bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measuring drug similarity using drug–drug interactions
Authors: Lv Ji , Liu Guixia , Ju Yuan , Huang Houhou , Sun Ying 
Published: April 2024

AbstractCombination therapy is a promising approach to address the challenge of antimicrobial resistance, and computational models have been proposed for predicting drug–drug interactions. Most existing models rely on drug similarity measures based on characteristics such as chemical structure and the mechanism of action. In this study, we focus on the network structure itself and propose a drug similarity measure based on drug–drug interaction networks. We explore the potential applications of this measure by combining it with unsupervised learning and semi‐supervised learning approaches. In unsupervised learning, drugs can be grouped based on their interactions, leading to almost monochromatic group–group interactions. In addition, drugs within the same group tend to have similar mechanisms of action (MoA). In semi‐supervised learning, the similarity measure can be utilized to construct affinity matrices, enabling the prediction of unknown drug–drug interactions. Our method exceeds existing approaches in terms of performance. Overall, our experiments demonstrate the effectiveness and practicability of the proposed similarity measure. On the one hand, when combined with clustering algorithms, it can be used for functional annotation of compounds with unknown MoA. On the other hand, when combined with semi‐supervised graph learning, it enables the prediction of unknown drug–drug interactions.
GCARDTI: Drug–target interaction prediction based on a hybrid mechanism in drug SELFIES
Authors: Feng Yinfei , Zhang Yuanyuan , Deng Zengqian , Xiong Mimi 
Published: April 2024

AbstractThe prediction of the interaction between a drug and a target is the most critical issue in the fields of drug development and repurposing. However, there are still two challenges in current deep learning research: (i) the structural information of drug molecules is not fully explored in most drug target studies, and the previous drug SMILES does not correspond well to effective drug molecules and (ii) exploration of the potential relationship between drugs and targets is in need of improvement. In this work, we use a new and better representation of the effective molecular graph structure, SELFIES. We propose a hybrid mechanism framework based on convolutional neural network and graph attention network to capture multi‐view feature information of drug and target molecular structures, and we aim to enhance the ability to capture interaction sites between a drug and a target. In this study, our experiments using two different datasets show that the GCARDTI model outperforms a variety of different model algorithms on different metrics. We also demonstrate the accuracy of our model through two case studies.
Containment control of systems with constraints and bounded disturbances
Authors: Zhang Jiayao , Li Zhi 
Published: April 2024

AbstractThis article studies the distributed containment control of a second‐order discrete‐time multi‐agent system with convex constraints on positions, nonconvex constraints on velocities, bounded disturbances on static points and switching topologies. A distributed control algorithm with disturbance information and local information is proposed. It is proved that when the static points with disturbances and the joint graph have a directed spanning forest among each time interval, all agents are gradually driven to the neighborhood of a convex hull spanned by the static points, and an upper bound of the neighborhood is obtained. The most innovative point is to utilize a rigorous mathematical theory to deal with convex constraint error rather than a geometric explanation. Meanwhile, another control algorithm with static point information and local information is proposed to converge all agents to the convex hull in the absence of external disturbances. Additionally, a numerical example is conducted to illustrate this theory.
Towards practical robotic chef: Review of relevant work and future challenges
Authors: Sochacki Grzegorz , Zhang Xiaoping , Abdulali Arsen , Iida Fumiya 
Published: April 2024

AbstractRobotic chefs are a promising technology that can improve the availability of quality food by reducing the time required for cooking, therefore decreasing food's overall cost. This paper clarifies and structures design and benchmarking rules in this new area of research, and provides a comprehensive review of technologies suitable for the construction of cooking robots. The diner is an ultimate judge of the cooking outcome, therefore we put focus on explaining human food preferences and perception of taste and ways to use them for control. Mechanical design of robotic chefs at a practically low cost remains the challenge, but some recently published gripper designs as well as whole robotic systems show the use of cheap materials or off‐the‐shelf components. Moreover, technologies like taste sensing, machine learning, and computer vision are making their way into robotic cooking enabling smart sensing and therefore improving controllability and autonomy. Furthermore, objective assessment of taste and food palatability is a challenge even for trained humans, therefore the paper provides a list of procedures for benchmarking the robot's tasting and cooking abilities. The paper is written from the point of view of a researcher or engineer building a practical robotic system, therefore there is a strong priority for solutions and technologies that are proven, robust and self‐contained enough to be a part of a larger system.
Manganese Dioxide Coated Piezoelectric Nanosonosensitizer for Cancer Therapy with Tumor Microenvironment Remodeling and Multienzyme‐Like Catalysis
Authors: Yue Zhaoyang , Zhao Qinyu , Wang Shaobo , Yao Shuncheng , Wan Xingyi , Hu Quanhong , Wen Kaikai , Zhao Yunchao , Li Linlin 
Published: April 2024

AbstractSonodynamic therapy (SDT) as an emerging method for cancer therapy has encountered difficulty in insufficient production of reactive oxygen species (ROS), especially in tumor microenvironment (TME) with elevated antioxidants and hypoxic conditions. In this work, the authors have fabricated heterostructured manganese dioxide (MnO2)‐coated BaTiO3 nanoparticles (BTO@M NPs) as a piezoelectric sonosensitizer, which exhibits the capacity of remodeling TME and multienzyme‐like catalysis for boosting SDT. Benefitting from the piezotronic effect, the formation of a p‐n junction between MnO2 and piezoelectric BTO with a built‐in electric field and band bending efficiently promotes the separation of charge carriers, facilitating the generation of superoxide anion (•O2−) and hydroxyl radical (•OH) under ultrasound (US) stimulation. Moreover, BTO@M NPs can catalyze the overexpressed hydrogen peroxide (H2O2) in TME to produce oxygen for replenishing the gas source in SDT, and also deplete antioxidant glutathione (GSH), realizing TME remodeling. During this process, the reduced Mn(II) can convert H2O2 into •OH, further amplifying cellular oxidative damage. With these combination effects, the versatile BTO@M NPs exhibit prominent cytotoxicity and tumor growth inhibition against 4T1 breast cancer. This work provides a feasible strategy for constructing high‐efficiency sonosensitizers for cancer SDT.
Separately measuring home‐field advantage for offenses and defenses: A panel‐data study of constituent channels within collegiate American football
Authors: McMahon Matthew J. , Quintanar Sarah Marx 
Published: April 2024

AbstractWe improve constituent‐channel estimates of home‐field and neutral‐site advantage for collegiate American football's top division by utilizing a richer, 12‐season data set and by exploiting the COVID‐19 pandemic as a random shock. Novel to the literature, we separately examine points scored by each team, allowing us to identify impacts on each team's offense and defense individually. The information set provided by our model is a strict superset of that provided by the previous standard in the literature, making ours a strictly dominant modeling choice. We demonstrate this improvement theoretically and empirically. Physiologically, away‐team travel distance does not impact their own score, but it increases home‐team scores, consistent with the notion that defenses tire faster than offenses. There is also similar but limited evidence of this effect for neutral‐site teams. Time zones may play a minor role, too. Psychologically, crowd size and density hurt away‐team scores but do not impact home or neutral‐site teams. The away‐team effect disappears in 2020, however, indicating that the pre‐2020 effect is caused by the crowd's noise, not their mere presence. We also find that increasing stadium capacity while holding crowd size constant hurts home‐team scores, highlighting the importance of considering ticket demand when considering stadium expansion. Tactically, stadium familiarity helps offenses, not defenses, while team‐opponent familiarity has the opposite effect. Weather also plays a role. At median values for key variables, we find an overall home‐field advantage of 4.1 points.
Diagnostic accuracy using artificial intelligence and ultrasound for rotator cuff pathology: A narrative review
Authors: McGuire Lisa B. 
Published: April 2024

AbstractIntroductionThis narrative review aims to assess and compare the diagnostic accuracy of artificial intelligence (AI) techniques with ultrasound in the context of diagnosing rotator cuff pathology.MethodsA comprehensive search of electronic databases was conducted to identify relevant studies published from 2013 to 2023.Studies compared the diagnostic accuracy and precision of AI algorithms and ultrasound for rotator cuff pathology detection.ResultsA total of eight studies met the inclusion criteria and were analysed. The review shows that AI techniques have shown promising results in diagnosing rotator cuff injuries, with reported comparative accuracy, specificity and sensitivity.ConclusionThe limited number of direct comparative studies makes it challenging to draw a definitive conclusion regarding superiority of one modality over another. However, the integration of AI in medical imaging holds significant potential to enhance diagnostic capabilities and streamline patient care.
Macrofloral biostratigraphy reflects late Carboniferous vegetation dynamics in the Nord‐Pas‐de‐Calais Coalfield, France
Authors: Molina‐Solís Azucena , Cleal Christopher J. , Monnet Claude , Cascales‐Miñana Borja 
Published: April 2024

AbstractThe Nord‐Pas‐de‐Calais Coalfield is formed by an almost continuous succession of upper Carboniferous deposits, from which an extremely diverse macroflora has historically been described. Recent evidence has highlighted a clear pattern of changing species diversity, showing some differences from what is seen in other coalfields of Variscan Euramerica. We further study this significant macroflora, focusing on the biostratigraphical changes and their palaeoecological implications. Clustering and ordination analyses have indicated key floral discontinuities that enable the standard regional macrofloral biozones to be recognized in the Nord‐Pas‐de‐Calais Coalfield. By combining these results with the previous diversity studies, six distinct phases in the evolution of the coal swamp vegetation in north‐eastern France can be identified: (1) an initial invasion of peat substrate vegetation in the earliest Langsettian; (2) a rapid diversification of the clastic substrate vegetation in the early–middle Langsettian; (3) a more gradual diversification of the vegetation of both clastic and peat substrates during the late Langsettian to middle Duckmantian glacial phase C3; (4) the appearance of more characteristically late Westphalian, but less diverse floras during the late Duckmantian to early Bolsovian C3–C4 interglacial phase; (5) a marked increase in species diversity in the middle–late Bolsovian, coinciding with the onset of the C4 glacial phase; and (6) a marked reduction in species diversity, and the appearance of new medullosaleans and marattialeans in the Asturian, possibly linked to climate change. The evidence clearly shows how this palaeotropical swamp vegetation was responding to climate change and orogenic landscape changes during Westphalian times.
Preparation of Starch Coconut Fatty Acid Inclusion Complexes by Twin‐Screw Extrusion
Authors: Selling Gordon , Cermak Steven C. , Kenar James A. , Finkenstadt Victoria L. 
Published: April 2024

AbstractStarch‐guest molecule amylose inclusion complexes (AIC) are of interest to industry as a means to encapsulate and deliver compounds. Coconut fatty acids (CFA) consist predominantly of medium chain fatty acids having useful food and nonfood applications. This article describes the formation of high amylose corn (HAC)‐ or waxy corn starch (WC)‐CFA AIC containing 0%, 2%, 7.5%, and 15% CFA using a continuous thermomechanical extrusion process at 20% feed moisture and a twin‐screw extruder with a unique screw design. The extrusion conditions completely destructure both the HAC and waxy starch granules and the resulting materials are evaluated using SEM, XRD, FT‐IR, FTIR‐m, and TGA. The HAC‐CFA materials are shown to contain AIC having 61 V type helical structure between amylose and the CFA that are confirmed by XRD and IR spectral analysis. By TGA, extruded HAC materials containing 15% CFA are shown to have excess CFA present in addition to formed AIC. In contrast, the WC is shown not to form AIC with the CFA and only trap the CFA within the starch matrix. The understanding gained from this study is helpful to design the processing of starch‐based biopolymers to prepare AIC having improved functional properties for potential commercial applications.
Implementation of the Brunswick model system into the Hydrus software suite
Authors: Diamantopoulos Efstathios , Simunek Jirka , Weber Tobias K. D. 
Published: April 2024

AbstractThe Brunswick modular framework for modeling unsaturated soil hydraulic properties (SHP) over the full moisture range was implemented in the Hydrus suite. Users can now additionally choose between four different variants of the Brunswick model: (i) van Genuchten–Mualem (VGM), (ii) Brooks–Corey, (iii) Kosugi, and (iv) modified van Genuchten. For demonstration purposes, simulation results for two different setups, (i) bare soil evaporation and (ii) root water uptake, are presented, along with a comparison of the original VGM model and its Brunswick variant. Results show that the original VGM model underestimates the simulated cumulative evaporation and cumulative transpiration due to the inconsistent representation of the SHP in the dry moisture range. We also implemented a two‐step hydro‐PTF (pedotransfer function) into the Hydrus suite that converts the parameters of the original VGM model (from Rosetta) to the corresponding Brunswick variant. In that way, physically comprehensive simulations are ensured if no data on SHP are directly available, but information on physical soil properties (e.g., texture and bulk density) exists.
Biliary atresia in Uganda: Current ethical challenges and advancement of public policy
Authors: Kakembo Nasser , Loy J. Isaac , Fitzgerald Tamara N. , Antiel Ryan M. 
Published: April 2024

AbstractBiliary atresia is a progressive cholangiopathy in neonates, which often results in liver failure. In high‐income countries, initial treatment requires prompt diagnosis followed by Kasai portoenterostomy. For those with a late diagnosis, or those in whom Kasai portoenterostomy fails, liver transplantation is the only lifesaving treatment. Unfortunately, in low‐ and middle‐income countries, timely diagnosis is a challenge and liver transplantation is rarely accessible. Here, we discuss the ethical dilemmas surrounding treatment of babies with biliary atresia in Uganda. Issues that require careful consideration include: risk of catastrophic health expenditure to families, ethical dilemmas of transplant tourism, medical risks of maintaining the transplant in a low‐resourced health system, and difficult decisions encountered by the surgeon caring for these patients. Four distinct models of the patient‐physician relationship are applied to biliary atresia in Uganda. These models describe differences in patient and physician roles, and patient values and autonomy. Solid organ transplantation is a rapidly evolving segment of healthcare in Uganda and ongoing policy advancements may shift ethical considerations in the future.
Application research of monochromatic micro x‐ray fluorescence in glass physical evidence traceability
Authors: Wang Xingyi , Li Yude , Wang Chenmeng , Huang Shaobo , Zhou Fengzi , Lin Xiaoyan 
Published: April 2024

AbstractMicro‐x‐ray fluorescence (μ‐XRF) is a commonly used elemental analysis technique for glass physical evidence in forensic cases, which can detect major and trace elements in samples and potentially identify glass fragments according to the differences in elemental composition. However, when a sample is irradiated with polychromatic x‐rays, bremsstrahlung scattering from the source radiation provides noise in the fluorescence spectrum and affects the detection results. To improve the signal‐to‐noise ratio of the fluorescence spectrum, a Mμ‐XRF spectrometer constructed under the low‐power Mo target x‐ray tube condition was used to analyze ten kinds of common glass fragments. The application of laboratory Mμ‐XRF analysis in single‐point detection of tiny glass materials was studied. Experimental results show that the detection limit of Sr element was 51 μg/L, and the spectrometer can distinguish different types of small glass fragments according to the fluorescence spectrum information.
The conformal manifold of S-folds in string theory
Authors: Bobev Nikolay , Gautason Friðrik Freyr , van Muiden Jesse 
Published: April 2024

Abstract
We continue the holographic exploration of the conformal manifold of 3d $$ \mathcal{N} $$
N
= 2 S-fold SCFTs constructed by gauging the flavor symmetry of the Gaiotto-Witten T[U(N)] theory. We show how to uplift the two-parameter family of AdS4 vacua dual to this conformal manifold to 10d backgrounds of type IIB supergravity. We use these uplifted solutions to shed new light on the mysterious nature of the infinite distance limit on the conformal manifold and to study probe strings and D3-branes. This analysis uncovers an intriguing structure of the S3 partition function of the S-fold SCFTs which resembles the giant graviton expansion of the superconformal index of 4d $$ \mathcal{N} $$
N
= 4 SYM. We also show how to each member of the family of supersymmetric AdS4 vacua one can associate a consistent truncation to 4d $$ \mathcal{N} $$
N
= 2 gauged supergravity and use this result, in conjunction with holography, to calculate the large N partition function of the 3d S-fold SCFT on compact Euclidean manifolds. Finally, we generalize the supersymmetric AdS4 vacua to a four-parameter family of non-supersymmetric AdS4 solutions.
On the symmetries of singular limits of spacetimes
Authors: Bergshoeff Eric , Matulich Javier , Ortín Tomás 
Published: April 2024

Abstract
We consider spacetime metrics with a given (but quite generic) dependence on a dimensionful parameter such that in the 0 and ∞ limits of that parameter the metric becomes singular. We study the isometry groups of the original spacetime metrics and of the singular metrics that arise in the limits and the corresponding symmetries of the motion of p-branes evolving in them, showing how the Killing vectors and their Lie algebras can be found in general. We illustrate our general results with several examples which include limits of anti-de Sitter spacetime in which the holographic screen is one of the singular metrics and of pp-waves.
Development of an analytical method for the determination of more than 300 pesticides and metabolites in the particulate and gaseous phase of ambient air
Authors: Debler Freya , Gandrass Juergen 
Published: April 2024

AbstractPesticides can enter the atmosphere during spraying or after application, resulting in environmental or human exposure. The study describes the optimisation and validation of analytical methods for the determination of more than 300 pesticides in the particulate and gaseous phases of the air. Pesticides were sampled with high-volume air samplers on glass-fibre filters (GFFs) and glass columns filled with polyurethane foam (PUF) and XAD-2 resin. Comparing different extraction methods, a QuEChERS extraction with acetonitrile was selected for the GFFs. For the PUF/XAD-2 columns, a cold-column extraction with dichloromethane was used. Instrumental determination was performed using liquid chromatography/electrospray ionisation-time-of-flight mass spectrometry (LC/ESI-QTOF) and gas chromatography/electron impact ionisation-tandem mass spectrometry (GC/EI-MS/MS). Recovery experiments showed recovery rates between 70 and 120% for 263 compounds on the GFFs and 75 compounds on the PUF/XAD-2 columns. Semi-quantitative determination was performed for 39 compounds on the GFFs and 110 compounds on the PUF/XAD-2 columns. Finally, 27 compounds on the GFFs and 138 compounds on the PUF/XAD-2 columns could be determined only qualitatively. For the determination of the PUF/XAD-2 samples, signal suppression (LC) or signal enhancement (GC) due to matrix effects were determined. Method quantification limits of the optimised methods ranged from 30 to 240 pg/m3 for the target compounds on the GFFs, and from 8 to 60 pg/m3 on the PUF/XAD-2 columns. The applicability of the method was demonstrated by means of environmental air samples from an agricultural area in the Netherlands.
Placing Green Bridges Optimally, with a Multivariate Analysis
Authors: Fluschnik Till , Kellerhals Leon 
Published: April 2024

AbstractWe study the problem of placing wildlife crossings, such as green bridges, over human-made obstacles to challenge habitat fragmentation. The main task herein is, given a graph describing habitats or routes of wildlife animals and possibilities of building green bridges, to find a low-cost placement of green bridges that connects the habitats. We develop three problem models for this task and study them from a computational complexity and parameterized algorithmics perspective.
Elastic thermobarometry on metapelites across the crustal section of the Famatinian Arc, Argentina
Authors: Giovanini Emanuel , Befus Kenneth S. , Otamendi Juan E. , Cristofolini Eber , Guerreiro Tomas , Cisneros Miguel 
Published: April 2024

AbstractWe applied elastic thermobarometry on garnet-bearing migmatites along two transects through the crustal section at Sierra Valle Fértil-La Huerta, Argentina. We performed quartz-in-garnet barometry and zircon-in-garnet thermometry on metapelites from different paleo-depths across the crustal section. Our work recovers entrapment pressures ranging from 240 to 1330 MPa and entrapment temperatures between 691 and 1574 °C. The entrapment conditions are broadly consistent with anticipated pressures and temperatures along the crustal section derived previously using conventional, thermodynamic thermobarometers. The quartz-in-garnet barometer reproduces those conventionally established entrapment conditions when samples only experienced conditions within the alpha-quartz stability field. Raman-derived pressures for samples that experienced beta-quartz reference conditions are commonly much higher than those established by conventional barometry. Samples that preserve compressive (positive) residual pressures best reproduce reference entrapment pressures. Entrapment temperatures show high variability and overestimation of temperature conditions compared to conventional results. These results indicate elastic thermobarometry over- or under-estimates crystallization conditions in rocks crystallized at high temperatures, as is common in the Famatinian Arc deep-crust. We suggest that modeling quartz behavior across the alpha–beta transition may present challenges, as does shape maturation, viscous deformation, and radiation damage in zircon.