bluuebunny/crossref_metadata_2025 huggingface dataset:
Rhetorical organizations of method chapter in bachelor’s theses by Indonesian TEFL undergraduates
Authors: Lubis Citra Utami , Dalimunte Ahmad Amin , Nuriatama Intan , Simbolon Sulistina Ratulani
Published: May 2024

In the scientific realm, the validity of studies and the reliability of empirical findings are of high significance to be presented through research reports, one of which is a thesis. In an undergraduate thesis, the methodology chapter plays an important role in reporting any key details, including research procedures, tools, data collection, and data analysis. Novice writer-researchers such as Indonesian undergraduate students face challenges in writing their methods chapters, one of which deals with the issue of rhetorical organization. Using a genre analysis approach by adopting the comprehensive moves model developed by Chen and Kuo (2012), we analyzed the rhetorical moves in the methods chapters of five Indonesian undergraduate theses. Five bachelor theses in the field of teaching English as a foreign language (TEFL) were selected as data sources due to their relevance to our objectives and predetermined criteria of data selection. The findings show three key moves used in the chapters, with varying frequency. Move 2 was the most frequently used, followed by Move 3, while Move 1 was the least one. Several recurred steps were presented to achieve the communicative purpose of the key moves. Thus, our findings can be useful for Indonesian student writers’ awareness of the importance of utilizing moves and steps in writing and crafting systematic and compelling method chapters.
IDENTIFICATION OF POTATO LEAF DISEASES USING ARTIFICIAL NEURAL NETWORKS WITH EXTREME LEARNING MACHINE ALGORITHM
Authors: Erkamim Moh. , Septarini Ri Sabti , Tonggiroh Mursalim , Nurhayati Siti
Published: May 2024

Potato plants have an important role in providing a source of carbohydrates for society. However, potato production is often threatened by various plant diseases, such as leaf disease, which can cause a decrease in yields. Identification of diseases on potato leaves is currently mostly done by farmers manually, so it is not always efficient and accurate. So the aim of this research is to identify diseases on potato leaves with artificial neural networks using the ELM (Extreme Learning Machine) approach and the GLCM (Gray Level Co-Occurrence Matrix) method for feature extraction. The GLCM approach functions to obtain texture features on objects by measuring how often certain pairs of pixel intensities appear together at various distances and directions in the image. Meanwhile, the ELM algorithm is used for image identification by adopting a one-time training method without iteration, which involves randomly determining weights and biases in hidden layers, thus allowing training to be carried out quickly and efficiently. Evaluation of the model by looking for the level of accuracy produces a value of 84.667%. The results show that the model developed is capable of accurate identification.
Integrasi Pembelajaran Bahasa dalam Penanganan Anak Berkebutuhan Khusus Pada Peserta Didik Sekolah Menengah Pertama (SMP) di Kota Samarinda (Kajian Multiple Intelegence Berperspektif Nilai Humanisme Pedagogik)
Authors: Arditiya Arditiya , Amalia Puji Astuti , Hidayat Amir , Azizah Anisah
Published: May 2024

Kredibilitas sistem pendidikan nasional telah menunjukkan arah yang humanis. Pengedepanan pola pembelajaran terbuka dan inovatif menjadi ciri pendidikan saat ini. Sistem yang ditawarkan adalah memaksimalkan potensi anak sesuai dengan tingkat kecerdasannya masing-masing. Multiple intelegence merupakan pendekatan yang diharapkan mampu menjawab problematika pembelajaran di setiap sekolah. Sekolah yang mampu mengelola anak berkebutuhan khusus sehingga dapat mengembangkan potensi dirinya, ialah sekolah yang berhasil. Sekolah yang humanis mewujudkan iklim komunikasi Bahasa yang interaktif sehinga menciptakan pendidikan bebas bullying, perundungan, dan kekerasan psikologis di sekolah. Penelitian ini bertujuan untuk mengoptimalkan pendidikan humanis, dengan memadukan formulasi pembelajaran bahasa peserta didik  berbasis multiple intelegence pedagogik. Penelitian ini bersifat kualitatif eksploratif. Data dan sumber data berupa satuan verbalitas yang memiliki satuan motivasional antara pendidik dan peserta didik dalam aktivitas pembelajaran di sekolah. Observasi partisipatoris, wawancara, studi kepustakaan dan dokumentasi merupakan tahapan pemerolehan data di lapangan. Instrumen penelitian berupa ketersediaan korpus data yang terintegrasi dengan kisi-kisi penjaring data agar memiliki validitas yang objektif. Hasil dan kesimpulan penelitian menunjukan bahwa 12 klasifikasi ABK dapat terintegrasi pada 8 komponen multiple intelegenge dalam perspektif pembelajaran bahasa.
Citra Perempuan Dalam Kumpulan Puisi Maskumambang Buat Ibu Karya Nenden Lilis A.
Authors: Hartati Dian , Murni Dewi
Published: May 2024

Perempuan semakin giat memulai pergerakan dalam segala bidang. Salah satunya turut andil mengembangkan kreativitas melalui karya sastra. Tujuan penelitian mendeskripsikan citra perempuan dalam kumpulan puisi Maskumambang Buat Ibu karya Nenden Lilis A. Penelitian memanfaatkan metode deskriptif analitik dengan pendekatan kualitatif. Teknik pengumpulan data memanfaatkan teknik membaca, mencatat, dan studi pustaka terhadap kutipan puisi yang memuat citra perempuan. Teknik analisis data menerapkan teknik analisis interaktif, meliputi reduksi data, penyajian data, dan penarikan kesimpulan. Hasil analisis menunjukkan kumpulan puisi Maskumambang Buat Ibu karya Nenden Lilis A. mengandung citra perempuan yang terdiri dari atas aspek fisik, psikis, dan sosial. Dalam aspek fisik perempuan digambarkan sebagai manusia bisa dibuahi karena dikaruniai Rahim oleh Tuhan, dan tubuh perempuan diciptakan dengan penuh keindahan. Dalam aspek psikis perempuan digambarkan mendapat tekanan karena pekerjaannya sebagai pelacur, dan beban seorang ibu harus membagi peran lebih dari satu demi kelangsungan anak-anaknya. Dalam aspek sosial, perempuan digambarkan berperan sebagai ibu, istri, tulang punggung keluarga, dan dalam ranah masyarakat diklaim sebagai pendatang. Dengan adanya penelitian, diharapkan pembaca dapat memperkokoh pemahaman bahwa puisi memengaruhi persepsi perempuan dalam masyarakat serta berkontribusi pada perubahan sosial dan budaya.
ANALISIS PROBLEMATIKA PEMBELAJARAN MATEMATIKA SEKOLAH MENENGAH PERTAMA
Authors: DHARSONO FARHAN MAULANA , Ratnaningsih Nani , Rahayu Diar Veni
Published: May 2024

This research aims to describe problems in mathematics learning and their solutions at Kawali 1 State Junior High School. The research method used in this research is a qualitative. The research subjects were six students from class IX and two mathematics teachers at SMP Negeri 1 Kawali who taught in class IX. The research instruments used in this research were observation, questionnaires and interviews. The learning problems that have been widely researched are problems related to students, even though teachers also need to be researched, so the advantage of this research is describing mathematics learning problems for students and teachers. The results of this research show the problems of mathematics learning at SMP Negeri 1 Kawali, namely that teachers are less innovative and creative when learning, less mature understanding of mathematical concepts, low ability of students to think creatively in mathematics, and low motivation of students. An alternative solution to this problem is that teachers must continue to learn or upgrade their knowledge regarding teaching styles, methods and learning media, teachers must be able to provide scaffolding, teachers must be able to train and hone students' creative thinking skills with learning that raises everyday problems that arise. non-routine, and the teacher must provide guidance and a psychological approach and the teacher must be clever in choosing suitable learning media in conveying Mathematics subject matter.
ANALISIS KESALAHAN SISWA DALAM MENYELESAIKAN SOAL FUNGSI KOMPOSISI DITINJAU DARI PERBEDAAN GENDER
Authors: Putra Eric Dwi , Rizqoh Zidna
Published: May 2024

This study was conducted with the aim of identifying errors that occur when students solve composition function problems by paying attention to gender differences. The research subjects were four students of class XI, two male students and two female students. The research method used was descriptive qualitative. Tests and interviews were conducted to collect data. The data were then analyzed by examining the students' answer sheets and classifying the errors made into four types, namely concept, principle, fact, and operation errors. The findings showed that male students made more errors than female students, especially in the category of fact and operation errors. Fact errors made by male students are errors in writing arithmetic operation signs, this is because male students do not understand the concept of multiplication and addition operation signs. While the error in determining the final answer was caused by an error in the previous process, where male students could not do the calculation correctly so that they got the wrong final result. The conclusion of this study confirms that female students have an advantage in the ability to solve math problems compared to male students.
The Making of the Celt. Ethnogenesis, Culture and Politics in the Atlantic Arc
Authors: Keating Michael
Published: May 2024

The theme of Celts and Celticism has attracted fierce controversy over more than two centuries. Passing over the question of ancient origins, this article places the birth of Celticism in the modern period, in line with current understandings of nationalism. Examining the construction of the Celt in Ireland, Scotland, Wales, Brittany, Galicia and Cornwall, it traces a movement from culture into politics in the course of the nineteenth century. Political pan-Celticism was ultimately a failure not because it was ‘artificial’ but because of the political conditions of the times and the force of competing projects. Like other nationalisms it relies on myth and tradition but these are social realities not easily to be dismissed by appeal to scientific history. After two hundred years, moreover, Celticism has a history of its own and continues to resonate both in culture and in politics.
KOMPETENSI MANAJERIAL PEJABAT PENGAWAS DALAM PERSPEKTIF PEJABAT PELAKSANA DI BADAN PENDAPATAN DAERAH KABUPATEN DONGGALA
Authors: Nasution Vivi Indra Amelia , Arianthi Mieke , Harta Ridho
Published: May 2024

ABSTRAK. Penelitian ini bertujuan untuk mengetahui tingkat kompetensi manajerial Pejabat Pengawas pada Badan Pendapatan Daerah Kabupaten Donggala yang didasarkan pada Standar Kompetensi Jabatan ASN sebagaimana diatur dalam Peraturan Menteri Pendayagunaan Aparatur Negara dan Reformasi Birokrasi Nomor 38 Tahun 2017, melalui persepsi Pejabat Pelaksana. Penelitian dilakukan melalui pendekatan deskriptif kualitatif untuk memberikan gambaran terkait kompetensi manajerial Pejabat Pengawas melalui persepsi Pejabat Pelaksana. Penelitian ini merupakan penelitioan studi kasus dab didukung oleh data yang bersumber pada hasil wawancara, observasi, dan dokumentasi. Wawancara dilakukan menggunakan purposive sampling dengan menentukan informan kunci. Terdapat sebelas Pejabat Pelaksana yang diwawancarai untuk melihat bagaimana kompetensi manajerial enam Pejabat Pengawas yang ada di Badan Pendapatan Daerah Kabupaten Donggala. Hasil penelitian menunjukkan bahwa sebagian besar Pejabat Pengawas belum mampu memenuhi lima dari delapan indikator kompetensi manajerial level dua sesuai indikator perilaku yang wajib dimiliki oleh Pejabat Pengawas. Adapun indikator kompetensi manajerial yang belum dapat dipenuhi yaitu orientasi pada hasil, mengelola perubahan, pelayanan publik, integritas, dan pengambilan keputusan. Sementara, indikator komunikasi, kerjasama, serta pengembangan diri dan orang lain, dipersepsikan sangat baik oleh Pejabat Pelaksana.
ÜNİVERSİTE ÖĞRENCİLERİNİN RUH SAĞLIĞI OKURYAZARLIĞI DÜZEYİNİN BELİRLENMESİ
Authors: Göktaş Ahmet , Utaş Mizgin , Fazla Özlem , Başkan Esra , Çoruh Sezen , Özbay Serhan
Published: May 2024

Bu araştırmanın amacı, üniversite öğrencilerinin ruh sağlığı okuryazarlığı düzeyini belirlemektir. Bu çalışma tanımlayıcı çalışma niteliğinde yapılmıştır. Çalışma bir üniversitede öğrenim gören 277 öğrencinin katılımıyla tamamlandı. Verilerin toplanmasında çevrimiçi olarak hazırlanan Kişisel Bilgi Formu ve Ruh Sağlığı Okuryazarlığı (RSOY) Ölçeği kullanıldı. Verilerin analizinde SPSS 26.0 kullanılmıştır. Araştırmaya 277 üniversite öğrencisi katılmıştır. Araştırmaya katılan öğrencilerin yaş ortalaması 21.88±2.90 ve %82.3’ü kadındır. Öğrencilerin %32.4’ü birinci sınıf, %80.5’i lisans öğrencisi ve %69’u sağlık bilimleri ile ilgili bir bölümde okumaktadır. Öğrencilerin %20.2’si ruh sağlığı ile ilgili eğitim almıştır. Öğrencilerin RSOY toplam puan ortalaması 14.97±3.50 olarak bulunmuştur. Ölçeğin bilgi odaklı, inanç odaklı ve kaynak odaklı RSOY puan ortalamaları sırasıyla 8.18±1.74, 4.42±2.05 ve 2.37±1.48 olarak bulunmuştur. Üniversite öğrencilerinin bilgi odaklı ruh sağlığı okuryazarlığı yüksek, inanç odaklı ruh sağlığı okuryazarlığı olumsuz, kaynak odaklı ruh sağlığı okuryazarlığı orta düzeylerdedir. Başta inanç odaklı ruh sağlığı okuryazarlığı olmak üzere genel olarak üniversite öğrencilerinin ruh sağlığı okuryazarlığı yeterli düzeyde değildir. Bütün öğrencilere yönelik kapsamlı eğitim programlarının düzenlenmesi önerilmektedir.
Advancing Practice for Regenerative Tomorrows
Authors: Cotsaftis Olivier
Published: May 2024

In an era characterised by the growing relevance of bio-based design solutions and the urgent need for transition to regenerative and more-than-human futures, a question arises: how can we nurture the growth of biodesigners? Here, a framework aimed at advancing biodesign practice and education is proposed, progressing from passive engagement with nature to active collaboration with living systems. This framework unfolds in three stages: designing with nature, for nature, and ultimately with living systems — reflecting a radical shift in the dynamics between designers and their environment. Equipped with principles of interconnectedness, regeneration and coexistence, the next generation of biodesigners is then positioned to drive the emergence of a bioeconomy and society serving the needs of both humanity and the planet. This framework underscores the transformative potential of cultivating biodesigners capable of reviving our connection with the broader web of life.
Утвердження та діяльність сестер Чину св. Василія Великого на Закарпатті та Пряшівщині у 20-х роках ХХ ст.
Authors: Ліхтей Ігор
Published: May 2024

Питання про організацію на Закарпатті обителі сестер василіянок постало на порядку денному восени 1921 р. Саме тоді активізувалися перемовини між монастирем сестер Чину св. Василія Великого (ЧСВВ) у Станіславові (нині – Івано-Франківськ) і духовними та світськими особами в Ужгороді, прихильними до ідеї поширення їхньої діяльності на теренах краю. Відтак зі Станіславова до Ужгорода прибули перші дві черниці та було започатковано процес створення монастиря. Щоправда, утвердження в Ужгороді сестер василіянок, кількість яких на початку 1922 р. зросла до п’яти, проходило з неабиякими труднощами. Адже на той час на Закарпатті не було належних умов для повноцінного функціонування чернечої обителі. Тож влітку 1922 р. сестри василіянки переїхали до Пряшева. Там вони перебували до осені 1924 р. За цей період сталися зміни в керівництві Мукачівської єпархії. У 1924 р. її новим очільником став єпископ Петро Гебей. На його побажання у вересні того ж року три черниці василіянки повернулися з Пряшева до Ужгорода. Так розпочалася їхня подвижницька місія на Закарпатті. Монахинь відразу ж було залучено до роботи в інтернаті для дівчат. У 1929 р. на Закарпатті налічувалося 28 сестер ЧСВВ. Вони опікувалися двома інтернатами й одним сиротинцем. Кілька василіянок залишилося на Пряшівщині. Там у їхньому віданні перебував сиротинець.
Schwannoma gástrico. Reporte de un caso
Authors: Montes N Darío , Cevallos R Nixon , Montes N Rubén
Published: May 2024

Introducción: Los schwannomas son tumores mesenquimatosos benignos de crecimiento lento, se originan en las células de Schwann de los nervios de los plexos Meiisner y Auebarch. Aunque pueden aparecer en cualquier localización, son poco frecuentes en el tracto gastrointestinal. Caso clínico: Nuestro caso es la presentación de un schawnnoma gástrico con evolución favorable y buen pronóstico tras su resección completa. Conclusión: La importancia de presentarlo radica en tenerlo presente en el diagnóstico diferencial de los tumores gástricos subepiteliales.
Optical non-linearities and applications of ZnS phosphors
Authors: Chauhan Ayushi , Sharma Rajesh , Singh Manjot , Sharma Reena
Published: May 2024

Optical non-linearities play a crucial role in enabling efficient and ultrafast switching applications that are essential for next-generation photonic devices. ZnS phosphor material produces the best results in terms of increased luminescence quantum yield when doped with certain impurities. Nevertheless, the investigation of the third-order non-linear optical susceptibility of the phosphor materials can be exploited for various switching applications. In this regard, we review the recent advancements in the investigation of non-linear optical properties of ZnS phosphors, where the knowledge of absorption and refraction is utilized in various optical and detector applications. Furthermore, the review highlights strategies employed to enhance the non-linear optical response of phosphor materials as well as a general discussion of an attosecond optical switching scheme which can be used to fabricate devices with petahertz speeds. Consequently, we provide a solution to the unsolved problem of the significant extension of optical limiting applications to switching applications by developing design strategies to manipulate conventional ZnS phosphor material. The potential challenges and future prospects of utilizing phosphor materials for switching applications are also addressed. The strategies for manipulating ZnS phosphor can be generalized for a broad range of other materials by minimizing linear and non-linear losses, while enhancing the values of the non-linear refractive index coefficient. We propose that the figure-of-merit of ZnS material can be enhanced by using a suitable combination of pump and probe wavelength values, which can be useful for optical switching applications.
Tongue feature recognition to monitor rehabilitation: deep neural network with visual attention mechanism
Authors: Yi Zhengheng , Lai Xinsheng , Sun Aining , Fang Senlin
Published: May 2024

Objective

We endeavor to develop a novel deep learning architecture tailored specifically for the analysis and classification of tongue features, including color, shape, and coating. Unlike conventional methods based on architectures like VGG or ResNet, our proposed method aims to address the challenges arising from their extensive size, thereby mitigating the overfitting problem. Through this research, we aim to contribute to the advancement of techniques in tongue feature recognition, ultimately leading to more precise diagnoses and better patient rehabilitation in Traditional Chinese Medicine (TCM).

Methods

In this study, we introduce TGANet (Tongue Feature Attention Network) to enhance model performance. TGANet utilizes the initial five convolutional blocks of pre-trained VGG16 as the backbone and integrates an attention mechanism into this backbone. The integration of the attention mechanism aims to mimic human cognitive attention, emphasizing model weights on pivotal regions of the image. During the learning process, the allocation of attention weights facilitates the interpretation of causal relationships in the model’s decision-making.

Results

Experimental results demonstrate that TGANet outperforms baseline models, including VGG16, ResNet18, and TSC-WNet, in terms of accuracy, precision, F1 score, and AUC metrics. Additionally, TGANet provides a more intuitive and meaningful understanding of tongue feature classification models through the visualization of attention weights.

Conclusion

In conclusion, TGANet presents an effective approach to tongue feature classification, addressing challenges associated with model size and overfitting. By leveraging the attention mechanism and pre-trained VGG16 backbone, TGANet achieves superior performance metrics and enhances the interpretability of the model’s decision-making process. The visualization of attention weights contributes to a more intuitive understanding of the classification process, making TGANet a promising tool in tongue diagnosis and rehabilitation.
Electromechanical efficiency index of skeletal muscle and its applicability: a systematic review
Authors: Turnsek Gasper , Paravlic Armin Huso
Published: May 2024

Introduction: The electromechanical efficiency of skeletal muscle represents the dissociation between electrical and mechanical events within a muscle. It has been widely studied, with varying methods for its measurement and calculation. For this reason, the purpose of this literature review was to integrate the available research to date and provide more insights about this measure.

Methods: A systematic search of the literature was performed across three online databases: PubMed, ScienceDirect, and SPORTDiscus. This yielded 1284 reports, of which 10 met the inclusion criteria. Included studies have used different methods to measure the electromechanical efficiency (EME) index, including electromyography (EMG), mechanomyography and tensiomyography (TMG).

Results: The EME index was used to assess muscle conditions such as muscle atrophy, pain syndromes, or to monitor rehabilitation in patients with knee problems, fatigue and the effects of exercise and rehabilitation. TMG has been shown to be one of the most reliable methods to obtain the EME index, but its use precludes obtaining the index during voluntary muscle contractions.

Conclusion: Standardizing the EME index is crucial for its diverse applications in clinical, sport, and rehabilitation contexts. Future research should prioritize standardization of measurement protocols for establishing the most repeatable, and reliable approach that can be used for inter-individual comparisons or for assessing an individual for multiple times over a longer period.

Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023440333 Identifier: CRD42023440333.
A mini review of mycotoxin’s occurrence in food in South America in the last 5 years: research gaps and challenges in a climate change era
Authors: Foerster Claudia , Müller-Sepúlveda Andrea , Copetti Marina Venturini , Arrúa Andrea Alejandra , Monsalve Liliam , Ramirez María Laura , Torres Adriana M.
Published: May 2024

Mycotoxins are natural metabolites produced by species of filamentous fungi belonging mainly to the genera Aspergillus, Fusarium, Penicillium, and Alternaria, which can grow in various crops and foodstuffs. The South American climate is diverse, varying from tropical, temperate, and arid to cold, ideal for the growth of different types of fungi and mycotoxin production. This mini review aimed to describe the natural occurrence of mycotoxin in food in South America from 2018 to 2023, identifying research gaps and challenges in an era of climate change. We analyzed 53 studies, 21 from Brazil. Most of the mycotoxins analyzed in South America were the traditional and regulated mycotoxins, with variable occurrences depending on the region, climatic conditions, and methodology used. Emerging and modified mycotoxins have only been studied in Argentina and Brazil, where some studies have shown high occurrences. Given this, it is essential to strengthen food safety laboratories and surveillance capabilities and establish early warning systems. It is also essential to continue working to raise awareness of mycotoxins as a public health issue and to study and prevent the impact of climate change on soil microbial population, the new prevalence of fungi, and the profile of toxigenic species. An effective connection and collaboration between disciplines and sectors in different countries is needed to meet this research challenge.
Non-invasive imaging techniques for early diagnosis of bilateral cardiac dysfunction in pulmonary hypertension: current crests, future peaks
Authors: Ahmad Ashfaq , Zou Yifan , Zhang Peng , Li Lingling , Wang Xiaoyu , Wang Yousen , Fan Fenling
Published: May 2024

Pulmonary arterial hypertension (PAH) is a chronic and progressive disease that eventually leads to heart failure (HF) and subsequent fatality if left untreated. Right ventricular (RV) function has proven prognostic values in patients with a variety of heart diseases including PAH. PAH is predominantly a right heart disease; however, given the nature of the continuous circulatory system and the presence of shared septum and pericardial constraints, the interdependence of the right and left ventricles is a factor that requires consideration. Accurate and timely assessment of ventricular function is very important in the management of patients with PAH for disease outcomes and prognosis. Non-invasive modalities such as cardiac magnetic resonance (CMR) and echocardiography (two-dimensional and three-dimensional), and nuclear medicine, positron emission tomography (PET) play a crucial role in the assessment of ventricular function and disease prognosis. Each modality has its own strengths and limitations, hence this review article sheds light on (i) ventricular dysfunction in patients with PAH and RV–LV interdependence in such patients, (ii) the strengths and limitations of all available modalities and parameters for the early assessment of ventricular function, as well as their prognostic value, and (iii) lastly, the challenges faced and the potential future advancement in these modalities for accurate and early diagnosis of ventricular function in PAH.
An efficient method for modeling and evaluating the bench terrain of open-pit mines
Authors: Wang Bonan , Gong Bing , Xu Wei , Shi Xiaoshan
Published: May 2024

In order to quantitatively analyze the roughness of the bench floor during open-pit mine blasting, this study proposes a real-time measuring method for the three-dimensional terrain of the bench floor during the excavation process. Real-time monitoring is conducted at the boundary and discrete internal points of the workbench floor during electric shovel operation, utilizing real-time kinematic global navigation satellite system (RTK-GNSS) positioning technology. An improved convex hull algorithm is introduced to automatically extract the optimal boundary of discrete point clouds based on their spatial distribution characteristics. This study establishes a digital elevation model (DEM) using five interpolation algorithms for 3D terrain visualization simulation. Through cross-validation, a comparative analysis of the DEM accuracy, the simulation results of the ordinary kriging interpolation algorithm were found to be optimized. The optimized interpolation algorithm is applied to simulate the 3D terrain in the Dexing open-pit copper mine, and the relevant terrain parameters were calculated. This dataset can serve as a precise foundation for the real-time path planning of elevation blasting design and ground leveling operations.
Identification of Milankovitch sedimentary cycle in Fengcheng Formation, Mahu depression: a case study of well Maye 1
Authors: Wang Ran , Chen Xuan , Chang Qiusheng , Zhao Xinmei
Published: May 2024

The sedimentary cycle of Fengcheng Formation in Junggar Basin changes rapidly and is difficult to identify. The low classification accuracy of high-frequency fine-grained sedimentary cycles restricts the exploration of unconventional shale oil and gas. Full-interval coring of well Maye 1 provides a solid foundation for small-layer research. In this paper, the high-frequency sedimentary cycle of Milan kovitch in Fengcheng Formation is studied by means of spectral analysis and wavelet transform, and the shale sweet spot is identified. The long period of eccentricity of 405ka, short period of eccentricity of 100ka and long period of axis slope of 42736a can be used as semi-quantitative basis for the classification of the fourth, fifth and sixth sequences. The Fengcheng Formation can be divided into 2 quaternary sequence cycles, 9 quaternary sequence cycles and 16 quaternary sequence cycles. A long period of eccentricity of 405ka can identify large-scale lake recessional and recessional, and there is a maximum lake flooding surface in the middle of the second Fengcheng Formation, which corresponds to high abundance of organic matter and high hydrocarbon generation potential. The 100ka short period eccentricity can identify the sweet spot layer, and there are 8 sweet spots in the well Maye 1, which is consistent with the results of nuclear magnetic interpretation. The research results provide a semi-quantitative basis for the classification of high-frequency sedimentary cycles and the identification of sweet spots of Fengcheng Formation in Mahu Sag, Junggar Basin.
Development of a fully implicit ODE-solver for containment analysis code
Authors: Huang Jun , Li Jinggang , Ma Yinxiang
Published: May 2024

The thermal–hydraulic dynamics in containment are governed by a system of stiff ordinary differential equations (ODEs). A fully implicit discretization scheme is adopted to discretize these ODEs in order to mitigate the effects of stiffness. In comparison with explicit or semi-implicit discretization schemes that are subject to Courant limits on time steps, the fully implicit discretization scheme is more suitable for a containment analysis code that focuses on predicting both short-term and long-term thermal–hydraulic parameters after an accident. This study introduces a general-purpose ODE solver for the containment analysis code. The outline of the solver is as follows: The fully implicit discrete equations lead to a large set of nonlinear equations that need to be solved using Newton’s iterative method. The partial derivative components in the Jacobi matrix are calculated by the perturbation method using finite difference approximation, which avoids the complicated derivation of partial derivatives. The scaling modification technique is incorporated into this ODE solver to deal with significant differences in unknown variable magnitudes, and the line search method is introduced to address the difficulty of obtaining an accurate root estimate with Newton’s method when the initial guess is far from the actual root. This proposed ODE solver was applied to two typical stiff ODE problems to test its stiffness-suppressed ability and to demonstrate that this proposed solver can perform calculations with a very large time step. Then, the CASSIA code, a containment analysis code developed by China Nuclear Power Technology Research Institute Co., Ltd (CNPRI), equipped with this ODE solver, was applied to the CSNI (Committee on the Safety of Nuclear Installations) benchmark problem and the Carolinas Virginia Tube Reactor (CVTR) test 3 problem to preliminarily demonstrate that the proposed ODE solver can perform containment thermal–hydraulic analysis correctly. This study could provide references for the development of a home-made containment analysis code.
Temperature compensation model for non-dispersive infrared CO2 gas sensor based on WOA-BP algorithm
Authors: Su Maoyuan , Chen Yumin , Li Qian , Wei Yang , Liu Jiansheng , Chang Zhengwei , Liu Xueyuan , Zhang Anan
Published: May 2024

Temperature compensation is the main measure to solve the problem that the detection accuracy of non-dispersive infrared CO2 gas sensor is affected by temperature. As the measurement accuracy of the non-dispersive infrared CO2 gas sensor is easily affected by the ambient temperature, this article analyzes the reasons why the sensor is affected by temperature, and proposes a temperature compensation method that integrates the Whale Algorithm (WOA) and BP neural network. The whale algorithm is used to optimize the weights and thresholds of the BP neural network to build a temperature compensation model for the non-dispersive infrared CO2 gas sensor and compare the superiority with the traditional BP neural network model and particle swarm optimization (PSO) BP neural network model. The experimental results show that the temperature compensation model error of WOA-BP algorithm is lower than 30 ppm, and the average absolute error percentage is 3.86%, which is far better than BP neural network and PSO-BP neural network, and effectively reduces the influence of temperature on the accuracy of the sensor.
Research progress of circRNA as a biomarker of osteoporosis
Authors: Du Xing , Chen Zhongyao , Shui Wei
Published: May 2024

Osteoporosis, as a chronic metabolic bone disease, has the characteristic of insidious disease progression, which often leads to relatively delayed disease diagnosis. Therefore, early screening for osteoporosis has become a major public health challenge. The latest research indicates that circRNA is widely involved in the regulation of bone metabolism and is closely related to the occurrence and development of osteoporosis. Based on its high degree of sequence conservation and stability, circRNA has the potential to become a new clinical biomarker. The study of biomarkers is generally based on body fluid samples or adjacent tissue samples, with blood being the most commonly used, which can be divided into sources such as serum, plasma, peripheral blood monocytes, and plasma exosomes. Therefore, this article aims to review the research status of circRNA as a biomarker of osteoporosis.
Clinico-genomic findings, molecular docking, and mutational spectrum in an understudied population with breast cancer patients from KP, Pakistan
Authors: Ahmad Hilal , Ali Asif , Khalil Ali Talha , Ali Roshan , Khan Ishaq , Khan Mah Muneer , Ahmed Ibrar , Basharat Zarrin , Alorini Mohammed , Mehmood Amna
Published: May 2024

In this study, we report the mutational profiles, pathogenicity, and their association with different clinicopathologic and sociogenetic factors in patients with Pashtun ethnicity for the first time. A total of 19 FFPE blocks of invasive ductal carcinoma (IDC) from the Breast Cancer (BC) tissue and 6 normal FFPE blocks were analyzed by whole-exome sequencing (WES). Various somatic and germline mutations were identified in cancer-related genes, i.e., ATM, CHEK2, PALB2, and XRCC2. Among a total of 18 mutations, 14 mutations were somatic and 4 were germline. The ATM gene exhibited the maximum number of mutations (11/18), followed by CHEK2 (3/18), PALB2 (3/18), and XRCC2 (1/18). Except one frameshift deletion, all other 17 mutations were nonsynonymous single-nucleotide variants (SNVs). SIFT prediction revealed 7/18 (38.8%) mutations as deleterious. PolyPhen-2 and MutationTaster identified 5/18 (27.7%) mutations as probably damaging and 10/18 (55.5%) mutations as disease-causing, respectively. Mutations like PALB2 p.Q559R (6/19; 31.5%), XRCC2 p.R188H (5/19; 26.31%), and ATM p.D1853N (4/19; 21.05%) were recurrent mutations and proposed to have a biomarker potential. The protein network prediction was performed using GeneMANIA and STRING. ISPRED-SEQ indicated three interaction site mutations which were further used for molecular dynamic simulation. An average increase in the radius of gyration was observed in all three mutated proteins revealing their perturbed folding behavior. Obtained SNVs were further correlated with various parameters related to the clinicopathological status of the tumors. Three mutation positions (ATMp. D1853N, CHEK2 p.M314I, and PALB2 p.T1029S) were found to be highly conserved. Finally, the wild- and mutant-type proteins were screened for two drugs: elagolix (DrugBank ID: DB11979) and LTS0102038 (a triterpenoid, isolated from the anticancer medicinal plant Fagonia indica). Comparatively, a higher number of interactions were noted for normal ATM with both compounds, as compared to mutants.
Causal relationship between inflammatory proteins and glioblastoma: a two-sample bi‑directional mendelian randomization study
Authors: Lin Xiang , Gao Wei , Huang Chen , Wu Minghua , She Xiaoling
Published: May 2024

Background: Observational studies have indicated a potential correlation between glioblastoma and circulating inflammatory proteins. Further investigation is required to establish a causal relationship between these two factors.

Methods: We performed a Mendelian randomization (MR) analysis using genome-wide association study (GWAS) summary of 91 circulating inflammation-related proteins (N = 14,824) to assess their causal impact on glioblastoma. The GWAS summary data for glioblastoma included 243 cases and 287,137 controls. The inverse variance weighted (IVW) method was used as the primary analytical method to assess causality. Four additional MR methods [simple mode, MR-Egger, weighted median, and weighted mode] were used to supplement the IVW results. Furthermore, several sensitivity analyses were performed to assess heterogeneity, horizontal pleiotropy, and stability. Reverse MR analysis was also performed. glioblastoma transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed to validate the findings obtained through MR, while pathway and functional enrichment analyses were conducted to predict the potential underlying mechanisms.

Results: Our findings from employing the inverse variance weighted method in our forward MR analysis provide robust evidence supporting a potential association between glioblastoma and elevated levels of Cystatin D, as well as decreased levels of fibroblast growth factor 21 (FGF21) in the circulation. Moreover, our reverse MR analysis revealed that glioblastoma may contribute to increased concentrations of C-X-C motif chemokine 9 (CXCL9) and Interleukin-33 (IL-33) in the bloodstream. Transcriptomic analysis showed that FGF21 expression was inversely associated with the risk of developing glioblastoma, whereas an increased risk was linked to elevated levels of CXCL9 and IL-33. Pathway and functional enrichment analyses suggested that Cystatin D might exert its effects on glioblastoma through intracellular protein transport, whereas FGF21 might affect glioblastoma via glucose response mechanisms.

Conclusion: These results indicate that FGF21 is a significant factor in glioblastoma susceptibility. Glioblastoma also affects the expression of inflammatory proteins such as C-X-C motif chemokine 9 and Interleukin-33, providing new insights into the mechanisms of glioblastoma genesis and clinical research.
Blood eosinophils levels in a Colombian cohort of biomass-and tobacco-related COPD patients
Authors: García Morales Olga Milena , Cañas-Arboleda Alejandra , Rodríguez Malagón María Nelcy , Galindo Pedraza Javier Leonardo , Rodríguez Torres Paola , Avendaño Morales Violeta Rosa , González-Rangel Andrés Leonardo , Celis-Preciado Carlos A.
Published: May 2024

Introduction

Chronic obstructive pulmonary disease (COPD) is a major cause of illness and death among adults. In 2019, the Global Initiative for Chronic Obstructive Lung Disease (GOLD) strategy incorporated blood eosinophils as a biomarker to identify patients at increased risk of exacerbations which, with the history of exacerbations during the previous year, allows identification of patients who would benefit from anti-inflammatory treatment to reduce the risk of future exacerbations. The aim of this study was to describe demographic and clinical characteristics, eosinophil counts, and exacerbations in a cohort of COPD patients stratified by clinical phenotypes (non-exacerbator, frequent exacerbator, asthma-COPD overlap) in a Colombian cohort at 2600 meters above sea level.

Methods

A descriptive analysis of a historical cohort of patients with a confirmed diagnosis of moderate to severe COPD (FEV1/FVC < 0.7 and at least one risk factor for COPD) from two specialized centers with comprehensive disease management programs was performed from January 2015 to March 2019. Data were extracted from medical records 1 year before and after the index date.

Results

200 patients were included (GOLD B: 156, GOLD E: 44; 2023 GOLD classification); mean age was 77.9 (SD 7.9) years; 48% were women, and 52% had biomass exposure as a COPD risk factor. The mean FEV1/FVC was 53.4% (SD 9.8), with an FEV1 of 52.7% (20.7). No differences were observed between clinical phenotypes in terms of airflow limitation. The geometric mean of absolute blood eosinophils was 197.58 (SD 2.09) cells/μL (range 0 to 3,020). Mean blood eosinophil count was higher in patients with smoking history and frequent exacerbators. At least one moderate and one severe exacerbation occurred in the previous year in 44 and 8% of patients, respectively; during the follow-up year 152 exacerbations were registered, 122 (80%) moderate and 30 (20%) severe. The highest rate of exacerbations in the follow-up year occurred in the subgroup of patients with the frequent exacerbator phenotype and eosinophils ≥300 cells/μL.

Discussion

In this cohort, the frequency of biomass exposure as a risk factor is considerable. High blood eosinophil count was related to smoking, and to the frequent exacerbator phenotype.
Individualized survival prediction and surgery recommendation for patients with glioblastoma
Authors: Zhu Enzhao , Wang Jiayi , Jing Qi , Shi Weizhong , Xu Ziqin , Ai Pu , Chen Zhihao , Dai Zhihao , Shan Dan , Ai Zisheng
Published: May 2024

Background

There is a lack of individualized evidence on surgical choices for glioblastoma (GBM) patients.

Aim

This study aimed to make individualized treatment recommendations for patients with GBM and to determine the importance of demographic and tumor characteristic variables in the selection of extent of resection.

Methods

We proposed Balanced Decision Ensembles (BDE) to make survival predictions and individualized treatment recommendations. We developed several DL models to counterfactually predict the individual treatment effect (ITE) of patients with GBM. We divided the patients into the recommended (Rec.) and anti-recommended groups based on whether their actual treatment was consistent with the model recommendation.

Results

The BDE achieved the best recommendation effects (difference in restricted mean survival time (dRMST): 5.90; 95% confidence interval (CI), 4.40–7.39; hazard ratio (HR): 0.71; 95% CI, 0.65–0.77), followed by BITES and DeepSurv. Inverse probability treatment weighting (IPTW)-adjusted HR, IPTW-adjusted OR, natural direct effect, and control direct effect demonstrated better survival outcomes of the Rec. group.

Conclusion

The ITE calculation method is crucial, as it may result in better or worse recommendations. Furthermore, the significant protective effects of machine recommendations on survival time and mortality indicate the superiority of the model for application in patients with GBM. Overall, the model identifies patients with tumors located in the right and left frontal and middle temporal lobes, as well as those with larger tumor sizes, as optimal candidates for SpTR.
Personalized anesthesia and precision medicine: a comprehensive review of genetic factors, artificial intelligence, and patient-specific factors
Authors: Zeng Shiyue , Qing Qi , Xu Wei , Yu Simeng , Zheng Mingzhi , Tan Hongpei , Peng Junmin , Huang Jing
Published: May 2024

Precision medicine, characterized by the personalized integration of a patient’s genetic blueprint and clinical history, represents a dynamic paradigm in healthcare evolution. The emerging field of personalized anesthesia is at the intersection of genetics and anesthesiology, where anesthetic care will be tailored to an individual’s genetic make-up, comorbidities and patient-specific factors. Genomics and biomarkers can provide more accurate anesthetic protocols, while artificial intelligence can simplify anesthetic procedures and reduce anesthetic risks, and real-time monitoring tools can improve perioperative safety and efficacy. The aim of this paper is to present and summarize the applications of these related fields in anesthesiology by reviewing them, exploring the potential of advanced technologies in the implementation and development of personalized anesthesia, realizing the future integration of new technologies into clinical practice, and promoting multidisciplinary collaboration between anesthesiology and disciplines such as genomics and artificial intelligence.
Identifying the risk factors of ICU-acquired fungal infections: clinical evidence from using machine learning
Authors: Zhao Yi-si , Lai Qing-pei , Tang Hong , Luo Ren-jie , He Zhi-wei , Huang Wei , Wang Liu-yang , Zhang Zheng-tao , Lin Shi-hui , Qin Wen-jian , Xu Fang
Published: May 2024

Background

Fungal infections are associated with high morbidity and mortality in the intensive care unit (ICU), but their diagnosis is difficult. In this study, machine learning was applied to design and define the predictive model of ICU-acquired fungi (ICU-AF) in the early stage of fungal infections using Random Forest.

Objectives

This study aimed to provide evidence for the early warning and management of fungal infections.

Methods

We analyzed the data of patients with culture-positive fungi during their admission to seven ICUs of the First Affiliated Hospital of Chongqing Medical University from January 1, 2015, to December 31, 2019. Patients whose first culture was positive for fungi longer than 48 h after ICU admission were included in the ICU-AF cohort. A predictive model of ICU-AF was obtained using the Least Absolute Shrinkage and Selection Operator and machine learning, and the relationship between the features within the model and the disease severity and mortality of patients was analyzed. Finally, the relationships between the ICU-AF model, antifungal therapy and empirical antifungal therapy were analyzed.

Results

A total of 1,434 cases were included finally. We used lasso dimensionality reduction for all features and selected six features with importance ≥0.05 in the optimal model, namely, times of arterial catheter, enteral nutrition, corticosteroids, broadspectrum antibiotics, urinary catheter, and invasive mechanical ventilation. The area under the curve of the model for predicting ICU-AF was 0.981 in the test set, with a sensitivity of 0.960 and specificity of 0.990. The times of arterial catheter (p = 0.011, OR = 1.057, 95% CI = 1.053–1.104) and invasive mechanical ventilation (p = 0.007, OR = 1.056, 95%CI = 1.015–1.098) were independent risk factors for antifungal therapy in ICU-AF. The times of arterial catheter (p = 0.004, OR = 1.098, 95%CI = 0.855–0.970) were an independent risk factor for empirical antifungal therapy.

Conclusion

The most important risk factors for ICU-AF are the six time-related features of clinical parameters (arterial catheter, enteral nutrition, corticosteroids, broadspectrum antibiotics, urinary catheter, and invasive mechanical ventilation), which provide early warning for the occurrence of fungal infection. Furthermore, this model can help ICU physicians to assess whether empiric antifungal therapy should be administered to ICU patients who are susceptible to fungal infections.
Case report: Uterine leiomyoma with fumarate hydratase deficiency
Authors: Bužinskienė Diana , Grinciūtė Dominyka , Šilkūnas Mindaugas , Šidlovska Evelina
Published: May 2024

Hereditary leiomyomatosis and renal cell cancer syndrome is a rare autosomal dominant disease caused by mutations in the fumarate hydratase gene. The syndrome is characterized by skin leiomyomatosis, uterine leiomyomatosis, and renal cell carcinoma. Herein, we report a case of fumarate hydratase deficient leiomyoma. The patient was a young female presenting with large uterine leiomyoma and multiple kidney angiomyolipomas. The report presents the chosen treatment and the challenges of differential diagnosis.