (HK), glucose-6-phosphate dehydrogenase (G6PD), glucose-6-phosphatase (G6P), and fructose-1,6-bisphosphatase (FBP), as well as average food and water intake (AFI and AWI), resulting in a decrease in blood glucose level by 56% compared to untreated diabetic rats.
Conclusion
Overall, the results of this research showed that CPC can be used as a functional food coloring as well as a compound to prevent various pathologies such as ulcers, oxidative stress, inflammation and metabolic diseases.
An Intelligent Collision Avoidance System Utilizing YOLOv8-Based Deep Learning
Authors: Farhat WAJDI , BenOthmen Souha , Rhaiem Olfa Ben , Faiedh Hassene , Souani Chokri
Published: January 2024

The authors have requested that this preprint be removed from Research Square.
Forced Vibration Analysis of Dispersed Nano-CNT FRP Hybrid Composite Plate Using Refined Plate Theory
Authors: K Lalitha Bhavani , K Dileep Kumar
Published: January 2024

In today's applications, such as aerospace, automotive, spacecraft, boats, sporting goods, and civil infrastructure, fiber reinforced composites, or FRP, are crucial. When synthetic fibers are manufactured, they may explode and release harmful substances that irritate the skin, eyes, and respiratory tract, among other things. Because natural fibers are biodegradable, they are used to counteract the effects of synthetic fibers. This study uses spider silk and flax fiber reinforced polymer composites, and to improve the mechanical properties, a small amount of carbon nanotubes (CNT) is added to the matrix and layer-wise hybridization is performed. The Mori-Tanaka method is used to determine the properties of CNT epoxy, and the Rule of Mixtures is used to determine the elastic properties of the lamina. To get the best structural design with the best performance characteristics, a thorough analysis of the composite structure's vibration behavior with various parameters is crucial. The vibration response of laminated hybrid composite plates under various boundary and loading conditions is studied using the refined plate theory, also known as the refined shear deformation theory (RPT). Hamilton's principle establishes the governing equations, and the Galerkin solution yields the solution. The influence of loading conditions, frequency ratio, CNT percentage variation, and boundary conditions is studied parametrically.
CNN based multi-output regression model to estimate infrastructural surface crack dimensions adopting a generalized patch size and FWHM-based width quantification
Authors: Debroy Sudipta , Sil Arjun
Published: January 2024

To cater the need for real-time crack monitoring of infrastructural facilities, a CNNRegression model is proposed to directly estimate the crack properties from patches. RGB crack images and their corresponding masks obtained from a public dataset are cropped into patches of 256 square-pixels that are classified with a pre-trained Deep Convolution Neural Network, the True Positives are segmented and crack properties extracted using two different methods. A statistical test has been performed for comparison and a database prepared with the more suitable method which is then fed into the neural network model to predict crack-length, crack-width and widthuncertainty directly. The proposed model has been tested on crack patches collected from different locations. Huber Loss has been used to ensure robustness of the proposed model selected from a set of 288 different variations of it. In spite of using a limited sized data set, quite satisfactory results have been achieved.