bluuebunny/crossref_metadata_2025 huggingface dataset:
ALP anarchy
Authors: Chadha-Day Francesca , Maxwell James , Turner Jessica
Published: September 2024

String theory models generically predict the existence of multiple axion-like particle (ALP) fields, yet the majority of both theoretical and experimental works have assumed only one ALP. In this paper, we discuss the phenomenology of systems with multiple ALPs that can undergo oscillations akin to neutrino oscillations. Motivated by this effect, we extend the `anarchy' framework, which has been used to predict neutrino oscillation parameters, to generate the parameters of many ALP systems. We explore the phenomenology of these ALP anarchy models in some of the leading ALP search strategies, including the CERN Axion Solar Telescope, magnetic white dwarfs and the gamma-ray spectra of distant blazars. We include both the ALP-photon and the ALP-electron coupling. We find that ALP anarchy models predict drastically different results than single ALP models.
Jet tagging with more-interaction particle transformer*
Authors: Wu 吴 Yifan 佚凡 , Wang 王 Kun 坤 , Li 李 Congqiao 聪乔 , Qu 曲 Huilin 慧麟 , Zhu 朱 Jingya 经亚
Published: September 2024

In this paper, we introduce the More-Interaction Particle Transformer (MIParT), a novel deep-learning neural network designed for jet tagging. This framework incorporates our own design, the More-Interaction Attention (MIA) mechanism, which increases the dimensionality of particle interaction embeddings. We tested MIParT using the top tagging and quark-gluon datasets. Our results show that MIParT not only matches the accuracy and AUC of LorentzNet and a series of Lorentz-equivariant methods, but also significantly outperforms the ParT model in background rejection. Specifically, it improves background rejection by approximately 25% with a signal efficiency of 30% on the top tagging dataset and by 3% on the quark-gluon dataset. Additionally, MIParT requires only 30% of the parameters and 53% of the computational complexity needed by ParT, proving that high performance can be achieved with reduced model complexity. For very large datasets, we double the dimension of particle embeddings, referring to this variant as MIParT-Large (MIParT-L). We found that MIParT-L can further capitalize on the knowledge from large datasets. From a model pre-trained on the 100M JetClass dataset, the background rejection performance of fine-tuned MIParT-L improves by 39% on the top tagging dataset and by 6% on the quark-gluon dataset, surpassing that of fine-tuned ParT. Specifically, the background rejection of fine-tuned MIParT-L improves by an additional 2% compared to that of fine-tuned ParT. These results suggest that MIParT has the potential to increase the efficiency of benchmarks for jet tagging and event identification in particle physics.
Filter banks guided correlational convolutional neural network for SSVEPs based BCI classification
Authors: Wen Xin , Jia Shuting , Han Dan , Dong Yanqing , Gao Chengxin , Cao Ruochen , Hao Yanrong , Guo Yuxiang , Cao Rui
Published: September 2024

Objective. In the field of steady-state visual evoked potential brain computer interfaces (SSVEP-BCIs) research, convolutional neural networks (CNNs) have gradually been proved to be an effective method. Whereas, majority works apply the frequency domain characteristics in long time window to train the network, thus lead to insufficient performance of those networks in short time window. Furthermore, only the frequency domain information for classification lacks of other task-related information. Approach. To address these issues, we propose a time-frequency domain generalized filter-bank convolutional neural network (FBCNN-G) to improve the SSVEP-BCIs classification performance. The network integrates multiple frequency information of electroencephalogram (EEG) with template and predefined prior of sine-cosine signals to perform feature extraction, which contains correlation analyses in both template and signal aspects. Then the classification is performed at the end of the network. In addition, the method proposes the use of filter banks divided into specific frequency bands as pre-filters in the network to fully consider the fundamental and harmonic frequency characteristics of the signal. Main results. The proposed FBCNN-G model is compared with other methods on the public dataset Benchmark. The results manifest that this model has higher accuracy of character recognition accuracy and information transfer rates in several time windows. Particularly, in the 0.2 s time window, the mean accuracy of the proposed method reaches

62.02
%
±
5.12
%

, indicating its superior performance. Significance. The proposed FBCNN-G model is critical for the exploitation of SSVEP-BCIs character recognition models.
A multi-network model of Parkinson’s disease tremor: exploring the finger-dimmer-switch theory and role of dopamine in thalamic self-inhibition
Authors: Sadeghi Fatemeh , Popova Mariia , Páscoa Dos Santos Francisco , Zittel Simone , Hilgetag Claus C
Published: September 2024

Background. Tremor is a cardinal symptom of Parkinson’s disease (PD) that manifests itself through complex oscillatory activity across multiple neuronal populations. According to the finger-dimmer-switch (FDS) theory, tremor is triggered by transient pathological activity in the basal ganglia-thalamo-cortical (BTC) network (the finger) and transitions into an oscillatory form within the inner circuitry of the thalamus (the switch). The cerebello-thalamo-cortical (CTC) network (the dimmer) is then involved in sustaining and amplifying tremor amplitude. In this study, we aimed to investigate the generation and progression dynamics of PD tremor oscillations by developing a comprehensive and interacting FDS model that transitions sequentially from healthy to PD to tremor and then to tremor-off state. Methods. We constructed a computational model consisting of 700 neurons in 11 regions of BTC, CTC, and thalamic networks. Transition from healthy to PD state was simulated through modulating dopaminergic synaptic connections; and further from PD to tremor and tremor-off by modulating projections between the thalamic reticular nucleus (TRN), anterior ventrolateral nucleus (VLa), and posterior ventrolateral nucleus (VLp). Results. Sustained oscillations in the frequency range of PD tremor emerged in thalamic VLp (5 Hz) and cerebellar dentate nucleus (3 Hz). Increasing self-inhibition in the thalamus through dopaminergic modulation significantly decreased tremor amplitude. Conclusion/Significance. Our results confirm the mechanistic power of the FDS theory in describing the PD tremor phenomenon and emphasize the role of dopaminergic modulation on thalamic self-inhibition. These insights pave the way for novel therapeutic strategies aimed at reducing the tremor by strengthening thalamic self-inhibition, particularly in dopamine-resistant patients.
A comprehensive survey of evolutionary algorithms and metaheuristics in brain EEG-based applications
Authors: Arif Muhammad , ur Rehman Faizan , Sekanina Lukas , Malik Aamir Saeed
Published: September 2024

Electroencephalography (EEG) has emerged as a primary non-invasive and mobile modality for understanding the complex workings of the human brain, providing invaluable insights into cognitive processes, neurological disorders, and brain–computer interfaces. Nevertheless, the volume of EEG data, the presence of artifacts, the selection of optimal channels, and the need for feature extraction from EEG data present considerable challenges in achieving meaningful and distinguishing outcomes for machine learning algorithms utilized to process EEG data. Consequently, the demand for sophisticated optimization techniques has become imperative to overcome these hurdles effectively. Evolutionary algorithms (EAs) and other nature-inspired metaheuristics have been applied as powerful design and optimization tools in recent years, showcasing their significance in addressing various design and optimization problems relevant to brain EEG-based applications. This paper presents a comprehensive survey highlighting the importance of EAs and other metaheuristics in EEG-based applications. The survey is organized according to the main areas where EAs have been applied, namely artifact mitigation, channel selection, feature extraction, feature selection, and signal classification. Finally, the current challenges and future aspects of EAs in the context of EEG-based applications are discussed.
Evaluation of radiation detection sensors and quality assurance relative dosimeters fabricated using methylammonium lead iodide for brachytherapy
Authors: Yang S.W. , Shin Y.H. , Park S.K.
Published: September 2024

Methylammonium lead iodide (MAPbI3) perovskite is a
well-known organic-inorganic lead halide perovskite that has gained
much attention because of its advantages such as a high absorption
coefficient for radiation absorption, high carrier mobility, high
defect tolerance, and outstanding solution processability. In this
study, we aimed to fabricate radiation detection sensors and
relative dosimeters using MAPbI3 and evaluate their
applicability as quality assurance (QA) equipment for
brachytherapy. MAPbI3 film dosimeters of various thicknesses
were fabricated, and their responses to Iridium-192 source were
evaluated to determine the suitable thickness for radiation
detection sensors. Additionally, the ability to use the fabricated
QA relative dosimeter for brachytherapy was determined based on the
results of reproducibility and linearity evaluations. The evaluation
of the reproducibility of the fabricated MAPbI3 radiation
detection sensors with thicknesses of 150 and 225 μm showed
standard deviations of 0.51% and 1.14%, respectively, which met
the evaluation criterion of ≤ 1.5%. The evaluation of
linearity indicated R2 values of 0.9999 and 0.9998,
respectively, which met the criterion of ≥ 0.9990. The results
clearly demonstrated that the MAPbI3 dosimeter fabricated
during this study may be used as a QA relative dosimeter for
brachytherapy.
Inter-product biases in extreme precipitation duration and frequency across China
Authors: Lu Jiayi , Wang Kaicun , Wu Guocan , Ye Aizhong , Mao Yuna
Published: September 2024

Accurately delineating the duration and frequency characteristics of extreme precipitation is vital for assessing climate change risks. This study reassesses the spatiotemporal variations in the frequency and persistence indices of extreme precipitation from 2001 to 2019 across thirteen widely used precipitation datasets. We quantify the inter-product biases using common accuracy indices based on reference data, derived from a national observation network of over 2400 stations. Regarding the duration of extreme precipitation, represented by consecutive dry days (CDD) and consecutive wet days (CWD), gauge-based datasets generally demonstrate better accuracy. Satellite retrieval datasets tend to overestimate CDD (4.58%) and CWD (60.50%) at continental scale. Meanwhile, reanalysis and fusion datasets tend to underestimate CDD (−30.27% and −15.39%, respectively) and overestimate CWD (148.44% and 93.41%, respectively). In terms of frequency indices, represented by the number of heavy precipitation days (R10MM) and the number of very heavy precipitation days (R20MM), gauge-based, satellite retrieval, and fusion datasets show weak biases in R10MM (all below 3.5%), while reanalysis datasets indicate substantial overestimation (33.62%). In the case of R20MM, there is an improvement in the performance of reanalysis datasets, while the performance of other datasets declines. However, almost all datasets fail to consistently capture variations in the Tibetan Plateau and Xinjiang regions, where gauge stations are limited and terrain is complex. Furthermore, multiple datasets present significant discrepancies in temporal trends from 2001 to 2019. Remote sensing datasets tend to overestimate CDD, while reanalysis datasets generally show persistent underestimation of CDD and persistent overestimation of other indices. This research contributes to guiding the application and improvement of global precipitation datasets in extreme precipitation studies.
Connection formulae in the collision limit I: case studies in Lifshitz geometry
Authors: Zhao Hao , Zhu Rui-Dong
Published: September 2024

The connection formulae provide a systematic way to compute physical quantities, such as the quasinormal modes, Green functions, in blackhole perturbation theories. In this work, we test whether it is possible to consistently take the collision limit, which brings two or more regular singularities into an irregular one, of the connection formulae, and we provide some supportive evidence for it.
General properties of the response function in a class of solvable non-equilibrium models
Authors: Corberi F , Smaldone L
Published: September 2024

We study the non-equilibrium response function

R

i
j

(
t
,

t

′

)

, namely the variation of the local magnetization

⟨

S
i

(
t
)
⟩

on site i at time t as an effect of a perturbation applied at the earlier time t′ on site j, in a class of solvable spin models characterized by the vanishing of the so-called asymmetry. This class encompasses both systems brought out of equilibrium by the variation of a thermodynamic control parameter, as after a temperature quench, or intrinsically out of equilibrium models with violation of detailed balance. The one-dimensional Ising model and the voter model (on an arbitrary graph) are prototypical examples of these two situations which are used here as guiding examples. Defining the fluctuation-dissipation ratio

X

i
j

(
t
,

t

′

)
=
β

R

i
j

/

(
∂

G

i
j

/

∂

t

′

)

, where

G

i
j

(
t
,

t

′

)
=
⟨

S
i

(
t
)

S
j

(

t

′

)
⟩

is the spin–spin correlation function and β is a parameter regulating the strength of the perturbation (corresponding to the inverse temperature when detailed balance holds), we show that, in the quite general case of a kinetics obeying dynamical scaling, on equal sites this quantity has a universal form

X

i
i

(
t
,

t

′

)
=
(
t
+

t

′

)

/

(
2
t
)

, whereas

lim

t
→
∞

X

i
j

(
t
,

t

′

)
=
1

/

2

for any ij couple. The specific case of voter models with long-range interactions is thoroughly discussed.
Phycoremediation of tofu wastewater using a mixed culture of Chlorella vulgaris and Nannochloropsis oculate with salicylic acid elicitor
Authors: Taufikurahman T , Irene J , Melani L
Published: September 2024

Wastewater from tofu industry contains suspended and organic matter which, if discharged directly into the waters, can degrade water quality. One method of wastewater treatment that can be done is phycoremediation, which utilizes the activity of microalgae which can assimilate N and P in tofu wastewater as a source of nutrients for growth. The addition of salicylic acid as elicitor can increase microalgal biomass, although administration of salicylic acid at high concentrations potentially could inhibit microalgae growth. Therefore, it is necessary to know the right concentration of salicylic acid which could increase microalgae biomass. In this study, cultivation of mixed microalgae Chlorella vulgaris, and Nannochloropsis oculata, with a ratio of 1:1 (v/v) was carried out for 7 days at the Open Raceway Pond (ORP) with a working volume of 55 L. The growth medium used was tofu wastewater with a concentration of 16% (v/v) of the working volume. On the fifth day, variations were made with the addition of salicylic acid 0 μM (control), 20 μM, and 200 μM. The use of mixed cultures was expected to increase resistance to various abiotic and biotic conditions, as well as optimize resource utilization. Parameters measured included specific growth rate, pH, initial and final levels of nitrate, orthophosphate, BOD, and COD. Mixed culture of C. vulgaris and N. oculata with the addition of 20 μM salicylic acid produced the best growth, with a specific growth rate of 0.66/day. The addition of 20 μM salicylic acid also resulted in the highest reduction in wastewater parameters, with the percentage of reductions in nitrate concentration (57.67%), orthophosphate (44.09%), BOD (62.48%), and COD (56.09%). The result showed that phycoremediation of tofu wastewater can be best carried out by utilizing a mixed culture of C. vulgaris and N. oculata with the addition of 20 μM salicylic acid.
Confined mass transport in two-dimensional capillary
Authors: Li Baowen , Wang Jiajun , Zhu Junliang , Tan Wang , Ji Jiahui , Yin Jun , Li Xuemei , Guo Wanlin
Published: September 2024

Over the past decade, nanofluidics has undergone significant expansion, propelled by advances in crafting artificial channels at nanometric and sub-nanometric scales with diverse geometries. Central to this domain, two-dimensional capillaries have risen as a pivotal research platform, marked by their angstrom-level precision, unparalleled wall surface smoothness, and clearly defined surface charge states. Their advent has profoundly deepened our understanding of mass transport dynamics, spanning gases, water molecules, and ions, shedding light on the complex interactions among various influencing factors and revealing a range of previously undiscovered physical phenomena. This review delves into the development of 2D capillaries, the principal fluid transport phenomena observed within, and the critical elements that affect these processes. We also touch on a fascinating discovery-the quantum liquid friction seen in water moving over carbon surfaces. In anticipation of future explorations in nanofluidics, we envision a trajectory aimed at emulating the efficiency levels of biological ion channels, setting the stage for a new era of scientific inquiry and technological innovation.
Harnessing the potential of electrospun TiO2 nanofibers and nanoparticles enriched with natural dyes: a path towards affordable aolutions for low-cost electronic devices
Authors: Mhetre Harshada , Chendake Yogesh , Nayyar Manan , Kumar Piyush , Sorte Sarvesh , Naik Nithesh , S A Salmataj , Hiremath Pavan
Published: September 2024

This study evaluates the morphological effects of TiO2 nanoparticles, nanofibers, and a bilayer configuration on electronic devices, such as Dye-Sensitized Solar Cells (DSSCs) and UV sensors. Cost-efficient natural dyes—curcumin, coffee beans, and banana peel—were used as sensitizers for nanomaterial films. TiO2 nanoparticles were synthesized using the sol–gel technique, while nanofibers were produced via electrospinning. Characterization techniques, including Scanning Electron Microscopy (SEM), Energy Dispersive x-ray Spectroscopy (EDS), and x-ray Diffraction (XRD), confirmed the formation and dimensions of the TiO2 nanostructures. UV–visible spectroscopy was used to determine the optical properties of the samples. TiO2 nanofibers and nanoparticles exhibited high surface-area-to-volume ratios, with nanofibers having a diameter of 20 nm and particles measuring 50 nm. A binder-free, low-temperature paste was prepared using TiO2 nanoparticles and nanofibers to develop thin films. The turmeric dye showed peak absorption at 470 nm with a band gap energy of 2.06 eV when loaded on a TiO2 bilayer film. This study aims to develop electronic devices that reduce costs and enhance performance by using low-cost, efficient, and economically viable dyes. TiO2 nanofiber and nanoparticle films show promise for cost-effective and high-performance electronic devices.
Sulfate resistance of alkali-activated flyash-slag-lime concrete: comparative study of drying-wetting cycles and conventional exposure
Authors: Jagadisha H M , Prashant Shreelaxmi , Pandit Poornachandra , G S Sandeep , Kamat Raghavendra
Published: September 2024

Sulfate resistance of concrete is a crucial parameter for design of offshore structures. Of late alkali-activated materials are been given due consideration for infrastructure projects. In this context, the present study aims to assess the sulfate resistance of Alkali-Activated Concrete (AAC) with ternary blend of flyash-Ground Granulated Blast furnace Slag (GGBS) and limestone as the principal binder. The first phase of the study includes, the optimization of AAC ternary mix with the inclusion of limestone as a potential binder to popularly used flyash slag blends. The inclusion of 5% limestone powder into the binder matrix is found to have beneficial effect on the mechanical properties of the ternary blended AAC. Further, an increase in the limestone powder content is not found to influence mechanical properties positively. The AAC mix with 5% limestone of total binder content was therefore selected for further evaluation of sulfate resistance. The sulfate resistance is evaluated under the alkaline media by subjecting AAC specimens to constant immersion and alternative drying and wetting cycles. The mechanical characteristics and mass reduction of the exposed samples were tested and compared with the conventional Ordinary Portland Cement (OPC) specimens. Evaluations were conducted over periods of 30, 45, 120, and 365 days of exposure. Scanning Electron Microscopy (SEM) and Energy Dispersion Spectroscopy (EDS) were also used to determine the surface morphology and mineral composition of samples after 365 days of exposure periods. The Flyash-Slag-Lime AAC exhibits denser morphology in comparison to OPC-based concrete, which in turn offers enhanced sulfate resistance.
Effect of the particle shape on the shear mechanical behavior of coral sand
Authors: Zhang Xin , Ma Linjian , Ke Jiewei , Yan Zhiqiang , Feng Zheyan , Zong Limingxin
Published: September 2024

Coral sand particles exhibit a wide range of shapes, which can be divided into four shapes, e.g., blocky, dendritic and rodlike, flaky, and shell debris. The particle shape of these mixtures is defined by the sphericity, concavity, aspect ratio, flatness and overall regularity, which ranges from 0 to 1. The effect of particle shape on the strength, crushing characteristics, and critical state parameter is systematically investigated through a series of triaxial drainage shear tests under different confining pressures. And the relationship between critical state parameters and mechanical parameters is established. The test results demonstrate the existence of an evident strain-hardening phenomenon in the stress–strain curve of coral sand, accompanied by a strain-softening phenomenon when the bias stress reaches its peak value. The sample is initially subjected to shear shrinkage, followed by shear expansion. The volumetric deformation of the coral sand decreased with increasing peripheral pressure. The particles are transformed from rough irregular shapes to smooth spheres as evidenced by an increase in the shape parameter. The greater the degree of irregularity in the shape of the particles, the more pronounced the resulting change in size reduction. In addition, the critical state parameter was found to be influenced by the shape of the coral sand particles and the mode of particle accumulation. The overall shear resistance of coral sand particles was found to depend on particle rearrangement in addition to particle surface roughness and interparticle friction. It is proposed that the general regularity critical state parameter equation relates the particle shape of coral sand to its critical state mechanical properties, which is of great importance to the practical application and research of coral sand in engineering, and provides an effective means of predicting mechanical properties granular materials.
Climate action on Twitter: perceived barriers for actions and actors, and sentiments during COP26
Authors: Wang Xinran , Judge Madeline , Steg Linda
Published: September 2024

We studied public perceptions of what climate actions are needed, which actors should and can act, and which factors inhibit or enable those actions using the naturally occurring discourse on climate actions on Twitter during COP26. By incorporating big data computational methods with a theory-based qualitative analysis, we aimed to identify climate actions and actors at the international, national, local, and individual levels, and systematically evaluate the perceived barriers and enablers in taking action and related public sentiments. We find that political and industry leaders are widely perceived as the most responsible and capable of taking action. Yet, their current inaction is perceived as inhibiting net-zero transitions and triggers anger, fear, and blame. In contrast, discourse on citizens and local communities demonstrates hope and solidarity in enacting pro-environmental changes from the bottom up, signaling strong public demand for ambitious climate policies and actions. These findings highlight the importance of removing institutional barriers and catalyzing socio-cultural support to accelerate collective climate progress. Overall, our mixed-method approach provides a more comprehensive understanding of how to step up societal-wide climate actions, paving the way for much-needed communications and collaborations across society to achieve a sustainable future.
Valuation of tourists’ willingness to pay for ecological conservation towards a sustainable financial mechanism for national parks: an empirical case of Cuc Phuong National Park, Red River delta, Vietnam
Authors: Lan Bui Thi Hoang , Truong Dinh Duc , Huy Huan Le , Hang Nguyen Dieu
Published: September 2024

National Parks (NPs) play an important role in preserving the ecological values of nature, while also bringing economic benefits to the community. However, current NPs in developing countries are facing the challenge of lacking financial resources for conservation goals. This study estimated tourists’ willingness to pay for ecological conservation in Cuc Phuong National Park (CPNP), Vietnam as well as factors affecting willingness to pay. Using dichotomous contingent valuation model and a research sample of 650 randomly selected tourists in Cuc Phuong, the study showed that tourists’ willingness to pay for conservation through additional entry fee was about 47,070 VND in the parametric model and 42,123 VND in the non-parametric model. Factors that influence the probability of accepting payments included income, education level, conservation attitude and awareness of ecological values and travel distance. From there, the study discussed and proposed implications that contribute to mobilizing finance for conservation from the community and financial mechanisms for conservation in NPs in Vietnam and developing countries in Asia.
Circular Bragg grating single-photon source design exploiting extreme dielectric confinement
Authors: Zhou Yueguang , Kountouris George , Wang Yujing , Yvind Kresten , Mørk Jesper , Gregersen Niels , Pu Minhao
Published: September 2024

We theoretically propose a single-photon source design based on a circular Bragg grating microcavity incorporating two air triangles in a bowtie configuration. Our proposed design allows for extreme light confinement with a Purcell factor of approximately 166 with a bandwidth of ~9 nm for a triangle separation of 5 nm combined with a collection efficiency above 80

%

. The Purcell factor is enhanced by a factor of 8 relative to the reference cavity thanks to the reduction of the mode volume. Furthermore, we demonstrate the critical role of the dipole emitter polarization orientation and spatial position in achieving optimal Purcell enhancement.
Estimating vegetation structure and aboveground carbon storage in Western Australia using GEDI LiDAR, Landsat and Sentinel data
Authors: Lutz Natasha , Rodriguez-Veiga Pedro , Oliveras Menor Imma
Published: September 2024

Worsening climate change impacts are amplifying the need for accurate estimates of vegetation structure and aboveground biomass density (AGBD) to assess changes in biodiversity and carbon storage. In Australia, increasing wildfire frequency and interest in the role of forests in the carbon cycle necessitates biomass mapping across large geographic extents to monitor forest change. The availability of spaceborne Light Detection and Ranging optimised for vegetation structure mapping through the Global Ecosystem Dynamics Investigation (GEDI) provides an opportunity for large-scale forest AGBD estimates of higher accuracy. This study assessed the use of the GEDI canopy height product to predict woody AGBD across five vegetation types in Western Australia: tall eucalypt forests, eucalypt open‒woodlands, low-lying heathland, tropical eucalypt savannas, and tussock and hummock grasslands. Canopy height models were developed using random forest regressions trained on GEDI canopy height discrete point data. Predictor variables included spectral bands and vegetation indices derived from synthetic aperture radar Sentinel‒1 data, and multispectral Landsat and Sentinel‒2 data. AGBD was subsequently estimated using power-law models derived by relating the predicted canopy heights to field AGBD plots. Mapping was conducted for 2020 and 2021. The accuracy of canopy height predictions varied with height quantiles; models underestimated the height of taller trees and overestimated the height of smaller trees. A similar underestimation and overestimation trend was observed for the AGBD estimates. The mean carbon stock was estimated at 69.0 ± 12.0 MgCha−1 in the tall eucalypt forests of the Warren region; 33.8 ± 5.0 MgCha−1 for the open eucalypt woodlands in the South Jarrah region; 7.1 ± 1.4 MgCha−1 for the heathland and shrublands in the Geraldton Sandplains region; 43.9 ± 4.9 MgCha−1 for the Kimberley eucalypt savanna; and 3.9 ± 1.0 MgCha−1 for the Kimberley savanna grasslands. This approach provides a useful framework for the future development of this process for fire management, and habitat health monitoring.
Nuclear basket proteins regulate the distribution and mobility of nuclear pore complexes in budding yeast
Authors: Zsok Janka , Simon Francois , Bayrak Göksu , Isaki Luljeta , Kerff Nina , Kicheva Yoana , Wolstenholme Amy , Weiss Lucien E. , Dultz Elisa
Published: September 2024

Nuclear pore complexes (NPCs) mediate all traffic between the nucleus and the cytoplasm and are among the most stable protein assemblies in cells. Budding yeast cells carry two variants of NPCs which differ in the presence or absence of the nuclear basket proteins Mlp1, Mlp2, and Pml39. The binding of these basket proteins occurs very late in NPC assembly and Mlp-positive NPCs are excluded from the region of the nuclear envelope that borders the nucleolus. Here, we use recombination-induced tag exchange to investigate the stability of all the NPC subcomplexes within individual NPCs. We show that the nuclear basket proteins Mlp1, Mlp2, and Pml39 remain stably associated with NPCs through multiple cell-division cycles, and that Mlp1/2 are responsible for the exclusion of NPCs from the nucleolar territory. In addition, we demonstrate that binding of the FG-nucleoporins Nup1 and Nup2 depletes also Mlp-negative NPCs from this region by an independent pathway. We develop a method for single NPC tracking in budding yeast and observe that NPCs exhibit increased mobility in the absence of nuclear basket components. Our data suggest that the distribution of NPCs on the nucleus is governed by multiple interaction of nuclear basket proteins with the nuclear interior.
Ultra-complex specialty medications: Meeting the challenges of significant medication requirements through an integrated specialty pharmacy model
Authors: Renfro Chelsea P , Donald Dustin R , Kibbons Amanda M , Littlejohn Monica D , Danielle Bryan E , Nix Ryan , Cherry Elizabeth , Zuckerman Autumn D
Published: September 2024

Purpose

There is a growing number of specialty medications with accompanying requirements that exceed standard characteristics, which may be referred to as “ultra complex.” This article details examples of ultra-complex specialty medications, including the characteristics that make them ultra complex, and strategies implemented by an integrated health-system specialty pharmacy (IHSSP) to maintain an optimal patient journey.

Before therapy initiation, ultra-complex specialty medications often require additional steps that go beyond what is required of traditional specialty treatments, such as ensuring patients have appointments scheduled and attended and coordinating medical procedures. At the time of initiation, ultra-complex therapy might require additional immunizations or dosing based on specific tests. Finally, specialty pharmacists managing ultra-complex medications often have to dedicate more time and effort to medication monitoring to ensure patients are able to stay on appropriate doses without treatment interruption. Manufacturers of ultra-complex medications must consider the resources and requirements that will be needed to ensure the success of these medications in the real world. Health systems must be aware of resource and staffing requirements necessary to ensure the success of ultra-complex medications. One consideration is the addition of a dedicated risk evaluation and mitigation strategy (REMS) pharmacist whose primary role is to ensure compliance with REMS requirements.

Conclusion

Ultra-complex specialty medications provide unprecedented therapeutic advancements but demand multidisciplinary resources and workflows to enable safe medication initiation, appropriate dosing and monitoring, and achievement of desired therapeutic goals. IHSSPs are integrated into the care team and provide advanced monitoring capabilities, making them an ideal setting for managing ultra-complex specialty medications. External IHSSP partnerships working together before and after the launch of ultra-complex specialty medications allow for an optimal patient and provider journey from medication initiation through ongoing care coordination and monitoring.
Can recent evolutionary history promote resilience to environmental change?
Authors: Bladon Eleanor K , Pascoal Sonia , Kilner Rebecca M
Published: September 2024

Principles of social evolution have long been used retrospectively to interpret social interactions, but have less commonly been applied predictively to inform conservation and animal husbandry strategies. We investigate whether differences in developmental environment, facilitated by divergent social conditions, can predict resilience to environmental change. Upon exposure to harsh novel environments, populations that previously experienced more benign social environments are predicted either to suffer fitness losses (the “mutation load hypothesis” and “selection filter hypothesis”) or maintain fitness (the “beneficial mutation hypothesis”). We tested these contrasting predictions using populations of burying beetles Nicrophorus vespilloides we had evolved experimentally for 45 generations under contrasting social environments by manipulating the supply of post-hatching parental care. We exposed sexually immature adults from each population to varying heat stress and measured the effect on survival and reproduction. The greater the level of parental care previously experienced by a population, the better its survival under heat stress during sexual maturation. Although this is consistent with the “beneficial mutation hypothesis,” it is also possible that populations that had evolved without post-hatching care were simply more prone to dying during maturation, regardless of their thermal environment. Overall, we suggest that stochastic genetic variation, probably due to founder effects, had a stronger influence on resilience. We discuss the implications for translocation and captive breeding programs.
OligoFormer: an accurate and robust prediction method for siRNA design
Authors: Bai Yilan , Zhong Haochen , Wang Taiwei , Lu Zhi John
Published: September 2024

Motivation

RNA interference (RNAi) has become a widely used experimental approach for post-transcriptional regulation and is increasingly showing its potential as future targeted drugs. However, the prediction of highly efficient siRNAs (small interfering RNAs) is still hindered by dataset biases, the inadequacy of prediction methods, and the presence of off-target effects. To overcome these limitations, we propose an accurate and robust prediction method, OligoFormer, for siRNA design.

Results

OligoFormer comprises three different modules including thermodynamic calculation, RNA-FM module, and Oligo encoder. Oligo encoder is the core module based on the transformer encoder. Taking siRNA and mRNA sequences as input, OligoFormer can obtain thermodynamic parameters, RNA-FM embedding, and Oligo embedding through these three modules, respectively. We carefully benchmarked OligoFormer against six comparable methods on siRNA efficacy datasets. OligoFormer outperforms all the other methods, with an average improvement of 9% in AUC, 6.6% in PRC, 9.8% in F1 score, and 5.1% in PCC compared to the best method among them in our inter-dataset validation. We also provide a comprehensive pipeline with prediction of siRNA efficacy and off-target effects using PITA score and TargetScan score. The ablation study shows RNA-FM module and thermodynamic parameters improved the performance and accelerated convergence of OligoFormer. The saliency maps by gradient backpropagation and base preference maps show certain base preferences in initial and terminal region of siRNAs.

Availability and implementation

The source code of OligoFormer is freely available on GitHub at: https://github.com/lulab/OligoFormer. Docker image of OligoFormer is freely available on the docker hub at https://hub.docker.com/r/yilanbai/oligoformer.
Causal inference using multivariate generalized linear mixed-effects models
Authors: Xu Yizhen , Kim Ji Soo , Hummers Laura K , Shah Ami A , Zeger Scott L
Published: September 2024

Dynamic prediction of causal effects under different treatment regimens is an essential problem in precision medicine. It is challenging because the actual mechanisms of treatment assignment and effects are unknown in observational studies. We propose a multivariate generalized linear mixed-effects model and a Bayesian g-computation algorithm to calculate the posterior distribution of subgroup-specific intervention benefits of dynamic treatment regimes. Unmeasured time-invariant factors are included as subject-specific random effects in the assumed joint distribution of outcomes, time-varying confounders, and treatment assignments. We identify a sequential ignorability assumption conditional on treatment assignment heterogeneity, that is, analogous to balancing the latent treatment preference due to unmeasured time-invariant factors. We present a simulation study to assess the proposed method’s performance. The method is applied to observational clinical data to investigate the efficacy of continuously using mycophenolate in different subgroups of scleroderma patients.
Planning cost-effective operational forest inventories
Authors: Karppinen Santeri , Ene Liviu , Engberg Sundström Lovisa , Karvanen Juha
Published: September 2024

We address a Bayesian two-stage decision problem in operational forestry where the inner stage considers scheduling the harvesting to fulfill demand targets and the outer stage considers selecting the accuracy of pre-harvest inventories that are used to estimate the timber volumes of the forest tracts. The higher accuracy of the inventory enables better scheduling decisions but also implies higher costs. We focus on the outer stage, which we formulate as a maximization of the posterior value of the inventory decision under a budget constraint. The posterior value depends on the solution to the inner stage problem and its computation is analytically intractable, featuring an NP-hard binary optimization problem within a high-dimensional integral. In particular, the binary optimization problem is a special case of a generalized quadratic assignment problem. We present a practical method that solves the outer stage problem with an approximation which combines Monte Carlo sampling with a greedy, randomized method for the binary optimization problem. We derive inventory decisions for a dataset of 100 Swedish forest tracts across a range of inventory budgets and estimate the value of the information to be obtained.
Towards Digital Adaption: An Exploration of Chinese Social Workers’ Experiences of Digital Service Challenges and Coping Strategies in the Context of COVID-19
Authors: Huang Dan , Luo Yingting , Lu Jiayi
Published: September 2024

This study is based on interviews with sixty-three Chinese social workers to explore the challenges they faced and the strategies they adopted when using digital technology for front-line services during the coronavirus disease 2019 (COVID-19) pandemic. Employing an ecosystem theory, thematic analysis is applied to analyse interview transcripts. The findings reveal three major challenges faced by social workers: limited digital capital, digital-mediated service predicaments and the digital burden. To address the aforementioned challenges, social workers adopted four strategies: digital empowerment, adjustment of online service processes, leveraging the advantages of digital technology and asking colleagues for support. This study suggests enhancing support for social workers through improved digital training and psychological care, integrating digital-mediated social work skills into academic curricula, and fostering interdisciplinary partnerships to develop and utilize reliable digital tools, thereby improving the quality and effectiveness of social work in the digital age.
The Impact of Political Stance on UK Newspaper Coverage of Child and Family Social Work
Authors: Worthington Jessica , Scourfield Jonathan
Published: September 2024

Previous research has shown that news coverage of the social work profession plays an important role in influencing public opinion, and can damage staff morale if negative, affecting recruitment and retention of staff. Relatively little research has been done to ascertain how factors such as political stance of news outlet influence the way social workers are portrayed. The focus of this research is how child and family social workers are portrayed in eight UK national newspapers between 2018 and 2021 and whether the political stance of the newspapers influenced this. All mentions of social workers in 257 articles from eight major UK national newspapers were coded as either positive, negative, or neutral portrayals. Each article was also categorised for the social work topic it was reporting on. Quantitative analysis of the data found that the political stance of the newspaper was associated with the type of social work it reported on and there was a significant difference in the rate of both positive and negative mentions according to political stance, with right-leaning newspapers having a higher rate of negative mentions than left-leaning and left-leaning papers having a higher rate of positive mentions.
Reproductive biology of Aristolochia trilobata L. (Aristolochiaceae)
Authors: Nakonechnaya Olga , Nesterova Svetlana , Kalachev Alexander
Published: September 2024

Aristolochia trilobata is a medicinal and ornamental liana that is distributed along the Caribbean coast of Central America and all over the West Indies. This species is a valuable component of the biotope, since its leaves serve as the only food for caterpillars of the vulnerable butterfly Parides ascanius. Because of rapid deforestation, the number of A. trilobata plants is decreasing. Hence, studying of A. trilobata reproductive biology is important to preserve this valuable species. We studied reproductive biology of this species in greenhouse conditions in Vladivostok. Our results indicate that the ontogeny of A. trilobata ex situ consists of the latent, pre-reproductive, and reproductive ontogenetic periods. The plants enter the reproductive period at ~3.5 years after seedling. The flowering process of each flower includes three phases: female, intermediate, and male. Protogynous flowers are adapted to cross-pollination by insects and bloom for 3 days. Their stigmas are receptive for the first 2 days of flowering. Pollen grains are spheroidal, inaperturate. When anthers open, the pollen grains rapidly germinate and this determines the fertilization success at the female phase of the anthesis. The plants can self-pollinate by geitonogamy, but the presence of a pollination agent is required. The fruit contains about 350 seeds. Rapid and synchronous seed germination, plant development to reproductive state, the regular flowering, high percentage of normal pollen, and rapid development of fruits with a high number of viable seeds indicate the high reproductive ability of A. trilobata and plants’ ability to adapt to ex situ conditions.
Thermo-responsive cascade antimicrobial platform for precise biofilm removal and enhanced wound healing
Authors: Du Ting , Cao Jiangli , Zhang Zhannuo , Xiao Zehui , Jiao Jingbo , Song Zhiyong , Du Xinjun , Wang Shuo
Published: September 2024

Background

Bacterial infection, tissue hypoxia and inflammatory response can hinder infected wound repair. This study aimed to develop a multifunctional specific therapeutic photo-activated release nanosystem [HMPB@MB@AuNPs@PMB@HA (HMAPH)] by loading photosensitizer methylene blue (MB) into hollow mesoporous Prussian blue nanostructures and modifying the surface with gold particles, polymyxin B (PMB) and hydrophilic hyaluronic acid.

Methods

The HMAPH was characterized using transmission electron microscopy, UV–vis, Fourier-transform infrared spectroscopy, X-ray diffraction and X-ray photon spectroscopy. The photothermal performance, iron ion release and free radical generation of the HMAPH were measured under different conditions to investigate its thermo-responsive cascade reaction. The antibacterial ability of HMAPH was investigated using live/dead fluorescence tests. The morphology and membrane integrity of Pseudomonas aeruginosa (P. aeruginosa) were investigated using transmission electron microscopy. The anti-biofilm activity of HMAPH was evaluated using crystal violet and SYBR Green I staining. Finally, we established a mouse model of a skin wound infected by P. aeruginosa to confirm the in vivo effectiveness of HMAPH. We used immunofluorescent staining, hematoxylin–eosin staining, Masson staining and enzyme-linked immunosorbent assay to examine whether HMAPH promoted wound healing and reduced inflammatory damage.

Results

In this study, hyaluronic acid was decomposed under the action of hyaluronidase. Also, the exposed nanomaterials specifically bound to the outer membrane of P. aeruginosa through PMB to increase the membrane sensitivity to photodynamic treatment. Under dual-light irradiation, a large amount of iron ions released by HMAPH underwent a Fenton reaction with H2O2 in bacteria to generate hydroxyl radicals (•OH), enabling direct killing of cells by hyperthermia. Additionally, the photodynamic activity of MB released by photo-induced activation led to the generation of reactive oxygen species, achieving synergistic and effective inhibition of P. aeruginosa. HMAPH also inhibited biofilm formation and downregulated the expression of virulence factors. In vivo experiments revealed that HMAPH accelerated the healing of P. aeruginosa-infected wounds by promoting angiogenesis and skin regeneration, inhibiting the inflammatory response and promoting M1 to M2 polarization.

Conclusions

Our study proposed a strategy against bacteria and biofilms through a synergistic photothermal–photodynamic–Fenton reaction, opening up new prospects for combating biofilm-associated infections.
Skin oncology
Authors: Tang Gia Toan , Wong Gwyneth Natalie , Nirenberg Alexander , Scardamaglia Laura
Published: September 2024

This case involves a 68-year-old woman who presented with self-resolving violaceous papules on the abdomen, and nodules and plaques on the back.