bluuebunny/crossref_metadata_2025 huggingface dataset:
The Big Bang Of The Interstellar Dirty Snow Ball Egg From Which The Solar System Originated
Authors: Yan Henghua
Published: December 2024

It is well known that the angular momentum distribution of the main celestial bodies of the solar system has been a puzzle problem to the astronomy circle. In fact, it is the implied proof that the solar system originated from the Big Bang of the Interstellar Dirty Snow Ball Egg (IDSB Egg). Through the expanding style of Big Bang, more than 99% of the original angular momentum of the Interstellar Dirty Snow Ball Egg (IDSB Egg) was transferred to the outer layer substance, which mostly had evolved to be the eight planets, and the residual angular momentum left to the Sun was only less than 1%. It is a fresh equivalent replacement method for the corresponding relationship between the main celestial bodies of the solar system (excluding the Moon) and the ancient plates group of the Earth. What’s more, it is accepted by the overwhelming majority of the geoscience community that the ancient plates distributed on the planet Earth and wandered by the human race and other animals had evolved from the breaking up of the unique supercontinent about 66 million years ago. Therefore, indirect proof has existed strongly on Earth that the solar system originated from the Big Bang of the Interstellar Dirty Snow Ball Egg (IDSB Egg). The Moon is not the original founder member of the birth of the solar system, and it had only something to do with the breaking up of the unique supercontinent of the planet Earth about 66 million years ago.
The Addis Declaration on Immunization: Assessing the Effectiveness and Efficiency of Immunization Service Delivery Systems in Africa as of End 2023
Authors: Mboussou Franck , Wiysonge Charles Shey , Farham Bridget , Bwaka Ado , Wanyoike Sarah , Petu Amos , Ndiaye Sidy , Bita Andre , Ticha Johnson , Amani Adidja , Obiang Regis , Bagayoko Magaran Monzon , Impouma Benido
Published: December 2024

To analyze African countries’ performance in achieving the fourth ADI commitment of the Addis Declaration on Immunization (ADI), a cross-sectional retrospective study was conducted including the 54 African Member States of the World Health Organization (WHO) out of 55 African Union (AU) Member States. The fourth ADI commitment aims at increasing the effectiveness and efficiency of immunization delivery systems and has four performance indicators. The median percentage of districts with less than 10% of dropout rate between DTP1 and DTP3 was 86.5%, ranging from 22% to 100%. Thirty-four countries (63%) recorded 80% or above districts with less than 10% dropout rate between DTP1 and DTP3. Eleven countries (20.3%) and 10 countries (18.5%) sustained 90% or above coverage for DTP3 and MCV1, respectively, in the past three years (2021-2023). Four countries (7.4%) had 44.5 skilled health workers per 10,000 people. Out of the 54 WHO Member States, seven achieved at least three of the four indicators of the fourth ADI commitment. It is critical, as a follow-up to this study, to document best practices from these seven countries that achieved the fourth ADI commitment. Additionally, a deeper analysis of factors associated with achieving the ADI commitments is required.
Modeling ALS with Patient-Derived iPSCs: Recent Advances and Future Potentials
Authors: Dawoody Nejad Ladan , Pioro Erik P
Published: December 2024

Amyotrophic lateral sclerosis (ALS) is a terminal complex neurodegenerative disease, with 10%-15% of cases being familial and the majority being sporadic with no known cause. We lack models for the 85-90% sporadic ALS cases. More creative, sophisticated models of ALS disease are required to unravel the mysteries of this complicated disease. While ALS patients require new medications and treatments urgently, suitable pre-clinical in vitro models for drug screening are lacking. Therefore, human-derived induced pluripotent stem cell (hiPSC) technology offers the opportunity to model diverse and unreachable cell types in a culture dish. In this review, we focus on recent hiPSC-derived ALS neuronal and non-neuronal models to examine the research progress of current ALS 2D monocultures, cocultures, and more complex 3D-model organoids. Despite the challenges inherent to hiPSC-based models, their application to preclinical drug studies is enormous.
In-Situ Osmundaceous Ferns-Dominated Landscapes in the Jurassic of Patagonia: A Case of Ecological Stasis from the Deseado Massif, Santa Cruz, Province, Argentina
Authors: García Massini Juan Leandro , Nunes Giovanni Cristian , Yañez Agustina , Escapa Ignacio Hernán , Guido Diego
Published: December 2024

Herein, we report the presence of a plant paleocommunity dominated by ferns of the family Osmundaceae embedded in siliceous chert blocks from the only known Mesozoic, fossiliferous geothermal deposits, from the La Matilde Formation (Middle-Upper Jurassic), in the Deseado Massif, southern Patagonia, Argentina. A total of 13 blocks sampled in an area of approximately 250 m2, which includes multiple structurally preserved, monotypic, in-situ, rhizomatous stems of Osmundaceae, embedded within their original swampy substrate are documented. Additional Osmundaceae and other ferns, and conifers are present in chert levels adjacent to the previous blocks. This mimics similar monotypic associations of Osmundaceae in high-altitude lagoons in northeastern Argentina in the middle of the Paraná Forest, suggesting that the fern assemblage found occupied similar open spaces in the Jurassic, becoming preserved in analogous configurations. In addition, observation of the preserved fern tissues and surrounding substrate revealed a variety of interacting microorganisms, which are comparable to those that make up the microbiological communities inhabiting modern osmundaceous environments. This finding reveals a case of ecological stasis, where members of the same fern family separated by more than 150 million years formed similar exclusive groupings of individuals in microecosystems of comparable structure and general characteristics.
A Novel Method to Forecast Nitrat Concentration Levels in Irrigation Areas Using ANN Model
Authors: Karahan Halil , Erkan Can Müge
Published: December 2024

In this study, an ANN-based model was developed to predict nitrate concentrations in drainage waters based on parameters that are easier and cheaper to measure in an irrigation area within the Lower Seyhan Basin, one of Turkey's important agricultural production regions. For this purpose, daily water samples were collected from a drainage measurement station during the 2022 and 2023 water years, and nitrate concentrations were determined in the laboratory. In addition to nitrate concentrations, other parameters, such as flow rate, EC, pH, and precipitation, were also measured simultaneously. The complex relationship between measured nitrate values and other parameters, which are easier and less costly to measure, was used in two different scenarios during the training phase of the ANN-Nitrate model. After the model was trained, nitrate values were estimated for the two scenarios using only the other parameters. In Scenario I, random values from the dataset were predicted, while in Scenario II, predictions were made as a time series, and model results were compared with measured values for both scenarios. The proposed model can be confidently used to fill gaps in the dataset (Scenario I) as well as to predict nitrate values in a time series (Scenario II).
The Impact of Covid-19 Pandemic on Thyroid Pathology in Mureș County, Romania: A Six-year Retrospective Study
Authors: Cătană Ramona Teodora , Nechifor-Boila Adela , Zahan Ancuța , Militaru Andreea Deborah , Radu Georgian-Nicolae , Borda Angela
Published: December 2024

Background/Objectives: In this study we aimed to assess the impact of Covid-19 pandemic period on the epidemiological trend of thyroid pathology in a university hospital in Romania. Methods: We performed a 6-years retrospective study (2017-2022) including all patients who underwent thyroid surgery, registered in the Pathology Department, Emergency County Hospital, Târgu-Mureș, Romania (n=971). Thyroid lesions were grouped into 3 major categories: (1) benign, non-tumoral, (2) benign, tumoral and (3) malignant, tumoral. To assess the impact of Covid-19 pandemic on the annual rate of thyroid surgeries and thyroid pathology, data were analyzed in comparison: before Covid-19 (2017-2019) versus Covid-19 and post-Covid-19 (2020-2022) period. Results: A significant decrease in the mean number of thyroid specimens per year was observed in the Covid-19 and post-Covid-19 period, compared to the previous period (131 versus 192 cases, p=0.0023). Thyroid benign lesions were the most frequent, but their prevalence was significantly lower during the pandemic period (50.8%), compared to the previous period (58.6%) (p=0.017). Benign tumors were rare, revealing similar occurrence rates in both periods. By contrast, the annual rate of malignant tumors increased significantly during Covid-19 and post-Covid-19 period (26.3% versus 35.4%, p=0.002), the most common histopathological type being papillary thyroid carcinoma. Conclusion: Along with Covid-19 pandemic (year 2020), due to reduced access to medical investigations, many thyroid cancers remained undiagnosed in our hospital. Consequently, this has led to an increased prevalence of malignant cases in the years that came after.
Characterization of Anthocyanins Including Acetylated Glycosides from Highbush Blueberry (Vaccinium corymbosum L.) Cultivated in Korea Based on UPLC-DAD-QToF/MS and UPLC-Qtrap-MS/MS
Authors: Kim Ju Hyung , Kwon Ryeong Ha , Kim So Ah , Na Hyemin , Cho Jeong-Yong , Kim Heon-Woong
Published: December 2024

In this study, anthocyanin glycosides from nine cultivars of highbush blueberries grown in Korea were characterized using UPLC-DAD-QToF/MS and UPLC-Qtrap-MS/MS. A total of twenty-two derivatives were identified, consisting of mono-glycosides with galactose, glucose, arabinose, acetyl-galactose, or acetyl-glucose moieties attached to aglycones such as cyanidin, peonidin, delphinidin, petunidin, and malvidin. Among them, seven acetylated glycosides were tentatively determined by comparing the related authentic standards and previous reports, and presented mass fragmentation in which the acetyl group remained as form attached to the sugar without deesterification in positive ionization mode. The mid-season cultivar ‘New Hanover’ showed the highest total anthocyanin content (1011.7 mg/100 g dry weight) with predominant malvidin and delphinidin glycosides. Particularly, the ‘Patriot’ (early-season) recorded the highest proportion of acetylated glycosides (19.7%). These detailed anthocyanin profiles will be supported as fundamental data for the development of superior cultivars and functional blueberry-based products as well as the further research of anthocyanin changes by cultivars, harvest time, cultivated methods, storage conditions, etc..
A Forgotten Rare Cause of Unilateral Basal Ganglia Calcinosis Due to Venous Angioma, and Complicating Acute Stroke Management: A Case Report and Literature
Authors: Balodis Arturs , Strautmane Sintija , Zariņš Oskars , Verzemnieks Kalvis , Vētra Jānis , Pavlovičs Sergejs , Naudiņš Edgars , Kupčs Kārlis
Published: December 2024

Background. Unilateral basal ganglia calcinosis (BGC) is a rare radiological finding that can be diagnosed on CT and MRI but often presents challenges for clinicians and radiologists in determining its underlying cause. So far, only a few potential causes that could explain unilateral basal ganglia calcification have been described in the literature. Case Report. A 54-year-old Caucasian male was admitted to a tertiary university hospital due to the sudden onset of speech impairment and right-sided weakness. The patient had no significant medical history prior to this event. Non-enhanced computed tomography (NECT) of the brain revealed no evidence of acute ischemia, CTA shows acute MCA M2 segment occlusion. CT perfusion (CTP) maps reveal an extensive penumbra-like lesion, which is potentially reversible upon achieving successful recanalization. However, a primary neoplastic tumor with calcifications in the basal ganglia was initially interpreted as the potential cause, therefore, acute stroke treatment with intravenous thrombolysis was contraindicated. A follow-up CT examination at 24 hours revealed an ischemic lesion localized to the left insula, predominantly involving the left parietal lobe and the superior gyrus of the left temporal lobe. Subsequent gadolinium-enhanced brain MRI revealed small blood vessels draining into the subependymal periventricular veins on the left basal ganglia. Digital subtraction angiography was conducted, confirming the diagnosis of venous angioma. Conclusion. Unilateral BGC caused by venous angioma is a rare entity with unclear pathophysiological mechanisms and heterogeneous clinical presentation. It may mimic conditions such as intracerebral hemorrhage or hemorrhagic brain tumors, complicating acute stroke management, as demonstrated in this case. Surrounding tissue calcification may provide a valuable radiological clue in diagnosing venous angiomas DVAs and vascular malformations.
A Survey on Advancements in Scheduling Techniques for Efficient Deep Learning Computations on GPUs
Authors: Kaur Rupinder , Asad Arghavan , Al Abdul Wahid Seham , Mohammadi Farah
Published: December 2024

This comprehensive survey explores recent advancements in scheduling techniques for efficient deep learning computations on GPUs. The article highlights challenges related to parallel thread execution, resource utilization, and memory latency in GPUs, which can lead to suboptimal performance. The surveyed research focuses on novel scheduling policies to improve memory latency tolerance, exploit parallelism, and enhance GPU resource utilization. Additionally, it explores the integration of prefetching mechanisms, fine-grained warp scheduling, and warp switching strategies to optimize deep learning computations. Experimental evaluations demonstrate significant improvements in throughput, memory bank parallelism, and latency reduction. The insights gained from this survey can guide researchers, system designers, and practitioners in developing more efficient and powerful deep learning systems on GPUs. Furthermore, potential future research directions include advanced scheduling techniques, energy efficiency considerations, and the integration of emerging computing technologies. By continuously advancing scheduling techniques, the full potential of GPUs can be unlocked for a wide range of applications and domains, including GPU-accelerated deep learning, task scheduling, resource management, memory optimization, and more.
Leveraging Thermal Infrared Imaging for Pig Ear Detection and Temperature Distribution Research: The TIRPigEar Dataset and New Deep Learning Model Performances
Authors: Ma Weihong , Wang Xingmeng , Yang Simon X. , Benjamin Madonna , Song Lepeng , Li Qifeng
Published: December 2024

The stable physiological structure and rich vascular network of pig ears more easily form distinct thermal characteristics, representing pig body temperature. Using thermal infrared imaging to identify pig ears offers a feasible approach to analyzing individual pig health status. Based on this background, a dataset comprising 23,189 thermal infrared images of pig ears (TIRPigEar) was established. The TIRPigEar dataset was obtained through a pig house health inspection robot equipped with an infrared thermal imaging device, with post-processing conducted via manual annotation. By labeling pig ear targets within these images, a total of 69,567 labeled files were generated, which can be directly used for training pig ear detection models and enabling the analysis of pig temperature information by integrating the corresponding thermal imaging data. To validate the dataset's utility, it was evaluated across various object detection algorithms. Experimental results show that the dataset achieves the highest precision, recall, and mAP50 on the YOLOv9m model, reaching 97.35%, 98.1%, and 98.6%, respectively. Overall, the TIRPigEar dataset demonstrates optimal performance when applied to the YOLOv9m algorithm. Utilizing thermal infrared imaging technology to detect pig ear information provides a non-contact, rapid, and effective method. Establishing the TIRPigEar dataset is highly significant, as it allows for a valuable resource for AI and precision livestock farming researchers to validate and improve their algorithms. This dataset will support many researchers in advancing precision livestock farming by enabling more accurate and timely pig-ear temperature analysis.
Pengaruh Metode Seleksi Fitur terhadap Akurasi Model SVM dalam Klasifikasi Customer Churn pada Perusahaan Telekomunikasi
Authors: Rohmaniar Mayke Andani , Habibi Roni , Pane Syafrial Fachri
Published: December 2024

Abstrak:

Penelitian ini menganalisis pengaruh metode seleksi fitur terhadap akurasi model Support Vector Machine dalam memprediksi pelanggan di industri telekomunikasi. Empat metode seleksi fitur (Correlation Matrix, PCA, dan GA) dan empat kernel (Linear, Polynomial, RBF, dan Sigmoid) dibandingkan menggunakan dataset pelanggan telekomunikasi dari Kaggle dengan 7043 entri dan 33 fitur. Metodologi CRISP-DM digunakan, meliputi Pemahaman Bisnis, Pemahaman Data, Persiapan Data, Pemodelan, Evaluasi, dan Implementasi. Hasil penelitian menunjukkan bahwa metode seleksi fitur menggunakan Correlation Matrix dengan kernel Linear memberikan kinerja terbaik. Model ini mencapai akurasi tertinggi sebesar 92,48%, dengan precision 0,93, recall 0,97, dan f1-score 0,95. Metode seleksi fitur lainnya, seperti PCA dan GA, memberikan hasil yang lebih rendah dibandingkan dengan Correlation Matrix. Implementasi model prediksi yang akurat diharapkan dapat membantu perusahaan telekomunikasi mengembangkan strategi retensi pelanggan yang lebih efektif.

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Abstract:

This study examines the impact of various feature selection methods on the accuracy of the Support Vector Machine (SVM) model in predicting customer behavior within the telecommunications sector. Specifically, the research compares four feature selection techniques: Correlation Matrix, Principal Component Analysis (PCA), and Genetic Algorithm (GA). Additionally, it evaluates the performance of four SVM kernels: Linear, Polynomial, Radial Basis Function (RBF), and Sigmoid. Utilizing a telecom customer dataset from Kaggle, which comprises 7043 entries and 33 features, the study adheres to the CRISP-DM methodology. This methodology includes phases such as Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Implementation. The findings indicate that the Correlation Matrix feature selection method, when paired with the Linear kernel, provides the best performance. This particular configuration achieves the highest accuracy rate of 92.48%, along with a precision score of 0.93, a recall score of 0.97, and an F1-score of 0.95. In contrast, other feature selection methods, such as PCA and GA, result in lower performance metrics. These findings underscore the effectiveness of the Correlation Matrix and Linear kernel combination in enhancing the predictive accuracy of SVM models.
Monitoring Tekanan Ban Sepeda Motor Portable Berbasis Android
Authors: Kusriyanto Medilla , Frebiyani Atika , Kurniawan Rafli Mustafid , Pramono Wahyudi Budi
Published: December 2024

Abstrak:

Keselamatan berkendara merupakan salah satu aspek yang sangat penting dalam penggunaan kendaraan bermotor, termasuk sepeda motor. Salah satu faktor yang sering diabaikan namun memiliki dampak besar terhadap keamanan dan efisiensi kendaraan adalah tekanan udara pada ban. Tekanan ban yang tidak sesuai standar dapat menyebabkan penurunan stabilitas, meningkatkan konsumsi bahan bakar, hingga memperbesar risiko kecelakaan. Penelitian ini mengembangkan sistem monitoring tekanan ban motor dengan perangkat smartphone menggunakan komunikasi Bluetooth. Sistem dibuat dengan integrasi sensor MD-PS002, HX-711, ESP32 dan smartphone. Aplikasi pada smartphone akan menampilkan tekanan ban sepeda motor dan memberi peringatan jika tekanan tidak sesuai standar. Hasil pengujian menunjukkan bahwa sistem dapat bekerja dengan baik dengan prosentase kesalahan sebesar 2,7%. Perangkat ini menawarkan solusi praktis dengan antarmuka yang sederhana.

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Abstract:

Safety is an essential aspect of using motorized vehicles, including motorbikes. One factor that is often overlooked but significantly impacts vehicle safety and efficiency is the air pressure in the tyres. Tyre pressure not up to standard can cause decreased stability, increased fuel consumption, and increased risk of accidents. This research develops a motorcycle tyre pressure monitoring system with a smartphone device using Bluetooth communication. The system was created by integrating the MD-PS002, HX-711, ESP32, and smartphone sensors. The smartphone application will display the motorbike tyre pressure and warn if the pressure does not meet the standard. The test results show that the system can work well with an error percentage of 2.7%. This device offers a practical solution with a simple interface.
Development of Project Based Learning Media Using Google Sites on Alternative Energy Topics
Authors: Laluna Tazkia Dick , Supurwoko Supurwoko , Zahroh Shofi Hikmatuz
Published: December 2024

Learning is carried out to arrange and organize the environment around students to foster their learning process. The student's learning process is carried out through inquiry, responding to questions regarding a problem or a complex challenge. This learning process can be conducted by applying the project-based learning model. The project-based learning model can be applied in the field of information and communication technology in line with the 21st century, such as using Google Sites. Therefore, this research aims to describe the specifications of Google Sites as a learning media using the project-based learning model on alternative energy topics and describe the assessment results from experts, educational practitioners, and learners regarding Google Sites as a learning media using the project-based learning model on alternative energy materials. This development research employs the 4D model by Thiagarajan, which consists of the following stages: define, design, develop, and disseminate. The learning media obtained validation from two experts and assessment from educational practitioners regarding content, media, and language aspects. The development trial of this media was conducted with phase E students. Data collection techniques included interviews and questionnaires, with data analysis performed qualitatively and quantitatively. The learning media comprises a primary topic, alternative energy, organized based on project-based learning syntax. It consists of three menus: the welcome menu, the main page, and the author's identity. Validation by experts and assessment by educational practitioners indicate that the learning media meets excellent content, media, and language criteria. The development trial results show that the learning media meets excellent criteria at each trial stage.
Effectiveness and safety of direct oral anticoagulants in patients with atrial fibrillation and chronic kidney disease: a systematic review and meta-analysis of clinical trials
Authors: Mezhonov E. M. , Safiullina Z. M. , Vyalkina Y. A. , Shalaev S. V.
Published: December 2024

Aim. To analyze published clinical trials to evaluate the safety and effectiveness of direct oral anticoagulants in comparison with warfarin in a population of patients with atrial fibrillation and chronic kidney disease stages C4-C5.Material and methods. The meta-analysis was conducted in accordance with PRISMA guidelines based on a literature search in the PubMed/MEDLINE database for the period from 01 January 2018 to 25 December 2023. Keywords included the MeSH terms "atrial fibrillation" and "dialysis" or "hemodialysis" or "end-stage kidney disease" or "end-stage renal disease" or "advanced renal disease" or "stage 4 or 5 chronic kidney disease" or "stage 5 chronic kidney disease" and "non-vitamin K antagonist oral anticoagulants" or "direct oral anticoagulants" or "novel oral anticoagulant" or "NOAC" or "DOAC" or "dabigatran" or "apixaban" or "rivaroxaban" and "vitamin K antagonist" or "warfarin" and "outcomes". ROBINS-I and RoB2 tools were used to assess the systematic error of the research.Results. When searching the literature based on the chosen strategy, 1,895 publications were selected, some of which were excluded due to inconsistency with the inclusion criteria; as a result, 13 studies that did not have exclusion criteria were included in the analysis. The meta-analysis included 60,109 patients from 13 studies, 9,991 of whom received direct oral anticoagulants and 50,118 received warfarin. The results showed that in patients with stage C4-C5 chronic kidney disease treated with direct oral anticoagulants, ischemic stroke/systemic embolism was 26% less likely to develop compared with warfarin (HR=0.74, 95% CI 0.57–0 .95, p=0.02). The pooled effect of direct oral anticoagulant treatment demonstrated a lower risk of major bleeding (HR=0.74, 95% CI 0.67–0.82, p<0.001). There was a trend towards a reduction in the risks of both intracranial hemorrhage (HR=0.70, 95% CI 0.49–1.00, p=0.05) and major gastrointestinal bleeding compared with warfarin (HR=0.87, 95% CI 0.76–1.00, p=0.05). When analyzing all-cause mortality, direct oral anticoagulant therapy was also associated with a 14% reduction (HR=0.86, 95% CI 0.80–0.92, p<0.001).Conclusion. Our meta-analysis shows that in a population of patients with atrial fibrillation and stage C4 and C5 chronic kidney disease, therapy with direct oral anticoagulants compared with warfarin is associated with greater effectiveness and safety in reducing the risks of ischemic stroke/systemic embolism and major bleeding.
The main misconceptions in cardiology concerning obesity
Authors: Eliashevich S. O. , Ignatiadi A. S. , Misharova A. P. , Drapkina O. M.
Published: December 2024

This article reviews common myths and stereotypes about obesity that distort the understanding of its causes and pathogenesis and contribute to the disease stigmatization among the cardiology medical community. Obesity is a chronic, relapsing, multifactorial disease characterized by excessive formation of adipose tissue, progressing in its natural course and, as a rule, having an increased cardiometabolic risk. For effective prevention of complications, it is necessary to start treating obesity at the risk and pre-disease stages (abdominal obesity and overweight). The causes of obesity include genetic, metabolic, social and environmental factors. The review emphasizes that obesity is not exclusively a consequence of a lack of willpower in choosing food products according to the rules of healthy eating or a sedentary lifestyle. Many stereotypes, such as the idea that all patients with excess body weight have an alimentary genesis of the disease and all clinical "findings" are associated with obesity, do not correspond to reality and hinder effective prevention and treatment strategies. No other chronic non-communicable disease is as stigmatized as obesity. Moreover, despite the development of modern pharmacotherapy, behavioral therapy for obesity, and bariatric surgery, there is high clinical inertia in timely initiation of treatment for this disease. Body weight is becoming the same target indicator in general therapeutic practice as blood pressure or glycemia. Modern medicine dictates the need to rely solely on the evidence base to refute myths in order to create a more inclusive and supportive environment that promotes the health and well-being of patients.
Conway Lake ecosystem restoration : soil investigations to support Engineering With Nature® and beneficial use of dredged sediment
Authors: Theiling Charles , McFarlane Aaron , Berkowitz Jacob , Suedel Burton
Published: December 2024

The purpose of this Technical Note is to describe Conway Lake ecosystem restoration adaptive management investigations to evaluate forest planting and soil response to three depths of fine sediment placed over a sand base.
Health of Islamic Banks in Indonesia After the Covid-19 Pandemic: Financial Performance Analysis
Authors: Rizal Fitra
Published: December 2024

Introduction: The Covid-19 pandemic has significantly impacted the global financial sector, including Indonesia. This study aims to analyze the health level of Islamic Commercial Banks after the Covid-19 pandemic in Indonesia using the NPF, ROA, and CAR Ratios from January 2020 to June 2024. Research Methods: The research method used is qualitative with a descriptive approach. Result: The study results show that the average NPF ratio of Islamic Commercial Banks in 2020-2024 was 2.44%, indicating that Islamic Commercial Banks are Healthy. The smaller the NPF, the healthier the bank. The average ROA ratio of Islamic Commercial Banks in 2020-2024 was 1.77%, indicating that Islamic Commercial Banks are in a very healthy condition. The greater the ROA, the healthier the bank. The average CAR ratio of Islamic Commercial Banks 2020-2024 of 24.91% shows that Islamic Commercial Banks are in a very healthy condition. The greater the CAR, the healthier the bank. Conclusion: From the study results above, it can be concluded that the health level of Islamic commercial banks in Indonesia after the Covid 19 pandemic is very well maintained. This confirms that Islamic banks in Indonesia have resilience in facing the economic crisis. This provides confidence for stakeholders to continue investing and participating in the Islamic financial ecosystem.
Reduced-Order Modeling for Subsurface Flow Simulation in Fractured Reservoirs
Authors: Gao Ming , Sun Wenyue , Xu Jianchun , Li Junchao
Published: December 2024

Reservoir simulation for fractured reservoirs is often challenging and time-consuming due to the strong heterogeneity and complex flow dynamics introduced by fracture-matrix interactions. In this study, we introduce a novel reduced-order modeling procedure to speed up the flow simulation of fractured reservoirs. The reduced-order model (ROM) is developed based on proper orthogonal decomposition (POD) in conjunction with the embedded discrete fracture model (EDFM) that provides full-order simulation results. With the full-order training simulation, snapshots of reservoir pressure and saturation state at different timesteps are captured and assembled into separate data matrices. Singular value decomposition (SVD) is then applied to these data matrices to obtain a reduced set of orthogonal base vectors for pressure and saturation solutions, respectively. These base vectors enable the projection of high-dimensional linear equations into much lower-dimensional spaces, which significantly accelerates the process of solving nonlinear governing equations under the EDFM approach. The developed reduced-order modeling procedure is implemented in the MATLAB reservoir simulation toolbox (MRST) and tested via multiple cases for both 2D and 3D fractured reservoirs under different boundary and well control scenarios. In certain challenging cases, the use of multiple training simulations is explored and is shown to provide improved predictions. Overall, the proposed ROM approach is able to provide simulation results that are very consistent with those obtained from the full-order simulations while achieving computational speedups of about an order of magnitude for large-scale cases. These observations indicate that the proposed ROM exhibits satisfactory generalization performance, making it suitable for problems that require many flow simulations under different settings, such as production optimization.
Meteorological indicators as predictor of timing and duration of malaria transmission
Authors: Bello Abdulrahman Babatunde , Hassan Adesola , Ayeola Nurain
Published: December 2024

Satellite derived climate variables are potential indicators malaria transmission season. However, there is dearth of information required for investigating the relationship between climate and malariometric data. The influence of climatic risk variables on the temporal distribution of malaria in Epe and Ibeju Lekki (IbL) Local Government Areas (LGAs), Nigeria was assessed. Monthly malaria cases data of Epe and IbL LGAs, from January, 2018 to June, 2019 was obtained from Ministry of Health, Lagos. Monthly climate data including rainfall, maximum and minimum temperatures, and relative humidity of Lagos was obtained from the Nigerian Meteorological Agency (NIMET). Association between monthly malaria cases and climate parameters was analysed using principal component analysis. Malaria cases was highest (2157) in May, 2018 and lowest (874) in March, 2018 in Epe while IbL recorded the highest (2886) in May, 2019 and lowest (1435) in June. Monthly malaria cases variation was significant in Epe, P < 0.05 and IbL, P < 0.05. Monthly malaria cases inversely varied between Epe and IbL r = -0.16. Biplot axis one (F1) of the principal component plan was explained positively by rainfall (Eigen Vector, EV = 0.85) and relative humidity (EV = 0.81), related to positive malaria predictor in Epe (EV = 0.22) and IbL (EV = 0.09), while negative predictors were maximum temperature (EV = -0.91) and minimum temperature (-0.74). The positive relationship between malaria cases, and rainfall and relative humidity in both Epe and IbL is an indication of a geographic location independence of the impact of the meteorological indices on malaria heterogeneity.
Chatter detection in turning using axis drive motor current
Authors: Jasiewicz Marcin , Miądlicki Karol , Powalka Bartosz
Published: December 2024

This article presents a sensorless method for the detection of chatter vibrations in turning. The method is based on the analysis of the currents generated during machining on the axis drives, which are recorded directly by the CNC control of the machine tool. An extensive experimental study was planned and carried out, which, in addition to electrical quantities, monitored the state of the process using classical sensors (accelerometers and microphone). Preliminary spectral analysis showed that machining vibrations are revealed in the axis drives, and the currents that carry information about machining vibrations are the torque components of the stator currents for the tool head axes. Due to the necessity of observing non-electrical phenomenon (vibration), it was essential to adequately process the current signal in order to filter the components resulting from electrical phenomena. For this purpose, a signal processing algorithm was proposed, including the determination of the cross power spectral density of x and z-axis currents. Spectral entropy indices calculated in frequency bands containing local maxima are then used to classify the state of the cutting process in terms of chatter. The efficiency of the method, understood as the correctness of the identification of cutting status exceeds 95%. The paper concludes with a discussion.
Televisit with TytoHome TM device in medically complex child in long-term mechanical ventilation: a pilot study
Authors: Onofri Alessandro , Ullmann Nicola , Verrillo Elisabetta , Paglietti Maria Giovanna , Pavone Martino , Cutrera Renato
Published: December 2024

Background
During the pandemic, the pneumology physician team of Bambin Gesù Children’s Hospital pointed out that the use of telemedicine was a helpful modality to follow up on the medical needs in Children with medical complexity (CMC) patients at distance. After the telemedicine approach experienced during the emergency, a telemedicine service was set up and new tools were tested to optimize the televisit and the global eHealt approach of the patient. In this respect, TytoHome TM device was tested to carry out the objective examination remotely. The pilot study carried out in our hospital investigated the management of the CMC in long-term mechanical ventilation through telemedicine platform and the device built by TytoHome.
Methods
A total of 10 pediatric patients were treated for one year of study. The patients involved were already followed in our hospital, and underwent long-term mechanical ventilation (LTV) at home, 4 in Invasive Mechanical Ventilation (VMI), 6 in Non Invasive Ventilation (NIV). A database was developed for the collection of patient datas relating to personal data, vital parameters, objective examination, audio quality, patient satisfaction. A subsequent descriptive analysis has been carried out.
Results
The families were “satisfied” with the remote follow-up visits and the health-care personnel perceived as “good” the quality of the ongoing audio of visits.
Conclusions
In conclusion, several were the advantages brought from Tyto device to the remote management of these patients. In our experience, Tyto has proved to be a useful modality for the remote management of medically complex patients.
Understanding the triacylglycerol-based carbon anabolic differentiation in Cyperus esculentus and Cyperus rotundus developing tubers via transcriptomic and metabolomic approaches
Authors: Zhang Honglin , Zhu Zhitao , Di Yining , Luo Jixun , Su Xianyue , Shen Yong , Liu Qing , Liu Tao , Xu Xiaoyu
Published: December 2024

Background
Yellow nutsedge (YSD, Cyperus esculentus) and purple nutsedge (XFZ, Cyperus rotundus), closely related Cyperaceae species, exhibit significant differences in triacylglycerol (TAG) accumulation within their tubers, a key factor in carbon flux repartitioning. Previous studies have attempted to elucidate the carbon anabolic discrepancies between these two species, however, a lack of comprehensive genome-wide annotation has hindered a detailed understanding of the underlying molecular mechanisms.
Results
This study utilizes transcriptomic analysis, supported by a comprehensive YSD reference genome, and metabolomic profiling to uncover the mechanisms of TAG-based carbon anabolic differentiation between the developing tubers of YSD and XFZ germplasms harvested in Yunnan province, China. Our findings indicate distinct expression patterns of key regulatory genes involved in TAG biosynthesis and lipid droplet formation, including ABI3 transcriptional factor, rate-limiting enzymes GPAT3/6/9 and DGAT2/3, and oleosin and caleosin homologs. Furthermore, our omics data suggest that these differences in gene expression are not the sole contributors to the diverse tuber compositions. Instead, complex interactions among highly regulated catalytic reactions, governing carbohydrate, protein, and species-specific metabolite metabolisms, collectively contribute to the pronounced carbon anabolic differentiation primarily evident in TAG accumulation, as well as the starch properties in mature tubers.
Conclusion
This study offers new metabolic insights into the high-value underground non-photosynthetic tissues of Cyperaceae species. The detailed omics analyses aim to deepen our understanding of the Cyperaceae species, which could significantly enhance their resource utilization and industrial applications in contemporary agricultural production.
Authentic Leadership's Impact on Employees Felt Obligation: Moderated Mediation Model
Authors: Eslamdoust Sina , Borhani Tahmineh , Dorri Rasam , Karandish Minoo
Published: December 2024

In contemporary organizational settings, leadership significantly shapes organizational dynamics and influences employee attitudes and behaviors. Despite extensive research on leadership styles, there remains a gap in understanding the impact of authentic leadership on key employee outcomes, such as organizational identification and felt obligation. Drawing on Social Identity Theory (SIT), this paper examines how authentic leadership fosters organizational identification and influences felt obligation among employees. We propose a framework that considers the role of job fit as a moderating factor in these relationships. By exploring the mechanisms through which authentic leadership enhances employee identification and obligation, this study bridges the gap between leadership theory and practical applications in organizational behavior. The findings offer valuable insights for organizational leaders and human resource practitioners on promoting authentic leadership and ensuring proper job fit to enhance overall organizational effectiveness.
Synoptic variability of the Chukchi Sea circulation 2013-2023 from satellite radar altimetry
Authors: Pisareva Maria N. , Müller Felix L. , Passaro Marcello , Schwatke Christian , Dettmering Denise , Seitz Florian
Published: December 2024

While difficult accessibility leads to a lack of oceanographic in-situ measurements in the Arctic Ocean, and in particular in the Chukchi Sea, satellite altimetry provides precise information on the sea surface at different spatial and temporal scales and can be used for studies of current patterns. Here, we created a novel long-term altimetry-based observational dataset of sea level and ocean currents, processed with the implementation of the recent advanced algorithms and special techniques for the reliable detection of leads and the determination of sea surface heights in the sea-ice-covered ocean. The dataset allowed us to observe the general patterns and synoptic variability of regional sea level and geostrophic flow. In the analysis, the reversals of the northward flow through the Bering Strait were investigated and linked to the anomalously strong northeasterly wind events over the Chukchi Shelf. While this phenomenon was previously described in purely oceanographic studies, the satellite altimetry-based dataset made it possible to assess its development, forcing, and variability with a high temporal-spatial resolution (10d/8km) over 2013-2023. The response of the along-strait flow to anomalously strong along-strait northerly winds is strong during fall in the absence of sea ice and well-correlated during winter and spring during partial ice cover.
Multi-step Model Reduction of Coagulation Schemes
Authors: Chen Junyi , Cazeres Quentin , Riber Eleonore , Nicoud Franck
Published: December 2024

This study introduces a comprehensive multi-step reduction technique for coagulation models, specifically targeting the dynamics of thrombin generation. By employing a synergistic approach that combines Direct Relation Graph with Error Propagation, Chemical Lumping, Quasi Steady State Assumption, and Conservation Analysis, the method efficiently reduces the complexity of original coagulation models without compromising accuracy. Applied to both extrinsic and intrinsic coagulation pathway schemes, this approach significantly diminishes the number of species and reactions, and the resulting reduced schemes appear to be robust to changes in initial conditions relevant to haemophilia A. The findings underscore the potential of this reduction method to facilitate more efficient computational simulations that retain the essential characteristics of different coagulation models.
Green Synthesis of silver nanoparticles using Amomum nilgiricum leaf extracts: Preparation, physicochemical characterization and ameliorative effect against human cancer cell lines
Authors: Konappa Narasimhamurthy , Patil Rajeshwari H , Kariyappa Anupama S. , Krishnamurthy Soumya , Ramachandrappa Niranjana Siddapura , Krishnappa Rahul , Chowdappa Srinivas
Published: December 2024

The present study to production of silver nanoparticles (AgNPs) by leaf extracts of A. nilgiricum and to evaluate the activity of anticancer by using AgNPs against cancer cell lines such as MCF-7, HEPG2, H9C2, HEK293 and H1975. The synthesized AgNPs were characterized by using UV–Vis spectroscopy, EDS, FT-IR, XRD, DLS, SEM and HRTEM with SAED patterns. The surface plasmon resonance (SPR) of AgNPs formed a peak centered at 427 nm by UV–Vis analysis. FTIR analysis reveals that existence of functional groups subjected to silver ions reduction to metallic silver. Crystalline form of the AgNPs was assessed by XRD analysis, four spectral peaks at 111, 200, 220, and 311 were formed and zeta potential peak was found at 28.5 mV indicating the higher stability. The size average diameter of the AgNPs was between 27–30 nm by TEM and SEM analysis was reveals the morphology of AgNPs as elongated, irregular and aggregated and some particles are spherical. EDX analysis confirmed the elemental composition of AgNPs with 81.43% Ag. The average diameter of AgNPs was found 21.49 nm in diameter and width was about 12.01nm by DLS analysis. Cytotoxicity of AgNPs was investigated by using MTT, SRB assay and comet assay was performed as a genotoxicity. The results revealed that AgNPs decreased the viability of cancer cells in a concentration dependent pattern (50 to 350µg/ml). The influence of AgNPs on cell cycle stop was studied on H1975, HEP-G2 and MCF-7 cells and found that AgNPs could induce sub G0 cell cycle arrest. The AgNPs was also induced DNA fragmentation confirms the DNA damage in nanoparticles treated cell lines. The anticancer action of nanoparticles was analyzed using proapoptotic and antiapoptotic caspase 8 and caspase 3 mRNA expression levels. Finally the results suggested that AgNPs is an effective anticancer agent which induces apoptosis in H1975, HEP-G2 and MCF-7 cells. Based on our studies, further identification of the major compounds of leaf extracts is acceptable.
ADD-YOLO: A New Model For Object Detection In Aerial Images
Authors: Yang Yifei , Feng Zhengyong , Jin Wei , Miao Pengcheng
Published: December 2024

Currently, object detection models utilized in UAV aerial image tasks encounter challenges such as small and dense objects, as well as interference from complex backgrounds. This paper presents an enhanced model based on YOLOv8s, named ADD-YOLO. In this model, the traditional convolutional layer is replaced with AKConv, which increases adaptability to variations in objects. The C2f_DRAC structure, integrated with AKConv and CBAM, is designed to enhance the model's capability to capture multi-scale contextual information, effectively addressing the issue of background interference. The DABFPN structure incorporates a small target detection layer, which boosts the performance of small object detection and tackles issues related to background interference. Additionally, CIoU-Soft-NMS is introduced to replace the original NMS, enhancing the detection of dense objects and addressing problems such as loss of adjacent prediction boxes and overlap in boundary frame IoU calculations. Extensive ablation studies and comparative experiments were conducted on the VisDrone2019 dataset and the UAVDT benchmark. The results demonstrate that ADD-YOLO outperforms the leading models in UAV aerial image detection tasks, achieving improvements of 15.7% and 7.3% in mAP@0.5 and 13.8% and 5.1% in mAP@0.5:0.95, respectively, thereby validating the effectiveness of this model.