bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Alternative Method to Analyze Waveforms from Bender Element Tests in Soft Clays
Authors: Fernández-Lavín Alfonso , Chamorro-Zurita Claudia , Ovando-Shelley Efraín 
Published: July 2023

AbstractBender element (BE) testing has become a widely used technique to evaluate S-wave velocities and to derive shear moduli from them in laboratory tests. Results of BE tests depend heavily on the proper identification of the S-wave travel time from waveforms often affected detrimentally by factors such as the near-field effect, crosstalk, noise, or drift. The authors have performed BE tests on soil specimens of Texcoco Clay over the last few years in triaxial cells and oedometers and have sometimes dealt with waveforms influenced by those undesirable factors thus, it was observed that the using of different available techniques to evaluate the S-wave travel time are often prone to errors. This paper shows that the S-wave travel time can be assessed unambiguously from the distance between the inflection points present in both the source and the received signals when waveforms generated with different input frequencies are superimposed, even in signals affected by the near-field effect, crosstalk, noise, or drift. This approach, named here the Wave Inflection Method (WI method), yields good results, at least when applied to data obtained from BE tests on soft Texcoco Clays. The method was validated by applying it to synthetic signals and experimental waveforms obtained from triaxial and oedometer tests equipped with BE. When applied to previously published waveforms on a wide range of soil types, our results suggest that the WI method significantly reduces subjectivity and produces improved reliability in evaluating the S-wave travel time.
Screening and Treatment for Co-occurring Gambling and Substance Use: A Scoping Review
Authors: Yarbakhsh Elisabeth , van der Sterren Anke , Bowles Devin 
Published: July 2023

AbstractThere is a high prevalence of gambling harms co-occurring with substance use harms. Where harms are co-occurring, they may be experienced as more severe. However, there is little evidence that services are systematically screening for such co-occurring harms in treatment-seeking populations. Furthermore, treatment modalities remain relatively under-developed, with treatment usually addressing only one source of harm.This scoping review looks at the current literature on screening and therapeutic interventions for co-occurring gambling and substance use harms to understand how co-occurring harms may be managed in a treatment setting. It draws together available data on the intersections of substance use harms and gambling related harms, in a treatment context.This research identifies a range of potentially useful validated tools for clinicians in substance use treatment settings to screen for gambling harms. For workers in gambling treatment settings who are seeking validated tools to screen for co-occurring substance use harms, the literature provides less guidance.The validated toolbox of therapeutic interventions for those experiencing co-occurring substance use and gambling harms is relatively sparse. Psychosocial interventions appear to offer the best outcomes on gambling measures for those experiencing co-occurring substance use harms. Further research is needed to establish the benefits of different combinations of treatment and treatment types in achieving reductions across both substance use and gambling harms, when these harms are experienced concurrently.
Go beyond the limits of genetic algorithm in daily covariate selection practice
Authors: Ronchi D. , Tosca E. M. , Bartolucci R. , Magni P. 
Published: July 2023

AbstractCovariate identification is an important step in the development of a population pharmacokinetic/pharmacodynamic model. Among the different available approaches, the stepwise covariate model (SCM) is the most used. However, SCM is based on a local search strategy, in which the model-building process iteratively tests the addition or elimination of a single covariate at a time given all the others. This introduces a heuristic to limit the searching space and then the computational complexity, but, at the same time, can lead to a suboptimal solution. The application of genetic algorithms (GAs) for covariate selection has been proposed as a possible solution to overcome these limitations. However, their actual use during model building is limited by the extremely high computational costs and convergence issues, both related to the number of models being tested. In this paper, we proposed a new GA for covariate selection to address these challenges. The GA was first developed on a simulated case study where the heuristics introduced to overcome the limitations affecting currently available GA approaches resulted able to limit the selection of redundant covariates, increase replicability of results and reduce convergence times. Then, we tested the proposed GA on a real-world problem related to remifentanil. It obtained good results both in terms of selected covariates and fitness optimization, outperforming the SCM.
Flash flood-risk areas zoning using integration of decision-making trial and evaluation laboratory, GIS-based analytic network process and satellite-derived information
Authors: Taherizadeh Mehrnoosh , Niknam Arman , Nguyen-Huy Thong , Mezősi Gábor , Sarli Reza 
Published: July 2023

AbstractAssessing areas prone to flash floods is crucial for effective disaster management and mitigation. This study proposes a framework for mapping flood-prone areas by integrating geographic information system (GIS), remote sensing data, and multi-criteria decision-making (MCDM) techniques. The hybrid MCDM model combines the decision-making trial and evaluation laboratory (DEMATEL) with GIS-based analytic network process (ANP) to evaluate flood vulnerability in Golestan province, Iran. Fourteen criteria related to flood potential, including elevation, slope, aspect, vegetation density, soil moisture, flow direction, river distance, rainfall and runoff, flow time, geomorphology, drainage density, soil type, lithology, and land use, were considered. In areas where official data was lacking, a questionnaire was administered to gather information from 15 specialists, experts, and 20 local managers. The relationships between criteria were analyzed using the DEMATEL method, and their weights were determined using the ANP method. Topography was found to have the greatest impact on flood risk, followed by the type of surface and vegetation cover. Hydrographic, soil and geology, climatic also influence flooding in the region. The study identified the northern and central parts of the study area being at higher risk of flooding compared to the southern part. Based on the flood intensity map, 68 villages (50% of all villages in the Qarasu watershed) with a population of approximately 83,595 were identified as at risk of flooding. The proposed GIS-DANP model provides a valuable tool for flood management and decision-making, aiding in risk reduction and minimizing casualties.
Smart soils track the formation of pH gradients across the rhizosphere
Authors: Patko Daniel , Yang Qizhi , Liu Yangminghao , Falireas Panagiotis , Briou Benoit , Tawade Bhausaheb V. , George Timothy S. , Daniell Tim J. , MacDonald Michael P. , Ladmiral Vincent , Ameduri Bruno , Dupuy Lionel X. 
Published: July 2023

Abstract
Aims
Our understanding of the rhizosphere is limited by the lack of techniques for in situ live microscopy. Current techniques are either destructive or unsuitable for observing chemical changes within the pore space. To address this limitation, we have developed artificial substrates, termed smart soils, that enable the acquisition and 3D reconstruction of chemical sensors attached to soil particles.

Methods
The transparency of smart soils was achieved using polymer particles with refractive index matching that of water. The surface of the particles was modified both to retain water and act as a local sensor to report on pore space pH via fluorescence emissions. Multispectral signals were acquired from the particles using a light sheet microscope, and machine learning algorithms predicted the changes and spatial distribution in pH at the surface of the smart soil particles.

Results
The technique was able to predict pH live and in situ within ± 0.5 units of the true pH value. pH distribution could be reconstructed across a volume of several cubic centimetres around plant roots at 10 μm resolution. Using smart soils of different composition, we revealed how root exudation and pore structure create variability in chemical properties.

Conclusion
Smart soils captured the pH gradients forming around a growing plant root. Future developments of the technology could include the fine tuning of soil physicochemical properties, the addition of chemical sensors and improved data processing. Hence, this technology could play a critical role in advancing our understanding of complex rhizosphere processes.
Follicular fluid composition and reproductive outcomes of women with polycystic ovary syndrome undergoing in vitro fertilization: A systematic review
Authors: Moreira Mafalda V. , Vale-Fernandes Emídio , Albergaria Inês C. , Alves Marco G. , Monteiro Mariana P. 
Published: July 2023

AbstractPolycystic ovary syndrome (PCOS) is recognized as one of the most prevalent endocrinopathy in women at reproductive age. As affected women tend to have poorer assisted reproductive technology (ART) outcomes, PCOS has been suggested to endanger oocyte quality and competence development. The aim of this systematic review was to summarize the available evidence on how the follicular fluid (FF) profile of women with PCOS undergoing in vitro fertilization (IVF) treatment differs from the FF of normo-ovulatory women. For that, an electronic search in PubMed and Web of Science databases was conducted (up to December 2021). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses - PRISMA guidelines were followed, and the Newcastle-Ottawa Scale was used to assess the risk of bias in the included studies. Data retrieved from papers included (n=42), revealed that the FF composition of women with PCOS compared to those without PCOS predominantly diverged at the following molecular classes: oxidative stress, inflammatory biomarkers, growth factors and hormones. Among those biomarkers, some were proposed as being closely related to pathophysiological processes, strengthening the hypothesis that low-grade inflammation and oxidative stress play a critical role in the pathogenesis of PCOS. Notwithstanding, it should be noticed that the available data on PCOS FF fingerprints derives from a limited number of studies conducted in a relatively small number of subjects. Furthermore, phenotypic heterogeneity of PCOS hampers wider comparisons and weakens putative conclusions. Therefore, future studies should be focused at comparing well characterized patient subgroups according to phenotypes.
Statistical Effective Diffusivity Estimation in Porous Media Using an Integrated On-site Imaging Workflow for Synchrotron Users
Authors: Le Houx James , Ruiz Siul , McKay Fletcher Daniel , Ahmed Sharif , Roose Tiina 
Published: July 2023

AbstractTransport in porous media plays an essential role for many physical, engineering, biological and environmental processes. Novel synchrotron imaging techniques and image-based models have enabled more robust quantification of geometric structures that influence transport through the pore space. However, image-based modelling is computationally expensive, and end users often require, while conducting imaging campaign, fast and agile bulk-scale effective parameter estimates that account for the pore-scale details. In this manuscript we enhance a pre-existing image-based model solver known as OpenImpala to estimate bulk-scale effective transport parameters. In particular, the boundary conditions and equations in OpenImpala were modified in order to estimate the effective diffusivity in an imaged system/geometry via a formal multi-scale homogenisation expansion. Estimates of effective pore space diffusivity were generated for a range of elementary volume sizes to estimate when the effective diffusivity values begin to converge to a single value. Results from OpenImpala were validated against a commercial finite element method package COMSOL Multiphysics (abbreviated as COMSOL). Results showed that the effective diffusivity values determined with OpenImpala were similar to those estimated by COMSOL. Tests on larger domains comparing a full image-based model to a homogenised (geometrically uniform) domain that used the effective diffusivity parameters showed differences below 2 % error, thus verifying the accuracy of the effective diffusivity estimates. Finally, we compared OpenImpala’s parallel computing speeds to COMSOL. OpenImpala consistently ran simulations within fractions of minutes, which was two orders of magnitude faster than COMSOL providing identical supercomputing specifications. In conclusion, we demonstrated OpenImpala’s utility as part of an on-site tomography processing pipeline allowing for fast and agile assessment of porous media processes and to guide imaging campaigns while they are happening at synchrotron beamlines.
Liquid submerged fermentation by selected microbial strains for onion skins valorization and its effects on polyphenols
Authors: Ramires Francesca Anna , Bavaro Anna Rita , D’Antuono Isabella , Linsalata Vito , D’Amico Leone , Baruzzi Federico , Pinto Loris , Tarantini Annamaria , Garbetta Antonella , Cardinali Angela , Bleve Gianluca 
Published: July 2023

AbstractOnion skins, actually recycled as organic fertilizers, could be used as a substrate in environmental-friendly bioprocesses to recover high-value bioactive compounds and food ingredients.In this work, a bioprospecting method was carried out including 94 bacterial and 45 yeast strains from several agri-food and environmental niches to verify their ability to grow on onion skins as unique nutrients source.Red and yellow onion skins were assessed by newly selected starter-driven liquid submerged fermentation assays mainly aimed at the release and modification of polyphenols through microbial activities. Fermented onion skins were also investigated as a inexpensive favourable source of microbial enzymes (amylases, proteases, lipases, esterases, cellulases, xylanases).In red onion skins, the treatment with Lactiplantibacillus plantarum TB 11–32 produced a slight increase of bioactive compounds in terms of total phenolics, whereas with the yeast strain Zygosaccharomyces mrakii CL 30 − 29 the quercetin aglycone content increased of about 25% of the initial raw material.In yellow onion skins inoculated, the highest content of phenolic compounds was detected with the yeast strain Saccharomyces cerevisiae En SC, while quercetin aglycone increased of about 60% of the initial raw material in presence of the bacterial strain L. plantarum C 180 − 34.In conclusion, the proposed microbial pre-treatment method can be a potential strategy to re-use onion skins as a fermentation substrate, and as a first step in the development of a biorefinery process to produce value-added products from onion by-products.
Power Usage Effectiveness in Stratosphere Based Computing Platforms: Re-evaluation and Need to Re-establish Performance Benefits via an Intelligent Light Server Selection Architecture
Authors: Periola A. A. 
Published: July 2023

AbstractThe need to reduce data center operational costs has necessitated siting cloud computing platforms in cold locations such as the stratosphere. The stratosphere has also been found to play an important role in understanding life origins as it hosts life forms. The use of stratosphere based computing platforms however requires the hosting of multiple server payloads (requiring high energy consumption) at a higher altitude. In addition, smaller server payloads lead to smaller sized stratospheric computing platforms (SCPs) which limit interaction with stratospheric organisms. However, these challenges are not considered when designing SCPs. Hence, there is a risk of wrongly evaluating the power usage effectiveness (PUE) associated with SCPs. In addition, there is a risk of installing and deploying large sized SCPs thereby leading to contamination and limiting research potential on studying life forms. The research being presented proposes an intelligent architecture enabling the identification, selection and use of only light weight servers aboard SCPs. The incorporation of the intelligent architecture is observed to enhance the PUE by 43.9%. In addition, the use of the intelligent architecture is noted to enhance the overall PUE by 59.6% for hosting altitudes spanning the low to mid stratosphere regions. In addition, the reduction in server weight by an amount exceeding 92% is noted by simulations to enable the realization of a PUE that is close to the ideal value of unity.
Effect of square pulse current densities on anticorrosive behavior of Ni–Zn multilayer deposited coatings on mild steel
Authors: Shetty Akshatha R. , Hegde A. Chitharanjan 
Published: July 2023

AbstractThis paper reports the production of Ni–Zn multilayer alloy coating to improve the anticorrosive behavior of the mild steel material. The deposition technique follows the square wave current pulse technique. Initially, the effect of current densities on the anticorrosive behavior of the Ni–Zn was investigated. Later, the current densities were optimized in different combinations to get a multilayer of Ni–Zn with different degrees of layering. The Ni–Zn multilayer coatings were developed on the surface of mild steel with different numbers of layers by square pulsing current density of 1 Adm−2 and 3 Adm−2. The deposited Ni–Zn alloy coating was studied for its electrochemical behavior toward corrosion. Results revealed that the anticorrosive behavior of the multilayer Ni–Zn alloy coating was found to be many folds higher than that of monolayer Ni–Zn alloy coating. The comparison study of corrosion data revealed that (Ni–Zn)1/3/300 multilayer coatings are less prone to undergo corrosion among all developed monolayer and multilayer coatings. The corrosion rate of (Ni–Zn)1/3/300 was found to be less and in the range of 0.37 mm year−1 among all developed coatings.
Lenalidomide treatment of Japanese patients with myelodysplastic syndromes with 5q deletion: a post-marketing surveillance study
Authors: Uno Shuji , Motegi Yoko , Minehata Kenichi , Aoki Yasuo 
Published: July 2023

AbstractLenalidomide was approved in Japan for the treatment of patients with myelodysplastic syndromes associated with a 5q deletion (del 5q-MDS) in August 2010. A post-marketing surveillance (PMS) study enrolled 173 patients with del 5q-MDS who started lenalidomide treatment between August 2010 and September 2011 (mean ± standard deviation [SD] age 72.4 ± 9.0 years) and observed for up to 6 cycles or 6 months. Adverse drug reactions (ADRs) and serious ADRs were reported in 78.0% and 50.9% of patients. The most commonly observed ADRs were thrombocytopenia or platelet count decreased (46.2%), neutropenia or neutrophil count decreased (42.2%), and rash (23.1%). Of 114 patients who were red blood cell transfusion-dependent at baseline, 39 (34.2%) achieved transfusion independence during lenalidomide treatment. Of 173 patients, 19 (11.0%) had confirmed acute myeloid leukemia (AML) progression during the study. Moreover, long-term follow-up (3 years) was available for 68 of the 173 patients, of whom 12 (17.6%) progressed to AML during the additional period. This PMS study investigated the safety and effectiveness of lenalidomide in patients with del 5q-MDS. No new safety concerns were noted in routine clinical use in Japan and no evidence was found for an increased risk of AML progression following lenalidomide treatment.
Nitrogen incorporated oxygen vacancy enriched MnCo2Ox/BiVO4 photoanodes for efficient and stable photoelectrochemical water splitting
Authors: Xu Liangcheng , Zhang Yingjuan , Liu Boyan , Wang Xin , Zhu Gangqiang , Wang Lianzhou , Wang Songcan , Huang Wei 
Published: July 2023

AbstractOxygen vacancies in oxygen evolution cocatalysts (OECs) can significantly improve the photoelectrochemical (PEC) water splitting performance of photoanodes. However, OECs with abundant oxygen vacancies have a poor stability when exposing to the highly-oxidizing photogenerated holes. Herein, we partly fill oxygen vacancies in a MnCo2Ox OEC with N atoms by a combined electrodeposition and sol-gel method, which dramatically improves both photocurrent density and stability of a BiVO4 photoanode. The optimized N filled oxygen vacancy-rich MnCo2Ox/BiVO4 photoanode (3 at.% of N) exhibits an outstanding photocurrent density of 6.5 mA·cm−2 at 1.23 VRHE under AM 1.5 G illumination (100 mW·cm−2), and an excellent stability of over 150 h. Systematic characterizations and theoretical calculations demonstrate that N atoms stabilize the defect structure and modulate the surface electron distribution, which significantly enhances the stability and further increases the photocurrent density. Meanwhile, other heteroatoms such as carbon, phosphorus, and sulfur are confirmed to have similar effects on improving PEC water splitting performance of photoanodes.
Soft computing models for assessing bond performance of reinforcing bars in concrete at high temperatures
Authors: Albostami Asad S. , Al-Hamd Rwayda Kh. S. , Alzabeebee Saif 
Published: July 2023

AbstractThe bond between steel and concrete in reinforced concrete structures is a multifaceted and intricate phenomenon that plays a vital role in the design and overall performance of such structures. It refers to the adhesion and mechanical interlock between the steel reinforcement bars and the surrounding concrete matrix. Under elevated temperatures, the bond is more complex under higher temperatures, yet having an accurate estimate is an important factor in design. Therefore, this paper focuses on using data-driven models to explore the performance of the concrete-steel bond under high temperatures using a Gene Expression Programming (GEP) soft computing model. The GEP models are developed to simulate the bond performance in order to understand the effect of high temperatures on the concrete-steel bond. The results were compared to the multi-objective evolutionary polynomial regression analysis (MOGA-EPR) models for different input variables. The new model would help the designers with strength predictions of the bond in fire. The dataset used for the model was obtained from experiments conducted in a laboratory setting that gathered a 316-point database to investigate concrete bond strength at a range of temperatures and with different fibre contents. This study also investigates the impact of the different variables on the equation using sensitivity analysis. The results show that the GEP models are able to predict bond performance with different input variables accurately. This study provides a useful tool for engineers to better understand the concrete-steel bond behaviour under high temperatures and predict concrete-steel bond performance under high temperatures.