bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intra-articular injection of bone marrow aspirate concentrate (mesenchymal stem cells) in KL grade III and IV knee osteoarthritis: 4 year results of 37 knees
Authors: Pabinger Christof , Lothaller Harald , Kobinia Georg Stefan 
Published: February 2024

AbstractCell based therapies are increasingly used and results of bone marrow aspirate concentrate (BMAC) show encouraging short- to middle term results, superior to hyaluronic acid and platelet rich plasma (PRP). Most studies describe patients with mild to moderate arthritis and results of patients with KL III and IV osteoarthritis of the knee are limited to short term evaluations. Hence, the aim of this prospective study was to investigate the mid-term outcome of BMAC injections in patients with severe osteoarthritis of the knee. The BMAC was retrieved from the iliac crest as previously published with the “reorientation technique” from the iliac crest in supine position in analgosedation and injected into the patients’ osteoarthritic knees. Patients were followed-up for 4 years. WOMAC, IKDC, SF 36 and walking distance were measured in a total of 37 participants. There was an improvement of IKDC and WOMAC from the first year onwards and a significant improvement beginning from year 2 up to the mid-term follow-up: IKDC increased significantly from 56 ± 12 (range 34–81) to 73 ± 13 (range 45–100), p < 0.001. WOMAC decreased significantly from 40 ± 23 (range 6–96) to 18 ± 18 (range 0–67), p < 0.001. 35 of 37 knees improved regarding IKDC and WOMAC score from the first to the last follow-up. Not a single protheses had to be implanted. Elaborate statistical analysis was done to exclude covariates and confounders (age, time, BMI,…). In summary, this is the first study on BMAC injections into 37 osteoarthritic knees with a 4-year follow up showing significant improvements in IKDC and WOMAC scores, and with a 95% success rate and significant improvement in walking distance.Clinical relevance Describes the 4-year outcome of BMAC injections for knees with severe osteoarthritis.
An explainable machine learning approach for Alzheimer’s disease classification
Authors: Alatrany Abbas Saad , Khan Wasiq , Hussain Abir , Kolivand Hoshang , Al-Jumeily Dhiya 
Published: February 2024

AbstractThe early diagnosis of Alzheimer’s disease (AD) presents a significant challenge due to the subtle biomarker changes often overlooked. Machine learning (ML) models offer a promising tool for identifying individuals at risk of AD. However, current research tends to prioritize ML accuracy while neglecting the crucial aspect of model explainability. The diverse nature of AD data and the limited dataset size introduce additional challenges, primarily related to high dimensionality. In this study, we leveraged a dataset obtained from the National Alzheimer’s Coordinating Center, comprising 169,408 records and 1024 features. After applying various steps to reduce the feature space. Notably, support vector machine (SVM) models trained on the selected features exhibited high performance when tested on an external dataset. SVM achieved a high F1 score of 98.9% for binary classification (distinguishing between NC and AD) and 90.7% for multiclass classification. Furthermore, SVM was able to predict AD progression over a 4-year period, with F1 scores reached 88% for binary task and 72.8% for multiclass task. To enhance model explainability, we employed two rule-extraction approaches: class rule mining and stable and interpretable rule set for classification model. These approaches generated human-understandable rules to assist domain experts in comprehending the key factors involved in AD development. We further validated these rules using SHAP and LIME models, underscoring the significance of factors such as MEMORY, JUDGMENT, COMMUN, and ORIENT in determining AD risk. Our experimental outcomes also shed light on the crucial role of the Clinical Dementia Rating tool in predicting AD.
Fabrication and characterization of different PbO borate glass systems as radiation-shielding containers
Authors: Abou Hussein E. M. , Madbouly A. M. 
Published: February 2024

AbstractThree borate glasses of 50, 35, and 15 mol% PbO-doped Ce, Sb, or Mn ions were fabricated via the melting-annealing procedure. Their structural features were inspected before and after 250 kGy of gamma irradiation using FTIR and ESR techniques. The spectra of the ESR and FTIR vibrational bands remain constant, with a minor reduction in N4 and an enhancement in density values after irradiation, indicating the large structural stability and glass compactness. Many radiation shielding parameters were studied, such as gamma dose rate (µSv/h), dose transmission %, lifetime cancer risk %, macroscopic effective removal cross-section (∑R), mass stopping power, and projected range values ​​were considered for protons particles by SRIM Monte Carlo simulation code and ESTAR program. The whole data reveals the high radiation shielding efficiency of the glasses compared to other standard shields to be used as glass immobilizers for radioactive wastes or storage containers, e.g., for nuclear medicine units in hospitals.
Biochar production under different pyrolysis temperatures with different types of agricultural wastes
Authors: Khater El-Sayed , Bahnasawy Adel , Hamouda Ramy , Sabahy Amr , Abbas Wael , Morsy Osama M. 
Published: February 2024

AbstractThe main aim of this study is to determine the physical and chemical properties of biochar synthesized from different materials (straw rice, sawdust, sugar cane, and tree leaves) at different pyrolysis temperatures (400, 600, and 800 °C). The physical and chemical properties such as moisture content, water holding capacity, bulk density, and porosity; and pH, electrical conductivity (EC), organic matter, organic carbon, total nitrogen, potassium, phosphorus, calcium, magnesium, sodium, and sulfur were determined, respectively. The results show that the biochar yield decreased with increasing pyrolysis temperature, and the values of the analyzed properties varied depending on the type of biochar and pyrolysis temperature. The moisture content ranged from 1.11 to 4.18%, and the water holding capacity ranged from 12.9 to 27.6 g water g−1 dry sample. The highest value of bulk density (211.9 kg m−3) was obtained from sawdust at a pyrolysis temperature of 800 °C. The porosity values ranged from 45.9 to 63.7%. The highest values of pH and EC (10.4 and 3.46 dS m−1) were obtained from tree leaves at a pyrolysis temperature of 800 °C. Total organic matter ranged from 66.0 to 98.1%, total organic carbon ranged from 38.3 to 56.9%, and total nitrogen ranged from 0.4 to 1.9%. The highest values of phosphorus and calcium content (134.6 and 649.0 mg kg−1) were obtained from sugar cane at a pyrolysis temperature of 800 °C. The magnesium, sodium and sulfur content had ranges of 10.9–51.7, 1124–1703 and 3568–12,060 mg kg−1, respectively.
Central auditory test performance predicts future neurocognitive function in children living with and without HIV
Authors: Joseph Jeff , Niemczak Christopher , Lichtenstein Jonathan , Kobrina Anastasiya , Magohe Albert , Leigh Samantha , Ealer Christin , Fellows Abigail , Reike Catherine , Massawe Enica , Gui Jiang , Buckey Jay C. 
Published: February 2024

AbstractTests of the brain’s ability to process complex sounds (central auditory tests) correlate with overall measures of neurocognitive performance. In the low- middle-income countries where resources to conduct detailed cognitive testing is limited, tests that assess the central auditory system may provide a novel and useful way to track neurocognitive performance. This could be particularly useful for children living with HIV (CLWH). To evaluate this, we administered central auditory tests to CLWH and children living without HIV and examined whether central auditory tests given early in a child’s life could predict later neurocognitive performance. We used a machine learning technique to incorporate factors known to affect performance on neurocognitive tests, such as education. The results show that central auditory tests are useful predictors of neurocognitive performance and perform as well or in some cases better than factors such as education. Central auditory tests may offer an objective way to track neurocognitive performance in CLWH.
Policy instruments as a trigger for urban sprawl deceleration: monitoring the stability and transformations of green areas
Authors: Filepné Kovács Krisztina , Varga Dalma , Kukulska-Kozieł Anita , Cegielska Katarzyna , Noszczyk Tomasz , Husar Milan , Iváncsics Vera , Ondrejicka Vladimir , Valánszki István 
Published: February 2024

AbstractThe socialist era postponed suburbanisation in Central and Eastern European countries. After 1990, the process became extremely intensive and transformed the compact form of cities into more decentralised and dispersed urban structures. Therefore, the study aims to identify the main trends in land-cover transformation caused by urban sprawl in peri-urban areas of three Central and Eastern European cities (NUTS 3 level: the Pest County, Bratislava Region, and Krakowski subregion). In addition, we identified various policy tools for green infrastructure protection. We further investigated the extent to which the presence of legal means of nature conservation affects the stability of natural and seminatural areas. The research used an original questionnaire and spatio-temporal analysis. It has been confirmed that after decades of socialism, a highly intensive urban sprawl process started in the analysed regions. It generally slowed down after 2000 except for the Krakowski subregion. The majority of new artificial areas replaced agricultural land. Despite the dynamic urban sprawl, almost one-third of the analysed Central and Eastern European peri-urban areas were stable natural and seminatural areas. The traditional nature conservation tools proved to be effective in preserving natural and seminatural areas, but the protection of landscapes exposed to urban sprawl needs specific tools. The effectiveness of urban sprawl control is hindered by the fact that spatial planning competences are dispersed. This research may influence monitoring urban sprawl and offer an innovative method because it combines spatial analysis (quantitative approach) with the impact of policy tools (qualitative approach).
A study on the evaluation of competitiveness in the aviation logistics industry cluster in Zhengzhou
Authors: Sun Zhihua 
Published: February 2024

AbstractAs the global economy continues to evolve, air transportation is increasingly seen as a crucial factor in enhancing regional competitiveness. In particular, aviation logistics industry clusters have emerged as a new driving force for regional economic development. In this context, the current study aims to evaluate the competitiveness of the aviation logistics industry cluster in Zhengzhou, China. To achieve this goal, the study employs the “GEM model” and constructs a GKA evaluation model using evaluation index data from 21 logistics node cities across China in 2021. The entropy-weighted TOPSIS method is used for empirical analysis of the data. The results of the study reveal that the competitiveness of Zhengzhou’s aviation logistics industry cluster is moderately low. This is primarily due to the weak competitiveness of its foundational and regulatory subsystems. Specifically, the study finds that Zhengzhou’s resources, facilities, markets, government, and industry aspects are all less competitive when compared to other cities in China. In order to enhance the competitiveness of Zhengzhou’s aviation logistics industry cluster, the study recommends that efforts be made to improve the competitiveness of key elements such as resources, facilities, markets, and government. In particular, the focus should be on elevating industry competitiveness, followed by the development of appropriate regulatory strategies. By doing so, the aviation logistics industry cluster in Zhengzhou would be better positioned to compete with other clusters within China and globally.
Effect of social capital, social support and social network formation on the quality of life of American adults during COVID-19
Authors: Larnyo Ebenezer , Tettegah Sharon , Griffin Brianna , Nutakor Jonathan Aseye , Preece Natasha , Addai-Dansoh Stephen , Dubon Natalia , Liu Senyuan 
Published: February 2024

AbstractThis study aims to evaluate the effect of social capital (SC), social support (SS), and social network formation (SNF) on the quality of life of American adults during COVID-19. Using a probability sample of American adults aged 49+, 2370 respondents were selected from the National Social Life Health and Aging Project (NSHAP) dataset for analysis using an integrated partial least squares based on structural equation modeling (PLS-SEM)-K-fold cross-validation approach. The analysis showed that social capital assessed using civic engagement, social cohesion, socioeconomic status (SES), social support, and social network formation were significantly and positively associated with American adults’ quality of life during the COVID-19 pandemic. Furthermore, the results showed that using the PLS-SEM and K-fold cross-validation approach produced a medium predictive power of the overall model, confirming the importance of SC, SS, and SNF in predicting quality of life-outcomes. These findings suggest that efforts to promote the well-being of American adults, especially older adults, during the pandemic should focus on strengthening social capital, social support and social network formation.
Brain tumor detection from images and comparison with transfer learning methods and 3-layer CNN
Authors: Khaliki Mohammad Zafer , Başarslan Muhammet Sinan 
Published: February 2024

AbstractHealth is very important for human life. In particular, the health of the brain, which is the executive of the vital resource, is very important. Diagnosis for human health is provided by magnetic resonance imaging (MRI) devices, which help health decision makers in critical organs such as brain health. Images from these devices are a source of big data for artificial intelligence. This big data enables high performance in image processing classification problems, which is a subfield of artificial intelligence. In this study, we aim to classify brain tumors such as glioma, meningioma, and pituitary tumor from brain MR images. Convolutional Neural Network (CNN) and CNN-based inception-V3, EfficientNetB4, VGG19, transfer learning methods were used for classification. F-score, recall, imprinting and accuracy were used to evaluate these models. The best accuracy result was obtained with VGG16 with 98%, while the F-score value of the same transfer learning model was 97%, the Area Under the Curve (AUC) value was 99%, the recall value was 98%, and the precision value was 98%. CNN architecture and CNN-based transfer learning models are very important for human health in early diagnosis and rapid treatment of such diseases.
Visual outcomes and their association with grey and white matter microstructure in adults born preterm with very low birth weight
Authors: Ingvaldsen Sigrid Hegna , Jørgensen Anna Perregaard , Grøtting Arnstein , Sand Trond , Eikenes Live , Håberg Asta K. , Indredavik Marit S. , Lydersen Stian , Austeng Dordi , Morken Tora Sund , Evensen Kari Anne I. 
Published: February 2024

AbstractIndividuals born with very low birth weight (VLBW; < 1500 g) have a higher risk of reduced visual function and brain alterations. In a longitudinal cohort study, we assessed differences in visual outcomes and diffusion metrics from diffusion tensor imaging (DTI) at 3 tesla in the visual white matter pathway and primary visual cortex at age 26 in VLBW adults versus controls and explored whether DTI metrics at 26 years was associated with visual outcomes at 32 years. Thirty-three VLBW adults and 50 term-born controls was included in the study. Visual outcomes included best corrected visual acuity, contrast sensitivity, P100 latency, and retinal nerve fibre layer thickness. Mean diffusivity, axial diffusivity, radial diffusivity, and fractional anisotropy was extracted from seven regions of interest in the visual pathway: splenium, genu, and body of corpus callosum, optic radiations, lateral geniculate nucleus, inferior-fronto occipital fasciculus, and primary visual cortex. On average the VLBW group had lower contrast sensitivity, a thicker retinal nerve fibre layer and higher axial diffusivity and radial diffusivity in genu of corpus callosum and higher radial diffusivity in optic radiations than the control group. Higher fractional anisotropy in corpus callosum areas were associated with better visual function in the VLBW group but not the control group.
Application of anatomy-based spacing of electrode contacts for achieving a uniform semitonal resolution: A novel concept in cochlear implant electrode design
Authors: Aljazeeri Isra Ali , Hagr Abdulrahman 
Published: February 2024

AbstractUsing anatomy-based fitting, we can determine the place-specific map with individualized center frequencies for each electrode contact that is a closer match to the natural pitch-place of the cochlea. The primary objective of this study is to evaluate the tonal presentation across the electrode array and to calculate the semitone difference between each adjacent pair of contacts according to their anatomy-based map. The secondary objective is to determine the distancing of the contacts that would result in an equal semitone difference with a uniform tonal presentation. A total of 167 ears were included in this retrospective study. The frequencies across the electrode arrays were found to be unequally presented. The semitonal condensations were higher in the apical inter-contact spaces compared to the basal inter-contact spaces, being 3.0–2.3 semitones/mm (Kruskal Wallis test, p < 0.000). The anatomy-based spacing of the electrode contacts was larger in the basal inter-contact spaces compared to the apical inter-contact spaces, ranging from 1.92 to 1.48 mm. In conclusion, the current electrode designs do not have uniform tonal representation throughout the electrode array. There is a more condensed tonal presentation in the apical electrodes than in the basal electrodes, resulting in a lower tonal resolution in the apical region.
Assessment of UV radiation effects on airborne mucormycetes and bacterial populations in a hospital environment
Authors: Sarkhoshkalat Mohammadmahdi , Nasab Mahdi Ahmadi , Yari Mohammad Reza , Tabatabaee Seyed Saeed , Ghavami Vahid , Joulaei Fatemeh , Sarkhosh Maryam 
Published: February 2024

AbstractInfections, such as mucormycosis, often result from inhaling sporangiospore present in the environment. Surprisingly, the extent of airborne Mucormycetes sporangiospore concentrations remains inadequately explored. This study aimed to assess the influence of UV radiation on microbial populations and Mucormycetes spore levels within a hospital environment in northern Iran. A comprehensive dataset comprising 298 air samples collected from both indoor and outdoor settings was compiled. The culture was conducted using Blood Agar and Dichloran Rose Bengal Chloramphenicol (DRBC) culture media, with Chloramphenicol included for fungal agents and Blood Agar for bacterial. Before UV treatment, the average count of Mucormycetes ranged from 0 to 26.4 ± 25.28 CFU m−3, fungal agents from 2.24 ± 3.22 to 117.24 ± 27.6 CFU m−3, and bacterial agents from 29.03 ± 9.9 to 359.37 ± 68.50 CFU m−3. Following UV irradiation, the averages were as follows: Mucormycetes ranged from 0 to 7.85 ± 6.8 CFU m−3, fungal agents from 16.58 ± 4.79 to 154.98 ± 28.35 CFU m−3, and bacterial agents from 0.38 ± 0.65 to 43.92 ± 6.50 CFU m−3. This study, notably marks the pioneering use of UV light to mitigate Mucormycetes spore counts and bacterial agents in northeastern Iran, contributing to the advancement of environmental health and safety practices in hospital settings.
Effects of nonalcoholic fatty liver disease on sarcopenia: evidence from genetic methods
Authors: Yuan Jiaqin , Zhang Jinglin , Luo Qiang , Peng Lipeng 
Published: February 2024

AbstractWith the aging of the population, sarcopenia has become more common. Studies have shown a broad association between liver disease and sarcopenia. However, this link remains unclear. Our study explored the link between NAFLD and sarcopenia and predicting the pathogenesis. To begin, we investigated the causal relationship and genetic correlation between them using MR and LDSC. Second, each GWAS was annotated by MAGMA. The annotated genes were analyzed for pleiotropy using the PLACO approach. Finally, functional analysis was conducted on the identified pleiotropic genes. We observed a significant genetic correlation between NAFLD and sarcopenia. Subsequently, we conducted gene-level pleiotropy analysis using PLACO and identified a total of 153 genes with pleiotropic effects. Functional analysis revealed enrichment of these genes in various tissues, including pancreas, liver, heart, blood, brain, and muscle, with involvement in cellular regulation, intracellular function, and antigen response. Moreover, our MR analysis provided evidence of a causal relationship between NAFLD and sarcopenia. Our study has discovered the genetic and causal relationships between NAFLD and sarcopenia, providing further insights into their pathophysiological mechanisms. The identification of pleiotropic genes also offers potential targets for future drug therapies aimed at controlling or treating NAFLD and sarcopenia.
Elementary cellular automata realized by stateful three-memristor logic operations
Authors: Wang Hongzhe , Wang Junjie , Yan Shiqin , Pan Ruicheng , Sun Mingyuan , Yu Qi , Chen Tupei , Chen Lei , Liu Yang 
Published: February 2024

AbstractCellular automata (CA) are computational systems that exhibit complex global behavior arising from simple local rules, making them a fascinating candidate for various research areas. However, challenges such as limited flexibility and efficiency on conventional hardware platforms still exist. In this study, we propose a memristor-based circuit for implementing elementary cellular automata (ECA) by extending the stateful three-memristor logic operations derived from material implication (IMP) logic gates. By leveraging the inherent physical properties of memristors, this approach offers simplicity, minimal operational steps, and high flexibility in implementing ECA rules by adjusting the circuit parameters. The mathematical principles governing circuit parameters are analyzed, and the evolution of multiple ECA rules is successfully demonstrated, showcasing the robustness in handling the stochastic nature of memristors. This approach provides a hardware solution for ECA implementation and opens up new research opportunities in the hardware implementation of CA.