bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting lake bathymetry from the topography of the surrounding terrain using deep learning
Authors: Martinsen Kenneth Thorø , Sand‐Jensen Kaj , Selvan Raghavendra 
Published: September 2023

AbstractLake morphometric features like surface area, volume, mean, and maximum depth are important predictors of many physical, biological, and ecological processes. Lake bathymetric maps that present the lake basin contours are thus an integral part of limnological investigations. Accurate but cumbersome traditional bathymetric surveys measure the depth using a lead line or echosounder. Recently, airborne bathymetric mapping using imagery or laser scanning has been attempted in shallow freshwater and coastal habitats. However, these methods depend on the ability of light to penetrate the water column, which can be problematic in eutrophic lakes and shallow lakes. To alleviate these issues, we developed and tested a deep learning model (based on the U‐net) using data from 153 lakes in Denmark to predict bathymetry using the topography of the surrounding terrain. The deep learning model performed much better (pixel‐wise mean absolute error: validation set = 1.75 and test set = 2.15 m) than baseline interpolation approaches (validation set = 3.12 m). In addition, the deep learning model generated more realistic bathymetry maps that did not suffer from interpolation artifacts. We find that the model performance improves slightly with increasing model size (number of trainable parameters) and the extent of the surrounding terrain. In addition, our pretraining procedure improved performance and reduced the time for model convergence. Because the model only relies on digital elevation data which are widely available, it can be fine‐tuned and used to predict lake bathymetry in other geographical regions.
Enhancement of Circularly Polarized Luminescence from Pulsating Nanotubules
Authors: Gu Zijian , Ma Wenyue , Feng Jun , Liu Zhaoyang , Xu Bin , Tian Wenjing 
Published: September 2023

AbstractEnhancing the dissymmetry factor (glum) is a crucial issue in developing circularly polarized luminescence (CPL) materials. Herein, based on supramolecular self‐assembly of diethyl l‐glutamate‐cyanodiarylethene (L‐GC) in mixed solution of EtOH‐H2O with different water fraction, enhanced circularly polarized emission from pulsating nanotubules is realized. In the mixture of ethanol and water (30/70, v/v), L‐GC self‐assembles into roll‐up‐type dense nanotubes and shows l‐CPL. Remarkably, by increasing the water fraction to 80% and 90%, the diameter of the roll‐up nanotubes increases and the dissymmetry factor of the nanotubes is significantly enhanced from 6.9 × 10−3 (dense nanotubes) to 3.7 × 10−2 (loose nanotubes) because of the enhanced intermolecular interactions and more ordered supramolecular stacking when increasing the water fraction. An efficient way is provided here to realize the increase of the dissymmetry factor by only changing the composition of solvents.
Predictive value of risk factors for bladder dysfunction in Chinese patients with type 2 diabetes mellitus: A case‐control study
Authors: Wang Ying , Wang Xiufen , Liang Surui , Cai Wenzhi , Chen Ling , Hu Yingjie , Hao Fengming , Ren Wei 
Published: September 2023

AbstractObjectiveTo analyze risk factors associated with bladder dysfunction in patients with type 2 diabetes mellitus (T2DM) and to construct a prediction model for early prediction of diabetic bladder dysfunction (DBD).MethodsWe included hospitalized patients with T2DM from the endocrinology department of Shenzhen Hospital, Southern Medical University, Shenzhen, China, from January 2019 to 2022. Factors associated with DBD in bivariate analysis with a p < 0.05 were included in a multivariate logistic regression analysis. Multivariate logistic regression analysis was used to determine independent risk factors and to construct a prediction model. The prediction model was presented as the model formula. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of the above risk factors and the prediction model for DBD. The model was internally verified by Boostrap resampling 1000 times.ResultsTwo hundred and eleven patients were included in this study, and they were divided into the DBD group (n = 101) and the non‐DBD group (n = 110). Eight variables showed significant significance in the bivariate analysis, including age, diabetic peripheral neuropathy (DPN), glycated hemoglobin (HbA1c), urinary microalbumin (mALB), red blood cell count (RBC), white blood cell count (WBC), absolute neutrophil count (ANC), percentage of monocyte (Mono%). Furthermore, multivariate logistic regression analysis revealed that age (OR [95% CI]: 1.077 [1.042−1.112]), p < 0.001; DPN (OR [95% CI]: 2.373 [1.013−5.561]), p = 0.047; HbA1c (OR [95% CI]: 1.170 [1.029−1.330]), p = 0.017 and ANC (OR [95% CI]: 1.234 [1.059−1.438]), p = 0.007 were independent risk factors for the DBD. The prediction model formula was Logit (p) = −6.611 + 0.074 age + 0.864 DPN + 0.157 HbA 1 c + 0.078 ANC. The area under the ROC curve (AUC) for the four risk factors were 0.676, 0.582, 0.618, and 0.674, respectively. The prediction model predicted DBD with higher accuracy than the individual risk factors, AUC = 0.817 (95% CI: 0.757−0.877), and the sensitivity and specificity were 88.1% and 50.0%, respectively. The model internal validation results showed that the AUC = 0.804 (95% CI: 0.707−0.901), and the calibration curve is close to the ideal diagonal line.ConclusionsAge, DPN, HbA1c, and ANC were risk factors for DBD. The prediction model constructed based on the four risk factors had a good predictive value for predicting the occurrence of DBD.
On functional observers for polynomial systems with nonlinear oscillations
Authors: Röbenack Klaus , Gerbet Daniel 
Published: September 2023

AbstractIn this contribution we discuss the design of functional observers for polynomial systems. Our approach is based on a high gain design employing an embedded observer. The functional to be estimated is generated from the high gain observer's state. The restriction to polynomial systems allows the representation of the system's and the observer's dynamics as polynomial ideals. For the calculations we utilize methods from algebraic geometry. Our approach is illustrated on a chaotic system.
Bilayer Couette flow over a profiled plate
Authors: Scholle Markus , Gaskell Philip H. , Ismail–Sutton Sara , Mellmann Marcel 
Published: September 2023

AbstractThe shear–driven, bilayer flow of two immiscible liquids sandwiched between a moving planar and a stationary corrugated plate, in parallel alignment and under Stokes flow conditions, is explored. The motivation, partly inspired by biomimetic considerations, is the use of surface texturing/topography to reduce friction and wear while increasing load carrying capacity in lubrication problems. The starting point of the associated mathematical formulation is a variational principle which, in addition to the classical fluid mechanical field quantities, includes potential fields enabling an elegant reformulation of the dynamic condition at the interface separating the two layers. Two methods of solution are utilised: (i) an analytic one of the field equations, boundary and interface conditions by invoking the long–wave approximation; (ii) an exact semi–analytic one, obtained after transformation to complex variables and application of a spectral method. For validation and comparison purposes a FE formulation of the classical continuity and Navier–Stokes equations is solved for. Resulting streamline patterns, interface shapes and wall shear stresses are discussed.
Sparse identification of the dynamics of a nonlinear multistable oscillator
Authors: Kamecke Steffen , Wulff Paul , Gräbner Nils , von Wagner Utz 
Published: September 2023

AbstractRecently, data‐driven modeling approaches are getting increasingly examined regarding their applicability for nonlinear mechanical or mechatronic systems. With a high data availability and often insufficiently accurate descriptions of complex behavior of real systems using established physical models, statistical models provide promising alternatives. Alongside machine learning techniques like deep neural networks, sparse regression is increasingly used to obtain models from measurement data. With sparse regression, governing equations are estimated from a given function space so that the data are explained with as few terms as possible while maintaining a low model error. This method is implemented in a framework called sparse identification of nonlinear dynamics. This paper demonstrates the application of this method on free and forced vibrations of a two degree of freedom nonlinear rotary oscillator with two stable equilibrium positions. The setup and data acquisition as well as the application of sparse identification are described. The selected function space containing the candidate functions is essential for an accurate representation of the system at hand. Monomials form a commonly used function space because they can approximate a wide variety of nonlinear characteristics. However, in this work, it is shown that monomials alone are insufficient when dry friction appears. Therefore, to account for Coulomb friction, a sign‐function is added as a candidate to the function space of monomials up to the fifth order. Adaptions of the common optimization algorithms turned out to be necessary for the inclusion of Coulomb friction. As a result, it is found that the addition of the sign‐function for Coulomb friction increases the model quality significantly.
How do different types and characteristics of green space impact mental health? A scoping review
Authors: Beute F. , Marselle M. R. , Olszewska‐Guizzo A. , Andreucci M. B. , Lammel A. , Davies Z. G. , Glanville J. , Keune H. , O'Brien L. , Remmen R. , Russo A. , de Vries S. 
Published: September 2023

Abstract

Green space matters for mental health but is under constant pressure in an increasingly urbanising world. Often there is little space available in cities for green areas, so it is vital to optimise the design and usage of these available green spaces. To achieve this, experts in planning, design and nature conservation need to know which types and characteristics of green spaces are most beneficial for residents' mental health.

A scoping review of studies that compare different green space types and characteristics on mental health was conducted. A total of 215 (experimental, observational and qualitative) papers were included in the scoping review.

This review highlights a high level of heterogeneity in study design, geographical locations, mental health outcomes and green space measures. Few of the included studies were specifically designed to enable direct comparisons between green space types and characteristics (e.g. between parks and forests). The included studies have predominantly experimental research designs looking at the effects of short‐term exposure to green space on short‐term mental health outcomes (e.g. affect and physiological stress). More studies enabled only indirect comparisons, either within the same study or between different studies.

Analysis of the direction of the mental health outcomes (positive, neutral, negative) from exposure to various types and characteristics of green space found positive (i.e. beneficial) effects across all green space types. However, green space characteristics did appear to render more diverse effects on mental health, which is especially the case for vegetation characteristics (e.g. higher vegetation density can be negative for mental health).

The scoping review reveals gaps in the present evidence base, with a specific need for more studies directly comparing green space types and characteristics within the same study. Proposed future research directions include the use of longitudinal research designs focusing on green space characteristics, considering actual exposure and systematically addressing heterogeneity in factors influencing the relation between green spaces and mental health (e.g. type of interaction, user experience).

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Optimized infusion rates for N,N‐dimethyltryptamine to achieve a target psychedelic intensity based on a modeling and simulation framework
Authors: Eckernäs Emma , Koomen Jeroen , Timmermann Christopher , Carhart‐Harris Robin , Röshammar Daniel , Ashton Michael 
Published: September 2023

AbstractN,N‐dimethyltryptamine (DMT) is a psychedelic compound that is being studied as a therapeutic option in various psychiatric disorders. Due to its short half‐life, continuous infusion of DMT has been proposed to extend the psychedelic experience and potential therapeutic effects. The primary aim of this work was to design an infusion protocol for DMT based on a desired level of psychedelic intensity using population pharmacokinetic/pharmacodynamic modeling. As a secondary aim, the impact of choosing a continuous variable or a bounded integer pharmacokinetic/pharmacodynamic model to inform such an infusion protocol was investigated. A previously published continuous variable model and two newly developed bounded integer models were used to assess optimal doses for achieving a target response. Simulations were performed to identify an optimal combination of a bolus dose and an infusion rate. Based on the simulations, optimal doses to achieve intensity ratings between 7 and 9 (possible range = 0–10) were a bolus dose of 16 mg DMT fumarate followed by an infusion rate of 1.4 mg/min based on the continuous variable model and 14 mg with 1.2 mg/min for the two bounded integer models. However, the proportion within target was low (<53%) for all models, indicating that individual dose adjustments would be necessary. Furthermore, some differences between the models were observed. The bounded integer models generally predicted lower proportions within a target of 7–9 with higher proportions exceeding target compared with the continuous variable model. However, results varied depending on target response with the major differences observed at the boundaries of the scale.
Rapid and simple identification of trace amounts of sodium azide in beverages and bodily fluids followed by derivatization and liquid chromatography–electrospray ionization tandem mass spectrometry
Authors: Prihed Hagit , Shifrovitch Avital , Shamai Yamin Tamar , Madmon Moran , Belay Chen , Blanca Merav , Weissberg Avi 
Published: September 2023

RationaleSodium azide (NaN3) is a toxic chemical agent to humans by ingestion and inhalation with a growing number of intentional exposures and accidental cases over the last few decades. Due to its low molecular weight and lack of any chromophore, its retention and detection by reverse‐phase liquid chromatography–ultraviolet–mass spectrometry methods are a challenging task.MethodsTo be able to confirm azide exposure, we have developed a method to identify azide in both beverages and bodily fluids. The identification of azide (N3−) is based on derivatization with N‐(2‐(bromomethyl)benzyl)‐N,N‐diethylethanaminium bromide (CAX‐B) at 25°C for 15 min followed by LC/ESI‐MS/MS analysis, with no other sample preparation.ResultsThe azide after derivatization (CAX‐N3) was stable, retainable by LC and sensitively detected by selected reaction monitoring. The ESI‐MS/MS fragmentation of the M+ precursor ion produced characteristic product ions at m/z 118, 100, 91 and 86. The calibration curves for CAX‐N3 showed linearity over two orders of magnitude with R2 value of 0.99. Low limits of identification of 0.1–0.5 ng/mL were obtained in all investigated matrices (drinking water, tea, orange juice, plasma and urine).ConclusionsCompared with previously reported chromatography‐based methods, this method that was based on derivatization and LC/ESI‐MS/MS analysis was substantially more sensitive, simpler and faster. The method can be used for forensic investigation to confirm azide exposure from fatal use to much smaller intoxication dose.
Comprehensive metabolite profiling of trimetazidine in camels using high‐resolution accurate mass spectrometry: Implications for doping control
Authors: Nalakath Jahfar , PT Rasik , Kadry Ahmed , Palathinkal Ansar Babu , Praseen Ondern Komathu , Nelliyott Ibrahimwaseem , Hebel Christiana , Selvapalam N. , Nagarajan E. R. 
Published: September 2023

RationaleTrimetazidine and its metabolites are prohibited substances in sports. With a growing number of adverse findings in human athletes, it is crucial to develop doping control strategies that include screening for trimetazidine in animal sports. This study aims to detect and characterize trimetazidine and its metabolites for doping control in camel racing.MethodsCamel urine and plasma samples were collected from four healthy animals following a single oral dose of trimetazidine. In vitro investigations were conducted using camel liver samples. Liquid–liquid extraction and solid‐phase extraction techniques were employed for the extraction of trimetazidine metabolites from plasma and urine matrices. The metabolites were analyzed using a Thermo Orbitrap Exploris LC‐MS system with optimized settings to achieve maximum sensitivity and accurate mass measurements.ResultsComprehensive metabolite profiling of trimetazidine in camels revealed the identification of seven phase I and five phase II metabolites. Phase I metabolites were primarily formed through dealkylation, while phase II metabolites were dominated by glucuronide conjugation of demethylated trimetazidine. The findings provided insights into the distinct metabolic pathways and biotransformation patterns of trimetazidine in camels under the experimental conditions.ConclusionThe developed method enables detection and characterization of trimetazidine and its metabolites in camels. The identified metabolites have the potential to serve as marker metabolites for trimetazidine abuse in camel racing. This study provides valuable insights into the metabolism of trimetazidine in camels.
High‐precision Sr and Nd isotope characterization of BHVO‐2 reference material by thermal ionization mass spectrometry
Authors: Fuenlabrada José M. 
Published: September 2023

RationaleControl over accuracy and precision in isotope geochemical analysis is highly necessary for reliable results. Use of reference materials in Sr and Nd isotope geochemistry provides a means of validating optimal sample preparation and instrument configurations.MethodsA comprehensive data set of Sr and Nd isotope analyses of BHVO‐2 reference material was obtained by thermal ionization mass spectrometry (TIMS). The intention is to assist other researchers in evaluating isotopic analyses of geological samples with similar chemical matrix.Results87Sr/86Sr isotope ratios analyzed in BHVO‐2 reference material over 88 replicas from 2015 to the present provide an average value of 0.703485 ± 0.000024. In turn, 143Nd/144Nd isotope ratios in 62 replicas show an average value of 0.512978 ± 0.000012. The high number of analyses here presented ensures a high reproducibility over time in a non‐certified material for isotopic analysis of these two elements.ConclusionsThis high precision and reproducibility of Sr and Nd analysis by TIMS provide a basis for validation of analytical processes in the absence of certified reference materials and support the correlation of isotopic results between laboratories and the overall improvement in the interpretation of isotope results for geological, environmental and archeological samples.
Molecular Doping Modulation and Applications of Structure‐Sorted Single‐Walled Carbon Nanotubes: A Review
Authors: Liu Ye , Zhao Zhigang , Kang Lixing , Qiu Song , Li Qingwen 
Published: September 2023

AbstractSingle‐walled carbon nanotubes (SWCNTs) that have a reproducible distribution of chiralities or single chirality are among the most competitive materials for realizing post‐silicon electronics. Molecular doping, with its non‐destructive and fine‐tunable characteristics, is emerging as the primary doping approach for the structure‐controlled SWCNTs, enabling their eventual use in various functional devices. This review provides an overview of important advances in the area of molecular doping of structure‐controlled SWCNTs and their applications. The first part introduces the underlying physical process of molecular doping, followed by a comprehensive survey of the commonly used dopants for SWCNTs to date. Then, it highlights how the convergence of molecular doping and structure‐sorting strategies leads to significantly improved functionality of SWCNT‐based field‐effect transistor arrays, transparent electrodes in optoelectronics, thermoelectrics, and many emerging devices. At last, several challenges and opportunities in this field are discussed, with the hope of shedding light on promoting the practical application of SWCNTs in future electronics.
Screening, preparation, and prototyping of metal–organic frameworks for adsorptive carbon capture under humid conditions
Authors: Jiang Long , Yong Jinyuan , Xie Renyu , Xie Pengfei , Zhang Xuejun , Chen Zhijie , Bao Zongbi 
Published: September 2023

AbstractAdsorption‐based carbon capture has been recognized as an attractive method for mitigating global warming. Metal–organic frameworks (MOFs) are promising candidate adsorbents for this purpose due to their high adsorption uptake and selectivity for carbon dioxide. However, in real‐world applications, such as direct air capture, the presence of moisture in the feed gas may pose a grand challenge for CO2 adsorption in MOFs. This paper aims to address the issue of water–CO2 co‐adsorption in MOFs and present screening criteria for selecting MOFs that preferentially adsorb CO2 under humid conditions. First, we uncover a comprehensive overview of CO2–water co‐adsorption characteristics of various MOFs. Then, the high‐throughput screening methods are summarized. Both computational and experimental efforts have been dedicated to identify the promising MOFs for humid CO2 capture. According to the screening results and adsorption mechanism, the optimal preparation strategies are proposed to modulate the effect of water on CO2 uptake in MOFs. Finally, current MOF‐based CO2 capture prototypes are presented to evaluate their practical feasibility and performance. This work could offer valuable guidance for the development and application of MOFs for CO2 capture in the presence of water and inspire further research in this field.