bluuebunny/crossref_metadata_2025_split huggingface dataset:
Zooplankton size-structure dynamics of a lowland tropical floodplain lake
Authors: Toruan Reliana Lumban , Lukman Lukman , Coggins Liah X. , Ghadouani Anas 
Published: August 2023

AbstractFloodplains are highly complex ecosystems representing high biodiversity and conservation values, but they are also one of the world’s most threatened ecosystems due to extensive development and anthropogenic activities. Lake Tempe is a lowland riverine floodplain lake in Sulawesi Island, Indonesia, that is subject to multiple stressors such as flow alteration, eutrophication and invasive species. In this study, the dynamics of the zooplankton community size structure was investigated in Lake Tempe. Five size-based metrics, including zooplankton mean body size, total abundance, total, biomass, and normalised biomass size spectra (NBSS) slope and intercept were assessed from net-sampled zooplankton collected monthly from March to December 2016, and the role of environmental variables in shaping these size-based metrics were also examined. Zooplankton community size structure is a useful metric as it is less labour intensive than traditional approaches, provides more data accuracy and does not require highly specialised taxonomic expertise. The zooplankton community in Lake Tempe was characterised by high density of small-sized zooplankton with an average mean body size < 500 µm equivalent spherical diameter. While the zooplankton density was characterised by the dominance of the size class 300–700 µm, there was evidence of a significant contribution of the size > 700 µm towards total biomass. Seasonal hydrological regimes, water temperature and eutrophication parameters, as indicated by total phosphorus and chlorophyll-a concentration, had a significant role in driving the variability of zooplankton community size structure in this system. The results of this study are not only a significant step in providing critical baseline information on the zooplankton assemblage of Lake Tempe, but is also a significant contribution to the overall understanding of zooplankton community structure in tropical lakes, and will aid in improving lake management plans in these regions.
On the refined Kaneko–Zagier conjecture for general integer indices
Authors: Ono Masataka , Yamamoto Shuji 
Published: August 2023

AbstractThe refined Kaneko–Zagier conjecture claims that the algebras spanned by two kinds of “completed” finite multiple zeta values, called$${\widehat{\mathcal {A}}}$$A^- and$${\widehat{\mathcal {S}}}$$S^-MZVs, are isomorphic. Recently, Komori defined$${\widehat{\mathcal {S}}}$$S^-MZVs of general integer (i.e., not necessarily positive) indices, extending the existing definition for positive indices. In view of the refined Kaneko–Zagier conjecture, Komori’s work suggests that these extended values are closely connected to$${\widehat{\mathcal {A}}}$$A^-MZVs of general indices, which can be defined in an obvious way. In this paper, we show that the generalization of the refined Kaneko–Zagier conjecture for general integer indices is actually deduced from the conjecture for positive indices. The key ingredient is an inductive formula for$${\widehat{\mathcal {A}}}$$A^-MZVs or$${\widehat{\mathcal {S}}}$$S^-MZVs of indices which contain at least one non-positive entry.
Influence of drought stress on increasing bioactive compounds of pomegranate (Punica granatum L.) juice. Exploratory study using LC–MS-based untargeted metabolomics approach
Authors: Gómez-Bellot M. J. , Garcia C. J. , Parra A. , Vallejo F. , Ortuño M. F. 
Published: August 2023

AbstractWater deficit is one of the most important abiotic factors that reduce the agricultural productivity. The impact of irrigation levels on bioactive compounds of one commercial pomegranate cultivar (‘Mollar de Elche’) was studied through LC–MS-based untargeted metabolomics approach. Two treatments were applied to explore crop responses to the timing and the regime of the irrigation applications. The main goal of the present study was to validate the untargeted metabolomics approach as analytical tool to find new markers related with the water deficit. Robust classification and prediction model was built with the use of supervised technique, partial least squares discriminant analysis (PLS-DA). The results revealed that pomegranate juices obtained from plants grown under DIr conditions experimented physiological stress, which significantly increased their bioactive compounds (polyphenols, phenylpropanoids, peptides, benzoic acid, tannins, and phospholipids) in comparison with the Control treatments. The results indicate that controlled irrigation stress would increase the production of bioactive compounds by increasing the phenylpropanoids metabolism. New metabolites were tentatively identified in pomegranate juice by the untargeted metabolomics techniques. This study showed, for the first time, the satisfactory application of the untargeted metabolomics approach using an UHPLC-QTOF system to identify bioactive secondary metabolites from pomegranate juices to discriminate among different irrigation conditions.
Outcome of Children with Transjugular Intrahepatic Portosystemic Shunt: A Meta-Analysis of Individual Patient Data
Authors: Deniz Sinan , Schinner Regina , Monroe Eric J. , Horslen Simon , Srinivasa Ravi N. , Lv Yong , Fan Daiming , Han Guohong , Sarma Moinak Sen , Srivastava Anshu , Poddar Ujjal , Yadav Rajanikant , Hoang Thi Phuong Thao , Lange Christian M. , Öcal Osman , Ricke Jens , Seidensticker Max , Lurz Eberhard , Di Giorgio Angelo , D’Antiga Lorenzo , Wildgruber Moritz 
Published: August 2023

Abstract
Purpose
The purpose of the study was to investigate outcome after pediatric transjugular intrahepatic portosystemic shunt (TIPS) with respect to survival

Material and Methods
After searching for studies on TIPS in children in Ovid, Medline, Embase, Scopus and Cochrane published between 2000 and 2022, individual patient data were retrieved from five retrospective cohorts. Overall survival (OS) and transplant-free survival (TFS) were calculated using Kaplan–Meier analysis and log-rank test and compared to the indication (ascites vs. variceal bleeding) as well as to the level of obstruction (pre-hepatic vs. hepatic vs. post-hepatic). Additionally, TIPS patency was analyzed.

Results
n = 135 pediatric patients were included in the final analysis. Indication for pediatric TIPS creation was heterogeneous among the included studies. TIPS patency decreased from 6 to 24 months, subsequent pediatric liver transplantation was performed in 22/135 (16.3%) of cases. The presence of ascites was related with poorer TFS (HR 2.3, p = 0.023), while variceal bleeding was not associated with impaired survival. Analysis of the level of obstruction (pre-hepatic, hepatic and post-hepatic) failed to prove significantly reduced OS for post-hepatic obstruction (HR 3.2, p = 0.092) and TFS (HR 1.3, p = 0.057). There was no difference in OS and TFS according to age at time of TIPS placement.

Conclusions
The presence of ascites associates with impaired survival after TIPS in children, with no differences in survival according to the age of the child. Interventional shunt procedures can be considered feasible for all ages.

Level of Evidence
Level 2a.

Graphical Abstract
Bidisperse magnetorheological fluids utilizing composite polypyrrole nanotubes/magnetite nanoparticles and carbonyl iron microspheres
Authors: Munteanu Andrei , Plachý Tomáš , Munteanu Lenka , Ngwabebhoh Fahanwi Asabuwa , Stejskal Jaroslav , Trchová Miroslava , Kubík Michal , Sedlačík Michal 
Published: August 2023

AbstractConductive polypyrrole nanotubes were synthesized with a two-step one-pot synthesis. During synthesis, the nanotubes were decorated with magnetite nanoparticles at different concentrations granting them magnetic properties. The characterization of the tubes revealed differences from the theoretical reactions. A bidisperse magnetorheological fluid (MRF) was prepared by mixing the composite polypyrrole nanotubes/magnetite nanoparticles with commercial carbonyl iron spherical microparticles in silicone oil. The rheological properties of the bidisperse system were studied under the presence of magnetic field at room and elevated temperature. An enhancement of the MR effect with the presence of the nanotubes was observed when compared with a standard MRF consisted only of magnetic microparticles. Due to the faster magnetic saturation of the nanotubes, this enhancement is exceptionally high at low magnetic fields. The stability of the system is studied under dynamic conditions where it is revealed that the nanotubes keep the standard particles well dispersed with the sedimentation improving by more than 50%.
Machine learning for adaptive deep brain stimulation in Parkinson’s disease: closing the loop
Authors: Oliveira Andreia M. , Coelho Luis , Carvalho Eduardo , Ferreira-Pinto Manuel J. , Vaz Rui , Aguiar Paulo 
Published: August 2023

AbstractParkinson’s disease (PD) is the second most common neurodegenerative disease bearing a severe social and economic impact. So far, there is no known disease modifying therapy and the current available treatments are symptom oriented. Deep Brain Stimulation (DBS) is established as an effective treatment for PD, however current systems lag behind today’s technological potential. Adaptive DBS, where stimulation parameters depend on the patient’s physiological state, emerges as an important step towards “smart” DBS, a strategy that enables adaptive stimulation and personalized therapy. This new strategy is facilitated by currently available neurotechnologies allowing the simultaneous monitoring of multiple signals, providing relevant physiological information. Advanced computational models and analytical methods are an important tool to explore the richness of the available data and identify signal properties to close the loop in DBS. To tackle this challenge, machine learning (ML) methods applied to DBS have gained popularity due to their ability to make good predictions in the presence of multiple variables and subtle patterns. ML based approaches are being explored at different fronts such as the identification of electrophysiological biomarkers and the development of personalized control systems, leading to effective symptom relief. In this review, we explore how ML can help overcome the challenges in the development of closed-loop DBS, particularly its role in the search for effective electrophysiology biomarkers. Promising results demonstrate ML potential for supporting a new generation of adaptive DBS, with better management of stimulation delivery, resulting in more efficient and patient-tailored treatments.
Aggressive B-cell non-Hodgkin lymphomas: a report of the lymphoma workshop of the 20th meeting of the European Association for Haematopathology
Authors: Rodriguez-Pinilla Socorro Maria , Dojcinov Stefan , Dotlic Snjezana , Gibson Sarah E. , Hartmann Sylvia , Klimkowska Monika , Sabattini Elena , Tousseyn Thomas A. , de Jong Daphne , Hsi Eric. D. 
Published: August 2023

AbstractAggressive B-cell non-Hodgkin lymphomas are a heterogeneous group of diseases and our concepts are evolving as we learn more about their clinical, pathologic, molecular genetic features. Session IV of the 2020 EAHP Workshop covered aggressive, predominantly high-grade B-cell lymphomas, many that were difficult to classify. In this manuscript, we summarize the features of the submitted cases and highlight differential diagnostic difficulties. We specifically review issues related to high-grade B-cell lymphomas (HGBCLs) with MYC and BCL2 and/or BCL6 rearrangements including TdT expression in these cases, HGBCL, not otherwise specified, large B-cell lymphomas with IRF4 rearrangement, high-grade/large B-cell lymphomas with 11q aberration, Burkitt lymphoma, and pleomorphic mantle cell lymphoma. Since the workshop, the 5th edition of the WHO Classification for Haematolymphoid Tumours (WHO-HAEM5) and International Consensus Classification (ICC) 2022 were published. We endeavor to use the updated terminology.
Computing a Link Diagram From Its Exterior
Authors: Dunfield Nathan M. , Obeidin Malik , Rudd Cameron Gates 
Published: August 2023

AbstractA knot is a circle piecewise-linearly embedded into the 3-sphere. The topology of a knot is intimately related to that of its exterior, which is the complement of an open regular neighborhood of the knot. Knots are typically encoded by planar diagrams, whereas their exteriors, which are compact 3-manifolds with torus boundary, are encoded by triangulations. Here, we give the first practical algorithm for finding a diagram of a knot given a triangulation of its exterior. Our method applies to links as well as knots, and allows us to recover links with hundreds of crossings. We use it to find the first diagrams known for 23 principal congruence arithmetic link exteriors; the largest has over 2500 crossings. Other applications include finding pairs of knots with the same 0-surgery, which relates to questions about slice knots and the smooth 4D Poincaré conjecture.
Modeling Ellipsoidal Block Impacts by an Advanced Rheological Model
Authors: Dattola G. , di Prisco C. , Crosta G. B. 
Published: August 2023

AbstractIn this paper, an advanced rheological model for impacts of ellipsoidal blocks on deformable ground surfaces, introducing the effects of block eccentricity and orientation at impact, is presented. This allows us to assess impact penetration and force, restitution coefficients, and block trajectories. A parametric analysis was carried out by considering different block aspect ratios, impact angles and initial block orientations at impact. The results are presented in terms of restitution coefficients, penetration and force time histories, maximum penetration depth, maximum force and rotational/total kinetic ratios. Impacts along the major block axis, versus those along minor axis, are characterized by larger penetrations (ranging from 3.3 to 50%), shorter impact durations (ca 50%) and very slightly larger vertical forces (ranging from 0.3 to 60%) according to the model parameter used. In contrast, the impact angle is shown to strongly affect maximum penetration and force values, and markedly increase rotation at impact. Analogously, normal restitution coefficient is severely dependent on impact angle, with a variation of more than two orders of magnitude. A mathematical expression for computing the energetic restitution coefficient from the normal and tangential apparent restitution coefficients and the ratio between the rotation and total kinetic energy is proposed. This overcomes the drawback of classical restitution coefficients greater than one when a change in block rotation occurs allowing us to bracket the coefficient of restitutions values to support and improve classical rock fall simulations also highlighting their intrinsic limitations. Finally, the effects of block geometry and initial angular velocity on rockfall simulations were analyzed by implementing the approach in the HyStone simulation code. The simulated frequencies of the maximum height during each ballistic trajectory follow an exponential distribution, whereas those for normal and tangential apparent restitution coefficients follow normal distributions.
The influence of water sorption on the microstructure of a hydro-sensitive granular material (couscous) deduced from simultaneous neutron and X-ray tomography
Authors: Vego Ilija , Tengattini Alessandro , Lenoir Nicolas , Viggiani Gioacchino 
Published: August 2023

Abstract
The effects of water on the behaviour of granular materials can be significant. Besides capillary bridges, several other chemo-hydro-mechanical processes can affect the response of hydro-sensitive granular assemblies, when water sorption critically alters the individual particles properties (i.e., swelling, deterioration of mechanical properties). It is very common to find such materials in food and pharmaceutical industries, where water sorption can often lead to important resources waste while processing or storing the product. It is therefore necessary to understand the phenomena that affect the material’s functionality, often related to particle agglomeration and degradation. However, despite the relevance of the problem, our knowledge about these phenomena is still relatively poor. With this study we aim to explore the link between water content increase and particle, contacts and assembly scale phenomena. Simultaneous neutron and X-ray tomography allows us to investigate respectively the water uptake and microstructure evolution of two couscous assemblies exposed to high relative humidity while subjected to constant stress, a configuration chosen to simulate the conditions in an industrial silo-storage. We acquire a data-set of images, from which we follow and quantify the variations of water content distribution and the resulting volumetric response of thousands of particles through bespoke algorithms. Despite the abundance of water provided, we observe spatial gradients in water content distribution and consequently in particle swelling. We find that the relation between these two variables can be described as (quasi-)linear. The contact area growth also seems to follow a similar trend.

Graphic abstract
Deep-learning-based upscaling method for geologic models via theory-guided convolutional neural network
Authors: Wang Nanzhe , Liao Qinzhuo , Chang Haibin , Zhang Dongxiao 
Published: August 2023

AbstractLarge-scale or high-resolution geologic models usually comprise a huge number of grid blocks, which can be computationally demanding and time-consuming to solve with numerical simulators. Therefore, it is advantageous to upscale geologic models (e.g., hydraulic conductivity) from fine-scale (high-resolution grids) to coarse-scale systems. Numerical upscaling methods have been proven to be effective and robust for coarsening geologic models, but their efficiency remains to be improved. In this work, a deep-learning-based method is proposed to upscale the fine-scale geologic models, which can assist to improve upscaling efficiency significantly. In the deep learning method, a deep convolutional neural network (CNN) is trained to approximate the relationship between the coarse block of fine-scale hydraulic conductivity fields and the corresponding hydraulic heads, which can then be utilized to replace the numerical solvers while solving the flow equations for each coarse block. In addition, physical laws (e.g., governing equations and periodic boundary conditions) can also be incorporated into the training process of the deep CNN model, which is termed the theory-guided convolutional neural network (TgCNN). With the physical information considered, dependence on the data volume of training the deep learning models can be reduced greatly. Several cases of subsurface flow, with varying two-dimensional and three-dimensional structures and isotropic and anisotropic conditions, are used to evaluate the performance of the proposed deep-learning-based upscaling method. The results show that the deep learning method can provide equivalent upscaling accuracy to the numerical method, and efficiency can be improved significantly compared to numerical upscaling.
Certified SAT solving with GPU accelerated inprocessing
Authors: Osama Muhammad , Wijs Anton , Biere Armin 
Published: August 2023

AbstractSince 2013, the leading SAT solvers in SAT competitions all use inprocessing, which, unlike preprocessing, interleaves search with simplifications. However, inprocessing is typically a performance bottleneck, in particular for hard or large formulas. In this work, we introduce the first attempt to parallelize inprocessing on GPU architectures. As one of the main challenges in GPU programming is memory locality, we present new compact data structures and devise a data-parallel garbage collector. It runs in parallel on the GPU to reduce memory consumption and improve memory locality. Our new parallel variable elimination algorithm is roughly twice as fast as previous work. Moreover, we augment the variable elimination with the first parallel algorithm for functional dependency extraction in an attempt to find more logical gates to eliminate that cannot be found with syntactic approaches. We present a novel algorithm to generate clausal proofs in parallel to validate all simplifications running on the GPU besides the CDCL search, giving high credibility to our solver and its use in critical applications such as model checkers. In experiments, our new solver ParaFROST solves numerous benchmarks faster on the GPU than its sequential counterparts. With functional dependency extraction, inprocessing in ParaFROST was more effective in reducing the solving time. Last but not least, all proofs generated by ParaFROST were successfully verified.
How Well Can we Diagnose Autism in Adults? Evaluating an Informant-based Interview: The Dutch Developmental, Dimensional and Diagnostic Interview – Adult Version (3Di-Adult)
Authors: Krijnen L.J.G. , Greaves-Lord K. , Mandy W. , Mataw K.J.S. , Hartog P. , Begeer S. 
Published: August 2023

AbstractThe current study evaluated a brief, informant-based autism interview: the Developmental, Dimensional and Diagnostic Interview – Adult Version (3Di-Adult). Feasibility, reliability and validity of the Dutch 3Di-Adult was tested amongst autistic participants (n = 62) and a non-autistic comparison group (n = 30) in the Netherlands. The 3Di-Adult consists of two scales based on DSM-5 criteria: A scale ‘Social communication and social interaction’ and B scale ‘Restricted, repetitive patterns of behavior, interests or activities’. ROC curves were used to determine cut-off scores for the A and the B scale, using an ASD diagnosis made by an independent clinician as the criterion. Mean administration time was 42 min. Internal consistency of the A scale (α = 0.92) and the B scale (α = 0.85) were good. Inter-rater reliability (ICCs = 0.99) and inter-rater agreement (ICCs ≥ 0.90) were promising. The 3Di-Adult showed good sensitivity (80.6%) and specificity (93.3%). Positive and negative predictive value were 96.2% and 70.0% respectively. Comparisons with the Autism-Spectrum Quotient-Short to investigate the convergent validity showed moderate, significant correlations with the 3Di-Adult in the total sample. Males, as compared to females, displayed significantly more autistic features on the 3Di-Adult. No relationship was found of the 3Di-Adult with education level, intelligence and age of the participants or informants. The feasibility and psychometric properties of the Dutch 3Di-Adult are promising, indicating that it can be a time-efficient, valid and reliable tool to use in diagnosing autism in adults according to DSM-5 criteria.
Expectations for Children with Autism Spectrum Disorders or Intellectual Disabilities in Ghana: A Comparison Between Service Providers and Parents
Authors: Washington-Nortey Melissa , Anum Adote , Serpell Zewelanji , Xu Yaoying 
Published: August 2023

AbstractLittle is known about care providers’ expectations for children with autism spectrum disorders (ASD) and intellectual disabilities (ID) in Ghana. This study used group concept mapping (n = 9) and a quantitative survey (n = 128) to explore and compare service providers’ and parents’ expectations for children with ASD or ID. Data were analyzed using hierarchical clustering procedures and Multivariate Analysis of Variance (MANOVA). Concept mapping results revealed several expectation clusters, including independence, love and acceptance, equal social rights and opportunities, and professional and caregiver training. MANOVA results revealed significant differences between parents, teachers, and healthcare providers in their perceptions of the importance and likelihood of a child achieving these expectations. Results are discussed in reference to the cultural context, and implications are outlined.