bluuebunny/crossref_metadata_2025 huggingface dataset:
Does counting change what counts? Quantification fixation biases decision-making
Authors: Chang Linda W. , Kirgios Erika L. , Mullainathan Sendhil , Milkman Katherine L.
Published: October 2024

People often rely on numeric metrics to make decisions and form judgments. Numbers can be difficult to process, leading to their underutilization, but they are also uniquely suited to making comparisons. Do people decide differently when some dimensions of a choice are quantified and others are not? We explore this question across 21 preregistered experiments (8 in the main text, N = 9,303; 13 in supplement, N = 13,936) involving managerial, policy, and consumer decisions. Participants face choices that involve tradeoffs (e.g., choosing between employees, one of whom has a higher likelihood of advancement but lower likelihood of retention), and we randomize which dimension of each tradeoff is presented numerically and which is presented qualitatively (using verbal estimates, discrete visualizations, or continuous visualizations). We show that people systematically shift their preferences toward options that dominate on tradeoff dimensions conveyed numerically—a pattern we dub “quantification fixation.” Further, we show that quantification fixation has financial consequences—it emerges in incentive-compatible hiring tasks and in charitable donation decisions. We identify one key mechanism that underlies quantification fixation and moderates its strength: When making comparative judgments, which are essential to tradeoff decisions, numeric information is more fluent than non-numeric information. Our findings suggest that when we count, we change what counts.
Carbon-centric dynamics of Earth’s marine phytoplankton
Authors: Stoer Adam C. , Fennel Katja
Published: October 2024

Marine phytoplankton are fundamental to Earth’s ecology and biogeochemistry. Our understanding of the large-scale dynamics of phytoplankton biomass has greatly benefited from, and is largely based on, satellite ocean color observations from which chlorophyll-a (Chla), a commonly used proxy for carbon biomass, can be estimated. However, ocean color satellites only measure a small portion of the surface ocean, meaning that subsurface phytoplankton biomass is not directly monitored. Chla is also an imperfect proxy for carbon biomass because cellular physiology drives large variations in their ratio. The global network of Biogeochemical (BGC)-Argo floats now makes it possible to complement satellite observations by addressing both these issues at once. In our study, we use ~100,000 water-column profiles from BGC-Argo to describe Earth’s phytoplankton carbon biomass and its spatiotemporal variability. We estimate the global stock of open ocean phytoplankton biomass at ~314 Tg C, half of which is present at depths not accessible through satellite detection. We also compare the seasonal cycles of carbon biomass stocks and surface Chla visible from space and find that surface Chla does not accurately identify the timing of the peak annual biomass in two-thirds of the ocean. Our study is a demonstration of global-scale, depth-resolved monitoring of Earth’s phytoplankton, which will be crucial for understanding future climate-related changes and the effects of geoengineering interventions if implemented.
Distributed feather-inspired flow control mitigates stall and expands flight envelope
Authors: Sedky Girguis , Simon Nathaniel , Othman Ahmed K. , Wiswell Hannah , Wissa Aimy
Published: October 2024

Multiple rows of feathers, known as the covert feathers, contour the upper and lower surfaces of bird wings. These feathers have been observed to deploy passively during high angle of attack maneuvers and are suggested to play an aerodynamic role. However, there have been limited attempts to capture their underlying flow physics or assess the function of multiple covert rows. Here, we first identify two flow control mechanisms associated with a single covert-inspired flap and their location sensitivity: a pressure dam mechanism and a previously unidentified shear layer interaction mechanism. We then investigate the additivity of these mechanisms by deploying multiple rows of flaps. We find that aerodynamic benefits conferred by the shear layer interaction are additive, whereas benefits conferred by the pressure dam effect are not. Nevertheless, both mechanisms can be exploited simultaneously to maximize aerodynamic benefits and mitigate stall. In addition to wind tunnel experiments, we implement multiple rows of covert-inspired flaps on a bird-scale remote-controlled aircraft. Flight tests reveal passive deployment trends similar to those observed in bird flight and comparable aerodynamic benefits to wind tunnel experiments. These results indicate that we can enhance aircraft controllability using covert-inspired flaps and form insights into the aerodynamic role of covert feathers in avian flight.
Perturbation-specific transcriptional mapping for unbiased target elucidation of antibiotics
Authors: Romano Keith P. , Bagnall Josephine , Warrier Thulasi , Sullivan Jaryd , Ferrara Kristina , Orzechowski Marek , Nguyen Phuong H. , Raines Kyra , Livny Jonathan , Shoresh Noam , Hung Deborah T.
Published: October 2024

The rising prevalence of antibiotic resistance threatens human health. While more sophisticated strategies for antibiotic discovery are being developed, target elucidation of new chemical entities remains challenging. In the postgenomic era, expression profiling can play an important role in mechanism-of-action (MOA) prediction by reporting on the cellular response to perturbation. However, the broad application of transcriptomics has yet to fulfill its promise of transforming target elucidation due to challenges in identifying the most relevant, direct responses to target inhibition. We developed an unbiased strategy for MOA prediction, called perturbation-specific transcriptional mapping (PerSpecTM), in which large-throughput expression profiling of wild-type or hypomorphic mutants, depleted for essential targets, enables a computational strategy to address this challenge. We applied PerSpecTM to perform reference-based MOA prediction based on the principle that similar perturbations, whether chemical or genetic, will elicit similar transcriptional responses. Using this approach, we elucidated the MOAs of three molecules with activity against
Pseudomonas aeruginosa
by comparing their expression profiles to those of a reference set of antimicrobial compounds with known MOAs. We also show that transcriptional responses to small-molecule inhibition resemble those resulting from genetic depletion of essential targets by clustered regularly interspaced short palindromic repeats interference (CRISPRi) by PerSpecTM, demonstrating proof of concept that correlations between expression profiles of small-molecule and genetic perturbations can facilitate MOA prediction when no chemical entities exist to serve as a reference. Empowered by PerSpecTM, this work lays the foundation for an unbiased, readily scalable, systematic reference-based strategy for MOA elucidation that could transform antibiotic discovery efforts.
Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade
Authors: Arulraj Theinmozhi , Wang Hanwen , Deshpande Atul , Varadhan Ravi , Emens Leisha A. , Jaffee Elizabeth M. , Fertig Elana J. , Santa-Maria Cesar A. , Popel Aleksander S.
Published: October 2024

Patients with metastatic triple-negative breast cancer (TNBC) show variable responses to PD-1 inhibition. Efficient patient selection by predictive biomarkers would be desirable but is hindered by the limited performance of existing biomarkers. Here, we leveraged in silico patient cohorts generated using a quantitative systems pharmacology model of metastatic TNBC, informed by transcriptomic and clinical data, to explore potential ways to improve patient selection. We evaluated and quantified the performance of 90 biomarker candidates, including various cellular and molecular species, at different cutoffs by a cutoff-based biomarker testing algorithm combined with machine learning–based feature selection. Combinations of pretreatment biomarkers improved the specificity compared to single biomarkers at the cost of reduced sensitivity. On the other hand, early on-treatment biomarkers, such as the relative change in tumor diameter from baseline measured at two weeks after treatment initiation, achieved remarkably higher sensitivity and specificity. Further, blood-based biomarkers had a comparable ability to tumor- or lymph node–based biomarkers in identifying a subset of responders, potentially suggesting a less invasive way for patient selection.
Observed carbon decoupling of subnational production insufficient for net-zero goal by 2050
Authors: Zioga Maria , Kotz Maximilian , Levermann Anders
Published: October 2024

Historically, economic growth has been closely coupled to carbon emissions responsible for climate change, but to stabilize global mean temperature, net-zero carbon emissions are necessary. Some economies have begun to reduce emissions while continuing to grow, but this decoupling is not fast enough to achieve global climate targets. Subnational climate actions seem to be crucial for the achievement of these targets. Here, we uncover the effectiveness of subnational efforts by estimating decoupling rates and CO2 emission intensities over the last three decades for over 1,500 subnational regions, encompassing 85% of global emissions, using global data on reported economic output and gridded production-based emissions. Thirty percent of regions with available data have fully decoupled, with higher-income and historically carbon-intensive regions exhibiting higher rates of decoupling and declining emission intensity. Countries of the Organization for Economic Co-operation and Development with greater spending on subnational climate actions show higher decoupling rates, as do subnational regions in EU countries where climate policies have been implemented, highlighting the effectiveness of subnational policies. Moreover, subnational analysis reveals greater variance of decoupling rates within national boundaries than between them and that countries with weaker governance typically show higher variance of decoupling within their borders. If recent rates of production-based carbon decoupling continue, less than half of subnational regions would reach net-zero before 2050, even when accounting for observed acceleration via socioeconomic development and assuming no interregional carbon leakage.
Evidence from bare verbs for the future versus non-future split in Creoles
Authors: Prescod Paula
Published: October 2024

Vincentian Creole makes a future/non-future temporal distinction on the basis of the categorisation proposed in
several studies, according to which languages combining present and future make a past/non-past distinction and those using the
same form for past and present make a future/non-future tense opposition. In Vincentian Creole examples of absolute tense,
underspecified (or unmarked) predicates do not generally obtain a future interpretation: only readings in the past tense (for
dynamic predicates) or the present (for non-dynamic predicates) are available. Thus, predicates in the future tense are
unambiguous regardless of the lexical aspect of these predicates, unlike the context of past and present tense interpretations
which I explored in my previous column. Evidence from other English-related creoles supports this claim.
Biodiversity and plant-insect interactions in fragmented habitats: A systematic review
Authors: Ojija Fredrick
Published: October 2024

Fragmentation is threatening insect biodiversity and intricate interactions in various ecosystems. Ecological interactions – especially those involving plants and insects – are significantly impacted by fragmented habitats. Because of fragmentation, edge effects and reduced habitat connectivity and quality affect insect species diversity, abundance, behavior, movement, life cycles, and interactions with plants, e.g., pollination, herbivory, and seed distribution. To a large degree, ecosystem services or processes are mediated by these interactions. While fragmented habitats create suitable conditions for invasive alien plants (IAPs), such invasions modify native plant composition and herbivorous insect communities because they cause a decline or loss in insect biodiversity. A systematic review was conducted by reviewing eighty-eight (88) articles to gather evidence for fragmentation effects on insect biodiversity, insects’ behavior and adaptations, plant-insect interactions (i.e., pollination, herbivory, and seed dispersal), and its influence on IAP invasions. This review deduced that any change in insect community composition and diversity due to fragmentation can have cascading effects on ecosystem processes within habitats. It further contends that successful conservation and management of fragmented habitats requires an understanding of the intricate dynamics of plant-insect interactions. However, the long-term resilience and health of ecosystems can be guaranteed by supporting sustainable land use, improving connectivity, and restoring habitats. These actions may help stop and/or reduce the effects of fragmentation on insect biodiversity and support the livelihoods and well-being of millions of people.
Footprints of innate immune activity during HIV-1 reservoir cell evolution in early-treated infection
Authors: Sun Weiwei , Gao Ce , Gladkov Gregory Takashi , Roseto Isabelle , Carrere Leah , Parsons Elizabeth M. , Gasca-Capote Carmen , Frater John , Fidler Sarah , Yu Xu G. , Lichterfeld Mathias ,   the RIVER Trial Study Group, Sandström Eric , Darbyshire Janet , Post Frank , Conlon Christopher , Anderson Jane , Maini Mala , Peto Timothy , Sasieni Peter , Miller Veronica , Weller Ian , Fidler Sarah , Frater John , Babiker Abdel , Stöhr Wolfgang , Pett Sarah , Dorrell Lucy , Pace Matthew , Olejniczak Natalia , Brown Helen , Robinson Nicola , Kopycinski Jakub , Yang Hongbing , Hanke Tomáš , Crook Alison , Kaye Stephen , McClure Myra , Erlwein Otto , Lovell Andrew , Khan Maryam , Gabriel Michelle , Bennett Rachel , Sy Aminata , Gregory Andrew , Hudson Fleur , Russell Charlotte , Wood Gemma , Box Hanna , Kingsley Cherry , Topping Katie , Lever Andrew , Wills Mark , Fun Alex , Bandara Mikaila , Kelly Damian , Collins Simon , Markham Alex , Rauchenberger Mary , Sowunmi Yinka , Shidfar Shaadi , Hague Dominic , Fidler Sarah , Pett Sarah , Nelson Mark , Cerrone Maddalena , Castrillo Martinez Nadia , Barber Tristan , Schoolmeesters Alexandra , Weaver Christine , Thunder Orla , Rowlands Jane , Higgs Christopher , Fedele Serge , Bracchi Margherita , Thomas Lervina , Bourke Peter , Nwokolo Nneka , Lawrenson Gaynor , Fiorino Marzia , Lukha Hinal , Kinloch Sabine , Johnson Margaret , Nightingale Alice , Ngwu Nnenna , Byrne Patrick , Cuthbertson Zoe , Jones Martin , Fernandez Tina , Clarke Aamanda , Fisher M. , Gleig Rebecca , Trevitt Vittorio , Fitzpatrick Colin , Adams Tanya , Finnerty Fiounnouala , Thornhill John , Lewis Heather , Kuldanek Kristin , Fox Julie , Lwanga Julianne , Uzu Hiromi , Lee Ming , Merle Simon , O’Rourke Patrick , Jendrulek Isabel , ZarkoFlynn Taras , Taylor Mark , Tiraboschi Juan Manuel , Murray Tammy
Published: October 2024

Antiretroviral treatment (ART) initiation during the early stages of HIV-1 infection is associated with a higher probability of maintaining drug-free viral control during subsequent treatment interruptions, for reasons that remain unclear. Using samples from a randomized-controlled human clinical trial evaluating therapeutic HIV-1 vaccines, we here show that early ART commencement is frequently associated with accelerated and efficient selection of genome-intact HIV-1 proviruses in repressive chromatin locations during the first year after treatment initiation. This selection process was unaffected by vaccine-induced HIV-1-specific T cell responses. Single-cell proteogenomic profiling demonstrated that cells harboring intact HIV-1 displayed a discrete phenotypic signature of immune selection by innate immune responses, characterized by a slight but significant upregulation of HLA-C, HLA-G, the IL-10 receptor, and other markers involved in innate immune regulation. Together, these results suggest an accelerated immune selection of viral reservoir cells during early-treated HIV-1 infection that seems at least partially driven by innate immune responses.
Bridging external and attenuated total reflection infrared spectroscopies through computational simulations
Authors: Vieira L G
Published: October 2024

This work provides an integrated view of attenuated total reflection (ATR) and external reflection (ER) for advanced undergraduate and postgraduate students beginning their study of infrared spectroscopy. The theoretical framework of reflectance is reviewed, and a computational tool developed using GNU Octave is presented to model ER and ATR spectra. Simulating spectra demonstrates how ER spectra evolve to ATR spectra by modifying relevant parameters. This unified approach offers advanced students a deeper understanding of infrared spectroscopy, enhancing their ability to correctly interpret ATR spectra and avoid common pitfalls. The computational exercises and provided code serve as valuable educational resources for exploring reflectance behaviour under different conditions.
A VOx-based optoelectronic memristor for application in visual perception
Authors: Pal Pratibha , Kumbhar Dhananjay D , Li Hanrui , Tytov Serhii , Syed Abdul Momin , El-Atab Nazek
Published: October 2024

While biological vision systems excel at in-memory processing with low power consumption, traditional silicon-based vision chips struggle with high energy demands. This gap motivates the exploration of alternative materials for artificial intelligence applications. This paper presents a VOx-based optoelectronic synaptic memristive device. The proposed artificial synaptic device ITO/VO
x
/Pt mimics biological functions such as potentiation (P), depression (D), long-term memory, short-term memory (STM), and paired-pulse facilitation (PPF). The PPF index, standing at 105%, suggests a favorable pattern in STM function. The device served as synapses within a spiking neural network showing an achievable pattern classification accuracy of 88.68%, highlighting the potential of the VO
x
synaptic device for pattern classification tasks. The suggested VO
x
-based synaptic devices could represent an efficient pattern recognition and visual perception application.
Control of coherent phonon dynamics in CoFeB/heavy metal heterojunction structures for future hybrid phononic and spintronic devices
Authors: Fang Ning , Wang Lei , Harris Nico , Teklu Alem , Kuthirummal Narayanan , Brennan Christian , Kern Noah , McConnell Aeron , Sun Dali , Zhou Ziyao , Gong Yu
Published: October 2024

The heterojunction structure of CoFeB/heavy metal has shown significant potential for spintronics, where both electrons and magnons potentially can serve as information carriers. However, another promising information carrier, coherent phonons, has not been fully explored for hybrid phononic and spintronic devices. In this study, we used time-resolved pump–probe spectroscopy to investigate the dynamic behaviour of coherent phonons. We observed variations in reflectivity spectra, corresponding to changes in phonon frequency and relaxation times, with different thicknesses of the heavy metal and CoFeB layers. The experimental results demonstrated a decrease in coherent phonon oscillation frequency as the thickness of the CoFeB and heavy metal layers increased. These findings were further supported by first-principles calculations, which showed that the frequency of the optical modes is suppressed due to interface relaxation between the magnetic and heavy metal layers.
Insights into mixed dye pollutant degradation by oxygen and air plasma bubbling array
Authors: Huang Jun , Luo Qianqian , Liu Fang , Xiao Yujun , Wang Xingquan , Li Mengchao , Tan Menghao , Chen Wei
Published: October 2024

Synthetic organic dye pollutants pose a serious threat to the aquatic ecological environment due to their difficulty in complete degradation. This study employed a plasma bubble array reactor to degrade individual and mixed dye pollutant solutions of sunset yellow (SY), methyl orange (MO), and methyl violet (MV). The degradation efficiencies and mechanisms of the plasma were investigated under different working gas atmospheres. It was found that oxygen plasma degraded the target dyes and their mixtures more significantly than air plasma. Specifically, compared with air plasma, the removal of single dyes SY, MO and MV by oxygen plasma was increased by 76.6%, 13.8% and 3%, respectively, after 20 min of treatment. As for mixed dyes, after 25 min treatment, oxygen plasma removed 99.1%, which was 31.6% higher than air plasma. However, the degradation kinetic order in oxygen plasma was SY > MO > MV, while that in air plasma was MV > MO > SY. Combined with the detection of reactive oxygen–nitrogen species, the results showed that the reactive oxygen species (ROS) played an important role in the degradation of SY, and it was also important for the degradation of MO, whereas both the ROS and reactive nitrogen species were important for the degradation of MV. Scavenger experiments revealed that hydroxyl (·OH) and superoxide anion (·O2
−) played the most important roles in the degradation process. The three dyes were basically completely degraded within 14–20 min of treatment, with corresponding yields of 3.08–4.43 g kWh−1. Possible degradation pathways for each dye were deduced based on LC-MS and the toxicities of solutions were evaluated by phytotoxicity tests and ion chromatography. The results showed that the biotoxicity of the intermediates was significantly reduced. This study may provide a feasible option for effective application of plasma technology in organic dye wastewater treatment.
First-principles studies of strain-tunable InN monolayer: applications for switching and optoelectronic devices
Authors: Xu Zhong-Hui , Wang Zhenyu , Jiang Junlin , Wei Kaiyu , Liu Guogang , Ke San-Huang , Luo Bing
Published: October 2024

Two-dimensional (2D) materials are attracting significant attention for their potential applications in the post-Moore era. In this work, we systematically investigate the effect of strains on the electronic structure, transport and optoelectronic properties of 2D Indium nitride (InN) monolayer using density functional theory and non-equilibrium Green’s function methods. The results show that strains can modulate the electronic properties. Specifically, biaxial strain triggers the transition from semiconductor to metal and indirect to direct band gap. On this basis, the constructed InN-based nanodevice exhibits current switching ratios up to 1010. In addition, the optoelectronic device based on InN monolayer exhibits a robust photoelectric response in the red light. Meanwhile, biaxial strain can improve the optoelectronic performance of InN-based optoelectronic devices. The compressive strains blue-shift the photocurrent peaks of the InN monolayer, which effectively modulates its detection range in the visible light region. These findings underscore the potential applications in nanotechnology, particularly in nano-switches and optoelectronic devices.
Single- and dual-band high-order polarization rotating frequency selective surface
Authors: Xu Honghui , Zhou Dongfang , Liu Qikun , Wang Xian , Tang Min , Qian Hang
Published: October 2024

This work presents the design and development of dual- and single-band polarization rotating frequency selective surfaces (PR-FSSs) based on aperture-coupled patch multimode resonators. Initially, an open-loop slot is incorporated into the patch of a second-order resonator to design a dual-band second-order PR-FSS (DPR-FSS), which enables effective polarization rotation and frequency selection across two distinct passbands. Then, to develop a single-band fourth-order PR-FSS (SPR-FSS), we introduce a metallic via into the DPR-FSS. This modification results in a single-band fourth-order response. The SPR-FSS offers a bandwidth of 41% with minimal insertion loss and high roll-off characteristics. Finally, experiments are conducted to verify the performance of the proposed structures. Good agreement can be observed between simulation and measurement.
Decay characteristic of gas arc in C4F7N/N2 and C4F7N/CO2 gas mixture by Thomson scattering
Authors: Liu Tianxiao , Sun Hao , Li Gang , Zhang Yushi , Wang Jiru , Xiao Jianqiao , Lu Yang , Niu Chunping , Wu Yi
Published: October 2024

C4F7N/N2 and C4F7N/CO2 gas mixtures are considered potential alternative gases to SF6, and it is of particular significance to investigate the plasma decay process in these mixtures for evaluating their circuit breaker breaking performance. To comprehend the decay process of electron density(n
e) in arc plasma within C4F7N/N2 and C4F7N/CO2 gas mixtures, an arc-generating circuit and a Thomson scattering experiment platform were established. Through coherent Thomson scattering diagnosis of gas arc plasma under various gas mixture conditions, a series of electron density results over time and space were obtained. The findings suggest that the initial electron density of the arc plasma diminishes with an increase in the proportion of C4F7N, and electron density decay is further accelerated as the proportion of C4F7N increases. Moreover, it was observed that the electron density decay rate is higher in the C4F7N/N2 mixture compared to the C4F7N/CO2 mixture. Notably, the electron decay rate in a 50% C4F7N/N2 mixture closely resembles that observed in pure SF6.
The strong coupling constant: state of the art and the decade ahead
Authors: d’Enterria D , Kluth S , Zanderighi G , Ayala C , Benitez-Rathgeb M A , Blümlein J , Boito D , Brambilla N , Britzger D , Camarda S , Cooper-Sarkar A M , Cridge T , Cvetič G , d’Enterria D , Dalla Brida M , Deur A , Giuli F , Golterman M , Hoang A H , Huston J , Jamin M , Kluth S , Kotikov A V , Krivokhizhin V G , Kronfeld A S , Leino V , Lipka K , Mäkelä T , Malaescu B , Maltman K , Marzani S , Mateu V , Moch S , Monni P F , Nadolsky P , Nason P , Nesterenko A V , Pérez-Ramos R , Peris S , Petreczky P , Pich A , Rabbertz K , Ramos A , Reichelt D , Rodríguez-Sánchez A , Rojo J , Saragnese M , Sawyer L , Schott M , Schumann S , Shaikhatdenov B G , Sint S , Soyez G , Teca D , Vairo A , Vos M , Waits C , Weber J H , Wobisch M , Xie K , Zanderighi G
Published: October 2024

Theoretical predictions for particle production cross sections and decays at colliders rely heavily on perturbative Quantum Chromodynamics (QCD) calculations, expressed as an expansion in powers of the strong coupling constant α

S
. The current

O
(
1
%
)

uncertainty of the QCD coupling evaluated at the reference Z boson mass,

α

S

(

m

Z

2

)
=
0.1179
±
0.0009

, is one of the limiting factors to more precisely describe multiple processes at current and future colliders. A reduction of this uncertainty is thus a prerequisite to perform precision tests of the Standard Model as well as searches for new physics. This report provides a comprehensive summary of the state-of-the-art, challenges, and prospects in the experimental and theoretical study of the strong coupling. The current

α

S

(

m

Z

2

)

world average is derived from a combination of seven categories of observables: (i) lattice QCD, (ii) hadronic τ decays, (iii) deep-inelastic scattering and parton distribution functions fits, (iv) electroweak boson decays, hadronic final-states in (v) e+e−, (vi) e–p, and (vii) p–p collisions, and (viii) quarkonia decays and masses. We review the current status of each of these seven

α

S

(

m

Z

2

)

extraction methods, discuss novel α

S
determinations, and examine the averaging method used to obtain the world-average value. Each of the methods discussed provides a ‘wish list’ of experimental and theoretical developments required in order to achieve the goal of a per-mille precision on

α

S

(

m

Z

2

)

within the next decade.
Sensitivity of wavelet-based optical flow velocimetry (wOFV) to common experimental error sources
Authors: Schmidt Bryan E , Page Wayne E , Jassal Gauresh Raj , Sutton Jeffrey A
Published: October 2024

The influence of several potential error sources and non-ideal experimental effects on the accuracy of a wavelet-based optical flow velocimetry (wOFV) method when applied to tracer particle images is evaluated using data from a series of synthetic flows. Out-of-plane particle displacements, severe image noise, laser sheet thickness reduction, and image intensity non-uniformity are shown to decrease the accuracy of wOFV in a similar manner to correlation-based particle image velocimetry (PIV). For the error sources tested, wOFV displays a similar or slightly increased sensitivity compared to PIV, but the wOFV results are still more accurate than PIV when the magnitude of the non-ideal effects remain within expected experimental bounds. For the majority of test cases, the results are significantly improved by using image pre-processing filters and the magnitude of improvement is consistent between wOFV and PIV. Flow divergence does not appear to have an appreciable effect on the accuracy of wOFV velocity estimation, even though the underlying fluid transport equation on which wOFV is based implicitly assumes that the motion is divergence-free. This is a significant finding for the broader applicability of planar velocimetry measurements using wOFV. Finally, it is noted that the accuracy of wOFV is not reduced notably in regions of the image between tracer particles, as long as the overall seeding density is not too sparse i.e. below 0.02 particles per pixel. This explicitly demonstrates that wOFV (when applied to particle images) yields an accurate whole field measurement, and not only at or adjacent to the discrete particle locations.
Detecting GNSS spoofing and Re-localization on UAV based on imagery matching
Authors: Liu Ruihang , Liu Haiying , Meng Xiaolin , Li Tiexiang , Hancock Craig M
Published: October 2024

Due to rapid advancements in global navigation satellite system (GNSS), computer, and microelectronics technologies, there is a growing popularity and widespread promotion of high-performance, cost-effective intelligent UAVs across various applications. Recently, GNSS spoofing attacks have emerged as a significant obstacle hindering the long-term development of UAVs. UAVs rely heavily on unprotected GNSS signals for navigation, making them highly vulnerable to spoofing. This paper presents an algorithm that employs image matching for detecting GNSS spoofing and re-localization on UAVs using a deep learning methodology. This method functions autonomously solely reliance on camera and does not require alterations to the antenna configuration. Utilizing a camera-equipped UAV, we evaluate the likeness between real-time aerial photographs and satellite imagery by leveraging the position information provided by UAV. By identifying disparities between images taken by a spoofing affected drone and authentic ones, the spoofing can be identified using deep neural network models. Upon detecting spoofing, this paper presents a vision-based re-localization method for UAVs. Experimental results demonstrate an approximately 88.4% accuracy of our model in detecting GNSS spoofing attacks within 100 ms and 88% success rate of re-localization with the accuracy of less than 15 m. Our algorithm exclusively depends on publicly accessible satellite imagery, offering an intelligent and efficient approach for detecting UAV GNSS spoofing and re-localization in GNSS denied environment.
MODVORTEx: computer vision-driven automation for magnetic domain wall velocity analysis
Authors: Raj Rakhul , Reddy V Raghavendra
Published: October 2024

This paper presents Magneto Optic Domain Velocity Observation and Real-Time Extraction (MODVORTEx), a comprehensive software solution for automating domain wall (DW) velocity measurements in magnetic materials using magneto-optic Kerr effect microscopy. Building upon our previous work on bubble domain structures, we introduce a versatile graphical user interface (GUI) that accommodates arbitrary domain shapes and employs advanced computer vision techniques. The software provides different methods for DW detection and velocity calculation, catering to various domain structures of arbitrary shape. Our approach significantly reduces the time and effort required for data extraction, transforming a process that previously took days of manual work into a task completable within minutes. We provide the details of the algorithmic implementation which is organized into pre-processing, DW detection, displacement measurement, and velocity extraction. This tool is applicable to a wide range of scenarios, including bubble domain dynamics, Dzyaloshinskii–Moriya interaction studies in perpendicular magnetic anisotropy systems, current-driven DW motion in patterned strips etc. By providing both GUI and Application Programing Interface, our software offers flexibility for integration into existing measurement systems and adaptability for specific research needs. This automation promises to accelerate research in spintronics and magnetic materials, enabling more comprehensive and accurate studies of DW dynamics.
Synthesis mechanism of TiO2 nanoparticles via high frequency electrical arc discharge
Authors: Tavakolian Amir Hossein , Abdullah Amir , Hoshmand Moini Saleh
Published: October 2024

The rapid advancement of nanofabrication techniques has significantly increased the utilization of nanoparticles in recent years. This study investigates the synthesis of titanium dioxide (TiO2) nanoparticles, highlighting their unique properties and diverse applications across scientific and industrial fields. These nanoparticles are valued for their biocompatibility and advantageous optical, electrical, and physical properties. Various synthesis methods—chemical, physical, and biological—are reviewed, with a particular focus on the electric arc discharge method. This method is distinguished by its efficiency and environmental friendliness, enabling the production of highly pure nanoparticles. Utilizing continuous and alternating sparks between two electrodes, the technique generates spherical nanoparticles with adjustable sizes, controlled by the energy of each spark. An RC circuit-based device was designed for this electrical discharge process. Dynamic light scattering (DLS) measurements revealed an average particle size of 164.51 nm with a standard deviation of 44.08 nm. Field emission scanning electron microscopy (FESEM) images showed both solid and hollow spherical TiO2 nanoparticles. Energy dispersive spectroscopy (EDS) confirmed that the TiO2 particles contained only titanium and oxygen, with no other elements detected. X-ray diffraction (XRD) analysis verified the crystal structure, predominantly identifying the anatase phase of the synthesized nanoparticles. This research enhances the understanding of TiO2 nanoparticle synthesis and characterization, providing a foundation for future innovations in their extensive applications.
A plaintext-related and ciphertext feedback mechanism for medical image encryption based on a new one-dimensional chaotic system
Authors: Xu Jianwu , Liu Kun , Huang Qingye , Li Quanjun , Huang Linqing
Published: October 2024

In recent years, Plaintext-Related Image Encryption (PRIE) algorithms have been introduced, demonstrating a commendable level of plaintext sensitivity to resist chosen plaintext attack (CPA). However, these approaches suffer from several drawbacks, including inability to fully reconstruct the original image, limited practical value and excessive computational demands etc.. Moreover, the exponential expansion of medical data necessitates the formulation of more secure and efficient encryption algorithms. In this paper, firstly, a novel one-dimensional chaotic map, designated as 1D-SAM, which strikes an excellent balance between structural complexity and chaotic performance is proposed. The 1D-SAM achieve a larger chaotic range and an elevated Lyapunov exponent, signifying enhanced dynamical complexity. Subsequently, we devise a lightweight medical image encryption system leveraging the 1D-SAM and an innovative diffusion architecture, termed the plaintext-related and ciphertext feedback mechanism(PRCFM). This encryption system is a symmetric-key cryptosystem, eliminating the need for transmitting supplementary data beyond the secret keys to the recipient. Notably, the encrypted image maintains identical dimensions to its original counterpart and is fully recoverable. Complete simulation experiments were conducted on a personal computer equipped with MATLAB
R2021a, OS Windows 11, 2.60 GHz CPU and 16GB
RAM. The experimental results indicate that our encryption system, employing a single permutation-diffusion round, efficiently encrypts a 512 × 512 image in approximately 0.2854 seconds. Leveraging the advantages of the PRCFM, our approach demonstrates superior plaintext sensitivity, achieving an average number of pixels changing rate (NPCR) of 99.6051% and a unified average changed intensity (UACI) of 33.4452%. In summary, our work addresses key limitations of contemporary encryption frameworks, exhibiting acceptable performance in both encryption speed and security strength.
Construction and analysis of symmetric Sprott B multi-attractors with electric implementation
Authors: Doungmo Goufo Emile F
Published: October 2024

In chaos theory, a number of systems and models which apparently contain simple ordinary differential equations (ODEs) turn out to show a dynamic characterized by complicated behaviors and complex trajectories. One of such systems is the Sprott B model. We construct some set of multi-attractors based on the Sprott B model where additional parameters and operators are considered. After summarizing important preliminaries relevant to simple chaotic differential systems, the model is firstly solved analytically and numerically, then graphical simulations are provided. The later show coexistence and evolution of two chaotic attractors in a symmetrical representation. Lastly, similar results and expected outcomes are recovered via an electrical circuit implementation, realized using the Field Programmable Gate Array (FPGA) board, the Digital-to-Analog Converter (DAC) and the Rigol Oscilloscope. They also show progressing sets of coexisting multi-attractors.
Disassembling one-dimensional chains in molybdenum oxides
Authors: Du 杜 Xian 宪 , Li 李 Yidian 义典 , Zhao 赵 Wenxuan 文轩 , Xu 许 Runzhe 润哲 , Zhai 翟 Kaiyi 恺熠 , Chen 陈 Yulin 宇林 , Yang 杨 Lexian 乐仙
Published: October 2024

The dimensionality of quantum materials strongly affects their physical properties. Although many emergent phenomena, such as charge-density wave and Luttinger liquid behavior, are well understood in one-dimensional (1D) systems, the generalization to explore them in higher dimensional systems is still a challenging task. In this study, we aim to bridge this gap by systematically investigating the crystal and electronic structures of molybdenum-oxide family compounds, where the contexture of 1D chains facilitates rich emergent properties. While the quasi-1D chains in these materials share general similarities, such as the motifs made up of MoO6 octahedrons, they exhibit vast complexity and remarkable tunability. We disassemble the 1D chains in molybdenum oxides with different dimensions and construct effective models to excellently fit their low-energy electronic structures obtained by ab initio calculations. Furthermore, we discuss the implications of such chains on other physical properties of the materials and the practical significance of the effective models. Our work establishes the molybdenum oxides as simple and tunable model systems for studying and manipulating the dimensionality in quantum systems.
Experimental identification of ion cyclotron emission on HL-2A using YOLO neural network algorithm
Authors: Zhang Jiahao , Zhao Jun , Liu Linzi , Tong Ruihai , Zhong Wulyu , Luo Yi
Published: October 2024

Identification of magnetohydrodynamics (MHD) instabilities with neural networks has been extensively applied in the research of magnetically controlled fusion plasmas. Ion Cyclotron Emission (ICE) is a potential fast ion diagnostic method in burning plasmas. To assess ICE as a fast ion diagnostic for International Thermonuclear Experimental Reactor, real-time identification of ICE is required in the fast ion diagnostic flow. In the present work, we employed YOLO (You Only Look Once) to identify core and edge ICE in a large labeled database of HL-2A discharges, achieving a precision of 85.4% and a recall rate of 77.3%. Subsequent improvements to the YOLO model resulted in a noteworthy 8.3% increment in the recall rate. The developed identification method demonstrates significant potential for real-time application in identifying MHD instabilities.
Identification of Key Performance Metrics for Different Ultrasonic Surgical Devices
Authors: Zhang Yuli , Luo Xiaoning , Wu Wei , Zhang Qing , Xiong Shuanghui , Lin Sen , Zhou Pan , Xu Yang , Hu Min , Zhou Zhaoying
Published: October 2024

Ultrasonic surgical devices utilize high-frequency sound waves to perform surgical tasks, including cutting, fragmenting, emulsifying, and sealing tissues. Their multifunctional capabilities have facilitated their broad application across various surgical disciplines, such as general surgery, neurosurgery, and orthopedic surgery. While the current international standard, IEC 61847:1998 “Ultrasonics - Surgical Systems - Measurement and Declaration of the Basic Output Characteristics”, outlines a set of fundamental output characteristics for these devices, the diverse applications and performance requirements of each device necessitate the identification of key performance metrics. In this study, we delve into the applicability of these basic output characteristics for different ultrasonic surgical devices. Through comprehensive experimental evaluations on biological tissues, we assessed the influence of specific parameters, namely drive frequency, excursion amplitude, power output, duty cycle, and primary sound output area, on the cutting efficiency and coagulation results of three distinct ultrasonic surgical devices. Our results highlight the paramount parameters that govern the primary functions of these devices. This research offers invaluable insights for device manufacturers and evaluators, guiding them in prioritizing and emphasizing crucial parameters during the design, manufacturing, and evaluation phases of ultrasonic surgical devices.
Truncated Newton full waveform inversion method for the human brain imaging
Authors: Wu Faxuan , He Qinglong , Li Yang , Han Bo , Wang Yangfei
Published: October 2024

It has been shown that full-waveform inversion (FWI) method can be a competitive alternative for medical imaging problems. It offers high-resolution results while delivering the advantages of being fast, safe, portable, and affordable, compared to magnetic resonance imaging (MRI) and x-ray computed tomography. However, to the best of our knowledge, FWI applications in medical imaging only use the first-order derivative information. In this case, the high parameter contrasts between different tissues of human body and multi-scatterings problems may lead FWI to local minima. Thus, we present a competitive truncated Newton method for high-resolution imaging of the human brain. This truncated Newton method, based on the efficient linear solver MINRES-QLP, can make full use of multiple scattering wavefield information. Compared with the truncated Newton method based on conjugate gradient, the MINRES-QLP iterative method presents various advantages when solving linear systems, such as the capacity to handle both non-singular and singular systems, less computational cost, and efficiency even for ill-conditioned systems. Numerical experiments for imaging the brain with and without the skull are conducted. Numerical results indicate that, compared with the truncated Newton method based on conjugate gradient, the truncated Newton method based on MINRES-QLP exhibits computational efficiency while maintaining the same level of accuracy.
Ring-array Ultrasound CT Reflection Imaging Applied to Breast Tumor Detection
Authors: Shi Lifan , Huang Xiao , Yuan Xuting , Zhang Wendong
Published: October 2024

Breast tumor is one of the most common malignant tumors among women worldwide. Ultrasound imaging is a widely used modality for its detection and diagnosis. In this study, we derived the theory of focusing and steering technique based on curved array and verified it by simulation. We proposed an ultrasound CT imaging method based on ring-array with multi-subarray simultaneous transmission and reception. We performed simulation and experimental tests and evaluated the images using SSIM, PSNR and image entropy. The simulation results showed that the proposed focusing and steering technique could accurately focus on the set position. And when the ring-array diameter was 200 mm, the imaging effect reached a better level when the number of array elements increased to 1024, and increasing the number of elements had little effect on the imaging effect. In the experimental test, the best result was obtained when the sub-aperture element number of the ring-array was 1, and the result was better when the ring-array element number was 1024. This result provides an effective significance for ultrasound CT imaging of breast cancer.
Decoupling of Photoacoustic Spectroscopy Based on Machine Learning for Bone Chemical Composition Assessment: Simulation Study
Authors: Liu Jiayi , Feng Ting , Xie Weiya , Cheng Qian
Published: October 2024

Photoacoustic (PA) spectroscopy technology can be utilized to identification of molecules in biological tissue based on the contrast of optical absorption. However, it is susceptible to the interference of overlapped optical absorption peaks from different chemical components, especially for dense bone tissue which contains both organic and non-organic chemical components. To accurately extract the relative contents of chemical components in bone tissue, this study established a decoupling method based on the PA band ratio and machine learning to quantitatively analyze the proportion of chemical components in bone tissue from the PA spectra. The predicted quantification parameters of different chemical components were consistent with the simulated presets, and could be used to characterize the changes of bone tissue components. Considering that PA technology is non-invasive and radiation-free, this technique shows great potential for the early diagnosis and monitoring of bone disease progression.
Adaptive weight determination schemes in angle and sub-band compounding for ultrasonic beamforming
Authors: Yoneda Junna , Saito Yuta , Zheng Jie , Tagawa Norio
Published: October 2024

We have proposed the Adaptive Sub-Band Compound (A-SBC) method, which uses subbands of different frequencies to improve the resolution by adaptive compounding. A-SBC effectively suppresses the sidelobe level by mainly utilizing the principle that the phases of subbands of different frequencies are inconsistent off-axis. There are many specific methods that can realize A-SBC. In this study, we propose three additional methods based on a previous application of A-SBC to multi-angle plane-wave beamforming. We evaluate these four methods through simulation and human carotid artery experiments.