Environmental Fluctuations Research Articles

Study of Bionic Tactile Sensors in Flexible Robots

This research investigates the advancement and implementation of bio-inspired tactile and mechanosensory systems, drawing inspiration from sophisticated biological mechanisms found in nature, particularly human sensory networks and the Venus flytrap's rapid response system. The study demonstrates significant progress in developing highly sensitive and precise sensor technologies that effectively mimic natural sensing capabilities. Through innovative material combinations and structural designs, including hybrid graphene-based platforms and advanced piezoelectric tactile arrays, these sensing systems achieve enhanced detection of mechanical forces, subtle vibrations, and environmental fluctuations. The research findings indicate substantial improvements in sensor performance metrics, including response time, sensitivity threshold, and signal-to-noise ratio. Current challenges in manufacturing scalability and cost-effectiveness are addressed, with proposed solutions for large-scale production and seamless system integration. The study outlines promising applications across multiple fields, from advanced prosthetic limbs with enhanced tactile feedback to sophisticated robotic systems capable of precise environmental interaction. Future research directions emphasize the development of more robust and adaptable sensing platforms, focusing on improved durability, reduced power consumption, and enhanced integration capabilities for next-generation biosensing applications.

Bias Calibration of Optically Pumped Magnetometers Based on Variable Sensitivity.

Optically pumped magnetometers (OPMs) functioning in the spin-exchange relaxation-free (SERF) regime have emerged as attractive options for measuring weak magnetic fields, owing to their portability and remarkable sensitivity. The operation of SERF-OPM critically relies on the ambient magnetic field; thus, a magnetic field compensation device is commonly employed to mitigate the ambient magnetic field to near zero. Nonetheless, the bias of the OPM may influence the compensation impact, a subject that remains unexamined. This paper introduced an innovative bias calibration technique for OPMs. The sensitivity of the OPM was altered by adjusting the cell temperature. The output of the OPM was then documented with varying sensitivity. It is assumed that the signal exhibits a linear correlation with the environmental magnetic field, and the statistical characteristics of the magnetic field are identical for both measurements, upon which the bias of the OPM is assessed. The bias was subsequently considered in the feedback magnetic field compensation mechanism. The results indicate that this technique might successfully reduce environmental magnetic fluctuations and enhance the sensitivity of the OPM. This technique measured the magnetic field produced by the human heart, confirming the viability of the ultra-weak biomagnetic field measurement approach.

Nonreciprocal and nonlinear transport and spontaneous voltage generation in MoGe/Ni81Fe19

The nonreciprocal, diode-like electric transport in a superconductor/ferromagnet bilayer system, MoGe/Ni81Fe19, has been investigated. We found that a MoGe film on Ni81Fe19 spontaneously generates d.c. voltage by rectifying environmental fluctuations. By comparing the effect between MoGe films on different magnetic materials, we show that the amplitude of the spontaneous voltage generation is almost proportional to that of the nonreciprocal electric transport in MoGe, suggesting that the observed rectification mainly originates from the motion of superconducting vortex strings that can feel asymmetry in the magnetic environment between the MoGe surfaces.

Population Genomics of Japanese Macaques (Macaca fuscata): Insights Into Deep Population Divergence and Multiple Merging Histories.

The influence of long-term climatic changes such as glacial cycles on the history of living organisms has been a subject of research for decades, but the detailed population dynamics during the environmental fluctuations and their effects on genetic diversity and genetic load are not well understood on a genome-wide scale. The Japanese macaque (Macaca fuscata) is a unique primate adapted to the cold environments of the Japanese archipelago. Despite the past intensive research for the Japanese macaque population genetics, the genetic background of Japanese macaques at the whole-genome level has been limited to a few individuals, and the comprehensive demographic history and genetic differentiation of Japanese macaques have been underexplored. We conducted whole-genome sequencing of 64 Japanese macaque individuals from 5 different regions, revealing significant genetic differentiation and functional variant diversity across populations. In particular, Japanese macaques have low genetic diversity and harbor many shared and population-specific gene loss, which might contribute to population-specific phenotypes. Our estimation of population demography using phased haplotypes suggested that, after the strong population bottleneck shared among all populations around 400 to 500 kya, the divergence among populations initiated around 150 to 200 kya, but there has been the time with strong gene flow between some populations after the split, indicating multiple population split and merge events probably due to habitat fragmentation and fusion during glacial cycles. These findings not only present a complex population history of Japanese macaques but also enhance their value as research models, particularly in neuroscience and behavioral studies. This comprehensive genomic analysis sheds light on the adaptation and evolution of Japanese macaques, contributing valuable insights to both evolutionary biology and biomedical research.

Mapping the metagenomic diversity of the multi-kingdom glacier-fed stream microbiome.

Glacier-fed streams (GFS) feature among Earth's most extreme aquatic ecosystems marked by pronounced oligotrophy and environmental fluctuations. Microorganisms mainly organize in biofilms within them, but how they cope with such conditions is unknown. Here, leveraging 156 metagenomes from the Vanishing Glaciers project obtained from sediment samples in GFS from 9 mountains ranges, we report thousands of metagenome-assembled genomes (MAGs) encompassing prokaryotes, algae, fungi and viruses, that shed light on biotic interactions within glacier-fed stream biofilms. A total of 2,855 bacterial MAGs were characterized by diverse strategies to exploit inorganic and organic energy sources, in part via functional redundancy and mixotrophy. We show that biofilms probably become more complex and switch from chemoautotrophy to heterotrophy as algal biomass increases in GFS owing to glacier shrinkage. Our MAG compendium sheds light on the success of microbial life in GFS and provides a resource for future research on a microbiome potentially impacted by climate change.

A review on the utility potential of rice derived products in weed management

AbstractRice, one of the most economically significant staple food crops, is widely cultivated worldwide. The abiotic factors exhibit linear correlations with environmental fluctuations, while biotic factors, although indirectly related, also significantly affect rice production yields. Among them, weeds pose the most threat as they are direct natural enemies to rice plants in the field. The herbicides are effective but their curious use is suggested due to their adverse effects on human health and the environment. Utilizing natural‐origin weed control chemicals, such as natural compounds from rice, holds significant potential as the preference for organic products grows increasingly popular. Among these, the perspicacious utilization of abundant biomass sources from rice by‐products, such as husks and straws, is a wise strategy in sustainable agriculture practices through the exploration and application of rice allelopathy. Therefore, this review put forward insights into the rice‐derived product potential for the development of natural‐based herbicides, contributing to sustainable weed management. In addition, various types of weed inhibitors from rice, including momilactones and phenolics, their mechanisms of action, and techniques for isolating and identifying these compounds in rice are discussed. The factors influencing allelochemical production in plants and their potential applications in sustainable agriculture are also presented. Plant growth inhibitors derived from rice could offer safer, natural herbicides while reducing labor‐intensive field work as compared to the incorporation of rice by‐products at 1–2 tons/ha in the fields to manage weeds. Several rice allelochemicals, including momilactones A and B, serve as phytoalexins and protectors against salinity and drought and should be further explored to utilize their potential for sustainable agricultural production.

Evaluating the performance and stability of microalgal-bacterial granular sludge in municipal wastewater treatment plants.

The microalgal-bacterial granular sludge (MBGS) process shows potential for carbon-neutral wastewater treatment, yet its application in wastewater treatment plants remains underexplored. This study attempted to use a continuous-flow raceway reactor to treat real municipal wastewater using the MBGS process. The results showed that the removal efficiencies of organics peaked on the fifth day, while declining trends were observed for nitrogen and phosphorus removal. Microbial community and functional gene analyses indicated that the removal of organics, nitrogen, and phosphorus might be heavily influenced by Proteobacteria, suggesting that fluctuations in their abundance significantly impacted the performance of MBGS. Bacteroidota and Actinobacteria played a vital role in cellulose decomposition via the cbhA gene. Moreover, energy shortages caused by light attenuation due to wastewater turbidity and environmental fluctuations disrupted the microbial balance, shifting metabolic activity towards carbon pathways. Key challenges for the broader application of the MBGS process include managing wastewater turbidity and ensuring process stability. These findings highlight the need for pretreatment measures and robust operational strategies to mitigate environmental fluctuations and maintain system performance.

Feedback-induced phase separation of hollow condensates to create biomimetic membraneless compartments.

Intracellular macromolecules have the ability to form membraneless compartments, such as vacuoles and hollow condensates, through liquid-liquid phase separation (LLPS) in order to adapt to changes in their environment. The development of artificial non-homogeneous compartments, such as multiphase hollow or multicavity condensates, has gained significant attention due to their potential to uncover the mechanisms underlying the formation of artificial condensates and biomolecular condensates. However, the complexity of design and construction has hindered progress, particularly in creating dynamic non-homogeneous compartments. In this study, we present a dynamic membraneless compartment using peptide-oligonucleotide conjugates derived from short elastin-like polypeptides (sELP-ONs), which undergo pH-mediated phase transition. Below pH 8.8, the microcompartment exists as microdroplets that transform into non-homogeneous hollow condensates above pH 8.8. Notably, these hollow condensates retain liquid properties and high molecular ordering, and effectively sequester guest molecules with a hollow condensed layer. Furthermore, our sELP-ON microcompartments exhibit a feedback-induced phase transition in response to environmental pH fluctuations generated by complex enzymatic reactions mimicking cellular metabolism, providing a novel dynamic model for creating biomimetic membraneless compartments.

Differential impacts of water diversion and environmental factors on bacterial, archaeal, and fungal communities in the eastern route of the South-to-North water diversion project.

Water diversion projects effectively mitigate the uneven distribution of water resources but can also influence aquatic biodiversity and ecosystem functions. Despite their importance, the impacts of such projects on multi-domain microbial community dynamics and the underlying mechanisms remain poorly understood. Utilizing high-throughput sequencing, we investigated bacterial, archaeal, and fungal community dynamics along the eastern route of the South-to-North water diversion project during both non-water diversion period (NWDP) and water diversion period (WDP). Our findings revealed competitive exclusion effects among bacterial and archaeal communities during the WDP, characterized by decreased species richness and increased biomass, while fungal biomass significantly declined. Distance-decay relationships suggested microbial homogenization during the WDP. Robustness analyses revealed reduced community stability during the WDP, with water diversion primarily influencing bacterial stability, while environmental factors had a greater impact on archaeal and fungal communities. Stochastic processes, primarily homogenizing dispersal and drift, intensified for bacterial and fungal communities during the WDP. Notably, only bacterial functional diversity decreased during the WDP, with increased relative abundance of chemoheterotrophic and organic compound catabolic bacteria and declined photoautotrophic bacteria. PLS-PM indicated that water diversion primarily shaped bacterial assembly processes and functional guilds, whereas environmental factors had a greater influence on archaeal communities. This study enhances our understanding of microbial dynamics during the WDP and underscores the importance of assessing both direct impacts and resulting environmental fluctuations.

Predicting Habitat Changes and Vulnerability of Climate-sensitive Insects under SSP Scenarios

Climate change significantly impacts the distribution and habitat suitability of insects, particularly those highly sensitive to environmental fluctuations. This study evaluated the habitat changes of 12 climate-sensitive insect species in South Korea under shared socioeconomic pathways (SSP) scenarios, SSP2-4.5 and SSP5-8.5, using random forest (RF) models. Bioclimatic variables, including annual mean temperature (BIO1) and annual precipitation (BIO12), were identified as key contributors to habitat suitability changes. The model demonstrated high predictive accuracy, with receiver operating characteristic (ROC) values exceeding 0.8 for five species, such as <i>Papilio helenus</i> and <i>Argynnis hyperbius</i>, while six species, including <i>Sympetrum pedemontanum elatum</i>, exhibited lower predictability due to data distribution challenges. The results revealed that SSP2-4.5 allowed more stable or expanding habitats for certain species, such as <i>Argynnis hyperbius</i> and <i>Lampides boeticus</i>, where habitat areas significantly increased by 2070. In contrast, SSP5-8.5 showed drastic habitat reductions for most species, including <i>Camponotus kiusiuensis</i> and <i>Sympetrum pedemontanum elatum</i>, with some habitats shrinking by over 90% by 2090. The study underscores the importance of climate variables, with temperature and precipitation consistently influencing habitat changes across species. This research provides critical insights into the ecological risks posed by climate change and emphasizes the necessity of mitigation strategies. While some species demonstrate adaptive potential under moderate scenarios, others face severe vulnerabilities under extreme climate conditions. These findings offer valuable guidance for biodiversity conservation and policy-making, highlighting the need for integrated approaches that account for non-climatic factors such as land-use changes.

Design and application of CNN for emission detection through thermal imagery

Motorcycle exhaust emissions (EE) that do not meet regulatory standards present a significant environmental and public health issue, particularly given the rising number of motorcycles in densely populated areas. These emissions release pollutants such as carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOx), which contribute to poor air quality and have adverse effects on human health. Traditional emission testing methods using gas analyzers, while commonly used, face limitations such as sensitivity to environmental fluctuations, the necessity for frequent recalibration, and an intensive testing process requiring specialized expertise. This study addresses these issues by developing an innovative method for emission detection using Convolutional Neural Networks (CNN) applied to thermal images of motorcycle exhausts. The research method involves five key stages: data acquisition, dataset formation, CNN model design and training, model testing, and validation. Thermal images were gathered from 27 motorcycles, representing various brands and engine configurations common in Indonesia, and each image set included 100 samples for both emission-compliant and non-compliant categories. By analyzing thermal patterns, the CNN model was trained to accurately detect combustion patterns indicative of emission status based on the lambda value. This approach enables the model to generalize across different motorcycle models, offering practical adaptability for widespread implementation. The results demonstrate that the CNN model delivers high predictive accuracy, precision, recall, and F1-score, making it a robust tool for assessing motorcycle emission compliance. This CNN-based approach provides a practical solution for real-time, large-scale emission monitoring and regulatory enforcement, reducing dependency on conventional methods. Its scalability and adaptability position it as a valuable advancement in emission monitoring technology, with significant potential for supporting environmental standards and improving air quality management

The analysis of the genetic loci affecting phenotypic plasticity of soybean isoflavone content by dQTG.seq model.

The dQTG.seq model was utilized to investigate the genetic underpinnings of phenotypic plasticity in soybean isoflavone content, leading to the identification of 100 marker sites associated with phenotypic plasticity, including 27 transcription factors. Overexpression of Glyma.18G091600 (GmERF7) hairy roots under low temperature, salt, and drought stress confirmed the regulatory role of GmERF7 in the phenotypic plasticity of soybean isoflavone content. Phenotypic plasticity is characteristic of organisms that undergo phenotypic changes in response to environmental fluctuations. This phenomenon is pivotal in evolutionary processes and the emergence of new traits. Isoflavones, significant secondary metabolites found in soybeans, have garnered considerable attention owing to their beneficial physiological effects on human health. The variation in isoflavone content among different soybean varieties is influenced by diverse environmental factors, thereby influencing the evaluation of high and low isoflavone varieties. In this study, we measured the phenotypic plasticity of isoflavone content in recombinant inbred lines Hefeng 25 and L-28 in three different environments over two years. Utilizing the dQTG.seq model, 100 statistically significant markers were identified, and 101 potential genes, including 27 transcription factors, were screened. Through qRT-PCR analysis, elevated expression levels of Glyma.18G091600, Glyma.09G196200, and Glyma.05G229500 were observed in various parts of soybean plants. Under low temperature, drought or salt stress conditions, the related enzymes involved in the isoflavone synthesis pathway were notably upregulated in Glyma.18G091600 (GmERF7) overexpressed hairy roots compared to wild-type controls, resulting to higher phenotypic plasticity values for DZ, GC, GT, and TI. These results suggest that GmERF7 influences the phenotypic plasticity of soybean isoflavone content, enhancing adaptation to adverse environments, while also promoting the synthesis and accumulation of soybean isoflavones.

Generalized end-product feedback circuit can sense high-dimensional environmental fluctuations.

Understanding computational capabilities of simple biological circuits, such as the regulatory circuits of single-cell organisms, remains an active area of research. Recent theoretical work has shown that a simple cross-talk architecture based on end-product inhibition can exhibit predictive behavior by learning fluctuation statistics of one or two environmental parameters. Here we extend this analysis to higher dimensions, i.e., a large number of fluctuating inputs. We show that a generalized version of the cross-talk architecture can learn not only the dominant direction of fluctuations, as shown previously, but also the subdominant modes, orienting its responsiveness spectrum to the fluctuation eigenmodes. We comment on the relevance of our results to living systems at other scales of organization, such as ecosystems of species competing for fluctuating resources.

Effects of Hyporheic Water Exchange on Microbial Community Structure and Function: A Case Study in the Beiluo River, Loess Plateau, China

ABSTRACT Microbial communities in riverine hyporheic zones provide essential ecosystem services. However, the mechanisms whereby they respond to hyporheic water exchange under different habitat stress conditions remain poorly understood. Therefore, investigating the impact of riverine hyporheic exchange on the microbial community composition and its potential ecological function is essential, particularly in the seasonal rivers of northern China. To elucidate the structure and function of hyporheic zone sediment microbial communities in response hyporheic exchange and environmental fluctuations, we examined associations by performing in situ falling‐head permeameter tests and eDNA techniques. The primary findings were as follows: (1) We detected variations in the spatial distribution patterns of streambed hydraulic conductivity (range, 0.055–3.490 m/day) and vertical fluxes (range, 1.886–342.0 mm/day) among different monitoring stations. (2) Microbial communities displayed compositional similarities and spatial heterogeneity. Stations with limited vertical exchange were characterised by reduced species diversity. (3) Prokaryotes showed better modularity characteristics with higher stability and functional diversity than eukaryotic communities. (4) Differences in the abundance of microbial metabolism and genetic functions were observed among different habitats. This study emphasises the significance of local hydrological patterns (such as downwelling) in maintaining riverine environmental elements and acting as hotspots for microbial diversity within the hyporheic zone. The heterogeneity of the hydrological patterns governing hyporheic water exchange can explain the abundance, species diversity and biogeochemical processes of microorganisms within this zone.

Stochastic Models for Ontogenetic Growth

Based on allometric theory and scaling laws, numerous mathematical models have been proposed to study ontogenetic growth patterns of animals. Although deterministic models have provided valuable insight into growth dynamics, animal growth often deviates from strict deterministic patterns due to stochastic factors such as genetic variation and environmental fluctuations. In this study, we extend a general model for ontogenetic growth proposed by West et al. to stochastic models for ontogenetic growth by incorporating stochasticity using white noise. According to data variance fitting for stochasticity, we propose two stochastic models for ontogenetic growth, one is for determinate growth and one is for indeterminate growth. To develop a universal stochastic process for ontogenetic growth across diverse species, we approximate stochastic trajectories of two stochastic models, apply random time change, and obtain a geometric Brownian motion with a multiplier of an exponential time factor. We conduct detailed mathematical analysis and numerical analysis for our stochastic models. Our stochastic models not only predict average growth well but also variations in growth within species. This stochastic framework may be extended to studies of other growth phenomena.

Weak effect of temperature fluctuations on the invasion of Raphidiopsis raciborskii (Cyanobacteria) in experimental plankton microcosms.

Biological invasions are a major threat for many aquatic ecosystems. In contrast to higher plants and animals, microbial invasions are less obvious and more difficult to detect. One of the most prominent microbial invaders is the cyanobacterium Raphidiopsis raciborskii. To better understand the environmental conditions favoring its invasion success, we studied invasion under three different temperature regimes (one constant and two variable) in experimental plankton communities by invader addition experiments. To account for intraspecific variation, we tested four different strains of R. raciborskii and the mixture of them. Invasion success of R. raciborskii was higher under constant temperature conditions than under fluctuations suggesting that the resident species responded faster to the environmental changes than the invaders. We observed a clear strain-specific effect, demonstrating that strain identity is an important determinant of invasion success. The interaction of temperature fluctuations and strain identity indicates that, among the tested strains, the response to the temperature regimes varied. The mixture of all four strains did not perform better than the best single strain showing no sign of a positive genetic diversity effect. In our experiment, environmental fluctuations did not widen a window of opportunity for the invasion of R. raciborskii.

Temporary Nanoencapsulation of Human Intestinal Organoids Using Silk Ionomers.

Human intestinal organoids (HIOs) are vital for modeling intestinal development, disease, and therapeutic tissue regeneration. However, their susceptibility to stress, immunological attack, and environmental fluctuations limits their utility in research and therapeutic applications. This study evaluated the effectiveness of temporary silk protein-based layer-by-layer (LbL) nanoencapsulation technique to enhance the viability and functions of HIOs against common biomedical stressors, without compromising their native functions. Cell viability and differentiation capacity are assessed, finding that nanoencapsulation significantly improved HIO survival under the various environmental perturbations studied without compromising cellular functionality. Post-stress exposures, the encapsulated HIOs still successfully differentiated into essential intestinal cell types such as enterocytes, goblet cells, enteroendocrine cells, and Paneth cells. Moreover, the silk nanocoatings effectively protected against environmental stressors such as ultraviolet (UV) light exposure, protease degradation, antibody binding, and cytokine-induced inflammation. This nanoencapsulation technique shows promise for advancing HIO applications in disease modeling, drug testing, and potential transplantation therapies.

Exploring the Microbial Ecology of Nitrification Denitrification in Wastewater Treatment: Innovations and Future Directions

The nitrification-denitrification process serves as a critical mechanism in the biological removal of nitrogen from wastewater, a necessity for mitigating the environmental impact of nitrogen compounds on aquatic ecosystems. This complex process is orchestrated by diverse microbial communities, whose ecological interactions and functional capabilities are central to the efficiency and stability of nitrogen removal. In recent years, advances in molecular biology and microbial ecology have shed new light on the intricate dynamics within these microbial communities, revealing the roles of lesser known microbial taxa and the importance of microbial community structure and function in optimizing nitrification denitrification processes. This review provides a comprehensive examination of the microbial ecology involved in nitrification and denitrification, exploring the roles of key microbial players, including ammonia oxidizing bacteria (AOB), Nitrite oxidizing Bacteria (NOB), ammonia oxidizing archaea (AOA), and denitrifying bacteria. The review also delves into the environmental factors that influence microbial community dynamics, such as pH, temperature, oxygen availability, and the presence of inhibitory substances. By understanding these factors, the review highlights the challenges of maintaining stable and efficient nitrogen removal processes, particularly in the face of environmental fluctuations and operational disturbances, the review discusses recent innovations in wastewater treatment technologies that leverage microbial ecology to enhance process efficiency. These include bio-augmentation strategies, where specific microbial strains are introduced to bolster nitrification and denitrification, and advanced bioreactor designs, such as moving bed biofilm reactors (MBBRs) and membrane bioreactors (MBRs), which provide optimized environments for microbial growth and activity. The integration of anaerobic ammonium oxidation (anammox) processes, which offer significant energy savings and reduce greenhouse gas emissions, is also explored as a promising alternative to traditional nitrification pathways.

A low-temperature tunable microcavity featuring high passive stability and microwave integration

Open microcavities offer great potential for the exploration and utilization of efficient spin-photon interfaces with Purcell-enhanced quantum emitters thanks to their large spectral and spatial tunability combined with high versatility of sample integration. However, a major challenge for this platform is the sensitivity to cavity length fluctuations in the cryogenic environment, which leads to cavity resonance frequency variations and thereby a lowered averaged Purcell enhancement. This work presents a closed-cycle cryogenic fiber-based microcavity setup, which is in particular designed for a low passive vibration level, while still providing large tunability and flexibility in fiber and sample integration, and high photon collection efficiency from the cavity mode. At temperatures below 10 K, a stability level of around 25 pm is reproducibly achieved in different setup configurations, including the extension with microwave control for manipulating the spin of cavity-coupled quantum emitters, enabling a bright photonic interface with optically active qubits.

Research Progress of Metal Additive Manufacturing Technology and Application in Space: A Review

Metal additive manufacturing in space is a cutting-edge technology that is designed to meet the needs of space exploration and space station construction. This technology is capable of customizing and repairing key metallic parts in a space microgravity environment, providing the feasibility for long-term space tasks. It enables astronauts to perform on-site repairs and replace broken parts, significantly reducing the risk of mission failure on the International Space Station or during future deep space missions. Further, this technique opens new possibilities for constructing space bases by directly utilizing the materials from space, thereby reducing reliance on Earth’s resources. However, metal additive manufacturing in space faces challenges due to the unclear underlying mechanisms that lie in (I) the significant differences in the melting behaviors of materials in a space microgravity environment compared to those on Earth; and (II) extreme environmental factors, i.e., radiation and temperature fluctuations, that influence the metal additive manufacturing process and, consequently, the properties of the manufactured materials. This review provides a comprehensive analysis of those mechanisms underlying metal additive manufacturing in space, based on published works. Emphasis is placed on aluminum, titanium, iron, and copper-based metals. Our work may offer valuable guidance for reducing mission costs, improving safety, and enabling the on-demand production of complex components in the harsh environment of space by using metal additive manufacturing.