bluuebunny/crossref_metadata_2025 huggingface dataset:
High-resolution MRI synthesis using a data-driven framework with denoising diffusion probabilistic modeling
Authors: Chang Chih-Wei , Peng Junbo , Safari Mojtaba , Salari Elahheh , Pan Shaoyan , Roper Justin , Qiu Richard L J , Gao Yuan , Shu Hui-Kuo , Mao Hui , Yang Xiaofeng
Published: January 2024

Objective. High-resolution magnetic resonance imaging (MRI) can enhance lesion diagnosis, prognosis, and delineation. However, gradient power and hardware limitations prohibit recording thin slices or sub-1 mm resolution. Furthermore, long scan time is not clinically acceptable. Conventional high-resolution images generated using statistical or analytical methods include the limitation of capturing complex, high-dimensional image data with intricate patterns and structures. This study aims to harness cutting-edge diffusion probabilistic deep learning techniques to create a framework for generating high-resolution MRI from low-resolution counterparts, improving the uncertainty of denoising diffusion probabilistic models (DDPM). Approach. DDPM includes two processes. The forward process employs a Markov chain to systematically introduce Gaussian noise to low-resolution MRI images. In the reverse process, a U-Net model is trained to denoise the forward process images and produce high-resolution images conditioned on the features of their low-resolution counterparts. The proposed framework was demonstrated using T2-weighted MRI images from institutional prostate patients and brain patients collected in the Brain Tumor Segmentation Challenge 2020 (BraTS2020). Main results. For the prostate dataset, the bicubic interpolation model (Bicubic), conditional generative-adversarial network (CGAN), and our proposed DDPM framework improved the noise quality measure from low-resolution images by 4.4%, 5.7%, and 12.8%, respectively. Our method enhanced the signal-to-noise ratios by 11.7%, surpassing Bicubic (9.8%) and CGAN (8.1%). In the BraTS2020 dataset, the proposed framework and Bicubic enhanced peak signal-to-noise ratio from resolution-degraded images by 9.1% and 5.8%. The multi-scale structural similarity indexes were 0.970 ± 0.019, 0.968 ± 0.022, and 0.967 ± 0.023 for the proposed method, CGAN, and Bicubic, respectively. Significance. This study explores a deep learning-based diffusion probabilistic framework for improving MR image resolution. Such a framework can be used to improve clinical workflow by obtaining high-resolution images without penalty of the long scan time. Future investigation will likely focus on prospectively testing the efficacy of this framework with different clinical indications.
Conservative and nonconservative forces for Mie particles in acoustic trapping
Authors: Cheng Huimin , Zhang Xixi , Li Xiao , Ng Jack
Published: January 2024

A general acoustic force field can be decomposed into a conservative gradient force (GF) and a non-conservative scattering force (SF), which have very different physical and mathematical properties. However, the profiles of such forces for Mie particles are unknown, let alone their underlying physics. Here, by using a fast Fourier transform approach, we calculated the GF and SF for spherical particle of various sizes and various incident waves. For the same focused incident waves, the normalized GF and SF are similar for different particle sizes, while the total force can be quite different owing to the varying relative strength between the GF and SF. GF and SF possess symmetries that are not found in the incident waves, indicating that these physically and mathematically distinct forces have symmetries that are hidden from the beam profile. For a vortex beam carrying a well-defined topological charge, acoustic forces alone cannot trap particles.
Delayed and fractional-order dynamics of a model for earthquake induced by stress perturbations
Authors: Bisong M S , Mofor I A , Fomekong M , Tsasse L C , Mando A K , Manfouo F , Tanekou G B , Motchongom M T , Afungchui D
Published: January 2024

Fractional calculus and time delay provide a powerful tool to model complex systems with memory and fractal systems and, the viscoelastic systems. Earthquakes are both complex systems with long-memory and some of their faults have fractal properties and, the rocks constituting faults have viscoelastic behavior. In this paper, we examined the dynamics of the spring-block considering the fractional viscous damping force and interaction between the blocks. The shear stress response is studied using the harmonic balance method and the numerical simulations are performed through Adams-Bashforth-Moulton scheme. The effects of the fractional-order and time delay on the amplitude-frequency curves and on the transition between steady state and seismic regime are investigated. The system response shows the existence of the resonance and anti-resonance. It is appears that the resonance amplitude and resonance frequency are strongly dependent on the time delay and fractional-order. This resonance phenomenon results in an accumulation of energy which can lead to the destabilization of the fault system. At the anti-resonance the system response has minimum amplitude, and the blocks move without accumulated energy. The results show that the delay and fractional viscous can affect the properties of the rock, which is characterized by the modified linear stiffness coefficient, modified linear damping coefficient and the modified linear friction coefficient. The stability and hopf bifurcation are investigated and the critical value of the time delay for the occurrence of Hopf bifurcation is determined. The transition from stationary state to the periodic orbit and vice-versa through the hopf bifurcation is observed in the system.
Analysis of misaligned optics effects on beam pointing stability in dual-pass optical system
Authors: Li Weiwei , Chen Fei , Zhang Kuo , Wang Jiamin , Lv Zhe
Published: January 2024

The high-power laser device utilizes a multi-pass amplification system to achieve elevated power laser output. Laser beam is transmitted several times through the amplifier, and the pointing stability is a critical factor affecting the efficiency of the system. Any perturbation of the optics during laser transmission can cause misalignment and further lead to beam pointing errors. Laser beam propagation simulation was conducted using the ray tracing method. Equivalent experiment was performed using a laser with a wavelength of 532 nm, and the centroid position data of the laser beam were collected to characterize the effect of the optics misalignment on laser pointing. A model evaluating the sensitivity of the optics was constructed, and the analysis of how various optics impact pointing accuracy was conducted. Results indicate that, a linear relationship exists between the misalignment of the optic and the pointing shift and angular deviation of the beam when a single optic is misaligned. If multiple optics are misaligned, the shift in centroid position of the laser beam can be calculated by adding up the shifts caused by each misaligned optic. Furthermore, the shift in the centroid position of the laser beam is the linear superposition of the misalignment of each optic.
Machine-learning-based mapping of blood oxygen saturation from dual-wavelength optoacoustic measurements
Authors: Kurakina D A , Kirillin M Yu , Khilov A V , Perekatova V V
Published: January 2024

We developed a novel machine-learning-based algorithm based on a gradient boosting regressor for three-dimensional pixel-by-pixel mapping of blood oxygen saturation based on dual-wavelength optoacoustic data. Algorithm training was performed on in silico data produced from Monte-Carlo-generated absorbed light energy distributions in tissue-like vascularized media for probing wavelengths of 532 and 1064 nm and the empirical instrumental function of the optoacoustic imaging setup with further validation of the independent in silico data. In vivo optoacoustic data for rabbit-ear vasculature was employed as a testing dataset. The developed algorithm allowed in vivo blood oxygen saturation mapping and showed clear differences in blood oxygen saturation values in veins at 15 °C and 43 °C due to functional arteriovenous anastomoses. These results indicated that dual-wavelength optoacoustic imaging could serve as a cost-effective alternative to complicated multiwavelength quantitative optoacoustic imaging.
Low-frequency hybridized excess vibrations of two-dimensional glasses
Authors: Fu 付 Licun 立存 , Zheng 郑 Yiming 一鸣 , Wang 王 Lijin 利近
Published: January 2024

One hallmark of glasses is the existence of excess vibrational modes at low frequencies ω beyond Debye’s prediction. Numerous studies suggest that understanding low-frequency excess vibrations could help gain insight into the anomalous mechanical and thermodynamic properties of glasses. However, there is still intensive debate as to the frequency dependence of the population of low-frequency excess vibrations. In particular, excess modes could hybridize with phonon-like modes and the density of hybridized excess modes has been reported to follow D
exc(ω) ∼ ω
2 in 2D glasses with an inverse power law potential. Yet, the universality of the quadratic scaling remains unknown, since recent work suggested that interaction potentials could influence the scaling of the vibrational spectrum. Here, we extend the universality of the quadratic scaling for hybridized excess modes in 2D to glasses with potentials ranging from the purely repulsive soft-core interaction to the hard-core one with both repulsion and attraction as well as to glasses with significant differences in density or interparticle repulsion. Moreover, we observe that the number of hybridized excess modes exhibits a decrease in glasses with higher density or steeper interparticle repulsion, which is accompanied by a suppression of the strength of the sound attenuation. Our results indicate that the density bears some resemblance to the repulsive steepness of the interaction in influencing low-frequency properties.
Optimized operation scheme of flash-memory-based neural network online training with ultra-high endurance
Authors: Feng Yang , Sun Zhaohui , Qi Yueran , Zhan Xuepeng , Zhang Junyu , Liu Jing , Kobayashi Masaharu , Wu Jixuan , Chen Jiezhi
Published: January 2024

With the rapid development of machine learning, the demand for high-efficient computing becomes more and more urgent. To break the bottleneck of the traditional Von Neumann architecture, computing-in-memory (CIM) has attracted increasing attention in recent years. In this work, to provide a feasible CIM solution for the large-scale neural networks (NN) requiring continuous weight updating in online training, a flash-based computing-in-memory with high endurance (109 cycles) and ultra-fast programming speed is investigated. On the one hand, the proposed programming scheme of channel hot electron injection (CHEI) and hot hole injection (HHI) demonstrate high linearity, symmetric potentiation, and a depression process, which help to improve the training speed and accuracy. On the other hand, the low-damage programming scheme and memory window (MW) optimizations can suppress cell degradation effectively with improved computing accuracy. Even after 109 cycles, the leakage current (I
off) of cells remains sub-10pA, ensuring the large-scale computing ability of memory. Further characterizations are done on read disturb to demonstrate its robust reliabilities. By processing CIFAR-10 tasks, it is evident that ~90% accuracy can be achieved after 109 cycles in both ResNet50 and VGG16 NN. Our results suggest that flash-based CIM has great potential to overcome the limitations of traditional Von Neumann architectures and enable high-performance NN online training, which pave the way for further development of artificial intelligence (AI) accelerators.
Electrical properties and structural optimization of GaN/InGaN/GaN tunnel junctions grown by molecular beam epitaxy
Authors: Fang Jun , Zhang Fan , Yang Wenxian , Tian Aiqin , Liu Jianping , Lu Shulong , Yang Hui
Published: January 2024

The InGaN films and GaN/InGaN/GaN tunnel junctions (TJs) were grown on GaN templates with plasma-assisted molecular beam epitaxy. As the In content increases, the quality of InGaN films grown on GaN templates decreases and the surface roughness of the samples increases. V-pits and trench defects were not found in the AFM images. p++-GaN/InGaN/n++-GaN TJs were investigated for various In content, InGaN thicknesses and doping concentration in the InGaN insert layer. The InGaN insert layer can promote good interband tunneling in GaN/InGaN/GaN TJ and significantly reduce operating voltage when doping is sufficiently high. The current density increases with increasing In content for the 3 nm InGaN insert layer, which is achieved by reducing the depletion zone width and the height of the potential barrier. At a forward current density of 500 A/cm2, the measured voltage was 4.31 V and the differential resistance was measured to be 3.75 × 10−3 Ω·cm2 for the device with a 3 nm p++-In0.35Ga0.65N insert layer. When the thickness of the In0.35Ga0.65N layer is closer to the “balanced” thickness, the TJ current density is higher. If the thickness is too high or too low, the width of the depletion zone will increase and the current density will decrease. The undoped InGaN layer has a better performance than n-type doping in the TJ. Polarization-engineered tunnel junctions can enhance the functionality and performance of electronic and optoelectronic devices.
Statistical mechanics of the maximum-average submatrix problem
Authors: Erba Vittorio , Krzakala Florent , Pérez Ortiz Rodrigo , Zdeborová Lenka
Published: January 2024

We study the maximum-average submatrix problem, wherein given an N × N matrix J, one needs to find the k × k submatrix with the largest average number of entries. We investigate the problem for random matrices J, whose entries are i.i.d. random variables, by mapping it to a variant of the Sherrington–Kirkpatrick spin-glass model at fixed magnetisation. We analytically characterise the phase diagram of the model as a function of the submatrix average and the size of the submatrix k in the limit

N
→
∞

. We consider submatrices of size

k
=
m
N

with

0
<
m
<
1

. We find a rich phase diagram, including dynamical, static one-step replica symmetry breaking (1-RSB) and full-step RSB. In the limit of m → 0, we find a simpler phase diagram featuring a frozen 1-RSB phase, where the Gibbs measure comprises exponentially many pure states each with zero entropy. We discover an interesting phenomenon, reminiscent of the phenomenology of the binary perceptron: there are efficient algorithms that provably work in the frozen 1-RSB phase.
Design and first experience of the prototype pixel layers for the ALICE FoCal
Authors: Bodova Tea , Alme Johan , Borshchov Viatcheslav , van den Brink Anthony , Groettvik Ola , Protsenko Maksym , Röhrich Dieter , Tymchuk Ihor , Ullaland Kjetil , Yang Shiming ,   the ALICE collaboration
Published: January 2024

The University of Bergen is involved in developing two calorimeters: the pixel section of
the Electromagnetic Forward Calorimeter for the ALICE Upgrade to be installed during LS3 for
data-taking in the period 2029–2032 and the Digital Tracking Calorimeter for the proton Computed
Tomography prototype. Both designs utilize pixel sensors and require a reliable connection to the
readout which is positioned approximately 5 meters away. Furthermore, the structural design of
these calorimeters calls for a compact layer assembly. This paper provides the strategies
deployed to meet these critical requirements, focusing on the implementation of the chip-on-flex
assembly, and the ultrasonic welding techniques. It further describes other design considerations
essential for maintaining good signal integrity. Finally, it gives insight into the experiences
and challenges faced while working with the prototypes, both in the laboratory and test beam
setups.
Measurement of secondary neutron spectra induced by 480 MeV proton and 430 MeV/u 4He beams with a thick aluminum target
Authors: Di Chicco A. , Boscolo D. , Luoni F. , Kozlova E. , Weber U. , Durante M. , Zboril M.
Published: January 2024

Knowledge of the characteristics of secondary neutrons produced by the interaction of
Galactic Cosmic Radiation with spacecraft shielding materials is becoming increasingly important
for predicting and mitigating biological risks of space explorers during deep-space travel. Hadron
accelerators for medical applications are well suited to reproduce part of the conditions found in
deep-space in terms of ion species and energies. The objectives of this work are to measure the
secondary neutron spectra produced by proton and helium ion beams hitting an aluminum target with
energies that correspond to the Galactic Cosmic Radiation peak during solar minimal activity and
to validate and compare physical models of Monte Carlo simulations. Neutron spectra were measured
with the extended-range Bonner sphere system NEMUS at two positions, 0° and 90° relative to the
direction of the primary ion beam. The experimental setup consisted of 480 MeV proton and 430 MeV/u 4He beams colliding with a 30×30×63.5 cm3 aluminum
target. The experimental neutron spectra were analyzed using the MAXED unfolding code and compared
to several Monte Carlo simulation codes. The results show deviations in terms of the shape of the
neutron energy distributions ranging between 1% and 14% and of the integral quantities of
fluence and ambient dose equivalent ranging between 1% and 5.2%.
Ionizing radiation influence on 28-nm MOS transistor's low-frequency noise characteristics
Authors: Apro M. , Michalowska-Forsyth A.
Published: January 2024

In this paper, we explore the transitions of low-frequency noise characteristics in high-k metal-gate bulk CMOS transistors induced by Total Ionizing Dose (TID). Due to the strong bias dependence of the noise characteristics, differentiating between noise shifts caused by the effective biasing change and the contribution of the newly generated traps becomes extremely challenging. In order to better understand the effects of irradiation, transistor noise had to be characterized at several biasing points, both in linear and saturation regions, before and after exposure to 1 Grad (SiO2) of TID. Correlation between shifts in time and frequency domain is presented in this work, along with possible explanations for each variation that occurs. We present examples of irradiation-generated Random Telegraph Noise (RTN) defects as well as various TID effects on noise Power Spectral Density (PSD) curves with pre-existing RTN sources.
Bionic study of distance-azimuth discrimination of multi-scattered point objects in bat bio-sonar
Authors: Wang Feng , Chen Ming
Published: January 2024

This paper presents a novel approach to enhance the discrimination capacity of multi-scattered point objects in bat bio-sonar. A broadband interferometer mathematical model is developed, incorporating both distance and azimuth information, to simulate the transmitted and received signals of bats. The Fourier transform is employed to simulate the preprocessing step of bat information for feature extraction. Furthermore, the bat bio-sonar model based on convolutional neural network (BS-CNN) is constructed to compensate for the limitations of conventional machine learning and CNN networks, including three strategies: Mix-up data enhancement, joint feature and hybrid atrous convolution module. The proposed BS-CNN model emulates the perceptual nerves of the bat brain for distance-azimuth discrimination and compares with four conventional classifiers to assess its discrimination efficacy. Experimental results demonstrate that the overall discrimination accuracy of the BS-CNN model is 93.4%, surpassing conventional CNN networks and machine learning methods by at least 5.9%. This improvement validates the efficacy of the BS-CNN bionic model in enhancing the discrimination accuracy in bat bio-sonar and offers valuable references for radar and sonar target classification.
Climate, fire, and anthropogenic disturbance determine the current global distribution of tropical forest and savanna
Authors: Williamson Grant J , Tng David YP , Bowman David MJS
Published: January 2024

Tropical forest and savanna biomes are pivotal in the functioning of the Earth system. Both are biodiverse and under increasing threat due to land clearing and anthropogenic climate change, and play important roles in the global carbon cycle, through maintenance of a large carbon pool in tropical forests, and exchange in savannas through extensive landscape fires. Reliable mapping of tropical forest and savanna is essential to understand how the current distribution of these vegetation types is controlled by climate land clearing and fire. Using Google Maps satellite imagery, we manually classified 24 239 random points as forest, savanna, or anthropogenic landscapes within the tropics and applied this novel dataset to defining the climatic zone where forest and savanna exist as alternative states. Because fire and climate are correlated, we developed separate geospatial models to rank the importance of climate, topography, and human influence on vegetation present. This modeling confirmed that those areas with more fires had lower probabilities of tropical forest, that forest was most likely in areas with high mean annual rainfall with little seasonal variation in precipitation, and that anthropogenic factors disrupt this environmental predictability. We also identified areas where tropical forest and savanna both co-occur, but these were relatively uncommon. These relationships suggest that future drier climates projected under anthropogenic climate change, combined with clearing and burning that have reduced tropical forest extent to a subset of its theoretical distribution, will lead to irreversible loss of tropical forests. Our modeling provides global mapping that can be used track further changes to distribution of tropical forests.
On the hierarchy and fine structure of blowups and gradient catastrophes for multidimensional homogeneous Euler equation
*
Authors: Konopelchenko B G , Ortenzi G
Published: January 2024

Blowups of derivatives and gradient catastrophes for the n-dimensional homogeneous Euler equation are discussed. It is shown that, in the case of generic initial data, the blowups exhibit a fine structure in accordance with the admissible ranks of certain matrix generated by the initial data. Blowups form a hierarchy composed by n + 1 levels with the singularity of derivatives given by

∂

u
i

/

∂

x
k

∼

|

δ

x

|

−
(
m
+
1
)

/

(
m
+
2
)

,

m
=
1
,
…
,
n

along certain critical directions. It is demonstrated that in the multi-dimensional case there is certain bounded linear superposition of blowup derivatives. Particular results for the potential motion are presented too. Hodograph equations are basic tools of the analysis.
Enhancement of lacrimal gland cell function by decellularized lacrimal gland derived hydrogel
Authors: Wiebe-Ben Zakour Katharina E , Kaya Sema , Matros Julia C , Hacker Michael C , Cheikh-Rouhou Amina , Spaniol Kristina , Geerling Gerd , Witt Joana
Published: January 2024

Sustainable treatment of aqueous deficient dry eye (ADDE) represents an unmet medical need and therefore requires new curative and regenerative approaches based on appropriate in vitro models. Tissue specific hydrogels retain the individual biochemical composition of the extracellular matrix and thus promote the inherent cell´s physiological function. Hence, we created a decellularized lacrimal gland (LG) hydrogel (dLG-HG) meeting the requirements for a bioink as the basis of a LG model with potential for in vitro ADDE studies. Varying hydrolysis durations were compared to obtain dLG-HG with best possible physical and ultrastructural properties while preserving the original biochemical composition. A particular focus was placed on dLG-HG´s impact on viability and functionality of LG associated cell types with relevance for a future in vitro model in comparison to the unspecific single component hydrogel collagen type-I (Col) and the common cell culture substrate Matrigel. Proliferation of LG epithelial cells (EpC), LG mesenchymal stem cells, and endothelial cells cultured on dLG-HG was enhanced compared to culture on Matrigel. Most importantly with respect to a functional in vitro model, the secretion capacity of EpC cultured on dLG-HG was higher than that of EpC cultured on Col or Matrigel. In addition to these promising cell related properties, a rapid matrix metalloproteinase-dependent biodegradation was observed, which on the one hand suggests a lively cell–matrix interaction, but on the other hand limits the cultivation period. Concluding, dLG-HG possesses decisive properties for the tissue engineering of a LG in vitro model such as cytocompatibility and promotion of secretion, making it superior to unspecific cell culture substrates. However, deceleration of biodegradation should be addressed in future experiments.
Point-like vacancies in two-dimensional transition metal dichalcogenides
Authors: Özcan Sibel , Gallardo Aurelio , Biel Blanca
Published: January 2024

This study explores the realm of two-dimensional transition metal dichalcogenides (TMDs), examining some of the most prevalent defects. Employing density functional theory, we scrutinize three common defect types across four extensively studied TMDs: MoS2, MoSe2, WS2, and WSe2. Our investigation spans the energetics of these defects, unveiling the most stable ones, and unraveling the alterations in structural and electronic properties induced by their presence. As a further step towards practical applications, we simulate the images that would be captured by both Atomic and Kelvin Probe Force Microscopes, aiming at a facile identification of these defects when probed at the microscopic level.
ELUQuant: event-level uncertainty quantification in deep inelastic scattering
Authors: Fanelli C , Giroux J
Published: January 2024

We introduce a physics-informed Bayesian neural network with flow-approximated posteriors using multiplicative normalizing flows for detailed uncertainty quantification (UQ) at the physics event-level. Our method is capable of identifying both heteroskedastic aleatoric and epistemic uncertainties, providing granular physical insights. Applied to deep inelastic scattering (DIS) events, our model effectively extracts the kinematic variables x, Q
2, and y, matching the performance of recent deep learning regression techniques but with the critical enhancement of event-level UQ. This detailed description of the underlying uncertainty proves invaluable for decision-making, especially in tasks like event filtering. It also allows for the reduction of true inaccuracies without directly accessing the ground truth. A thorough DIS simulation using the H1 detector at HERA indicates possible applications for the future electron–ion collider. Additionally, this paves the way for related tasks such as data quality monitoring and anomaly detection. Remarkably, our approach effectively processes large samples at high rates.
Pyroelectric influence on lithium niobate during the thermal transition for cryogenic integrated photonics
Authors: Thiele Frederik , Hummel Thomas , Lange Nina Amelie , Dreher Felix , Protte Maximilian , Bruch Felix vom , Lengeling Sebastian , Herrmann Harald , Eigner Christof , Silberhorn Christine , Bartley Tim J
Published: January 2024

Lithium niobate has emerged as a promising platform for integrated quantum optics, enabling efficient generation, manipulation, and detection of quantum states of light. However, integrating single-photon detectors requires cryogenic operating temperatures, since the best performing detectors are based on narrow superconducting wires. While previous studies have demonstrated the operation of quantum light sources and electro-optic modulators in LiNbO3 at cryogenic temperatures, the thermal transition between room temperature and cryogenic conditions introduces additional effects that can significantly influence device performance. In this paper, we investigate the generation of pyroelectric charges and their impact on the optical properties of lithium niobate waveguides when changing from room temperature to 25 K, and vice versa. We measure the generated pyroelectric charge flow and correlate this with fast changes in the birefringence acquired through the Sénarmont-method. Both electrical and optical influence of the pyroelectric effect occur predominantly at temperatures above 100 K.
Unveiling the electronic structure of GaSb/AlGaSb quantum dots emitting in the third telecom window
Authors: Leguay Lucie , Chellu Abhiroop , Hilska Joonas , Luna Esperanza , Schliwa Andrei , Guina Mircea , Hakkarainen Teemu
Published: January 2024

Epitaxially-grown semiconductor quantum dots (QDs) provide an attractive platform for the development of deterministic sources of high-quality quantum states of light. Such non-classical light sources are essential for quantum information processing and quantum communication. QDs emitting in the telecom wavelengths are especially important for ensuring compatibility with optical fiber systems required to implement quantum communication networks. To this end, GaSb QDs fabricated by filling local-droplet etched nanoholes are emerging as a viable approach, yet the electronic properties of such nanostructures have not been studied in detail. In this article, an insight into the electronic structure and carrier dynamics in GaSb/AlGaSb QDs is provided through a systematic experimental analysis of their temperature-dependent photoluminescence behavior. A steady-state rate equation model is used to reveal the relevant energy barriers for thermally activated carrier capture and escape processes. Furthermore, results of detailed theoretical simulations of quantum-confined energy states using the multi-band k·p model and the effective mass method are presented. The purpose of the simulations is to reveal the direct and indirect energy states, carrier wavefunctions, and allowed optical transitions for GaSb QDs with different physical dimensions.
Harnessing stochasticity for superconductive multi-layer spike-rate-coded neuromorphic networks
Authors: Edwards Alexander J , Krylov Gleb , Friedman Joseph S , Friedman Eby G
Published: January 2024

Conventional semiconductor-based integrated circuits are gradually approaching fundamental scaling limits. Many prospective solutions have recently emerged to supplement or replace both the technology on which basic devices are built and the architecture of data processing. Neuromorphic circuits are a promising approach to computing where techniques used by the brain to achieve high efficiency are exploited. Many existing neuromorphic circuits rely on unconventional and useful properties of novel technologies to better mimic the operation of the brain. One such technology is single flux quantum (SFQ) logic—a cryogenic superconductive technology in which the data are represented by quanta of magnetic flux (fluxons) produced and processed by Josephson junctions embedded within inductive loops. The movement of a fluxon within a circuit produces a quantized voltage pulse (SFQ pulse), resembling a neuronal spiking event. These circuits routinely operate at clock frequencies of tens to hundreds of gigahertz, making SFQ a natural technology for processing high frequency pulse trains. This work harnesses thermal stochasticity in superconducting synapses to emulate stochasticity in biological synapses in which the synapse probabilistically propagates or blocks incoming spikes. The authors also present neuronal, fan-in, and fan-out circuitry inspired by the literature that seamlessly cascade with the synapses for deep neural network construction. Synapse weights and neuron biases are set with bias current, and the authors propose multiple mechanisms for training the network and storing weights. The network primitives are successfully demonstrated in simulation in the context of a rate-coded multi-layer XOR neural network which achieves a wide classification margin. The proposed methodology is based solely on existing SFQ technology and does not employ unconventional superconductive devices or semiconductor transistors, making this proposed system an effective approach for scalable cryogenic neuromorphic computing.
The singularity probability of a random symmetric matrix is exponentially small
Authors: Campos Marcelo , Jenssen Matthew , Michelen Marcus , Sahasrabudhe Julian
Published: January 2024

Let

A
A

be drawn uniformly at random from the set of all

n
×
n

n\times n

symmetric matrices with entries in

{
−
1
,
1
}

\{-1,1\}

. We show that
\[

P

(
det
(
A
)
=
0
)
⩽

e

−
c
n

,

\mathbb {P}( \det (A) = 0 ) \leqslant e^{-cn},

\]
where

c
>
0

c>0

is an absolute constant, thereby resolving a long-standing conjecture.
Eurosceptic Vote Deviation and the Impact of News Media
Authors: Kritzinger Sylvia , Johann David
Published: January 2024

The chapter examines first how many voters deviate from the party they are closest to in left‐right terms, but rather vote for a Eurosceptic party. In addition, the contestation of the European issue is regarded. As voters require information about the political agenda to make a decision, the chapter explores contestation effects by analysing the impact of news media reporting. Using public opinion and media data of the 1999, 2004, and 2009 European Election Studies, it finds that only a few voters deviate from their left‐right preferences and choose a Eurosceptic party. Moreover, the news media hardly exert an influence on changes in ideological vote deviations even when taking individuals’ pre‐held EU attitudes into account.
Talking It Up or Talking It Down?
Authors: Boomgaarden Hajo G.
Published: January 2024

The chapter explains public opinion about the state of European democracy by focusing on the role of communication. It is argued that political talk, described as a core component of democratic life, is likely to be consequential for public assessments of EU democracy, but that the direction of relationship depends on context characteristics. Following prior literature the chapter focuses on the democratic quality of national political institutions. The findings indeed show that, in particular, in countries in which national institutions perform rather poorly, talking about the EP election is related to better assessments of EU democracy. The reverse pattern, however, is less evident. Overall people to some degree do rely on their national political institutions as a benchmark against which to talk about EU democracy.
SimService: a lightweight library for building simulation services in Python
Authors: Sego T J
Published: January 2024

Integrative biological modeling requires software infrastructure to launch, interconnect, and execute simulation software components without loss of functionality. SimService is a software library that enables deploying simulations in integrated applications as memory-isolated services with interactive proxy objects in the Python programming language. SimService supports customizing the interface of proxies so that simulation developers and users alike can tailor generated simulation instances according to model, method, and integrated application.

Availability and implementation

SimService is written in Python, is freely available on GitHub under the MIT license at https://github.com/tjsego/simservice, and is available for download via the Python Package Index (package name “simservice”) and conda (package name “simservice” on the conda-forge channel).
MetaNorm: incorporating meta-analytic priors into normalization of NanoString nCounter data
Authors: Barth Jackson , Yang Yuqiu , Xiao Guanghua , Wang Xinlei
Published: January 2024

Motivation

Non-informative or diffuse prior distributions are widely employed in Bayesian data analysis to maintain objectivity. However, when meaningful prior information exists and can be identified, using an informative prior distribution to accurately reflect current knowledge may lead to superior outcomes and great efficiency.

Results

We propose MetaNorm, a Bayesian algorithm for normalizing NanoString nCounter gene expression data. MetaNorm is based on RCRnorm, a powerful method designed under an integrated series of hierarchical models that allow various sources of error to be explained by different types of probes in the nCounter system. However, a lack of accurate prior information, weak computational efficiency, and instability of estimates that sometimes occur weakens the approach despite its impressive performance. MetaNorm employs priors carefully constructed from a rigorous meta-analysis to leverage information from large public data. Combined with additional algorithmic enhancements, MetaNorm improves RCRnorm by yielding more stable estimation of normalized values, better convergence diagnostics and superior computational efficiency.

Availability and implementation

R Code for replicating the meta-analysis and the normalization function can be found at github.com/jbarth216/MetaNorm.
Exposome in ischaemic heart disease: beyond traditional risk factors
Authors: Montone Rocco A , Camilli Massimiliano , Calvieri Camilla , Magnani Giulia , Bonanni Alice , Bhatt Deepak L , Rajagopalan Sanjay , Crea Filippo , Niccoli Giampaolo
Published: January 2024

Ischaemic heart disease represents the leading cause of morbidity and mortality, typically induced by the detrimental effects of risk factors on the cardiovascular system. Although preventive interventions tackling conventional risk factors have helped to reduce the incidence of ischaemic heart disease, it remains a major cause of death worldwide. Thus, attention is now shifting to non-traditional risk factors in the built, natural, and social environments that collectively contribute substantially to the disease burden and perpetuate residual risk. Of importance, these complex factors interact non-linearly and in unpredictable ways to often enhance the detrimental effects attributable to a single or collection of these factors. For this reason, a new paradigm called the ‘exposome’ has recently been introduced by epidemiologists in order to define the totality of exposure to these new risk factors. The purpose of this review is to outline how these emerging risk factors may interact and contribute to the occurrence of ischaemic heart disease, with a particular attention on the impact of long-term exposure to different environmental pollutants, socioeconomic and psychological factors, along with infectious diseases such as influenza and COVID-19. Moreover, potential mitigation strategies for both individuals and communities will be discussed.
Michener’s group-size paradox in cooperatively breeding birds
Authors: Downing Philip A
Published: January 2024

According to Michener’s paradox, most altruistic groups in nature should be small and large groups should not exist. This is because per capita productivity is thought to decrease as groups get larger, meaning that the share of indirect fitness available to each group member declines, which favours dispersal. The empirical evidence for a decrease in per capita productivity is contradictory, however, and limited to the social Hymenoptera. I report that per capita reproductive success decreased with increasing group size across 26 cooperatively breeding bird species. Small groups comprising two or three individuals were the most common (79% of 16,101 groups), and these had the highest per capita reproductive success. This close fit between per capita reproductive success and the distribution of group sizes in nature suggests that it may indeed be difficult for large groups to evolve through indirect fitness benefits alone.
Ling-Gui-Zhu-Gan decoction protects against doxorubicin-induced myocardial injury by downregulating ferroptosis
Authors: Yang Ya-li , Zhao Chuan-zhi , Zhao Chun-chun , Wen Zhong-yu , Ma Yao-yao , Zhao Xiao-ni , Wang Liang , Huang Jin-ling , Zhou Peng
Published: January 2024

Objective

To investigate the mechanism of Ling-Gui-Zhu-Gan decoction (LGZGD) protects against doxorubicin (DOX)-induced myocardial injury.

Methods

In vivo experiment, rats were divided into six groups: normal group, model group (15 mg/kg, DOX), Dex group(150 mg/kg, Dex), LGZGD-L group (2.1 g/kg), LGZGD-M group (4.2 g/kg), and LGZGD-H group (8.4 g/kg). We used HE and Masson staining to observe the histopathological changes, echocardiography to assess the cardiac function, and western blot and RT-qPCR to detect the expressions of Nrf2, GPX4, Fpn1, and Ptgs2. In vitro experiment, we used immunofluorescence to detect ROS production, and RT-qPCR to detect gene expression of GPX4, Fpn1, and Ptgs2.

Key findings

In vivo, LGZGD improved cardiac systolic function. LGZGD significantly reduced MDA, LDH, and CK levels, increased SOD activity, enhanced the protein expression of Nrf2, GPX4, and Fpn1, and decreased Ptgs2 levels. In vitro, LGZGD-containing serum significantly reduced ROS, increased the gene expression of GPX4 and Fpn1, and decreased the gene expression of Ptgs2. Furthermore, compared with the LGZGD (si-NC) group, the LGZGD (si-Nrf2) group had decreased gene expression of Nrf2, GPX4, and Fpn1 and increased gene expression of Ptgs2.

Conclusions

LGZGD can ameliorate DOX-cardiotoxicity by activating the Nrf2 signaling pathway and inhibiting ferroptosis in cardiomyocytes.
Temporal Dynamics, Discovery, and Emergence of Human-Transmissible RNA Viruses
Authors: Lu Lu , Zhang Feifei , Brierley Liam , Robertson Gail , Chase-Topping Margo , Lycett Samantha , Woolhouse Mark
Published: January 2024

Transmissibility, the ability to spread within host populations, is a prerequisite for a pathogen to have epidemic or pandemic potential. Here, we estimate the phylogenies of human infectivity and transmissibility using 1,408 genome sequences from 743 distinct RNA virus species/types in 59 genera. By repeating this analysis using data sets censored by virus discovery date, we explore how temporal changes in the known diversity of RNA viruses—especially recent increases in recognized nonhuman viruses—have altered these phylogenies. Over time, we find significant increases in the proportion of RNA virus genera estimated to have a nonhuman-infective ancestral state, in the fraction of distinct human virus lineages that are purely human-transmissible or strictly zoonotic (compared to mixed lineages), and in the number of human viruses with nearest relatives known not to infect humans. Our results are consistent with viruses that are capable of spreading in human populations commonly emerging from a nonhuman reservoir. This is more likely in lineages that already contain human-transmissible viruses but is rare in lineages that contain only strictly zoonotic viruses.
BIL9 Promotes Both Plant Growth via BR Signaling and Drought Stress Resistance by Binding with the Transcription Factor HDG11
Authors: Surina Surina , Yamagami Ayumi , Miyaji Tomoko , Chagan Zhana , Chung KwiMi , Mitsuda Nobutaka , Nishida Kaisei , Tachibana Ryo , Zhu Zhangliang , Miyakawa Takuya , Shinozaki Kazuo , Sakuta Masaaki , Asami Tadao , Nakano Takeshi
Published: January 2024

Drought stress is a major threat leading to global plant and crop losses in the context of the climate change crisis. Brassinosteroids (BRs) are plant steroid hormones, and the BR signaling mechanism in plant development has been well elucidated. Nevertheless, the specific mechanisms of BR signaling in drought stress are still unclear. Here, we identify a novel Arabidopsis gene, BRZ INSENSITIVE LONG HYPOCOTYL 9 (BIL9), which promotes plant growth via BR signaling. Overexpression of BIL9 enhances drought and mannitol stress resistance and increases the expression of drought-responsive genes. BIL9 protein is induced by dehydration and interacts with the HD-Zip IV transcription factor HOMEODOMAIN GLABROUS 11 (HDG11), which is known to promote plant resistance to drought stress, in vitro and in vivo. BIL9 enhanced the transcriptional activity of HDG11 for drought-stress-resistant genes. BIL9 is a novel BR signaling factor that enhances both plant growth and plant drought resistance.
Epistemic Arguments for a Democratic Right to Silence
Authors: Degerman Dan , Bellazzi Francesca
Published: January 2024

While much ink has been spilt over the political importance of speech, much less has been dedicated to the political importance of silence. This article seeks to fill that gap. We propose the need for a robust, democratic right to silence in public life and argue that there are politically salient epistemic reasons for recognising that right. We begin by defining what silence is and what a robust right to silence entails. We then argue that the right to silence offers two politically salient epistemic benefits. The first is that, if the right to silence is maintained, we can avoid the epistemic harm that may be caused when an individual is compelled to lie in public. The second is that the right to silence can protect marginalised individuals against the epistemic injustices that may arise when others are likely to misconstrue their speech.
Developmental exposure to pesticides that disrupt retinoic acid signaling causes persistent retinoid and behavioral dysfunction in zebrafish
Authors: Hawkey Andrew B , Shekey Nathan , Dean Cassandra , Asrat Helina , Koburov Reese , Holloway Zade R , Kullman Seth W , Levin Edward D
Published: January 2024

Early developmental exposure to environmental toxicants may play a role in the risk for developing autism. A variety of pesticides have direct effects on retinoic acid (RA) signaling and as RA signaling has important roles in neurodevelopment, such compounds may cause developmental neurotoxicity through an overlapping adverse outcome pathway. It is hypothesized that a pesticide’s embryonic effects on retinoid function may correspond with neurobehavioral disruption later in development. In the current studies, we determined the effects of RA-acting pesticides on neurobehavioral development in zebrafish. Buprofezin and imazalil caused generalized hypoactivity in the larval motility test, whereas chlorothalonil and endosulfan I led to selective hypoactivity and hyperactivity, respectively. With buprofezin, chlorothalonil, and imazalil, hypoactivity and/or novel anxiety-like behaviors persisted in adulthood and buprofezin additionally decreased social attraction responses in adulthood. Endosulfan I did not produce significant adult behavioral effects. Using qPCR analyses of adult brain tissue, we observed treatment-induced alterations in RA synthesis or catabolic genes, indicating persistent changes in RA homeostasis. These changes were compound-specific, with respect to expression directionality, and potential patterns of homeostatic disruption. Results suggest the likely persistence of disruptions in RA signaling well into adulthood and may represent compensatory mechanisms following early life stage exposures. This study demonstrates that early developmental exposure to environmental toxicants that interfere with RA signaling causes short as well as long-term behavioral disruption in a well-established zebrafish behavioral model and expand upon the meaning of the RA adverse outcome pathway, indicating that observed effects likely correspond with the nature of underlying homeostatic effects.