bluuebunny/crossref_metadata_2025 huggingface dataset:
Simultaneous measurement of particle size distribution and mixing ratio based on Monte Carlo ultrasonic attenuation model
Authors: Zhang Shiwei , Su Geyi , Niu Gege , Chen Jingwen , Su Mingxu
Published: January 2025

Mixed particle systems are commonly employed in industrial processes, where the characterization of particle size parameters and mixing ratio can frequently serve as key indicators in process control and production optimization. A Monte Carlo (MC) model was developed to numerically predict and study the ultrasonic attenuation spectrum characteristics in the polymethyl methacrylate (PMMA)-glass aqueous suspension, and together with the particle swarm optimization (PSO) algorithm, to handle the inverse problem in solving the particle size, distribution width, and mixing ratio. The results of the numerical simulations indicate that there exists a linear relationship between the attenuation coefficient and the mixing ratio, with the particle size exerting a significant influence. Furthermore, the multi-parameter simultaneous inversion also yielded calculation deviations of less than 1%, 3%, and 6% for the mixing ratio, characteristic diameter, and distribution width, respectively, in comparison to their given values. Afterward, a series of experiments were conducted to quantify the particle size and mixing ratio through the analysis of ultrasonic spectra. In spherical PMMA-glass aqueous suspensions, the measurement error for the mixing ratio and particle size parameters are found to be less than 7% and 10%, respectively, when compared to the image method and the given values. Nevertheless, the measurement errors are slightly increased in a non-spherical mixed particle system, where the volume median diameter and mixing ratio are still less than 10%. The MC modeling and PSO algorithm offer the potential to characterize particle size and mixing ratio for mixed particle systems in industrial applications.
The role of SOL plasma in the confinement of NBI fast ions in W7-X
Authors: Kiviniemi T P , Kurki-Suonio T , Lazerson S , Äkäslompolo S , Ollus P , Sanchis L , Kulla D ,   the W7-X Team
Published: January 2025

The impact of the scrape-off layer (SOL) plasma on deposition, confinement and losses of neutral beam injected fast ions was investigated in W7-X plasma. The effect of SOL width, density, temperature profiles, radial electric field, and charge–exchange reactions (CX) was explored. Ionization and slowing down partly counterbalance each other, as slowing down in cold SOL plasma compensates for ionization effects in radially decaying model profiles. However, the effect of SOL plasma on more vulnerable steel components is mitigated over a wide range of different profiles, because for those components the collisionality effect overrules the effect of SOL on ionization. The effect of the radial electric field is mitigated for steel components in the experimentally observed direction of the field. The effect of CX reactions is shown to lead to a widely spread low power load distribution with no clear effect on peak load. Statistical challenges caused by hugely varying triangle sizes in the discretization of walls are discussed.
Modelling of ETG turbulent transport in the TCV pedestal
Authors: Krutkin O , Chapman-Oplopoiou B , Frassinetti L , Brunner S , Coda S , Labit B ,   the TCV team,   the EUROfusion Tokamak Exploitation Team
Published: January 2025

Results of the first gyrokinetic simulations of the TCV pedestal are presented. Two discharges at varying levels of gas puffing are considered as input parameters for the local GENE simulations. Linear and nonlinear simulations are carried out for electron scale turbulence to determine the role of the electron temperature gradient (ETG) mode in the pedestal transport. The heat flux associated with ETG is found to be negligible compared to the total experimental electron heat flux at lower gas puff. At higher gas puff, computed heat flux was find to account for experimental values, demonstrating the importance of the ETG-driven transport in this case. Additional simulations are carried out with modified density profiles to investigate the difference between the two discharges. The change of the electron heat flux is found to be associated with the transition from slab- to toroidal-ETG due to the reduction of the normalized density gradient in the pedestal at the higher gas puffing.
Two-step inertial ADMM for the solution of nonconvex nonsmooth optimization problems with nonseparable structure
Authors: Dang Yazheng , Kun Xu , Lu Jinglei
Published: January 2025

In this paper, we propose an algorithmic framework called two-step inertial alternating direction methods of multipliers (TIADMM) to solve a class of nonconvex and nonsmooth optimization problems with nonseparable structure. The new algorithm adds two-step inertial effect to each subproblem and introduces three relaxed terms into the dual update step to improve the convergence. This work employs two assumptions; (1) the auxiliary function satisfies the Kurdyka-Łojasiewicz property, and (2) the parameters satisfy some conditions to prove the global convergence of the sequence generated by the algorithm. Furthermore, the algorithm is extended to a linearization vision for solving nonconvex optimization problems. Finally, tests are conducted on two numerical examples to show the effectiveness.
Dynamical study of the reaction of N+ ions with O2 neutrals
Authors: Swaraj Dasarath , Judy Jerin , Zappa Fabio , Viggiano Albert A , Gerlich Dieter , Wester Roland
Published: January 2025

The ion-molecule reaction N+ + O2 has been investigated experimentally using crossed beam velocity map imaging in the collision energy range from 0.15 eV to 3.0 eV. From the differential scattering cross sections, information on the branching ratios, the electronic states and vibrational levels populated in the two product channels, O

2

+

+ N and NO+ + O, have been obtained. These data are compared with previous results obtained using a rotatable ion source setup developed many years ago at the University of Freiburg, Germany. Furthermore, a small fraction of NO+ products populate excited electronic states as observed in chemiluminescence measurements.
New results about controllability and stability of ψ-Caputo-type stochastic fractional integro-differential systems with control delay
Authors: Panneer Selvam A , Sivalingam S M , Govindaraj V
Published: January 2025

This study explores the controllability and stability criteria for the fractional integro-differential stochastical systems with control delay employing the Ψ-Caputo-type fractional derivative (Ψ-CTFD) of order σ ∈ (0, 1). The necessary and sufficient conditions for the controllability of linear stochastical systems are obtained by utilizing the positive definiteness of the Grammian matrix. The sufficient conditions for the controllability criteria of semilinear and integro-differential stochastical systems are derived by employing Banach’s contraction principle. The sufficient conditions for the stability of integro-differential stochastical systems are derived from the Hyer’s-Ulam stability criteria. Additionally, a few examples and appropriate graphical representations are included in the work to help understand the theoretical conclusions.
Application of fractional shifted vieta-fibonacci polynomials in nonlinear reaction diffusion equation with variable order time-space fractional derivative
Authors: Hassani Hossein , Avazzadeh Zakieh , Turan-Dincel Arzu , Katani Roghayeh
Published: January 2025

In this article, an accurate optimization algorithm based on new polynomials namely generalized shifted Vieta-Fibonacci polynomials (GSVFPs) is employed to solve the nonlinear variable order time-space fractional reaction diffusion equation (NVOTSFRDE). The algorithm combines GSVFPs, new variable order fractional operational matrices in the Caputo sense, and the Lagrange multipliers to achieve the optimal solution. First, the solution of the NVOTSFRDE is approximated as a series of GSVFPs with unknown coefficients and parameters. Then, the Lagrange multipliers method is adopted so that the NVOTSFRDE can be transformed into a class of nonlinear algebraic system of equations and we solve these equations using MATLAB and MAPLE software. Solving this system and substituting the coefficients and parameters into the approximation of the guessed functions, the solution of the NVOTSFRDE is obtained. The convergence analysis of the approach are discussed. The accuracy of the algorithm is verified through error analysis and mathematical examples. The accuracy of the new method is higher than that of the exciting method. The reconstruction results demonstrate that the proposed optimization algorithm is efficient for the NVOTSFRDE, and the algorithm is also convergent.
A search for the fine-structure constant evolution from fast radio bursts and type Ia supernovae data
Authors: Lemos Thais , Gonçalves Rodrigo , Carvalho Joel , Alcaniz Jailson
Published: January 2025

The search for a space-time variation of the fundamental constants has been explored over the years to test our physical theories. In this paper, we use the dispersion measure (DM) of fast radio bursts (FRB) combined with type Ia supernovae (SNe) data to investigate a possible redshift evolution of the fine-structure constant (α), considering the runaway dilaton scenario, which predicts Δα/α = - γln(1+z), where γ is a constant proportional to the current value of the coupling between the dilaton field and hadronic matter. We derive all the relevant expressions for the DM dependence concerning the fine-structure constant and constrain the parameter γ from measurements of 17 well-localized FRBs and 1048 SNe data from the Pantheon compilation. We also use Monte Carlo simulations to forecast the constraining power of larger samples of FRB measurements for data sets with N = 500 and N = 1000 points. We found that the uncertainty on γ can be improved by one order of magnitude and that limits on Δα/α beyond σ ∼ 10-2 will depend crucially on better control of statistical and systematic uncertainties of upcoming FRB data.
Hyperons during proto-neutron star deleptonization and the emission of dark flavoured particles
Authors: Fischer Tobias , Camalich Jorge Martin , Kochankovski Hristijan , Tolos Laura
Published: January 2025

Complementary to high-energy experimental efforts, indirect astrophysical searches of
particles beyond the standard model have long been pursued. The present article follows the
latter approach and considers, for the first time, the self-consistent treatment of the energy
losses from dark flavoured particles produced in the decay of hyperons during a core-collapse
supernova (CCSN). To this end, general relativistic supernova simulations in spherical symmetry
are performed, featuring six-species Boltzmann neutrino transport, and covering the long-term
evolution of the nascent remnant proto-neutron star (PNS) deleptonization for several tens of
seconds. A well-calibrated hyperon equation of state (EOS) is therefore implemented into the
supernova simulations and tested against the corresponding nucleonic model. It is found that
supernova observables, such as the neutrino signal, are robustly insensitive to the appearance of
hyperons for the simulation times considered in the present study. The presence of hyperons
enables an additional channel for the appearance of dark sector particles, which is considered at
the level of the Λ hyperon decay. Assuming massless particles that escape the PNS after
being produced, these channels expedite the deleptonizing PNS and the cooling behaviour. This, in
turn, shortens the neutrino emission timescale. The present study confirms the previously
estimated upper limits on the corresponding branching ratios for low and high mass PNS, by
effectively reducing the neutrino emission timescale by a factor of two. This is consistent with
the classical argument deduced from the neutrino detection associated with SN1987A.
The study of barocaloric effect in ferroelastic Pb3(VO4)2
Authors: Cheng Pengtao , Chen Zuhua , Zhang Chengliang , Zhang Zhengming , Li Bing , Wang Dunhui
Published: January 2025

The barocaloric effect is considered as one of the most promising refrigeration with the potential to replace traditional gas compression refrigeration. One of the main obstacles to the application of barocaloric materials lies in the requirement for high driving pressures. In this paper, we report on the barocaloric effect of Pb3(VO4)2, which exhibits a ferroelastic transition from a high-temperature trigonal structure to a low-temperature monoclinic structure at 357 K, accompanied by a substantial volume change. The entropy change induced by hydrostatic pressure can reach up 14 J·kg-1·K-1 under a relatively low pressure of 80 MPa. This work is expected to expand the selection range of barocaloric materials.
Frequency shifts of high-order harmonics from ZnO crystals by the chirped laser pulses
Authors: Zhao Yu , Liu Xiao-Jin , Wang Shuang , Huo Xiao-Xin , Xing Yun-He , Zhang Jun
Published: January 2025

We investigate theoretically the effects of chirped laser pulses on high-order harmonic generation (HHG) from solids. We find that the harmonic spectra display redshifts for the driving laser pulses with negative chirp and blueshifts for those with positive chirp, which is due to the change in the instantaneous frequency of the driving laser for the different chirped pulses. The analysis of the crystal-momentum-resolved (kresolved) HHG reveals that the frequency shifts are equal for the harmonics generated by different crystal momentum channels. The frequency shifts in the cutoff region are larger than the shifts in the plateau region. With the increase of the absolute value of the chirp parameters, the frequency shifts of HHG become more significant, leading to the shifts from odd- to even-order harmonics. We also demonstrate that the frequency shifts of harmonic spectra are related to the duration of the chirped laser field, but are insensitive to the laser intensity and dephasing time.
Decoding speech intent from non-frontal cortical areas
Authors: Prakash Prashanth Ravi , Lei Tianhao , Flint Robert D , Hsieh Jason K , Fitzgerald Zachary , Mugler Emily , Templer Jessica , Goldrick Matthew A , Tate Matthew C , Rosenow Joshua , Glaser Joshua , Slutzky Marc W
Published: January 2025

Objective. Brain machine interfaces (BMIs) that can restore speech have predominantly focused on decoding speech signals from the speech motor cortices. A few studies have shown some information outside the speech motor cortices, such as in parietal and temporal lobes, that also may be useful for BMIs. The ability to use information from outside the frontal lobe could be useful not only for people with locked-in syndrome, but also to people with frontal lobe damage, which can cause nonfluent aphasia or apraxia of speech. However, temporal and parietal lobes are predominantly involved in perceptive speech processing and comprehension. Therefore, to be able to use signals from these areas in a speech BMI, it is important to ascertain that they are related to production. Here, using intracranial recordings, we sought evidence for whether, when and where neural information related to speech intent could be found in the temporal and parietal cortices Approach. Using intracranial recordings, we examined neural activity across temporal and parietal cortices to identify signals associated with speech intent. We employed causal information to distinguish speech intent from resting states and other language-related processes, such as comprehension and working memory. Neural signals were analyzed for their spatial distribution and temporal dynamics to determine their relevance to speech production. Main results. Causal information enabled us to distinguish speech intent from resting state and other processes involved in language processing or working memory. Information related to speech intent was distributed widely across the temporal and parietal lobes, including superior temporal, medial temporal, angular, and supramarginal gyri. Significance. Loss of communication due to neurological diseases can be devastating. While speech BMIs have made strides in decoding speech from frontal lobe signals, our study reveals that the temporal and parietal cortices contain information about speech production intent that can be causally decoded prior to the onset of voice. This information is distributed across a large network. This information can be used to improve current speech BMIs and potentially expand the patient population for speech BMIs to include people with frontal lobe damage from stroke or traumatic brain injury.
Nadaraya–Watson kernel smoothing as a random energy model
Authors: Zavatone-Veth Jacob A , Pehlevan Cengiz
Published: January 2025

Precise asymptotics have revealed many surprises in high-dimensional regression. These advances, however, have not extended to perhaps the simplest estimator: direct Nadaraya–Watson (NW) kernel smoothing. Here, we describe how one can use ideas from the analysis of the random energy model (REM) in statistical physics to compute sharp asymptotics for the NW estimator when the sample size is exponential in the dimension. As a simple starting point for investigation, we focus on the case in which one aims to estimate a single-index target function using a radial basis function kernel on the sphere. Our main result is a pointwise asymptotic for the NW predictor, showing that it re-scales the argument of the true link function. Our work provides a first step towards a detailed understanding of kernel smoothing in high dimensions.
Plasma displacement calculation for TT-1 device based on multiple magnetic probes fitting methods
Authors: Shu Shuangbao , Zhang Shurui , Ding Yongzhi , Luo Jiarong , Lang Xianli
Published: January 2025

The HT-6M device has been upgraded and rebranded as the
Thailand Tokamak 1 (TT-1), which has been reinstalled and is now
operational in Thailand. In tokamak discharge experiments, precise
monitoring of plasma position and the implementation of effective
feedback control are essential for ensuring the stability of the
high-temperature plasma. Accurate calculation of plasma displacement
is critical to the success of the experiment. This paper presents a
method for calculating plasma displacement through a multi-probe
fitting technique, utilizing data from twelve magnetic field
probes. Initially, magnetic field signals generated by the plasma
are collected via multiple magnetic field probes installed
poloidally outside the vacuum chamber, coupled with corresponding
signal conditioning and integration circuits, with each probe
undergoing calibration. Subsequently, during tokamak discharges,
interference signals from the toroidal field coils, ohmic heating
coils, and vertical field coils are generated by the magnetic system
and corrected through a detailed calibration process. Lastly, the
distances between the probes and the plasma are computed using data
from the magnetic field probes, which are arranged in a circular
configuration. The least squares method is employed to formulate a
residual equation for fitting the actual plasma displacement. The
effectiveness of this approach was validated through experimental
data from the TT-1 device, demonstrating that the calculated plasma
displacement exhibits a consistent trend with the CCD video
recordings. This multi-probe displacement calculation method enables
precise control of plasma displacement, thereby providing
theoretical support for tokamak experiments and establishing a
foundation for future experimental operations and data analysis.
Changes in soil water content and lateral flow exert large effects on soil thermal dynamics across Alaskan landscapes
Authors: Liu Xiangyu , Zhuang Qianlai , Liao Chang , Jorgenson M Torre
Published: January 2025

Both lateral surface and subsurface water flow affect soil moisture dynamics, yet most land surface models only solve subsurface water movement vertically. Here, we use a 3D ecosystem model that considers both land surface and subsurface hydrologic processes to simulate soil moisture, which is then used to drive a 1-D vertical soil thermal model to simulate the soil moisture effects on soil thermal dynamics in central Alaska. Our coupled model improves soil temperature (ST) estimates by 43.5% in comparison with observational data. Soil moisture has little effect on ST during the wet season (−1.5%) and a substantial influence during the dry season (60%). Spatially, water lateral flow has significant impacts on both soil moisture and ST, causing model estimates for thawed areas in the transition season to increase by ∼10% in the study area. Our results highlight the importance of considering dynamical soil moisture, as well as lateral flow effects, on soil thermal dynamics in permafrost regions.
Eco-benign synthesis of multifunctional silver nanoparticles using leptochloa fusca for enhanced biomedical and catalytic applications
Authors: Khan Riaz Ahmad , Khan Hidayat Ullah , Shahnaz  , Tahir Kamran , Refat Moamen S , Adam Abdel Majid A , Alsuhaibani Amnah Mohammed
Published: January 2025

The synthesis of nanomaterials with diverse biomedical and catalytic potentials is crucial in this era of rapidly advancing technology and increasing demand for innovative solutions in medicine and catalysis. The current study explores Leptochloa fusca aqueous extract for the eco-benign and cost-effective green synthesis of multifunctional silver nanoparticles (LF-AgNPs) with enormous potential of biomedical and catalytic applications. The bio-fabricated nanoparticles were characterized employing various analytical techniques including UV–Visible, FTIR, XRD, EDX, SEM and TGA. These analyses confirmed the synthesis, chemical composition, size, morphology, crystalline nature and thermal stability of LF-AgNPs. The surface plasmon resonance of LF-AgNPs was recorded at 432–436 nm and the particle size measured via SEM analysis was noted to be 30 to 200 nm. The synthesized LF-AgNPs were examined for their biomedical and catalytic applications. The binding affinity of LF-AgNPs with ssDNA and BSA was ratified spectroscopically by UV–Visible and FTIR techniques. The hyperchromism observed in the UV–vis absorption spectra, as well as changes in the FTIR spectra of ssDNA and BSA upon interaction with LF-AgNPs, indicate the formation of LF-AgNPs–ssDNA and LF-AgNPs–BSA complexes. This type of binding results in conformational changes in ssDNA and BSA structures and therefore LF-AgNPs hold potential for numerous applications like drug delivery, anticancer agents and receptor targeting. The biosynthesized LF-AgNPs were also found to have effective antioxidant (70%) and H2O2 scavenging (77%) properties. Additionally, the agar well diffusion technique demonstrated efficient antibacterial efficacy for LF-AgNPs against both Gram +ve (Staphylococcus aureus) and Gram -ve (Klebsiella pneumoniae) strains with ZOI values of 19 ± 0.7 mm and 19 ± 0.5 mm, respectively. LF-AgNPs efficiently catalysed the reduction of methylene blue in less than 9 min, using NaBH4 as a reducing agent. These findings suggest that LF-AgNPs exhibit significant capability for integration into catalytic process of MB reduction and selected biomedical applications.
Modelling and validation of a 6 MV compact linear accelerator via Monte Carlo simulation using Geant4 Application for Tomographic Emission (GATE)
Authors: Limbaco Maynard E , Toledo Franklin U , Tondo Renna Mae V , Nawang Salasa A
Published: January 2025

Objective. To accurately model and validate the 6 MV Elekta Compact linear accelerator using the Geant4 Application for Tomographic Emission (GATE). In particular, this study focuses on the precise calibration and validation of critical parameters, including jaw collimator positioning, electron source nominal energy, flattening filter geometry, and electron source spot size, which are often not provided in technical documentation. Methods. Simulation of the Elekta CompactTM 6 MV linear accelerator was performed using the Geant4 Application for Tomographic Emission (GATE) v.9.1. A 50 cm × 50 cm × 50 cm water phantom was irradiated with a source-to-surface distance of 100 cm. Percentage Depth Dose Profile (PDD) and Lateral Dose Profile (Crossplane and Inplane) were assessed as reference dose measurements. The half-length field difference (FHLD) method was introduced to optimize the jaw collimator setup. Gamma index analysis was used to quantitatively assess the accuracy of the simulated dosimetry data in relation to the actual dose measurements. Results. Crucial parameters of the Linac Head have been successfully optimized. The validation achieved Gamma-Index acceptance rates of 97.93% for the Depth Dose profile, 100% for the Crossplane (X) Dose Profile, and 93.98% for the Inplane (Y) Dose Profile, all meeting the 1%/1 mm Gamma-Index criteria. Conclusion. The simulation and calibration of the Elekta Compact Linac have achieved a reliable model with high fidelity in dosimetry calculations which could pave the way for the future development and application of new techniques using Elekta CompactTM Linear Accelerator.
The impact of digital intelligence on energy-intensive firms’ green transformation
Authors: Hao Mengge , Zhang Feng , Xu Shichun , Dong Zhixin , He Zhengxia
Published: January 2025

The green transformation of energy-intensive firms is expected to make an outstanding contribution to global carbon neutrality. Digital intelligence, the new phase of digitalization, has injected fresh momentum into corporate green development. Most previous studies focused on the green effect of digitalization using statistical data from listed firms, and failed to make detailed exploration on the impact of digital intelligence on energy-intensive firms’ green transformation based on survey data. Based on empowerment theory and technology-organization-environment theory, this study proposed a three-dimensional concept of digital intelligence, including digital intelligence technology, digital intelligence organization and digital intelligence environment. Using survey data from 348 energy-intensive firms in China, this paper employed the structural equation modeling and bootstrap test to investigate the influence of digital intelligence on energy efficiency transformation and green emission transformation, and the mediating effect of energy management. The results indicate that digital intelligence technology, digital intelligence organization and digital intelligence environment promote energy efficiency and green emission of energy-intensive firms. Energy management is the key to the green transformation of energy-intensive firms in the context of digital intelligence. Specifically, energy saving literacy, energy audit, and energy use structure optimization play the positive mediating effects between digital intelligence and energy-intensive firms’ green transformation. It is worth noting that the mediating effect of energy saving literacy between digital intelligence environment and energy-intensive firms’ green transformation is insignificant. These findings provide policy and practice references for the government and practitioners in energy-intensive industries to leverage digital intelligence to promote green sustainability.
Climate response to stratospheric aerosol injection during the Harmattan season in West Africa
Authors: Nkrumah Francis , Quenum Gandome Mayeul Leger Davy , Quagraine Kwesi A , Tilmes Simone , Klutse Nana Ama Browne , Dommo Atanas , Koffi Hubert A , Essien Patrick , Bediako Rebecca
Published: January 2025

Stratospheric Aerosol Injection (SAI), a proposed climate intervention, aims to reduce the amount of solar radiation reaching the Earth’s surface by increasing the reflectivity of the atmosphere, thereby offsetting the warming effect of greenhouse gases. During the Harmattan season (December–February) in West Africa (WA), a natural meteorological phenomenon injects dust and sand particles into the atmosphere, leading to a cooling effect. In this study, we investigate the influence of SAI on West African surface temperature, dust, and other meteorological variables using the Whole Atmosphere Community Climate Model under the Shared Socioeconomic Pathway 2-4.5 scenario and the Assessing Responses and Impacts of Solar Climate Intervention on the Earth system with SAI (ARISE-SAI) dataset. Our findings indicate that SAI intervention significantly impacts the projected surface temperatures, specific humidity, and wind speed changes during the Harmattan season. Compared to a future without SAI, the intervention shows a significant net cooling effect over most parts of WA during the mid-future period (2050–2069). Also, SAI intervention significantly decreases moisture content over southern and northern WA in the near-future (2035–2054), mainly due to the net cooling effects over WA, when compared to a future without SAI. This feature is enhanced in the mid-future period. The cooling effects of SAI are likely to reduce the air’s capacity to hold moisture, leading to lower specific humidity levels relative to a future without SAI. It could also have negative implications, such as increased aridity compared to a future without SAI in the northern and central regions of WA. These findings also highlight the potential for SAI to improve air quality in certain areas but also underscore the need for careful consideration of implementation strategies and possible trade-offs. The changes from SAI observed are specific to the ARISE simulation and may differ from other SAI simulations.
Escalated begging does not compromise nestling health
Authors: Parejo-Pulido Daniel , Redondo Tomás , Casquero Silvia , Pérez-Rodríguez Lorenzo
Published: January 2025

A widely accepted explanation for the reliability of offspring begging signals assumes a differential benefit model balanced by direct viability costs independent of offspring nutritional condition. However, supporting evidence for this idea is inconclusive and often hampered by methodological limitations, including differential stimulation protocols and reliance on single, potentially biased markers of nestling health. This study tested the existence of direct, intrinsic, and condition-independent allocation trade-offs between begging and body mass, immunity and oxidative stress by manipulating the begging effort of spotless starling (Sturnus unicolor) nestlings while maintaining constant food intake. We addressed potential problems of previous experimental protocols, ensuring uniform stimulation levels and evaluating multiple immune and oxidative markers. We observed no significant effects of experimentally increased begging effort in any of the 14 physiological markers analyzed, with 95% confidence intervals of effect sizes consistently including zero or one (for the lysis capacity of plasma), indicating no biologically relevant effects. Overall, our findings suggest no physiological trade-offs associated with intense begging.
QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics
Authors: Wang Zexuan , Zhan Qipeng , Yang Shu , Mu Shizhuo , Chen Jiong , Garai Sumita , Orzechowski Patryk , Wagenaar Joost , Shen Li
Published: January 2025

Single-cell technologies have enabled the high-dimensional characterization of cell populations at an unprecedented scale. The innate complexity and increasing volume of data pose significant computational and analytical challenges, especially in comparative studies delineating cellular architectures across various biological conditions (i.e. generation of sample-level distance matrices). Optimal Transport is a mathematical tool that captures the intrinsic structure of data geometrically and has been applied to many bioinformatics tasks. In this paper, we propose QOT (Quantized Optimal Transport), a new method enabling efficient computation of sample-level distance matrix from large-scale single-cell omics data through a quantization step. We apply our algorithm to real-world single-cell genomics and pathomics datasets, aiming to extrapolate cell-level insights to inform sample-level categorizations. Our empirical study shows that QOT outperforms existing two OT-based algorithms in accuracy and robustness when obtaining a distance matrix from high throughput single-cell measures at the sample level. Moreover, the sample level distance matrix could be used in the downstream analysis (i.e. uncover the trajectory of disease progression), highlighting its usage in biomedical informatics and data science.
Identifying cancer prognosis genes through causal learning
Authors: Wu Siwei , Yin Chaoyi , Wang Yuezhu , Sun Huiyan
Published: January 2025

Accurate identification of causal genes for cancer prognosis is critical for estimating disease progression and guiding treatment interventions. In this study, we propose CPCG (Cancer Prognosis’s Causal Gene), a two-stage framework identifying gene sets causally associated with patient prognosis across diverse cancer types using transcriptomic data. Initially, an ensemble approach models gene expression’s impact on survival with parametric and semiparametric hazard models. Subsequently, an iterative conditional independence test combined with graph pruning is utilized to infer the causal skeleton, thereby pinpointing prognosis-related genes. Experiments on transcriptomic data from 18 cancer types sourced from The Cancer Genome Atlas Project demonstrate CPCG’s effectiveness in predicting prognosis under four evaluation metrics. Validations on 24 additional datasets covering 12 cancer types from the Gene Expression Omnibus and the Chinese Glioma Genome Atlas Project further demonstrate CPCG’s robustness and generalizability. CPCG identifies a concise but reliable set of genes, obviating the need for gene combination enumeration for survival time estimation. These genes are also proved closely linked to crucial biological processes in cancer. Moreover, CPCG constructs a stable causal skeleton and exhibits insensitivity to the order of data shuffling. Overall, CPCG is a powerful tool for extracting cancer prognostic biomarkers, offering interpretability, generalizability, and robustness. CPCG holds promise for facilitating targeted interventions in clinical treatment strategies.
Recent advances of precision immunotherapy in sepsis
Authors: Arapis Antonios , Panagiotopoulos Dimitrios , Giamarellos-Bourboulis Evangelos J
Published: January 2025

Precision immunotherapy signifies the administration of the required type of immune intervention tailored to the state of immune activation at the appropriate time window. The classification of patients into the different states of immune activation is usually done by either a protein blood biomarker or a molecular blood endotype that is diagnostic of the precise immune state. Evidence coming from trials of the last decade suggests that immune interventions should be split into strategies aiming to attenuate the exaggerated immune responses, restore sepsis-induced immunoparalysis (SII) and restore the vascular tone. Suggested strategies to attenuate the immune responses are anakinra, nangibotide and tocilizumab. Biomarkers that guide their use are ferritin, soluble triggering receptor expressed on myeloid cells-1 and C-reactive protein. Suggested strategies to restore SII are nivolumab, recombinant human interferon-gamma, CYT107, granulocyte macrophage colony stimulating factor and IgM-enriched immunoglobulin prepapations. Biomarkers that guide their use are the expression of the human leukocyte antigen DR on blood monocytes, the absolute lymphocyte count and blood levels of immunoglobulin M. One recently suggested strategy to restore vascular tone is adrecizumab, the use of which is guided by blood levels of bio-adrenomedulin. The use of these precision treatment strategies is still hampered by the need for large-scale randomized controlled trials.
Contributions of short- and long-range white matter tracts in dynamic compensation with aging
Authors: Chakraborty Priyanka , Saha Suman , Deco Gustavo , Banerjee Arpan , Roy Dipanjan
Published: January 2025

Optimal brain function is shaped by a combination of global information integration, facilitated by long-range connections, and local processing, which relies on short-range connections and underlying biological factors. With aging, anatomical connectivity undergoes significant deterioration, which affects the brain’s overall function. Despite the structural loss, previous research has shown that normative patterns of functions remain intact across the lifespan, defined as the compensatory mechanism of the aging brain. However, the crucial components in guiding the compensatory preservation of the dynamical complexity and the underlying mechanisms remain uncovered. Moreover, it remains largely unknown how the brain readjusts its biological parameters to maintain optimal brain dynamics with age; in this work, we provide a parsimonious mechanism using a whole-brain generative model to uncover the role of sub-communities comprised of short-range and long-range connectivity in driving the dynamic compensation process in the aging brain.

We utilize two neuroimaging datasets to demonstrate how short- and long-range white matter tracts affect compensatory mechanisms. We unveil their modulation of intrinsic global scaling parameters, such as global coupling strength and conduction delay, via a personalized large-scale brain model. Our key finding suggests that short-range tracts predominantly amplify global coupling strength with age, potentially representing an epiphenomenon of the compensatory mechanism. This mechanistically explains the significance of short-range connections in compensating for the major loss of long-range connections during aging. This insight could help identify alternative avenues to address aging-related diseases where long-range connections are significantly deteriorated.
Equations for estimating resting energy expenditure in patients on peritoneal dialysis
Authors: Xu Xiao , Abi Nanzha , Yang Zhikai , Ma Tiantian , Zhang Nan , Zheng Yingdong , Dong Jie
Published: January 2025

Background

In peritoneal dialysis (PD) patients, determining energy expenditure is essential for recommending energy intake in nutrition management.

Objective

We aimed to develop and validate a resting energy expenditure (REE) equation for patients with PD and compare it to previously available REE equations in dialysis patients.

Design

This cross-sectional study enrolled 200 patients with PD from two hospitals in Beijing, China. Stepwise linear regression analysis was used to derive a new REE equation (eREE-PD) based on actual REE (aREE) measured using indirect calorimetry (IC) in the development dataset. The eREE-PD value was then validated with aREE in the validation dataset and compared with values from existing equations obtained in general populations and those developed for chronic kidney disease and dialysis patients, in terms of bias, precision, and accuracy.

Results

The bias, precision, and accuracy of the eREE-PD equation were significantly better than those of the Harris–Benedict, WHO, and Schofield equations (P < .005) and comparable to the Mifflin equation (P = .541 for bias, .988 for precision, and .359 for accuracy), with IC as the reference method. Either bias, precision or accuracy of the eREE-PD were significantly better than eREE-V, eREE-Bscr, and eREE-CFFM equations significantly (P < .005) and similar to eREE-CKD, eREE-Bcrp, and eREE-Cweighht equations (P > .05 for bias, precision, and accuracy). The bias, precision, and accuracy of the eREE-PD equation were consistent across subgroups categorized by hs-CRP levels.

Conclusion

The eREE-PD equation, based on age, sex, and weight data, may serve as a reliable and practical tool for estimating REE in patients with PD, aiding in individualized nutritional management. However, external validation in other populations is required to confirm its generalizability beyond the studied cohort.
Real-world continuous smartwatch-based user authentication
Authors: Al-Naffakh N , Clarke N , Li F , Haskell-Dowland P
Published: January 2025

User authentication is often regarded as the “gatekeeper” of cyber security. It has, however, long suffered from significant usability issues that have resulted in research focussing upon frictionless and transparent biometric approaches. Activity-based user authentication—a technique that authenticates a user by what they are physically doing at a specific point in time has attracted significant attention, particularly due to the increasing popularity of smartwatches. This research aims to overcome limitations in prior work by exploring the viability of the approach in real-world conditions. The study presents two principal experiments, one focused upon a constrained environment to provide a control and a second reflecting real-life. With over 1000 h of sampled data across 60 participants, the study sought to explore sensor, feature composition, and classifier design to explore the practical viability of the approach. Whilst the control experiment achieved best case Equal Error Rate of 0.29%, an improvement upon the prior art using optimisation, the best-case real-world results were not too far behind at 0.7%. This demonstrates that whilst the feature generated in the real-life experiment are subject to increased levels of noise, the performance is viable within the context of a transparent and continuous user authentication approach.
Dysplasia and Colorectal Cancer Surveillance in Ulcerative Colitis Patients in Latin America: Real-World Data
Authors: Parra-Izquierdo Viviana , Otero-Regino William , Juliao-Baños Fabian , Frías-Ordoñez Juan Sebastián , Ibañez-Pinilla Edgar , Gil-Parada Fabio Leonel , Marulanda-Fernández Hernando , Otero-Parra Lina , Otero-Ramos Elder , Puentes-Manosalva Fabian Eduardo , Guzmán Rojas Gerardo Andrés , Ernest-Suárez Kenneth , Villa-Ovalles Keyla , Paredes-Mendez Juan Eloy , Jara-Alba María Luisa , Andrade-Zamora David , Ardila-Báez Manuel Alonso , Flórez-Sarmiento Cristian , Veitia Guillermo , Sánchez Abel , Arango-Molano Lazaro Antonio , Fluxa Fernando , Freitas Queiroz Natália Sousa , Serrano Mariastella
Published: January 2025

Background

The prevalence of colorectal cancer (CRC) in patients with ulcerative colitis (UC) is higher than in the general population, in Latin America there is a progressive increase of UC, and information about CRC screening in inflammatory bowel disease (IBD) is scarce. The aim of this study was to analyze the findings of endoscopic surveillance of CRC in patients with IBD according to available technology.

Methods

Multicenter, cross-sectional, analytical study conducted in Latin American countries, in patients with UC, predominantly with more than 8 years of diagnosis and different degrees of disease activity. Surveillance colonoscopies were performed according to available technology. Risk factors for dysplasia detection were analyzed.

Results

One hundred and forty-four patients, 55.5% women, mean age 47.3 (range 17.1 to 90; SD 15.64) years and mean duration of disease 12.71 (range 0.64 to 57.13; SD 8.08) years. Forty-nine lesions were identified, 18 corresponded to dysplasia. The detection rate of dysplasia per lesion and per procedure was 36.7% and 12.5%, respectively. By logistic regression analysis, the duration of disease (OR 1.12;95%CI:1.047 to 1.215, P = .002) and the presence of post-inflammatory polyps (OR 3.4;95%CI:1.11 to 10.36, P = .031) were risk factors for higher detection of dysplasia. Digital chromoendoscopy was associated with greater detection of dysplasia (OR 4.99, 95%CI: 1.092 to 22.864, P = .038).

Conclusions

In our region, the duration of disease and the presence of post-inflammatory polyps were the factors with the highest association for dysplasia detection, and digital chromoendoscopy with directed biopsies was the technique of choice. The implementation of a specific surveillance program in colonoscopy in IBD is an effective strategy to achieve high detection rates.
Cardiometabolic Multimorbidity and Dementia Onset among Middle-aged and Older Adults: Differences by Race/Ethnicity
Authors: Chen Siting , Quiñones Ana R , Nagel Corey L , Bishop Nicholas , Allore Heather G , Newsom Jason T , Kaye Jeffrey , Botoseneanu Anda
Published: January 2025

Background

Racial/ethnic minoritized groups in the U.S. have higher prevalence of cardiometabolic multimorbidity and experience higher risk of dementia. This study evaluates the relationship between cardiometabolic multimorbidity and dementia onset according to racial/ethnic group in a nationally representative cohort of U.S. middle-aged and older adults.

Methods

Data from the Health & Retirement Study (1998-2018, N=7,960, mean baseline age 59.4 years) and discrete-time survival models were used to estimate differences in the risk of dementia onset, defined by Langa-Weir classification. Models included race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic), chronic disease/multimorbidity categories (no disease, one disease, cardiovascular multimorbidity, metabolic multimorbidity, cardiometabolic multimorbidity, other multimorbidity), age, sex, education, wealth, body-mass index, and proxy status.

Results

Over a mean follow-up of 14.6 years, 7.7% of the participants (n=614) developed dementia. In the fully adjusted model, participants with cardiometabolic multimorbidity had the highest risk of dementia onset (HR:3.27, 95%CI: 2.06,5.21), followed by metabolic (HR:1.83, 95%CI: 1.14,2.94) and cardiovascular (HR:1.81, 95%CI: 1.24,2.64) multimorbidity, relative to participants with no disease. The risk of dementia was significantly greater among Black (HR: 6.40, 95% CI: 3.84,10.67) and Hispanic participants (HR: 4.90, 95% CI: 2.85,8.43) with cardiometabolic multimorbidity, compared to White adults with no disease.

Conclusions

Individuals from racial/ethnic minoritized groups have a higher risk of dementia. The risk of dementia onset was significantly greater for Black and Hispanic participants experiencing cardiometabolic multimorbidity, highlighting the value of intervening on cardiometabolic conditions among middle-age and older adults, in particular those from racial/ethnic minoritized backgrounds to reduce the risk of developing dementia.
Life-Space Restriction Following Disruptive Life Events: Evidence From the COVID-19 Pandemic
Authors: Lin Sapphire H , Chew Mary Su-Lynn , Lim Gek Hsiang , Ng Yee Sien
Published: January 2025

Objectives

Restriction of life-space mobility is associated with adverse health outcomes including depression, morbidity, mortality, and poorer quality of life. In this study, we aimed to determine the impact of coronavirus disease 2019 (COVID-19) and associated employment loss on the life space of older adults in Singapore.

Methods

An in-person survey was administered to a cohort of older Singaporeans above 50 years old (N = 1,118). Data collected included self-report measures of life space, sensory function, well-being, cognitive function, depression, frailty, and objective measures of muscle mass and body mass index. Tests of association and linear regression were performed to test the hypotheses while accounting for the effects of health and sociodemographic covariates.

Results

The life space of older adults has significantly diminished after the pandemic. This loss remained significant despite controlling for covariates and was more pronounced among those who had lost employment during the pandemic. In addition, losing employment during the pandemic was associated with having smaller life spaces.

Discussion

Life-space assessments are a potential important noninvasive marker for not only health and longevity but also the ability to sustain employment. Public health crises like the COVID-19 pandemic and employment loss negatively affect the life spaces of older adults. It is needful to emphasize the maintenance of life space when faced with disruptive life events and provide multidisciplinary collaborative solutions to restore the quality of life among vulnerable older adults.