bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recent Advances in Nanoclay‐ and Graphene‐Based Thermoplastic Nanocomposites for Packaging Applications
Authors: Ghosh Suman Kumar , Das Narayan Chandra 
Published: March 2024

ABSTRACTOver the past few years, thermoplastic nanocomposites reinforced with different types of nanofillers have seen widespread use in the automotive, pharmaceutical, food packaging and electronic sectors. Among the different nanofillers used to fabricate thermoplastic composite–based packaging materials, nanoclay and graphene are very beneficial for producing high‐barrier packaging materials. The high aspect ratio and large surface area of both nanoclay and graphene facilitate uniform filler dispersion and tortuous path in the thermoplastic matrix, which ultimately improves the physico‐mechanical, thermal and barrier to oxygen, water vapour and light as well as antimicrobial properties, which are key requirements for packaging materials. Because graphene nanomaterials are electrically and thermally conductive, these thermoplastic nanocomposites may display excellent electrical‐, thermal‐ and microwave‐shielding capabilities, allowing them to be used in electronic packaging. This review aims to summarize the preparation and characterization of thermoplastic nanocomposites based on different types of nanoclay, graphene and graphene derivatives, as well as their prospective applications in food and electronic packaging. This review paper also discusses the factors that can affect the performance and attributes of these packaging materials, such as processing conditions, types of nanofillers, functionalization or modification of nanofillers for better filler dispersion and so forth. This paper presents a comprehensive and state‐of‐the‐art article on nanoclay‐ and graphene‐loaded thermoplastic nanocomposite–based packaging materials.
A dual‐channel transferable RUL prediction method integrated with Bayesian deep learning and domain adaptation for rolling bearings
Authors: Guo Junyu , Wang Zhiyuan , Yang Yulai , Song Yuhang , Wan Jia‐Lun , Huang Cheng‐Geng 
Published: March 2024

AbstractMany deep learning methods typically assume that the marginal probability distribution between the training and testing bearing data is similar or the same. However, the probability distribution of rolling bearings may deviate significantly under diverse working conditions. To address the above limitations, a novel transferable remaining useful life (RUL) prediction method integrated with Bayesian deep learning and unsupervised domain adaptation (DA) is proposed. First, the signal alignment is executed on the data after the first prediction time to maintain the same granularity and scale across both source and target domains. Second, the multi‐domain features are extracted and sent into the dual‐channel Transformer network (DCTN) incorporating the convolutional block attention module (CBAM) to adequately exploit the abundant degradation information. Then, the DA module is incorporated into the model to mitigate the distribution discrepancies of the extracted high‐level merged features between the source and target domains. Finally, by applying the variational inference method, the DCTN‐CBAM is extended to the Bayesian deep neural network, and the RUL prediction and its corresponding confidence intervals can be conveniently derived. In addition, the generalization capability and effectiveness are validated through six bidirectional transfer RUL prediction tasks across two rolling bearing datasets. The experimental results demonstrate that it could provide a more reliable RUL prediction and efficiently account for the prediction uncertainty.
The effects of pastoral hill country natural landscape features and land management practices on nitrate losses and its potential attenuation for improved water quality
Authors: Chibuike Grace , Singh Ranvir , Burkitt Lucy 
Published: March 2024

AbstractPastoral farming on hill country landscapes influences nitrogen (N) dynamics and its losses to freshwater. This study reviewed the current literature identifying key effects of pastoral hill country landscape features and land management practices on nitrate losses to receiving waters. The review also highlighted the potential effects of inherent landscape features on nitrate attenuation pathways for better water quality outcomes. Intensive land use activities involving high rates of fertiliser application, higher stocking rates and cattle grazing, relative to sheep grazing, are more likely to increase nitrate loss, especially on lower slopes. However, soils with a high carbon (C) storage capacity such as allophanic soils potentially limit nitrate loss via denitrification in subsoil layers. Hill country seepage wetlands also offer an opportunity to attenuate nitrate loss, though their efficacy is largely impacted by hydrological variations in their inflows and outflows. By enhancing the natural nitrate attenuation capacity of seepage wetlands, mapping and strategic use of high subsoil denitrification potential, effective riparian management, efficient fertiliser and grazing practices and the incorporation of these farm management strategies into Freshwater Farm Plans (FWFPs), wider environmental and farm productivity/profitability goals, including improved water quality, would be achieved on pastoral hill country landscapes.
Investigation of Antimicrobial Activity and Cytotoxicity of Silver Nanoparticle Synthesized using Dopamine as a Reducing and Capping Agent
Authors: Shumbula Ndivhuwo P. , Ndala Zakhele B. , Nkabinde Siyabonga S. , Nchoe Obakeng , Mpelane Siyasanga , Shumbula Poslet M. , Muthwa Sindisiwe F. , Mdluli Phumlani S. , Mente Pumza , Njengele‐Tetyana Zikhona , Tetyana Phumlani , Mlambo Mbuso , Moloto Nosipho 
Published: March 2024

AbstractWe present a study focused on the controlled fabrication of silver nanoparticles (AgNPs) through colloidal synthesis, employing dopamine as a reducing and capping agent. By manipulating the concentration of silver nitrate, the production of spherical AgNPs with distinct particle diameters (16, 24, 48, and 74 nm) was achieved. The investigation extended to the evaluation of AgNPs′ impact on human embryonic kidney cells, revealing a concentration‐dependent response. At lower AgNPs concentrations, cell viability remained nearly 100 %, progressively declining with rising AgNPs concentrations. Importantly, the cytotoxic thresholds observed were notably elevated, underscoring the relatively mild to moderate toxicity profile of the nanoparticles. Furthermore, the antimicrobial efficacy of these synthesized AgNPs was probed against E. coli and S. aureus bacterial strains. Notably, the AgNPs exhibited robust antimicrobial activity, with superior performance exhibited by smaller‐sized particles compared to larger ones. Impressively, the minimum inhibitory concentration reached as low as 3.5 μg/mL, indicating their potent antimicrobial potential. The achieved distinct particle diameters, concentration‐dependent cytotoxic responses, and potent antimicrobial efficacy against bacterial strains underscore the multifaceted potential of these nanoparticles. These findings contribute valuable insights for their application in diverse fields, from biomedicine to antimicrobial solutions.
Silver Nanoparticles as Antiviral and Antibacterial Agents: A Comprehensive Review of Synthesis Methods and Therapeutic Application
Authors: Sabaghian Hanieh 
Published: March 2024

AbstractSilver nanoparticles have shown inhibitory capabilities and its use in battling viral infections are strengthened by its potent antibacterial activity. Notably, since it directly affects antiviral efficacy, the proper choice of synthesis process for making silver nanoparticles is a vital element to be taken into consideration. The synthesis of silver nanoparticles for the treatment of viral and bacterial infections involves creating silver particles at the nanoscale with unique antimicrobial properties. Various methods exist for synthesizing silver nanoparticles, including chemical reduction, green synthesis, and physical methods. Chemical reduction involves using reducing agents to convert silver ions into silver nanoparticles. Green synthesis employs reducing agents in an environmentally friendly manner. Physical methods rely on techniques such as laser ablation or thermal evaporation to produce silver nanoparticles. In order to provide technological guidance for choosing antiviral silver nanoparticle manufacturing methods, this paper introduces and explores alternative synthesis methods for creating silver nanoparticles.
5‐Bromosalicylaldehyde: Theoretical, Experimental and Spectroscopic (FT‐IR, Raman, H1and C13‐NMR, UV‐Vis) Studies and Their Photovoltaic Parameters
Authors: Bahçeli Semiha , Sarıkaya Ebru Karakaş , Dereli Ömer 
Published: March 2024

AbstractThis study aims to identify a 5‐bromosalicylaldehyde (5BSA) and assess its performance for application in organic solar cells. In the current work, the 5BSA was investigated using various techniques such as FT‐IR, Raman, NMR, and UV‐Vis spectroscopy to characterize the title molecule. The possible conformers of the 5BSA were studied using the MMFF methodology in Spartan software. The geometry optimization of modifications for each conformation was computed using the DFT approach for the B3LYP/6‐311++G(d,p) functional. The energy and dipole moment of most stable form were determined −1879057.42 kcal/mol and 1.455 Debye, respectively. The FT‐IR and Raman vibrational frequencies, the H1and C13NMR chemical shift values (in vacuum and in DMSO‐d6), the UV spectrum calculations (both in vacuum and in the solvent ethanol), the HOMO‐LUMO energy, and the map of MEP. Meanwhile, by considering the properties of organic photovoltaic cells, the open‐circuit voltage (VOC), hole reorganization energy (λh) and electron reorganization energy (λe), light‐harvesting efficiency (LHE), total reorganization energy (λtotal), the short‐circuit current density (Jsc), the driving force (ΔGinject), binding energy (Eb) were also computed for the title compound. In addition, transition density matrix (TDM) and density of states (DOS) analyses were conducted for the 5BSA molecule.
Photocatalytic CO2 Reduction Using Homogeneous Carbon Dots with a Molecular Cobalt Catalyst
Authors: Kim Dongseok , Bhattacharjee Subhajit , Lam Erwin , Casadevall Carla , Rodríguez‐Jiménez Santiago , Reisner Erwin 
Published: March 2024

AbstractA simple and precious‐metal free photosystem for the reduction of aqueous CO2 to syngas (CO and H2) is reported consisting of carbon dots (CDs) as the sole light harvester together with a molecular cobalt bis(terpyridine) CO2 reduction co‐catalyst. This homogeneous photocatalytic system operates in the presence of a sacrificial electron donor (triethanolamine) in DMSO/H2O solution at ambient temperature. The photocatalytic system exhibits an activity of 7.7 ± 0.2 mmolsyngas gCDs−1 (3.6 ± 0.2 mmolCO gCDs−1 and 4.1 ± 0.1 mmolH2 gCDs−1) after 24 hours of full solar spectrum irradiation (AM 1.5G). Spectroscopic and electrochemical characterization supports that this photocatalytic performance is attributed to a favorable association between CDs and the molecular cobalt catalyst, which results in improved interfacial photoelectron transfer and catalytic mechanism. This work provides a scalable and inexpensive platform for the development of CO2 photoreduction systems using CDs.
Emergency mitigation of drought worldwide: Qualitative descriptive design
Authors: Ha Kyoo‐Man 
Published: March 2024

AbstractA popular idea is that slow‐moving droughts worldwide require long‐lasting emergency mitigation. In this article, we describe our study on how human society could improve its emergency mitigation of droughts for the ultimate objective of emergency management. The research methodology involved a qualitative descriptive design. As a paradigm shift, we initially examined middle‐term emergency mitigation to regional droughts to draw the implementation of long‐term emergency mitigation to regional droughts through three stakeholders (i.e., three analytical units such as international institutions, drought‐prone nations, and drought‐resistant nations). A major finding was that the three stakeholders should transform their current middle‐term drought mitigation strategies into long‐term drought mitigation ones. Based on the effectiveness of long‐term emergency mitigation, they must address multiple alternatives to include the strategic vision, Earth's community approach, social impacts of drought, drought fund initiative, lessons from few national cases (e.g., Australia and UAE), education, and scenario‐based training and could integrate droughts with other issues. It is advised that in the future, researchers will expand their study to encompass all nations worldwide.
Numerical analysis of thermal improvement in hydrogen‐based host fluids under buoyancy force and EPNM effects: Study for vertical cylinder
Authors: Adnan  , Abbas Waseem , Eladeb Aboulbaba , Kolsi Lioua 
Published: March 2024

AbstractThe nanofluids became much of interest due to their superior heat mechanism over the conventional fluids. The addition of nanoparticles in the host solvent enhances the internal ability of the liquid to store and transmit heat. Therefore, these fluids are widely used in biomedical engineering, detergents, medication, applied thermal engineering, mechanical, and chemical engineering and so forth. Keeping in mind the significance of nanofluids, this study is conducted to investigate the comparative heat transmission in and under the Effective Prandtl Number Model (EPNM) effects over a vertical permeable cylinder. Formulation of the model is carried out over a vertical cylinder about the stagnation point and the heat transport model is achieved after the successful implementation of the cylindrical stream function, nanofluids effective characteristics, and cylindrical similarity equations. The mathematical treatment was done via RK technique and furnished the results. The nanofluids have the capacity to control the fluid motion more effectively than ordinary fluid and combined convection is better where rapid fluid movement is desired. In the existence of EPNM, higher heat transmission is achieved and is prominent for based on their thermophysical values. Further, the skin friction and Nusselt number are optimum for against .
Analytic and numerical bootstrap for the long-range Ising model
Authors: Behan Connor , Lauria Edoardo , Nocchi Maria , van Vliet Philine 
Published: March 2024

Abstract
We combine perturbation theory with analytic and numerical bootstrap techniques to study the critical point of the long-range Ising (LRI) model in two and three dimensions. This model interpolates between short-range Ising (SRI) and mean-field behaviour. We use the Lorentzian inversion formula to compute infinitely many three-loop corrections in the two-dimensional LRI near the mean-field end. We further exploit the exact OPE relations that follow from bulk locality of the LRI to compute infinitely many two-loop corrections near the mean-field end, as well as some one-loop corrections near SRI. By including such exact OPE relations in the crossing equations for LRI we set up a very constrained bootstrap problem, which we solve numerically using SDPB. We find a family of sharp kinks for two- and three-dimensional theories which compare favourably to perturbative predictions, as well as some Monte Carlo simulations for the two-dimensional LRI.
Topology of critical points in boundary matrix duals
Authors: Yerra Pavan Kumar , Bhamidipati Chandrasekhar , Mukherji Sudipta 
Published: March 2024

Abstract
Computation of topological charges of the Schwarzschild and charged black holes in AdS in canonical and grand canonical ensembles allows for a classification of the phase transition points via the Bragg-Williams off-shell free energy. We attempt a topological classification of the critical points and the equilibrium phases of the dual gauge theory via a phenomenological matrix model, which captures the features of the $$\mathcal{N}$$ = 4, SU(N) Super Yang-Mills theory on S3 at finite temperature at large N. With minimal modification of parameters, critical points of the matrix model at finite chemical potential can be classified as well. The topological charges of locally stable and unstable dynamical phases of the system turn out to be opposite to each other, totalling to zero, and this matches the analysis in the bulk.
Tidal Calibration of the Gladwin Tensor Strain Monitor (GTSM) Array in Taiwan
Authors: Mandler Eugenio , Canitano Alexandre , Belardinelli Maria Elina , Nespoli Massimo , Serpelloni Enrico , Linde Alan 
Published: March 2024

AbstractTo ensure the accuracy and reliability of crustal strain measures, sensors require a thorough calibration. In Taiwan, the complicated dynamics of surface and subsurface hydrological processes under semi-tropical climate conditions conjugated with the rough surface topography could have impacted strainmeter deployment, pushing the installation conditions astray from the optimal ones. Here, we analyze the complex response of 11 Gladwin Strain Monitor (GTSM) strainmeter type deployed in north and central Taiwan and we propose a novel calibration methodology which relies on waveform modeling of Earth and ocean tidal strain-related deformations. The approach is completely data-driven, starting from a simple calibration framework and progressively adding complexity in the model depending on the quality of the data. However, we show that a simple quasi-isotropic model (three calibration factors) is generally suitable to resolve the orientation and calibration of 8 instruments out of 11. We also highlight the difficulty of clearly defining the behavior of instruments that are highly affected by hydrological forcing.
Addressing the generalization of 3D registration methods with a featureless baseline and an unbiased benchmark
Authors: Bojanić David , Bartol Kristijan , Forest Josep , Petković Tomislav , Pribanić Tomislav 
Published: March 2024

AbstractRecent 3D registration methods are mostly learning-based that either find correspondences in feature space and match them, or directly estimate the registration transformation from the given point cloud features. Therefore, these feature-based methods have difficulties with generalizing onto point clouds that differ substantially from their training data. This issue is not so apparent because of the problematic benchmark definitions that cannot provide any in-depth analysis and contain a bias toward similar data. Therefore, we propose a methodology to create a 3D registration benchmark, given a point cloud dataset, that provides a more informative evaluation of a method w.r.t. other benchmarks. Using this methodology, we create a novel FAUST-partial (FP) benchmark, based on the FAUST dataset, with several difficulty levels. The FP benchmark addresses the limitations of the current benchmarks: lack of data and parameter range variability, and allows to evaluate the strengths and weaknesses of a 3D registration method w.r.t. a single registration parameter. Using the new FP benchmark, we provide a thorough analysis of the current state-of-the-art methods and observe that the current method still struggle to generalize onto severely different out-of-sample data. Therefore, we propose a simple featureless traditional 3D registration baseline method based on the weighted cross-correlation between two given point clouds. Our method achieves strong results on current benchmarking datasets, outperforming most deep learning methods. Our source code is available on github.com/DavidBoja/exhaustive-grid-search.
Energy absorption of PLA-based metamaterials manufactured by material extrusion: dynamic loads and shape recovery
Authors: Desole Maria Pia , Gisario Annamaria , Barletta Massimiliano 
Published: March 2024

AbstractThe objective of the study is to evaluate the performance of solid cellular structures in Polylactic Acid (PLA) by extrusion of material. The structures studied are Strut-Based, Triply Periodic Minimal Surfaces (TPMS) and Spinoidal. Impact tests allowed the identification of three categories of energy absorption (low, medium, high). The structures with lower deformation were subsequently subjected to cyclic impact tests, while the others were discarded from the analysis. Once the structures were deformed, they were immersed in a thermostat bath at 70 ºC, a temperature higher than the glass transition of PLA, necessary for the recovery of shape. TPMS structures display the best performance for high and medium impact energies, thanks to the presence of few internal defects. Spinoidal structures perform well at low impact energies but are less suitable for cyclic testing due to their geometric characteristics. Despite featuring the same density of TPMS structures, the strut based ones are not suitable for cyclic testing due to poor mechanical strength. The experimental findings are very promising as the best performing structures can be suitable for the fabrication of products with an increased life cycle, especially in the ever growing and flourishing market of technical items for impacts protection.
Shape-Programming in Hyperelasticity Through Differential Growth
Authors: Ortigosa-Martínez Rogelio , Martínez-Frutos Jesús , Mora-Corral Carlos , Pedregal Pablo , Periago Francisco 
Published: March 2024

AbstractThis paper is concerned with the growth-driven shape-programming problem, which involves determining a growth tensor that can produce a deformation on a hyperelastic body reaching a given target shape. We consider the two cases of globally compatible growth, where the growth tensor is a deformation gradient over the undeformed domain, and the incompatible one, which discards such hypothesis. We formulate the problem within the framework of optimal control theory in hyperelasticity. The Hausdorff distance is used to quantify dissimilarities between shapes; the complexity of the actuation is incorporated in the cost functional as well. Boundary conditions and external loads are allowed in the state law, thus extending previous works where the stress-free hypothesis turns out to be essential. A rigorous mathematical analysis is then carried out to prove the well-posedness of the problem. The numerical approximation is performed using gradient-based optimisation algorithms. Our main goal in this part is to show the possibility to apply inverse techniques for the numerical approximation of this problem, which allows us to address more generic situations than those covered by analytical approaches. Several numerical experiments for beam-like and shell-type geometries illustrate the performance of the proposed numerical scheme.