Search Results (1,062)

Low solar radiation, caused by climate change or dense planting patterns, now limits wheat production. Although wheat breeding has increased lodging resistance and yield potential through the introduction of dwarfing genes, it still reduces wheat yields. Few studies have been conducted to clarify the lodging sensitivity to shading of different-era wheat cultivars in China’s Huang-Huai-Hai region, as well as the characteristics of lodging resistance as affected by paclobutrazol under shading stress. To address this gap, the experiment included two wheat cultivars released in different decades, grown under shade and treated with or without paclobutrazol. The results showed that reductions in filling degree and lignin content, together with increases in length of the basal internode and gravity center height, markedly reduced the section modulus and breaking strength of shaded wheat culms. These changes impaired lodging resistance and raised lodging risk. However, paclobutrazol application effectively reduced lodging incidence and increased wheat yield under shading stress. Furthermore, these responses were more pronounced in the old cultivar (YZM) than in the modern cultivar (S28). This indicates that the culm mechanical parameters of the old cultivar were more shade-sensitive than those of the modern cultivar. Moreover, shading downregulated the relative expression levels of key genes associated with lignin biosynthesis to decrease the activities of key enzymes, thereby inhibiting the biosynthesis and deposition of lignin in culms to increase the risk of wheat lodging. Paclobutrazol application alleviated the inhibitory effects of shading on lignin biosynthesis, thereby strengthening culms and enhancing lodging resistance. These findings may provide a basis for exploring cultivation regulation methods to enhance wheat lodging resistance under overcast and low-sunshine conditions, and to offer guidance for the breeding of wheat cultivars with lodging resistance and shade tolerance. Full article

This research presents a reinforcement learning framework for stable quadruped locomotion using Proximal Policy Optimization (PPO). We address critical challenges in articulated robot control—including mechanical complexity and trajectory instability by implementing a 12-degree-of-freedom model in PyBullet simulation. Our approach features three key innovations: (1) a hybrid reward function ($R_t=0.72 · e^{-\Delta {\mathrm{CoG}}_t} + 0.25 · v_t - 0.11 · ‖{\tau }_t‖$) explicitly prioritizing center-of-gravity (CoG) stabilization; (2) rigorous benchmarking demonstrating Adam’s superiority over SGD for policy convergence (68% lower reward variance); and (3) a four-metric evaluation protocol quantifying locomotion quality through reward progression, CoG deviation, policy loss, and KL-divergence penalties. Experimental results confirm an 87.5% reduction in vertical CoG oscillation (from 2.0″ to 0.25″) across 1 million training steps. Policy optimization achieved −6.2 × 10⁻⁴ loss with KL penalties converging to 0.13, indicating stable gait generation. The framework’s efficacy is further validated by consistent CoG stabilization during deployment, demonstrating potential for real-world applications requiring robust terrain adaptation. Full article

We demonstrate the potential of using the convolutional equivalent layer to jointly process large gravity-gradient datasets. Based on the equivalent-layer principle, we assume a single fictitious physical property distribution on a planar layer can approximate all components of the gravity-gradient tensor. Estimating this distribution using the classical technique ensures physical consistency among components. However, the classical approach becomes computationally prohibitive for large datasets due to the need to solve a large-scale inversion with a massive sensitivity matrix. To overcome this limitation, we exploit the block-Toeplitz Toeplitz-block structure of the sensitivity matrix for data on a regular horizontal grid. This structure significantly reduces computational cost—by orders of magnitude—compared to the classical method. Applications to synthetic and real datasets show that our method offers a computationally efficient alternative for processing large gravity-gradient data from various acquisition systems (AGG and FTG), even when data are irregularly spaced or flight lines are misaligned. On a standard laptop configuration, our method processed over 290,000 AGG data points in a few tens of seconds. It also handled between 726,000 FTG and 1,250,000 AGG data points within seconds to a couple of minutes, demonstrating practical computational efficiency for large-scale datasets. Full article

The general framework of Entropic Dynamics (ED) is used to construct non-relativistic models of relational Quantum Mechanics from well-known inference principles—probability, entropy and information geometry. Although only partially relational—the absolute structures of simultaneity and Euclidean geometry are still retained—these models provide a useful testing ground for ideas that will prove useful in the context of more realistic relativistic theories. The fact that in ED the positions of particles have definite values, just as in classical mechanics, has allowed us to adapt to the quantum case some intuitions from Barbour and Bertotti’s classical framework. Here, however, we propose a new measure of the mismatch between successive states that is adapted to the information metric and the symplectic structures of the quantum phase space. We make explicit that ED is temporally relational and we construct non-relativistic quantum models that are spatially relational with respect to rigid translations and rotations. The ED approach settles the longstanding question of what form the constraints of a classical theory should take after quantization: the quantum constraints that express relationality are to be imposed on expectation values. To highlight the potential impact of these developments, the non-relativistic quantum model is parametrized into a generally covariant form and we show that the ED approach evades the analogue of what in quantum gravity has been called the problem of time. Full article

Background/Objectives: Environmental stressors, including spaceflight and altered gravity, can negatively affect the symbiotic relationship between the gut microbiome and host health. Dietary prebiotics, which alter components of the gut microbiome, show promise as an effective way to mitigate the negative impacts of stressor exposure. It remains unknown, however, if the stress-protective effects of consuming dietary prebiotics will extend to chronic altered-gravity exposure. Methods: Forty female C57BL/6 mice consumed either a control diet or a prebiotic diet containing galactooligosaccharides (GOS) and polydextrose (PDX) for 4 weeks, after which half of the mice were exposed to 3 times the gravitational force of Earth (3g) for an additional 4 weeks. Fecal microbiome samples were collected weekly for 8 weeks, sequenced, and analyzed using 16S rRNA gene sequencing. Terminal physiological endpoints, including immune and red blood cell characteristics, were collected at the end of the study. Results: The results demonstrate that dietary prebiotic consumption altered the gut microbial community structure through changes to β-diversity and multiple genera across time. In addition, consuming dietary prebiotics reduced the neutrophil-to-lymphocyte ratio (NLR) and increased red blood cell distribution width (RDW-CV). Importantly, the prebiotic diet prevented the impacts of altered-gravity on β-diversity and the bloom of problematic genera, such as Clostridium_sensu_stricto_1 and Turicibacter. Furthermore, several prebiotic diet-induced genera-level changes were significantly associated with several host physiological changes induced by 3g exposure. Conclusions: These data demonstrate that the stress-protective potential of consuming dietary prebiotics extends to environmental stressors such as altered gravity, and, potentially, spaceflight. Full article

In this work we study the spectral dimensionality of spacetime around a radiating Schwarzschild black hole using a recently introduced formalism of quantum gravity, where the alterations of the gravitational field produced by the radiation are represented on an extended manifold, and describe a non-commutative and nonlinear quantum algebra. The relation between classical and quantum perturbations of spacetime can be measured by the parameter $z\ge 0$. In this work we have found that when $z=(1+\sqrt{3})/2\simeq 1.3660$, a relativistic observer approaching the Schwarzschild horizon perceives a spectral dimension $N\left(z\right)=4\left[\theta \left(z\right)-1\right]\simeq 2.8849$, which is related to quantum gravitational interference effects in the environment of the black hole. Under these conditions, all studied Schwarzschild black holes with masses ranging from the Planck mass to ${10}^{46}$ times the Planck mass present the same stability configuration, which suggests the existence of a universal property of these objects under those particular conditions. The difference from the spectral dimension previously obtained at cosmological scales leads to the conclusion that the spacetime dimensionality is scale-dependent. Another important result presented here is the fundamental alteration of the effective gravitational potential near the horizon due to Hawking radiation. This quantum phenomenon prevents the potential from diverging to negative infinity as the observer approaches the Schwarzschild horizon. Full article

Measurable changes in electrophysiology have been documented in spaceflight, creating a pathway for disease genesis and progression in astronauts. These electrophysiology changes can be measured using potential difference (PD). A probe to measure PD was developed and is used clinically on Earth; this probe relies on fluid perfusion to establish an electrical connection to make PD measurements. The changes to fluid behavior in microgravity and partial gravity (including lunar and Martian gravity) drives the need to test this probe in a spaceflight environment. Here, we test the PD probe in a novel nasal cavity phantom in parabolic flight, simulating microgravity, lunar gravity, Martian gravity, and hypergravity conditions across 37 parabolas. The results are evaluated across gravity conditions using the Wilcoxon Rank Sum test. We record no statistically significant difference in probe PD measurements in 1 g, microgravity, lunar gravity, and hypergravity (approximately 1.8 g) conditions, reaching a NASA Technology Readiness Level 6. Martian gravity findings are inconclusive. Perfusion-based PD probes are therefore successfully demonstrated for use in spaceflight operation in microgravity, lunar gravity, and hypergravity environments; this establishes a foundation for moving towards the in-space testing of perfusion-based probes in astronauts. Full article

High-resolution groundwater storage is essential for effective regional water resource management. While Gravity Recovery and Climate Experiment (GRACE) satellite data offer global coverage, the coarse spatial resolution (0.25–0.5°) limits the data’s applicability at regional scales. Traditional downscaling methods often fail to effectively capture spatial heterogeneity within regions, leading to reduced model performance. To overcome this limitation, a zoned downscaling strategy based on time series clustering is proposed. A K-means clustering algorithm with dynamic time warping (DTW) distance, combined with a random forest (RF) model, was employed to partition the Hexi Corridor region into relatively homogeneous subregions for downscaling. Results demonstrated that this clustering strategy significantly enhanced downscaling model performance. Correlation coefficients rose from 0.10 without clustering to above 0.84 with K-means clustering and the RF model, while correlation with the groundwater monitoring well data improved from a mean of 0.47 to 0.54 in the first subregion (a) and from 0.40 to 0.45 in the second subregion (b). The driving factor analysis revealed notable differences in dominant factors between subregions. In the first subregion (a), potential evapotranspiration (PET) was found to be the primary driving factor, accounting for 33.70% of the variation. In the second subregion (b), the normalized difference vegetation index (NDVI) was the dominant factor, contributing 29.73% to the observed changes. These findings highlight the effectiveness of spatial clustering downscaling methods based on DTW distance, which can mitigate the effects of spatial heterogeneity and provide high-precision groundwater monitoring data at a 1 km spatial resolution, ultimately improving water resource management in arid regions. Full article

Mining and analyzing information from multiple sources—such as geophysics and geochemistry—is a key aspect of big data-driven mineral prediction. Clustering, which groups large datasets based on distance metrics, is an essential method in multidimensional data analysis. The Two-Step Clustering (TSC) approach offers advantages by handling both categorical and continuous variables and automatically determining the optimal number of clusters. In this study, we applied the TSC method to mineral prediction in the northeastern margin of the Jiaolai Basin by: (i) converting residual gravity and magnetic anomalies into categorical variables using Ward clustering; and (ii) transforming 13 stream sediment elements into independent continuous variables through factor analysis. The results showed that clustering is sensitive to categorical variables and performs better with fewer categories. When variables share similar distribution characteristics, consistency between geophysical discretization and geochemical boundaries also influences clustering results. In this study, the (3 × 4) and (4 × 4) combinations yielded optimal clustering results. Cluster 3 was identified as a favorable zone for gold deposits due to its moderate gravity, low magnetism, and the enrichment in F1 (Ni–Cu–Zn), F2 (W–Mo–Bi), and F3 (As–Sb), indicating a multi-stage, shallow, hydrothermal mineralization process. This study demonstrates the effectiveness of combining Ward clustering for variable transformation with TSC for the integrated analysis of categorical and numerical data, confirming its value in multi-source data research and its potential for further application. Full article

With the launch of the Artemis program and the International Lunar Research Station project, the construction of lunar bases has emerged as a global research focus. In situ manufacturing technologies for robust lunar regolith-based building materials are critical to ensuring building safety under the Moon’s extreme environmental conditions. This paper reviews the relevant advancements in two areas: solidification technologies for lunar regolith-based construction materials and simulation techniques of extreme lunar environments. This review reveals that, although significant advancements have been made in solidification technologies, the development of lunar environment simulation technologies, particularly for 1/6 g gravity, has lagged, thereby hindering the assessment of the in situ applicability of these solidification methods. To address these limitations, this paper introduces a newly developed comprehensive lunar extreme environment simulation system based on superconducting magnetic suspension technology and its potential applications in lunar regolith-based construction material solidification. This review highlights the current progress and challenges in solidification techniques for lunar regolith-based building materials, aiming to enhance researchers’ attention to the extreme environmental conditions on the lunar surface. Full article

Accurately monitoring terrestrial water storage (TWS) variations is essential due to global climate change and growing water demands. This study investigates TWS changes in Oregon, USA, using Global Navigation Satellite System (GNSS) data from the Nevada Geodetic Laboratory, Gravity Recovery and Climate Experiment (GRACE) level-3 mascon data from the Jet Propulsion Laboratory (JPL), and Noah model data from the Global Land Data Assimilation System (GLDAS) data. The results show that the GNSS inversion offers superior spatial resolution, clearly capturing a water storage gradient from 300 mm in the Cascades to 20 mm in the basin and accurately distinguishing between mountainous and basin areas. However, the GRACE data exhibit blurred spatial variability, with the equivalent water height amplitude ranging from approximately 100 mm to 145 mm across the study area, making it difficult to resolve terrestrial water storage gradients. Moreover, GLDAS exhibits limitations in mountainous regions. The GNSS can provide continuous dynamic monitoring, with results aligning well with seasonal trends seen in GRACE and GLDAS data, although with a 1–2 months phase lag compared to the precipitation data, reflecting hydrological complexity. Future work may incorporate geological constraints, region-specific elastic models, and regularization strategies to improve monitoring accuracy. This study demonstrates the strong potential of GNSS technology for monitoring TWS dynamics and supporting environmental assessment, disaster warning, and water resource management. Full article

The Cao’e-Jiaojiang-Oujiang River Basin possesses abundant vernacular architectural heritage with significant historical–cultural value. However, challenges like dispersed distribution and inconsistent conservation hinder its systematic protection and utilization within territorial spatial planning, necessitating a deeper understanding of its spatiotemporal patterns. Utilizing 570 identified heritage sites, this study employed ArcGIS spatial analysis (Kernel Density Estimation, Nearest Neighbor Index), correlation analysis with DEM data, and suitability analysis (Minimum Cumulative Resistance model, Gravity Model) to systematically examine spatial distribution characteristics, their evolution, and relationships with the geographical environment and historical context. Results revealed a distinct “four cores and three belts” spatial pattern. Temporally, distribution evolved from “discrete” (Song-Yuan) to “aggregated” (Ming-Qing) and then “diffused” (Modern era). Spatially, heritage showed density in plains, preference for low slopes, and settlement along waterways. Suitability analysis indicated higher corridor potential in the northern section (Cao’e-Jiaojiang) than the south (Oujiang), leading to the identification of a “Northern Segment (Shaoxing-Ningbo-Shengzhou-Taizhou)” and “Southern Segment (Wenzhou-Lishui)” corridor structure. This research provides a scientific basis for systematic conservation and integrated heritage corridor construction of vernacular architectural heritage in the basin, supporting Zhejiang’s Poetry Road Cultural Belt initiatives and cultural heritage protection within territorial spatial planning. Full article

We present a miniaturized, inexpensive, and user-friendly microfluidic platform to support biological applications. The system integrates a mini-incubator providing controlled environmental conditions and housing a microfluidic device for long-term cell culture experiments. The incubator is designed to be compatible with standard inverted optical microscopes and Raman spectrometers, allowing for the non-invasive imaging and spectroscopic analysis of cell cultures in vitro. The microfluidic device, which reproduces a dynamic environment, was optimized to sustain a passive, gravity-driven flow of medium, eliminating the need for an external pumping system and reducing mechanical stress on the cells. The platform was tested using Raman analysis and adherent tumoral cells to assess proliferation prior and subsequent to hydrogen peroxide treatment for oxidative stress induction. The results demonstrated a successful adhesion of cells onto the substrate and their proliferation. Furthermore, the platform is suitable for carrying out optical monitoring of cultures and Raman analysis. In fact, it was possible to discriminate spectra deriving from control and hydrogen peroxide-treated cells in terms of DNA backbone and cellular membrane modification effects provoked by reactive oxygen species (ROS) activity. The 800–1100 cm⁻¹ band highlights the destructive effects of ROS on the DNA backbone’s structure, as its rupture modifies its vibration; moreover, unpaired nucleotides are increased in treated sample, as shown in the 1154–1185 cm⁻¹ band. Protein synthesis deterioration, led by DNA structure damage, is highlighted in the 1257–1341 cm⁻¹, 1440–1450 cm⁻¹, and 1640–1670 cm⁻¹ bands. Furthermore, membrane damage is emphasized in changes in the 1270, 1301, and 1738 cm⁻¹ frequencies, as phospholipid synthesis is accelerated in an attempt to compensate for the membrane damage brought about by the ROS attack. This study highlights the potential use of this platform as an alternative to conventional culturing and analysis procedures, considering that cell culturing, optical imaging, and Raman spectroscopy can be performed simultaneously on living cells with minimal cellular stress and without the need for labeling or fixation. Full article

Since farmers in the inland valley region of the Niger Delta mostly rely on experience rather than empirical evidence when it comes to irrigation, flood irrigation being the most popular technique, the region’s agricultural sector needs more efficient water management. In order to better understand the intricate hydrodynamics of water flow through the soil subsurface, this study aimed to develop a soil column laboratory experimental setup for soil water infiltration. The objective was to measure the soil water content and soil matric potential at 10 cm intervals to study the soil water characteristic curve as a relationship between the two hydraulic parameters, mimicking drip soil subsurface micro-irrigation. A specially designed cylindrical vertical soil column rig was built, and an EQ3 equitensiometer of Delta-T Devices was used in the laboratory as a precision sensor to measure the soil matric potential Ψ (kPa), and the volumetric soil water content θ (%) was measured using a WET150 sensor of Delta-T Devices. The relationship between the volumetric soil water content and the soil matric potential resulted in the generation of the soil water characteristic curve. Two separate monoliths of undisturbed soil samples from Ivrogbo and Oleh in the Nigerian inland valley of the Niger Delta, as well as a uniformly packed sample of soil from Aberdeen, UK, for comparison, were used in gravity-driven flow experiments. In each case, tests were performed once on the monoliths of undisturbed soil samples. In contrast, the packed sample was subjected to an experiment before being further agitated to simulate ploughing and then subjected to an infiltration experiment, resulting in a total of four samples. The Van Genuchten model of the soil water characteristic curve was used for the verification of the experimental results. Comparing the four samples’ volumetric soil water contents and soil matric potentials at various depths revealed a significant variation in their behaviour. However, compared to the predicted curve, the range of values was narrower. Compared to n = 2 in the Van Genuchten curve, the value of n at 200 mm depth was found to be 15, with θr of 0.046 and θs of 0.23 for the packed soil sample, resulting in a percentage difference of 86.7%. Additionally, n = 10 for the ploughed sample resulted in an 80% difference, yet θr = 0.03 and θs = 0.23. For the Ivrogbo sample and the Oleh sample, the range of the matric potential was relatively too small for the comparison. The pre-experiment moisture content of the soil samples was part of the cause of this, in addition to differences in the soil types. Furthermore, the data revealed a remarkable agreement between the measured behaviour and the projected technique of the soil water characteristic curve. Full article

Aging is a complex biological process marked by a progressive decline in cellular function, leading to age-related diseases such as neurodegenerative disorders, cancer, and cardiovascular diseases. Despite significant advancements in aging research, finding effective interventions to decelerate aging remains a challenge. This review explores microgravity as a novel therapeutic approach to combat aging and promote healthy longevity. The hallmarks of aging, including genomic instability, telomere shortening, and cellular senescence, form the basis for understanding the molecular mechanisms behind aging. Interestingly, microgravity has been shown to accelerate aging-like processes in model organisms and human tissues, making it an ideal environment for studying aging mechanisms in an accelerated manner. Spaceflight studies, such as NASA’s Twins Study and experiments aboard the International Space Station (ISS), reveal striking parallels between the physiological changes induced by microgravity and those observed in aging populations, including muscle atrophy, bone density loss, cardiovascular deconditioning, and immune system decline in a microgravity environment. However, upon microgravity recovery, cellular behavior, gene expression, and tissue regeneration were seen, providing vital insights into aging mechanisms and prospective therapeutic approaches. This review examines the potential of microgravity-based technologies to pioneer novel strategies for decelerating aging and enhancing healthspan under natural gravity, paving the way for breakthroughs in longevity therapies. Full article