bluuebunny/crossref_metadata_2025 huggingface dataset:
Variability in Diagnosis and Management of Hypoglycemia in Neonatal Intensive Care Unit
Authors: Dinu Daniela , Hagan Joseph L. , Rozance Paul J.
Published: April 2024

Objective Hypoglycemia, the most common metabolic derangement in the newborn period remains a contentious issue, not only due to various numerical definitions, but also due to limited therapeutical options which either lack evidence to support their efficacy or are increasingly recognized to lead to adverse reactions in this population. This study aimed to investigate neonatologists' current attitudes in diagnosing and managing transient and persistent hypoglycemia in newborns admitted to the Neonatal Intensive Care Unit (NICU).

Methods A web-based electronic survey which included 34 questions and a clinical vignette was sent to U.S. neonatologists.

Results There were 246 survey responses with most respondents using local protocols to manage this condition. The median glucose value used as the numerical definition of hypoglycemia in first 48 hours of life (HOL) for symptomatic and asymptomatic term infants and preterm infants was 45 mg/dL (2.5 mmol/L; 25–60 mg/dL; 1.4–3.3 mmol/L), while after 48 HOL the median value was 50 mg/dL (2.8 mmol/L; 30–70 mg/dL; 1.7–3.9 mmol/L). There were various approaches used to manage transient and persistent hypoglycemia that included dextrose gel, increasing caloric content of the feeds using milk fortifiers, using continuous feedings, formula or complex carbohydrates, and use of various medications such as diazoxide, glucocorticoids, and glucagon.

Conclusion There is still large variability in current practices related to hypoglycemia. Further research is needed not only to provide evidence to support the values used as a numerical definition for hypoglycemia, but also on the efficacy of current strategies used to manage this condition.

Key Points
Einheitlich, interdisziplinär und anwenderfreundlich: Logisch verknüpfte Terminologie-Standards
Authors: Hölbling Catrin
Published: April 2024

Nur eine digitale Pflege- und Behandlungsdokumentation, die auf einer standardisierten Terminologie basiert, liefert strukturierte und auswertbare Daten, die auch jenseits des Krankenbetts relevant sind: sei es im Qualitätsmanagement, bei der automatisierten Ableitung von Scores oder Pflegegraden, bei der Abrechnung oder als Basis für AI-basierte Anwendungen. Terminologie-Standards lassen sich gut in Klinik-informationssysteme integrieren und entlasten das Klinikpersonal.
Evolution der Motivation: Meine, Deine, unsere Pflicht
Authors: Napp Barbara
Published: April 2024

Macht Sie eigentlich Ihr Pflichtbewusstsein glücklich? Goethe hat als eines seiner Maxime geschrieben „Was aber ist Deine Pflicht? Die Forderung des Tages!“ Und ja, ich bin glücklich und zufrieden, wenn ich den Forderungen meines (Arbeits-)Tages begegnet bin.
Gesundheitsmanagementkongress beim HSK: Von Reform bis Fachkräftemangel
Authors: Reisinger Kathrin
Published: April 2024

Wenn vom 26. bis 28. Juni 2024 der Hauptstadtkongress in Berlin seine Tore öffnet, wird es für die Medizin in Deutschland wohl so spannend wie noch nie. Von „dringenden Problemen“, „Hängepartie“ und „gefühltem Stillstand“ reden immer mehr Manager, Ärzte, Wissenschaftler und Pflegekräfte in allen Bereichen.
Editorial: Auf dem Weg, aber längst noch nicht da
Authors: Herrschelmann Anna
Published: April 2024

Die Vision eines nahtlos vernetzten Gesundheitssystems scheint zum Greifen nah. Doch bis die Vision zur Realität wird, sind noch viele Hürden zu meistern.
Digitale Transformation: Die Zeit läuft ab
Authors: Gocke Peter
Published: April 2024

Mit dem Krankenhauszukunftsgesetz (KHZG) hatte sich 2020 der frühere Bundesgesundheitsminister Jens Spahn (CDU) nahtlos in die Reihe seiner Vorgänger eingefügt. Ihr gemeinsames Ziel: Mehr Schub für die Digitalisierung des Gesundheitswesens. Doch die KHZG-Förderung ist bald Geschichte. Und was dann?
Roboterassistenzsysteme: Revolution in der Chirurgie
Authors: Heeser Alexandra
Published: April 2024

Roboter sind in der Medizin nicht mehr wegzudenken. Gerade in der Chirurgie kommen die präzisen Helfer da Vinci, Mako und Co. zum Einsatz und tragen zu einer verbesserten Patientenversorgung bei. Auch für die Mikrochirurgie gibt es mittlerweile Robotiksysteme, die jedoch umstritten sind.
Dienstplanerstellung: Blockaden durch den Betriebsrat vermeiden
Authors: Pirpamer Bernd
Published: April 2024

Ein wesentliches Element des Arbeitszeitmanagements ist die Aufstellung von Dienstplänen. Dabei ist zwingend der Betriebsrat zu beteiligen. Denn ohne dessen Zustimmung darf der Dienstplan nicht umgesetzt werden. Häufig ergeben sich dadurch rechtliche und operative Konflikte.
MVZ: Kampf gegen „Heuschrecken“
Authors: Rößing Sabine
Published: April 2024

Bundesgesundheitsminister Karl Lauterbach will renditeorientierte Finanzinvestoren aus der ambulanten Versorgung drängen. Er hat Gesetze angekündigt, die ihr Vordringen in den Bereich der medizinischen Versorgungszentren erschweren sollen. Doch bislang scheint neben vielen Gutachten wenig Zählbares herauszukommen. Die Debatte steckt fest.
EU-Medizinprodukte-Verordnung: Flaschenhals MDR
Authors: Kucera Martin
Published: April 2024

Die Kritik an der neuen Medizinprodukte-Verordnung reißt nicht ab. Sie schwächt die Wettbewerbs- und Innovationskraft der mittelständisch geprägten Branche und gefährdet die Patientenversorgung in der EU, so Industrieverbände und Fachgesellschaften. Die Erfahrung der betroffenen Hersteller bestätigt das.
COVID-19, the Russia–Ukraine war and the connectedness between the U.S. and Chinese agricultural futures markets
Authors: Zhang Yongmin , Sun Yiru , Shi Haili , Ding Shusheng , Zhao Yingxue
Published: April 2024

This study focuses on how recent global crises such as the COVID-19 pandemic and the Russia–Ukraine war have affected the relationship between the U.S. and Chinese agricultural futures markets. By applying wavelet coherence analysis (WCA) and time-varying parameter vector autoregression (TVP-VAR), we obtain the following findings. First, both events have changed the correlation and lead–lag comovement between U.S. and Chinese soybean and corn futures returns but have little impact on the comovement between the two cotton futures returns. Second, U.S. agricultural markets transmit more volatility risk to Chinese markets than the risk spillover from the reverse direction. Third, the risk spillover enhancement effect from the war is stronger than that from the pandemic, which is obvious in both the soybean and corn futures markets but not in the cotton market. Our paper has implications for policy makers seeking to stabilize agricultural commodity prices during global crisis episodes and for designing strategies for cross-market hedging of spillover risks among commodity markets for international investors.
The future of the labor force: higher cognition and more skills
Authors: Zhang Wen , Lai Kee-Hung , Gong Qiguo
Published: April 2024

Skills can be categorized into two types: social-cognitive and sensory-physical. Sensory-physical skills, governed by explicit rules and transparent rationales, can be effectively executed through meticulous programming, with humans spontaneously trusting machines to perform these skills. In contrast, social-cognitive skills entail open interpretations reliant on personal opinions or intuition and are contextually and problem-dependent. The inherent complexity and subjectivity of social-cognitive skills, underscored by Polanyi’s paradox and algorithm aversion, render machines less capable of replicating these skills. Thus, automation exerts differential impacts on these two skill sets. Moreover, the specialization of machines leads to expensive setup costs when switching tasks, whereas humans switch tasks with much less effort. The versatility in skills enables workers to adapt to a wide array of tasks, making them less prone to automation. Our empirical research, utilizing skill score data from O*NET and employment data from Employment and Wage Statistics (OEWS), validated the attributes of labor resistant to automation: the higher the scores of cognitive skills in a job, the lower its susceptibility to automation; workers endowed with a diverse array of skills experience an increase in their employment share. Conversely, jobs focusing on sensory-physical skills are more likely to be supplanted by machines. Therefore, workers can adopt two strategies to maintain a competitive edge. First, they can enhance cognitive skills, such as creativity and critical thinking. Second, they can develop diverse skills, encompassing both social-cognitive and sensory-physical skills. Specializing in a specific sensory-physical skill does not offer an advantage. Fostering a workforce proficient in cognitive skills and equipped with multifaceted skills, that is, flexible workers, becomes imperative. Our investigation represents the inaugural effort to empirically affirm the differential impact of automation on sensory-physical versus social-cognitive skills, thereby delineating the characteristics of irreplaceable labor. This analysis offers critical insights for individual career development and the strategic planning of national educational systems.
COVID-19 vaccination, preventive behaviours and pro-social motivation: panel data analysis from Japan
Authors: Yamamura Eiji , Tsutsui Yoshiro , Ohtake Fumio
Published: April 2024

The COVID-19 vaccine reduces infection risk; even if one contracts COVID-19, the probability of complications such as death or hospitalisation is lower. However, vaccination may prompt people to decrease preventive behaviours, such as staying home, washing hands, and wearing a mask. Therefore, if vaccinated people pursue only self-interest, the vaccine’s effect may be lower than expected. However, if vaccinated people are pro-social (motivated toward benefits for the whole society), they might maintain preventive behaviours to reduce the spread of infection. We conducted 26 surveys almost once a month from March 2020 (the early stage of COVID-19) to September 2022 in Japan. By corresponding with identical individuals, we independently constructed the original panel data (N = 70,908). Based on the data, we identified the timing of the second vaccine shot and compared preventive behaviours before and after vaccination. We investigated whether second-shot vaccination correlated with changes in preventive behaviours. Furthermore, we explored whether the vaccination effect differed between the older and younger groups. We then investigated the effect of pro-social motivation on preventive behaviours. Major findings are as follows: (1) Being vaccinated led people to increase preventive behaviours, such as mask-wearing by 1.04 (95% confidence intervals [Cis]: 0.96–1.11) points, and hand hygiene by 0.34 (95% CIs: 0.30–0.38) points on a 5-point scale. (2) Vaccinated people under 65 are less likely to stay home. (3) People with pro-social motivation to be vaccinated are more likely to maintain prevention than those not so motivated; on a 5-point scale, the difference is 0.08 (95% CIs: 0.01–0.15) points for mask-wearing and 0.05 (95% CIs: 0.001–0.10) points for hand hygiene. After vaccination, the opportunity cost of staying home outweighs its benefits, and people are less inclined to stay at home. This effect is lower in older people who are at a higher risk of serious illness. The opportunity cost of wearing masks and hand hygiene is lower than that of staying home, and the benefit persists after vaccination if people are motivated to maintain these behaviours for others’ well-being.
Photodissociation studies on (H2O)
n
+(n=2–5) clusters at 308 nm
Authors: Zhao Yunxiao , Hu Gaoming , Li Youqing , Chen Yang , Zhao Dongfeng
Published: April 2024

The photodissociation dynamics of small (H2O)n+ (n=2–5) clusters have been studied at 308 nm using a high resolution cryogenic cylindrical ion trap velocity map imaging spectrometer. Time-of-flight mass spectra and images of ionic photofragments are recorded. (H2O)2+ clusters dissociate to yield H3O+ and H2O+ photofragments, indicating the presence of both proton-transferred (H3O+-OH) and hemibonded (H2O-OH2)+ structures for the dimer cluster. (H2O)n+ (n=3–5) clusters prevailingly dissociate to the H+(H2O)n–2, …,1 photofragments by losing both of OH and H2O components, and the (H2O)5+ cluster shows an additional channel to produce H+(H2O)4 by only losing OH. The former suggests the (H2O)n–2H3O+OH structures for the (H2O)n+ (n=3–5) clusters, while the latter suggests in (H2O)5+ that, the H3O+ core and OH are separated by H2O. The results elucidate the structure progresses of small (H2O)n+ clusters. The experimental images yield negative and small values for the anisotropy parameters of photofragments, indicating that (H2O)n+ (n=2–5) clusters undergo vertical electronic transitions upon photon absorption followed by slow dissociation, and lead to highly internally excited photofragments.
Direct observation of long-lived vibrational hot ground states by ultrafast spectroscopy and visible/lnfrared double excitation fluorescence
Authors: Yu Qirui , Li Xinmao , Shen Chengzhen , Yu Zhihao , Guan Jianxin , Zheng Junrong
Published: April 2024

It is widely believed that the relaxation-induced bleaching signals at nanoseconds observed in ultrafast infrared spectroscopic measurements are due to the local heat effect resulting from the thermalization of the infrared excitations. In this work, combining ultrafast IR pump/probe, 2D-IR, visible pump/IR probe, and ultrafast visible/IR double resonant fluorescence experiments, the vibrational hot ground states of fluorescein dianion in methanol solutions are found to be unexpectedly long, at the time scale of nanoseconds. This result indicates that the long-standing bleaching signal observed in the nonlinear IR experiments must have significant contributions from these hot ground states for the initial couple of ns. It is likely that a similar mechanism can also hold for other molecular systems. The hot ground states can last much longer than conventionally expected, which can potentially be applied to modify chemical reactions.
Stability of fluorescence emission from gold nanoclusters and photocatalytic redox on surface
Authors: Zeb Johar , Guo Huijun , Yuan Qunhui , Gan Wei
Published: April 2024

The fluorescent emission and the photocatalytic activity of gold nanoclusters (AuNCs) are important properties of AuNCs. Here, we synthesized water-soluble, captopril (Capt) and glutathione (GSH) covered Au25(Capt)18 and Au15(GSH)13 nanoclusters and investigated their fluorescence stabilities which are correlated with the photo-redox of their surface. It was observed that Au25(Capt)18 exhibited a decay in its two-photon fluorescence emission induced by surface oxidation upon irradiation of femtosecond near-infrared laser (810 nm, 300 mW) in the presence of oxygen (O2). On the other hand, the two-photon fluorescence from Au15(GSH)13 was stable upon the same excitation. The different stabilities of the fluorescence of the two AuNCs were attributed to their different band gaps. This interpretation was confirmed by one-photon excitation with photon energy beyond the band gaps of the two AuNCs. Using experiments with the addition of several agents, the photocat alytic redox activities of gold atoms on the surface of Au25(Capt)18 were understood and tuned.
Investigation of 10 kHz filtered Rayleigh scattering and CH2O planar laser-induced fluorescence measurement in two-stage swirl combustor
Authors: Yin Shengming , Fei Zhiyong , Li Linye , Wang Shaojie , Xu Liangliang , Lin Yang , Wang Sheng , Ye Jingfeng , Xia Xi , Gu Mingming , Qi Fei
Published: April 2024

We present an exploration of two-dimensional flame thermometry and CH2O field measurement in a swirling flame within a two-stage radial stratified swirl combustor, operating under atmospheric pressure conditions. The research details the calibration and analysis of filtered Rayleigh scattering (FRS) signal intensity, employing a planar flame from a Hencken burner to establish a calibration curve for the FRS signal ratio and temperature. The 2-D temperature field results for the swirling flame are then showcased, all obtained using the calibrated FRS system. Parametric analysis focuses on the temperature fields of methane/air mixtures with equivalence ratios ranging from 0.65 to 1.05. The flame shape changes from V-shape to M-shape for a single-swirling flame with an equivalence ratio of 0.85, and that this change in shape is due to a combination of thermal diffusion effects and air-conducting effects. Furthermore, in the dual-swirling flame, the study identifies a transition from mergence to stratification during combustion in both the pilot and main stage flames under the same operating conditions. The article concludes by presenting and comparing the phase-averaged temperature field distributions and instantaneous CH2O distributions during the stratified phenomena of the dual-swirling flame.
Recent advances in analyzing protein and peptide structures at
interfaces using vibrational sum-frequency generation
Authors: Wang Baihui , Bai Yimin , Peng Jiahui , Zhang Miaomiao , Zhang Weiting , Bian Hongtao , Fang Yu
Published: April 2024

The structure of protein and peptide at interfaces plays a crucial role in various biological processes and technological advancements. Understanding these structures is critical for diagnosing diseases, drug delivery, and developing biomaterials. However, the complexity of these systems and limitations in analytical tools have hindered the in-depth exploration. Despite significant efforts in determining protein structures using advanced techniques like X-ray crystallography and cryo-electron microscopy, the understanding of surface-bound protein structures in real conditions remains relatively limited, posing a current challenge in this field. Vibrational sum frequency generation (SFG) spectroscopy has been developed as a versatile method for elucidating molecular structures of proteins across interfaces. This review is intended to introduce the basic principle of SFG spectroscopy, discuss its current advancements in phase measurement, and showcase recent examples (2021–2023) illustrating SFG’s ability in revealing the molecular structure of peptides and proteins at interfaces. This concise review aims to establish a foundation for future studies and applications exploring different types of peptides and proteins at interfaces using SFG.
Plasmon induced heat funneling from Au to Cu in the bimetallic Au@Cu core-shell nanoparticles
Authors: Shi Danli , Yang Jingyi , Li Minjie , Lv Jianchang , Liu Xi , Liu Ao , Guo Shaoshi , Wan Yan
Published: April 2024

The bimetallic nanostructures that mix a plasmonic metal with a transition metal in the form of the core-shell nanoparticles are promising to promote catalytic performance. But it is still unclear how the heat (hot electrons and phonons) transfers on the interface between two metals. We have designed and synthesized Au@Cu bimetallic nanoparticles with Au as core and Cu as shell. By using transient absorption spectroscopy, we find that there are two plasmon induced heat funneling processes from Au core to Cu shell. One is the electron temperature equilibrium (electron heat transfer) with equilibration time of ~560 fs. The other is the lattice temperature equilibrium (lattice heat transfer) with equilibration time of ~13 ps. This plasmon induced heat funneling may be universal in similar bimetallic nanostructures, so our finding could contribute to further understanding the catalytic mechanism of bimetallic plasmonic photothermal catalysis.
One-dimensional Schrödinger operator with decaying white noise potential
Authors: Minami Nariyuki
Published: April 2024

In this paper, we consider a random one-dimensional Schrödinger operator Hω on the half line which has, as its potential term, Gaussian white noise multiplied by a decaying factor. Although the potential term is not an ordinary function, but a distribution, it is possible to realize Hω as a symmetric operator in L2([0, ∞); dt) as was pointed out by the present author [Minami, Lect. Notes Math. 1299, 298 (1986)], and it will be shown that Hω is actually self-adjoint with probability one. When the white noise in Hω is replaced by random functions of a specific type, [Kotani and Ushiroya, Commun. Math. Phys. 115, 247 (1988)] made a precise analysis of the positive part of the spectrum. According to them, if the decaying factor is not square integrable, the positive part of the spectrum typically consists of singular continuous and dense pure-point parts, which are separated by a threshold number. On the other hand, the positive part of the spectrum is purely absolutely continuous when the decaying factor is square integrable. In this work, we shall focus on the case of square integrable decaying factor, and prove the absolute continuity of the positive part of the spectrum of Hω. We shall further prove that the negative part of the spectrum of Hω is discrete, with no accumulation points other than 0.
Enhancing quantum annealing in digital–analog quantum computing
Authors: Kadowaki Tadashi
Published: April 2024

Digital–analog quantum computing (DAQC) offers a promising approach to addressing the challenges of building a practical quantum computer. By efficiently allocating resources between digital and analog quantum circuits, DAQC paves the way for achieving optimal performance. We propose an algorithm designed to enhance the performance of quantum annealing. This method employs a quantum gate to estimate the goodness of the final annealing state and find the ground state of combinatorial optimization problems. We explore two strategies for integrating the quantum annealing circuit into the DAQC framework: (1) state preparation, and (2) embedding within the quantum gate. While the former strategy does not yield performance improvements, we discover that the latter enhances performance within a specific range of annealing time. Algorithms demonstrating enhanced performance utilize the imaginary part of the inner product of two states from different quantum annealing settings. This measure reflects not only the energy of the classical cost function but also the trajectory of the quantum dynamics. This study provides an example of how processing quantum data using a quantum circuit can outperform classical data processing, which discards quantum information.
A new hybrid odd exponential-Φ family: Properties and applications
Authors: Mahdi Ghanam A. , Khaleel Mundher A. , Gemeay Ahmed M. , Nagy M. , Mansi A. H. , Hossain Md. Moyazzem , Hussam Eslam
Published: April 2024

The paper introduces the hybrid odd exponential-Φ (HOE-Φ) family, a novel framework for generating a continuous distribution characterized by an additional parameter. The extensive statistical properties of this family are derived and explored in detail. Parameter estimation is performed using the maximum likelihood estimation technique. The efficacy and versatility of the proposed model are demonstrated through a comparative analysis involving two distinct real-world datasets.
Emulation techniques for scenario and classical control design of tokamak plasmas
Authors: Agnello A. , Amorisco N. C. , Keats A. , Holt G. K. , Buchanan J. , Pamela S. , Vincent C. , McArdle G.
Published: April 2024

The optimization of scenarios and design of real-time-control in tokamaks, especially for machines still in design phase, requires a comprehensive exploration of solutions to the Grad–Shafranov (GS) equation over a high-dimensional space of plasma and coil parameters. Emulators can bypass the numerical issues in the GS equation, if a large enough library of equilibria is available. We train an ensemble of neural networks to emulate the typical shape-control targets (separatrix at midplane, X-points, divertor strike point, flux expansion, and poloidal beta) as a function of plasma parameters and active coil currents for the range of plasma configurations relevant to spherical tokamaks with a super-X divertor, with percent-level accuracy. This allows a quick calculation of the classical-control shape matrices, potentially allowing real-time calculation at any point in a shot with submillisecond latency. We devise a hyperparameter sampler to select the optimal network architectures and quantify uncertainties on the model predictions. To generate the relevant training set, we devise a Markov-chain Monte Carlo algorithm to produce large libraries of forward Grad–Shafranov solutions without the need for user intervention. The algorithm promotes equilibria with desirable properties, while avoiding parameter combinations resulting in problematic profiles or numerical issues in the integration of the GS equation.
On the instability of particle-laden flows in channels with porous walls
Authors: Mirbod P. , Hooshyar S. , Taheri E. , Yoshikawa H. N.
Published: April 2024

We investigate the stability of flows with low particle volume fractions in channels featuring porous walls. The particles, which are neutrally buoyant, interact with the carrier fluid through the Stokes drag force. Our study explores stability concerning particle relaxation time and mass fraction, employing different porous walls with varying permeabilities while maintaining a fixed porosity of 0.6. Our results reveal that in highly permeable porous walls, flow stability is mainly governed by the porous structure. The particle volume fraction and relaxation time exert relatively minor destabilizing and stabilizing effects, respectively. However, as porous wall permeability decreases, flow behavior becomes more sensitive to the particle volume fraction. In such cases, higher particle volume fractions and longer relaxation times contribute to stabilization. This suggests that particles and porous walls can effectively control flow, either maintaining laminar flow or inducing a transition to turbulence. We also analyze the impact of the momentum transfer coefficient at the porous surface, τ, on flow stability. Finally, we compare marginal stability curves obtained for various commonly used porous materials to conclude our study.
Autonomous navigation of smart microswimmers in non-uniform flow fields
Authors: Sankaewtong Krongtum , Molina John J. , Yamamoto Ryoichi
Published: April 2024

We employ a combination of direct numerical simulations and deep reinforcement learning to investigate the autonomous navigation capabilities of smart microswimmers in nonuniform flow conditions, specifically with an applied zig-zag shear flow. The smart microswimmers are equipped with sensors on their body surface to perceive local hydrodynamic signals, i.e., surface stresses, and have the capability of performing torque-free rotation of the propelling axis, such that by mimicking the ciliary beating around their bodies, which is represented by the azimuthal velocity term C1 in the squirmer model. By focusing on a puller-type swimmer, we explore its performance in three distinct navigation tasks: swimming in the flow (1), shear-gradient (2), and vorticity (3) directions. We first investigate the impact of the C1 mode on swimming performance in steady zig-zag shear flow. We then explore the influence of oscillatory shear flow and its convergence to the non-shear flow navigation as the applied frequency increases. Additionally, we extend our methodology to investigate the collective swimming behavior of multiple swimmers in the shear-gradient direction, revealing their ability to swim collectively in a sinusoidal pattern. Finally, we apply our approach to introduce collective behaviors in bulk multi-swimmer dispersions, targeting regimes previously predicted to exhibit non-cohesive behavior.
Melting point of iron at high pressure: An assessment of uncertainties and effect of electronic temperature
Authors: Zhao Liming , Lordi Vincenzo , Samanta Amit
Published: April 2024

An accurate calculation of the melting point of iron at various pressures in the Earth's core is important for understanding the core structure, geodynamo, and the Earth's history. Previous studies have assessed the melt line of iron at these extreme conditions using various experimental measurement techniques as well as both ab initio and classic molecular dynamics simulations. However, experimental measurements have uncertainties up to several hundred Kelvin, and inconsistencies remain among simulation results. In this work, we propose an iterative framework that couples density functional theory (DFT) calculations and molecular dynamics simulations performed using an ensemble of interatomic potentials to assess the effect of electronic temperature on the melting point. We systematically validate the potentials by comparing lattice constants and phonon dispersion curves at 0 K and enthalpy differences between liquid and HCP, FCC, BCC phases of iron close to the melt line at 300 GPa with DFT. Our results show that HCP iron melts at 6144 K (at 300 GPa), BCC phase is thermodynamically unstable, and FCC is metastable at this temperature. The melting points of FCC and BCC phases at 300 GPa are 5858 and 5647 K, respectively.
Study of the in situ test setup and analysis methods for self-healing properties of metallized film capacitors
Authors: Zhou Shaopeng , Chen Deping , Du Baoyu , Wang Pan , Wang Xiucai , Zhu Wenbo , Liu Si , Xiao Peng , Chen Jianwen
Published: April 2024

Metallized film capacitors (MFCs) are widely used in the power electronics industry due to their unique self-healing (SH) capability. SH performance is an essential assessment for MFC reliability verification in industrial production. The SH phenomenon of metallized films usually occurs rapidly in a very short period, and its real-time evolution details are often difficult to capture and analyze. In this paper, a test system for the SH performance of metallized films for capacitors was constructed. The system consists of three components: a voltage–current characteristic testing and current pulse capture device, a microscopic image real-time acquisition device, and an integrated analysis processing device. Through the voltage–current characteristic testing and current pulse capture device, the electrical parameters of the SH point, such as SH times, breakdown field strength, SH current, and SH energy, are obtained; through a microscopic image real-time acquisition device, the real-time spatial positioning of the SH point was obtained, and the interconnection between the morphology of the SH point and the electrical properties was established. The relationship between the SH point and the temperature distribution was further established using thermal imaging technology, which lays the foundation for a thorough and timely assessment and analysis of the failure mechanism and the real-time evolution of the metallized film SH process. This significantly improves the effectiveness of SH property research.
Intermittent flow influences plant root growth: A phytofluidics approach
Authors: Padhi Prasenjeet , Mehta Sumit Kumar , Agarwal Kaushal , Mondal Pranab Kumar
Published: April 2024

The challenges of food security are exacerbated by the world's expanding population and diminishing agricultural land. In response, hydroponic cultivation offers a potentially more sustainable approach to growing nutrient-dense crops compared to traditional methods. Motivated by this understanding, we conducted a series of experiments to explore the behavior of Brassica juncea (Pusa Jaikisan) plant roots under various flow configurations within a controlled environment. The flow configurations considered were no-flow/flow (NF/F), continuous flow, flow/no-flow (F/NF), and stagnation. Additionally, we conducted anatomical sectioning of plant roots to study how different flow configurations affect the cellular structure of the plant root cross section. We also performed numerical simulations to investigate the internal stress generated within plant roots under various flow conditions. We observed that an increased number of cortical cells developed in response to higher internal stress in the case of continuous flow, which protected the inner vascular bundle from excessive biological stress. Comparing the designs, we found that continuous flow resulted in a longer root length compared to the F/NF and NF/F configurations. The root length per unit average flow power was highest for the 2 h F/NF case, followed by the 2 h NF/F, 3 h F/NF, and continuous flow cases. This suggests that periodic flow conditions (F/NF and NF/F) with lower average power, a necessary requirement for economical use, led to longer root lengths. Furthermore, we observed that the nitrogen uptake per unit average flow power was higher for the F/NF configuration compared to continuous flow. Consequently, we infer that in hydroponic cultivation, altering the flow configuration to a F/NF type could be more cost-effective with less nutrient solution wastage, promoting better plant root growth compared to a continuous flow scenario.
Biophysical and biochemical aspects of immune cell–tumor microenvironment interactions
Authors: Benmelech Shoham , Le Thien , McKay Maggie , Nam Jungmin , Subramaniam Krupakar , Tellez Daniela , Vlasak Grace , Mak Michael
Published: April 2024

The tumor microenvironment (TME), composed of and influenced by a heterogeneous set of cancer cells and an extracellular matrix, plays a crucial role in cancer progression. The biophysical aspects of the TME (namely, its architecture and mechanics) regulate interactions and spatial distributions of cancer cells and immune cells. In this review, we discuss the factors of the TME—notably, the extracellular matrix, as well as tumor and stromal cells—that contribute to a pro-tumor, immunosuppressive response. We then discuss the ways in which cells of the innate and adaptive immune systems respond to tumors from both biochemical and biophysical perspectives, with increased focus on CD8+ and CD4+ T cells. Building upon this information, we turn to immune-based antitumor interventions—specifically, recent biophysical breakthroughs aimed at improving CAR-T cell therapy.
Shale permeability and microstructural alternation during CO2 pre-fracturing: A mechanistic study
Authors: Tang Weiyu , Zheng Xiaoyu , Liu Cheng , Zhou Fujian , Liu Xiongfei , Zhou Hang , Wang Bo , Wang Xiukun , Hou Xiaoyu
Published: April 2024

CO2 pre-fracturing technology represents a novel approach to CO2 fracturing, effectively enhancing carbon capture efficiency in shale reservoirs while increasing the recovery of hydrocarbon resources. This study systematically quantifies the impact of water injection on the pore structure and permeability of shale samples saturated with pre-injected CO2. Based on X-ray diffraction (XRD) and low-temperature nitrogen adsorption (LT-NA) results, the dominant mechanism of the swelling-chemical coupling effect in shale property is clarified. Pre-injected CO2 can effectively mitigate the impact of water absorption. After a reaction time of 7 days, the permeability of the CO2-involved hydrated shale samples is four times that of samples without CO2. Nevertheless, the influence of subsequently injected water on shale permeability persists, resulting in an 80% reduction in shale permeability. XRD and LT-NA results indicate that the swelling-chemical coupling effect is the dominant factor in shale property variation during CO2 pre-fracturing. In the initial stage, the decline in calcite and clay mineral content is significant, and chemical dissolution dominates the change in pore structure. As the reaction progresses, the intensity of chemical reactions weakens, and clay mineral swelling becomes the primary factor affecting the shale properties. In this stage, K+ generated from original minerals effectively inhibits clay mineral swelling. Therefore, the swelling-chemical coupling effects should be comprehensively considered during the CO2 pre-fracturing process, and an appropriate soaking time should be selected to maximize CO2 storage efficiency and oil and gas production.
Identifying the charge states of carbon vacancies in 4H-SiC by ab initio metadynamics
Authors: Huang Yuanchao , Jiang Xuanyu , Deng Tianqi , Yang Deren , Pi Xiaodong
Published: April 2024

4H Silicon carbide (4H-SiC) is widely recognized as a highly promising material for high-voltage and high-power electronic applications due to its exceptional properties. The performance of devices based on 4H-SiC is often weakened by the presence of carbon-related point defects, particularly carbon vacancies (VC). The defects of VC introduce deep-level traps (e.g., Z1/2 and EH6/7) that deteriorate device functionality. Experimental and theoretical studies on VC have led to some conflicting results about the charge states of VC, especially for the charge state ordering of EH6/7. We now employ ab initio metadynamics (META) to systematically investigate configuration space including the direction and magnitude of bond distortion and identify the most stable structures of VC. Eventually, the charge states of VC in 4H-SiC are identified. The Z1 (EH6) and Z2 (EH7) indicate transitions from acceptor (donor) levels of VC, located on the h and k sublattice sites, respectively. Z1 and Z2 demonstrate negative-U ordering, characterized by U values of −0.16 and −0.37 eV, respectively. Conversely, EH6 and EH7 display positive-U ordering, with U values of 0.16 and 0.08 eV, respectively. The current results provide insights into the properties of VC in 4H-SiC, highlighting the effectiveness of META in the exploration of complex potential energy surfaces associated with point defects in solids.
Robust pressure prediction of oil and gas pipeline networks based on equipment embedding neural network
Authors: Jiang Wei-xin , Li Zong-ze , Yuan Qing , Gong Jun-hua , Yu Bo
Published: April 2024

Currently, extensive pipeline networks are developed in response to the demands of the oil and gas industry. The accurate estimation of the hydraulic condition of pipeline networks holds significant importance in the fields of pipeline design and safety management. Nevertheless, predicting the pressure of oil and gas pipeline networks with different equipment and structures remains challenging. To meet this challenge, a novel pressure prediction model for the oil and gas pipeline networks based on the equipment embedding neural network (EENN) is proposed in this study. The proposed model embeds different equipment models into the neural network model. The neural network in this model is used to focus on learning the connection characteristics of the pipeline network to achieve higher prediction accuracy. The present study first explores different embedding combinations of the EENN model to estimate the pressure in an oil pipeline network system that involves a non-isothermal batch transportation process. Then, the trained model is applied to predict the pressure in a gas pipeline network. The optimal EENN exhibits an average prediction error of 18.5% for oil pipelines and 0.36% for gas pipelines, which is lower than 20.8% and 3.57% under the neural network. The findings of this study demonstrate the efficacy of the proposed EENN in accurately forecasting pressures in diverse oil and gas pipeline networks by reducing the complexity of the learning process.
Temperature field of non-Oberbeck–Boussinesq Rayleigh–Bénard convection in a low aspect ratio cell
Authors: Kashanj Sina , Nobes David S.
Published: April 2024

A time-resolved experimental investigation was undertaken on the temperature evolution of Rayleigh–Bénard convection (RBC) in a slender convection cell with aspect ratio of Γ=0.1. Experiments were conducted for Rayleigh numbers of Ra=5.3×107, 7.6×107, and 9.5×107 and Prandtl number of Pr≈6 within the non-Oberbeck–Boussinesq (NOB) condition with a temperature difference variation in the range of 30 °C≤ΔT≤40 °C. Measurement of the temperature was by applying time-resolved two-color planar laser-induced fluorescence over the initial 2400 s. Experimental observations showed that the lateral confinement of the convection cell leads to the development of a single large-scale thermal plume instead of multiple plumes. Results showed that contrary to expectations, lateral confinement was found to be ineffective in suppressing temperature oscillations near thermal boundaries. Results also indicated that for Ra=5.3×107, 7.6×107, the temperature oscillations had a frequency of f≈0.028 Hz similar to the frequency of the oscillations in Oberbeck–Boussinesq (OB) RBC. For Ra=9.5×107, however, it was found that the frequency of the oscillations was much lower than the OB RBC with a relatively wide range of the oscillations in the vicinity of f≈0.006 Hz. It is also found that the lateral confinement and formation of singular high-energy thermal plumes leads to an increase in the nonsymmetrical temperature distribution of NOB RBC with a bimodal distribution of the temperature field, deviating significantly from the Gaussian distribution temperature field found in OB RBC.
Three-dimensional reconstruction of x-ray emission volumes in magnetized liner inertial fusion from sparse projection data using a learned basis
Authors: Fein Jeffrey R. , Harding Eric C. , Lewis William E. , Weis Matthew R. , Schaeuble Marc-Andre
Published: April 2024

The ability to visualize x-ray and neutron emission from fusion plasmas in 3D is critical to understand the origin of the complex shapes of the plasmas in experiments. Unfortunately, this remains challenging in experiments that study a fusion concept known as Magnetized Liner Inertial Fusion (MagLIF) due to a small number of available diagnostic views. Here, we present a basis function-expansion approach to reconstruct MagLIF stagnation plasmas from a sparse set of x-ray emission images. A set of natural basis functions is “learned” from training volumes containing quasi-helical structures whose projections are qualitatively similar to those observed in experimental images. Tests on several known volumes demonstrate that the learned basis outperforms both a cylindrical harmonic basis and a simple voxel basis with additional regularization, according to several metrics. Two-view reconstructions with the learned basis can estimate emission volumes to within 11% and those with three views recover morphology to a high degree of accuracy. The technique is applied to experimental data, producing the first 3D reconstruction of a MagLIF stagnation column from multiple views, providing additional indications of liner instabilities imprinting onto the emitting plasma.
Artificial neural network-substituted transition model for crossflow instability: Modeling strategy and application prospect
Authors: Wu Lei , Cui Bing , Wang Rui , Xiao Zuoli
Published: April 2024

Data-driven approaches have made preliminary inroads into the area of transition–turbulence modeling, but are still in their infancy with regard to widespread industrial adoption. This paper establishes an artificial neural network (ANN)-based transition model to enhance the capacity of capturing the crossflow (CF) transition phenomena, which are frequently identified over a wide range of aerodynamic problems. By taking a new CF-extended shear stress transport (SST) transition-predictive (SST-γ) model as the baseline, a mapping from mean flow variables to transition intermittency factor (γ) is constructed by ANN algorithm at various Mach and Reynolds numbers of an infinite swept wing. Generalizability of the resulting ANN-based (SST-γANN) model is fully validated in the same infinite swept wing, an inclined 6:1 prolate spheroid, and a finite swept wing in extensive experiment regimes, together with two effective a priori analysis strategies. Furthermore, the calculation efficiency, grid dependence, and performance of the present model in non-typical transitional flow are also assessed to inspect its industrial feasibility, followed by the elucidation of rationality behind the preliminary success and transferability of present framework. The results manifest that the SST-γANN model aligns well with the benchmark SST-γ model, and both can capture the CF transition accurately compared with their experiment counterpart, completely breaking through the disability of original SST-γ model without CF correction. In addition, good properties of efficiency, robustness, and generalizability are achieved for the ANN-alternative transition model, together with the usability of present framework across various transitional flows.
Features of phonon scattering by a spherical pore: Molecular dynamics insight
Authors: Isaiev Mykola , Kyrychenko Nataliia , Kuryliuk Vasyl , Lacroix David
Published: April 2024

There is still a gap in understanding phonon scattering by geometrical defects at the nanoscale, and it remains a significant challenge for heat transfer management in nanoscale devices and systems. In this study, we aim to explore the characteristics of phonon scattering by a single pore to gain insights into thermal transport in nanostructures. The paper outlines a methodology for assessing the spatial distribution of the magnitude of the radial, azimuthal, and polar components of the velocity of scattered phonons by a spherical pore. We demonstrated that the size parameter, commonly employed in electromagnetic wave scattering theory, is vital in determining the scattering regime. Specifically, we show that the calculated scattering efficiency has the same pattern as that commonly obtained in classical wave scattering theory. However, we found that crystallographic directions are pivotal in shaping the scattering patterns, especially in the regions where scattering patterns are defined by the Mie resonances. This observation holds significance in understanding the influence of phonon coherence on thermal transport in nanostructured materials.
The effect of viscosity on the self-similar growth of conic cusps on the surface of a conducting liquid in an electric field: Limiting cone angle
Authors: Zubarev N. M.
Published: April 2024

The dynamics of the formation of conic cusps on an initially smooth surface of a perfectly conducting liquid (liquid metal) in an external electric field is analytically studied. When the singularity is formed, the apex curvature radius of the accelerating protrusion, local electric field strength, and fluid velocity become infinite in a finite time. It has been demonstrated that two scales with different types of fluid behavior can be distinguished in this process. At the nanoscale (the curvature radius of the conic apex is tens of nanometers or less; the electric field strength at the apex is about 108 V/cm and higher), viscous effects play a decisive role, and a cone with the limiting opening angle of 33.1° is formed. On the macroscopic scale (the local field strength is less than 108 V/cm for liquid metals), the ideal fluid approximation is applicable, and a cone of the opening angle 98.6° (Taylor's angle) develops. In both cases, self-similar fluid flow regimes are realized, for which the spatial scale decreases with time following the power law (t0 – t)2/3, where t0 is the blowup time. In this process, the Weber number remains practically unchanged and, according to our estimates, approximately equal to 102; at the same time, the Reynolds number decreases as (t0 – t)1/3.