bluuebunny/crossref_metadata_2025_split huggingface dataset:
The composition of subduction zone fluids and the origin of the trace element enrichment in arc magmas
Authors: Rustioni Greta , Audetat Andreas , Keppler Hans 
Published: June 2021

AbstractThe partitioning of major and trace elements between eclogite and aqueous fluids with variable salinity was studied at 700–800 °C and 4–6 GPa in piston cylinder and multi anvil experiments. Fluid compositions were determined using the diamond trap technique combined with laser ablation ICP-MS measurements in the frozen state. In addition to NaCl, SiO2 is the main solute in the fluids. The fluid/eclogite partition coefficients of the large ion lithophile elements (LILE), such as Rb, Cs, Sr, and Ba as well as those of the light rare earths (LREE), of Pb, and of U increase by up to three orders of magnitude with salinity. These elements will therefore be efficiently transported by saline fluids. On the other hand, typical high field strength elements, such as Ti, Nb, and Ta, are not mobilized even at high salinities. Increasing temperature and pressure gradually increases the partitioning into the fluid. In particular, Th is mobilized by silica-rich fluids at 6 GPa already at low salinities. We show that we can fully reproduce the trace element enrichment pattern of primitive arc basalts by adding a few percent of saline fluid (with 5–10 wt% Cl) released from the basaltic slab to the zone of melting in the mantle wedge. Assuming 2 wt% of rutile in the eclogite equilibrated with the saline fluid produces a negative Nb Ta anomaly that is larger than in most primitive arc basalts. Therefore, we conclude that the rutile fraction in the subducted eclogite below most arcs is likely < 1 wt%. In fact, saline fluids would even produce a noticeable negative Nb Ta anomaly without any rutile in the eclogite residue. Metasomatism by sediment melts alone, on the other hand, is unable to produce the enrichment pattern seen in arc basalts. We, therefore, conclude that at least for primitive arc basalts, the release of hydrous fluids from the basaltic part of the subducted slab is the trigger for melting and the main agent of trace element enrichment. The contribution of sediment melts to the petrogenesis of these magmas is likely negligible. In the supplementary material, we provide a “Subduction Calculator” in Excel format, which allows the calculation of the trace element abundance pattern in primitive arc basalts as function of fluid salinity, the amount of fluid released from the basaltic part of the subducted slab, the fluid fraction added to the source, and the degree of melting.
Planned surgery in the COVID-19 pandemic: a prospective cohort study from Nottingham
Authors: Catton J , Banerjea A , Gregory S , Hall C , Crooks CJ , Lewis-Lloyd CA , Marshall A , Humes DJ 
Published: June 2021

Abstract
Purpose
Globally planned surgical procedures have been deferred during the current COVID-19 pandemic. The study aimed to report the outcomes of planned urgent and cancer cases during the current pandemic using a multi-disciplinary prioritisation group.

Methods
A prospective cohort study of patients having urgent or cancer surgery at a NHS Trust from 1st March to 30th April 2020 who had been prioritised by a multi-disciplinary COVID Surgery group. Rates of post-operative PCR positive and suspected COVID-19 infections within 30 days, 30-day mortality and any death related to COVID-19 are reported.

Results
Overall 597 patients underwent surgery with a median age of 65 years (interquartile range (IQR) 54–74 years). Of these, 86.1% (514/597) had a current cancer diagnosis. During the period, 60.8% (363/597) of patients had surgery at the NHS Trust whilst 39.2% (234/597) had surgery at Independent Sector hospitals. The incidence of COVID-19 in the East Midlands was 193.7 per 100,000 population during the study period. In the 30 days following surgery, 1.3% (8/597) of patients tested positive for COVID-19 with all cases at the NHS site. Overall 30-day mortality was 0.7% (4/597). Following a PCR positive COVID-19 diagnosis, mortality was 25.0% (2/8). Including both PCR positive and suspected cases, 3.0% (18/597) developed COVID-19 infection with 1.3% at the independent site compared to 4.1% at the NHS Trust (p=0.047).

Conclusions
Rates of COVID-19 infection in the post-operative period were low especially in the Independent Sector site. Mortality following a post-operative diagnosis of COVID-19 was high.
PuraStat in gastrointestinal bleeding: results of a prospective multicentre observational pilot study
Authors: Branchi Federica , Klingenberg-Noftz Rolf , Friedrich Kristina , Bürgel Nataly , Daum Severin , Buchkremer Juliane , Sonnenberg Elena , Schumann Michael , Treese Christoph , Tröger Hanno , Lissner Donata , Epple Hans-Jörg , Siegmund Britta , Stroux Andrea , Adler Andreas , Veltzke-Schlieker Winfried , Autenrieth Daniel , Leonhardt Silke , Fischer Andreas , Jürgensen Christian , Pape Ulrich-Frank , Wiedenmann Bertram , Möschler Oliver , Schreiner Maximilian , Strowski Mathias Z. , Hempel Volkmar , Huber Yvonne , Neumann Helmut , Bojarski Christian 
Published: June 2021

Abstract
Background
A recently developed haemostatic peptide gel for endoscopic application has been introduced to improve the management of gastrointestinal bleeding. The aim of this pilot study was to evaluate the feasibility, safety, efficacy and indication profiles of PuraStat in a clinical setting.

Methods
In this prospective observational multicentre pilot study, patients with acute non-variceal gastrointestinal bleeding (upper and lower) were included. Primary and secondary application of PuraStat was evaluated. Haemoglobin, prothrombin time, platelets and transfusion behaviour were documented before and after haemostasis. The efficacy of PuraStat was assessed during the procedure, at 3 days and 1 week after application.

Results
111 patients with acute gastrointestinal bleeding were recruited into the study. 70 percent (78/111) of the patients had upper gastrointestinal bleeding and 30% (33/111) had lower gastrointestinal bleeding. After primary application of PuraStat, initial haemostatic success was achieved in 94% of patients (74/79, 95% CI 88–99%), and in 75% of the patients when used as a secondary haemostatic product, following failure of established techniques (24/32, 95% CI 59–91%). The therapeutic success rates (absence of rebleeding) after 3 and 7 days were 91% and 87% after primary use, and 87% and 81% in all study patients. Overall rebleeding rate at 30 day follow-up was 16% (18/111). In the 5 patients who finally required surgery (4.5%), PuraStat allowed temporary haemostasis and stabilisation.

Conclusions
PuraStat expanded the therapeutic toolbox available for an effective treatment of gastrointestinal bleeding sources. It could be safely applied and administered without complications as a primary or secondary therapy. PuraStat may additionally serve as a bridge to surgery in order to achieve temporary haemostasis in case of refractory severe bleeding, possibly playing a role in preventing immediate emergency surgery.
A PCA-based clustering algorithm for the identification of stratiform and convective precipitation at the event scale: an application to the sub-hourly precipitation of Sicily, Italy
Authors: Sottile Gianluca , Francipane Antonio , Adelfio Giada , Noto Leonardo V. 
Published: June 2021

AbstractUnderstanding the structure of precipitation and its separation into stratiform and convective components is still today one of the important and interesting challenges for the scientific community. Despite this interest and the advances made in this field, the classification of rainfall into convective and stratiform components is still today not trivial. This study applies a novel criterion based on a clustering approach to analyze a high temporal resolution precipitation dataset collected for the period 2002–2018 over the Sicily (Italy). Starting from the rainfall events obtained from this dataset, the developed methodology makes it possible to classify the rainfall events into four different classes, which can be related to the convective and stratiform components of the events on the basis of their hyetograph shapes and average intensities. The results show that the occurrence of stratiform events is always much higher than the convective ones, especially in the winter and spring seasons, while from the summer to the mid-autumn the rainfall depth due to convective events results to be higher than that due to the stratiform events. Moreover, the comparison with a more widely accepted separation methodology demonstrates the physical consistency of the proposed methodology.
Machine learning for computationally efficient electrical loads estimation in consumer washing machines
Authors: Casagrande Vittorio , Fenu Gianfranco , Pellegrino Felice Andrea , Pin Gilberto , Salvato Erica , Zorzenon Davide 
Published: June 2021

AbstractEstimating the wear of the single electrical parts of a home appliance without resorting to a large number of sensors is desirable for ensuring a proper level of maintenance by the manufacturers. Deep learning techniques can be effective tools for such estimation from relatively poor measurements, but their computational demands must be carefully considered, for the actual deployment. In this work, we employ one-dimensional Convolutional Neural Networks and Long Short-Term Memory networks to infer the status of some electrical components of different models of washing machines, from the electrical signals measured at the plug. These tools are trained and tested on a large dataset (502 washing cycles $$\approx$$
≈
1000 h) collected from four different washing machines and are carefully designed in order to comply with the memory constraints imposed by available hardware selected for a real implementation. The approach is end-to-end; i.e., it does not require any feature extraction, except the harmonic decomposition of the electrical signals, and thus it can be easily generalized to other appliances.
Measurement of S-glutathionylated proteins by HPLC
Authors: Giustarini Daniela , Milzani Aldo , Dalle-Donne Isabella , Rossi Ranieri 
Published: June 2021

AbstractS-glutathionylated proteins (GSSP), i.e., protein-mixed disulfides with glutathione (GSH), are considered a suitable biomarker of oxidative stress. In fact, they occur within cells at low level and their concentration increases markedly under pro-oxidant conditions. Plasma is something different, since it is physiologically rich in S-thiolated proteins (RSSP), i.e., protein-mixed disulfides with various types of low molecular mass thiols (LMM-SH). However, albumin, which is largely the most abundant plasma protein, possesses a cysteine residue at position 34 that is mostly reduced (about 60%) under physiological conditions, but easily involved in the formation of additional RSSP in the presence of oxidants. The quantification of GSSP requires special attention to sample handling, since their level can be overestimated as a result of artefactual oxidation of GSH. We have developed the present protocol to avoid this methodological problem. Samples should be treated as soon as possible after their collection with the alkylating agent N-ethylmaleimide that masks –SH groups and prevents their oxidation. The GSH released from mixed disulfides by reduction with dithiothreitol is then labeled with the fluorescent probe monobromobimane and quantified by HPLC. The method can be applied to many different biological samples, comprising blood components, red blood cell plasma membrane, cultured cells, and solid organs from animal models.
Defining business model key performance indicators using intentional linguistic summaries
Authors: Gilsing Rick , Wilbik Anna , Grefen Paul , Turetken Oktay , Ozkan Baris , Adali Onat Ege , Berkers Frank 
Published: June 2021

AbstractTo sustain competitiveness in contemporary, fast-paced markets, organizations increasingly focus on innovating their business models to enhance current value propositions or to explore novel sources of value creation. However, business model innovation is a complex task, characterized by shifting characteristics in terms of uncertainty, data availability and its impact on decision making. To cope with such challenges, business model evaluation is advocated to make sense of novel business models and to support decision making. Key performance indicators (KPIs) are frequently used in business model evaluation to structure the performance assessment of these models and to evaluate their strategic implications, in turn aiding business model decision making. However, given the shifting characteristics of the innovation process, the application and effectiveness of KPIs depend significantly on how such KPIs are defined. The techniques proposed in the existing literature typically generate or use quantitatively oriented KPIs, which are not well-suited for the early phases of the business model innovation process. Therefore, following a design science research methodology, we have developed a novel method for defining business model KPIs, taking into account the characteristics of the innovation process, offering holistic support toward decision making. Building on theory on linguistic summarization, we use a set of structured templates to define qualitative KPIs that are suitable to support early-phase decision making. In addition, we show how these KPIs can be gradually quantified to support later phases of the innovation process. We have evaluated our method by applying it in two real-life business cases, interviewing 13 industry experts to assess its utility.
A technique for evaluating and improving the semantic transparency of modeling language notations
Authors: Bork Dominik , Roelens Ben 
Published: June 2021

AbstractThe notation of a modeling language is of paramount importance for its efficient use and the correct comprehension of created models. A graphical notation, especially for domain-specific modeling languages, should therefore be aligned to the knowledge, beliefs, and expectations of the targeted model users. One quality attributed to notations is their semantic transparency, indicating the extent to which a notation intuitively suggests its meaning to untrained users. Method engineers should thus aim at semantic transparency for realizing intuitively understandable notations. However, notation design is often treated poorly—if at all—in method engineering methodologies. This paper proposes a technique that, based on iterative evaluation and improvement tasks, steers the notation toward semantic transparency. The approach can be efficiently applied to arbitrary modeling languages and allows easy integration into existing modeling language engineering methodologies. We show the feasibility of the technique by reporting on two cycles of Action Design Research including the evaluation and improvement of the semantic transparency of the Process-Goal Alignment modeling language notation. An empirical evaluation comparing the new notation against the initial one shows the effectiveness of the technique.
Predicting approximate seismic responses in multistory buildings from real-time earthquake source information, for earthquake early warning applications
Authors: Cremen Gemma , Velazquez Omar , Orihuela Benazir , Galasso Carmine 
Published: June 2021

AbstractRegional earthquake early warning (EEW) alerts and related risk-mitigation actions are often triggered when the expected value of a ground-motion intensity measure (IM), computed from real-time magnitude and source location estimates, exceeds a predefined critical IM threshold. However, the shaking experienced in mid- to high-rise buildings may be significantly different from that on the ground, which could lead to sub-optimal decision-making (i.e., increased occurrences of false and missed EEW alarms) with the aforementioned strategy. This study facilitates an important advancement in EEW decision-support, by developing empirical models that directly relate earthquake source parameters to resulting approximate responses in multistory buildings. The proposed models can leverage real-time earthquake information provided by a regional EEW system, to provide rapid predictions of structure-specific engineering demand parameters that can be used to more accurately determine whether or not an alert is triggered. We use a simplified continuum building model consisting of a flexural/shear beam combination and vary its parameters to capture a wide range of deformation modes in different building types. We analyse the approximate responses for the building model variations, using Italian accelerometric data and corresponding source parameter information from 54 earthquakes. The resulting empirical prediction equations are incorporated in a real-time Bayesian framework that can be used for building-specific EEW applications, such as (1) early warning of floor-shaking sensed by occupants; and (2) elevator control. Finally, we demonstrate the improvement in EEW alert accuracy that can be achieved using the proposed models.
Anisotropy of Unstably Stratified Near-Surface Turbulence
Authors: Stiperski Ivana , Chamecki Marcelo , Calaf Marc 
Published: June 2021

AbstractClassic Monin–Obukov similarity scaling states that in a stationary, horizontally homogeneous flow, in the absence of subsidence, turbulence is dictated by the balance between shear production and buoyancy production/destruction, whose ratio is characterized by a single universal scaling parameter. An evident breakdown in scaling is observed though, through large scatter in traditional scaling relations for the horizontal velocity variances under unstable stratification, or more generally in complex flow conditions. This breakdown suggests the existence of processes other than local shear and buoyancy that modulate near-surface turbulence. Recent studies on the role of anisotropy in similarity scaling have shown that anisotropy, even if calculated locally, may encode the information about these missing processes. We therefore examine the possible processes that govern the degree of anisotropy in convective conditions. We first use the reduced turbulence-kinetic-energy budget to show that anisotropy in convective conditions cannot be uniquely described by a balance of buoyancy and shear production and dissipation, but that other terms in the budget play an important role. Subsequently, we identify a ratio of local time scales that acts as a proxy for the anisotropic state of convective turbulence. This ratio can be used to formulate a new non-dimensional group. Results show that building on this approach the role of anisotropy in scaling relations over complex terrain can be placed into a more generalized framework.
Topography of Movement-Related Delta and Theta Brain Oscillations
Authors: Körmendi János , Ferentzi Eszter , Weiss Béla , Nagy Zoltán 
Published: June 2021

AbstractThe aim of this study was to analyse the high density EEG during movement execution guided by visual attention to reveal the detailed topographic distributions of delta and theta oscillations. Twenty right-handed young subjects performed a finger tapping task, paced by a continuously transited repeating visual stimuli. Baseline corrected power of scalp current density transformed EEG was statistically assessed with cluster-based permutation testing. Delta and theta activities revealed differences in their spatial properties at the time of finger tapping execution. Theta synchronization showed a contralateral double activation in the parietal and fronto-central regions, while delta activity appeared in the central contralateral channels. Differences in the spatiotemporal topography between delta and theta activity in the course of movement execution were identified on high density EEG.
Matching Local Knowledge and Environmental Change with Policy Changes in Rangeland Tenure
Authors: Peng-Peng Bai , Mancini Mattia , Du Juan , Mace Ruth 
Published: June 2021

AbstractHardin’s Tragedy of the Commons has often been cited as the rationale for the privatization of pastures throughout the world, yet rangeland degradation is still widespread. A significant body of ecological research has demonstrated negative impacts from limiting herd movement through fencing. The privatization of pastures has often followed heterogeneous patterns. We use a natural experiment in common grazing areas on the eastern Qinghai-Tibetan Plateau where land use was privatized beginning in 1999 following different land use division patterns. We measure the relationship between land use privatization paths and grassland quality using satellite data from 1989 to 2011 in five different villages, and compare how well herder environmental perceptions match satellite data. We find that rangeland degradation has significantly increased following privatization of land use, and that grassland in small individually managed fenced plots is deteriorating more significantly than in larger fenced areas with group herding. We further find that herders’ had accurate perceptions of the state of their pastures that closely match remotely sensed data.
Inductive learning of answer set programs for autonomous surgical task planning
Authors: Meli Daniele , Sridharan Mohan , Fiorini Paolo 
Published: June 2021

AbstractThe quality of robot-assisted surgery can be improved and the use of hospital resources can be optimized by enhancing autonomy and reliability in the robot’s operation. Logic programming is a good choice for task planning in robot-assisted surgery because it supports reliable reasoning with domain knowledge and increases transparency in the decision making. However, prior knowledge of the task and the domain is typically incomplete, and it often needs to be refined from executions of the surgical task(s) under consideration to avoid sub-optimal performance. In this paper, we investigate the applicability of inductive logic programming for learning previously unknown axioms governing domain dynamics. We do so under answer set semantics for a benchmark surgical training task, the ring transfer. We extend our previous work on learning the immediate preconditions of actions and constraints, to also learn axioms encoding arbitrary temporal delays between atoms that are effects of actions under the event calculus formalism. We propose a systematic approach for learning the specifications of a generic robotic task under the answer set semantics, allowing easy knowledge refinement with iterative learning. In the context of 1000 simulated scenarios, we demonstrate the significant improvement in performance obtained with the learned axioms compared with the hand-written ones; specifically, the learned axioms address some critical issues related to the plan computation time, which is promising for reliable real-time performance during surgery.
Towards a reliable implementation of least-squares collocation for higher index differential-algebraic equations—Part 1: basics and ansatz function choices
Authors: Hanke Michael , März Roswitha 
Published: June 2021

AbstractIn the two parts of the present note we discuss several questions concerning the implementation of overdetermined least-squares collocation methods for higher index differential-algebraic equations (DAEs). Since higher index DAEs lead to ill-posed problems in natural settings, the discrete counterparts are expected to be very sensitive, which attaches particular importance to their implementation. In the present Part 1, we provide a robust selection of basis functions and collocation points to design the discrete problem. We substantiate a procedure for its numerical solution later in Part 2. Additionally, in Part 1, a number of new error estimates are proven that support some of the design decisions.