Miracle-dz/UniFAR-FTUs huggingface dataset:
Importance of Ekman transport and gyre circulation change on seasonal variation of surface dissolved iron in the western subarctic North Pacific

Iron (Fe) is an essential nutrient for marine phytoplankton and it constitutes an important element in the marine carbon cycle in the ocean. This study examined the mechanisms controlling seasonal variation of dissolved Fe (dFe) in the western subarctic North Pacific (WSNP), using an ocean general circulation model coupled with a simple biogeochemical model incorporating a dFe cycle fed by two major sources (atmospheric dust and continental shelf sediment). The model reproduced the seasonal cycle of observed concentrations of dFe and macro nutrients at the surface in the Oyashio region with maxima in winter (February–March) and minima in summer (July–September), although the simulated seasonal amplitudes are a half of the observed values. Analysis of the mixed-layer dFe budget indicated that both local vertical entrainment and lateral advection are primary contributors to the wintertime increase in dFe concentration. In early winter, strengthened northwesterly winds excite southward Ekman transport and Ekman upwelling over the western subarctic gyre, transporting dFe-rich water southward. In mid- to late winter, the southward western boundary current of the subarctic gyre and the outflow from the Sea of Okhotsk also bring dFe-rich water to the Oyashio region. The contribution of atmospheric dust to the dFe budget is several times smaller than these ocean transport processes in winter. These results suggest that the westerly wind-induced Ekman transport and gyre circulation systematically influence the seasonal cycle of WSNP surface dFe concentration.
Cationic Vitamin E-TPGS Mixed Micelles of Berberine to Neutralize Doxorubicin-Induced Cardiotoxicity via Amelioration of Mitochondrial Dysfunction and Impeding Apoptosis

Anthracycline antibiotics, namely, doxorubicin (DOX) and daunorubicin, are among the most widely used anticancer therapies, yet are notoriously associated with severe myocardial damage due to oxidative stress and mitochondrial damage. Studies have indicated the strong pharmacological properties of Berberine (Brb) alkaloid, predominantly mediated via mitochondrial functions and nuclear networks. Despite the recent emphasis on Brb in clinical cardioprotective studies, pharmaceutical limitations hamper its clinical use. A nanoformulation for Brb was developed (mMic), incorporating a cationic lipid, oleylamine (OA), into the TPGS-mixed corona of PEGylated-phosphatidylethanolamine (PEG-PE) micelles. Cationic TPGS/PEG-PE mMic with superior Brb loading and stability markedly enhanced both intracellular and mitochondria-tropic Brb activities in cardiovascular muscle cells. Sub-lethal doses of Brb via cationic OA/TPGS mMic, as a DOX co-treatment, resulted in significant mitochondrial apoptosis suppression. In combination with an intense DOX challenge (up to ~50 µM), mitochondria-protective Brb-OA/TPGS mMic showed a significant 24 h recovery of cell viability (p ≤ 0.05–0.01). Mechanistically, the significant relative reduction in apoptotic caspase-9 and elevation of antiapoptotic Bcl-2 seem to mediate the cardioprotective role of Brb-OA/TPGS mMic against DOX. Our report aims to demonstrate the great potential of cationic OA/TPGS-mMic to selectively enhance the protective mitohormetic effect of Brb to mitigate DOX cardiotoxicity.
Semi-Supervised 3D Shape Segmentation via Self Refining

3D shape segmentation is a fundamental and crucial task in the field of image processing and 3D shape analysis. To segment 3D shapes using data-driven methods, a fully labeled dataset is usually required. However, obtaining such a dataset can be a daunting task, as manual face-level labeling is both time-consuming and labor-intensive. In this paper, we present a semi-supervised framework for 3D shape segmentation that uses a small, fully labeled set of 3D shapes, as well as a weakly labeled set of 3D shapes with sparse scribble labels. Our framework first employs an auxiliary network to generate initial fully labeled segmentation labels for the sparsely labeled dataset, which helps in training the primary network. During training, the self-refine module uses increasingly accurate predictions of the primary network to improve the labels generated by the auxiliary network. Our proposed method achieves better segmentation performance than previous semi-supervised methods, as demonstrated by extensive benchmark tests, while also performing comparably to supervised methods.
Two-Phase Fermentation Systems for Microbial Production of Plant-Derived Terpenes

Microbial cell factories, renowned for their economic and environmental benefits, have emerged as a key trend in academic and industrial areas, particularly in the fermentation of natural compounds. Among these, plant-derived terpenes stand out as a significant class of bioactive natural products. The large-scale production of such terpenes, exemplified by artemisinic acid—a crucial precursor to artemisinin—is now feasible through microbial cell factories. In the fermentation of terpenes, two-phase fermentation technology has been widely applied due to its unique advantages. It facilitates in situ product extraction or adsorption, effectively mitigating the detrimental impact of product accumulation on microbial cells, thereby significantly bolstering the efficiency of microbial production of plant-derived terpenes. This paper reviews the latest developments in two-phase fermentation system applications, focusing on microbial fermentation of plant-derived terpenes. It also discusses the mechanisms influencing microbial biosynthesis of terpenes. Moreover, we introduce some new two-phase fermentation techniques, currently unexplored in terpene fermentation, with the aim of providing more thoughts and explorations on the future applications of two-phase fermentation technology. Lastly, we discuss several challenges in the industrial application of two-phase fermentation systems, especially in downstream processing.
Self-Supervised Monocular Depth Estimation With Positional Shift Depth Variance and Adaptive Disparity Quantization

Recently, attempts to learn the underlying 3D structures of a scene from monocular videos in a fully self-supervised fashion have drawn much attention. One of the most challenging aspects of this task is to handle independently moving objects as they break the rigid-scene assumption. In this paper, we show for the first time that pixel positional information can be exploited to learn SVDE (Single View Depth Estimation) from videos. The proposed moving object (MO) masks, which are induced by the depth variance to shifted positional information (SPI) and are referred to as ‘SPIMO’ masks, are highly robust and consistently remove independently moving objects from the scenes, allowing for robust and consistent learning of SVDE from videos. Additionally, we introduce a new adaptive quantization scheme that assigns the best per-pixel quantization curve for depth discretization, improving the fine granularity and accuracy of the final aggregated depth maps. Finally, we employ existing boosting techniques in a new way that self-supervises moving object depths further. With these features, our pipeline is robust against moving objects and generalizes well to high-resolution images, even when trained with small patches, yielding state-of-the-art (SOTA) results with four- to eight-fold fewer parameters than the previous SOTA techniques that learn from videos. We present extensive experiments on KITTI and CityScapes that show the effectiveness of our method.
Intermittent hypoxia preconditioning can attenuate acute hypoxic injury after a sustained normobaric hypoxic exposure: A randomized clinical trial

Abstract Background Intermittent hypoxia (IH) is emerging as a cost‐effective nonpharmacological method for vital organ protection. We aimed to assess the effects of a short‐term moderate intermittent hypoxia preconditioning protocol (four cycles of 13% hypoxia lasting for 10 min with 5‐min normoxia intervals) on acute hypoxic injury induced by sustained hypoxic exposure (oxygen concentration of 11.8% for 6 h). Methods One hundred healthy volunteers were recruited and randomized to the IH group and the control group to receive IH or sham‐IH preconditioning for 5 days, respectively, and then were sent to a hypoxic chamber for simulated acute high‐altitude exposure (4500 m). Results The overall incidence of acute mountain sickness was 27% (27/100), with 14% (7/50) in the IH group and 40% (20/50) in the control group (p = 0.003). After 6‐h simulated high‐altitude exposure, the mean Lake Louise Score was lower in the IH group as compared to controls (1.30 ± 1.27 vs. 2.04 ± 1.89, p = 0.024). Mean peripheral oxygen saturations (SpO2) and intracranial pressure (ICP) measures after acute hypoxic exposure exhibited significant differences, with the IH group showing significantly greater SpO2 values (85.47 ± 5.14 vs. 83.10 ± 5.15%, p = 0.026) and lower ICP levels than the control group (115.59 ± 32.15 vs. 130.36 ± 33.83 mmH2O, p = 0.028). IH preconditioning also showed greater effects on serum protein gene product 9.5 (3.89 vs. 29.16 pg/mL; p = 0.048) and C‐reactive protein (−0.28 vs. 0.41 mg/L; p = 0.023). Conclusion The short‐term moderate IH improved the tolerance to hypoxia and exerted protection against acute hypoxic injury induced by exposure to sustained normobaric hypoxia, which provided a novel method and randomized controlled trial evidence to develop treatments for hypoxia‐related disease.
Research on Electric Oil–Pneumatic Active Suspension Based on Fractional-Order PID Position Control

In this study, an electric oil and gas actuator based on fractional-order PID position feedback control is proposed, through which the damping coefficient of the suspension system is adjusted to realize the active control of the suspension. An FOPID algorithm is used to control the motor’s rotational angle to realize the damping adjustment of the suspension system. In this process, the road roughness is collected by the sensors as the criterion of damping adjustment, and the particle swarm algorithm is utilized to find the optimal objective function under different road surface slopes, to obtain the optimal cornering value. According to the mathematical and physical model of the suspension system, the simulation model and the corresponding test platform of this type of suspension system are built. The simulation and experimental results show that the simulation results of the fractional-order nonlinear suspension model are closer to the actual experimental values than those of the traditional linear suspension model, and the accuracy of each performance index is improved by more than 18.5%. The designed active suspension system optimizes the body acceleration, suspension dynamic deflection, and tire dynamic load to 89.8%, 56.7%, and 73.4% of the passive suspension, respectively. It is worth noting that, compared to traditional PID control circuits, the FOPID control circuit designed for motors has an improved control performance. This study provides an effective theoretical and empirical basis for the control and optimization of fractional-order nonlinear suspension systems.
Reduction of monoclonal antibody viscosity using interpretable machine learning

ABSTRACT Early identification of antibody candidates with drug-like properties is essential for simplifying the development of safe and effective antibody therapeutics. For subcutaneous administration, it is important to identify candidates with low self-association to enable their formulation at high concentration while maintaining low viscosity, opalescence, and aggregation. Here, we report an interpretable machine learning model for predicting antibody (IgG1) variants with low viscosity using only the sequences of their variable (Fv) regions. Our model was trained on antibody viscosity data (>100 mg/mL mAb concentration) obtained at a common formulation pH (pH 5.2), and it identifies three key Fv features of antibodies linked to viscosity, namely their isoelectric points, hydrophobic patch sizes, and numbers of negatively charged patches. Of the three features, most predicted antibodies at risk for high viscosity, including antibodies with diverse antibody germlines in our study (79 mAbs) as well as clinical-stage IgG1s (94 mAbs), are those with low Fv isoelectric points (Fv pIs < 6.3). Our model identifies viscous antibodies with relatively high accuracy not only in our training and test sets, but also for previously reported data. Importantly, we show that the interpretable nature of the model enables the design of mutations that significantly reduce antibody viscosity, which we confirmed experimentally. We expect that this approach can be readily integrated into the drug development process to reduce the need for experimental viscosity screening and improve the identification of antibody candidates with drug-like properties.
The Effect of Microwaves on Protein Structure: Molecular Dynamics Approach

The impact of microwave (MW) irradiation on protein folding, potentially inciting misfolding, was investigated by employing molecular dynamics (MD) simulations. Twenty-nine proteins were subjected to MD simulations under equilibrium (300 K) and MW conditions, where the rotational temperature was elevated to 700 K. The utilized replacement model captures the microwave effects of δ- and γ-relaxation processes (frequency range of ∼300 MHz to ∼20 GHz). The results disclosed that MW heating incited a shift toward more compact protein conformations, as indicated by decreased root-mean-square deviations, root-mean-square fluctuations, head-to-tail distances, and radii of gyration. This compaction was attributed to the intensification of intramolecular electrostatic interactions and hydrogen bonds within the protein caused by MW-destabilized hydrogen bonds between the protein and solvent. The solvent-accessible surface area (SASA), particularly that of polar amino-acid residues, shrank under MW conditions, corresponding to a reduced polarity of the water solvent. However, MW irradiation produced no significant alterations in protein secondary structures; hence, MW heating was observed to primarily affect the protein tertiary structures.
Characterising the rural-urban gradient through the participatory mapping of ecosystem services: insights for landscape planning

The application of the ecosystem services (ES) framework in landscape planning has become particularly relevant in rural-urban gradients since it allows for the integration of the complex interactions between ES supply and demand. This framework might be a powerful tool to inform landscape planning and decision-making intended to maintain the current and future flow of ES. In this study, we developed a process of participatory mapping of ES in a rural-urban gradient in southern Spain, which comprises the Sierra Nevada mountain range, the Granada valley and the city of Granada. First, we interviewed 21 key stakeholders from different professional sectors and gradient zones. These stakeholders prioritised nine ES in terms of their importance for local human well-being and their vulnerability to current drivers of change. Then, a workshop was organised in which 23 local actors shared their experience and knowledge regarding ES in the studied ‡,§ |,§ ¶,# § © Palomo-Campesino S et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. landscape. Sorted into five groups (composed of stakeholders with different profiles), the participants spatially mapped the most important supply and demand areas for the nine ES previously prioritised. The results show that the city of Granada has a very high demand for ES and a very low supply, while the Sierra Nevada mountain range and the valley of Granada appear to be very important ES supply areas. According to 95% of the stakeholders that attended the workshop, participatory mapping of ES is a very important (69%) or an important (26%) methodology to elicit the views and perceptions of the population, to identify the main conflicts and potential solutions for the territory and to visualise the high dependence of urban areas on the ES provided by adjacent rural areas. Our results also highlight the importance of incorporating the analysis of ES flows to inform landscape planning at the regional scale. Participatory mapping of ES can enhance decision-making regarding the maintenance of human well-being and the sustainability of social-ecological systems.
ULF geomagnetic activity effects on tropospheric temperature, specific humidity, and cloud cover in Antarctica, during 2003–2010

In the present study we investigated the possible relationship between the ULF geomagnetic activity and the variations of several atmospheric parameters. In particular, we compared the ULF activity in the Pc1‐2 frequency band (100 mHz–5 Hz), computed from geomagnetic field measurements at Terra Nova Bay in Antarctica, with the tropospheric temperature T, specific humidity Q, and cloud cover (high cloud cover, medium cloud cover, and low cloud cover) obtained from reanalysis data set. The statistical analysis was conducted during the years 2003–2010, using correlation and Superposed Epoch Analysis approaches. The results show that the atmospheric parameters significantly change following the increase of geomagnetic activity within 2 days. These changes are evident in particular when the interplanetary magnetic field Bz component is oriented southward (Bz<0) and the By component duskward (By>0). We suggest that both the precipitation of electrons induced by Pc1‐2 activity and the intensification of the polar cap potential difference, modulating the microphysical processes in the clouds, can affect the atmosphere conditions.
Investigating the origins of the Jovian decimetric emission's variability

[1] The long-term variability of the Jovian radiation observed at 13-cm wavelength over 30 years is investigated using a physical model of the radiation belts. The model enables us to quantify the effect of the geometric parameter DE on the synchrotron emission. When a full Jupiter rotation is taken into account in the computations, the variability of the total radio flux with DE is only ≃1% of that measured. Such a dependence is not detectable. In contrast, radio fluctuations observed at a central meridian longitude (CML) and caused by DE changes can be very important, up to 10% of that measured. This strong dependence of the total radio flux on the geometric factor can result in difficulties for examining the origins of the Jovian synchrotron emission's fluctuations during periods where times of observation are not covering large CML range values. The numerical computations reveal that the variability either of the populations injected near the outer boundary of our simulations (Io's orbit) or the inward radial transport can, independently or in combined action, conduct variability in the decimetric emission. The theoretical fluctuations required in our computations for reproducing the radio measurements do not confirm any direct correlation between the long-term changes in the radio data and the radial transport driven by solar wind conditions or solar radio fluxes. Nevertheless, a linear relationship between the total radio flux and solar wind ram pressure for the period of 1970 to 2002 is established. The maximum correlation is reached when the Psw data are shifted by ≃2.7 years prior to the radio observations. Using this time-lag in the computations, the simulation results show that (Psw)γ can be associated with the variations of the particle injections and the radial transport. The correlation coefficient, associated with the fit between radio data and simulated radio flux densities, is 0.59 for the period of 1971–2002, 0.93 for the period of 1971–1972, and 0.83 for the periods of 1975–1989 and 1992–1995. The index γ is set to 0.35 when only particle injections are fluctuating with time, to 0.50 when temporal variations are driving the radial transport, and to 0.15–0.20 when the particles injected in the inner magnetosphere and their transport are simultaneously following the variations of the solar wind ram pressure. The model suggests that the solar wind ram pressure fluctuations can be related to variations of the Jovian decimetric emission on timescales of months, particularly to the enhancements in total radio flux observed in 1987, 1988, 1990 and 1994. Our results thus support the idea that the increase in radio emission in July 1994 was due to the impact of Comet Shoemaker-Levy 9 into Jupiter, in addition to the response of the Jovian magnetosphere to steep changes in solar wind conditions. The divergence between observations and simulations indicates that mechanisms other than those discussed in the modeling must govern the radiation belts dynamics for the periods of 1972–1975 and 1996–2002.
Pleistocene to Holocene Growth of a Large Upper Crustal Rhyolitic Magma Reservoir beneath the Active Laguna del Maule Volcanic Field, Central Chile

The rear-arc Laguna del Maule volcanic ﬁeld (LdM) in the Andean Southern Volcanic Zone, 36 (cid:2) S, is among the most active latest Pleistocene–Holocene rhyolitic centers globally and has been inﬂating at a rate of > 20 cm a –1 since 2007. At least 50 eruptions during the last 26 kyr allow for a thorough interrogation of changes in the physical and chemical state of this large, (cid:3) 20 km diameter, silicic system. Trace element concentrations and Sr, Pb and Th isotope ratios indicate that the maﬁc precursors to the LdM rhyolites result from mixing between partial melts of garnet-bearing mantle and crust in Th-excess and partial melts of garnet-free crust in U-excess. The 238 U/ 230 Th ratios of the LdM lavas are decoupled from the slab ﬂuid signature, similar to several recently studied frontal arc volcanic centers in the Southern Volcanic Zone. A narrow range of radiogenic isotope compositions and increasing isotopic homogeneity with differentiation indicate that silicic magma is generated by magma hybridization and crystallization in the upper crust with limited involvement of older, radiogenic material. New 40 Ar/ 39 Ar and 36 Cl ages reveal a wide footprint of silicic volcanism during the early post-glacial (25–19 ka) and Holocene ( c. 8–2 ka) periods, but focused within a single eruptive center during the interim period. Subtle temporal variations in trace element compositions and two-oxide temperatures indicate that these eruptions, issued from vents distributed within a similar area, tapped at least two physically discrete rhyolite reservoirs. This compositional distinction favors punctuated extraction and ephemeral storage of the erupted magma batches. Frequent maﬁc recharge incubates this long-lived, growing shallow silicic magma reservoir above the granite eutectic, which favors magma interactions over rejuvenation of near- to sub-solidus silicic cumulates. A long-term rate of mass addition—extrapolated from surface deformation accumulated over the past decade—is comparable with those that have produced moderate- to large-volume caldera-forming eruptions elsewhere. element rhyolites north south do not require, reservoir LdM basin. (b)