bluuebunny/crossref_metadata_2025_split huggingface dataset:
2D Conductive Metal‐Organic Frameworks Based on Tetraoxa[8]circulenes as Promising Cathode for Aqueous Zinc Ion Batteries
Authors: Chang Zixin , Zhu Mengsu , Li Ze , Wu Sha , Yin Siping , Sun Yimeng , Xu Wei 
Published: March 2024

AbstractAqueous zinc‐ion batteries (ZIBs) are the new generation electrochemical energy storage systems. Recently, two‐dimensional conductive metal‐organic frameworks (2D c‐MOFs) are attractive to serve as cathode materials of ZIBs due to their compositional diversity, abundant active sites, and excellent conductivity. Despite the growing interest in 2D c‐MOFs, their application prospects are still to be explored. Herein, a tetraoxa[8]circulene (TOC) derivative with unique electronic structure and interesting redox‐active property are synthesized to construct c‐MOFs. A series of novel 2D c‐MOFs (Cu‐TOC, Zn‐TOC and Mn‐TOC) with different conductivities and packing modes are obtained by combining the linker tetraoxa[8]circulenes‐2,3,5,6,8,9,11,12‐octaol (8OH‐TOC) and corresponding metal ions. Three c‐MOFs all exhibit typical semiconducting properties, and Cu‐TOC exhibits the highest electrical conductivity of 0.2 S cm−1 among them. Furthermore, their electrochemical performance as cathode materials for ZIBs have been investigated. They all performed high reversible capacity, decent cycle stability and excellent rate capability. This work reveals the key insights into the electrochemical application potential of 2D c‐MOFs and advances their development as cathode materials in ZIBs.
A Facile NMR Method for Pre‐MRI Evaluation of Trigger‐Responsive T1 Contrast Enhancement
Authors: Jian Cheng‐Bang , Wu Ying‐Yann , Lin Ming‐Huang , Gao Hua‐De , Chen Chong‐Yan , Leong Shwee Khuan , Tzou Der‐Lii M. , Hwang Dennis W. , Lee Hsien‐Ming 
Published: March 2024

AbstractThere is a growing interest in developing paramagnetic nanoparticles as responsive magnetic resonance imaging (MRI) contrast agents, which feature switchable T1 image contrast of water protons upon biochemical cues for better discerning diseases. However, performing an MRI is pragmatically limited by its cost and availability. Hence, a facile, routine method for measuring the T1 contrast is highly desired in early‐stage development. This work presents a single‐point inversion recovery (IR) nuclear magnetic resonance (NMR) method that can rapidly evaluate T1 contrast change by employing a single, optimized IR pulse sequence that minimizes water signal for “off‐state” nanoparticles and allows for sensitively measuring the signal change with “switch‐on” T1 contrast. Using peptide‐induced liposomal gadopentetic acid (Gd3+‐DTPA) release and redox‐sensitive manganese oxide (MnO2) nanoparticles as a demonstration of generality, this method successfully evaluates the T1 shortening of water protons caused by liposomal Gd3+‐DTPA release and Mn2+ formation from MnO2 reduction. Furthermore, the NMR measurement is highly correlated to T1‐weighted MRI scans, suggesting its feasibility to predict the MRI results at the same field strength. This NMR method can be a low‐cost, time‐saving alternative for pre‐MRI evaluation for a diversity of responsive T1 contrast systems.
Profiling and characterization of the constituents of taibai ginseng using ultra‐high performance liquid chromatography‐quadrupole time of flight mass spectrometry
Authors: Gao Xin , Sun Wenjun , Wang Yaxuan , Li Xiaohui , Liu Xia , Li Yunzhe , Niu Xiaofeng 
Published: March 2024

AbstractTaibai ginseng (roots of Pedicularis decora Franch.) has been reported to possess anti‐Alzheimer's disease (anti‐AD) activity and can be potentially used for treating AD. However, the chemical constituents of taibai ginseng have not yet been elucidated because of the paucity of relevant studies, which hinders further research on the pharmacological mechanism and utilization of taibai ginseng. In this study, a rapid and efficient method for comprehensively analyzing the chemical constituents of taibai ginseng was established for the first time. We used ultra‐high performance liquid chromatography‐quadrupole time of flight mass spectrometry in combination with the UNIFI data‐processing platform to automatically characterize and identify the chemical profile of taibai ginseng. As a result, more than 76 compounds were detected, and their structures were characterized. These compounds include 24 iridoid glycosides, 24 phenylethanol glycosides, 15 terpenoids, and 13 other components. More than fifty of these compounds from taibai ginseng were reported for the first time. Our results provide a reference for the quality control of taibai ginseng and establish a higher quality standard for pharmacodynamic research. Appropriate modification of the method reported herein can enable its use for the screening and characterization of taibai ginseng and other compounds from the Pedicularis genus.
Histology and immunofluorescent study of the pancreas in lovebird (Agapornis personatus)
Authors: Goodarzi Nader , Bashiri Ayda 
Published: March 2024

AbstractBackgroundLovebird (Agapornis personatus) is a monotypic species of bird of the lovebird genus in the parrot family Psittaculidae and order Psittaciformes.ObjectivesThe present study was designed to investigate the histology and immunohistochemistry of the pancreas in the lovebird.MethodsTotally, three adult birds were used. The pancreas was assessed using histological and immunofluorescent staining to detect insulin, glucagon, somatostatin, pancreatic polypeptide (PP) and neuropeptide Y (NY).ResultsThe exocrine pancreas was composed of pyramidal acinar cells with zymogen granules at the apical cytoplasm. The endocrine pancreas was identified as large alpha, small beta and mixed islets of Langerhans. No intercalated duct was observed. Alpha cells with a density of 28.55% were the most numerous cell type, which were populated throughout the large islets, especially at the periphery. The beta cells with a density of 15.78% were accumulated mostly at the periphery of islets. The delta cells exhibited 17.81% intensity. Despite their lower density, the distribution of delta cells was like that of A cells throughout the islets. PP and NY cells were distinguished with densities of 14.69% and 20.63%, respectively.ConclusionsAlthough the arrangement of acinar cells, ductal systems and endocrine islets reflects patterns observed in various avian species, the absence of intercalated duct, the presence of three types of Langerhans islets as alpha, beta and mixed islets and the high expression of NY in the islets were some unique features observed in the current study. These findings contribute to the broader understanding of avian pancreas histology.
Rescue and rehabilitation of maned wolf (Chrysocyon brachyurus) in Paraguay: Case description
Authors: Vetter Hiebert Joerg Richard , Petters Cabrera José Gaspar , Benítez del Puerto Santhiago , González Vatteone Roger , Florentín Morel Marlene , Dacak Aguilera Diego Augusto , Brítez Valinotti César Esteban , Ramírez Diarte Raquel , González González Lilian Maria , Coronel Díaz Carlos , Osorio Paola , Cardozo Walter , Bracho Fátima , Soto Claudia Raquel , Domínguez Barreto Nilsa Melissa , Sciabarrasi Antonio Alejandro 
Published: March 2024

AbstractThe maned wolf, Chrysocyon brachyurus, is the largest South American canid, with a natural distribution that stretches across Peru, Bolivia, Brazil, Argentina, Paraguay and Uruguay. The present study reports the case of a rescued specimen of maned wolf that underwent a rehabilitation process in Paraguay, starting in October 2020 with its rescue, and finalising in May 2021 with the reintroduction. Herein, we document findings regarding the general management, biometrics, feeding and environmental enrichment; chemical immobilisation and monitoring; haematology, blood biochemistry and specific serology‐relevant pathogens; skin examination and bone marrow cytology; orthopaedic, ophthalmological and dental evaluation; abdominal and cardiac ultrasonography; radiology and copro‐parasitology. Main findings include the feeding habits of the individual and enrichment opportunities. The animal weighed 7 kg on arrival, with an estimated age of 5 months, and 18 kg on reintroduction, with an estimated age of 1 year. The animal tested negative to serologic tests for Brucella canis, Dirofilaria, canine distemper, Toxoplasmosis and canine parvovirus. Leptospira testing showed antibodies against L. grippotyphosa on both samplings, L. wolffi and L. ictero on the first sampling, and L. pomona on the second sampling. Abdominal organs were examined and measured through ultrasound evaluation and kidneys showed no alterations. Echocardiography showed preserved mitral, tricuspid and aortic valve flows, but turbulent pulmonary valve flow. Copro‐parasitology reported the presence of Lagochilascaris sp. and Balantidium sp. All the information gathered aided in diagnosing the health status of the individual, and the response to environmental enrichment helped assess the behaviour, which led to the suggestion of reintroducing the animal. These data constitute the first published health check of a maned wolf in Paraguay, which can contribute to the species’ conservation in the country. The protocol presented in this study can serve as a basis for developing an action plan for the maned wolf in Paraguay.
Causality and causal inference for engineers: Beyond correlation, regression, prediction and artificial intelligence
Authors: Naser M. Z. 
Published: March 2024

AbstractIn order to engineer new materials, structures, systems, and processes that address persistent challenges, engineers seek to tie causes to effects and understand the effects of causes. Such a pursuit requires a causal investigation to uncover the underlying structure of the data generating process (DGP) governing phenomena. A causal approach derives causal models that engineers can adopt to infer the effects of interventions (and explore possible counterfactuals). Yet, and for the most part, we continue to design experiments in the hope of empirically observing engineered intervention(s). Such experiments are idealized, complex, and costly and hence are narrow in scope. On the contrary, a causal investigation will allow us to peek into the how and why of a DGP and provide us with the essential means to articulate a causal model that accurately describes the phenomenon on hand and better predicts the outcome of possible interventions. Adopting a causal approach in engineering is perhaps more warranted than ever—especially with the rise of big data and the adoption of artificial intelligence (AI); wherein AI models are naivety presumed to describe causal ties. To bridge such knowledge gap, this primer presents fundamental principles behind causal discovery, causal inference, and counterfactuals from an engineering perspective and contrasts that to those pertaining to correlation, regression, and AI.This article is categorized under:
Application Areas > Industry Specific Applications
Algorithmic Development > Causality Discovery
Application Areas > Science and Technology
Technologies > Machine Learning
Enhanced Recovery after Surgery recommendations that most impact patient care: A multi‐institutional, multidiscipline analysis in the United States
Authors: Cochran Allyson R. , Shaw George , Shue‐McGuffin Katherine , Elias Kevin , Vrochides Dionisios 
Published: March 2024

AbstractBackgroundCompliance to the entire Enhanced Recovery after Surgery (ERAS) protocol improves surgical recovery, where higher compliance improves outcomes. However, specific items may predict improved recovery more than others. Studies have evaluated the impact of individual ERAS recommendations though they are either single center, not based in the United States (US), or focus on colorectal procedures only. This study aims to evaluate compliance on surgical outcomes in two large healthcare systems in the US across four surgery types.MethodsCompliance to individual recommendations, limited patient characteristics, and outcomes data from two US ERAS Centers of Excellence (CoE) for hepatectomy, pancreatectomy, radical cystectomy, and head and neck (HN) resections were evaluated. Outcomes included 30‐day Clavien–Dindo≥3, readmission, mortality, and length of stay (LOS). Multivariate regressions were performed as appropriate for the data for each surgery type. Clavien≥3 was included to control for severity of complications, and the CoE variable was force‐retained.ResultsA total of 2886 records were analyzed. Controlling for CoE and severity of patient complications, early removal of Foley catheter was associated with significant reductions in LOS in the liver, pancreas, and HN procedures and reductions in complications in the liver and pancreas. Limited use of NG tubes reduced LOS in the pancreas and complications in urology. Oral carbohydrate loading reduced LOS in the pancreas, and patient education reduced mortality in HN patients.ConclusionsThis study reports the effect of ERAS compliance on outcomes, by surgery type, in a multi‐institutional US setting. Future studies should validate these findings and consider surgery‐specific predictive models comprised of individual ERAS recommendations in real‐world applications.
Remarks on some unidirectional flows of Maxwell fluids through a rectangular channel filled with porous medium
Authors: Fetecau Constantin , Mirza Itrat Abbas , Vieru Dumitru , Shah Nehad Ali 
Published: March 2024

AbstractExact solutions for the dynamics of incompressible fluids showing rate‐type behavior have mostly been found in circumstances where the boundary velocities are given in the body of existing research. This phenomenon results from the constitutive equation of the corresponding extra‐stress tensor, which specifies the natural relationship between velocity and shear stress. In this paper, we focus on a unique observation of the magnetohydrodynamic (MHD) movements of incompressible Maxwell fluids, and the governing equations regulating velocity and shear stress. We focus our analysis on the case of an infinite plate submerged in a porous substance. Within this framework, we do an analytical analysis of a motion issue with a boundary that has a predetermined shear stress. We can easily ascertain the shear stress associated with the motion brought on by a flat plate in order to be more exact. The fluid is subjected to a shear stress by this plate that changes over time. The velocity field from a boundary motion with a predetermined velocity is used to achieve this. We give two graphical representations of individual solutions for the sake of clarity and result verification. Last but not least, we use graphical depiction to highlight how a magnetic field and a porous media affect the fluid's flow resistance. The results show that the flow resistance of the fluid increases in the presence of a porous media and decreases when a magnetic field is present.
Pre-equilibrium photons from the early stages of heavy-ion collisions
Authors: Garcia-Montero Oscar , Mazeliauskas Aleksas , Plaschke Philip , Schlichting Sören 
Published: March 2024

Abstract
We use QCD kinetic theory to compute photon production in the chemically equilibrating Quark-Gluon Plasma created in the early stages of high-energy heavy-ion collisions. We do a detailed comparison of pre-equilibrium photon rates to the thermal photon production. We show that the photon spectrum radiated from a hydrodynamic attractor evolution satisfies a simple scaling form in terms of the specific shear viscosity η/s and entropy density dS/dζ ∼ (Tτ1/3)3/2∞. We confirm the analytical predictions with numerical kinetic theory simulations. We use the extracted scaling function to compute the pre-equilibrium photon contribution in $$ \sqrt{s_{NN}} $$

s
NN

= 2.76 TeV 0–20% PbPb collisions. We demonstrate that our matching procedure allows for a smooth switching from pre-equilibrium kinetic to thermal hydrodynamic photon production. Finally, our publicly available implementation can be straightforwardly added to existing heavy ion models.
Binary discrimination through next-to-leading order
Authors: Larkoski Andrew J. 
Published: March 2024

Abstract
Binary discrimination between well-defined signal and background datasets is a problem of fundamental importance in particle physics. With detailed event simulation and the advent of extensive deep learning tools, identification of the likelihood ratio has typically been reserved as a computational problem. However, this approach can obscure overtraining or excessive sensitivity to tuned features of the simulation that may not be well-defined theoretically. Here, we present the first analysis of binary discrimination for signal and background distributions for which their likelihood ratio is infrared and collinear safe, and can therefore be calculated order-by-order in perturbation theory. We present explicit, general formulas for receiver operator characteristic curves and the area under it through next-to-leading order. These results can then establish absolute upper bounds on discrimination performance because any realistic implementation will have measurement errors, undetected particles, or restrictions on fiducial phase space. As a demonstration of this formalism, we apply it to discrimination of highly-boosted Higgs decays from gluon splitting to bottom quarks. Effects at next-to-leading order are first sensitive to the flow of color in the jet and significantly modify discrimination performance at leading-order. In the limit of infinite boost, these events can be perfectly discriminated because only the gluon will radiate at finite angles from the bottom quarks, and we find that large effects persist at energies accessible at the Large Hadron Collider. Next-to-leading order is therefore required to qualitatively understand results using machine-learning methods.
From amplitudes to analytic wavefunctions
Authors: Lee Mang Hei Gordon 
Published: March 2024

Abstract
The field-theoretic wavefunction has received renewed attention with the goal of better understanding observables at the boundary of de Sitter spacetime and studying the interior of Minkowski or general FLRW spacetime. Understanding the analytic structure of the wavefunction potentially allows us to establish bounds on physical observables. In this paper we develop an “amplitude representation” for the flat space wavefunction, which allow us to write the flat space wavefunction as an amplitude-like Feynman integral integrated over an energy-fixing kernel. With this representation it is possible to separate the wavefunction into an amplitude part and a subleading part which is less divergent as the total energy goes to zero. In turn the singularities of the wavefunction can be classified into two sets: amplitude-type singularities, which can be mapped to singularities found in amplitudes (including anomalous thresholds), and wavefunction-type singularities, which are unique to the wavefunction. As an example we study several tree level and one loop diagrams for scalars, and explore their singularities in detail.
Generalized Partial-Slice Monogenic Functions: A Synthesis of Two Function Theories
Authors: Xu Zhenghua , Sabadini Irene 
Published: March 2024

AbstractIn this paper, we review the notion of generalized partial-slice monogenic functions that was introduced by the authors in Xu and Sabadini (Generalized partial-slice monogenic functions,arXiv:2309.03698, 2023). The class of these functions includes both the theory of monogenic functions and of slice monogenic functions over Clifford algebras and it is obtained via a synthesis operator which combines a generalized Cauchy–Riemann operator with an operator acting on slices. Besides recalling the fundamental features, we provide a notion of$$*$$∗-product based on the CK-extension and discuss the smoothness of generalized partial-slice functions.
Chemometric Optimization of SPE for the Determination of Multiclass Pesticides in Portable Water Samples by UHPLC-MS/MS
Authors: Drimaropoulou Garyfallia , Christophoridis Christophoros , Zacharis Constantinos K. , Fytianos Konstantinos 
Published: March 2024

AbstractThis study aimed on the development of a SPE-UHPLC-MS/MS method for the simultaneous determination of pesticide residues in drinking water samples. A chemometric approach was applied to optimize the efficiency of the SPE pretreatment procedure. This study involved (i) the application of a Full Factorial Design for the screening of the significant factors, (ii) the application of a Central Composite Design for the determination of the optimal conditions and (iii) the evaluation and validation of the significance of the statistically proposed models. Oasis HLB cartridges were used for the extraction. The optimum sample volume was 300 mL and the elution solvent 3 mL of the mixture of methanol:ethylacetate 70:30 v/v. The method was validated according to the international guidelines. Recoveries were ranged from 63 to 116% and the detection limits were between 0.1 and 1.5 pg mL− 1. The validated method could be used in routine analysis for pesticides screening.
A generalized method aiming at predicting the polymer melt flow field in the metering zone of large-scale single-screw extruders
Authors: Pricci Alessio , Percoco Gianluca 
Published: March 2024

AbstractSingle-screw extruders (SSE) are commonly used in a wide variety of applications, ranging from polymer-extrusion to pellet additive manufacturing (PAM). Existing mathematical models focus on Newtonian and power-law rheologies to model melt flow in the last screw vanes. However, molten polymers usually follow more complex rheological patterns, and a generalized extrusion model is still lacking. Therefore, a semi-analytical model aiming at describing the flow of molten polymers in SSE is presented, to encompass a wide range of non-Newtonian fluids, including generalized non-Newtonian fluids (GNF). The aim is to evaluate the molten polymer flow field under the minimum set of dimensionless parameters. The effect of dimensionless extrusion temperature, flow rate, channel width, and height on the flow field has been investigated. A full factorial plane has been chosen, and it was found that the impact of dimensionless flow rate is the most prominent. The results were initially compared to numerical computations, revealing a strong agreement between the simulations and the proposed GNF method. However, significant deviations emerged when employing the traditional power-law model. This is particularly true at high values of flow rate and extrusion temperature: the mean error on overall flow speed is reduced from 12.91% (traditional power-law method) to 1.04% (proposed GNF method), while keeping a reasonable computational time (time reduction: 96.70%, if compared to fully numerical solutions). Then, the predicted pressure drop in the metering section was benchmarked against established literature data for industrial-scale extruders, to show the model’s accuracy and reliability. The relative errors of the traditional model range between 34.33 and 62%. The proposed method reduces this gap (errors ranging between 5.34% and 10.97%). The low computational time and high accuracy of the GNF method will pave the way for its integration in more complex mathematical models of large-scale additive manufacturing processes.