bluuebunny/crossref_metadata_2025_split huggingface dataset:
Toward quantitative CEST imaging of glutamate in the mouse brain using a multi‐pool exchange model calibrated by 1H‐MRS
Authors: Maguin Cécile , Mougel Eloïse , Valette Julien , Flament Julien 
Published: October 2024

AbstractPurposeTo develop a CEST quantification model to map glutamate concentration in the mouse brain at 11.7 T, overcoming the limitations of conventional glutamate‐weighted CEST (gluCEST) contrast (magnetization transfer ratio with asymmetric analysis).Methods1H‐MRS was used as a gold standard for glutamate quantification to calibrate a CEST‐based quantitative pipeline. Joint localized measurements of Z‐spectra at B1 = 5 μT and quantitative 1H‐MRS were carried out in two voxels of interest in the mouse brain. A six‐pool Bloch‐McConnell model was found appropriate to fit experimental data. Glutamate exchange rate was estimated in both regions with this dedicated multi‐pool fitting model and using glutamate concentration determined by 1H‐MRS.ResultsGlutamate exchange rate was estimated to be ˜1300 Hz in the mouse brain. Using this calibrated value, maps of glutamate concentration in the mouse brain were obtained by pixel‐by‐pixel fitting of Z‐spectra at B1 = 5 μT. A complementary study of simulations, however, showed that the quantitative model has high sensitivity to noise, and therefore, requires high‐SNR acquisitions. Interestingly, fitted [Glu] seemed to be overestimated compared to 1H‐MRS measurements, although it was estimated with simulations that the model has no intrinsic fitting bias with our experimental level of noise. The hypothesis of an unknown proton‐exchanging pool contributing to gluCEST signal is discussed.ConclusionHigh‐resolution mapping of glutamate in the brain was made possible using the proposed calibrated quantification model of gluCEST data. Further studying of the in vivo molecular contributions to gluCEST signal could improve modeling.
Design method of transverse gradient coils based on nonuniform rational B‐spline (NURBS) curves
Authors: Zhu Chenxi , Song Weiran , Liu Lifei 
Published: October 2024

AbstractPurposeTo propose a hybrid transverse gradient coil design method that leverages current density‐based methods and nonuniform rational B‐spline (NURBS) curves to optimize the performance and manufacturability of gradient coils.MethodsOur method begins by generating an initial wire configuration using a density‐based method. Then, we fit NURBS curves to the configuration, and adjust the control parameters of these curves to meet performance requirements. To ensure adequate spacing and even distribution of wires, an objective function utilizing the sigmoid function to modulate the distances between adjacent wires is constructed. Critical factors including gradient efficacy, linearity, eddy current, and torque, are incorporated as constraints. The piecewise nature of the curves provides the flexibility to independently control specific segments without impacting others.ResultsWe validated our method by designing three shielded transverse gradient coils: a whole‐body coil, an ultra‐short whole‐body coil, and an ultra‐short asymmetric head coil. The primary design objectives were to improve linearity and maintain gradient efficiency. All optimized coils demonstrated significant linearity across large diameters of spherical volumes (DSVs), while gradient efficiency, eddy currents, and torque were well‐balanced. The objective function effectively managed the wire concentrations required for high linearity, ensuring even wire arrangement and adequate spacing. We leveraged the flexibility of the curves to individually tailor wire paths for specific objectives, such as preventing interference between coils and passive shimming and accommodating wire connections and cooling circuits.ConclusionThis method provides a versatile and effective approach for designing high‐performance and manufacturable gradient coils.
Ischemia‐Free Liver Implantation Versus Normothermic Machine Perfusion: Evaluation of Feasibility and Security
Authors: Chen Zhitao , Dong Yuqi , Chen Maogen , Zhao Qiang , Wang Tielong , Guo Yiwen , Chen Honghui , Zhang Tao , Yang Yongqi , Gao Yifang , Guo Zhiyong , Ju Weiqiang , He Xiaoshun 
Published: October 2024

ABSTRACTBackgroundFurther optimization and improvement of normothermic machine perfusion (NMP) is necessary, as it can still lead to ischemia injury in transplanted livers. We propose a novel method, termed ischemia‐free liver implantation (IFLI), which maintains a constant blood supply throughout both the preservation and implantation processes. This study aimed to evaluate the feasibility and safety of IFLI compared to NMP.MethodsThirty‐four recipients of IFLI and 17 recipients of NMP were enrolled. The recovery of liver function, complication rates, and survival outcomes were compared between the groups.ResultsThe mean cold ischemia time (CIT), anhepatic time, and surgical duration were 5.94 ± 0.41 h, 50.59 ± 2.10 min, and 439.32 ± 13.25 min for the IFLI group, and 6.29 ± 0.52 h, 54.65 ± 4.32 min, and 428.06 ± 22.04 min for the NMP group (p = 0.333, 0.086, and 0.135, respectively). The IFLI group had a significantly lower incidence of post‐reperfusion syndrome compared to the NMP group (8% vs. 58.8%, p < 0.001), and the incidence rate of PNF was higher in the NMP group (p = 0.041).ConclusionIFLI, by maintaining constant blood supply during implantation, avoids re‐ischemia‐reperfusion injury (re‐IRI) and demonstrates improved postoperative liver function recovery, fewer complications, and greater safety compared to standard NMP.
Populism and policy capacity: Evidence from an opposition municipality in Istanbul
Authors: Ertugal Ebru , Gür Faik , Sevinç İnan 
Published: October 2024

AbstractDespite achievements in its conceptual rigor, policy capacity still represents a relatively depoliticized concept that fails to sufficiently consider the ways in which politics plays a role in its creation, mobilization, or decay. This article seeks to contribute to this debate by investigating the impact of populism on policy capacity, the type of policy capacity challenges posed and how they are related to populist policy design. Based on a case study of a municipality in Istanbul the article shows how populist politics and national populist policy design erode long‐term municipal policy capacity by enabling the (ab)use of the rule of law, loss of expertise, exhaustion of critical assets such as urban land and financial resources, and erosion of public citizenship due to growing expectations in the form of particularistic benefits. Declining policy capacity in turn leads to a shift in municipal policy priorities.
Mechanical recycling of polyamide 6 and polypropylene for automotive applications
Authors: Dehghani Samaneh , Salehiyan Reza , Srithep Yottha 
Published: October 2024

AbstractThis study investigates the mechanical recycling of polyamide 6 (PA6) from discarded fishing nets and polypropylene (PP) from automotive battery scraps and household waste for automotive applications. The mechanical properties of both materials were evaluated through tensile, impact, and thermal testing, revealing that recycled PA6 (r‐PA6) and recycled PP (r‐PP) can achieve mechanical performance similar to virgin materials. Recycled PA6 was reinforced with 30% glass fiber (GF), significantly enhancing its tensile strength from 70 to 170 MPa, comparable with virgin PA6's (76 MPa). Furthermore, the tensile modulus of r‐PA6 increased from 7720 to 8500 MPa. Recycled PP was compounded with thermoplastic elastomers (TPE) and fillers, such as calcium carbonate (CaCO₃) and talc, improving its impact strength from 5 to 18 KJ/m2 and improving thermal stability, with a heat deflection temperature (HDT) reaching 95°C. The optimized formulations for r‐PP, particularly from automotive battery scrap, achieved a melt flow index (MFI) of 12–16 g/10 min, preventing molding defects. This study highlights the importance of controlled thermal treatments, appropriate additive use, and accurate processing conditions in producing high‐quality recycled polymer compounds.Highlights
Recycled PA6 reinforced with 30% GF achieves a tensile strength of 170 MPa.
Thermal treatment increases the tensile modulus of r‐PA6 to 8500 MPa, similar to virgin PA6.
Incorporating TPE improves the impact strength of r‐PP to 18 KJ/m2.
Calcium carbonate and talc enhance the thermal stability of r‐PP to 95°C.
The melt flow index of r‐PP optimized to 12–16 g/10 min for better moldability.
An improved interval‐grey‐probability QFD method for prioritizing engineering characteristics under vague environment
Authors: Cheng Yongbo , Liu Xiao , Zhou Yu , Zhang Qiaoke , Wan Liangqi 
Published: October 2024

AbstractAt present, the interval‐grey quality function deployment (QFD) has been widely used to address a vague information at the early stage of product design. However, the existing interval‐grey QFD method suffers from a problem that it is incapable of comparing specific values from any two intervals within overlapping segments associated with the importance of engineering characteristics (ECs) during the process of prioritizing their importance. This problem consequently impedes the effective prioritization of their magnitudes, thus hindering the prioritization of the importance of ECs. Aiming at addressing the problem, an improved interval‐grey‐probability QFD method is proposed. The proposed method integrates interval grey numbers, grey relational analysis (GRA), and interval‐probability ranking method into the interval‐grey QFD framework to prioritize the importance of ECs under a vague environment. Specifically, the interval grey numbers are used to assess the importance of customer requirements (CRs) and the GRA method is adopted to construct the relationship matrix of CRs‐ECs, respectively. Based on the importance of CRs and the relationship matrix of CRs‐ECs, the interval‐probability ranking method is introduced to measure the prioritization of the importance of ECs. The proposed method is validated by a multi‐function flash drive. Results show that the proposed method is more accurate than existing methods in terms of the deviation degree.
Enhanced Quantum Entanglement Detection of General Two Qubits Systems Based on Modified CNN‐BiLSTM Model
Authors: Sun Qian , Liao Zhichuan , Jiang Nan 
Published: October 2024

AbstractEntanglement is a key element in quantum information processing. The detection of entanglement is crucial in many long‐range quantum information tasks, including secure communication and fundamental tests of quantum physics, but it is also highly resource‐intensive. Even for simple 2‐qubits systems, satisfactory detection is challenging. In this work, a modified entanglement detection model combining a convolutional neural network (CNN) and a bidirectional long short‐term memory network (BiLSTM) is proposed. It shows that the proposed model can effectively extract the deep features and correlations, enabling accurate classification of simple quantum states, even with only a few tens of training samples. When trained with a large number of highly random samples, the model exhibits outstanding fitting capability, resulting in the reliable classification of nearly all common 2‐qubits systems. Furthermore, the model exhibits exceptional adaptability and significant application potential in higher‐dimensional systems.
Enhancing Greenhouse Performance Through Robotic Roof Cleaning Solutions: A Review
Authors: Amin Ahmed , Wang Xiaochan , Chen Yanyu , Guoxiang Sun , Xuekai Huang , Rottok Luke Toroitich , Sayed Hassan A. A. , Okasha Mahmoud , Hassanien Reda Hassanien Emam 
Published: October 2024

ABSTRACTThe robotics industry has seen significant growth and advancement in the agricultural sector, particularly, in agricultural greenhouses. This study presents the most common cleaning methods for greenhouse roofs, including manual and automatic cleaning techniques. On the other hand, it provides greenhouse types, designs, and factors affecting lighting. It highlights the importance of cleaning and discusses the challenges of various robot designs and their future prospects. It was found that dust accumulation on greenhouse roofs could decrease the light intensity by 30%. Consequently, it could reduce the crop yield and quality by over 30%. Therefore, regular cleaning is crucial to provide the optimal light intensity for crops. The manual or traditional cleaning methods can cause damage, injuries, inefficiency, high costs, and labor shortages. This study investigates greenhouse‐cleaning robots and devices in terms of their operation, specifications, quality, and accuracy. Meanwhile, it summarizes the pros and cons of automatic cleaning. Furthermore, it evaluates robots based on a movement system, cleaning efficiency, and all characteristics in different countries. It was found that robots for Venlo‐type greenhouses are the most common and advanced robots, which achieve a light transmittance of up to 88% after cleaning. China and the Netherlands are at the forefront of commercial research technology applications. In conclusion, this study recommends investing more in robotic greenhouse cleaners to boost productivity and develop an intelligent cleaning system for greenhouse roofs. In addition, further research should be implemented to improve the durability and decrease the prices of robots.
Alkali‐Mediated/Catalyzed Transition‐Metal‐Free Tandem Reaction Triggered by the Borrowing Hydrogen and Aerobic Dehydrogenation Processes of Alcohols
Authors: Chang Ai , Zhou Weihao , Zhao Sicong , Song Haowen , Zhuang Yi , Lin Yamei , Huang Shenlin , Lu Guo‐Ping 
Published: October 2024

AbstractThe transformation of alcohols to important classes of compounds is a central topic in chemistry because they are abundant, renewable, and attractive building blocks. The alkali‐mediated/catalyzed borrowing hydrogen and aerobic dehydrogenation processes of alcohols open a new and sustainable access for the alcohol conversion under transition‐metal‐free conditions. In this review, we summarize the recent alkali‐mediated/catalyzed sequential reactions involving the borrowing hydrogen and aerobic dehydrogenation processes of alcohols. Furthermore, this review not only introduces the tentative pathways of these transformations, but also discusses the role of alkali, solvent effects, and substrate reactivity on these reactions.
Design of Novel Naphthalimidopropanediol Derivatives as Staphylococcus Aureus Antibacterial Agents Utilizing 3D‐QSAR, ADMET, Molecular Docking, and Dynamics Simulations
Authors: Xiong Fei , Xu Jie , Wang Zhonghua 
Published: October 2024

AbstractStaphylococcus aureus is a prevalent foodborne pathogen, and its resistance has become more pronounced due to antibiotic overuse. In this paper, we constructed a 3D‐QSAR model using 47 naphthalimidopropanediols derivatives (NIOLs). The results indicate that the CoMFA model (q2 = 0.771, r2 = 0.998) and CoMSIA‐ASH model (q2 = 0.638, r2 = 0.995) exhibit favorable predictive capabilities, leading to the design of 11 novel NIOLs as antibacterial agents. ADMET was used to validate their pharmacokinetic characteristics, molecular docking was performed to validate the binding capability of the designed molecules, dynamics simulations, and binding free energy were employed to verify the accuracy of docking results. The results demonstrate excellent performance of the designed novel molecules, which may provide significant references for the development of novel and effective antibacterial agents against S. aureus.
Nanoimprinting of Crosslinked Polyurethane / Polycaprolactone Blends: Scratch Recovery of Surface Topographies
Authors: Ramasamy Chitrakala , Tan Jeck Chuang , Low Hong Yee 
Published: October 2024

AbstractScratch recovery of micro‐nano‐patterned polymer surfaces extends the service life of products that require tunable surface properties and contributes to more sustainable development. Scratch recovery has been widely studied in bulk and 4D‐printed polymers via intrinsic self‐healing mechanisms. Existing studies on self‐healing of micro/nano‐scale polymeric surfaces are limited to the recovery of controlled tensile or compressive strain. Scratch recovery requires material transport to close the gap created by a scratch. Here, for the first time, scratch recovery of thermally nanoimprinted polymer surfaces in a heterogeneous polymer is reported. A blend of Polyurethane (TPU) and poly(caprolactone) (PCL) with selectively crosslinked TPU imparts shape‐memory properties, and the uncrosslinked PCL retains chain mobility for molecular diffusion during scratch recovery. Scratch recovery of nanoimprinted micro‐pillars has been achieved spontaneously and completely by heat and without any pressure input. The healing temperature is determined to be the melting point of PCL at 60 °C. Rapid recovery is also achieved at 60 s with complete closure of scratch width of 5 µm and topography recovery of the nanoimprinted micro‐pillars.
Advanced X/γ‐Ray‐Shielding Materials Enabled by the In Situ Generation of Cerium–Tungsten Nanoparticles Within Regenerated Collagen Fibers
Authors: Wang Yaping , Wang Xirui , Yi Han , Yan Linping , Liao Xuepin , Shi Bi 
Published: October 2024

AbstractAdvanced X‐ and γ‐ray‐shielding materials are conventionally designed and fabricated via the uniform dispersion of high‐Z elements into the substrate. These soluble high‐Z elements considerably reduced the particle size of functional components; however, the as‐obtained composites exhibited weak absorption region at 40–80 keV and poor water resistance. To address these issues, such materials are fabricated by introducing cerium and tungsten into regenerated collagen fibers (RCFs) using a “dual impregnation–desolvation” strategy. The uniform dispersion of functional components is achieved via the in situ generation of cerium–tungsten nanoparticles (CeW NPs) under multiple impregnating and desolvating cycles; as a result, the CeW NPs achieved an ultrasmall particle size of 17.15 nm. Benefiting from the ultrasmall particle size and uniform dispersion of CeW NPs, the fabricated CeW‐RCF composites exhibit satisfactory X‐ and γ‐ray‐shielding capabilities with an ultrahigh mass attenuation coefficient (MAC) of 5.9 cm2 g−1 at 83 keV, higher than that of lead plates. The CeW‐RCF composites also exhibit outstanding mechanical strength, low density, and high air permeability, demonstrating their superior wearability. This work provides novel insights into the design and fabrication of advanced X‐ and γ‐ray‐shielding materials with high radiation‐shielding performance and enhanced wearability.
Vapor–Solid Interface Synthesis of Highly Crystalline Covalent Triazine Frameworks for Use as Efficient Photocatalysts
Authors: Chen Minghui , Xiong Ji , Shi Quan , Zhang Weiwei , Chen Zhuoran , Wang Xiaolin , Zhu Xinyue , Guo Kai , Feng Yaqing , Zhang Bao 
Published: October 2024

AbstractHarsh synthetic conditions for crystalline covalent triazine frameworks (CTFs) and associated limitations on structural diversities impede not only further development of functional CTFs, but also practical large‐scale synthesis. Herein, a mild and universal vapor–solid interface synthesis strategy is developed for highly crystalline CTFs employing trifluoromethanesulfonic acid vapor as catalysts. A series of highly ordered simple and functional CTFs (CTF‐TJUs) can be facilely produced. In particular, the porphyrin‐involved functional CTF (CTF‐TJU‐Por1) with high crystallinity is synthesized for the first time via this universal approach. The mechanism of vapor‐catalyzed trimerization of nitrile monomers is thoroughly investigated through semi in situ characterizations. As a proof of concept, the photocatalytic performance of synthesized CTFs for water splitting is evaluated. CTF‐TJU‐133 exhibits significantly greater photocatalytic rates for hydrogen (4.35 µmol h−1) and oxygen (2.18 µmol h−1) evolutions during overall water splitting under visible light irradiations compared to other CTF‐TJUs, representing one of the highest values among reported CTF photocatalysts. Further studies reveal that enhanced photocatalytic performance of CTF‐TJU‐133 results from optimized band structure, extended visible‐light absorption, and high carrier separation efficiency. This study provides a promising strategy to synthesize various simple and functional CTFs, which significantly enriched diversities of CTF family for different application purposes.
A Bio‐Inspired Magnetic Soft Robotic Fish for Efficient Solar‐Energy Driven Water Purification
Authors: Qin Jingjing , Li Jiahao , Yang Guozheng , Chu Kaibin , Zhang Leiqian , Xu Fangping , Chen Yujie , Zhang Yaoxin , Fan Wei , Hofkens Johan , Li Bo , Zhu YinBo , Wu HengAn , Tan Swee Ching , Lai Feili , Liu Tianxi 
Published: October 2024

AbstractSolar‐driven water evaporation is a promising solution for global water scarcity but is still facing challenges due to its substantial energy requirements. Here, a magnetic soft robotic bionic fish is developed by combining magnetic nanoparticles (Fe3O4), poly(N‐isopropylacrylamide), and carboxymethyl chitosan. This bionic fish can release liquid water through hydrophilic/hydrophobic phase transition and dramatically reduce energy consumption. The introduced Fe3O4 nanoparticles endow the bionic fish with magnetic actuation capability, allowing for remote operation and recovery. Additionally, the magnetic actuation process accelerates the water absorption rate of the bionic fish as confirmed by the finite element simulations. The results demonstrate that bionic fish can effectively remove not only organic molecular dyes dissolved in water but also harmful microbes and insoluble microparticles from natural lakes. Moreover, the bionic fish maintains a good purification efficiency even after five recycling cycles. Furthermore, the bionic fish possesses other functions, such as salt purification and salt rejection. Finally, the mechanism of water purification is explained in conjunction with molecular dynamics calculations. This work provides a new approach for efficient solar‐energy water purification by phase transition behavior in soft robotics.
On Optimizing Resources for Real‐Time End‐to‐End Machine Learning in Heterogeneous Edges
Authors: Nguyen Minh‐Tri , Truong Hong‐Linh 
Published: October 2024

ABSTRACTDeploying end‐to‐end ML applications on edge resources becomes a viable solution to achieve performance and data regulations. With the microservice architecture, these applications can scale dynamically, improving service availability under dynamic workloads. However, orchestrating multiple end‐to‐end ML applications within heterogeneous edge environments must deal with numerous challenges while sharing computing resources. Prevalent orchestration tools/frameworks supporting edge ML serving are inefficient in provisioning methods due to constrained resources, diverse resource demands and utilization patterns. In this work, we present a provisioning method to optimize resource utilization for end‐to‐end ML applications on a heterogeneous edge. By profiling all microservices within the application, we estimate scales and allocate them on desired hardware platforms with sufficient resources when considering their runtime utilization patterns. We also provide several practical analyses on runtime monitoring metrics to detect and mitigate resource contentions, guaranteeing performance. The experiments with three real‐world ML applications demonstrate the practicality of our method on a heterogeneous edge cluster of Raspberry Pis and Jetson Developer Kits.