Environmental Conditions Research Articles

Developmental and environmental effects on VTC2-dependent leaf ascorbate accumulation and functions.

In nature, environmental conditions strongly fluctuate, frequently subjecting plants to periods of immediate photo-oxidative stress. The small molecule ascorbate allows plants to cope with such stress conditions. Ascorbate scavenges reactive oxygen species and enables the rapid and full induction of photoprotective non-photochemical quenching (NPQ). NPQ is dependent on zeaxanthin (Zx), which requires ascorbate as the electron donor during its synthesis by the violaxanthin de-epoxidase. The VTC2 gene encodes for one of two isoforms of GDP-L-galactose phosphorylase, the rate-controlling enzyme of ascorbate biosynthesis. In the current study, by including a newly identified vtc2 allele, we found that loss of VTC2 depleted ascorbate mainly from the mature leaves and thereby limited NPQ specifically in this tissue. Growth in fluctuating light and controlled climate suppressed the slow NPQ induction phenotype of vtc2 mature leaves to some degree. This was concurrent with a constitutively higher accumulation of zeaxanthin under this condition. When plants were shifted to natural conditions, with strongly fluctuating light and temperature, the ascorbate deficient mature leaves of vtc2 bleached. Together, our results reveal developmental and environmental effects on VTC2-dependent ascorbate accumulation and function.

Bioenergetic trade-offs can reveal the path to superior microbial CO2 fixation pathways.

A comprehensive optimization of known prokaryotic autotrophic carbon dioxide (CO2) fixation pathways is presented that evaluates all their possible variants under different environmental conditions. This was achieved through a computational methodology recently developed that considers the trade-offs between energy efficiency (yield) and growth rate, allowing us to evaluate candidate metabolic modifications in silico for microbial conversions. The results revealed the superior configurations in terms of both yield (efficiency) and rate (driving force). The pathways from anaerobic organisms appear to fix carbon at lower net ATP cost than those found in aerobic organisms, and the reverse TCA cycle pathway shows the lowest overall energy cost and maximum adaptability across a broad range of CO2 and electron donor (H2) concentrations. The reverse tricarboxylic acid cycle and Wood-Ljungdahl pathways appear highly efficient under a broad range of conditions, while the 3-hydroxypropionate 4-hydroxybutyrate cycle and the 3-hydroxypropionate bicycle appear capable of generating large thermodynamic driving forces at only moderate ATP yield losses.IMPORTANCEBiotechnology can lead to cost-effective processes for capturing carbon dioxide using the natural or genetically engineered metabolic capabilities of microorganisms. However, introducing desirable genetic modifications into microbial strains without compromising their fitness (growth yield and rate) during industrial-scale cultivation remains a challenge. The approach and results presented can guide optimal pathway configurations for enhanced prokaryotic carbon fixation through metabolic engineering. By aligning strain modifications with these theoretically revealed near-optimal pathway configurations, we can optimally engineer strains of good fitness under open culture industrial-scale conditions.

Developing Strategies for Carbon Neutrality Through Restoration of Ecological Spatial Networks in the Thal Desert, Punjab

Carbon neutrality is an important goal for addressing global warming. It can be achieved by increasing carbon storage and reducing carbon emissions. Vegetation plays a key role in storing carbon, but it is often lost or damaged, especially in areas affected by desertification. Therefore, restoring vegetation in these areas is crucial. Using advanced techniques to improve ecosystem structure can support ecological processes, and enhance soil and environmental conditions, encourage vegetation growth, and boost carbon storage effectively. This study focuses on optimizing Ecological Spatial Networks (ESNs) for revitalization and regional development, employing advanced techniques such as the MCR model for corridor construction, spatial analysis, and Gephi for mapping topological attributes. Various ecological and topological metrics were used to evaluate network performance, while the EFCT model was applied to optimize the ESN and maximize carbon sinks. In the Thal Desert, ecological source patches (ESPs) were divided into four modularity levels (15.6% to 49.54%) and five communities. The northeastern and southwestern regions showed higher ecological functionality but lower connectivity, while the central region exhibited the reverse. To enhance the ESN structure, 27 patches and 51 corridors were added to 76 existing patches, including 56 forest and 20 water/wetland patches, using the EFCT model. The optimized ESN resulted in a 14.97% improvement in carbon sink capacity compared to the unoptimized structure, primarily due to better functioning of forest and wetland areas. Enhanced connectivity between components contributed to a more resilient and stable ESN, supporting both ecological sustainability and carbon sequestration.

Investigating the Post-Mortem Risk of Transmission of SARS-CoV-2 Virus in Cadaveric Tissues: A Systematic Review of the Literature

The emergence of SARS-CoV-2, responsible for the COVID-19 pandemic, has prompted extensive research into its transmission dynamics; yet, a critical aspect that remains underexplored is the post-mortem infectivity of the virus within cadaveric tissues. Understanding the mechanisms by which SARS-CoV-2 maintains infectivity after death is essential, as it raises significant concerns regarding public health and forensic practices. Research indicates that the virus can persist in various tissues, including lung, liver, and kidney tissues, with studies showing that factors such as the time elapsed since death, the presence of underlying health conditions, and environmental conditions at the time of death can influence the level of infectivity in deceased individuals. These findings are not only crucial for establishing safety protocols for forensic investigators who handle cadavers but also for informing public health guidelines that govern the management of bodies during and after outbreaks. As we investigate the implications of post-mortem SARS-CoV-2 infectivity, it becomes imperative to establish comprehensive protocols to mitigate risks associated with the handling and disposal of infected bodies, thereby protecting public health and ensuring the safety of those working in forensic environments. This paper aims to elucidate the mechanisms of infectivity in cadaveric tissues, explore the persistence of the virus in various tissue types, and assess the broader implications for public health and forensic investigations, ultimately contributing to a safer approach in dealing with COVID-19-related fatalities.

Loss of γ-aminobutyric acid D-Type Motor Neurons in Young Adult Caenorhabditis elegans Following Exposition with Silica Nanoparticles

Although Caenorhabditis elegans is commonly used to assess the neurotoxicity of environmental pollutants, studies that explore the intricate biology of its nervous system, particularly those addressing long-term effects and aging in adult worms, are rare. These models offer significant advantages for understanding the full spectrum of neurobiological impacts. Here, we investigated the effects of silica nanomaterials on the γ-aminobutyric acid (GABA) neural system in young to middle-aged nematodes and found a unique degeneration pattern characterized by loss of anterior- and posteriormost GABAergic D-type motor neurons. Four-day-old nematodes were identified as a vulnerable age group, where the pollutant-accelerated neurodegeneration that is typically seen in old C. elegans. Proteomics of 4-day-old C. elegans revealed significant alterations of protein abundance, including the downregulation of proteins such as glutamate dehydrogenase (gdh-1) and glutamate oxaloacetate transaminase (got-1.2), which are essentially involved in GABA metabolic pathways. Consistent with these findings, we demonstrated locomotion deficits in C. elegans exposed to nanoscale silica by establishing a semi-automated behavioral arena. Our setup not only visualizes but also automatically quantifies vulnerabilities at the individual worm level. This novel neurodegeneration model now enables the simulation of real-world pollutant mixtures and environmental conditions, capturing the complexity of the exposome.

ЭКОЛОГИЧЕСКАЯ РЕАКЦИЯ УРОЖАЙНОСТИ ПШЕНИЦЫ ЯРОВОЙ МЯГКОЙ НА ИЗМЕНЕНИЕ ПРИРОДНЫХ УСЛОВИЙ В ПРОСТРАНСТВЕ И ВО ВРЕМЕНИ

The purpose of the study is to determine the dependence of the yield of soft spring wheat on climatic conditions in the time lag and in natural zones using the example of the Altai Region. Objectives: to determine the variation in the yield of spring soft wheat for 2016–2020, research on the subzones of the Altai Region; to calculate specific conditions and evaluate the effect of hydrothermal conditions on the yield of soft spring wheat. The object of the study was soft spring wheat and its productivity. It was found that the sustainability of agricultural land use in the Altai Region depends on environmental conditions and factors affecting the ecological response (yield) of wheat in the subzones of the region. Yields were studied for five years in five subzones. It was found that the variation (decrease) in the yield of spring wheat by subzones in the studied time lag occurs as you move from east to west of the region. This is evidenced by the interval and range of variation, arithmetic mean, standard deviation and other statistical values calculated by zones and years of study. Next, according to the HTC value, the years were ranked and the specific conditions of the spring wheat yield were determined. At the next stage of the work, the calculation of the general information content and the coefficient of efficiency of information transfer from the hydrothermal coefficient to the yield of spring soft wheat were carried out. It has been reliably established that in all subzones, the formation of the crop is largely influenced by the HTC in the first half of the growing season (May–June), and to a lesser extent in July–August. The results of the study can be used in forecasting the grain harvest and the formation of domestic consumption and exports.

КОМБИНАЦИОННАЯ СПОСОБНОСТЬ МЯГКОЙ ЯРОВОЙ ПШЕНИЦЫ ПО МАССЕ ЗЕРНА КОЛОСА В ТОПКРОССНЫХ СКРЕЩИВАНИЯХ

The purpose of research is to analyze the general and specific combining ability of soft spring wheat based on the trait “grain weight per spike” in the conditions of the Priob forest-steppe of the Altai Region. The experiment was conducted in 2020–2021 using pure fallow on the experimental field of the Federal Altai Scientific Center for Agrobiotechnology, located in the Priob forest-steppe of the Altai Region. The work studied the combinative ability of varieties and lines of soft spring wheat for the trait “grain weight per main spike” according to a topcrossing scheme consisting of 13 maternal and 3 paternal forms. The weather conditions during the years of the experiment are characterized. It has been established that the level of manifestation and the nature of inheritance of the trait under consideration, as well as the effects of general (GCA) and specific (SCA) combinative ability, largely depend on environmental conditions and the analyzed generation of hybrids (F1 and F2). The dominant contribution to the total dispersion of spike grain weight is made by year conditions (97.8 %), followed by genotypic characteristics (2.1 %) and their general interaction (0.1 %). The leading role in the system of genetic control of a trait belongs to genes with an additive type of action, with a small contribution from non-additive gene effects. The varieties and lines of test crosses differed significantly in the analyzed trait. On average, over 2 years of research, the following varieties differed in higher spike grain weight among maternal forms: Omskaya 42, Lutescens 186/04-6 and Lutescens 6/04-4 (with values from 1.45 to 1.95 g), and among paternal forms – Lider 80 (with values from 1.31 to 2.03 g). Valuable combinations of crosses with high expression of the studied trait have been selected, which are promising both in terms of selection of the desired genotypes in early generations of hybrids, and in terms of direct use in recurrent selection when creating new commercial varieties.

A DOF transcriptional repressor-gibberellin feedback loop plays a crucial role in modulating light-independent seed germination.

Plants evolved several strategies to cope with the ever-changing environment. One example of this is given by seed germination, which must occur when environmental conditions are suitable for plant life. In the model system Arabidopsis thaliana seed germination is induced by light; however in nature, seeds of several plant species can germinate regardless of this stimulus. Whereas the molecular mechanisms triggered by light for seed germination are well understood, the ones permitting plants to germinate in the dark are still vague mostly due to the lack of suitable model systems. Here we employ Cardamine hirsuta, a close Arabidopsis relative, as a powerful model system to uncover the molecular mechanisms underlying light-independent germination. Comparing Cardamine and Arabidopsis we show that the maintenance of the pro-germination hormone Gibberellin (GA) levels prompt Cardamine seeds to germinate in dark and light conditions. Via genetic and molecular biology experiments, we show that the Cardamine DOF transcriptional repressor DOF AFFECTING GERMINATION 1 (ChDAG1), homologous to the Arabidopsis DAG1 transcription factor, is involved in this process functioning to mitigate GA levels via negative regulation of ChGA3OX1 and ChGA3OX2 gibberellin biosynthetic genes, independently of light conditions. We also demonstrate that this mechanism is likely to be conserved in other Brassica species capable of germinating in dark conditions, such as Lepidium sativum and Camelina sativa. Our data support the proposal that Cardamine is a new model system suitable for light-independent germination studies. Exploiting this system we also resolved a long-time question about the mechanisms controlling the light-independent germination in plants, opening new frontiers for future studies.

Climate Change and Plant Foods: The Influence of Environmental Stressors on Plant Metabolites and Future Food Sources

Climate change is reshaping global agriculture by altering temperature regimes and other environmental conditions, with profound implications for food security and agricultural productivity. This review examines how key environmental stressors—such as extreme temperatures, water scarcity, increased salinity, UV-B radiation, and elevated concentrations of ozone and CO2—impact the nutritional quality and bioactive compounds in plant-based foods. These stressors can modify the composition of essential nutrients, particularly phytochemicals, which directly affect the viability of specific crops in certain regions and subsequently influence human dietary patterns by shifting the availability of key food resources. To address these challenges, there is growing interest in resilient plant species, including those with natural tolerance to stress and genetically modified variants, as well as in alternative protein sources derived from plants. Additionally, unconventional food sources, such as invasive plant species and algae, are being explored as sustainable solutions for future nutrition.

Precise measurement of the 7Be electron capture decay half-life in silicon carbide

Abstract In this work we present to our knowledge the most precise measurement of the 7Be electron capture decay half-life in a host material. A silicon carbide sample with ~8.62 × 109 7Be atoms was measured for 83.5 d on an ultra-low background high purity Ge detector located deep underground in the Laboratori Nazionali del Gran Sasso, Italy. The result obtained for the decay half-life is T 1/2 = 53.284 ± 0.016 d, which corresponds to an uncertainty of 0.3‰. Thanks to the high sensitivity achieved, this measurement is paving the way to further investigations on this process aiming to understand how environmental conditions may affect the decay half-life.

Hotter temperatures alter riparian plant outcomes under regulated river conditions

AbstractClimate change and river regulation alter environmental controls on riparian plant occurrence and cover worldwide. Simultaneous changes to river flow and air temperature could result in unanticipated plant responses to novel environmental conditions. Increasing temperature could alter riparian plant response to hydrology and other factors, while river regulation may exacerbate environmental stress through novel flows like those resulting from power generation. Further, plant establishment and growth may require differing conditions, which may be decoupled by novel conditions. Using a large dataset that spans a natural 5°C mean annual temperature (MAT) gradient and a Bayesian model that integrates plant occurrence and cover, we address four questions: (1) Does hotter MAT modify plant response to hydrology, substrate composition, topography, and cover of co‐occurring plant species? (2) Does the timing of hydropower tides benefit some species over others? (3) Does dam‐induced erosion hinder riparian species more than upland species? (4) Do occurrence and cover respond to different environmental variables, allowing for decoupling of life history processes? We addressed these questions with data collected along 364 km of the Colorado River downstream of Glen Canyon Dam, Arizona, United States of America. Occurrence and cover class were recorded in >10,000 plots from 2016 to 2020, along with environmental covariates that repeat across the climate gradient. For 36 species, plant occurrence and cover were modeled with respect to MAT, hydrology, substrate, topography, other plant cover, and their interactions with MAT. There were four key results. (1) Increasing MAT will not only directly influence plants but will mediate their responses to the environment, including greater dependence on stable water supplies. (2) The timing of hydropower tides shapes plant community composition. (3) Dam‐related erosion has an outsized effect on riparian species, which could lead to a loss of regionally unique plant species. (4) For all species, the most important covariates driving occurrence differed from those for cover, suggesting the potential for these life stages to be decoupled. Not only will climate change and river regulation independently alter plant distributions, interactions among hotter temperature, dam‐controlled flow patterns, and limited fine sediments will determine which species flourish or perish under future conditions.

Physicochemical Properties of Nanoencapsulated Essential Oils: Optimizing D-Limonene Preservation

Essential oils exhibit antioxidant properties but are prone to oxidative degradation under environmental conditions, making their preservation crucial. Therefore, the purpose of this work was to evaluate the physicochemical properties of nanoencapsulated essential oils (EOs) extracted from the peel of sweet lemon, mandarin, lime, and orange using four formulations of wall materials consisting of gum arabic (GA), maltodextrin (MD), and casein (CAS). The results showed that EOs from sweet lemon, mandarin, lime, and orange showed higher solubility (79.5% to 93.5%) when encapsulated with GA/MD. Likewise, EOs from sweet lemon showed the highest phenolic content when using GA/CAS (228.27 mg GAE/g sample), and the encapsulated EOs of sweet lemon and mandarin with GA/MD/CAS (1709 and 1599 μmol TE/g) had higher antioxidant capacity. On the other hand, higher encapsulation efficiency was obtained in EOs of lime encapsulated with GA/MD (68.5%), and the nanoencapsulates of EOs from sweet lemon with GA/MD had higher D-limonene content (613 ng/mL). Using gum arabic and maltodextrin increased the encapsulation efficiency and D-limonene content in EO of sweet lemon. On the other hand, the formulations with casein were the most efficient wall materials for retaining D-limonene from the EOs of mandarin, lime, and orange.

More on mobility and sedentism: Changes in adaptation from Upper Paleolithic to Incipient Jomon, Tanegashima Island, southern Japan.

Sedentism is an adaptive alternative in human societies which is often associated with the emergence of complex societies in the Holocene. To elucidate the factors and processes of the emergence of sedentary societies, continuous accumulation of case studies based on robust evidence from across the world is required. Given abundant archaeological and geological evidence from the late Pleistocene to early Holocene, Tanegashima Island, situated in the southern Japanese Archipelago of the northwestern Pacific Rim, has significant potential to unravel factors and processes of sedentism. Our study evaluates long-term change in hunter-gatherer mobility on Tanegashima Island from the Upper Paleolithic to Incipient Jomon (ca.36,000-12,800 cal BP). Based on Bayesian age modelling, we performed diachronic analyses on lithic toolkit structure, lithic reduction technology, lithic raw material composition, and occupation intensity. The results illustrate that settlement-subsistence strategies on Tanegashima primarily correspond to the change in environmental conditions, mainly food resources, and foragers increased their degrees of sedentism when abundant forest existed. More important is that highly stable sedentism, which is not observed until the Incipient Jomon, depends not only on such a productive environment, but also on the increase in population size. High occupation intensity during the Incipient Jomon on the island is likely attributed to an influx of people from Kyushu proper. Although the relationship between cause and effect of these factors is still to be clarified in future work, our study provides insights on the fundamental causes of sedentism in the temperate forest of the late Pleistocene.

Advanced Technologies in Plant Factories: Exploring Current and Future Economic and Environmental Benefits in Urban Horticulture

Abstract Plant factories (PFs), also known as vertical farms, are advanced agricultural production systems that operate independently of geographical and environmental conditions. They utilize artificial light and controlled environments to produce horticultural plants year-round. This approach offers a promising solution for the stable and efficient supply of high-quality horticultural produce in urban areas, enhancing resilient urban food systems. This review explores the economic and environmental impacts and potential of PFs. Breakthroughs in PF research and development are highlighted, including increased product yields and quality, reduced energy input and CO2 emissions through optimized growing conditions and automation systems, transitioning to clean energy, improved resource use efficiency, and reduced food transport distances. Moreover, innovations and applications of PFs have been proposed to address challenges from both economic and environmental perspectives. The proposed development of PF technologies for economic and environmental benefits represents a comprehensive and promising approach to urban horticulture, significantly enhancing the impact and benefits of fundamental research and industrial applications.

Response of Leaf Non-Structural Carbohydrates to Elevation in Dioecious Plants, Populus cathayana and Hippophae rhamnoides

Non-structural carbohydrates (NSCs) can reflect the balance of resource allocation and trade-offs, as well as the adaptability of plants to the environment. Alterations in environmental conditions across an elevation gradient may impact the carbon balance within leaves. Nonetheless, it remains highly uncertain whether the effect of elevation on NSCs differs among species and sexes. To reveal the response patterns of leaf NSCs in dioecious plants with elevation, Populus cathayana Rehd. and Hippophae rhamnoides L., distributed at four elevations in the subalpine region of western Sichuan, China, were selected, and female and male leaves were sampled and measured for their contents of NSCs, soluble sugar, and starch. Meanwhile, the relationships of NSCs, soluble sugar, and starch with leaf nitrogen and phosphorus were analyzed. The results showed that the elevational patterns of NSCs were mainly dependent on species and were slightly affected by sex. Leaf NSCs in both sexes of P. cathayana did not exhibit significant linear changes, whereas those in H. rhamnoides increased significantly and linearly with elevation. For P. cathayana, a significant increase in leaf starch with elevation was only found in female plants and may benefit from phosphorus deficiency, as it was significantly negatively correlated with phosphorus. However, leaf soluble sugar and starch between sexes of H. rhamnoides showed similar patterns of significant increases with elevation, and they were not correlated significantly with nitrogen and phosphorus. This might be due to H. rhamnoides, which is a nitrogen-fixing plant and thereby did not show deficiencies or limitations in nitrogen and phosphorus, as shown by the decreased or unchanged elevational patterns of nitrogen/phosphorus, starch/phosphorus, and soluble sugar/phosphorus. Overall, our results emphasize that species, rather than sex, is an important factor influencing the elevational pattern of NSCs, but for specific species, such as P. cathayana, in this study, there was a divergence in the elevational response of the allocation of starch and soluble sugar between sexes, reflecting the specific adaptive strategies of different plant species or sexes in response to changes in the growing environment.

Effects of 2,4-D with and without wiper-applied glyphosate on leafy spurge (Euphorbia esula) shoot, shoot regrowth, and root biomass

Abstract Pot studies outdoors under natural environmental conditions were conducted to determine leafy spurge biomass reduction resulting from broadcast application of 2,4-D (2,244 g ae ha-1) with and without wiper-applied glyphosate. Glyphosate (575 g ae L-1) was applied at 0, 33, 50, and 75% diluted concentrate with a wiper 24 hrs after 2,4-D was broadcast applied. Injury estimates and shoot biomass did not differ between plants treated with 2,4-D-only or the addition of wiper-applied glyphosate 21 days after treatment. Shoot regrowth biomass of plants treated with 2,4-D-only was approximately 560% greater compared to nontreated plants three months after treatment. Plants treated with wiper-applied glyphosate had shoot regrowth biomass of less than 10% compared to the nontreated plants 3 months after treatment. Root biomass of 2,4-D-only treated plants (160% of nontreated plants) followed a similar pattern of shoot regrowth biomass. Root biomass of plants treated with wiper-applied glyphosate exhibited approximately 50% reductions compared to nontreated plants. The concentrations of glyphosate tested reduced all vegetative metrics equally; therefore, all labeled concentrations should be effective. The results of the experiment show that broadcast-applied 2,4-D is more effective at reducing leafy spurge biomass with the addition of wiper-applied glyphosate.

A comparative study of the performance of ten metaheuristic algorithms for parameter estimation of solar photovoltaic models

This study conducts a comparative analysis of the performance of ten novel and well-performing metaheuristic algorithms for parameter estimation of solar photovoltaic models. This optimization problem involves accurately identifying parameters that reflect the complex and nonlinear behaviours of photovoltaic cells affected by changing environmental conditions and material inconsistencies. This estimation is challenging due to computational complexity and the risk of optimization errors, which can hinder reliable performance predictions. The algorithms evaluated include the Crayfish Optimization Algorithm, the Golf Optimization Algorithm, the Coati Optimization Algorithm, the Crested Porcupine Optimizer, the Growth Optimizer, the Artificial Protozoa Optimizer, the Secretary Bird Optimization Algorithm, the Mother Optimization Algorithm, the Election Optimizer Algorithm, and the Technical and Vocational Education and Training-Based Optimizer. These algorithms are applied to solve four well-established photovoltaic models: the single-diode model, the double-diode model, the triple-diode model, and different photovoltaic module models. The study focuses on key performance metrics such as execution time, number of function evaluations, and solution optimality. The results reveal significant differences in the efficiency and accuracy of the algorithms, with some algorithms demonstrating superior performance in specific models. The Friedman test was utilized to rank the performance of the various algorithms, revealing the Growth Optimizer as the top performer across all the considered models. This optimizer achieved a root mean square error of 9.8602187789E−04 for the single-diode model, 9.8248487610E−04 for both the double-diode and triple-diode models and 1.2307306856E−02 for the photovoltaic module model. This consistent success indicates that the Growth Optimizer is a strong contender for future enhancements aimed at further boosting its efficiency and effectiveness. Its current performance suggests significant potential for improvement, making it a promising focus for ongoing development efforts. The findings contribute to the understanding of the applicability and performance of metaheuristic algorithms in renewable energy systems, providing valuable insights for optimizing photovoltaic models.

Vision-based manipulation of transparent plastic bags in industrial setups

IntroductionThis paper addresses the challenges of vision-based manipulation for autonomous cutting and unpacking of transparent plastic bags in industrial setups, contributing to the Industry 4.0 paradigm. Industry 4.0, emphasizing data-driven processes, connectivity, and robotics, enhances accessibility and sustainability across the value chain. Integrating autonomous systems, including collaborative robots (cobots), into industrial workflows is crucial for improving efficiency and safety.MethodsThe proposed system employs advanced Machine Learning algorithms, particularly Convolutional Neural Networks (CNNs), for identifying transparent plastic bags under diverse lighting and background conditions. Tracking algorithms and depth-sensing technologies are integrated to enable 3D spatial awareness during pick-and-place operations. The system incorporates vacuum gripping technology with compliance control for optimal grasping and manipulation points, using a Franka Emika robot arm.ResultsThe system successfully demonstrates its capability to automate the unpacking and cutting of transparent plastic bags for an 8-stack bulk-loader. Rigorous lab testing showed high accuracy in bag detection and manipulation under varying environmental conditions, as well as reliable performance in handling and processing tasks. The approach effectively addressed challenges related to transparency, plastic bag manipulation and industrial automation.DiscussionThe results indicate that the proposed solution is highly effective for industrial applications requiring precision and adaptability, aligning with the principles of Industry 4.0. By combining advanced vision algorithms, depth sensing, and compliance control, the system offers a robust method for automating challenging tasks. The integration of cobots into such workflows demonstrates significant potential for enhancing efficiency, safety, and sustainability in industrial settings.

Exploration and implication of green macroalgal proliferation in the Nanhui-east-tidal-flat: an investigation of post-reclamation mudflat wetlands

The Nanhui-east-tidal-flat (NETF), the largest marginal shoal in the Yangtze River of China, is significantly impacted by human activities. Prior research has not detected the presence of green macroalgae in the NETF, nor has it explored the effects of reclamation on the distribution of macroalgae. However, in 2021, a small-scale aggregated attached algal mats emerged in the NETF, potentially signaling the onset of a green tide and necessitating vigilant monitoring. Morphological and molecular biological identification analysis revealed that all collected green macroalgae were attributed to a single dominant species, Ulva prolifera, characterized by broad blades and prominent air bladders, colonizing various substrates. The attached U. prolifera exhibited continuous growth from March to May 2021, peaking at a wet weight of 373.6229 g/m² and a dry weight of 72.7904 g/m² on May 1, 2021, within the accessible sampling period. The rapid proliferation of the “opportunistic” Ulva was facilitated by high-level eutrophication and favorable environmental conditions. Furthermore, six potential germplasm sources of U. prolifera are summarized. The dominance of Ulva in the intertidal zone often indicates high eutrophication and deteriorating ecological conditions. With long-term reclamation and repeated ecological restoration projects, the intertidal vegetation is subjected to a vicious cycle of growth and destruction. Therefore, it is important to recognize that U. prolifera germplasm (macroalgae and micropropagules) will persist over the long term, and mudflats with monotonous and eutrophic habitats are highly likely to experience future large-scale algal blooms. Notably, a small-scale floating green tide was observed in the sea area near NETF in July 2023, and such concerns are not unfounded. This study conducts foundational scientific research on the attached green tide algae, a type of research that is relatively scarce in other marine areas. Most studies tend to initiate foundational research only after the outbreak of green tides, lacking early background data from the marine environment, thus rendering this study of significant reference value. Concurrently, this study emphasizes that field surveys remain an essential approach for conducting foundational scientific research on green tide algae in the NETF region, with the need to select appropriate research methods based on the occurrence and development of algal mats, as required by the situation. Importantly, this study reflects the stability of marine ecosystems as a prerequisite for modern ocean management and services, provides new perspectives on the occurrence and development of green tides, and highlights potential ecological risk factors that should be considered in the implementation of intertidal construction projects.

Performance evaluation of four cascade impactors for airborne ultrafine-particle (UFP) collection: the influence of particle type, concentration, mass, and chemical nature

Abstract. Ultrafine particles (UFPs) have aerodynamic diameters of 100 nm or less. As UFPs potentially impact human and environmental health, their chemical composition is of interest. However, their small mass presents challenges for sampling and chemical characterization methods. Therefore, we conducted a comprehensive characterization and comparison of four cascade impactors suitable for separating and collecting UFPs – namely, the 120R Micro-Orifice Uniform Deposit Impactor (120R MOUDI-II), ultraMOUDI, electrical low-pressure impactor (ELPI), and personal nanoparticle sampler (PENS) – under controlled laboratory conditions and in a field application. In the laboratory, we evaluated pressure drops, cutoff diameters, the steepness of the cutoff curve, losses, particle bounce, and transmitted particle mass. We observed that the performance of the impactors varied between 59 and 116 nm in cutoff diameter (electromobility diameter), depending on the impactor's design and the type of test aerosol mixture – salt particles (NaCl), simulated secondary organic aerosol (SimSOA), or soot. All impactors separated UFPs, with the best agreement in cutoff diameters for SimSOA, which showed maximum deviations of about 4 nm. The cutoff curve was steeper for soot compared to SimSOA and NaCl. Pressure drops were measured at 260 ± 1 hPa (PENS), 420 ± 2 hPa (ultraMOUDI), 600 ± 3 hPa (120R MOUDI-II), and 690 ± 3 hPa (ELPI). Losses were assessed as maximum transmissions in the ultrafine fraction at 30 nm, yielding 83 ± 8 % for the PENS, 77 ± 8 % for the ultraMOUDI, 75 ± 8 % for the 120R MOUDI-II, and 69 ± 7 % for the ELPI. We compared two additional impactor-specific factors crucial for mass-based analyses of organic marker compounds: the evaporation of semi-volatile compounds due to a high-pressure drop across the impactor and material addition from larger particles bouncing off upper stages. “Bounce-off” was influenced by the particle number concentration in the sampled air and could be partially mitigated by applying a coating to the upper impaction plates. In the field application, we deployed the four cascade impactors side by side under environmental conditions to sample urban air. We analyzed six markers representing typical UFP sources and various molecular properties using HPLC-MS/FLD (high-performance liquid chromatography with mass spectrometry and fluorescence detection). These markers comprised benzo[a]pyrene (BaP), benzo[b]fluoranthene (BbF), levoglucosan (Levo), pinic acid (PA), terpenylic acid (TA), and N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD). The impactors showed the best agreement for BaP and BbF. BaP had an average mass concentration of 175 ± 25 pg m−3 across all impactors and sampling days. However, concentrations were about 29 % higher when sampled with the PENS and 30 % lower when sampled with the 120R MOUDI-II, indicating a maximum disagreement of nearly 60 %. The mass concentrations of the semi-volatile markers (PA, TA, and Levo) decreased on average from the PENS to the ultraMOUDI, then to the 120R MOUDI-II, and finally to the ELPI. We attributed this tendency to the following two effects. (1) Evaporation losses of these markers were likely driven by the pressure drop within the impactor, which increased from the PENS to the ELPI. (2) Despite the applied coating, bounce-off might have affected the smallest impactors (i.e., the PENS and ultraMOUDI) the most as they have fewer stages for retaining larger particles and fragments.