bluuebunny/crossref_metadata_2025 huggingface dataset:
Pengaruh Finger Painting Menggunakan Tablet Lcd Drawing Board Terhadap Kemampuan Motorik Halus Anak Usia 3-4 Tahun Di Kbit Al-Muthmainnah Kota Jambi
Authors: Sari Fitri Luvita , Sofyan Hendra , Utami Winda Sherly
Published: June 2024

Kemampuan motorik halus sangat penting bagi pertumbuh perkembang anak dikarenakan mampu meningkatkan kreativitas, dan juga kesehatan anak melalu gerakan-gerakan sehingga menimbulkan kepercayaan diri untuk bersosialisas dengan lingkungan sekitar. Untuk mendorong keterampilan motorik halus anak-anak diperlukan kegiatan baru. Salah satunya adalah finger painting dengan menggunakan tablet LCD drawing board yang belum pernah digunakan oleh guru. Tujuan dar penelitian ini adalah untuk mengetahui pengaruh permainan finger painting table LCD drawing board terhadap kemampuan motorik halus anak prasekolah. Dari 3 Apri hingga 27 Mei 2023, penelitian dilakukan. Penelitian ini menggunakan desain eksperimen yang dikenal dengan Pre-Experimental Design, khususnya One-Group Pretest-Posttest Design. Metode pengumpulan data menggunakan observasi Temuan penelitian ini menunjukkan bahwa finger painting pada papan gambar LCD tablet berdampak pada kemampuan motorik halus anak di Kbit Al-Muthmainnah Kota Jambi. Dari data hasil pengujian terlihat bahwa ada pengaruh finger painting menggunakan tablet LCD drawing board terhadap keterampilan motorik halus siswa kelas KBIT Al-Muthmainnah Kota Jambi karena t hitung (11,786) > t tabel (2,101) menunjukkan bahwa t hitung lebih besar dari t tabel. Akibatnya, Ho ditolak dan Ha diterima.
Review : Kajian Potensi Bakteri Endofit sebagai Agen Biodegradasi Linear Alkylbenzene Sulfonate (LAS)
Authors: Mahmudah Arini Nurul , Faizah Hanik , Munir Misbakhul
Published: June 2024

Linear Alkylbenzene Sulfonate (LAS) is a type of anionic surfactant which is commonly used as a raw material in making commercial detergents or cleaners. Even though LAS can be degraded naturally in the environment, detergent wastewater containing LAS still needs to be treated properly before being discharged into the environment. One way that can be done to reduce the toxic effects of LAS is biodegradation. The use of bacteria, especially endophytic bacteria associated with plants, is known to have potential as a biodegradation agent for LAS. This review aims to examine the potential of endophytic bacteria as LAS biodegradation agents. The method used in this review is a literature review from several international and national journal references. Data were analyzed descriptively and presented in narrative and table form. The results of the research show that several species of endophytic bacteria isolated from various types of plants have the potential to degrade pollutants, such as heavy metals, benzene, phenol, phenanthrene (PHE), diesel, ammonium, phosphate, COD, and hydrocarbons which also shows that endophytic bacteria have the potential to degrades LAS.
Pengembangan Modul Ajar Pencemaran Lingkungan dengan Materi Realitas Lokal Indralaya pada Jenjang SMA Kelas X
Authors: Anggraini Nike , Rohmawati Shofi , Meilinda Meilinda , Tibrani Masagus Muhammad
Published: June 2024

This research is a type of development research which aims to develop the Merdeka Curriculum teaching module with material on environmental pollution accompanied by material on the local reality context of Indralaya which is suitable to be donated or used at the class X high school level. This research includes development research (development research) which uses a model ADDIE development consists of 5 stages, namely analysis, design, development, implementation and evaluation, where the evaluation carried out is a formative evaluation. The assessment results from the validators obtained a feasibility score of 85.16% with several suggestions given as well as the conclusion from the two validators that the product being developed could be tested with improvements according to the suggestions. After the development stage, an evaluation stage is carried out, namely by improving it according to suggestions from the validator. The results of trials with students showed that all students who were respondents could understand and read the contents of the teaching module being developed. According to the results obtained, the Merdeka Curriculum teaching module product on environmental pollution along with material on the local reality context of Indralaya has been successfully developed and received a feasibility validation score in the very valid category.
Implementing the Quantum Learning Model to Enhance Students' Physics Learning Outcomes
Authors: Azmi Irham , Prayogi Saiful , Asy'ari Muhammad
Published: June 2024

The students' mastery of the subject matter has been identified to not reach the attainment indicator. The low learning outcomes of the students are suspected to be a result of the predominantly lecture-based teaching method, leading to passive engagement in the learning process. This research aims to describe the improvement in students' physics learning outcomes on the topic of quantities and units using the quantum learning model. The study employed a classroom action research conducted in two cycles, including planning, implementation, observation, evaluation, and reflection stages. Twenty-seven students were involved as subjects in this research. The data on students' learning outcomes were collected using a 20-item multiple-choice test, and the evaluation of the learning process was conducted by two observers using observation sheets. The research results indicate that the students' classical mastery in the first cycle was 63.16% and increased to 85% in the second cycle. This study concludes that the implementation of the quantum learning model can enhance the physics learning outcomes of the students at MTs Nahdlatul Mujahidin NW Jempong on the topic of quantities and units.
Co-Precipitation Synthesis and Analysis of Co and Zn Doped Barium M-Hexaferrites
Authors: Pangga Dwi , Pathoni Haerul , Suprianto Suprianto
Published: June 2024

Barium hexaferrite (BaFe12O19) is a material of significant interest due to its wide range of applications. In this study, we synthesized barium M-hexaferrites (BaFe12-2xCoxZnxO19) powders through the co-precipitation method, starting from BaCO3 and FeCl3.6H2O powders, with Co and Zn powders used as dopant materials. The variations in x values were set at 0, 0.2, 0.4, 0.6, 0.8, and 1. Our findings indicate that the co-precipitation method is highly effective for synthesizing barium M-hexaferrites (BaFe12-2xCoxZnxO19) nanomaterials, which contain more than 89% iron elements and have an average particle size of 50 nm. The Differential Thermal Analysis (DTA) and Thermogravimetric Analysis (TGA) reveal that phase transformations occur at temperatures of 285°C and in the range of 750-840°C. Further analysis using the Rietveld refinement method demonstrates that the barium M-hexaferrite phase begins to form at relatively low temperatures, with the most optimal yield observed at x = 0.4. At temperatures exceeding 740°C, there is a tendency to form a single-phase α-Fe2O3 (hematite). The introduction of Co and Zn as dopant ions results in only minor changes to the lattice parameters of the basic hexagonal crystal structure. This comprehensive study underscores the viability of the co-precipitation method for producing high-quality barium M-hexaferrites and provides valuable insights into the effects of Co and Zn doping on the structural and thermal properties of these materials.
EBEVEYNLERİN DİJİTAL EBEVEYNLİK YETERLİLİKLERİ: SOSYOEKONOMİK FARKLILIKLAR VE TEKNOLOJİ DENEYİMİ BAĞLAMINDA BİR İNCELEME
Authors: Akan Salman , Keskin Sinan , Şener Kübra
Published: June 2024

Ebeveynler çocuklarına interneti ve teknolojiyi nasıl doğru kullanacakları ile ilgili bilgi verebilmeleri, yol gösterebilmeleri, onları sanal dünyadaki tehlikelerden koruyabilmek için belli yeterliklere sahip olmalıdır. Dijital ortamlarda çocukların çeşitli risklerden korunması ve o risklere karşı tedbirlerin alınması konusu ebeveynlerin sorumluluğunda olup dijital ebeveynlik kavramı ile açıklanmaktadır. Bu araştırmada teknoloji erişimi ve sosyoekonomik açılardan birbirinden farklı olan İstanbul ve Ağrı illerinde yaşayan velilerin dijital ebeveynlik yeterlikleri incelenmiştir. Araştırmada nicel araştırma yöntemlerinden ilişkisel araştırma modeli kullanılmıştır. Bu araştırmanın çalışma grubunu iki lisenin velileri oluşturmaktadır. Çalışma grubu 252 kadın ve 183 erkek olmak üzere 435 ebeveynden oluşmuştur. Veri toplama aracı olarak kişisel bilgi formu ve ebeveynlerin dijital ebeveynlik yeterlikleri ölçeği kullanılmıştır. Verilerin analizinde t-testi, ANOVA ve Spearman korelasyon katsayısı kullanılmıştır. Araştırma sonuçlarına göre velilerin sosyal medya kullanımları ve dijital ebeveynlik yeterlikleri illere göre farklılaşmaktadır. Araştırma sonucunda kadın ve erkek velilerin benzer dijital ebeveynlik yeterliliğine sahip olduğu görülmüştür. İnternet kullanım deneyimi ile dijital ebeveynlik arasında Ağrı ilindeki veliler için bir ilişki gözlemlenirken İstanbul ilindeki veliler için anlamlı bir ilişki görülmemiştir. Buna göre özellikle dezavantajlı bölgeler için teknoloji sahipliği, deneyim gibi faktörler dijital uçurumu her geçen gün daha fazla derinleştirdiği ileri sürülebilir. Ayrıca bu bölgelerdeki çocukların dijital ebeveynlikten daha fazla yoksun kaldıkları da söylenebilir. Özellikle ebeveynlerin teknoloji sahipliği ve kullanımının düşük olduğu bölgelerde; çocukların dijital okuryazarlık, iletişim ve güvenlik konularında okullar tarafından desteklenmesi önerilmektedir.
PENINGKATAN POTENSI PARIWISATA ALAM BUTTA TOA ADALAH JEMBATAN UNTUK MENYEJAHTERAKAN MASYARAKAT DALAM WUJUD RANCANGAN PERATURAN DAERAH
Authors: Akhyuning Andi Rismunadia , Fattah Sulaeman
Published: June 2024

Pariwisata merupakan bagian integral dari pembangunan nasional yang memberikan dampak yang signifikan terhadap pertumbuhan perekonomian dalam menyejahterakan masyarakat. Salah satu klasifikasi pariwisata yang banyak diminati masyarakat adalah pariwisata alam. Kabupaten Bantaeng menjadi salah satu daerah yang memiliki potensi pariwisata yang sangat besar khususnya pariwisata alam mengingat letak geografisnya yang strategis namun, sebagian besar dari destinasi tempat wisata alam yang dimiliki masih belum terkelola oleh pemerintah dan sangat disayangkan apabila potensinya dibiarkan begitu saja, maka dari itu diperlukan peningkatan potensi pariwisata sebagai realisasi pemerintah dalam upaya menyejahterakan masyarakat dan melestarikan kekayaan sumber daya yang ada. Penelitian ini ditujukan untuk merumuskan dan menyusun Rancangan Peraturan Daerah Kabupaten Bantaeng sebagai pondasi kuat dalam perancangan kebijakan publik mengenai peningkatan potensi pariwisata yang berfungsi sebagai arah pengaturan dan penyelenggaraan yang terencana. Dalam menyusun Naskah Akademik ini digunakan metode yuridis normatif dan yuridis empiris dengan metode pengumpulan data yang dilakukan secara kualitatif yaitu dengan melakukan kajian pustaka serta dengan melakukan wawancara dengan seluruh stakeholders terkait. Adapun hasil dari penelitian ini berupa Naskah Akademik yang disusun sesuai dengan ketentuan pembentukan peraturan perundang-undangan serta dengan memperhatikan peraturan perundang-undangan yang lebih tinggi.
Symptoms and management of cow's milk allergy: perception and evidence
Authors: Robert E. , Al-Hashmi H. A. , Al-Mehaidib A. , Alsarraf K. , Al-Turaiki M. , Aldekhail W. , Al-Herz W. , Alkhabaz A. , Bawakid Khalid O. , Elghoudi A. , El Hodhod M. , Hussain Ali A. , Kamal Naglaa M. , Goronfolah L. T. , Nasrallah B. , Sengupta K. , Broekaert I. , Domellöf M. , Indrio F. , Lapillonne A. , Pienar C. , Ribes-Koninckx C. , Shamir R. , Szajewska H. , Thapar N. , Thomassen R. A. , Verduci E. , West C. E. , Vandenplas Y.
Published: June 2024

Introduction

The diagnosis and management of cow's milk allergy (CMA) is a topic of debate and controversy. Our aim was to compare the opinions of expert groups from the Middle East (n = 14) and the European Society of Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) (n = 13).

Methods

These Expert groups voted on statements that were developed by the ESPGHAN group and published in a recent position paper. The voting outcome was compared.

Results

Overall, there was consensus amongst both groups of experts. Experts agreed that symptoms of crying, irritability and colic, as single manifestation, are not suggestive of CMA. They agreed that amino-acid based formula (AAF) should be reserved for severe cases (e.g., malnutrition and anaphylaxis) and that there is insufficient evidence to recommend a step-down approach. There was no unanimous consensus on the statement that a cow's milk based extensively hydrolysed formula (eHF) should be the first choice as a diagnostic elimination diet in mild/moderate cases. Although the statements regarding the role for hydrolysed rice formula as a diagnostic and therapeutic elimination diet were accepted, 3/27 disagreed. The votes regarding soy formula highlight the differences in opinion in the role of soy protein in CMA dietary treatment. Generally, soy-based formula is seldom available in the Middle-East region. All ESPGHAN experts agreed that there is insufficient evidence that the addition of probiotics, prebiotics and synbiotics increase the efficacy of elimination diets regarding CMA symptoms (despite other benefits such as decrease of infections and antibiotic intake), whereas 3/14 of the Middle East group thought there was sufficient evidence.

Discussion

Differences in voting are related to geographical, cultural and other conditions, such as cost and availability. This emphasizes the need to develop region-specific guidelines considering social and cultural conditions, and to perform further research in this area.
Hounsfield unit for assessing bone mineral density distribution within lumbar vertebrae and its clinical values
Authors: Chen Jiabao , Li Yanhong , Zheng Han , Li Haotian , Wang Haidong , Ma Lei
Published: June 2024

Study Design

Retrospective radiological analysis.

Objective

The aim of this study is to evaluate the distribution of bone mineral density (BMD) in lumbar vertebrae using the Hounsfield unit (HU) measurement method and investigate the clinical implications of HU values for assessing lumbar vertebrae BMD.

Method

Two hundred and ninety-six patients were retrospectively reviewed and divided into six groups according to age: Group 1(20–29 years old), Group 2 (30–39 years old), Group 3 (40–49 years old), Group 4 (50–59 years old), Group 5 (60–69 years old), Group 6 (70–79 years old). Six different locations from each vertebra of L1-L5 were selected as regions of interest: the anterior, middle and posterior parts of the upper and lower slices of the vertebrae. HU values were measured for the six regions of interest, followed by statistical analysis.

Results

The HU values of vertebrae showed a decreasing trend from young patients to elderly patients in Group 1 to Group 5. There was no significant difference in HU values among different vertebrae in the same age group. In all age groups, the HU values of the anterior and posterior part of the vertebral body were significantly different from L1 to L3, with the anterior part of the vertebral body having lower HU values than the posterior part. The HU values of the anterior and posterior part of the vertebral body of L4 and L5 were statistically significant only in Group 5 and Group 6, and the HU values of the anterior part of the vertebral body were lower than those of the posterior part. The HU values of posterior part of L4 and L5 in Group6 were higher than those in Group5.

Conclusion

Bone mineral density in the lumbar vertebrae is not uniformly distributed, potentially attributed to varying stress stimuli. The assessment of local HU values in the lumbar spine is of significant importance for surgical treatment.
Application of research on carbon neutral strategy of physical education teaching based on attention mechanism in digital energy transformation
Authors: Yuan Tianlei , Cai Feng , Han HuiJun
Published: June 2024

With the global goal of carbon neutrality being emphasized, the implementation of carbon-neutral strategies has become a crucial task across various domains. As an integral part of social activities, physical education also necessitates considerations on how to reduce carbon emissions and implement carbon-neutral strategies within the teaching process. This study focuses on physical education and explores carbon-neutral strategies based on an end-to-end architecture with an attention mechanism. Firstly, we introduce an end-to-end framework that enables the integration and optimization of various aspects within the teaching process to achieve comprehensive carbon-neutral objectives. This framework serves as a unified optimization platform, facilitating the collaboration of different components involved in teaching activities and balancing the reduction of carbon emissions with teaching effectiveness. Secondly, we employ Convolutional Neural Networks (CNN) as the foundational model within the end-to-end architecture. Through training the CNN model, we automate the analysis of carbon emissions during the teaching process and provide corresponding carbon-neutral recommendations for different segments. Most importantly, we incorporate an attention mechanism to enhance the effectiveness and interpretability of the carbon-neutral strategy. The attention mechanism assists the model in automatically focusing on features or regions closely related to carbon-neutral objectives, thereby achieving more accurate and efficient carbon-neutral strategy recommendations. Finally, we conduct training and testing on the proposed model using a dataset constructed from carbon-neutral scenarios in physical education (the country where physical education occurred and digital energy have been scrutinized). The results demonstrate that the improved model surpasses a 90% threshold in mainstream evaluation metrics such as Action Recognition Accuracy (ARA), Action Recognition Recall (ARR), and Action Optimization Rate (AOR). The enhanced model exhibits notable improvements in inference speed and accuracy.
Disease-specific autoantibody production in the lungs and salivary glands of anti-synthetase syndrome
Authors: Takeshita Masaru , Suzuki Katsuya , Nakazawa Maho , Kamata Hirofumi , Ishii Makoto , Oyamada Yoshitaka , Oshima Hisaji , Usuda Satoshi , Tsunoda Kazuyuki , Takeuchi Tsutomu
Published: June 2024

Interstitial lung disease is a common complication of anti-synthetase syndrome (ASS), and lymphocytic infiltration is often observed in the lesion. We have recently reported that disease-specific autoantibodies are produced by infiltrating lymphocytes in some autoimmune diseases. Here, we investigate the antigen specificity of B cells in the lung lesions of ASS patients. A total of 177 antibodies were produced from antibody-secreting cells in bronchoalveolar fluid (BALF) of three each of serum anti-Jo-1 and serum anti-EJ antibody–positive patients. Twelve to 30% and 50 to 62% of these antibodies were disease-specific autoantibodies, respectively. These autoantibodies recognized conformational epitopes of the whole self-antigen and had affinity maturations, indicating that self-antigens themselves are the target of humoral immunity. In addition, 100 antibodies were produced from two salivary gland tissues, obtained by chance, of ASS patients. Salivary glands are not generally recognized as lesions of ASS, but unexpectedly, ASS-related autoantibody production was also observed similar to that of BALF. Immunostaining confirmed the presence of ASS-related autoantibody-producing cells in salivary glands. Our results suggest that disease-specific autoantibody production at lesion sites is a common pathogenesis of autoimmune diseases, and that tissue-specific production of autoantibodies can provide insights regarding the distribution of organ manifestations in autoimmune diseases.
Corticosteroid-depending effects on peripheral immune cell subsets vary according to disease modifying strategies in multiple sclerosis
Authors: Höpner Lena , Proschmann Undine , Inojosa Hernan , Ziemssen Tjalf , Akgün Katja
Published: June 2024

Background

The primary treatment for acute relapses in multiple sclerosis (MS) is the intravenous administration of high-dose methylprednisolone (IVMP). However, the mechanisms through which corticosteroid treatment impacts acute neuroinflammation in people with MS (pwMS) remain not fully understood. In particular, the changes induced by glucocorticoids (GCs) on cells of the innate immune system and the differences between patients with distinct immunotherapies have received little attention to date.

Methods

We conducted immunophenotyping using flow cytometry on peripheral blood mononuclear cells of pwMS who received IVMP treatment during a relapse. We compared the impact of an IVMP treatment on a broad variety of immune cell subsets within three groups: twelve patients who were treatment-naïve to disease modifying therapies (wDMT) to ten patients on platform therapies (PT) and eighteen patients on fingolimod therapy (FTY).

Results

We observed pronounced interindividual short- and intermediate-term effects of IVMP on distinct immune cells subsets. In addition to the well-documented decrease in T-helper cells (Th cells), we detected significant alterations after the first IVMP infusion within the innate immune response among neutrophil, eosinophil and basophil granulocytes, monocytes and plasmacytoid dendritic cells (pDCs). When comparing patients wDMT to the PT and FTY cohorts, we found that IVMP had a similar impact on innate immune cells across all treatment groups. However, we did not observe a significant further decline in T lymphocyte counts during IVMP in patients with pre-existing lymphopenia under FTY treatment. Although T cell apoptosis is considered the main mechanism of action of GCs, patients with FTY still reported symptom improvement following IVMP treatment.

Conclusion

In addition to T cell suppression, our data suggests that further immunoregulatory mechanisms of GC, particularly on cells of the innate immune response, are of greater significance than previously understood. Due to the regulation of the adaptive immune cells by DMTs, the impact of GC on these cells varies depending on the underlying DMT. Additional studies involving larger cohorts and cerebrospinal fluid samples are necessary to gain a deeper understanding of the immune response to GC in pwMS with different DMTs during relapse to define and explain differences in clinical response profiles.
Multiparametric MRI-based radiomics approach with deep transfer learning for preoperative prediction of Ki-67 status in sinonasal squamous cell carcinoma
Authors: Lin Naier , Shi Yiqian , Ye Min , Wang Luxi , Sha Yan
Published: June 2024

Purpose

Based on comparison of different machine learning (ML) models, we developed the model that integrates traditional hand-crafted (HC) features and ResNet50 network-based deep transfer learning (DTL) features from multiparametric MRI to predict Ki-67 status in sinonasal squamous cell carcinoma (SNSCC).

Methods

Two hundred thirty-one SNSCC patients were retrospectively reviewed [training cohort (n = 185), test cohort (n = 46)]. Pathological grade, clinical, and MRI characteristics were analyzed to choose the independent predictor. HC and DTL radiomics features were extracted from fat-saturated T2-weighted imaging, contrast-enhanced T1-weighted imaging, and apparent diffusion coefficient map. Then, HC and DTL features were fused to formulate the deep learning-based radiomics (DLR) features. After feature selection and radiomics signature (RS) building, we compared the predictive ability of RS-HC, RS-DTL, and RS-DLR.

Results

No independent predictors were found based on pathological, clinical, and MRI characteristics. After feature selection, 42 HC and 10 DTL radiomics features were retained. The support vector machine (SVM), LightGBM, and ExtraTrees (ET) were the best classifier for RS-HC, RS-DTL, and RS-DLR. In the training cohort, the predictive ability of RS-DLR was significantly better than those of RS-DTL and RS-HC (p< 0.050); in the test set, the area under curve (AUC) of RS-DLR (AUC = 0.817) was also the highest, but there was no significant difference of the performance between DLR-RS and HC-RS.

Conclusions

Both the HC and DLR model showed favorable predictive efficacy for Ki-67 expression in patients with SNSCC. Especially, the RS-DLR model represented an opportunity to advance the prediction ability.
No advantage of antimicrobial prophylaxis in AML/MDS/CMML patients treated with azacitidine—a prospective multicenter study by the Polish Adult Leukemia Group
Authors: Mądry Krzysztof , Lis Karol , Sienkiewicz Elzbieta , Drozd-Sokołowska Joanna , Biecek Przemysław , Sośnia Oktawia , Gołos Aleksandra , Olszewska-Szopa Magdalena , Obara Agata , Walkowiak Zuzanna , Ściesińska Joanna , Subocz Edyta , Butrym Aleksandra , Machowicz Rafał , Budziszewska Katarzyna , Basak Grzegorz
Published: June 2024

Introduction

Infections represent one of the most frequent causes of death of higher-risk MDS patients, as reported previously also by our group. Azacitidine Infection Risk Model (AIR), based on red blood cell (RBC) transfusion dependency, neutropenia <0.8 × 109/L, platelet count <50 × 109/L, albumin <35g/L, and ECOG performance status ≥2 has been proposed based on the retrospective data to estimate the risk of infection in azacitidine treated patients.

Methods

The prospective non-intervention study aimed to identify factors predisposing to infection, validate the AIR score, and assess the impact of antimicrobial prophylaxis on the outcome of azacitidine-treated MDS/AML and CMML patients.

Results

We collected data on 307 patients, 57.6 % males, treated with azacitidine: AML (37.8%), MDS (55.0%), and CMML (7.1%). The median age at azacitidine treatment commencement was 71 (range, 18-95) years. 200 (65%) patients were assigned to higher risk AIR group. Antibacterial, antifungal, and antiviral prophylaxis was used in 66.0%, 29.3%, and 25.7% of patients, respectively. In total, 169 infectious episodes (IE) were recorded in 118 (38.4%) patients within the first three azacitidine cycles. In a multivariate analysis ECOG status, RBC transfusion dependency, IPSS-R score, and CRP concentration were statistically significant for infection development (p < 0.05). The occurrence of infection within the first three azacitidine cycles was significantly higher in the higher risk AIR group – 47.0% than in lower risk 22.4% (odds ratio (OR) 3.06; 95% CI 1.82-5.30, p < 0.05). Administration of antimicrobial prophylaxis did not have a significant impact on all-infection occurrence in multivariate analysis: antibacterial prophylaxis (OR 0.93; 0.41-2.05, p = 0.87), antifungal OR 1.24 (0.54-2.85) (p = 0.59), antiviral OR 1.24 (0.53-2.82) (p = 0.60).

Discussion

The AIR Model effectively discriminates infection-risk patients during azacitidine treatment. Antimicrobial prophylaxis does not decrease the infection rate.
Recognition of dynamic facial expressions of emotions in forensic inpatients who have committed sexual offenses: a signal detection analysis
Authors: Tiberi Luca A. , Gillespie Steven M. , Saloppé Xavier , Vicenzutto Audrey , Pham Thierry H.
Published: June 2024

Emotion recognition is central in prosocial interaction, enabling the inference of mental and affective states. Individuals who have committed sexual offenses are known to exhibit socio-affective deficits, one of the four dynamic risk assessment dimensions found in the literature. Few research focused on emotion recognition. The available literature, exclusively on individuals in prison who have committed sexual offenses, showed contrasting results. Some found a global (across all emotions) or specific (e.g., anger, fear) deficit in emotion recognition. In contrast, others found no difference between individuals in prison who have committed sexual offenses and those who have committed non-sexual offenses. In addition, no such study has been undertaken among forensic inpatients who exhibit socio-affective deficits. This study aims to investigate the recognition of dynamic facial expressions of emotion in 112 male participants divided into three groups: forensic inpatients who have committed sexual offenses (n = 37), forensic inpatients who have committed non-sexual offenses (n = 25), and community members (n = 50), using the Signal Detection Theory indices: sensitivity (d’) and response bias (c). In addition, measures related to reaction time, emotion labeling reflection time, task easiness, and easiness reflection time were also collected. Non-parametric analyses (Kruskall-Wallis’ H, followed by Mann-Whitney’s U with Dunn-Bonferroni correction) highlighted that the two forensic inpatient groups exhibited emotion recognition deficits when compared to community members. Forensic inpatients who have committed sexual offenses were more conservative in selecting the surprise label than community members. They also took significantly more time to react to stimuli and to select an emotional label. Despite emotion recognition deficits, the two forensic inpatient groups reported more stimuli easiness than community members.
Utilizing the Short Mood and Feelings Questionnaire to measure symptoms of depression among Vietnamese adolescents in Hanoi, Vietnam, during the COVID-19 pandemic
Authors: Vinh Ngo Anh , Long Nguyen Thanh , Trang Do Thi , Trang Le Thu , Thuy Le Thi Thanh
Published: June 2024

Objective

This study aimed to measure depression among children and adolescents during the COVID-19 pandemic in Hanoi, Vietnam and its associated factors by using the Short Mood and Feelings Questionnaire (SMFQ) instrument.

Methods

We conducted a cross-sectional study among students from grades 6 to 9 within two secondary schools in Hanoi, the capital of Vietnam. A structured questionnaire was used, including information about personal characteristics, perception of COVID-19, and SMFQ. Factor analysis, Multivariate logistic and Tobit regression models were used.

Results

Among 2378 students, 8.8% had depressive symptoms. The mean SMFQ score was 4.5 (SD=5.0). Being female, studying in higher grades, perceived low household income, higher perceived impacts of COVID-19 on health and higher perceived impacts of COVID-19-related quarantine on life were positively associated with factors’ scores, SMFQ score and depressive symptoms. Meanwhile, having better academic performance, living with parents and having higher perceived knowledge about COVID-19 were negatively associated with factors scores, SMFQ score and depressive symptoms.

Conclusions

Depressive symptoms were common among secondary school students in Hanoi, Vietnam, during the COVID-19 pandemic. Tailored interventions to improve pandemic-related knowledge and family and school support should be warranted for the students to enhance their mental well-being.
Fault Detection of Flow Control Valves Using Online LightGBM and STL Decomposition
Authors: Liu Shaodong , Zhao Tao , Zhang Dengfeng
Published: June 2024

In the process industrial systems, flow control valves are deemed vital components that ensure the system’s safe operation. Hence, detecting faults in control valves is of significant importance. However, the stable operating conditions of flow control valves are prone to change, resulting in a decreased effectiveness of the conventional fault detection method. In this paper, an online fault detection approach considering the variable operating conditions of flow control valves is proposed. This approach is based on residual analysis, combining LightGBM online model with Seasonal and Trend decomposition using Loess (STL). LightGBM is a tree-based machine learning algorithm. In the proposed method, an online LightGBM is employed to establish and continuously update a flow prediction model for control valves, ensuring model accuracy during changes in operational conditions. Subsequently, STL decomposition is applied to the model’s residuals to capture the trend of residual changes, which is then transformed into a Health Index (HI) for evaluating the health level of the flow control valves. Finally, fault occurrences are detected based on the magnitude of the HI. We validate this approach using both simulated and real factory data. The experimental results demonstrate that the proposed method can promptly reflect the occurrence of faults through the HI.
Synergistic Combination of Aztreonam and Ceftazidime–Avibactam—A Promising Defense Strategy against OXA-48 + NDM Klebsiella pneumoniae in Romania
Authors: Cismaru Ioana Miriana , Văcăroiu Maria Cristina , Soium Elif , Holban Tiberiu , Radu Adelina Maria , Melinte Violeta , Gheorghiță Valeriu
Published: June 2024

With the increasing burden of carbapenem-resistant Klebsiella pneumoniae (CR-Kp), including high rates of healthcare-associated infections, treatment failure, and mortality, a good therapeutic strategy for attacking this multi-resistant pathogen is one of the main goals in current medical practice and necessitates the use of novel antibiotics or new drug combinations. Objectives: We reviewed the clinical and microbiological outcomes of seven patients treated at the “Agrippa Ionescu” Clinical Emergency Hospital between October 2023 and January 2024, aiming to demonstrate the synergistic activity of the ceftazidime–avibactam (C/A) plus aztreonam (ATM) combination against the co-producers of blaNDM + blaOXA-48-like CR-Kp. Material and Methods: Seven CR-Kp with blaNDM and blaOXA-48 as resistance mechanisms were tested. Seven patients treated with C/A + ATM were included. The synergistic activity of C/A + ATM was proven through double-disk diffusion in all seven isolates. Resistance mechanisms like KPC, VIM, OXA-48, NDM, IMP, and CTX-M were assessed through immunochromatography. Results: With a mean of nine days of treatment with the synergistic combination C/A + ATM, all patients achieved clinical recovery, and five achieved microbiological recovery. Conclusions: With the emerging co-occurrence of blaOXA-48 and blaNDM among Kp in Romania, the combination of C/A and ATM could be a promising therapeutic option.
Modeling the Dynamics of Water and Mud Inrush in Fault Fracture Zones: The Role of Seepage–Erosion Interactions
Authors: Zhang Qingyan , Zhou Xiaowen
Published: June 2024

By using the principles of porous media seepage mechanics and solute transport theories, a seepage–erosion theory model was developed to uncover the dynamics of mud and water inrush in fault rupture zones during the construction of tunnels. This model consists of a mass conservation equation, a flow transformation equation, a porosity evolution equation, and a permeability evolution equation. These components illustrate the interaction between seepage–erosion particle loss and the transformation of seepage flow patterns throughout the mud and water inrush evolution in the fault fracture zone. This model proves to be effective in illustrating the catastrophic process of mud and water inrushes within tunnels located in fault rupture zones. To address the spatial and temporal variations, the implicit difference and Galerkin finite element schemes were utilized, and the Newton–Raphson iteration method was applied to handle the nonlinear attributes of the equations. The theoretical model underwent further development and numerical simulations were performed using COMSOL multi-field coupling software. A comparison with existing indoor water inrush mud model test results validated the effectiveness of our model. The theoretical model was then applied to the Yong Lian tunnel scenario within the fault rupture zone. This computational analysis exposed the sequence of flow pattern transformations and the instability in seepage–erosion evolution within the fault rupture zone, ultimately leading to the emergence of mud and water inrush disasters. The findings of this study offer valuable insights for addressing tunnel engineering challenges related to underwater inrush disasters.
Analysis of the Image Magnification Produced by Inline Holographic Systems Based on the Double-Sideband Filter
Authors: Ramírez Claudio , Estévez Irene , Lizana Ángel , Campos Juan , García-Canseco Luisa
Published: June 2024

In-line digital holography is a powerful tool widely used for microscopic object imaging. Usually, in-line and out-line configurations are used to implement holographic systems, but in-line-based set-ups are preferable as they are less sensitive to mechanical vibrations and refraction index variations. However, non-desired blurred conjugate images are superposed to the reconstructed object image by using in-line systems. One strategy to remove the conjugate image contribution is to include a double-sideband filter at the Fourier plane of the system. After using the filter, data obtained at the CCD are processed to retrieve the magnitude and phase (hologram) of the diffracted wavefront while removing the conjugated image. Afterwards, a diffraction integral equation is used to digitally propagate the hologram. Despite the above-mentioned factors, there is not a thorough analysis in the literature of magnification parameters associated with the final reconstructed image, this aspect being crucial for the experimental application of the above-stated approach. Under this scenario, a theoretical analysis of the longitudinal and transverse magnifications of the reconstructed images is provided in this work. The method is validated through the simulation and experimental results of different microscopic objects: glass microspheres, a micrometric reticle, and a resolution test chart USAF 1951. The obtained results provide that the combination of magnification relations with methods for hologram propagation and optimal focused image identification is effective for object position determination. This approach could be useful for 3D microparticle localization and monitoring with optimized magnification within real-time applications.
A Masked-Pre-Training-Based Fast Deep Image Prior Denoising Model
Authors: Ji Shuichen , Xu Shaoping , Cheng Qiangqiang , Xiao Nan , Zhou Changfei , Xiong Minghai
Published: June 2024

Compared to supervised denoising models based on deep learning, the unsupervised Deep Image Prior (DIP) denoising approach offers greater flexibility and practicality by operating solely with the given noisy image. However, the random initialization of network input and network parameters in the DIP leads to a slow convergence during iterative training, affecting the execution efficiency heavily. To address this issue, we propose the Masked-Pre-training-Based Fast DIP (MPFDIP) Denoising Model in this paper. We enhance the classical Restormer framework by improving its Transformer core module and incorporating sampling, residual learning, and refinement techniques. This results in a fast network called FRformer (Fast Restormer). The FRformer model undergoes offline supervised training using the masked processing technique for pre-training. For a specific noisy image, the pre-trained FRformer network, with its learned parameters, replaces the UNet network used in the original DIP model. The online iterative training of the replaced model follows the DIP unsupervised training approach, utilizing multi-target images and an adaptive loss function. This strategy further improves the denoising effectiveness of the pre-trained model. Extensive experiments demonstrate that the MPFDIP model outperforms existing mainstream deep-learning-based denoising models in reducing Gaussian noise, mixed Gaussian–Poisson noise, and low-dose CT noise. It also significantly enhances the execution efficiency compared to the original DIP model. This improvement is mainly attributed to the FRformer network’s initialization parameters obtained through masked pre-training, which exhibit strong generalization capabilities for various types and intensities of noise and already provide some denoising effect. Using them as initialization parameters greatly improves the convergence speed of unsupervised iterative training in the DIP. Additionally, the techniques of multi-target images and the adaptive loss function further enhance the denoising process.
Antioxidant Properties of Wafers with Added Pumpkin Seed Flour Subjected to In Vitro Digestion
Authors: Karaś Monika , Szymanowska Urszula , Borecka Magdalena , Jakubczyk Anna , Kowalczyk Dariusz
Published: June 2024

In this study, our research aim was to assess the influence of pumpkin seed flour addition on the antioxidant properties, consumer acceptability, functional properties, and texture of wafers. The in vitro gastrointestinal digestion process was used to assess the effectiveness of fortification in terms of the potential bioavailability of phenolic compounds and peptides. The antioxidant activity of the obtained hydrolysates and potentially bioavailable fractions (≤3.5 kDa) was tested. The highest antiradical activity and Fe2+ chelation ability (IC50) were noted for the fraction obtained from wafers with the greatest addition of pumpkin seed flour—Pf4 (0.49 mg/mL for ABTS+*, 3.84 mg/mL for DPPH*, and 2.04 mg/mL for Fe2+ chelation). The addition of pumpkin seed flour caused the color of the wafers to change to a darker one (24.46% differences in L* between C and P4), which influenced consumer ratings. This study shows that adding pumpkin seed flour increases the peptide and phenolic contents of wafers (1.13 mg/mL and 1.01 mg/mL of peptides and 0.429 mg/mL and 0.351 mg/mL of phenolics for P4 and C hydrolysates, respectively) and enhances their antioxidant activity, with only minimal effects on taste, aroma, crispness, water and fat adsorption capacity, and foaming ability. Fractions ≤ 3.5 kDa showed greater antioxidative activity than hydrolysates, and the addition of pumpkin seed flour improved these properties. To sum up, pumpkin seeds are a valuable source of antioxidant compounds (phenolic compounds and peptides) and can be used to enrich various products.
AI-Enhanced Prediction of Peak Rate of Torque Development from Accelerometer Signals
Authors: Cossich Victor R. A. , Katz Larry , Laett Conrado T.
Published: June 2024

This study explores the use of accelerometer signals as the predictors of Rate of Torque Development (RTD) using an artificial neural network (ANN) prediction model. Sixteen physically active men participated (29 ± 5 years), performing explosive isometric contractions while acceleration (ACC) signals were measured. The dataset, comprising ACC signals and corresponding RTD values, was split into training and testing (70–30%) sets for ANN training. The trained model predicted the peak RTD values from the ACC signal inputs. The measured and predicted peak RTD values were compared, with no significant differences observed (p = 0.852). A strong linear fit (R² = 0.81), ICC = 0.94 (p < 0.001), and a mean bias of 30.8 Nm/s demonstrated almost perfect agreement between measures. The study demonstrates the feasibility of using accelerometer data to predict peak RTD, offering a portable and cost-effective method compared to traditional equipment. The ANN prediction model provides a reliable means of estimating RTD from ACC signals, potentially enhancing accessibility to RTD assessment in sports and rehabilitation settings. The findings support the use of ANN models for predicting RTD, highlighting the potential of AI in developing performance analysis tools.
Utilizing MicroGenetic Algorithm for Optimal Design of Permanent-Magnet-Assisted WFSM for Traction Machines
Authors: Seo Han-Soo , Park Chan-Bae , Kim Seong-Hwi , Lei Gang , Guo Youguang , Lee Hyung-Woo
Published: June 2024

With increasing worries about the environment, there is a rising focus on saving energy in various industries. In the e-mobility industry of electric motors, permanent magnet synchronous motors (PMSMs) are widely utilized for saving energy due to their high-efficiency motor technologies. However, challenges like environmental degradation from rare earth development and difficulties in controlling magnetic field fluctuations persist. To address these issues, active research focuses on the wound field synchronous motor (WFSM), known for its ability to regulate field current efficiently across various speeds and operating conditions. Nevertheless, compared with other synchronous motors, the WFSM tends to exhibit relatively lower efficiency and torque density. Because the WFSM involves winding both the rotor and the stator, it results in increased copper and iron losses. In this article, a model that enhances torque density by inserting permanent magnets (PMs) into the rotor of the basic WFSM is proposed. This proposed model bolsters the d axis magnetic flux, thereby enhancing the motor’s overall performance while addressing environmental concerns related to rare-earth materials and potentially reducing manufacturing costs when compared with those of the PMSM. The research methodology involves a comprehensive sensitivity analysis to identify key design variables, followed by sampling using optimal Latin hypercube design (OLHD). A surrogate model is then constructed using the kriging interpolation technique, and the optimization process employs a micro-genetic algorithm (MGA) to derive the optimal model configuration. The algorithm was performed to minimize the use of PMs when the same torque as that of the basic WFSM is present, and to reduce torque ripple. Error assessment is conducted through comparisons with finite element method (FEM) simulations. The optimized permanent-magnet-assisted WFSM (PMa-WFSM) model improved efficiency by 1.08% when it was the same size as the basic WFSM, and the torque ripple decreased by 5.43%. The proposed PMa-WFSM derived from this article is expected to be suitable for use in the e-mobility industry as a replacement for PMSM.
An Improved Low-Density Parity-Check Decoder and Its Field-Programmable Fate Array Implementation
Authors: Wang Hao-Yu , Wang Zhong-Xun , Shang Shuo
Published: June 2024

Based on the IEEE 802.16e standard’s (672,336) LDPC code and the normalized Min-Sum decoding algorithm, this paper designs and implements an LDPC decoder that optimizes the channel information. The correction factor for check nodes is converted into a correction factor for the initial channel information, replacing the optimization of check node information with that of initial channel information. This achieves decoding performance equivalent to the traditional normalized Min-Sum decoding algorithm. Different correction factor values vary in complexity during FPGA implementation, as they involve different amounts of shift-add operations. For NMS decoding requiring a high number of shift-add operations to achieve optimal correction values, this can be converted into an LDPC decoding algorithm optimized for channel information, reducing computational overhead without sacrificing performance. A partially parallel improved decoder was designed and implemented on an FPGA, and its feasibility was verified using the Vivado simulation platform.
Boosting Engineering Education with Virtual Reality: An Experiment to Enhance Student Knowledge Retention
Authors: Anjos Fernando Elemar Vicente dos , Martins Adriano de Oliveira , Rodrigues Gislene Salim , Sellitto Miguel Afonso , Silva Debora Oliveira da
Published: June 2024

This article is about experiments investigating teaching and learning processes and their effects on students. Specifically, the laboratory experiment method aims to determine if using virtual reality in classes leads to better learning outcomes, knowledge retention, satisfaction, engagement, and attractiveness compared to traditional teaching methods. The study found that students who used VR (Experimental Group—EG) had significantly better learning outcomes (with an average of 5.9747) compared to the control group (Control Group—CG), who only had traditional classes (with an average of 4.6229). The study employed a Likert scale from 1 to 7. The difference between EG and CG was 29.2%. Furthermore, the study found that students in the EG had higher knowledge retention, satisfaction, engagement, and attractiveness compared to the CG. All measurements were above 6.4 on the same scale. This study is important because it explores innovative teaching methods and their potential to improve learning outcomes, satisfaction, and efficiency. It also opens up avenues for further research on teaching methodologies for undergraduate students.