bluuebunny/crossref_metadata_2025 huggingface dataset:
Transfer function approach to understanding periodic forcing of signal transduction networks
Authors: Tran Nguyen H N , Clayton Andrew H A
Published: March 2023

Signal transduction networks are responsible for transferring biochemical signals from the extracellular to the intracellular environment. Understanding the dynamics of these networks helps understand their biological processes. Signals are often delivered in pulses and oscillations. Therefore, understanding the dynamics of these networks under pulsatile and periodic stimuli is useful. One tool to do this is the transfer function. This tutorial outlines the basic theory behind the transfer function approach and walks through some examples of simple signal transduction networks.
Bringing Stellar Evolution and Feedback Together: Summary of Proposals from the Lorentz Center Workshop
Authors: Geen Sam , Agrawal Poojan , Crowther Paul A. , Keller B. W. , de Koter Alex , Keszthelyi Zsolt , van de Voort Freeke , Ali Ahmad A. , Backs Frank , Bonne Lars , Brugaletta Vittoria , Derkink Annelotte , Ekström Sylvia , Fichtner Yvonne A. , Grassitelli Luca , Götberg Ylva , Higgins Erin R. , Laplace Eva , You Liow Kong , Lorenzo Marta , McLeod Anna F. , Meynet Georges , Newsome Megan , André Oliva G. , Ramachandran Varsha , Rey Martin P. , Rieder Steven , Romano-Díaz Emilio , Sabhahit Gautham , Sander Andreas A. C. , Sarwar Rafia , Stinshoff Hanno , Stoop Mitchel , Szécsi Dorottya , Trebitsch Maxime , Vink Jorick S. , Winch Ethan
Published: March 2023

Stars strongly impact their environment, and shape structures on all scales throughout the universe, in a process known as “feedback.” Due to the complexity of both stellar evolution and the physics of larger astrophysical structures, there remain many unanswered questions about how feedback operates and what we can learn about stars by studying their imprint on the wider universe. In this white paper, we summarize discussions from the Lorentz Center meeting “Bringing Stellar Evolution and Feedback Together” in 2022 April and identify key areas where further dialog can bring about radical changes in how we view the relationship between stars and the universe they live in.
High performance trench diamond junction barrier Schottky diode with a sidewall-enhanced structure
Authors: Zhu Ying , Lin Wang , Li Dong-Shuai , Li Liu-An , Lv Xian-Yi , Wang Qi-Liang , Zou Guang-Tian
Published: March 2023

The trench diamond junction barrier Schottky (JBS) diode with a sidewall enhanced structure is designed by Silvaco simulation. Comparing with the conventional trench JBS diode, Schottky contact areas are introduced on the sidewall of the trench beside the top cathode. The sidewall Schottky contact weakens the junction field-effect transistor effect between the trenches to realize a low on-resistance and a high Baliga’s figure of merit (FOM) value. In addition, the existence of the n-type diamond helps to suppress the electric field crowding effect and enhance the reverse breakdown voltage. With the optimal parameters of device structure, a high Baliga’s FOM value of 2.28 GW/cm2 is designed. Therefore, the proposed sidewall-enhanced trench JBS diode is a promising component for the applications in diamond power electronics.
Spin reorientation in easy-plane kagome ferromagnet Li9Cr3(P2O7)3(PO4)2
Authors: Dong Yuanhao , Fu Ying , Liu Yixuan , Hao Zhanyang , Wang Le , Liu Cai , Deng Ke , Mei Jiawei
Published: March 2023

We report the successful growth and characterization of Li9Cr3(P2O7)3(PO4)2 single crystal, and investigate its magnetic properties under external magnetic fields via magnetization and heat capacity measurements. Our study reveals that Li9Cr3(P2O7)3(PO4)2 is an easy-plane kagome ferromagnet with S = 3/2, as evidenced by the Curie–Weiss temperature of 6 K which implies a ferromagnetic exchange coupling in the material. Under zero magnetic field, Li9Cr3(P2O7)3(PO4)2 undergoes a magnetic transition at T
C = 2.7 K from a paramagnetic state to a ferromagnetically ordered state with the magnetic moment lying in the kagome plane. By applying a c-axis directional magnetic field to rotate the spin alignment from the kagome plane to the c-axis, we observe a reduction in the magnetic transition temperature as the field is increased. We construct a magnetic phase diagram as a function of temperature and magnetic field applied parallel to the c-axis of Li9Cr3(P2O7)3(PO4)2 and find that the phase boundary is linear over a certain temperature range. Regarding that theoretically, the field-induced phase transition of the spin reorientation in the easy-plane ferromagnet can be viewed as the ferromagnetic magnon Bose–Einstein condensation (BEC), the phase boundary scaling of field-induced (B ∥ c) magnetic transition in Li9Cr3(P2O7)3(PO4)2 can be described as the quasi-2D magnon BEC, which has been observed in other ferromagnetic materials such as K2CuF4.
Entropies of the various components of the universe*
Authors: Yu Hao , Liu Yu-Xiao , Li Jin
Published: March 2023

In this study, we investigate the entropies of photons, ideal gas-like dust (baryonic matter), and a special kind of dark energy in the context of cosmology. When these components expand freely with the universe, we calculate the entropy and specific entropy of each component from the perspective of statistics. Under specific assumptions and conditions, the entropies of these components can satisfy the second law of thermodynamics independently. Our calculations show that the specific entropy of matter cannot be a constant during the expansion of the universe, except for photons. When these components interact with the space-time background, particle production (annihilation) can occur. We study the influence of the interaction on the entropies of these components and obtain the conditions guaranteeing that the entropy of each component satisfies the second law of thermodynamics.
An Improved Pair Method to Probe the Dust Extinction Law
Authors: Wang Yuxi , Gao Jian , Ren Yi , Li Jun
Published: March 2023

Dust extinction law is crucial to recover the intrinsic energy distribution of celestial objects and infer the characteristics of interstellar dust. Based on the traditional pair method, an improved pair method is proposed to model the dust extinguished spectral energy distribution (SED) of an individual star. Instead of the mathematically parameterizing extinction curves, the extinction curves in this work are directly from the silicate-graphite dust model, so that the dust extinction law can be obtained and the dust properties can be analyzed simultaneously. The ATLAS9 stellar model atmosphere is adopted for the intrinsic SEDs in this work, while the silicate-graphite dust model with a dust size distribution of

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for each component is adopted for the model extinction curves. One typical extinction tracer in the dense region (V410 Anon9) and one in the diffuse region (Cyg OB2 #12) of the Milky Way are chosen to test the reliability and the practicability of the improved pair method in different stellar environments. The results are consistent with their interstellar environments and are in agreement with the previous observations and studies, which prove that the improved pair method is effective and applicable in different stellar environments. In addition to the reliable extinction results, the derived parameters in the dust model can be used to analyze the dust properties, which cannot be achieved by other methods with the mathematical extinction models. With the improved pair method, the stellar parameters can also be inferred and the extinction law beyond the wavelengths of observed data can be predicted based on the dust model as well.
Convolutional neural network classifies visual stimuli from cortical response recorded with wide-field imaging in mice
Authors: De Luca Daniela , Moccia Sara , Lupori Leonardo , Mazziotti Raffaele , Pizzorusso Tommaso , Micera Silvestro
Published: March 2023

Objective. The optic nerve is a good location for a visual neuroprosthesis. It can be targeted when a subject cannot receive a retinal prosthesis and it is less invasive than a cortical implant. The effectiveness of an electrical neuroprosthesis depends on the combination of the stimulation parameters which must be optimized, and an optimization strategy might be performing closed-loop stimulation using the evoked cortical response as feedback. However, it is necessary to identify target cortical activation patterns and to associate the cortical activity with the visual stimuli present in the visual field of the subjects. Visual stimuli decoding should be performed on large areas of the visual cortex, and with a method as translational as possible to shift the study to human subjects in the future. The aim of this work is to develop an algorithm that meets these requirements and can be leveraged to automatically associate a cortical activation pattern with the visual stimulus that generated it. Approach. Three mice were presented with ten different visual stimuli, and their primary visual cortex response was recorded using wide-field calcium imaging. Our decoding algorithm relies on a convolutional neural network (CNN), trained to classify the visual stimuli from the correspondent wide-field images. Several experiments were performed to identify the best training strategy and investigate the possibility of generalization. Main results. The best classification accuracy was 75.38% ± 4.77%, obtained pre-training the CNN on the MNIST digits dataset and fine-tuning it on our dataset. Generalization was possible pre-training the CNN to classify Mouse 1 dataset and fine-tuning it on Mouse 2 and Mouse 3, with accuracies of 64.14% ± 10.81% and 51.53% ± 6.48% respectively. Significance. The combination of wide-field calcium imaging and CNNs can be used to classify the cortical responses to simple visual stimuli and might be a viable alternative to existing decoding methodologies. It also allows us to consider the cortical activation as reliable feedback in future optic nerve stimulation experiments.
Tracking the effects of propofol, sevoflurane and (S)-ketamine anesthesia using an unscented Kalman filter-based neural mass model
Authors: Liang Zhenhu , Wang Dihuan , Jin Xing , Fan Luxin , Wen Xin , Wei Changwei , Li Xiaoli
Published: March 2023

Objective. Neural mass model (NMM) has been widely used to investigate the neurophysiological mechanisms of anesthetic drugs induced general anesthesia (GA). However, whether the parameters of NMM could track the effects of anesthesia still unknown. Approach. We proposed using the cortical NMM (CNMM) to infer the potential neurophysiological mechanism of three different anesthetic drugs (i.e. propofol, sevoflurane, and (S)-ketamine) induced GA, and we employed unscented Kalman filter (UKF) to track any change in raw electroencephalography (rEEG) in frontal area during GA. We did this by estimating the parameters of population gain [i.e. excitatory/inhibitory postsynaptic potential (EPSP/IPSP, i.e. parameter A/B in CNMM) and the time constant rate of EPSP/IPSP (i.e. parameter a/b in CNMM). We compared the rEEG and simulated EEG (sEEG) from the perspective of spectrum, phase-amplitude coupling (PAC), and permutation entropy (PE). Main results. Under three estimated parameters (i.e. A, B, and a for propofol/sevoflurane or b for (S)-ketamine), the rEEG and sEEG had similar waveforms, time-frequency spectra, and PAC patterns during GA for the three drugs. The PE curves derived from rEEG and sEEG had high correlation coefficients (propofol: 0.97 ± 0.03, sevoflurane: 0.96 ± 0.03, (S)-ketamine: 0.98 ± 0.02) and coefficients of determination (R
2) (propofol: 0.86 ± 0.03, sevoflurane: 0.68 ± 0.30, (S)-ketamine: 0.70 ± 0.18). Except for parameter A for sevoflurane, the estimated parameters for each drug in CNMM can differentiate wakefulness and non-wakefulness states. Compared with the simulation of three estimated parameters, the UKF-based CNMM had lower tracking accuracy under the simulation of four estimated parameters (i.e. A, B, a, and b) for three drugs. Significance. The results demonstrate that a combination of CNMM and UKF could track the neural activities during GA. The EPSP/IPSP and their time constant rate can interpret the anesthetic drug’s effect on the brain, and can be used as a new index for depth of anesthesia monitoring.
Brain network dynamics in the alpha band during a complex postural control task
Authors: Aubonnet R , Hassan M , Mheich A , Di Lorenzo G , Petersen H , Gargiulo P
Published: March 2023

Objective. To decipher brain network dynamic remodeling from electroencephalography (EEG) during a complex postural control (PC) task combining virtual reality and a moving platform. Approach. EEG (64 electrodes) data from 158 healthy subjects were acquired. The experiment is divided into several phases, and visual and motor stimulation is applied progressively. We combined advanced source-space EEG networks with clustering algorithms to decipher the brain networks states (BNSs) that occurred during the task. Main results. The results show that BNS distribution describes the different phases of the experiment with specific transitions between visual, motor, salience, and default mode networks coherently. We also showed that age is a key factor that affects the dynamic transition of BNSs in a healthy cohort. Significance. This study validates an innovative approach, based on a robust methodology and a consequent cohort, to quantify the brain networks dynamics in the BioVRSea paradigm. This work is an important step toward a quantitative evaluation of brain activities during PC and could lay the foundation for developing brain-based biomarkers of PC-related disorders.
Physical and technical basis of Materials Plasma Exposure eXperiment from modeling and Proto-MPEX results*
Authors: Lau C. , Biewer T.M. , Bigelow T.S. , Caneses J.F. , Caughman J.B.O. , Goulding R.H. , Rapp J.
Published: March 2023

The Materials Plasma Exposure eXperiment (MPEX) is a steady-state linear plasma device that will address plasma-material interaction (PMI) science and enable testing of fusion reactor-relevant divertor plasma-facing materials. The MPEX source concept consists of a helicon plasma source to generate the plasma, electron cyclotron heating (ECH) for electron heating, and ion cyclotron heating (ICH) for ion heating. The MPEX source plasma is then transported axially to the PMI material target region to test material samples in fusion reactor-relevant divertor conditions. This paper will summarize the physical and technical basis of MPEX. The paper will first define the MPEX parameters and scenarios at the target relevant to PMI science for various fusion reactor-relevant divertor conditions and show plasma transport modeling results to set the MPEX source parameters. Recent experimental and modeling results from Proto-MPEX, a short-pulse experiment to develop the plasma production, heating, and transport physics for MPEX, will be shown. From these results, it will be shown that MPEX can reach its desired scenarios. The MPEX physical and technical basis will also determine important functional requirements for magnetic field, radiofrequency (RF) power, RF frequency, and neutral pressure in the helicon, ECH, ICH, and PMI regions that are required to achieve the desired MPEX scenarios. The necessity for key in-vessel components such as skimmers, limiters, and microwave absorbers will also be highlighted.
The analysis and experimental research of ultrahigh vacuum ConFlat-type flange joints applied in accelerator and space technology
Authors: Davtyan A. , Isunts H. , Dekhtiarov V. , Vardanyan A. , Avagyan V. , Mkrtchyan T.
Published: March 2023

Finite element analysis (FEA) of ultrahigh vacuum
ConFlat-type flange joints for both Wheeler's and CERN's models were
carried out. These models differ in the angle of inclination between
the two shelves of knife-edge. The main value of this research is a
computer simulation for deformable flanges and gaskets because all
analyses before this have been done for absolutely rigid flanges
(non-deformable flanges) and deformable gaskets. The analysis
variable parameters are the radius of rounding at the tip of the
knife-edge (0.05 … 0.2 mm), the angle between the shelves
forming the knife-edge (70° and 90°) and the
material properties of the copper ring (annealed and 1/4
hard). The calculation of bolted connections for tightening the
flanges was also carried out as the experience has shown that during
the tightening of bolts, they reach the yield point and begin to
deform plastically. That leads to incomplete tightening of the
flanges and, therefore incomplete sealing of the joint. The
experimental research of the flanges tightening and the comparison
with computer simulation results were carried out.
Development of CMOS dosimetry in proton minibeams for enhanced QA and primary standard absorbed dose calorimetry
Authors: Flynn Samuel , Allport Philip , De Marzi Ludovic , Green Stuart , Homer Michael , Lee Nigel , Ortiz Ramon , Patriarca Annalisa , Prezado Yolanda , Thomas Russell , Price Tony
Published: March 2023

Performing accurate and reliable dosimetry in spatially
fractionated beams remains a significant challenge due to the steep
dose gradients and microscopic scale of features. This results in
many conventional detectors and instrumentation being unsuitable for
online dosimetry, necessitating frequent offline validation using
radiochromic film.

In this study, the use of a Complementary Metal-Oxide-Semiconductor
(CMOS) detector for evaluation of relative real-time dosimetry of
proton minibeam radiation therapy (pMBRT) was investigated. The
linearity of the CMOS detector was investigated by varying the
proton beam current, with a comparison to a PTW 34001 Roos
ionisation chamber used to carry out an independent check. It was
found that the relative peaks and valleys of the pMBRT beam could be
measured, with results comparable to EBT3XD film. The high
sensitivity of the CMOS detector meant it was able to measure dose
profiles from peak to valley regions, something not possible with
the EBT3XD. The CMOS detector was compared to the treatment
delivery log files, with correlation in beam position seen as the
beam is scanned along each slit, but not across; and agreement in
beam intensity, with the CMOS detector able to observe beam
interruptions.

Lastly, the CMOS detector was used in conjunction with the
NPL primary-standard proton calorimeter (NPL PSPC) for a preliminary
study on combining the NPL PSPC with high resolution temporal
information about the incident pMBRT beam. The ultimate aim of this
approach is to facilitate detailed thermal modelling to reduce the
overall uncertainty in the absolute dose measured from the
calorimeter. In these experiments, saturation in the CMOS pixels
prevented further thermal modelling of the radiation induced heat
flow, however the instantaneous dose rate was observed to be
comparable with the predicted NPL PSPC response obtained by masking
the CMOS detector.
Test beam measurement of ATLAS ITk Short Strip module at warm and cold operational temperature
Authors: Arling J.-H , Becot C , Buchanan E , Dopke J , Gallop B , Kaplon J , Keller J.S , Kroll J , Li Y , Li Z , Liu J , Liu Y , Ng S.Y , Privara R , Renardi A , Rodriguez Rodriguez A , Rossi E , Ruehr F , Sawyer C , Sperlich D , Weidberg A.R , Zhang D.F
Published: March 2023

This study is focused on an investigation of the performance
of the Short Strip module developed by the ATLAS Inner Tracker (ITk)
strip collaboration using electron beams of energy 5.4 GeV and
5.8 GeV at the DESY-II Testbeam Facility. The noise at
+30 °C and -30 °C was
measured. The ratio of the two measurements is compared with a
circuit-model calculation. The measured noise at
-30 °C is compared with the maximum noise that
would correspond to an acceptable signal-to-noise ratio after the
expected radiation damage from operation at HL-LHC. The measured
charge distributions at +30 °C and
-30 °C are compared with GEANT4 simulations. The
detection efficiency and noise-occupancy were measured as a function
of threshold at both +30 °C and
-30 °C. The average cluster width was measured
as a function of threshold. Scans of detection efficiency versus
threshold at different delay settings were used to reconstruct the
pulse shape in time. The resulting pulse shape was compared with a
circuit model calculation.
Increased salinity decreases annual gross primary productivity at a Northern California brackish tidal marsh
Authors: Russell Sarah J , Windham-Myers Lisamarie , Stuart-Haëntjens Ellen J , Bergamaschi Brian A , Anderson Frank , Oikawa Patty , Knox Sara H
Published: March 2023

Tidal marshes sequester 11.4–87.0 Tg C yr−1 globally, but climate change impacts can threaten the carbon capture potential of these ecosystems. Tidal marshes occur across a wide range of salinity, with brackish marshes (0.5–18 ppt (parts per thousand)) dominating global tidal marsh extents. A diverse mix of freshwater- and saltwater-tolerant plant and microbial communities has led researchers to predict that carbon cycling in brackish wetlands may be less sensitive to changes in salinity than fresh- or saltwater wetlands. Rush Ranch, a well-monitored brackish tidal wetland of the San Francisco Bay National Estuarine Research Reserve, experiences highly variable annual salinity regimes. Within a five-year period (2014–2018), Rush Ranch experienced particularly extreme drought-induced salinization during the 2014 and 2015 growing seasons. During drought years, tidal channel salinity rose from a 15 year baseline of 4.7 ppt to growing season peaks of 10.3 ppt and 12.5 ppt. Continuous eddy covariance data from 2014 to 2018 demonstrate that during drought summers, gross primary productivity (GPP) decreased by 24%, whereas ecosystem respiration remained similar among all five years. Stepwise linear regression revealed that salinity, not air temperature or tidal height, was the dominant driver of annual GPP. A random forest model trained to predict GPP based on environmental data from low salinity years (i.e. naive to salinization) significantly over predicted GPP in drought years. When growing season salinities were doubled, annual estimates of net ecosystem exchange of CO2 decreased by up to 30%. These results provide ecosystem-scale evidence that increased salinity influences CO2 fluxes dominantly through reductions in GPP. This relationship provides a starting point for incorporating the effect of changes in salinity in wetland carbon models, which could improve wetland carbon forecasting and management for climate resilience.
Identifying historical climate changes in Australia through spatial analogs
Authors: King Andrew D
Published: March 2023

Spatial analogs have previously been used to communicate climate projections by comparing the future climate of a location with an analogous recent climate at a different location which is typically hotter. In this study, spatial climate analogs were computed using observational data to identify and quantify past changes. A sigma dissimilarity metric was computed to compare the recent climates of nine major Australian cities and early 20th century climate across Australia. Evidence is found for climate shifts, particularly in Darwin where temperature variability is lower than in extratropical cities. Analogs designed to capture extremes, including a human health-relevant climate analog, were constructed and these also highlight significant climate shifts. The analogs may also be used to examine extreme events in the context of a reference city climate and identify unusual events. This work demonstrates the utility of climate analogs for monitoring past climate changes and extreme events as well as examining and communicating future change. Care should be taken in interpretation of the movement of analogous climates and the design of analyses, but climate analogs have many potential applications beyond previous uses. Tailored analogs could be studied to communicate climate changes relevant to specific stakeholders.
Effects of large-scale changes in environmental factors on the genesis of Arctic extreme cyclones
Authors: Liu Yujun , He Yijun
Published: March 2023

The Arctic cyclone is an active weather system in the Arctic, and the Arctic extreme cyclone (AEC) strongly influences polar weather. Thus, many studies have focused on the activity of AEC and its relationship with large-scale circulation in the Arctic. In this study, Arctic cyclones were detected using the ERA5 Reanalysis data from 1979 to 2020, and the AECs of cold and warm semesters were defined using the 5th percentile of sea level pressure. An Arctic cyclone genesis index, GPIArctic, is established by using the least square fitting of absolute vorticity, omega, wind shear, and long-wave radiation with Eady growth rate. Our findings show that wind shear and long-wave radiation strongly influence AECs. In the cold semester, the high value of GPIArctic mainly occurs in the south of Greenland, while in the warm semester, the high value of GPIArctic also occurs in northeast Eurasia. The results of the multi-model integration of CMIP6 show that more AECs will be formed in the Arctic in the future (2021–2050), and their seasonal contrast will be stronger in northeast Eurasia.
Crop diversity buffers the impact of droughts and high temperatures on food production
Authors: Renard Delphine , Mahaut Lucie , Noack Frederik
Published: March 2023

Weather extremes like droughts and heat waves are becoming increasingly frequent worldwide, with severe consequences for agricultural production and food security. Although the effects of such events on the production of major crops is well-documented, the response of a larger pool of crops is unknown and the potential of crop diversity to buffer agricultural outputs against weather extremes remains untested. Here, we evaluate whether increasing the diversity of crop portfolios at the country level confers greater resistance to a country’s overall yield and revenues against losses to droughts and high temperatures. To do this, we use 58 years of annual data on weather, crop yields and agricultural revenues for 109 crops in 127 countries. We use the spatial distribution of each crop and their cropping cycle to determine their exposure to weather events. We find that growing greater crop diversity within countries reduces the negative impacts of droughts and high temperatures on agricultural outputs. For drought, our results suggest that the effect is explained not only by crop diversity itself, but also by the sensitivity of the most abundant crops (in terms of harvested areas) to this extreme. Countries dedicating more land to minor, drought-tolerant crops reduce the average sensitivity of country-scale crop portfolios and show greater resistance of yield and revenues to drought. Our study highlights the unexploited potential for putting crop biodiversity to work for greater resilience to weather, specifically in poorer developing countries that are likely to suffer disproportionately from climate change impacts.
Duality cascades and parallelotopes
Authors: Furukawa Tomohiro , Moriyama Sanefumi , Sasaki Hikaru
Published: March 2023

Duality cascades are a series of duality transformations in field theories, which can be realized as the Hanany–Witten transitions in brane configurations on a circle. In the setup of the Aharony–Bergman–Jafferis–Maldacena theory and its generalizations, from the physical requirement that duality cascades always end and the final destination depends only on the initial brane configuration, we propose that the fundamental domain of supersymmetric brane configurations in duality cascades can tile the whole parameter space of relative ranks by translations, hence is a parallelotope. We provide our arguments for the proposal.
The solitary wave, kink and anti-kink solutions coexist at the same speed in a perturbed nonlinear Schrödinger equation
Authors: Zheng Hang , Xia Yonghui
Published: March 2023

Persistence of the traveling wave solutions of a perturbed higher order nonlinear Schrödinger equation with distributed delay is studied by the geometric singular perturbation theory. The solitary wave, kink and anti-kink solutions are proved to coexist simultaneously at the same speed c by combing the Melnikov method and the bifurcation analysis. Interestingly, a new type of traveling wave solution possessing crest, trough and kink (anti-kink) is discovered. Further, numerical simulations are carried out to confirm the theoretical results.
PyXLA: Python x-ray-tracing for Lobster-Eye application
Authors: Nentvich Ondrej , Urban Martin , Hudec Rene
Published: March 2023

Collimation of x-rays is challenging, especially for a wide range of grazing-incidence angles. One of the promising x-ray optics can be a wide-field Lobster-Eye (LE) optics in Schmidt’s arrangement, which raised interest in recent years, and will be considered for simulations and description and is perspective for space missions. This paper introduces a newly developed simulator, PyXLA, written in Python and which evaluates and simulates specific types of x-ray reflective optics, particularly LE optics. The software utilises fundamental ray-tracing principles and, in combination with design, can determine the particular design’s behaviour. The design relies on the mirrors’ arrangements, surface finishing and reflectivity, and the x-ray detector, which catches the rays. This paper describes the newly developed PyXLA software, showing simulator principles and examples of outputs with a discussion of the applicability of results and other future extensions.
Highly-stable optical injection wavelength locking of Er-doped random fiber lasers
Authors: Pang Hai-Yue , Li Zhao-Yun , Zheng Jia-Teng , Yuan Cheng , Zhang Yu-Kun , Tao Zhi-Yong , Fan Ya-Xian
Published: March 2023

A highly-stable and effective Er-doped random fiber laser (RFL) is proposed and experimentally demonstrated based on external optical injection locking technology. By adjusting the optical injected wavelength, the lasing wavelength can be selected precisely and emitted separately within the spectral bandwidth of 1555.5 nm to 1563.5 nm. The wavelength and output power fluctuation are less than 0.004% and 2.9%, respectively, indicating that optical injection locking of the RFL is quite stable over a long time. The optical injection locking technology is used in the half-open cavity incoherent RFL systems based on the random distributed Rayleigh scattering scheme, which provides an effective method to control or select the wavelength emission with high stability in a RFL.
Restoring and tailoring very high dimensional spatial entanglement of a biphoton state transmitted through a scattering medium
Authors: Devaux Fabrice , Mosset Alexis , Popoff Sébastien M , Lantz Eric
Published: March 2023

We report experimental results where a momentum entangled biphoton state with a Schmidt number of a few thousand is retrieved and manipulated when only one photon of the pair is transmitted through a thin scattering medium. For this purpose, the transmission matrix of the complex medium is first measured with a phase-shifting interferometry measurement method using a spatial light modulator (SLM) illuminated with a laser source. From this matrix, different phase masks are calculated and addressed on the SLM to spatially control the focusing of the laser through the complex medium. These same masks are used to manipulate the phase of the biphoton wave function transmitted by the thin diffuser in order to restore and control in the same way the momentum correlations between the far-field images of twin beams issued from strongly spatial-multi-mode spontaneous parametric down conversion.
Progresses on cryo-tribology: lubrication mechanisms, detection methods and applications
Authors: Cui Wenyan , Chen Hongzhan , Zhao Jianxun , Ma Quansheng , Xu Qiang , Ma Tianbao
Published: March 2023

Tribology at cryogenic temperatures has attracted much attention since the 1950s with the acceleration of its applications in high-tech equipment such as cryogenic wind tunnels, liquid fuel rockets, space infrared telescopes, superconducting devices, and planetary exploration, which require solid lubrication for moving parts at low temperatures down to 4 K in cryogenic liquid, gaseous, or vacuum environments. Herein, the research progress regarding cryo-tribology is reviewed. The tribological properties and mechanisms of solid lubricants listed as carbon materials, molybdenum disulfide, polymers, and polymer-based composites with decreasing temperature are summarized. The friction coefficient increases with decreasing temperature induced by thermally activated processes. The mechanism of transfer film formation should be considered as a significant way to enhance the tribological properties of solid lubricants. In addition, applications of solid lubrication on moving parts under cryogenic conditions, such as spherical plain bearings and roller bearings, are introduced. The technology for tribological testing of materials and bearings at cryogenic temperatures is summarized, where the environmental control, motion and loading realization, as well as friction and wear measurement together in a low-temperature environment, result in the difficulties and challenges of the low-temperature tribotester. In particular, novel technologies and tribotesters have been developed for tribotests and tribological studies of solid lubricants, spherical plain bearings, and roller bearings, overcoming limitations regarding cooling in vacuum and resolution of friction measurement, among others, and concentrating on in-situ observation of friction interface. These not only promote a deep understanding of friction and wear mechanism at low temperatures, but also provide insights into the performance of moving parts or components in cryogenic applications.
A scientific portrait of Giorgio Parisi: complex systems and much more
Authors: Cugliandolo Leticia F
Published: March 2023

This article summarises the outstanding scientific career of Giorgio Parisi, who was awarded the 2021 Nobel Prize in Physics, with special emphasis on his contributions to the description of the equilibrium properties of disordered systems.
B2-Net: an artificial intelligence powered machine learning framework for the classification of pneumonia in chest x-ray images
Authors: Abubeker K M , Baskar S
Published: March 2023

A chest x-ray radiograph is still the global standard for diagnosing pneumonia and helps distinguish between bacterial and viral pneumonia. Despite several studies, radiologists and physicians still have trouble correctly diagnosing and classifying pneumonia without false negatives. Modern mathematical modeling and artificial intelligence could help to reduce false-negative rates and improve diagnostic accuracy. This research aims to create a novel and efficient multiclass machine learning framework for analyzing and classifying chest x-ray images on a graphics processing unit (GPU). Researchers initially applied a geometric augmentation using a positional transformation function to the original dataset to enhance the sample size and aid future transfer learning. Models with the best accuracy, area under the receiver operating characteristics (AUROC), F1 score, precision, recall, and specificity are chosen from a pool of nine state-of-the-art neural network models. The best-performing models are then retrained using an ensemble technique using depth-wise convolutions, demonstrating significant improvements over the baseline models employed in this research. With a remarkable 97.69% accuracy, 100% recall, and 0.9977 AUROC scores, the proposed Bek-Bas network (B2-Net) model can differentiate between normal, bacterial, and viral pneumonia in chest x-ray images. A superior model is retrained using the chosen dense convolutional network-160, residual network-121, and visual geometry group network-16 ensemble models. The diagnostic accuracy of the x-ray classification unit is enhanced by the newly designed multiclass network, the B2-Net model. The developed GPU-based framework has been examined and tested to the highest clinical standards. After extensive clinical testing, the final B2-Net model is implemented on an NVIDIA Jetson Nano GPU computer. Healthcare facilities have confirmed the B2-Net is the most effective framework for identifying bacterial and viral pneumonia in chest x-rays.
Perspective on investigation of neurodegenerative diseases with neurorobotics approaches
Authors: Tolu Silvia , Strohmer Beck , Zahra Omar
Published: March 2023

Neurorobotics has emerged from the alliance between neuroscience and robotics. It pursues the investigation of reproducing living organism-like behaviors in robots by means of the embodiment of computational models of the central nervous system. This perspective article discusses the current trend of implementing tools for the pressing challenge of early-diagnosis of neurodegenerative diseases and how neurorobotics approaches can help. Recently, advances in this field have allowed the testing of some neuroscientific hypotheses related to brain diseases, but the lack of biological plausibility of developed brain models and musculoskeletal systems has limited the understanding of the underlying brain mechanisms that lead to deficits in motor and cognitive tasks. Key aspects and methods to enhance the reproducibility of natural behaviors observed in healthy and impaired brains are proposed in this perspective. In the long term, the goal is to move beyond finding therapies and look into how researchers can use neurorobotics to reduce testing on humans as well as find root causes for disease.
Climate change adaptation across the life-course - from pregnancy to adolescence – it’s time to advance the field of climate change and child health
Authors: Helldén Daniel , Ndejjo Rawlance , Sturm Amanda , Persson Ida , Wanyenze Rhoda , Ebi Kristie L , Nilsson Maria , Alfvén Tobias
Published: March 2023

Children are bearing and will continue to bear a high burden from climate change, through direct and indirect pathways. Climate change adaptation interventions are essential to limit the current and projected impacts of climate change on child health. However, the perspective of children and their health with regards to adaptation in research and policy is limited. Ensuring that adaptation interventions are context specific, consider interrelated barriers to implementation and leverage existing structures including multisectoral collaboration is vital. Further, a life-course perspective on child health and well-being could serve as a template for tailoring adaptation interventions to the specific vulnerabilities and needs of specific development periods of the child. A meaningful engagement of children and young persons in the design and implementation of adaptation interventions is essential to increase effectiveness and uptake. With climate change effecting millions of children worldwide, it is high time to put child health at the center of adaptation.
Increased Breast and Colorectal Cancer Risk in Type 2 Diabetes: Awareness Among Adults With and Without Diabetes and Information Provision on Diabetes Websites
Authors: Ashley Laura , Robb Kathryn A , O’Connor Daryl B , Platt Rebecca , Price Mollie , Robinson Olivia , Travis Elizabeth , Lipscombe Lorraine , Ajjan Ramzi , Birch Rebecca
Published: March 2023

Background

People with type 2 diabetes mellitus (T2DM) have a higher risk of developing breast and bowel cancers but are less likely to participate in cancer screening.

Purpose

Two interlinked studies examined public awareness of the fact that T2DM increases breast and bowel cancer risk, and provision of this information on diabetes websites.

Methods

Study-1: phase-1 surveyed awareness of T2DM-increased cancer risk in a nationally-representative British sample aged 50–74 (N = 1,458) and compared respondents with and without T2DM (n = 125 vs. n = 1,305); phase-2 surveyed an additional exclusively T2DM sample (N = 319). Study-2: High-ranking diabetes websites (N = 25) were reviewed to determine the rate of inclusion of cancer risk and cancer screening information in evident sections about diabetes-related health conditions.

Results

A low proportion of respondents were aware that T2DM increases risk of breast (13.7%) and bowel (27.6%) cancers, compared to much higher awareness of other diabetes-related conditions such as sight loss (82.2%) and foot problems (81.8%). Respondents with T2DM were significantly more likely than those without T2DM to be aware of all the surveyed diabetes-related health conditions (e.g., sight loss, OR: 3.14, 95%CI: 1.61–6.15; foot problems, OR: 2.58, 95%CI: 1.38–4.81), except breast (OR: 0.82, 95%CI: 0.46–1.45) and bowel (OR: 0.95, 95%CI: 0.63–1.45) cancer, for which awareness was equally low among people with and without T2DM. Few diabetes websites with a section on diabetes-related health conditions included cancer in this section (n = 4/19), and fewer still included cancer screening among any noted cancer-protective behaviors (n = 2/4).

Conclusions

There is low public awareness that T2DM increases the risk of developing breast and bowel cancers, even among people with T2DM, which may be partly due to limited information provision regarding T2DM-increased cancer risk from diabetes care providers and organizations.
Invited Commentary: Aligning Methodological Research on Pregnancy Weight Gain With the Questions That Matter Most for Public Health Guidelines
Authors: Hutcheon Jennifer A , Platt Robert W
Published: March 2023

The inherent correlation between the total amount of weight gained in pregnancy and the duration of pregnancy creates major methodological challenges in the study of pregnancy weight gain. In this issue (Am J Epidemiol. 2022;191(10):1687–1699), Richards et al. examine the extent to which different measures of pregnancy weight gain (including covariate adjustment for gestational age and standardizing weight gain for gestational duration using a pregnancy weight gain chart) are able to disentangle the effects of low weight gain on perinatal health from the role of younger gestational age at delivery for 3 outcomes: small-for-gestational-age birth, cesarean delivery, and low birth weight. While methodological research to understand how to best disentangle the effects of gestational weight gain from pregnancy duration is valuable, we argue that the practical utility of this type of research would be increased by aligning the specific research questions more closely with health outcomes on which evidence is most needed—those not considered in current weight gain guidelines due to lack of high-quality evidence (such as pre-eclampsia and stillbirth). Further, evaluations of weight gain charts should separate out the potential for bias introduced by the use of a normative chart per se from the use of a chart unsuitable for the study population.
Invited Commentary: Concealed Carrying of Firearms, Public Policy, and Opportunities for Mitigating Harm
Authors: Matthay Ellicott C , Kagawa Rose M C
Published: March 2023

In the last 30 years, 25 US states have relaxed laws regulating the concealed carrying of firearms (concealed-carry weapons (CCW) laws). These changes may have substantial impacts on violent crime. In a recent study, Doucette et al. (Am J Epidemiol. 2023;192(3):342–355) used a synthetic control approach to assess the effects of shifting from more restrictive “may/no-issue” CCW laws to less restrictive “shall-issue” CCW laws on homicides, aggravated assaults, and robberies involving a gun or committed by other means. The study adds to the evidence that more permissive CCW laws have probably increased rates of firearm assault in states adopting these laws. Importantly, this study is the first to identify that specific provisions of shall-issue CCW laws—including denying permits to persons with violent misdemeanor convictions, a history of dangerous behavior, or “questionable character” and live-fire training requirements—may help mitigate harms associated with shall-issue CCW laws. These findings are timely and salient given the recent Supreme Court ruling striking down a defining element of may-issue laws. This thorough study offers actionable results and provides a methodological model for state firearm policy evaluations. Its limitations reflect the needs of the field more broadly: greater focus on racial/ethnic equity and within-state variation, plus strengthening the data infrastructure on firearm violence and crime.
Evaluation of Phosphatidylethanol Elimination in Alcohol Use Disorder Patients Undergoing Withdrawal Treatment
Authors: Stöth Frederike , Weinmann Wolfgang , Soravia Leila Maria , Pfeifer Philippe
Published: March 2023

Aims

Phosphatidylethanol (PEth) is used to monitor alcohol consumption in alcohol use disorder (AUD). In this study, we aim to evaluate the elimination time of PEth with regard to the clinically established 200 and 20 ng/ml cutoffs for PEth 16:0/18:1.

Methods

Data from 49 patients undergoing treatment for AUD were evaluated. PEth concentrations were measured at the beginning and repeatedly during the treatment period of up to 12 weeks to monitor the elimination of PEth. We evaluated the time in weeks until the cutoff concentrations of <200 and <20 ng/ml were achieved. The correlation between the initial PEth concentration and the number of days until the PEth concentration had dropped below 200 and 20 ng/ml was assessed by calculating Pearson’s correlation coefficients.

Results

The initial PEth concentrations ranged from <20 to >2500 ng/ml. In 31 patients, the time until the cutoff values were reached could be documented. Even after 6 weeks of abstinence, PEth concentrations above the cutoff of 200 ng/ml could still be detected in two patients. A strong significant positive correlation was found between the initial PEth concentration and the time required to drop below the two cutoffs.

Conclusion

A waiting period of more than 6 weeks after declared abstinence should be granted for individuals with AUD before using only one single PEth concentration to assess the consumption behavior. However, we recommend to always use at least two PEth concentrations for the evaluation of alcohol-drinking behaviors in AUD patients.
NeuroPred-PLM: an interpretable and robust model for neuropeptide prediction by protein language model
Authors: Wang Lei , Huang Chen , Wang Mingxia , Xue Zhidong , Wang Yan
Published: March 2023

Neuropeptides are a diverse and complex class of signaling molecules that regulate a variety of biological processes. Neuropeptides provide many opportunities for the discovery of new drugs and targets for the treatment of a wide range of diseases, and thus, computational tools for the rapid and accurate large-scale identification of neuropeptides are of great significance for peptide research and drug development. Although several machine learning-based prediction tools have been developed, there is room for improvement in the performance and interpretability of the proposed methods. In this work, we developed an interpretable and robust neuropeptide prediction model, named NeuroPred-PLM. First, we employed a language model (ESM) of proteins to obtain semantic representations of neuropeptides, which could reduce the complexity of feature engineering. Next, we adopted a multi-scale convolutional neural network to enhance the local feature representation of neuropeptide embeddings. To make the model interpretable, we proposed a global multi-head attention network that could be used to capture the position-wise contribution to neuropeptide prediction via the attention scores. In addition, NeuroPred-PLM was developed based on our newly constructed NeuroPep 2.0 database. Benchmarks based on the independent test set show that NeuroPred-PLM achieves superior predictive performance compared with other state-of-the-art predictors. For the convenience of researchers, we provide an easy-to-install PyPi package (https://pypi.org/project/NeuroPredPLM/) and a web server (https://huggingface.co/spaces/isyslab/NeuroPred-PLM).