bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Self-Reflection Using Reflective Journal on Oxytocin Massage Skills in Diploma Three Midwifery Students
Authors: Arbie Rina Sulisthia , Budu Budu , Ahmad Mardiana , Bukhari Agussalim , Alasiry Ema , Usman Andi Nilawati
Published: May 2024

Midwifery is a profession based on women-centered and evidence-based care through the provision of mutually respectful professional relationships and partnerships. To train students' skills, repeated learning is needed, learning can be sourced from experiences such as doing self-reflection by keeping a reflective journal. This research aims to analyze the effect of applying self-reflection using a reflective journal on oxytocin massage skills. This research is an experimental research using a one-group pretest-posttest group design approach, taking samples using a simple random sampling technique. The research population was all level III students in a bivariate analysis using the Friedman ANOVA test. The results showed that the pretest mean value was 59.28 increasing to 79.50 in the first posttest and 83.38 in the second posttest with a p-value <0.05, which means that there is an effect of applying reflective journals using reflective journals on oxytocin massage skills. Having students write reflective journals is a great way for them to learn new concepts. This approach is also useful for lecturers to get feedback on the concepts being studied by students. The use of reflective journals will guide students to analyze what they have and do not know about the material being studied and how to overcome the obstacles encountered so that learning goals are achieved and foster independent learning in students.
Difference of Cycle Threshold Value, Oxygen Saturation and D-dimer to COVID-19 Vaccination
Authors: Redhono Harioputro Dhani , Dasa Ramadhan Arsyi , Nurhayatun Evi , Budi Susilo Satrio , Agung Prabowo Nurhasan
Published: May 2024

Many factors can affect the prognosis of COVID-19 patients, and Cycle Threshold value can be used to estimate the amount of virus in the body. Oxygen saturation and D-dimer are important components in determining the severity. This study aims to analyze the difference of CT value, oxygen saturation, D-dimer, and degree of severity on vaccination state. This study is the observational analytic study of patients admitted to the isolation ward of a referral hospital in Surakarta, Indonesia. The analysis covered assessing the normality of the data, the Kruskal-Wallis correlation test, and ANOVA to assess the differences between variables. A total of 154 patients with, 65.6% of them did not participate in the full vaccination program. The results of the analysis showed a significant difference between the D-dimer and the degree of severity with a p-value of < 0.05, while the CT value and oxygen saturation had no significant difference with the vaccination state. Vaccination showed a significant difference with D-dimer and the degree of severity of COVID-19 infection, so giving a complete vaccine can reduce the severity of COVID-19 patients, and we recommended to be able to complete the vaccine for the whole community.
The Effect of Dayak Onion Extract (Eleutherine palmifolia (L.) Merr) on Swimming Time and Oxidative Stress Levels in Mice with the Forced Swimming Test Model
Authors: Ramadhani Aulia , Doewes Muchsin , Listyawati Shanti
Published: May 2024

Excessive physical exercise can increase the occurrence of oxidative stress, which is characterized by cell damage caused by free radicals. Antioxidants found in Dayak Onion such as flavonoids, saponins, tannins, and vitamin C can be used as alternative ingredients to neutralize free radicals. The purpose of this study was to determine the effect of dose and duration of administration of Dayak onion extract on malondialdehyde (MDA) levels in a rat model of the forced gum test, extraction of Dayak onions using 96% ethanol. The type if research is Randomized Pre and Post Test Control Group Design. Male Sprague Dawley rats aged 2 months (weighing 150-200g) were divided into 5 groups: K- (control group, rats not given Dayak Onion extract but underwent forced swimming test), K+ (rats given xanthine and forced swimming test), P1 (rats given Dayak Onion extract at a dose of 50 mg/200 rats body weight/day), P2 (rats given Dayak Onion extract at a dose of 100 mg/200 rats body weight/day), P3 (rats given Dayak Onion extract at a dose of 200 mg/200 rats body weight/day). Dayak Onion extract was administered for 21 days with for 21 days with forced swimming test treatment, and changes in MDA levels were observed. The results showed that the administration of Dayak onion extract at a dose of 50 mg/200 rats/day, 100 mg/200 rats/day, and 200 mg/200 rats/day had an effect on preventing the increase in MDA, but at a dose of 200 mg/200 rats mice/day is the optimal dose. The conclusion is administration of Dayak Onion (Eleutherine palmifolia (L.) Merr) significantly decreased MDA levels in male Sprague Dawley rats with forced swimming test model.
Father's Role in Exclusive Breastfeeding in Developing Countries: Scoping Review
Authors: Sari Siti Nurul Fadhilah , Astuti Andari Wuri
Published: May 2024

The father is the closest person after the baby's mother, who plays a role in exclusive breastfeeding. The interventions of dads attempt to improve breastfeeding knowledge, positive attitudes, and fathers' engagement in providing practical, physical, and emotional support to mothers, which can improve breastfeeding behaviors. The purpose of this study is to map current information about the role of fathers in exclusive breastfeeding in developing countries by including relevant sources of evidence from each article that has been found. The research method uses a Scoping review with the Arkey and O'Malley approach. It consists of 5 steps, namely: (1) identifying each scoping review question, (2) identifying relevant articles, (3) selecting articles, (4) charting data (5) compiling, summarizing and reporting results. Article search uses three databases, PubMed, ScienceDirect and Wiley, published between 2018-2022. Keywords used in the search process are (Father Role* OR Partner Role*) AND (Exclusive Breastfeeding* OR Lactation* OR Breast Milk*).  There are 14 articles found, including several developing countries from various continents, nine articles from Thailand, Vietnam, Iran, India, Philippines, and China from the Asian continent, and five articles from the countries Tanzania, Ethiopia, and South Africa from the African continent. The results of the study show that the father's role in exclusive breastfeeding in developing countries is to provide emotional support, practical support and informational support so that mothers have a greater chance of producing breast milk more effectively. Husband’s support towards breastfeeding mothers positively affects the mother's psychological condition and success, especially in exclusive breastfeeding. The next author is expected to help make the policy if health workers are required, especially the policy for husbands to be involved in giving counseling while accompanying their wives in health facilities.
The Effect of Visual Media Education in the Management Therapy on the Level of Knowledge of Patients Diabetes Mellitus with Comorbid
Authors: Utami Primanitha Ria , Devi Ristian Octavia
Published: May 2024

Diabetes Mellitus (DM) is a group of metabolic diseases characterized by hyperglycemia that occurs due to abnormalities in insulin secretion, insulin action or both and is often accompanied by increased blood pressure. One of the drug-related problems that are frequently encountered is patient non-compliance in taking drugs. This can occur due to a lack of knowledge about managing pharmacological and non-pharmacological therapies, making therapeutic outcomes difficult. This study aims to determine the effect of visual media education on managing pharmacological and non-pharmacological treatment on the level of knowledge of type 2 DM patients with comorbid hypertension. This type of research is quasi-experimental, with pretest and posttest designs without a control group design. The research sample is the age group that has the age of 18-68 years, as many as 123 people using Purposive Sampling. The results showed that the level of knowledge before being given education was in a good category (4.81%), sufficient (42.29%), and less (52.90%). After being given education visual media, there was an increase in knowledge results for the good (74.25%), sufficient (18.14%) and poor (7.61%) categories. The results of the Wilcoxon test analysis obtained a p-value (0.000) < (0.005), which means that there is an effect of visual media education on the level of knowledge of type 2 DM patients with comorbid hypertension. Through the results of this study, it is hoped that pharmacists can provide ongoing educational counselling to chronic disease patients receiving polypharmacy to prevent drug-related problems.
Evaluating the Usability of the AKUDia Mobile App for Blood Sugar Monitoring: A Feasibility Study
Authors: Badriah Siti , Bahtiar Yanyan , Setiawan Henri
Published: May 2024

A variety of ultra-invasive portable blood sugar test kits have been available on the market; these kits require drawing blood from capillaries, which can still be painful and uncomfortable and even enhance the risk of infection. To develop a non-invasive blood sugar meter that is painless and comfortable to use, innovation is required. AKUDia, a mobile application for monitoring blood sugar, was developed as a smart wearable device to help older adults with diabetes stay healthy. This study aimed to measure the usability of the AKUDia application using a usage questionnaire. In terms of a feasibility study, this was quantitative. USE Questionnaire contains a list of questions encompassing 30 questions divided into four dimensions: Usefulness, Ease to use, Ease of learning, and Satisfaction. 50 respondents were recruited for this study, meeting the inclusion criteria of DM patients who had completed a week-long training program on using the AKUDia application. Samples were selected by simple random sampling, and descriptive and univariate data analyses were performed. The AKUDia feasibility test results demonstrated a usability value of 83%, which was classified as very feasible; an ease of use value of 74 percent, which was classified as feasible; an ease of learning value of 83%, which was classified as very feasible; and a satisfaction aspect of 71% at the feasible level. The average usability value of the four categories (usability, ease of use, ease of learning, and satisfaction), which was obtained at 78 percent, indicates that the AKUDia application's usability is at a practicable level. The usability of the AKUDia application is feasible. Governments should support the use and implementation of this innovation in addition to healthcare professionals like doctors and nurses. Information technology systems have the potential to serve as an instrument for illness prevention, treatment, and rehabilitation in addition to promoting health. Future studies should be enhanced to investigate, through experimental research, how the AKUDia application supports nursing care and health management for individuals with diabetes mellitus and the general population.
Effectiveness of Aloe Vera-Based Topical Therapy Products on Breastfeeding Mothers with Milk Scratches in Hamparan Perak Village
Authors: Arma Nuriah , Harahap Novy Ramini , Wulan Mayang , Firnanda Yuka Okta
Published: May 2024

In Indonesia, a study revealed that approximately 86.4% of breastfeeding mothers encounter nipple issues such as blisters, dryness, and pain. The World Health Organization (WHO) emphasizes that chafed nipples contribute to substantial pain, discomfort, and diminished milk production among nursing mothers, thereby posing a hindrance to exclusive breastfeeding initiatives. This study aims to investigate the effectiveness of an aloe vera-based topical therapy product in reducing nipple chafing in breastfeeding mothers in Hamparan Perak District. Conducted as an experimental study with a pre-test and post-test control group design, the research transpired in Hamparan Perak village. The study enlisted breastfeeding mothers experiencing sore nipples, with 20 individuals in the intervention group receiving aloe vera-based topical therapy in gel form, and 20 individuals in the control group receiving a placebo. The assessment of effectiveness centered on measuring blister occurrence and nipple pain scores both before and after the intervention, employing the Mann-Whitney test for data analysis. Bivariate analysis utilizing the Mann-Whitney U-test yielded a significant P-value of 0.001. Consequently, it can be inferred that aloe vera gel demonstrably influences nipple pain, with aloe vera gel proving to be 5,537 times more effective in pain reduction. Future research could incorporate objective measures, such as clinical assessments or laboratory analyses, to validate the reported outcomes.
Pengaruh Kemampuan Pemahaman Konsep Matematika Mahasiswa melalui Metode Pembelajaran Learning Starts with a Question
Authors: Fitri Puspa Sari Eka
Published: May 2024

Penelitian ini bertujuan untuk mengetahui adakah pengaruh kemampuan pemahaman konsep matematika mahasiswa setelah diterapkannya metode pembelajaran Learning Starts with a Question. Subjek penelitian adalah mahasiswa semester 5 pendidikan matematika Universitas PGRI Palembang tahun ajaran 2016/2017 yang berjumlah 40 orang. Metode penelitian yang digunakan yaitu eksperimen (Posttes-only control design). Teknik pengumpulan data yang digunakan yaitu tes. Hasil penelitian yang didapat bahwa ada pengaruh metode pembelajaran Learning Starts with a Question terhadap kemampuan pemahaman konsep matematika mahasiswa.
Meningkatkan Kemampuan Pemecahan Masalah dan Komunikasi Matematik melalui Pendekatan Problem Posing dalam Pembelajaran Matematika di SMA
Authors: Sofyan Deddy , Sukandar Madio Sukanto
Published: May 2024

Tujuan penelitian ini adalah untuk meningkatkan kemampuan siswa SMA dalam pemecahan masalah dan komunikasi matematik melalui pendekatan problem posing dalam pembelajaran matematika. Metode penelitian yang digunakan adalah metode kuasi eksperimen. Populasi penelitian ini adalah siswa di salah satu SMA Negeri di Kabupaten Garut. Sampel penelitian dipilih secara acak berdasarkan kelas, sampelnya adalah kelas XII IPA 1 yang mendapat pembelajaran menggunakan pendekatan problem posing dan siswa kelas XII IPA 3 yang mendapat pembelajaran konvensional. Simpulan hasil penelitian ini adalah bahwa dalam pembelajaran matematika di SMA: 1. Kemampuan pemecahan masalah matematik siswa yang mendapatkan pendekatan problem posing lebih baik dibandingkan dengan konvensional, 2. Tidak terdapat perbedaan kemampuan komunikasi matematik antara siswa yang mendapatkan pendekatan problem posing dengan konvensional, 3. Tidak terdapat kaitan yang signifikan antara kemampuan pemecahan masalah matematik dengan kemampuan komunikasi matematik pada siswa yang mendapatkan pendekatan problem posing.
Hubungan Kemampuan Awal terhadap Kemampuan Berpikir Kritis Matematika pada Siswa Kelas VII SMP Pesantren Immim Putri Minasatene
Authors: Razak Firdha
Published: May 2024

Jenis penelitian ini adalah penelitian Ex-post facto yang bertujuan untuk mengetahui ada tidaknya hubungan kemampuan awal terhadap kemampuan berpikir kritis matematika pada siswa kelas VII SMP Pesantren IMMIM Putri Minasatene. Populasi dalam penelitian ini adalah seluruh siswa kelas VII SMP Pesantren IMMIM Putri Minasatene dan sampel penelitian adalah siswa kelas VII.II yang ditentukan dengan teknik purposive sampling. Instrumen yang digunakan adalah tes kemampuan awal dan tes kemampuan berpikir kritis kemudian dianalisis dengan korelasi product moment dari pearson. Berdasarkan hasil analisis diperoleh nilai koefisien korelasi rxy = 0,748 dan nilai r =1, kemudian nilai sig. = 0,001. Dimana pada nilai tersebut berada pada interval koefisien 0,600 - 0,799 dengan tingkat hubungan yang kuat dan nilai r = 1 artinya korelasinya sangat kuat dengan arah yang positif. Kemudian nilai sig. = 0,000 sehingga nilai Sig. < 0,05 atau 0,001 < 0,05 maka ada korelasi yang signifikan berarti H0 ditolak dan H1 diterima yaitu ada hubungan antara kemampuan awal terhadap kemampuan berpikir kritis matematika pada siswa SMP Pesantren IMMIM Putri Minasatene.
Eksploitasi Kesalahan Konsep Teori Graf dalam Perkuliahan Matematika Diskrit Menggunakan Metode Game "Tantangan Berhadiah Point"
Authors: Mardiani Dian
Published: May 2024

Tujuan dari penelitian ini adalah untuk mengetahui kesalahan konsep teori graf apa saja yang dapat terjadi ketika game “tantangan berhadiah point” diterapkan dalam perkuliahan matematika diskrit dengan tema sejarah dan teori graf. Subjek penelitian dari penelitian ini adalah kelas 2B Prodi Pendidikan Matematika tahun ajaran 2016/2017 berjumlah 34 mahasiswa. Penelitian ini merupakan penelitian deskriptif. Hasil analisa data penelitian ini, ditemukan ada tujuh jenis kesalahan yang terjadi. Mahasiswa salah  mengingat dalam menulis nama tokoh sejarah atau nama tempat dalam sejarah graf sebanyak 68%, kemudian 35% mahasiswa salah dalam menulis simbol derajat dari suatu simpul, 18% salah dalam memahami konsep derajat suatu simpul pada graf, 18% salah dalam memahami konsep sisi dan simpul pada graf, 15% mahasiswa salah dalam proses berhitung, 3% salah dalam mengingat informasi, 24% mahasiswa  salah memahami konsep derajat dari graf yang mengandung loop. Dari survey diperoleh 88% mahasiswa memberikan pendapat positif terhadap game ini, walaupun hanya 9% yang berhasil menjawab sempurna semua soal tes. Kesimpulannya game ini tidak menjamin efektifitas perkuliahan namun memberikan suasana belajar yang lebih positif.
The purpose of this study is to find out mistakes in learning Graph theory while applying the concept with games “Challenge made point” in Discrete Math lecturing with theme: Story and Graph Theory. Subjects of this study are 34 students of Math Program class 2B year 2017-2018. This descriptive study found that there are seven mistakes occurred. Some students were false to remember in writing the name of Math expert or the name of history place of Graph theory about 68%, meanwhile 35% students were false to write symbol degree concept from a knot of Graph, 15% students were false in counting process, 3% students were false to remember information, and 24 % students were false to understand degree concept of Graph had loop. Meanwhile, from survey, it found that 88% students gave positive response toward this game, although only 9% student’s success to answer the test perfectly. The main point is, this game didn’t ensure effective lecturing, but it made more positive atmosphere while teaching and learning process.
Research trends and perspective of low-intensity pulsed ultrasound in orthopedic rehabilitation treatment based on Web of Science: A bibliometric analysis
Authors: Zhang Bin , Zeng Jiahao , Zhang Jiayi , Song Keyan , Kuang Liang , Wu Xiangbo , Zhao Guang , Shang Huijuan , Ni Zhenhong , Chen Lin
Published: May 2024

BACKGROUND: Ultrasound has a long history as a diagnostic and therapeutic tool. Low-intensity pulsed ultrasound (LIPUS), whose intensity is below 300 mW/cm2, has been widely used in orthopedic rehabilitation treatment. However, the detailed bioeffects and underlying mechanisms of LIPUS treatment need to be explored. OBJECTIVE: To make a comprehensive view of the field, bibliometric and visualization analysis was used to reveal the global research trends of LIPUS in orthopedics and rehabilitation treatment between 1994 and 2023. METHODS: All literature data on LIPUS were retrieved from the Web of Science Core Collection database. VOSviewer and CiteSpace were applied for the bibliometric and visualization analysis. RESULTS: A total of 760 publications were included. The distribution of publications generally showed an unstable rising trend. China had the highest number of publications (28.0%), and Chong Qing Medical University was the organization with the highest number of publications (5.8%). Ultrasound in Medicine and Biology had the highest number of publications (8.8%), while BMJ-British Medical Journal had the highest impact factor among the retrieved journals. Ling Qin from the Chinese University of Hong Kong was the most active researcher. Our overlay visualization map showed that the keywords such as pain, knee osteoarthritis, apoptosis, chondrocytes, cartilage, and autophagy, which link to osteoarthritis, have becoming the new research trends and hotspots. CONCLUSION: LIPUS is a popular and increasingly important area of orthopedic rehabilitation, and collaboration of authors from different countries should be further strengthened. Predictably, clinical application of LIPUS on chronic inflammation-related diseases and regenerative medicine, and in-depth biological mechanisms are the orientations of LIPUS in orthopedic rehabilitation treatment.
BIPOOLNET: An advanced UNet architecture for enhanced lane detection in autonomous vehicles
Authors: P Santhiya , Jebadurai Immanuel JohnRaja , Paulraj Getzi Jeba Leelipushpam , A Jenefa
Published: May 2024

In the rapidly evolving landscape of autonomous vehicle technology, the imperative to bolster safety within smart urban ecosystems has never been more critical. This endeavor requires the deployment of advanced detection systems capable of navigating the intricacies of pedestrian, near-vehicle, and lane detection challenges, with a particular focus on the nuanced requirements of curved lane navigation – a domain where traditional AI models exhibit notable deficiencies. This paper introduces BIPOOLNET, an innovative encoder-decoder neural architecture, ingeniously augmented with a feature pyramid to facilitate the precise delineation of curved lane geometries. BIPOOLNET integrates max pooling and average pooling to extract critical features and mitigate the complexity of the feature map, redefining the benchmarks for lane detection technology. Rigorous evaluation using the TuSimple dataset underscores BIPOOLNET’s exemplary performance, evidenced by an unprecedented accuracy rate of 98.45%, an F1-score of 98.17%, and notably minimal false positive (1.84%) and false negative (1.09%) rates. These findings not only affirm BIPOOLNET’s supremacy over extant models but also signal a paradigm shift in enhancing the safety and navigational precision of autonomous vehicles, offering a scalable, robust solution to the multifaceted challenges posed by real-world driving dynamics.
When line meets agile in public service organizations: Exploring the role of felt accountability amongst line managers
Authors: Yadav Yashwant Singh
Published: May 2024

Despite citizen calls for agile government, public service organizations often default to hierarchy and adopt dual structure organization designs combining agile and non-agile units. However, ensuring effective collaboration and avoiding accountability challenges at the interface of line and agile units remains a vexing issue. Although accountability is implicitly assumed in agile organizing, it is not readily manifested or experienced. Through this interpretive case study of a public service organization in the Nordics, we examine through the lens of felt accountability, the reaction and roles of line managers to emergent accountability challenges precipitated by parallel maintenance of agile and non-agile unit combinations.
Simplifying Alzheimer’s Disease Monitoring: A Novel Machine-Learning Approach to Estimate the Clinical Dementia Rating Sum of Box Changes Using the Mini-Mental State Examination and Functional Activities Questionnaire
Authors: Sato Kenichiro , Niimi Yoshiki , Ihara Ryoko , Suzuki Kazushi , Iwata Atsushi , Iwatsubo Takeshi ,   the Alzheimer’s Disease Neuroimaging Initiative,   the Japanese Alzheimer’s Disease Neuroimaging Initiative
Published: May 2024

Background:

Primary outcome measure in the clinical trials of disease modifying therapy (DMT) drugs for Alzheimer’s disease (AD) has often been evaluated by Clinical Dementia Rating sum of boxes (CDRSB). However, CDR testing requires specialized training and 30–50 minutes to complete, not being suitable for daily clinical practice.

Objective:

Herein, we proposed a machine-learning method to estimate CDRSB changes using simpler cognitive/functional batteries (Mini-Mental State Examination [MMSE] and Functional Activities Questionnaire [FAQ]), to replace CDR testing.

Methods:

Baseline data from 944 ADNI and 171 J-ADNI amyloid-positive participants were used to build machine-learning models predicting annualized CDRSB changes between visits, based on MMSE and FAQ scores. Prediction performance was evaluated with mean absolute error (MAE) and R2 comparing predicted to actual rmDeltaCDRSB/rmDeltayear. We further assessed whether decline in cognitive function surpassing particular thresholds could be identified using the predicted rmDeltaCDRSB/rmDeltayear.

RESULTS:

The models achieved the minimum required prediction errors (MAE < 1.0) and satisfactory prediction accuracy (R2>0.5) for mild cognitive impairment (MCI) patients for changes in CDRSB over periods of 18 months or longer. Predictions of annualized CDRSB progression>0.5, >1.0, or >1.5 demonstrated a consistent performance (i.e., Matthews correlation coefficient>0.5). These results were largely replicated in the J-ADNI case predictions.

CONCLUSIONS:

Our method effectively predicted MCI patient deterioration in the CDRSB based solely on MMSE and FAQ scores. It may aid routine practice for disease-modifying therapy drug efficacy evaluation, without necessitating CDR testing at every visit.
Prognostic Power? Do the Plasma Biomarkers, Neurofilament Light and Phospho-Tau 181, Improve Prediction of Progression to Alzheimer’s Disease Using a Machine Learning Approach in the ADNI Cohort?
Authors: McIntire Laura Beth
Published: May 2024

With the advent of therapeutics with potential to slow Alzheimer’s disease progression the necessity of understanding the diagnostic value of plasma biomarkers is critical, not only for understanding the etiology and progression of Alzheimer’s disease, but also for access and response to potentially disease modifying therapeutic agents. Multiple studies are currently assessing the sensitivity and specificity of plasma biomarkers in large cohorts such as the Alzheimer’s Disease Neuroimaging Initiative. This study uses machine learning to predict the progression from mild cognitive impairment using plasma biomarkers in conjunction with well-established cerebrospinal fluid and imaging biomarkers of disease progression.
A review on synthesis of coumarin derived Schiff’s base metal complexes and their control over E. coli bacterium
Authors: Sharma Ankita , Devi Sushma , Kumar Sunil
Published: May 2024

Nowadays, the dilemma of drug resistance to antibacterial strains is of huge concern. Among the bacteria, Escherchia coli ( E. coli) is the major pathogen, which is found in human and other animals. It is responsible for variety of severe diseases. A variety of commonly used antibiotics such as amoxicillin, gentamycin, etc and fluid replacement method are the suggested treatments for the infections caused by E. coli. In a study, it was established that the metal-based heterocyclic drugs demonstrated a different mode of action compared to the commonly used heterocyclic antibacterial drugs. Coumarin, an oxaheterocycle, is a privileged scaffold in medicinal chemistry. Metal complexes of coumarin-derived Schiff’s bases exhibit a broad range of pharmacological activities. Therefore, in the present review article, we have focused on the synthesis of metal complexes of coumarin derived Schiff’s bases as well as their respective Schiff’s base ligands and their antibacterial activities against the gram-negative bacterium E. coli.
Novel ionic liquid systems based on three-nitro phenoxide: Spectroscopic and electronic characterization using theoretical and experimental study
Authors: Esfahani Sahar , Akbari Jafar , Soleimani-Amiri Somayeh
Published: May 2024

After extensive computations, novel trinitro compounds, triethyl ammonium 2,4,6-trinitro phenoxide (TEA-TNP) and tetramethyl guanidinium 2,4,6-trinitro phenoxide (TMG-TNP), are designed, synthesized, and identified. The Geometrical parameters, electronic properties, and spectroscopic analysis have been investigated by comparison of theoretical and experimental methods. Spectrum features that include IR and Raman have been calculated, and 1H and 13C NMR spectra are compared to experimental data. Electronic analysis has been investigated through NLO, FMO, UV-Vis, NBO, and MEP calculations. B3LYP/6-311++G(d,p) is highly successful and dependable for predicting ionic liquid stability, electrical characteristics, and spectroscopy. Both TEA-TNP and TMG-TNP are introduced as suitable candidates for NLO material. TMG-TNP with greater nucleophilicity ( N) is a noncorrosive lubricant additive that reduces friction and wear for tribological performance.
A novel method for gas mixing and distribution in multi-chamber embryo incubators
Authors: Zeng Weijun , Xiao Donggen , Chen Ruitao , Lu Yao , Liang Weiguo , Sun Haixuan
Published: May 2024

BACKGROUND: High-quality control of the gas environment in incubators is crucial for in vitro embryo development, which requires high accuracy, fast recovery, and low gas consumption. OBJECTIVE: In this study, we propose a novel gas mixing and distribution system and method as an alternative solution for multi-chamber embryo incubators. METHODS: The system-based embryo incubator enables a controllable gas circulation process and a quantitative supply of CO2 and N2. To determine the optimal parameters for the mixing time and flow rate of the circulated gases, we conducted contrast experiments on the system-based incubator. To evaluate the performance of the gas system in the incubator, we conducted tests under four different initial conditions, simulating various practical application scenarios. Furthermore, we performed a mouse embryo assay to assess the system’s effectiveness. RESULTS: The results show that the system achieved a gas concentration accuracy of ± 0.2% (volume fraction) after stabilization, a minimum recovery time of 5 minutes, an average consumption of 8.9 L/d for N2 and 0.83 L/d for CO2 during routine operation, and a blastocyst rate exceeding 90% observed after 96 hours of culture in the incubator. CONCLUSION: The system and method demonstrate a significant advantage in terms of low gas consumption compared to existing incubators, while still maintaining high accuracy and fast recovery.
A novel approach for estimating initial sound level for speech reception threshold test
Authors: Lee Heonzoo , Park Rayoung , Kim Sejin , Cho Hyong-Ho , Won Yonggwan
Published: May 2024

BACKGROUND: The speech reception threshold (SRT), synonymous with the speech recognition threshold, denotes the minimum hearing level required for an individual to discern 50% of presented speech material. This threshold is measured independently in each ear with a repetitive up-down adjustment of stimulus level starting from the initial SRT value derived from pure tone thresholds (PTTs), measured via pure-tone audiometry (PTA). However, repetitive adjustments in the test contributes to increased fatigue for both patients and audiologists, compromising the reliability of the hearing tests. OBJECTIVE: Determining the first (initial) sound level closer to the finally determined SRT value, is important to reduce the number of repetitions. The existing method to determine the initial sound level is to average the PTTs called pure tone average (PTAv). METHODS: We propose a novel method using a machine learning approach to estimate a more optimal initial sound level for the SRT test. Specifically, a convolutional neural network with 1-dimensional filters (1D CNN) was implemented to predict a superior initial level than the conventional methods. RESULTS: Our approach produced a reduction of 37.92% in the difference between the initial stimulus level and the final SRT value. CONCLUSIONS: This outcome substantiates that our approach can reduce the repetitions for finding the final SRT, and, as the result, the hearing test time can be reduced.
Comparative analysis of supervised learning algorithms for prediction of cardiovascular diseases
Authors: Dou Yifeng , Liu Jiantao , Meng Wentao , Zhang Yingchao
Published: May 2024

BACKGROUND: With the advent of artificial intelligence technology, machine learning algorithms have been widely used in the area of disease prediction. OBJECTIVE: Cardiovascular disease (CVD) seriously jeopardizes human health worldwide, thereby needing the establishment of an effective CVD prediction model that can be of great significance for controlling the risk of the disease and safeguarding the physical and mental health of the population. METHODS: Considering the UCI heart disease dataset as an example, initially, a single machine learning prediction model was constructed. Subsequently, six methods such as Pearson, chi-squared, RFE and LightGBM were comprehensively used for the feature screening. On the basis of the base classifiers, Soft Voting fusion and Stacking fusion was carried out to build a prediction model for cardiovascular diseases, in order to realize an early warning and disease intervention for high-risk populations. To address the data imbalance problem, the SMOTE method was adopted to process the data set, and the prediction effect of the model was analyzed using multi-dimensional and multi-indicators. RESULTS: In the single classifier model, the MLP algorithm performed optimally on the preprocessed heart disease dataset. After feature selection, five features eliminated. The ENSEM_SV algorithm that combines the base classifiers to determine the prediction results by soft voting on the results of the classifiers achieved the optimal value on five metrics such as Accuracy, Jaccard_Score, Hamm_Loss, AUC, etc., and the AUC value reached 0.951. The RF, ET, GBDT, and LGB algorithms were employed in the first stage sub-model composed of base classifiers. The AB algorithm was selected as the second stage model, and the ensemble algorithm ENSEM_ST, obtained by Stacking fusion of the two stages exhibited the best performance on 7 indicators such as Accuracy, Sensitivity, F1_Score, Mathew_Corrcoef, etc., and the AUC reached 0.952. Furthermore, a comparison of the algorithms’ classification effects based on different training set occupancy was carried out. The results indicated that the prediction performance of both the fusion models was better than the single models, and the overall effect of ENSEM_ST fusion was stronger than the ENSEM_SV fusion. CONCLUSIONS: The fusion model established in this study improved the overall classification accuracy and stability of the model to a significant extent. It has a good application value in the predictive analysis of CVD diagnosis, and can provide a valuable reference in the disease diagnosis and intervention strategies.
Simulation and experimental study on rope driven artificial hand and driven motor
Authors: Guo Kai , Lu Jingxin , Yang Hongbo
Published: May 2024

BACKGROUND: Prosthetic hands have the potential to replace human hands. Using prosthetic hands can help patients with hand loss to complete the necessary daily living actions. OBJECTIVE: This paper studies the design of a bionic, compact, low-cost, and lightweight 3D printing humanoid hand. The five fingers are underactuated, with a total of 9 degrees of freedom. METHODS: In the design of an underactuated hand, it is a basic element composed of an actuator, spring, rope, and guide system. A single actuator is providing power for five fingers. And the dynamic simulation is carried out to calculate the motion trajectory effect. RESULTS: In this paper, the driving structure of the ultrasonic motor was designed, and the structural size of the ultrasonic motor vibrator was determined by modal and transient simulation analysis, which replace the traditional brake, realize the lightweight design of prosthetic hand, improve the motion accuracy and optimize the driving performance of prosthetic hand. CONCLUSIONS: By replacing traditional actuators with new types of actuators, lightweight design of prosthetic hands can be achieved, improving motion accuracy and optimizing the driving performance of prosthetic hands.
Regulatory role of BNP in the spinal center of rats with nonbacterial prostatitis
Authors: Yang Xiaorong , Hu Jieping , Chen Qiang , Yang Lin , Liu Yifu , Luo Longhua , Ma Ming , Xie Wenjie , Gong Binbin , Sun Ting , Tang Jiazhen , Liu Fang
Published: May 2024

BACKGROUND: A growing body of evidence has shown that activating spinal cord glial cells (typically astrocytes and microglial cells) is closely related to hyperpathia and persistent pain. OBJECTIVE: To investigate the expression of GFAP and CR3/CD11b in cornu dorsale medullae spinalis of rats with nonbacterial prostatitis, to explore the therapeutic efficacy and action mechanism of intrathecal injection of BNP alleviating chronic neuropathic pain. METHODS: Eighteen male SPF SD rats were randomly divided into sham operation control group, nonbacterial prostatitis group (NBP) and intrathecal injection BNP group, the NBP model was established by intraprostatic injection of CFA, and the spinal cord of L6-S1 segment was extracted seven days after intrathecal injection of BNP; The expression of GFAP and CR3/CD11b in dorsal horn of spinal cord were detected by immunofluorescence and Western blot. RESULTS: The cumulative optical density values of GFAP and CR3/CD11b immunofluorescence assay in the NBP group were higher than those in the sham operation group, with statistical significance (p⁢<⁢¼⁢ 0.01); The expression of GFAP and CR3/CD11b in intrathecal injection BNP group were lower than those in NBP group, the differences were statistically significant (p⁢<⁢¼⁢ 0.01). Western blot results showed that the expression of GFAP and CR3/CD11B in NBP group were higher than those in sham operation group, with statistical significance (p⁢<⁢¼⁢ 0.05). The expression of GFAP and CR3/CD11B in intrathecal injection BNP group were lower than those in NBP group, the differences were statistically significant (p⁢<⁢¼⁢ 0.05). CONCLUSION: Intrathecal injection of BNP can down-regulate the expressions of GFAP and CR3/CD11b in L6-S1 spinal cord of NBP rat model and to further inhibit chronic pain caused by NBP.
Super-resolution of diffusion-weighted images using space-customized learning model
Authors: Zhao Xitong , Wen Zhijie
Published: May 2024

BACKGROUND: Diffusion-weighted imaging (DWI) is a noninvasive method used for investigating the microstructural properties of the brain. However, a tradeoff exists between resolution and scanning time in clinical practice. Super-resolution has been employed to enhance spatial resolution in natural images, but its application on high-dimensional and non-Euclidean DWI remains challenging. OBJECTIVE: This study aimed to develop an end-to-end deep learning network for enhancing the spatial resolution of DWI through post-processing. METHODS: We proposed a space-customized deep learning approach that leveraged convolutional neural networks (CNNs) for the grid structural domain (x-space) and graph CNNs (GCNNs) for the diffusion gradient domain (q-space). Moreover, we represented the output of CNN as a graph using correlations defined by a Gaussian kernel in q-space to bridge the gap between CNN and GCNN feature formats. RESULTS: Our model was evaluated on the Human Connectome Project, demonstrating the effective improvement of DWI quality using our proposed method. Extended experiments also highlighted its advantages in downstream tasks. CONCLUSION: The hybrid convolutional neural network exhibited distinct advantages in enhancing the spatial resolution of DWI scans for the feature learning of heterogeneous spatial data.
Imaging findings of Epstein-Barr Virus-positive inflammatory follicular dendritic cell sarcoma of spleen: A case report
Authors: Zhao Xingyu , Gai Lulu , Wang Liang , Xu Lei
Published: May 2024

BACKGROUND: Spleen Epstein-Barr Virus (EBV)-positive inflammatory follicular dendritic cell sarcoma (FDCS) is rare, and the imaging signs are unclear. The COVID-19 has been confirmed to be the cause of pneumonia and can cause a variety of diseases including myocarditis. However, it has not been reported to be the cause of the exacerbation or activation of EBV-positive inflammatory FDCS. OBJECTIVE: The objective is to extract the imaging features of EBV-positive inflammatory FDCS in the spleen and analyze the reasons for the special features of this case. METHODS: By analyzing the patient’s treatment process and imaging examinations (A 77-year-old female was admitted to the hospital due to generalized discomfort and pain symptoms. When she was admitted to the hospital a year earlier with COVID-19 pneumonia, a chest CT scan showed that she had a splenic tumor. During this admission, CT scans showed two irregularly shaped and unevenly dense soft tissue density masses within the spleen, with uneven enhancement on contrast-enhanced im-aging within the solid components and along the edges. PET/CT scans revealed elevated glucose metabolism in the masses. Postoperative pathological diagnosis confirmed splenic EBV-positive inflammatory FDCS.), reading the literature, sorting out the disease cognitive process, epidemiology, and pathological data of EBV-positive inflammatory FDCS, we discussed the imaging manifestations and possible differential diagnosis of the disease. RESULTS: The patient was finally diagnosed with splenic EBV-positive inflammatory FDCS. CONCLUSIONS: Imaging features of EBV-positive inflammatory FDCS in the spleen include a high incidence of hemorrhage and necrosis, persistent moderate enhancement of the solid portion, a “capsular-like enhancement” structure at the tumor edge, and possibly active glucose metabolism with high Standardized Uptake Values (SUVs). COVID-19 infection and long-term COVID-19 sequelae may exacerbate and activate EBV-positive inflammatory FDCS in the spleen, and the mechanism remains to be further studied.
Development of sarcopenia assessment system using balance and gait ability: Preliminary tests in the elderly
Authors: Seo Shinbae , Kwon Taekyu , Shin Miyeon , Jeong Hochoon , Yu Mi , Jeong Jongkyun , Yu Changho
Published: May 2024

BACKGROUND: Sarcopenia is a disease that has recently become an issue, and research on various assessment methods is being conducted based on guidelines published for the diagnosis of sarcopenia. However, most assessments are complex because the inspector must measure each device to collect data, or the elderly must directly manipulate and get assessment. OBJECTIVE: In this study, we developed an sarcopenia assessment system to assess and analyze various sarcopenia in one system. METHODS: The system consists of a scaffold sensor for balance ability assessment, a chair sensor for assessing the walking and lower extremity function, and a hand-held dynamometer for assessing grip strength. The balance pad consists of 326 FSR (Force Sensitive Resistor) sensors, and the accuracy is 10 kg/± 10%. The chair sensor applied four weight sensors (Loadcells) to the corner of the hip of the chair, and the accuracy is up to 150 kg ± 10%, and the resolution is 1 kg ± 10%. All data is transmitted to the software through a USB cable to assess sarcopenia through data analysis. The software has built a database to manage user-specific data. The assessment items consisted of “Short Physical Performance Battery (SPPB) Test” and “Hand Grip Strength Test.” After completion, the software automatically terminates the assessment results and classifies sarcopenia according to the presented reference value. RESULTS: The average value of the total SPPB test scores, including the balance test, gait speed test, and chair stand test, of all participants was 9.06 ± 1.97. The average values of the balance test, gait speed test, and chair stand test scores of all participants were 8.48 ± 2.80 sec (score 3.28 ± 1.23), 1.05 ± 0.26 m/sec (score 3.69 ± 0.79), and 16.05 ± 4.62 sec (score 2.08 ± 1.13). The average value of the hand grip test of all participants was 28.57 ± 2.94 kgf. CONCLUSIONS: A preliminary assessment was conducted on the elderly in their 60 s or older with the developed system, and its performance confirmed that the assessment and result analysis were conducted well without any errors in software or hardware. Future studies intend to verify the reliability and accuracy of the assessment results compared to the existing direct measurement methods. In addition, we would like to conduct a study to establish data on the muscle reduction index by age group of Koreans.
Intelligent deep learning supports biomedical image detection and classification of oral cancer
Authors: Chen Rongcan , Wang Qinglian , Huang Xiaoyuan
Published: May 2024

BACKGROUND: Oral cancer is a malignant tumor that usually occurs within the tissues of the mouth. This type of cancer mainly includes tumors in the lining of the mouth, tongue, lips, buccal mucosa and gums. Oral cancer is on the rise globally, especially in some specific risk groups. The early stage of oral cancer is usually asymptomatic, while the late stage may present with ulcers, lumps, bleeding, etc. OBJECTIVE: The objective of this paper is to propose an effective and accurate method for the identification and classification of oral cancer. METHODS: We applied two deep learning methods, CNN and Transformers. First, we propose a new CANet classification model for oral cancer, which uses attention mechanisms combined with neglected location information to explore the complex combination of attention mechanisms and deep networks, and fully tap the potential of attention mechanisms. Secondly, we design a classification model based on Swim transform. The image is segmented into a series of two-dimensional image blocks, which are then processed by multiple layers of conversion blocks. RESULTS: The proposed classification model was trained and predicted on Kaggle Oral Cancer Images Dataset, and satisfactory results were obtained. The average accuracy, sensitivity, specificity and F1-Socre of Swin transformer architecture are 94.95%, 95.37%, 95.52% and 94.66%, respectively. The average accuracy, sensitivity, specificity and F1-Score of CANet model were 97.00%, 97.82%, 97.82% and 96.61%, respectively. CONCLUSIONS: We studied different deep learning algorithms for oral cancer classification, including convolutional neural networks, converters, etc. Our Attention module in CANet leverages the benefits of channel attention to model the relationships between channels while encoding precise location information that captures the long-term dependencies of the network. The model achieves a high classification effect with an accuracy of 97.00%, which can be used in the automatic recognition and classification of oral cancer.
The improvement of pain symptoms in patients with burning mouth syndrome through combined laser and medication therapy
Authors: Li Xingcen , Li Qianpeng , Li Jinhan , Wang Xiaoyi , Zou Huaxiu , Wang Shuyang , Fan Jingyi
Published: May 2024

BACKGROUND: The etiology of Burning Mouth Syndrome (BMS) remains unclear. OBJECTIVE: To explore the differences in the therapeutic efficacy of pain improvement between medication therapy and laser therapy in patients with BMS. METHODS: 45 BMS patients were randomly divided into three groups: The Combination therapy group (Group A, n= 15), The Medication therapy group (Group B, n= 15), and the Laser therapy group (Group C, n= 15). The pain condition of the patients was evaluated using the Numeric Rating Scale (NRS), and the improvement in pain before and after treatment was compared among the three groups. RESULTS: All three groups (A, B, and C) showed a significant reduction in NRS scores after treatment, with statistically significant differences observed among the different groups. Group A exhibited the most significant improvement, with a statistically significant difference before and after treatment. CONCLUSION: Laser and medication therapy are effective methods for reducing oral burning pain * symptoms, and their combined use yields more significant therapeutic effects.