bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incorporating Spatio-Temporal Changes of Well Irrigation into a Distributed Hydrologic Model to Improve Groundwater Anomaly Estimations for Basins with Expanding Agricultural Lands
Authors: Koycegiz Cihangir , Demirel Mehmet Cuneyd , Sen Omer Lutfi , Buyukyildiz Meral 
Published: March 2024

AbstractThis paper seeks to address the deficiency of utilizing satellite-based GRACE observations and model-based GLDAS water budget components in estimating the changes in the groundwater storage in Konya Endorheic Basin (KEB), a basin experiencing considerable land use land cover (LULC) change, primarily agricultural expansion. Cereal cultivation in the basin has a slight decreasing trend, however, the cultivation of crops with high water consumption, such as maize and sunflower, is increasing substantially. And total agricultural areas are increasing. GRACE-GLDAS approach does not accurately give the long-term groundwater decline in the basin, mainly because the land surface models employed in GLDAS cannot realistically simulate variations in water budget components as they do not consider the changes in LULC and do not possess an elaborated irrigation scheme. Here, we used a fully-distributed mesoscale hydrologic model, mHM, that can handle multiple LULC maps from different years. The model was modified to incorporate the spatio-temporal changes of agricultural fields in KEB and an explicit irrigation scheme since we hypothesized that the groundwater depletion is mainly caused by well irrigation. mHM was calibrated against streamflow observations for the period 2004–2019. The simulations show that the use of mHM with the incorporated features gives groundwater storage changes that are more consistent with the well-based observations than those obtained from the GRACE-GLDAS approach. On the other hand, the mHM simulation with a static LULC map, as in GLDAS models but with a better representation of irrigated fields, provides groundwater anomaly changes that are more consistent with the GRACE-GLDAS results, a further justification of insufficiency of the GLDAS-based approach in estimating groundwater variations for basins with considerable landscape change.
Highly Sensitive Detection of Melanin in Melanomas Using Multi-harmonic Low Frequency EPR
Authors: Wehbi Mohammad , Mignion Lionel , Joudiou Nicolas , Harkemanne Evelyne , Gallez Bernard 
Published: March 2024

Abstract
Purpose
Low frequency EPR can noninvasively detect endogenous free radical melanin in melanocytic skin lesions and could potentially discriminate between benign atypical nevi and malignant melanoma lesions. We recently succeeded in demonstrating the ability of clinical EPR to noninvasively detect the endogenous melanin free radical in skin lesions of patients. However, the signal-to-noise ratio (SNR) was extremely low warranting further research to boost the sensitivity of detection. In the present study, we assessed the performance of a clinical EPR system with the capability to perform multi-harmonic (MH) analysis for the detection of melanin.

Procedures
The sensitivity of MH-EPR was compared with a classical continuous wave (CW)-EPR (1st harmonic) detection in vitro in melanin phantoms, in vivo in melanoma models with cells implanted in the skin, in lymph nodes and having colonized the lungs, and finally on phantoms placed at the surface of human skin.

Results
In vitro, we observed an increase in SNR by a factor of 10 in flat melanin phantoms when using MH analysis compared to CW combined with an increase in modulation amplitude. In B16 melanomas having grown in the skin of hairless mice, we observed a boost in sensitivity in vivo similar to that observed in vitro with the capability to detect melanoma cells at an earlier stage of development. MH-EPR was also able to detect non-invasively the melanin signal coming from melanoma cells present in lymph nodes as well as in lungs. We also observed a boost of sensitivity using phantoms of melanin placed at the surface of human skin.

Conclusions
Overall, our results are paving the way for new clinical trials that will use MH clinical EPR for the characterization of pigmented skin lesions.
Machine learning prediction of methane, ethane, and propane solubility in pure water and electrolyte solutions: Implications for stray gas migration modeling
Authors: Kooti Ghazal , Taherdangkoo Reza , Chen Chaofan , Sergeev Nikita , Doulati Ardejani Faramarz , Meng Tao , Butscher Christoph 
Published: March 2024

AbstractHydraulic fracturing is an effective technology for hydrocarbon extraction from unconventional shale and tight gas reservoirs. A potential risk of hydraulic fracturing is the upward migration of stray gas from the deep subsurface to shallow aquifers. The stray gas can dissolve in groundwater leading to chemical and biological reactions, which could negatively affect groundwater quality and contribute to atmospheric emissions. The knowledge of light hydrocarbon solubility in the aqueous environment is essential for the numerical modelling of flow and transport in the subsurface. Herein, we compiled a database containing 2129 experimental data of methane, ethane, and propane solubility in pure water and various electrolyte solutions over wide ranges of operating temperature and pressure. Two machine learning algorithms, namely regression tree (RT) and boosted regression tree (BRT) tuned with a Bayesian optimization algorithm (BO) were employed to determine the solubility of gases. The predictions were compared with the experimental data as well as four well-established thermodynamic models. Our analysis shows that the BRT-BO is sufficiently accurate, and the predicted values agree well with those obtained from the thermodynamic models. The coefficient of determination (R2) between experimental and predicted values is 0.99 and the mean squared error (MSE) is 9.97 × 10−8. The leverage statistical approach further confirmed the validity of the model developed.
Scientific and technological innovations of wastewater treatment in China
Authors: Huang Hui , Ma Rui , Ren Hongqiang 
Published: March 2024

AbstractThe “dual-carbon” strategy promotes the development of the wastewater treatment sector and is an important tool for leading science and technology innovations. Based on the global climate change and the new policies introduced by China, this paper described the new needs for the development of wastewater treatment science and technology. It offered a retrospective analysis of the historical trajectory of scientific and technological advancements in this field. Utilizing bibliometrics, it delineated the research hotspots within wastewater treatment, notably highlighting materials genomics, artificial intelligence, and synthetic biology. Furthermore, it posited that, in the future, the field of wastewater treatment should follow the paths of technological innovations with multi-dimensional needs, such as carbon reduction, pollution reduction, health, standardisation, and intellectualisation. The purpose of this paper was to provide references and suggestions for scientific and technological innovations in the field of wastewater treatment, and to contribute to the common endeavor of moving toward a Pollution-Free Planet.
Voacanga madureirae (Apocynaceae), a new species from Atlantic Central Africa
Authors: Lachenaud Olivier , Paiva Jorge , Covelo Filipe , Cheek Martin , Onana Jean Michel 
Published: March 2024

SummaryA new species of Apocynaceae from Atlantic Central Africa, Voacanga madureirae Paiva, O.Lachenaud & Covelo, is mapped, described and illustrated. It occurs on the Gulf of Guinea islands of Príncipe (São Tomé and Príncipe) and Bioko (Equatorial Guinea) and in the highlands of western Cameroon. The new species differs from other African Voacanga by its calyx distinctly exceeding the corolla (vs shorter or at most equalling it). It is further separated from V. chalotiana Pierre ex Stapf by the presence of a row of colleters in the upper half of the calyx (not near the base) and from other Central African species by its syncarpous fruits and almost straight (not strongly twisted) corolla tube. It is assessed as Near Threatened according to IUCN criteria.
Aspergillus-associated diseases from an infectious diseases and allergological perspective
Authors: Stemler Jannik , Nacov Julia A. , Sprute Rosanne , Cornely Oliver A. , Joest Marcus , Becker Sven , Klimek Ludger 
Published: March 2024

AbstractAspergillus-associated diseases are rare and pose challenges for practitioners. Diagnosis is complex and requires rational, targeted, and multidisciplinary collaboration, as well as a high degree of expertise and an individualized approach. For the infectious diseases physician, the focus is on the question of infection or colonization. In severely immunocompromised patients, invasive aspergillosis occurs, which most frequently affects the lungs (IPA) and is characterized by invasive, destructive growth. This acute clinical picture is associated with a high mortality rate. Chronic pulmonary aspergillosis (CPA) develops on the basis of pre-existing changes in lung structure caused by other pulmonary diseases and often requires surgical treatment. Another chronic form is allergic bronchopulmonary aspergillosis (ABPA). It is often associated with bronchiectasis in patients with bronchial asthma or cystic fibrosis. Sinus mycoses are divided into non-invasive and invasive forms, which can occur in immunocompromised patients and most commonly affect the maxillary sinus. Here, local surgical measures are an obligatory part of treatment, whereas the non-invasive form usually has an allergic component. In addition, drug-based antifungal and/or anti-inflammatory therapy is used for all entities.
CO2 capture by modified clinoptilolite and its regeneration performance
Authors: Jiang Bo , Zhang Bo , Duan Xuqin , Xing Yi 
Published: March 2024

AbstractThis study focuses on CO2 capture by pressure swing adsorption (PSA), with modified clinoptilolite as the adsorbent. Natural clinoptilolite is modified by roasting, by acid pickling, by a combination of acid pickling and roasting, and by ion exchange. Modification by acid pickling–roasting and by ion exchange are found to give the highest CO2 adsorption capacities, of 730 mL/g and 876.7 mL/g, respectively. It is found that regeneration of clinoptilolite by a combination of vacuum desorption and heating enables recovery of as much as 89% of its previous CO2 adsorption capacity. To examine the CO2 adsorption capacity of clinoptilolite when applied to mixed gas, a simulated coking exhaust containing 12% CO2 and 4% O2 is used, and it is found that ion exchange modified clinoptilolite achieves a CO2 removal efficiency of 92.5%. A BET test reveals that acid pickling–roasting and Na+ modification enhance the porosity of clinoptilolite, thereby improving its adsorption capacity. This work demonstrates the feasibility of applying modified clinoptilolite as an effective adsorbent for CO2 capture, providing a promising tool for dealing with greenhouse gases.
Multi-step modeling of well logging data combining unsupervised and deep learning algorithms for enhanced characterization of the Quaternary aquifer system in Debrecen area, Hungary
Authors: Mohammed Musaab A. A. , Szabó Norbert P. , Szűcs Péter 
Published: March 2024

AbstractIn this research, a multi-step modeling approach is followed using unsupervised and deep learning algorithms to interpret the geophysical well-logging data for improved characterization of the Quaternary aquifer system in the Debrecen area, Hungary. The Most Frequent Value-Assisted Cluster Analysis (MFV-CA) is used to map lithological variations within the aquifer system. Additionally, the Csókás method is used to discern both vertical and horizontal fluctuations in hydraulic conductivity. MFV-CA is introduced to cope with the limitation of the conventional Euclidean distance-based k-means clustering known for its low resistance to outlying values, resulting in deformed cluster formation. However, the computational time and demands of MFV-CA are evident, making them costly and time-consuming. As a result, Deep Learning (DL) methods are suggested to provide fast characterization of the groundwater aquifers. These methods include Multi-Layer Perceptron Neural Networks (MLPNN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM), which are implemented for classification and regression. The classification categorized the inputs into three distinct lithologies trained initially by the results of MFV-CA. At the same time, the regression model offered a continuous estimations of hydraulic conductivity trained by the results of the Csókás model. The results demonstrated significant compatibility between the outcomes derived from the clustering and Csókás approaches and DL algorithms. Accordingly, the lithofacies and hydraulic conductivity variations across the main hydrostratigraphical units are mapped. This integration enhanced the understanding of the groundwater system, offering promising inputs for groundwater and development and management.
Reading for Pleasure: A Review of Current Research
Authors: Vogrinčič Čepič Ana , Mascia Tiziana , Aerila Juli-Anna 
Published: March 2024

AbstractThe narrative review examines the current state of research on reading for pleasure and its relevance in education and personal development. By analysing 22 studies published over the past several years (2014–2022), the authors have sought to identify the key trends and areas of focus within this field. The selected articles have been coded and analysed, and the results have been used to, among others, examine the type of research on reading for pleasure, the subject areas covered, the research methods used, the variables analysed, and the target groups involved. A particular attention has been paid to possible conceptualisations of reading for pleasure and reading for pleasure pedagogy, to the type of reading and the texts reading for pleasure may predominantly be associated with, as well as to its social dimension and relationship to the digital literary environment. The literature review shows that the studies on reading for pleasure highlight the importance of personalisation in reading for pleasure pedagogy and acknowledge the role of the material and social dimension of reading. Further, there are signs of a broader definition of reading materials, like comics, also in the educational context. The findings of the present review indicate the gaps in the research of reading for pleasure and highlight the need for a more profound understanding of the title concept and its benefits, thus contributing to the development of its future research and promotion.
Assessment of lake-level variations to decipher geological controlling factors and depositional architecture of Lake Fuxian, Yunnan Plateau: preliminary insights from geophysical data
Authors: Ashraf Umar , Zhang Hucai , Anees Aqsa , Zhang Xiaonan , Duan Lizeng 
Published: March 2024

AbstractLake Fuxian is one of the deepest tectonic plateau freshwater lakes in the southeastern Tibetan Plateau, China. However, questions such as how old the lake is, how deep the total sedimentary thickness sequences are, and what landscape of the lake basin settings and geological structures are unknown. Here, based on fifteen seismic reflection profiles, we applied seismic facies and seismic sequence stratigraphic analyses to interpret the lake sequences. The results of the seismic response reveal that the maximum thickness of the sedimentation is ca. 1238 m and lies toward the NNE region of the lake basin on the L10-2 survey line. Lake sediments can be categorized into five seismic sequences and six seismic horizons. The oldest clinoforms in the deepest sequence (Sq-5) show that the depositional center was shifted to ~ 19 km from the NNE region to the SSW modern location and was ~ 930 m lower than the current lake floor. Multiple and complex tectonic activities strongly impacted on the lake basin, and a series of normal faults created an overall crustal extensional regime, resulting in the formation of many horst and graben structures.
The “Schwarze Mander” of the Court Church in Innsbruck, Austria: Manufacture and Production of Monumental Brass Statues in the Renaissance
Authors: Mödlinger Marianne , Asmus Bastian , Ghiara Giorgia 
Published: March 2024

Abstract
The 28 "Schwarze Mander" (Black Men) are undoubtedly amongst the most magnificent monumental brass statues of the Renaissance. Commissioned by the Holy Roman Emperor Maximilian I for his funeral monument at the beginning of the 16th century, they were completed more than 30 years after the Emperor's death and are now part of his cenotaph in the Hofkirche in Innsbruck. Revising the original manuscripts and letters exchanged between Maximilian I and the various artists sheds light on the manufacturing process and the challenges the artists encountered whilst producing the statues. Moreover, the alloys used in the manufacture of the statues, now all blackened due to patination processes, were identified through non-invasive chemical analysis of all the statues.
A preliminary study on multi-material fused filament fabrication of an embedded strain gauge for low-cost real-time monitoring of part strain
Authors: Minetola Paolo , Giubilini Alberto 
Published: March 2024

AbstractUnlike other manufacturing techniques, additive manufacturing enables part consolidation through the production of multi-material parts with enhanced functionality. With reference to the functionality of monitoring the structural integrity of a product during its use, conductive filaments can be used in additive manufacturing. This work aims to investigate the applications of multi-material fused filament fabrication to produce embedded strain gauges for real-time monitoring of part deformations. In layer-by-layer fabrication, conductive filaments can be used to produce strain-sensitive elements inside products at a low cost. This preliminary study demonstrated the feasibility of the proposed approach using tensile samples fabricated through additive manufacturing. The samples were produced using a polyethylene terephthalate glycol filament and an acrylonitrile styrene acrylate filament, while electrically conductive polylactic acid was used for the strain gauge. The characterization and testing activities were conducted by comparing the results of the tensile testing with data acquired through an experimental system set up with an Arduino board, aligning with the resistance-based strain gauge theory. The findings show that the co-fabricated strain gauge successfully traces part deformation, enabling real-time monitoring of strain in the elastic field. Nevertheless, further optimization of the proposed approach is imperative to enhance the reliability and accuracy of the methodology.
Blockchain Use Cases in the Sports Industry: A Systematic Review
Authors: Berkani Ahmed-Sami , Moumen Hamouma , Benharzallah Saber , Yahiaoui Said , Bounceur Ahcène 
Published: March 2024

AbstractSince its inception, Blockchain Technology, the underlying technology of Bitcoin has gained a lot of popularity and interest in various industries, varying from the healthcare industry, Internet-of-Things, smart grid, and supply chain management. Sports is one industry where blockchain can have significant breakthroughs where it can reshape the way the sports industry works by providing reliable athlete data management, secure mechanisms for data sharing, reforming the event management practices, collectibles traceability, and many more, but so far its impact is overshadowed by the hype surrounding the use of fan tokens and Non-Fungible-Tokens (NFT) collectibles. This paper aims to provide a systematic review of the ongoing research on the application of blockchain in the sports industry. this work shows that many studies have proposed different use cases for the application of blockchain in the sports industry on and off the field and targeting different stakeholders. However, we inferred a lack of adequate prototype implementations to evaluate the effectiveness of these proposed use cases. We further highlighted the technical details of the implementation of these blockchain-based applications, their limitations, and challenges, and proposed some solutions to support the integration of blockchain in this domain. The findings of this work will be beneficial for researchers, policymakers, and practitioners in the sports industry.
Recruitment strategies and retention rates for five National Dental PBRN studies
Authors: Mungia Rahma , Funkhouser Ellen , Cochran David L. , Cunha-Cruz Joana , Gordan Valeria V. , Rindal Donald B. , Meyerowitz Cyril , Allareddy Veerasathpurush , Fellows Jeffrey L. , Gilbert Gregg H. ,   National Dental PBRN Collaborative Group
Published: March 2024

Abstract

Background:
We describe a retrospective assessment of practitioner and patient recruitment strategies, patient retention strategies, and rates for five clinical studies conducted in the National Dental Practice-Based Research Network between 2012 and 2019, and practitioner and patient characteristics associated with retention.

Methods:
Similar recruitment strategies were adopted in the studies. The characteristics of the practitioners and patients are described. The proportion of patients who either attended a follow-up (FU) assessment or completed an online assessment was calculated. For studies with multiple FU visits or questionnaire assessments, rates for completing each FU were calculated, as were the rates for completing any and for completing all FU assessments. The associations of practitioner and patient characteristics with all clinic FU visits, and with the completion of all assessments for a study were ascertained.

Results:
Overall, 591 practitioners and 12,159 patients were included. FU rates by patients for any assessment varied from 91% to 96.5%, and rates for participating in all assessments ranged from 68% to 87%. The mean total number of patients each practitioner recruited was 21 (sd = 15); the mean number per study was 13 (sd = 7). For practitioners, practice type and patient enrollment were associated with greater clinic retention, while only race was associated with their patients completing post-visit online assessments. For patients, age was associated with clinic retention, while female gender, age, race, and education were all associated with greater completion of post-visit online assessments.

Conclusion:
The Network efficiently recruited practitioners and patients and achieved high patient retention rates for the five studies.
Minimal monoids generating varieties with complex subvariety lattices
Authors: Gusev Sergey V. 
Published: March 2024

AbstractA variety is finitely universal if its lattice of subvarieties contains an isomorphic copy of every finite lattice. We show that the 6-element Brandt monoid generates a finitely universal variety of monoids and, by the previous results, it is the smallest generator for a monoid variety with this property. It is also deduced that the join of two Cross varieties of monoids can be finitely universal. In particular, we exhibit a finitely universal variety of monoids with uncountably many subvarieties which is the join of two Cross varieties of monoids whose lattices of subvarieties are the 6-element and the 7-element chains, respectively.