bluuebunny/crossref_metadata_2025 huggingface dataset:
Intra-specific variation in relative embryo length and germination of wild Daucus carota across climate gradients in North America and Europe
Authors: Vandelook Filip , Van de Vyver Ann , Soltani Elias
Published: December 2024

Although seed trait variations and their relationship to the ecological niche have been studied extensively at the species level, they do not necessarily reflect variations at the population level. In this study, we explored the intra-specific variation in relative embryo length, seed mass and germination speed in 40 populations of Daucus carota distributed across Europe and North America. By including information on local climate conditions, we aimed to examine the impact of the geographical origin on various seed functional traits and to detect potential local adaptation. No significant difference was observed in final seed germination for European and North American seeds incubated at 20°C, nor in seed viability. In European populations, relative embryo length significantly increased with increasing seed mass, but no such relation was found in North American populations. Larger relative embryo length at dispersal resulted in increased germination speed in both European and North American populations. Populations in drier areas typically had seeds with larger relative embryo lengths. Precipitation-related climate variables showed a negative relationship with relative embryo length, indicating a reduction in relative embryo length with increased precipitation. No clear relationship between climate and seed mass was observed. We can conclude that seed functional traits of D. carota are adapted to local climate conditions, as a clear gradient was observed in the relative embryo length of D. carota, which was associated with germination speed and climate. This gradient was less pronounced in North America, which can be explained by its relatively recent introduction to the continent.
Prediction of p-block-based ternary superconductors XC2H8 at low pressure
Authors: Wrona Izabela A. , Niegodajew Paweł , Li Yinwei , Durajski Artur P.
Published: December 2024

Achieving room-temperature superconductivity under ambient conditions is one of the most important goals in solid-state physics and material science. Recent discoveries of high-Tc superconductivity in binary hydrides H3S and LaH10 at high pressures have focused the search for room-temperature superconductors on dense hydrides with conventional phonon-mediated pairing mechanisms. In this study, we predict a novel family of superconducting ternary hydrides under moderate compression, XC2H8 (X = Ga, In, Tl, Sn, Pb, Sb, Bi, Te, Po). Unlike H3S and LaH10, these new materials are stable at just around 20 GPa. Among the analyzed compounds, SbC2H8 exhibits the highest critical temperature of 73 K at a pressure of 100 GPa, which is attributed to its energetically favorable high-symmetry crystal structure ($$Fm{\bar{3}}m$$

F
m

3

¯

m

), high density of states at the Fermi level (1.27 states/eV) and strong electron–phonon coupling constant (1.02). We expect that our findings provide crucial insights into achieving high-temperature superconductivity at moderate pressures and accelerate the progress of experimental research.
Downregulation of IRF7-mediated type-I interferon response by LmCen–/– parasites is necessary for protective immunity
Authors: Sepahpour Telly , Alshaweesh Jalal , Azodi Nazli , Singh Komudi , Ireland Derek D. C. , Valanezhad Farzaneh , Nakamura Risa , Satoskar Abhay R. , Dey Ranadhir , Hamano Shinjiro , Nakhasi Hira L. , Gannavaram Sreenivas
Published: December 2024

Leishmaniasis is a tropical disease caused by Leishmania parasites and currently has no licensed vaccines. We developed a dermotropic Leishmania major centrin gene-deleted strain (LmCen–/–) as a live attenuated vaccine. Recent studies have shown that type I interferons (IFNs) play important roles in immunity to parasitic and viral pathogens. However, their relevance in protective immunity following vaccination is not understood. We found that immunization with LmCen–/– induces a transient increase in type I IFN response along with its regulatory factor IRF7 that is downregulated 7–21 days post-immunization, coincided with the induction of a robust Th1 adaptive immune response. Challenge infection with virulent L. donovani parasites showed a significant reduction of splenic and hepatic parasite burden in IRF7–/– mice than wild type mice following immunization with LmCen–/–, suggesting that ablation of type I IFN response is a pre-requisite for the induction of LmCen–/– mediated Th1 immunity against L. donovani infection.
Global datasets of geospatial-AI-resolved energy consumers including climate-driven energy demands, geographical and socioeconomic realities for a transition reset
Authors: Moya Diego , Copara Dennis , Giarola Sara , Hawkes Adam
Published: December 2024

Traditional models deliberately simplify millions of consumers into a single, homogeneous, representative agent with perfect market knowledge and rational expectations, limiting their capacity to capture real-world complexities. To address this limitation in mainstream models, this article provides global datasets to parametrise energy consumers within climate-energy-economy models considering climate-driven energy demand, socioeconomic and demographic factors. The datasets emerge from applying geospatial artificial intelligence, machine learning and big data analytics on a range of geospatial parameters at 1 km2 resolution. Twenty distinctive energy consumers are defined using three heterogeneous geospatial features, eight diverse and two evolving parameters. This parametrisation of consumers strengthens the applicability of climate-energy-economy models to guide effective, equitable and just climate policy design. This comprehensive analysis of complex interactions between climate, socioeconomic and demographic factors supports more realistic decision-making for a sustainable transition reset. This research emphasises the geospatial distribution of energy consumers to enhance technoeconomic assessment, understanding consumer dynamics for consumer-led resource allocation and informed policy implementation. These datasets can be used in climate-energy-economy models to parametrise consumers beyond traditional approaches.
Corneal protein repair after amniotic membrane photo-tissue bonding versus amniotic membrane graft in the treatment of corneal ulcer (an experimental study)
Authors: Mohammad Shaimaa , Abdelkawi Salwa , Ebrahim Mona , Ahmed Aziza , Fouad Dina
Published: December 2024

Corneal alkali burns persist as a significant challenge in our field, often leading to a prolonged treatment course with various sight-threatening problems. This work, of utmost importance, aimed to apply the photo-tissue bonding technique (PTB) to weld the amniotic membrane (AM) to the corneal surface versus an amniotic membrane graft (AMG) and explore its safety in saving corneal protein against alkali burn.

Methods Twenty-seven rabbits with an induced corneal ulcer using 1 mol/L NaOH solution. Nine rabbits were used as an ulcer group without treatment, and the rest (n = 18) were subjected to two treatment protocols with AM. The first was attaching the AM to the corneal ulcer through photo-tissue bonding using 532 nm and rose Bengal stain as a photosynthesizing agent. The second was using cyanoacrylate glue as a tissue adhesive. The corneal total protein (TP), refractive index (RI), DNA fragmentation, and oxidative stress index (OSI) were evaluated. Results: The cornea’s TP showed a significant decrease (p˂0.001) immediately, 1 week, and 2 weeks after ulcer induction (-58.9%, -64.4%, and − 72.6%, respectively). The treatment with AM PTB showed improvement immediately (-45.2%, p˂0.001), after one week (-27.4%, p˂0.01), and after two weeks (-14.38%, p˂0.05). Moreover, the treatment with AMG showed improvement after the same periods with percentage changes of -52.05%, (p˂0.001), -41.8% (p˂0.001), and − 32.2%, (p˂0.01) with respect to the control. Moreover, RI of corneal protein showed improvement after two weeks of treatment with AM PTB (3%, p˃0.05) and AMG (7%, p˃0.05), respectively. The corneal protein DNA base pairs improved 88.49% for AM PTB and 82.35% for the AMG group. The oxidative stress was shifted towards an antioxidative state in AM PTB (-3.9%, P > 0.05) and the AMG group (15.9%, P < 0.05). Conclusion: The AM PTB technique used in corneal ulcers showed promising improvement in total corneal proteins, refractive index, DNA fragmentation, and OSI than AMG using cyanoacrylate glue. These results strongly support the use of AM PTB for ophthalmic purposes, suggesting its potential to enhance clinical research and practice for patients with corneal ulcers and ocular surface diseases.
A novel spatiotemporal prediction approach to fill air pollution data gaps using mobile sensors, machine learning and citizen science techniques
Authors: Baruah Arunik , Bousiotis Dimitrios , Damayanti Seny , Bigi Alessandro , Ghermandi Grazia , Ghaffarpasand O. , Harrison Roy M. , Pope Francis D.
Published: December 2024

Particulate Matter (PM) air pollution poses significant threats to public health. We introduce a novel machine learning methodology to predict PM2.5 levels at 30 m long segments along the roads and at a temporal scale of 10 seconds. A hybrid dataset was curated from an intensive PM campaign in Selly Oak, Birmingham, UK, utilizing citizen scientists and low-cost instruments strategically placed in static and mobile settings. Spatially resolved proxy variables, meteorological parameters, and PM properties were integrated, enabling a fine-grained analysis of PM2.5. Calibration involved three approaches: Standard Random Forest Regression, Sensor Transferability and Road Transferability Evaluations. This methodology significantly increased spatial resolution beyond what is possible with regulatory monitoring, thereby improving exposure assessments. The findings underscore the importance of machine learning approaches and citizen science in advancing our understanding of PM pollution, with a small number of participants significantly enhancing local air quality assessment for thousands of residents.
Storm Daniel fueled by anomalously high sea surface temperatures in the Mediterranean
Authors: Argüeso D. , Marcos M. , Amores A.
Published: December 2024

In September 2023, Cyclone Daniel formed in the Mediterranean, severely affecting Greece and Libya, and becoming the deadliest storm in Mediterranean history. The Mediterranean’s unusually high sea surface temperatures (SST) likely contributed to the cyclone’s intensity and extreme rainfall. Greece saw over 700 mm of rain in 18 h, while Libya experienced daily records exceeding 400 mm, leading to catastrophic infrastructure failures. Our hypothesis is that high SSTs provided additional energy and moisture fueling Daniel’s intensification. Using the Weather Research and Forecasting model, we conducted numerical experiments to quantify the role of high SSTs during the event. Comparing actual conditions with a counterfactual scenario, we found that the long-term global warming signal in SSTs significantly increased the storm’s intensity and precipitation. This study underscores the need to understand rising SSTs contribution to predicting and mitigate future tropical-like cyclones as global temperatures increase.
Predicting the tumor microenvironment composition and immunotherapy response in non-small cell lung cancer from digital histopathology images
Authors: Patkar Sushant , Chen Alex , Basnet Alina , Bixby Amber , Rajendran Rahul , Chernet Rachel , Faso Susan , Kumar Prashanth Ashok , Desai Devashish , El-Zammar Ola , Curtiss Christopher , Carello Saverio J. , Nasr Michel R. , Choyke Peter , Harmon Stephanie , Turkbey Baris , Jamaspishvili Tamara
Published: December 2024

Immune checkpoint inhibitors (ICI) have become integral to treatment of non-small cell lung cancer (NSCLC). However, reliable biomarkers predictive of immunotherapy efficacy are limited. Here, we introduce HistoTME, a novel weakly supervised deep learning approach to infer the tumor microenvironment (TME) composition directly from histopathology images of NSCLC patients. We show that HistoTME accurately predicts the expression of 30 distinct cell type-specific molecular signatures directly from whole slide images, achieving an average Pearson correlation of 0.5 with the ground truth on independent tumor cohorts. Furthermore, we find that HistoTME-predicted microenvironment signatures and their underlying interactions improve prognostication of lung cancer patients receiving immunotherapy, achieving an AUROC of 0.75 [95% CI: 0.61-0.88] for predicting treatment responses following first-line ICI treatment, utilizing an external clinical cohort of 652 patients. Collectively, HistoTME presents an effective approach for interrogating the TME and predicting ICI response, complementing PD-L1 expression, and bringing us closer to personalized immuno-oncology.
Development of a Helmholtz free energy equation of state for fluid and solid phases via artificial neural networks
Authors: Chaparro Gustavo , Müller Erich A.
Published: December 2024

A longstanding challenge in thermodynamics has been the development of a unified analytical expression for the free energy of matter capable of describing all thermodynamic properties. Although significant strides have been made in modeling fluid phases using continuous equations of state (EoSs), the crystalline state has remained largely unexplored because of its complexity. This work introduces an approach that employs artificial neural networks to construct an EoS directly from comprehensive molecular simulation data. The efficacy of this method is demonstrated through application to the Mie potential, resulting in a thermodynamically consistent model seamlessly bridging fluid and crystalline phases. The proposed EoS accurately predicts metastable regions, enabling a comprehensive characterization of the phase diagram, which includes the critical and triple points.
Highly sensitive terbium-based metal–organic framework scintillators applied in flexible X-ray imaging
Authors: Wang Peng-Kun , Wang Wen-Fei , Li Bao-Yi , Qian Rui-Xuan , Gao Zhao-Xing , Wang Shuai-Hua , Zheng Fa-Kun , Guo Guo-Cong
Published: December 2024

A high radioluminescence sensitivity and low detection limit terbium-based metal–organic framework scintillator was applied for high-resolution flexible X-ray imaging.
Organocatalytic enantioselective [2 + 2] cycloadditions towards chiral fused α-trifluoromethyl azetidines
Authors: Zhang Song , Luo Xingjie , Fang Siqiang , Wu Jia-Hong , Pan Jianke , Xu Zhipeng , Wang Tianli
Published: December 2024

Herein, we report straightforward access to chiral fused α-trifluoromethyl azetidines via organocatalytic asymmetric [2 + 2] cycloadditions. This method is characterized by mild reaction conditions, high efficiency, and excellent stereoselectivities.
Determining the acceleration regions of in situ electrons using remote radio and X-ray observations
Authors: Morosan D. E. , Dresing N. , Palmroos C. , Gieseler J. , Jebaraj I. C. , Warmuth A. , Fedeli A. , Normo S. , Pomoell J. , Kilpua E. K. J. , Zucca P. , Dabrowski B. , Krankowski A. , Mann G. , Vocks C. , Vainio R.
Published: December 2024

Context. Solar energetic particles in the heliosphere are produced by flaring processes on the Sun or by shocks driven by coronal mass ejections. These particles are regularly detected remotely as electromagnetic radiation (X-rays or radio emission), which they generate through various processes, or in situ by spacecraft monitoring the Sun and the heliosphere.

Aims. Our aim is to combine remote-sensing and in situ observations of energetic electrons to determine the origin and acceleration mechanism of these particles.

Methods. Here we investigate the acceleration location, escape, and propagation directions of electron beams producing radio bursts observed with the Low Frequency Array (LOFAR), hard X-ray (HXR) emission, and in situ electrons observed at Solar Orbiter on 3 October 2023. These observations are combined with a three-dimensional (3D) representation of the electron acceleration locations and results from a magnetohydrodynamic (MHD) model of the solar corona in order to investigate the origin and connectivity of electrons observed remotely at the Sun to in situ electrons.

Results. We observed a type II radio burst with good connectivity to Solar Orbiter, where a significant electron event was detected. However, type III radio bursts and hard X-rays were also observed co-temporally with the electron event, but likely connected to Solar Orbiter by different far-side field lines. The injection times of the Solar Orbiter electrons are simultaneous with both the onset of the type II radio burst, the group of type III bursts, and the presence of a second HXR peak; however, the most direct connection to Solar Orbiter is that of the type II burst location. The in situ electron spectra point to shock acceleration of electrons with a short-term connection to the source region.

Conclusions. We propose that there are two contributions to the Solar Orbiter electron fluxes based on the results and magnetic connectivity determined from remote-sensing data: a smaller flare contribution from the far-side of the Sun and a main shock contribution from the region close to the eastern limb as viewed from Earth. We note that these two electron acceleration regions are distinct and separated by a large distance and are connected via two separate field lines to Solar Orbiter.
PRATIC: A soluble-boron-free, pressurized water cooled, SMR core benchmark
Authors: Vuiart Romain , Eustache Aimeric , Eveillard Sarah , Prulhière Géraud
Published: December 2024

Current nuclear reactor research is actively exploring small modular pressurized water reactors (PWRs), particularly soluble-boron-free (SBF) configurations. SBF designs utilize control rods and gadolinium-poisoned fuel rods to manage reactivity. Additionally, small modular reactors (SMRs) commonly integrate steel reflectors to minimize neutron leakage. However, the compactness of SMRs and the adoption of these technical solutions result in notable fluctuations in neutron flux within the core during normal cycle operation. Hence, comprehensive analysis is essential, especially concerning reactor performance under normal and accident conditions, the reliability of neutronics calculation assumptions, etc. Research into these issues requires reactor core neutronics benchmarks that are consistent with industrial concepts so that the analysis results can be applied to real reactors. In this context, this article introduces PRATIC, a SBF-PWR SMR core neutronics benchmark designed to match the global performances of industrial concepts. The development of PRATIC was conducted using a deterministic calculation scheme coupling the APOLLO2 and CRONOS2 codes. PRATIC features a thermal power of 350 MWth, an equilibrium cycle length of 1.9 years, and an average discharge burnup of about 34 GWd/t, while maintaining controlled power distributions. The article elaborates on the design assumptions for PRATIC, then details the reactor core and its equilibrium cycle. Access to the PRATIC modeling data is available via a GIT repository, accessible upon request via email at pratic@cea.fr.
Stimulus-invariant aspects of the retinal code drive discriminability of natural scenes
Authors: Hoshal Benjamin D. , Holmes Caroline M. , Bojanek Kyle , Salisbury Jared M. , Berry Michael J. , Marre Olivier , Palmer Stephanie E.
Published: December 2024

Everything that the brain sees must first be encoded by the retina, which maintains a reliable representation of the visual world in many different, complex natural scenes while also adapting to stimulus changes. This study quantifies whether and how the brain selectively encodes stimulus features about scene identity in complex naturalistic environments. While a wealth of previous work has dug into the static and dynamic features of the population code in retinal ganglion cells (RGCs), less is known about how populations form both flexible and reliable encoding in natural moving scenes. We record from the larval salamander retina responding to five different natural movies, over many repeats, and use these data to characterize the population code in terms of single-cell fluctuations in rate and pairwise couplings between cells. Decomposing the population code into independent and cell–cell interactions reveals how broad scene structure is encoded in the retinal output. while the single-cell activity adapts to different stimuli, the population structure captured in the sparse, strong couplings is consistent across natural movies as well as synthetic stimuli. We show that these interactions contribute to encoding scene identity. We also demonstrate that this structure likely arises in part from shared bipolar cell input as well as from gap junctions between RGCs and amacrine cells.
Confinement-sensitive volume regulation dynamics via high-speed nuclear morphological measurements
Authors: Li Yixuan , Ong Hui Ting , Cui Hongyue , Gao Xu , Lee Jia Wen Nicole , Guo Yuqi , Li Rong , Pennacchio Fabrizio A. , Maiuri Paolo , Efremov Artem K. , Holle Andrew W.
Published: December 2024

Diverse tissues in vivo present varying degrees of confinement, constriction, and compression to migrating cells in both homeostasis and disease. The nucleus in particular is subjected to external forces by the physical environment during confined migration. While many systems have been developed to induce nuclear deformation and analyze resultant functional changes, much remains unclear about dynamic volume regulation in confinement due to limitations in time resolution and difficulty imaging in PDMS-based microfluidic chips. Standard volumetric measurement relies on confocal microscopy, which suffers from high phototoxicity, slow speed, limited throughput, and artifacts in fast-moving cells. To address this, we developed a form of double fluorescence exclusion microscopy, designed to function at the interface of microchannel-based PDMS sidewalls, that can track cellular and nuclear volume dynamics during confined migration. By verifying the vertical symmetry of nuclei in confinement, we obtained computational estimates of nuclear surface area. We then tracked nuclear volume and surface area under physiological confinement at a time resolution exceeding 30 frames per minute. We find that during self-induced entrance into confinement, the cell rapidly expands its surface area until a threshold is reached, followed by a rapid decrease in nuclear volume. We next used osmotic shock as a tool to alter nuclear volume in confinement, and found that the nuclear response to hypo-osmotic shock in confinement does not follow classical scaling laws, suggesting that the limited expansion potential of the nuclear envelope might be a constraining factor in nuclear volume regulation in confining environments in vivo.
Alveolar macrophages are early targets of mumps virus
Authors: Patel Aum R. , Garg Amit , Rosberger Haylen T. , Kowdle Shreyas , Reis Rebecca A. , Frere Justin J. , Januska Megan N. , Dawodu Gbalekan , Valencia Estefania , Yang Min-Chi , Stevens Christian S. , Rao Vishal N. , Haas Griffin D. , Chen Ya-Wen , Lee Benhur , Lim Jean K.
Published: December 2024

Formerly a common childhood pathogen, mumps virus (MuV) remains active worldwide, despite relatively high vaccine coverage. MuV is thought to infect the upper respiratory tract before disseminating to other organs; however, the early cellular targets of MuV in vivo are unknown. To address this, we generated a green fluorescent protein (GFP)-tagged vaccine strain (JL5) of MuV to infect leukocytic cell lines and found that replication was greatest in monocytes. Infection of peripheral blood mononuclear cells (PBMCs) also showed that both JL5 and a circulating strain of MuV (Iowa 2006; genotype G), preferentially infected monocytes. Further, monocyte-derived macrophages showed high susceptibility to MuV, with genotype G infecting macrophages to a much greater extent. While mice are generally resistant to MuV infection, we inoculated immunocompetent Rosa26-tdTomato mice intranasally with a GFP and Cre recombinase tagged MuV to determine whether monocytes/macrophages are important targets in vivo. We observed a small population of tdTomato
+
cells within the lungs, which included epithelial cells; however, the vast majority were alveolar macrophages (AMs). To validate these findings, we infected murine AMs isolated from Rosa26-tdTomato mice with the GFP and Cre recombinase tagged MuV and found that while MuV could enter AMs, as determined by tdTomato positivity, only a small percentage of these expressed GFP, suggesting that inhibition in murine cells occurs postentry. To translate these findings, we infected cells from human bronchoalveolar lavage fluid with MuV and found that most infected cells were AMs. These findings highlight the high susceptibility of AMs and provide a basis for early MuV pathogenesis and subsequent dissemination.
Understanding student challenges with circulation and Ampère–Maxwell law
Authors: Suárez Álvaro , Marti Arturo C , Zuza Kristina , Guisasola Jenaro
Published: December 2024

We investigated how students apply the concept of circulation when faced with problems related to the Ampère–Maxwell law. For this purpose, we designed a metacognitive pencil-and-paper question, presented it to 65 students, and analysed their responses using phenomenography. We complemented our research by conducting interviews with 12 students. The results show that students tend to think that they can only use the magnetic field circulation to calculate magnetic fields if the curve used is symmetric, and that they do not take into account the shape of the magnetic field lines when applying it. We also find that some students believe that a variable electric field must cross the entire Amperian curve in order to apply Ampère–Maxwell's law and find the magnetic field.
Efficient sparsity-promoting MAP estimation for Bayesian linear inverse problems
Authors: Lindbloom Jonathan , Glaubitz Jan , Gelb Anne
Published: December 2024

Bayesian hierarchical models can provide efficient algorithms for finding sparse solutions to ill-posed linear inverse problems. The models typically comprise a conditionally Gaussian prior model for the unknown augmented by a generalized gamma hyper-prior model for the variance hyper-parameters. This investigation generalizes such models and their efficient maximum a posterior estimation using the iterative alternating sequential algorithm in two ways: (1) general sparsifying transforms: diverging from conventional methods, our approach permits use of sparsifying transformations with nontrivial kernels; (2) unknown noise variances: the noise variance is treated as a random variable to be estimated during the inference procedure. This is important in applications where the noise estimate cannot be accurately estimated a priori. Remarkably, these augmentations neither significantly burden the computational expense of the algorithm nor compromise its efficacy. We include convexity and convergence analysis and demonstrate our method’s efficacy in several numerical experiments.
A BP-Smith combined temperature control method for thin film preparation processing
Authors: Huang Yajie , Zhang Donglai , Zhang Bin , Pan Shimin , Li Anshou , Wang Yi
Published: December 2024

Thin film preparation methods are receiving increasing attention because of their wide range of applications in semiconductor devices, optoelectronics, flat panel displays, solar cells, sensors, micromechanical systems, and other fields, and they provide essential technologies for the development and application of various advanced materials. This paper proposes a method combining BP neural network control and Smith prediction to solve the nonlinear thermal regulation control problem and consider the coupling effect between temperature regions in a multi-region setting. The BP neural network is used to control the dynamic neural network to identify the dynamic model of the temperature area and realize online learning of neural network weights. The system uses Smith prediction to solve the delay problem and ensure system performance. Our controlled equipment is a tank for the boron diffusion process. The control goal of this paper is to track the target temperature stably and accurately through the proposed method. The temperature control accuracy is within ±1 °C tolerance of set point in steady state. The temperature control strategy proposed here also adds an error factor for temperature coupling in the neural network part, and the control results are better able to meet the temperature control requirements of the actual process. This method provides innovative insights into and effective solutions for temperature control during thin film preparation. It reduces the amount of overshoot, saves a lot of power and manpower for model change temperature control, and is a highly adaptive model change control method. This paper begins by theoretically analyzing the advantages of neural networks and Smith predictive control. Secondly, thermal simulations are performed to analyzes the coupling conditions between the temperature zones. Finally, experimental tests evaluate the steady-state and dynamic performances of the control strategy and verify the intended advantages of the proposed control method.
Validation of the static forward Grad–Shafranov equilibrium solvers in FreeGSNKE and Fiesta using EFIT++ reconstructions from MAST-U
Authors: Pentland K , Amorisco N C , El-Zobaidi O , Etches S , Agnello A , Holt G K , Ross A , Vincent C , Buchanan J , Pamela S J P , McArdle G , Kogan L , Cunningham G
Published: December 2024

A key aspect in the modelling of magnetohydrodynamic (MHD) equilibria in tokamak devices is having access to fast, accurate, and stable numerical simulation methods. There is an increasing demand for reliable methods that can be used to develop traditional or machine learning-based shape control feedback systems, optimise scenario designs, and integrate with other plasma edge or transport modelling codes. To handle such applications, these codes need to be flexible and, more importantly, they need to have been validated against both analytically known and real-world tokamak equilibria to ensure they are consistent and credible. In this paper, we are interested in solving the static forward Grad–Shafranov (GS) problem for free–boundary MHD equilibria. Our focus is on the validation of the static forward solver in the Python-based equilibrium code FreeGSNKE by solving equilibria from magnetics-only EFIT
++ reconstructions of MAST-U shots. In addition, we also validate FreeGSNKE against equilibria simulated using the well-established MATLAB-based equilibrium code Fiesta. To do this, we develop a computational pipeline that allows one to load the same (a)symmetric MAST-U machine description into each solver, specify the required inputs (active/passive conductor currents, plasma profiles and coefficients, etc.) from EFIT++, and solve the GS equation for all available time slices across a shot. For a number of different MAST-U shots, we demonstrate that both FreeGSNKE and Fiesta can successfully reproduce various poloidal flux quantities and shape targets (e.g. midplane radii, magnetic axes, separatrices, X-points, and strikepoints) in agreement with EFIT++ calculations to a very high degree of accuracy. We also provide public access to the code/data required to load the MAST-U machine description in FreeGSNKE/Fiesta and reproduce the equilibria in the shots shown.
FreeFEM analysis of thermally induced higher-grade Darcy-Forchheimer flow through heated semi-circular cylinders
Authors: Khan M S , Azmat U
Published: December 2024

In this article, a higher grade Darcy-Forchheimer porous model is derived by using the concepts of tensor calculus. The model presented is accounting for non-linear flow behavior at highly permeable media where the flow is induced by temperature boundary conditions. To this end, a square geometry with two semi-circular heating cylinders mounted at its bottom wall is considered for the analysis of thermal flow dynamics. To solve the obtained coupled system of highly nonlinear partial differential equations the finite element procedure is adopted. Weak formulation of the problem is calculated via the application of variational calculus. The numerical algorithm is implemented through the open source code FreeFEM++. Obtained solutions are validated by reduced model with exact solutions. Mesh independence of the solution is shown through mesh independence analysis test. Results are computed for varying physical parameters with some interesting new observations. Moreover, streamline plots for the velocities and isotherms are shown and discussed. It is found that the Nusselt number increases with increasing Grashhoff and Frochheimer numbers, but decreases with increasing medium porosity.
STOLAS: STOchastic LAttice Simulation of cosmic inflation
Authors: Mizuguchi Yurino , Murata Tomoaki , Tada Yuichiro
Published: December 2024

We develop a C++ package of the STOchastic LAttice Simulation (STOLAS) of cosmic inflation. It performs the
numerical lattice simulation in the application of the stochastic-δ N formalism.
STOLAS can directly compute the three-dimensional map of the observable curvature
perturbation without estimating its statistical properties. In its application to two toy models
of inflation, chaotic inflation and Starobinsky's linear-potential inflation, we confirm that
STOLAS is well-consistent with the standard perturbation theory. Furthermore, by introducing
the importance sampling technique, we have success in numerically sampling the current abundance
of primordial black holes (PBHs) in a non-perturbative way. The package is available at
https://github.com/STOchasticLAtticeSimulation/STOLAS_dist.
Investigation on the Mechanical Properties of the Protective Shield in an Industrial Smart Safety Vest
Authors: Yip Tong Joe , Singh Amares
Published: December 2024

This research investigates the mechanical properties of polyester fabric and Kevlar for use as protective shields in industrial smart safety vests. Through ANSYS simulations, the tensile strength, impact resistance, and hardness of these materials were analysed. The findings highlight the suitability of these materials for different industrial applications, focusing on design considerations and integration with smart technology components. Recommendations for future research include advanced material development, multi-physics simulations, and long-term durability studies.
Investigation of Leakage Current in 150 kV Payakumbuh Koto Panjang Insulators
Authors: Amalia Sitti , Rajab Abdul , Novizon  , Warmi Yusreni , Kasmar Andre Febrian
Published: December 2024

Insulators in electrical energy transmission and distribution systems play an important role. This study investigates the impact of surface contamination, including dust and moss, on the leakage current (LC) characteristics of 150 kV insulators in the Payakumbuh - Koto Panjang area, West Sumatra. Testing the leakage current with varying temperature and humidity conditioning and measuring NSDD (non-soluble deposit density) and ESDD (equivalent salt deposit density) using the swab technique in accordance with the IEC TS 60815-1-2008 standard, this study aims to determine the LC and the level of contamination. Research results. In insulators with one disk, the LC is about 0.15 mA for moss and 0.18 mA for dust. For two disks, the LC increases to about 0.17 mA for moss and 0.22 mA for dust, while at three disks, the LC reaches about 0.2 mA for moss and 0.32 mA for dust. In addition, dust-contaminated insulators show higher ESDD (0,206128196) and NSDD (0,379475496) values than moss-contaminated EDDD (0, 058510867) and NSDD (0, 164784579). In conclusion, addressing dust contamination is critical to improving electrical system reliability, given its more pronounced effect on insulator performance compared to moss contamination of 150 kV insulators at Payakumbuh - Koto Panjang.
Study of Types of Biomass Briquettes with Molding Machine Production Rotary Press System Briquettes Made from Natural Fiber
Authors: Handra Nofriady , Indra Ade , Nurzal  , Maryam
Published: December 2024

The potential for agricultural residue-derived organic matter in Indonesia is quite abundant, including substance empty fruit bunches (EFB), areca and coconut substance. Biomass residue can serve as an ingredient option combustible in the form of compressed combustible blocks. This research aims to analyse the type of organic matter compressed combustible blocks used by using different types of substances. Processing and making compressed combustible blocks using organic matter residue is an option for producing combustible sources, where in this research several varieties of organic matter substance residue are used to make compressed combustible blocks, including EFB, coconut and areca substance residue which is processed using a rotary press briquette press. The binder uses starch with a composition of 70% and 30%. The lowest water composition was found in EFB fiber compressed combustible blocks (6.3%), areca nut fiber compressed combustible blocks (6.8%), and coconut (7.6%), all of which were below SNI standards. The ash composition produced by EFB compressed combustible blocks was higher at 8.7% and the lowest was 6.8% for coconut substance compressed combustible blocks. The findings of evaluation the power composition of all types of natural fiber substances used as organic matter compressed combustible blocks show that the highest power composition is produced in EFB substance with a size of 12 mesh of 4203 cal/g. At the substance briquette size of 16 mesh, the highest measurement was obtained for the areca fiber briquette fiber with a power composition of 3992 cal/g, while at the 20 mesh size the highest measurement was obtained for the areca substance briquette fiber with a power composition of 4056 cal/g. Based on the division of briquette classes based on power composition, the highest power composition of compressed combustible blocks is in class D between 4200 - 2941 cal/g.
Optimizing Heat Sink Design: Achieving an Enhanced Heat Dissipation through Oval Perforation
Authors: Mohammed Abdulrahman , A Singh
Published: December 2024

This paper explores the thermal efficiency of the perforated in a typical heat sink used in automotive industry. The aim is to investigate the heat dissipation in the heat sink. The research includes designing heat sinks using 3D SolidWorks model and performing steady-state thermal analysis with ANSYS. The outcome showed an 18 % increase in the maximum heat flux, indicating better thermal performance and increased heat dissipation capacities for the oval perforations. Additionally, the perforations led to an approximate 29% decrease in the cost of producing a heat sink. The maiden results indicate the potential for improving thermal efficiency of a heat sink in a via oval-shaped perforations.
Tidal-induced and wind-driven ocean surface current data analysis derived from HF radar in Bali Strait
Authors: Aldini I , Permanasari AE , Hidayat R , Ramdhani A
Published: December 2024

The ocean surface currents (OSC) are subject to the influences of surface wind, tidal conditions, and various other factors. Understanding these forces is essential for efficient coastal management, port activities, environmental surveillance, and the precise forecasting of ocean currents in the region. This study examined ocean surface current (OSC) data in the Bali Strait from December 2020 to November 2021. The analysis used HF radar data and the DCCA (De-trended Cross-Correlation) method. The DCCA approach examined the correlation between OSC with tidal and wind data. The study demonstrated the capabilities of HF radar data and the DCCA technique in providing valuable insights into OSC behaviours associated with tidal and wind impacts. The peak correlation value was observed when the OSC value reached its highest point in July 2021. The study showed that, overall, the correlation of OSC with tide data surpassed its correlation with wind data, emphasizing the significant influence of both tidal and wind forces on the ocean surface current in the Bali Strait. Tidal forces exhibited a stronger correlation with OSC, highlighting their crucial roles in shaping ocean surface currents in the region. These discoveries are essential for enhancing our comprehension of ocean surface currents in several sectors, especially for their application in environmental monitoring and forecasting ocean currents to maintain environmental safety and efficient coastal management practices.
Prospects, Challenges and Solutions for Achieving Sustainability in Implementing Green Architecture Strategies in High-Rise Buildings: A Review
Authors: Aduwo E. B. , Sholanke A. B. , Eleagu J. C.
Published: December 2024

Due to the escalating concerns over climate change and environmental degradation, the adoption of green architecture principles in high-rise buildings has become imperative. This study examined existing literature on green architecture with a view to determine prospects, challenges and solutions of implementing green architecture features within the context of skyscrapers to achieve sustainability. The study is a review paper that relied on secondary sources to gather data from 43 articles. The data were content analysed using thematic approach and the findings descriptively presented in themes, with the aid of figures and tables. The findings underscored the potential of green architecture to address pressing concerns related to climate change and environmental degradation. The review revealed that incorporating green architecture principles in high-rise buildings offers significant potential for reducing energy consumption, minimizing environmental impact, and enhancing occupant’s well-being. However, conflicting priorities, operational inefficiencies, and the potential pitfalls of green building initiatives pose significant hurdles to implementing green architecture strategies in high-rise buildings. Also, the scale and complexity of skyscrapers which demand innovative solutions and careful considerations that are not oftentimes fully envisaged in the planning and design stages, is also a challenge. The study suggests fostering communication among stakeholders and advocates for widespread adoption of green building practices towards enhancing sustainability in the development of high-rise buildings.
Intelligence as Computation
Authors: Brock Oliver
Published: December 2024

This paper proposes a specific conceptualization of intelligence as computation. This conceptualization is intended to provide a unified view for all disciplines of intelligence research. Already, it unifies several conceptualizations currently under investigation, including physical, neural, embodied, morphological, and mechanical intelligences. To achieve this, the proposed conceptualization explains the differences among existing views by different computational paradigms, such as digital, analog, mechanical, or morphological computation. Viewing intelligence as a composition of computations from different paradigms, the challenges posed by previous conceptualizations are resolved. Intelligence is hypothesized as a multi-paradigmatic computation relying on specific computational principles. These principles distinguish intelligence from other, non-intelligent computations. The proposed conceptualization implies a multi-disciplinary research agenda that is intended to lead to unified science of intelligence.
3D printed elastomers with superior stretchability and mechanical integrity by parametric optimization of extrusion process using Taguchi Method
Authors: Bayati Abbas , Ahmadi Mina , Rahmatabadi Davood , Khodaei Mohammad , Xiang Hao , Baniassadi Majid , Abrinia Karen , Zolfagharian Ali , Bodaghi Mahdi , Baghani Mostafa
Published: December 2024

This study focused on a modified Fused Deposition Modeling (FDM) 3D printing method, specifically the direct pellet printing of a propylene-based thermoplastic elastomer, Vistamaxx™ 6202, to address challenges like printability and weak mechanical properties. The main objective was optimizing printing parameters and investigating their impact on the mechanical properties. The Taguchi method was used to design the experiments, reducing the required experiments and optimizing printing parameters to maximize desired properties. Three influential parameters were chosen, each changing to three levels. By employing the Taguchi method, the number of experiments decreased from 27 full factorials to 9. Regression models were created through analysis of variance (ANOVA) and verified by additional experiments. Tensile tests were performed according to the ASTM D638 standard. SEM imaging was used to assess interlayer adhesion and structural integrity. The results demonstrated satisfactory interlayer adhesion and structural integrity of the printed samples. Notably, the printed thermoplastic elastomers achieved significant stretchability, reaching up to 5921.3%. The tensile strength was 5.22 MPa, with a tensile modulus of 1.7 MPa. The effect of each parameter and their contribution percentage to the tensile strength, elongation, and elastic modulus were obtained from the variance analysis.
Detection of sleep K-complexes using BOHB-tuned XGBoost based on multi-domain feature extraction and KMeansSMOTE
Authors: Xiong Xin , Ren Shixin , Yi Sanli , Wang Chunwu , Liu Ruixiang , He Jianfeng
Published: December 2024

The K-complex, a distinctive brain wave pattern observed during sleep, holds significant importance in sleep research. Traditional manual annotation of electroence-phalogram (EEG) signals is time-consuming,labor-intensive and prones to errors. Although some studies have focused on the automatic detection of K-complexes, they still struggle to effectively address the issues caused by data imbalance. Therefore, the study demonstrates a method for detecting sleep K-complexs based on multi-domain feature extraction, KMeansSMOTE technology, and the combination of BOHB-Tuned XGBoost is proposed. There are four steps below. Firstly, the EEG data is preprocessed and 22 features are extracted. Then, the KMeansSMOTE oversampling technique is applied to generate samples for the minority class in the imbalanced data, aiming to achieve a balance between positive and negative samples. Next, XGBoost is employed for ranking feature importance and it is integrated with correlation analysis for feature selection. Finally, the BOHB-Tuned XGBoost model is utilized for K-complex detection using the selected features. Experimental results show that the model has an average accuracy of 96.60%, precision of 97.67%, sensitivity of 89.05%, specificity of 99.1%, and an F1 score of 92.99%. The method proposed in this study not only addresses the problem of data imbalance effectively but also demonstrates a more stable, high classification performance. This can assist sleep experts in analyzing EEG signals.