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A class of strong lower bounds on the solution value of a Linearised Integer Programming reformulation is introduced for the binary quadratic optimisation model to assign origin and destination nodes to strip and stack doors, resp., in a cross-dock infrastructure. The goal is to minimise the transportation cost of the commodities to be handled at the cross-dock. Strip- and stack-related decomposition submodels are developed by taking benefit of the Integer Linearisation Property that appears in the new model. A linear search heuristic is also provided for obtaining feasible solutions by exploiting the special structure of the problem. We present an extensive computational study on a testbed of 55 instances to show that the proposed joint scheme for lower bounding and feasible solution providing is very efficient. The results obtained by our proposal are similar to those obtained by CPLEX in the 50 instances taken from the literature, but usually the time is much smaller for the large instances. The comparison with CPLEX is particularly good for the new five largest instances, which make it very promising for its application in real-life cases. [ABSTRACT FROM AUTHOR]

The present study aimed to clarify the development of motor unit (MU) firing properties and the association between those neural properties and force steadiness (FS)/neurological tests in 6- to 12-year-old children. Fifty-eight school-aged children performed maximal voluntary knee extension contraction, a submaximal FS test at 10% of maximal voluntary knee extension contraction, knee extension reaction time to light stimulus test, and single-leg standing test, and data from 38 children who passed the criteria were subject to analysis. During the FS test, high-density surface electromyography was recorded from the vastus lateralis muscle to identify individual MU firing activity. FS was improved with an increase in age (r = −.540, P <.001). The MU firing rate (MUFR) was significantly decreased with an increase in age (r = −.343, P =.035). MUFR variability was not associated with age. Although there was no significant correlation between FS and MUFR, FS was significantly correlated with MUFR variability even after adjustment for the effect of age (r =.551, P =.002). Neither the reaction time nor the single-leg standing test was correlated with any MU firing properties. These findings suggest that MUFR variability makes an important contribution to precise force control in children but does not naturally develop with age. [ABSTRACT FROM AUTHOR]

Estuarine wetlands harbor considerable carbon stocks, but rising sea levels could affect their ability to sequester soil carbon as well as their potential to emit methane (CH4). While sulfate loading from seawater intrusion may reduce CH4 production due to the higher energy yield of microbial sulfate reduction, existing studies suggest other factors are likely at play. Our study of 11 wetland complexes spanning a natural salinity and productivity gradient across the San Francisco Bay and Delta found that while CH4 fluxes generally declined with salinity, they were highest in oligohaline wetlands (ca. 3-ppt salinity). Methanogens and methanogenesis genes were weakly correlated with CH4 fluxes but alone did not explain the highest rates observed. Taxonomic and functional gene data suggested that other microbial guilds that influence carbon and nitrogen cycling need to be accounted for to better predict CH4 fluxes at landscape scales. Higher methane production occurring near the freshwater boundary with slight salinization (and sulfate incursion) might result from increased sulfate-reducing fermenter and syntrophic populations, which can produce substrates used by methanogens. Moreover, higher salinities can solubilize ionically bound ammonium abundant in the lower salinity wetland soils examined here, which could inhibit methanotrophs and potentially contribute to greater CH4 fluxes observed in oligohaline sediments.IMPORTANCELow-level salinity intrusion could increase CH4 flux in tidal freshwater wetlands, while higher levels of salinization might instead decrease CH4 fluxes. High CH4 emissions in oligohaline sites are concerning because seawater intrusion will cause tidal freshwater wetlands to become oligohaline. Methanogenesis genes alone did not account for landscape patterns of CH4 fluxes, suggesting mechanisms altering methanogenesis, methanotrophy, nitrogen cycling, and ammonium release, and increasing decomposition and syntrophic bacterial populations could contribute to increases in net CH4 flux at oligohaline salinities. Improved understanding of these influences on net CH4 emissions could improve restoration efforts and accounting of carbon sequestration in estuarine wetlands. More pristine reference sites may have older and more abundant organic matter with higher carbon:nitrogen compared to wetlands impacted by agricultural activity and may present different interactions between salinity and CH4. This distinction might be critical for modeling efforts to scale up biogeochemical process interactions in estuarine wetlands.

The disparity in absenteeism between kindergarteners with and without disabilities is a persistent phenomenon across schools in the United States and reflects ongoing systemic inequities that disadvantage young children with disabilities. Yet, evidence of factors underlying this disparity remains less well understood, limiting the ability for schools to transform how they support students with disabilities in ways that could help narrow the disparity. In our study, we investigate how a set of factors, grounded in a socioecological framework of absenteeism, correlates with chronic absenteeism in kindergarteners with and without disabilities. Importantly, we examine the extent to which distributional differences in these factors between children with and without disabilities explain the attendance disparity. Our study draws upon a nationally representative sample of N = 13,860 kindergarteners (52 % male, 48 % female, M age = 5.5 years, n = 1240 with disabilities) from the Early Childhood Longitudinal Survey Kindergarten Class of 2010–11. We analyze our data using multiple logistic regression to identify significant factors that correlate with chronic absenteeism and leverage the Kitagawa-Blinder-Oaxaca decomposition method to describe how distributional differences in those factors contribute to absenteeism disparities. Results show that internalizing behaviors in students with disabilities and their parents’ health are significantly associated with chronic absenteeism as well as help explain the disparity (12 % and 3 % of the disparity, respectively). Importantly, since differences in internalizing behaviors can be generated, in part, by school practices and policies that treat early elementary students with disabilities inequitably, our work suggests that reducing gaps in early absenteeism may require schools to reduce exposure to experiences that can lead to internalizing problem behaviors in young children with disabilities.

Models estimating decomposition rates of dead wood across space and time are mainly based on studies carried out in temperate zones where microbes are dominant drivers of decomposition. However, most dead wood biomass is found in tropical ecosystems, where termites are also important wood consumers. Given the dependence of microbial decomposition on moisture with termite decomposition thought to be more resilient to dry conditions, the relative importance of these decomposition agents is expected to shift along gradients in precipitation that affect wood moisture. Here, we investigated the relative roles of microbes and termites in wood decomposition across precipitation gradients in space, time and with a simulated drought experiment in tropical Australia. We deployed mesh bags with non-native pine wood blocks, allowing termite access to half the bags. Bags were collected every 6 months (end of wet and dry seasons) over a 4-year period across five sites along a rainfall gradient (ranging from savanna to wet sclerophyll to rainforest) and within a simulated drought experiment at the wettest site. We expected microbial decomposition to proceed faster in wet conditions with greater relative influence of termites in dry conditions. Consistent with expectations, microbial-mediated wood decomposition was slowest in dry savanna sites, dry seasons and simulated drought conditions. Wood blocks discovered by termites decomposed 16–36% faster than blocks undiscovered by termites regardless of precipitation levels. Concurrently, termites were 10 times more likely to discover wood in dry savanna compared with wet rainforest sites, compensating for slow microbial decomposition in savannas. For wood discovered by termites, seasonality and drought did not significantly affect decomposition rates. Taken together, we found that spatial and seasonal variation in precipitation is important in shaping wood decomposition rates as driven by termites and microbes, although these different gradients do not equally impact decomposition agents. As we better understand how climate change will affect precipitation regimes across the tropics, our results can improve predictions of how wood decomposition agents will shift with potential for altering carbon fluxes. Read the free Plain Language Summary for this article on the Journal blog.

To improve the utilization level and energy conversion efficiency of converter flue gas, a novel technology is proposed for the online production of slagging and dephosphorization agent by utilizing the waste heat of converter flue gas. Herein, the effects of Fe‐oxide dust in converter flue gas on the phase composition and microstructure of decomposed product and decomposition degree are investigated by high‐temperature drop tube furnace experiment and thermogravimetric experiment to clarify the influencing mechanism of Fe‐oxide dust on limestone powder decomposition. The results show that Ca2Fe2O5 is formed during limestone decomposition in the flue gas with Fe‐oxide dust, and the increase of Fe‐oxide dust content promotes the decomposition reaction of limestone powder and formation of calcium ferrite. With the Fe‐oxide dust content increasing from 10% to 30%, the decomposition degree increases from 80.1% to 96.2% and the proportion of Ca2Fe2O5 increases from 6.35% to 35.90%. Moreover, FeO in the dust reacts with both CaCO3 and CaO completely to form calcium ferrite with the presence of external oxygen gas in converter flue gas, whereas FeO has no significant effect on the decomposition of CaCO3 in an inert atmosphere and no Ca2Fe2O5 is formed. [ABSTRACT FROM AUTHOR]

The processing of organic matter is a central ecosystem function in freshwater ecosystems that allows the integration of terrestrial plant material into aquatic heterotrophic food webs. From an energetic perspective, many temperate aquatic systems fundamentally depend on such allochthonous inputs. Current research established that this central ecosystem function may be linked to population density of few yet dominant invertebrate detritivores, showing a negative density‐dependent relationship. Here, we extended the current knowledge and experimentally assessed the processing of leaf litter by freshwater amphipods, using broad density gradients, interspecific competition, and laboratory and field experiments. We used two species of dominant amphipods, namely the native Gammarus fossarum and the non‐native Gammarus roeselii, varying their density by two orders of magnitude, both in single‐species and two‐species treatments. Results from 252 mesocosms in the lab and 97 mesocosms in a natural stream show that per capita leaf litter processing rates are strongly negatively dependant on population density in monocultures. Interspecific competition in two‐species treatments corroborated the negative density‐dependent ecosystem function and highlighted the functional redundancy of the two detritivore species. We identified a flattening in the processing rates at previously unreported but well‐defined breakpoints. These breakpoints may reflect minimal metabolic requirements at which survival takes precedence over any other process, such as interference competition. The breakpoints were consistent across both species, indicating that they must process leaf litter equalling one fifth to one fourth of their dry body weight per day as a minimal nutritional threshold. Our results suggest the need for integrating nonlinear density‐dependencies and breakpoint population densities in key ecosystem functions in aquatic ecosystem modelling alongside classical biodiversity–ecosystem functioning relationships. Depending on the population density the corresponding ecosystem functioning could differ significantly. This corroborates the need to better understand biodiversity–abundance relationships when protecting aquatic ecosystems. [ABSTRACT FROM AUTHOR]

Summary Resource storage is a critical component of plant life history. While the storage of nonstructural carbohydrates in wood has been studied extensively, the multiple functions of mineral nutrient storage have received much less attention. Here, we highlight the size of wood nutrient pools, a primary determinant of whole‐plant nutrient use efficiency, and a substantial fraction of ecosystem nutrient budgets, particularly tropical forests. Wood nutrient concentrations also show exceptional interspecific variation, even among co‐occurring plant species, yet how they align with other plant functional traits and fit into existing trait economic spectra is unclear. We review the chemical forms and location of nutrient pools in bark and sapwood, and the evidence that nutrient remobilization from sapwood is associated with mast reproduction, seasonal leaf flush, and the capacity to resprout following damage. We also emphasize the role wood nutrients are likely to play in determining decomposition rates. Given the magnitude of wood nutrient stocks, and the importance of tissue stoichiometry to forest productivity, a key unresolved question is whether investment in wood nutrients is a relatively fixed trait, or conversely whether under global change plants will adjust nutrient allocation to wood depending on carbon gain and nutrient supply. [ABSTRACT FROM AUTHOR]

Compost Me: A More-Than-Humanifesto speaks to my desire to be composted, exploring what human composting is and how the process works, in addition to what human composting can teach us about being and becoming more-than-human. As part of this more-than-humanifesto, I advocate for an extended sense of self – one that mixes and mingles with other beings and bodies – to compost discourses that present humans as separate from, and superior to, the ecologies in which they are intimately a part. [ABSTRACT FROM AUTHOR]

This paper proposes a multi‐objective evolutionary algorithm based on bilayered decomposition (MOEA/BLD) for solving constrained multi‐objective optimization problems. MOEA/D is an effective method for solving unconstrained multi‐objective optimization problems. It decomposes the objective space using weight vectors and simultaneously searches for solutions for the subproblems. However, real‐world applications impose many constraints, and these constraints must be handled appropriately when searching for good feasible solutions. The proposed MOEA/BLD treats such constraints as an additional objective function. Furthermore, in addition to the conventional weight vector, an augmented weight vector is introduced that decomposes the objective space and constraint violation space hierarchically. In the first stage, the objective space is decomposed by conventional weight vectors. In the next stage, the bi‐objective space consisting of the scalarizing function and constraint violation is decomposed by augmented weight vectors. The augmented weights are adjusted so that they decrease linearly in the search process as the search gradually moves from infeasible regions to feasible regions. The proposed algorithm is compared to several state‐of‐the‐art constrained MOEA/Ds using multi‐ and many‐objective problems. The results show that the proposed method outperforms existing methods, in terms of search performance, under various conditions. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Deadwood is a key component of nutrient cycling in natural tropical forests, serving as a globally important carbon storage and habitat for a high number of species. The conversion of tropical forests to agriculture modifies deadwood pools, but we know little about deadwood dynamics in forests recovering from human disturbance. Here we quantified the volume and diversity of coarse woody debris (CWD, ≥ 7 cm diameter) and the mass of fine woody debris (FWD, < 7 cm) along a chronosequence of natural forest recovery in the lowlands of the Ecuadorian Chocó region. We sampled forest plots ranging from 1–37 years of recovery post-cessation of agricultural use as either cacao plantation or cattle pasture, as well as actively managed cacao plantations and cattle pastures, and old-growth forests. In contrast to our expectation, we found no significant increase in deadwood volume with recovery time. The diversity in size, decay stage and type of CWD increased along the recovery gradient, with no effect of previous land use type. The mass of FWD increased overall across the recovery gradient, but these results were driven by a steep increase in former pastures, with no change observed in former cacao plantations. We suggest that the range of sizes and decomposition stages of deadwood found in these two major tropical agricultural systems could provide suitable resources for saproxylic organisms and an overlooked carbon storage outside old-growth forests. Our estimates of deadwood in agricultural systems and recovering forests can help improve global assessments of carbon storage and release in the tropics. [ABSTRACT FROM AUTHOR]

The decomposition of carcasses by scavengers and microbial decomposers is an important component of the biochemical cycle that can strongly alter the chemical composition of soils locally. Different scavenger guilds are assumed to have a different influence on the chemical elements that leak into the soil, although this assumption has not been empirically tested. Here, we experimentally determine how different guilds of vertebrate scavengers influence local nutrient dynamics. We performed a field experiment in which we systematically excluded different subsets of vertebrate scavengers from decomposing carcasses of fallow deer (Dama dama), and compared elemental concentrations in the soil beneath and in the vegetation next to the carcasses over time throughout the decomposition process. We used four exclusion treatments: excluding (1) no scavengers, thus allowing them all; (2) wild boar (Sus scrofa); (3) all mammals; and (4) all mammals and birds. We found that fluxes of several elements into the soil showed distinct peaks when all vertebrates were excluded. Especially, trace elements (Cu and Zn) seemed to be influenced by carcass decomposition. However, we found no differences in fluxes between partial exclusion treatments. Thus, vertebrate scavengers indeed reduce leakage of elements from carcasses into the soil, hence influencing local biochemical cycles, but did so independent of which vertebrate scavenger guild had access. Our results suggest that carcass-derived elements are dispersed over larger areas rather than locally leak into the soil when vertebrate scavengers dominate the decomposition process. [ABSTRACT FROM AUTHOR]

Lignocellulose is a major component of vascular plant biomass. Its decomposition is crucial for the terrestrial carbon cycle. Microorganisms are considered primary decomposers, but evidence increases that some invertebrates may also decompose lignocellulose. We investigated the taxonomic distribution and evolutionary origins of GH45 hydrolases, important enzymes for the decomposition of cellulose and hemicellulose, in a collection of soil invertebrate genomes. We found that these genes are common in springtails and oribatid mites. Phylogenetic analysis revealed that cellulase genes were acquired early in the evolutionary history of these groups. Domain architectures and predicted 3D enzyme structures indicate that these cellulases are functional. Patterns of presence and absence of these genes across different lineages prompt further investigation into their evolutionary and ecological benefits. The ubiquity of cellulase genes suggests that soil invertebrates may play a role in lignocellulose decomposition, independently or in synergy with microorganisms. Understanding the ecological and evolutionary implications might be crucial for understanding soil food webs and the carbon cycle. [ABSTRACT FROM AUTHOR]

With increasing urbanization and the demand for efficient, flexible transportation solutions, demand-responsive transportation services (DTRS) has emerged as a viable alternative to traditional public transit. However, determining the optimal fleet size to balance the investment and operational revenue remains a significant challenge for service providers. In this article, we address the optimization of fleet size in point-to-point shared demand DRTS, which widely operates within many cities. To capture the uncertain passenger demands in the future when planning the fleet size currently, we model this problem with a framework of two-stage stochastic programming with recourse. Fleet sizing decisions are made in the first stage before the uncertain demands are revealed. After the uncertainty is revealed, the second stage involves making additional decisions to maximize operational revenue. The objective is to optimize the total revenue of the first-stage decisions and the expected revenue of the recourse actions. To solve this practical problem, we resort to the Model Predictive Control method (MPC) and propose a network decomposition approach that first converts the transportation network to a nodal tree structure and then develops a Nodal Tree Recourse with Dependent Arc Capacities (NTRDAC) algorithm to obtain the exact value of the expected recourse functions. In the experiments, NTRDAC is able to produce results within seconds for transportation networks with over 30 nodes. In contrast, a commercial solver is only capable of solving networks with up to five nodes. The stability tests show that NTRDAC remains robust as the problem size varies. Lastly, the value of the stochastic solution (VSS) was evaluated, and the results indicate that it consistently outperforms the expected value solutions. Numerical experiments show that the performance of the NTRDAC algorithm is quite encouraging and fit for large-scale practical problems. [ABSTRACT FROM AUTHOR]

Accurate full‐parameter construction of the Jones matrix is of great significance for encoding multiple functions in a single metasurface. Supercells composed of several elements are used for this purpose through coherent superposition. But all the elements in the reported studies should be lossless with near‐unity transmission, which limits the material system and restricts the Jones matrix construction in a unitary manner. Here a non‐unitary matrix decomposition method is proposed to build the supercell using a pair of 0°‐oriented rods and a pair of 45°‐oriented rods for on‐demand design of arbitrary symmetric Jones matrices. This method is applicable for lossy metasurfaces and offers straightforward physical guidance for structure design without optimization. The accuracy of the on‐demand Jones matrix generation is demonstrated by several 3D‐printed alumina metalenses with 3‐, 4‐, and 6‐channel polarization‐multiplexed focusing. The study opens a new pathway for non‐silicon meta‐optics and holds great potential for dynamic or switchable applications. [ABSTRACT FROM AUTHOR]

Since the mid‐twentieth century, the Global South has experienced unprecedently rapid and pervasive changes in reproductive behavior with fertility declining from high pre‐transitional levels to below 3 births per woman in most low‐ and middle‐income countries (LMICs). Over time a rough consensus has been reached on major theories about the causes of these declines. However, a controversy remains about the widely held view that changing reproductive preferences (i.e., declining desired family size and rising demand for birth limitation) are the dominant drivers of fertility transitions. Several studies question this conclusion and suggest instead that the rising implementation of existing demand is the main cause of the reproductive revolution in LMICs. The objective of this study is to reconcile the competing “demand” and “implementation” perspectives. This paper assesses the strengths and weaknesses of published decompositions which take trends in the observed total fertility and contraceptive prevalence and break them down into their respective demand and implementation components. The main conclusion from this exercise is that fertility transitions are driven by changes in both preferences and their implementation. Claims of a completely dominant role for either demand or implementation are based on flawed methods and hence must be rejected. [ABSTRACT FROM AUTHOR]

Increased temperatures are altering rates of organic matter (OM) breakdown in stream ecosystems with implications for carbon (C) cycling in the face of global change. The metabolic theory of ecology (MTE) provides a framework for predicting temperature effects on OM breakdown, but differences in the temperature dependence of breakdown driven by different organismal groups (i.e., microorganisms vs. invertebrate detritivores) and litter species remain unresolved. Over two years, we conducted 12 60‐day leaf litterbag incubations in 20 headwater streams in the southern Appalachian Mountains (USA). We compared temperature dependence (as activation energy, Ea) between microbial and detritivore‐mediated breakdown, and between a highly recalcitrant (Rhododendron maximum) and a relatively labile (Acer rubrum) leaf species. Detritivore‐mediated breakdown had a higher Ea than microbial breakdown for both leaf species (Rhododendron: 1.48 > 0.56 eV; Acer: 0.97 > 0.29 eV), and Rhododendron breakdown had a higher Ea than Acer breakdown for both organismal groups. Similarly, the Ea of total (coarse‐mesh) Rhododendron breakdown was higher than the Ea of total Acer breakdown (0.89 > 0.52 eV). These effects for total breakdown were large, implying that the number of days to 95% mass loss would decline by 40% for Rhododendron and 26% for Acer between 12°C (our mean temperature value) and 16°C (+4°C, reflecting projected increases in global surface temperature due to climate change). Despite patterns in Ea, overall breakdown rates were higher for microbes than detritivores, and for Acer than Rhododendron over most of our temperature gradient. Additionally, the Ea for a subset of the microbial breakdown data declined from 0.40 to 0.22 eV when fungal biomass was included as a model predictor, highlighting the key role of fungi in determining the temperature dependence of litter breakdown. Our results imply that, as streams warm, routing of leaf litter C to detritivore‐mediated fates will increase faster than predicted by previous studies and MTE, especially for labile litter. As temperatures rise, earlier depletion of autumn‐shed, labile leaf litter combined with rapid breakdown rates of recalcitrant litter could exacerbate seasonal resource limitation and alter carbon storage and transport dynamics in temperate headwater stream networks. [ABSTRACT FROM AUTHOR]

Background: Wearable sensors have revolutionized cardiac health monitoring, with Seismocardiography (SCG) at the forefront due to its non-invasive nature. However, the substantial motion artefacts have hindered the translation of SCG-based medical applications, primarily induced by walking. In contrast, our innovative technique, Adaptive Bidirectional Filtering (ABF), surpasses these challenges by refining SCG signals more effectively than any motion-induced noise. ABF leverages a noise-cancellation algorithm, operating on the benefits of the Redundant Multi-Scale Wavelet Decomposition (RMWD) and the bidirectional filtering framework, to achieve optimal signal quality. Methodology: The ABF technique is a two-stage process that diminishes the artefacts emanating from motion. The first step by RMWD is the identification of the heart-associated signals and the isolating samples with those related frequencies. Subsequently, the adaptive bidirectional filter operates in two dimensions: it uses Time-Frequency masking that eliminates temporal noise while engaging in non-negative matrix Decomposition to ensure spatial correlation and dorsoventral vibration reduction jointly. The main component that is altered from the other filters is the recursive structure that changes to the motion-adapted filter, which uses vertical axis accelerometer data to differentiate better between accurate SCG signals and motion artefacts. Outcome: Our empirical tests demonstrate exceptional signal improvement with the application of our ABF approach. The accuracy in heart rate estimation reached an impressive r-squared value of 0.95 at − 20 dB SNR, significantly outperforming the baseline value, which ranged from 0.1 to 0.85. The effectiveness of the motion-artifact-reduction methodology is also notable at an SNR of − 22 dB. Consequently, ECG inputs are not required. This method can be seamlessly integrated into noisy environments, enhancing ECG filtering, automatic beat detection, and rhythm interpretation processes, even in highly variable conditions. The ABF method effectively filters out up to 97% of motion-related noise components within the SCG signal from implantable devices. This advancement is poised to become an integral part of routine patient monitoring. [ABSTRACT FROM AUTHOR]

Leaf litter in coastal wetlands lays the foundation for carbon storage, and the creation of coastal wetland soils. As climate change alters the biogeochemical conditions and macrophyte composition of coastal wetlands, a better understanding of the interactions between microbial communities, changing chemistry, and leaf litter is required to understand the dynamics of coastal litter breakdown in changing wetlands. Coastal wetlands are dynamic systems with shifting biogeochemical conditions, with both tidal and seasonal redox fluctuations, and marine subsidies to inland habitats. Here, we investigated gene expression associated with various microbial redox pathways to understand how changing conditions are affecting the benthic microbial communities responsible for litter breakdown in coastal wetlands. We performed a reciprocal transplant of leaf litter from four distinct plant species along freshwater‐to‐marine gradients in the Florida Coastal Everglades, tracking changes in environmental and litter biogeochemistry, as well as benthic microbial gene expression associated with varying redox conditions, carbon degradation, and phosphorus acquisition. Early litter breakdown varied primarily by species, with highest breakdown in coastal species, regardless of the site they were at during breakdown, while microbial gene expression showed a strong seasonal relationship between sulfate cycling and salinity, and was not correlated with breakdown rates. The effect of salinity is likely a combination of direct effects, and indirect effects from associated marine subsidies. We found a positive correlation between sulfate uptake and salinity during January with higher freshwater inputs to coastal areas. However, we found a peak of dissimilatory sulfate reduction at intermediate salinity during April when freshwater inputs to coastal sites are lower. The combination of these two results suggests that sulfate acquisition is limiting to microbes when freshwater inputs are high, but that when marine influence increases and sulfate becomes more available, dissimilatory sulfate reduction becomes a key microbial process. As marine influence in coastal wetlands increases with climate change, our study suggests that sulfate dynamics will become increasingly important to microbial communities colonizing decomposing leaf litter. [ABSTRACT FROM AUTHOR]

An automorphism u of a vector space is called unipotent of index 2 whenever (u − id) 2 = 0. Let b be a non-degenerate symmetric or skewsymmetric bilinear form on a vector space V over a field F of characteristic different from 2. Here, we characterize the elements of the isometry group of b that are the product of two unipotent isometries of index 2. In particular, if b is skewsymmetric and nondegenerate we prove that an element of the symplectic group of b is the product of two unipotent isometries of index 2 if and only if it has no Jordan cell of odd size for the eigenvalue −1. As an application, we prove that every element of a symplectic group is the product of three unipotent elements of index 2 (and no fewer in general). For orthogonal groups, the classification closely matches the classification of sums of two square-zero skewselfadjoint operators that was obtained in a recent article [7]. [ABSTRACT FROM AUTHOR]

The traditional model of factor-driven economic growth can no longer be maintained due to an increasing demand to save energy and reduce emissions and a rapid rise in the cost of related factors. The concept of green total factor productivity (GTFP) has emerged as an essential component of high-quality economic growth; consequently, how to boost GTFP through the development of technical advancement has become an important question in recent years. An improved CES production function of labor, capital, and energy is created using the theoretical framework for biased technological growth as its foundation. Subsequently, the mechanisms resulting from the synergy of factor structure, factor efficiency and biased technological progress (BTP) on GTFP are theoretically deduced and empirically analyzed. The conclusion shows that the types of technical advancement are mainly net labor-enhancing and net energy-enhancing technical advancement in China from 2001 to 2017. Due to the biased effect of technical advancement, the relative comparison of the three elements is determined predominantly by excessive capital investment and less by labor and energy. Factor-enhancing technical advancement led to the growth of GTFP, while the synergistic effect of BTP, factor structure and factor efficiency hindered the growth of GTFP. [ABSTRACT FROM AUTHOR]

Time series data, characterized by large volumes and wide-ranging applications, requires accurate predictions of future values based on historical data. Recent advancements in deep learning models, particularly in the field of time series forecasting, have shown promising results by leveraging neural networks to capture complex patterns and dependencies. However, existing models often overlook the influence of short-term cyclical patterns in the time series, leading to a lag in capturing changes and accurately tracking fluctuations in forecast data. To overcome this limitation, this paper introduces a new method that utilizes an interpolation technique to create a fine-scaled representation of the cyclical pattern, thereby alleviating the impact of the irregularity in the cyclical component and hence enhancing prediction accuracy. The proposed method is presented along with evaluation metrics and loss functions suitable for time series forecasting. Experiment results on benchmark datasets demonstrate the effectiveness of the proposed approach in effectively capturing cyclical patterns and improving prediction accuracy. [ABSTRACT FROM AUTHOR]

Taking account, of the increasing environmental awareness, this study explores the potential of liquid residues from Furcraea sp. for the development of eco-friendly detergents, responding to the demand for sustainable household cleaning products. The research focused on stabilizing and characterizing these residues for bio-based detergent formulation, examining the effects of heat treatment on saponin and vitamin E levels, as well as product shelf life. The cleaning efficiency of the resulting bio-based detergent was assessed and compared with that of conventional synthetic detergents. Findings reveal that processing methods preserved the concentrations of saponin (1034—1148 mg/L) and vitamin E (11.9—11.7 mg/L), maintaining the essential surfactant properties. The bio-based detergent demonstrated an acceptable shelf life and efficiency comparable to commercial synthetic detergents, indicating the potential of utilizing liquid waste and residues as feedstock for cleaning product production. Furthermore, the decomposition of liquid residues released numerous volatile compounds into the environment, including previously unidentified volatile surfactants specific to Furcraea sp., along with various other compounds such as alcohols, esters, aldehydes, ketones, terpenoids, and fatty acids. [ABSTRACT FROM AUTHOR]

Accurate wind speed prediction is of essential importance for the stability and safe operation of power systems. Given the complexity of wind speed sequence, this paper proposed a new two-stage decomposition and integrated hybrid model to improve the accuracy of wind speed prediction. A two-stage decomposition method combining robust local mean decomposition (RLMD), sample entropy (SE) and variational modal decomposition (VMD) was used to decompose the wind speed signal in the data preprocessing stage. Firstly, the wind speed signal was decomposed into various components by RLMD, and the complexity of each component was calculated using the SE to classify them into random, detail component and trend component. Then, a secondary decomposition of the random component with the highest SE was performed using the VMD. In the prediction stage, two different prediction models were used for prediction depending on the smoothness of each component. Stochastic configuration networks (SCN) was used to predict the detail and trend components with relatively smoothness. Echo state network (ESN) was used to predict the components of the secondary decomposition. Finally, the actual wind speed data were compared by different prediction models, which illustrated that the prediction method proposed in this paper had good prediction accuracy and generalizability. [ABSTRACT FROM AUTHOR]

Background: Since the outbreak of the COVID-19 pandemic, the excess mortality P-score has gained prominence as a measure of pandemic burden. The P-score indicates the percentage by which observed deaths deviate from expected deaths. As the P-score is regularly used to compare excess mortality between countries, questions arise regarding the age dependency of the measure. In this paper we present formal and empirical results on the population structure bias of the P-score with a special focus on cross-country comparisons during the COVID-19 pandemic in Europe. Methods: P-scores were calculated for European countries for 2021, 2022, and 2023 using data from the 2024 revision of the United Nations' World Population Prospects and the HMDs Short Term Mortality Fluctuations data series. The expected deaths for 2021, 2022, and 2023 were estimated using a Lee–Carter forecast model assuming pre-pandemic conditions. P-score differences between countries were decomposed using a Kitagawa-type decomposition into excess-mortality and structural components. To investigate the sensitivity of P-score cross-country rankings to differences in population structure we calculated the rank-correlation between age-standardized and classical P-scores. Results: The P-score is an average of age-specific percent excess deaths weighted by the age-distribution of expected deaths. It can be shown that the effect of differences in the distribution of deaths only plays a marginal role in a European comparison. In most cases, the excess mortality effect is the dominant effect. P-score rankings among European countries during the COVID-19 pandemic are similar under both age-standardized and classical P-scores. Conclusions: Although the P-score formally depends on the age-distribution of expected deaths, this structural component only plays a minor role in a European comparison, as the distribution of deaths across the continent is similar. Thus, the P-score is suitable as a measure of excess mortality in a European comparison, as it mainly reflects the differences in excess mortality. However, this finding should not be extrapolated to global comparisons, where countries could have very different death distributions. In situations were P-score comparisons are biased age-standardization can be applied as a solution. [ABSTRACT FROM AUTHOR]

Experiments on methylamine (CH3NH2${\rm CH}_3{\rm NH}_2$) decomposition in shock tubes, flow reactors, and batch reactors have been re‐examined to improve the understanding of hydrocarbon/amine interactions and constrain rate constants for CHx${\rm CH}_{ x}$ + NHy${\rm NH}_{ y}$ reactions. In high‐temperature shock tube experiments, the rapid thermal dissociation of CH3NH2${\rm CH}_3{\rm NH}_2$ provides a fairly clean source of CH3${\rm CH}_3$ and NH2${\rm NH}_2$ radicals, allowing an assessment of reactions of CH3${\rm CH}_3$ with NH2${\rm NH}_2$ and NH. At the lower temperatures in batch and flow reactors, CH3NH2${\rm CH}_3{\rm NH}_2$ is mostly consumed by reaction with H to form CH2NH2${\rm CH}_2{\rm NH}_2$ + H2${\rm H}_2$; these results are useful in determining the fate of the CH2NH2${\rm CH}_2{\rm NH}_2$ radical. Interpretation of these data, along with flow reactor data for the CH3NH2${\rm CH}_3{\rm NH}_2$/H system at lower temperature, indicates that at temperatures up to about 1400 K at atmospheric pressure and above 2000 K at 100 atm, the CH3${\rm CH}_3$ + NH2${\rm NH}_2$ reaction forms mainly methylamine. At sufficiently high temperature, H‐abstraction to form CH4${\rm CH}_4$ + NH and addition–elimination to form CH2NH2${\rm CH}_2{\rm NH}_2$ + H become competitive. The CH3${\rm CH}_3$ + NH reaction, with a rate constant close to collision frequency, forms CH2NH${\rm CH}_2{\rm NH}$ + H, also leading into the hydrocarbon amine pool. Thus, methylamine can be expected to be an important intermediate in co‐combustion of natural gas and ammonia, and more work on the chemistry of CH3NH2${\rm CH}_3{\rm NH}_2$ is desirable. [ABSTRACT FROM AUTHOR]

Accurately predicting the deviation factor (Z-factor) of natural gas is crucial for the estimation of natural gas reserves, evaluation of gas reservoir recovery, and assessment of natural gas transport in pipelines. Traditional machine learning algorithms, such as Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Artificial Neural Network (ANN) and Bidirectional Long Short-Term Memory Neural Networks (BiLSTM), often lack accuracy and robustness in various situations due to their inability to generalize across different gas components and temperature-pressure conditions. To address this limitation, we propose a novel and efficient machine learning framework for predicting natural gas Z-factor. Our approach first utilizes a signal decomposition algorithm like Variational Mode Decomposition (VMD), Empirical Fourier Decomposition (EFD) and Ensemble Empirical Mode Decomposition (EEMD) to decouple the Z-factor into multiple components. Subsequently, traditional machine learning algorithms is employed to predict each decomposed Z-factor component, where combination of SVM and VMD achieved the best performance. Decoupling the Z-factors firstly and then predicting the decoupled components can significantly improve prediction accuracy of all traditional machine learning algorithms. We thoroughly evaluate the impact of the decoupling method and the number of decomposed components on the model's performance. Compared to traditional machine learning models without decomposition, our framework achieves an average correlation coefficient exceeding 0.99 and an average mean absolute percentage error below 0.83% on 10 datasets with different natural gas components, high temperatures, and pressures. These results indicate that hybrid model effectively learns the patterns of Z-factor variations and can be applied to the prediction of natural gas Z-factors under various conditions. This study significantly advances methodologies for predicting natural gas properties, offering a unified and robust solution for precise estimations, thereby benefiting the natural gas industry in resource estimation and reservoir management. [ABSTRACT FROM AUTHOR]

Citric acid is widely used in the Food and Pharmaceutical Industry. Various issues regarding its thermal behavior and infrared spectrum require clarification. Here, we studied citric acid monohydrate (raw, heated, freeze-dried and recrystallized from D2O) via Differential Scanning Calorimetry, Thermogravimetric Analysis, Infrared Spectroscopy, and antioxidant capacity assay. Also, we used ab initio Density Functional Theory calculations for further supporting the interpretations of the experimental results. Citric acid monohydrate exhibits desolvation inability and upon heating does not dehydrate but esterifies. Nor by freeze drying can it be dehydrated. The heated sample is not anhydrous, it exhibits melting inability, and any fluidization occurs simultaneously with decomposition. In other words, the interpretations regarding the two endothermic peaks in the DSC curve of citric acid that have been attributed to water evaporation and melting are not correct. The increase in the molecular weight due to esterification is most likely responsible for the increased antioxidant/chelation capacity of the heated sample. We concluded that what we call citric acid monohydrate and anhydrous do not exist in a pure form (in the solid state) and actually are mixtures of different compositions of citric acid, water and a citric acid oligomer that is produced through esterification. The esterification reaction seems to be able to proceed easily under mild heating or even at room temperature. The presence of the ester oligomer and water affect the infrared spectrum of citric acid monohydrate and anhydrous and is responsible for the existence of multiple peaks in the C=O stretching region, which partially overlaps with the water H-O-H bending vibration. The insights presented in this work could be useful for optimizing the design, performance and quality of food and drug products in which citric acid is used. [ABSTRACT FROM AUTHOR]

Heart weight is a routine measurement at post-mortem examination. An increased heart weight is associated with pre-existing heart disease and sudden cardiac death. However, during decomposition, the heart weight measured at post-mortem examination may not reflect the weight at the time of death. A previous study showed that heart dimensions can be used to estimate heart weight. This study documents the changes in heart dimensions during decomposition using porcine and ovine animal models. It shows that, in contrast to heart weight, which decreases in the post-mortem interval, the heart dimensions increase. Heart width increases and subsequently plateaus at the end of the 18 days to a mean of 6 and 8 mm in ovine and porcine hearts, whereas the length continues to increase. Using the results of this study, in conjunction with previous published literature, the heart width may be used as a parameter to estimate heart weight and determine cardiac hypertrophy at the time of death in decomposed hearts. [ABSTRACT FROM AUTHOR]

Let Kn denote a complete graph on n vertices and Sk denote a complete bipartite graph K1,k. A Bowtie Bl is a graph formed by the union of two cycles Cn and Cm intersecting at a common vertex. A decomposition of a graph G is a collection of edge-disjoint subgraphs H, such that every edge of G belongs to exactly one H. Given non-isomorphic subgraphs H1 and H2 of G, a (H1,H2) — multi-decomposition of G is the decomposition of G into a copies of H1 and b copies of H2, such that aH1 ⊕ bH2 = G, for some integers a,b ≥ 0. In this paper, the multi-decomposition of Kn into Sk and Bl has been investigated and obtained a necessary and sufficient condition when k = l = 6. It is proved that for a given positive integer n, Kn can be decomposed into a copies of S6 and b copies of B6 for some pair of non-negative integers (a,b) if and only if 6(a + b) = n 2, for all n ≥ 9. [ABSTRACT FROM AUTHOR]

Terrestrial plants form primarily mutualistic symbiosis with mycorrhizal fungi based on a compatible exchange of solutes between plant and fungal partners. A key attribute of this symbiosis is the acquisition of soil nutrients by the fungus for the benefit of the plant in exchange for a carbon supply to the fungus. The interaction can range from mutualistic to parasitic depending on environmental and physiological contexts. This review considers current knowledge of the functionality of ectomycorrhizal (EM) symbiosis in the mobilisation and acquisition of soil nitrogen (N) in northern hemisphere forest ecosystems, highlighting the functional diversity of the fungi and the variation of symbiotic benefits, including the dynamics of N transfer to the plant. It provides an overview of recent advances in understanding 'mycorrhizal decomposition' for N release from organic or mineral-organic forms. Additionally, it emphasises the taxon-specific traits of EM fungi in soil N uptake. While the effects of EM communities on tree N are likely consistent across different communities regardless of species composition, the sink activities of various fungal taxa for tree carbon and N resources drive the dynamic continuum of mutualistic interactions. We posit that ectomycorrhizas contribute in a species-specific but complementary manner to benefit tree N nutrition. Therefore, alterations in diversity may impact fungal-plant resource exchange and, ultimately, the role of ectomycorrhizas in tree N nutrition. Understanding the dynamics of EM functions along the mutualism-parasitism continuum in forest ecosystems is essential for the effective management of ecosystem restoration and resilience amidst climate change. Key points: • Mycorrhizal symbiosis spans a continuum from invested to appropriated benefits. • Ectomycorrhizal fungal communities exhibit a high functional diversity. • Tree nitrogen nutrition benefits from the diversity of ectomycorrhizal fungi. [ABSTRACT FROM AUTHOR]

Vertebrate scavengers represent important taphonomic agents that can act on a body, particularly when in an outdoor environment. Understanding the effects of these agents will direct how and where to search for human remains and influence the likelihood of discovery in a particular region. The current study aimed to identify the taphonomic impact of scavenger guilds in the peri‐urban and rural regions of southeastern British Columbia. Vertebrate scavenger activity on pig carcasses was recorded remotely using trail cameras and analyzed to determine temporal scavenging profiles. Both the peri‐urban and rural environments produced comparable scavenger guilds, namely: turkey vultures, American crows/northern ravens (classified as “corvids”), American black bears, and coyotes. Although the two locations had different study lengths due to variable degrees of scavenging, for the period that was common to both locations (summer to early fall), the black bear was the most frequent scavenger followed by coyote. However, the dispersal of remains by the mammalian scavengers was distinctly different between sites. Only 12%–33% of skeletal elements were recovered at the rural sites compared to 80%–90% recovered at the peri‐urban sites, even though the latter sites had a longer study timeframe. The extended timeframe of the peri‐urban sites confirmed that certain scavengers (e.g., turkey vultures and black bears) are only seasonally active in this region. These findings demonstrate the variability of scavenger behavior and the need to assign caution and local ecological knowledge when predicting scavenger trends. Such taphonomic information is relevant for human remains searches in regions with comparable scavenger guilds. [ABSTRACT FROM AUTHOR]

Fungal traits can provide a mechanistic understanding of how wood‐inhabiting fungi interact with their environment and how that influences community assembly in deadwood. However, fungal trait exploration is relatively new and almost no studies measure fungal traits in their environment.In this study we tested species‐ and trait‐environment relationships in reproducing fungal communities inhabiting 571 Norway spruce (Picea abies) logs in 55 isolated forest patches (0.1–9.9 ha) of different naturalness types, located in Northern boreal Sweden. The studied patches were (1) semi‐natural set‐aside patches within highly managed landscapes, or (2) old‐growth natural patches located in an unmanaged landscape. We tested species and trait relationships to deadwood substrate and forest patch variables. We measured mean fruit body size and density for each of the 19 species within communities.Traits assembled in relation to log decay stage and forest patch naturalness, illustrating the important role of deterministic environmental filtering in shaping reproducing wood‐inhabiting fungal communities. Early decay stage communities had larger, less dense, annual fruiting bodies of half‐resupinate type and were more often white‐rot fungi. Species rich mid‐decay stage communities had mixed trait assemblages with more long lived perennial fruit bodies of intermediate size, and both brown‐ and white‐rot fungi equally represented. Finally, late decay stage communities had smaller, denser and perennial fruit bodies, more often of the brown‐rot type.The relationships between the studied traits and decay stages were similar in both set‐aside and natural patches. However, set‐aside semi‐natural patches in highly managed landscapes more frequently supported species with smaller, perennial and resupinate fruit bodies compared to natural patches in an unmanaged landscape.Synthesis. We found that log decay stage was the primary driver of fungal community assembly of species and traits in isolated forest patches. Our results suggest that decay stage filters four reproduction traits (fruit body density, size, lifespan and type) and one resource‐use trait (white or brown rot). Our results highlights, for the first time, that communities with diverse fungal reproductive traits are maintained foremost across all deadwood decay stages under different forest naturalness conditions. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Introduction The lack of scale-dependent information related to soil properties has largely led to limitations in agriculture, hydrology, climate, ecology, and environmental studies. In this regard, the study aims to analyze the scaledependent changes in estimating the spatial distribution of soil pH and salinity in Tabriz. The proposed method applies the decomposition approach to increase the accuracy of soil properties spatial distribution estimation which includes creating a relationship between soil salinity and pH with the sub-series of input variables from the decomposition method, construction of a relationship between soil salinity and pH sub-series with sub-series of input variables and finally, using a data reduction approach for the effective sub-series determination from decomposition. Materials and Methods The sampling points of the study are related to Tabriz City in East Azerbaijan province. 60 and 38 samples were collected from zero to 20 cm depth for soil pH and salinity monitoring, respectively. Changes in soil properties are evident from one region to another. The cyclical behavior of soil properties is called periodicity. Previous studies in the spatial changes description have mainly focused on the spatial similarities obtained between properties in a region, in which the change of spatial arrangement-spatial dependence or periodicity of soil properties has not been regarded. Spectral analysis can measure the periodicity in spatial changes by approximating a series of spatial data with the sum of sine and cosine functions. The purpose of discrete wavelet transformation is to decompose the signal into the sub-series to obtain a comprehensive input signal analysis. Discrete wavelet transform is used to calculate approximation coefficients in a signal. Maximum overlap discrete wavelet transform (MODWT) is similar to discrete wavelet transform in which low and high pass filters are applied to the input signal at each level. However, the elimination of coefficients is not done by MODWT. Principle component analysis (PCA) was used as the reduction method to find the effective sub-series of decomposition. Results and Discussion In this study, 48 and 12 points were used in soil pH modeling, and 30 and eight points were used in soil salinity modeling in the calibration and validation periods, respectively. Longitude, latitude, height above sea level, slope, and slope aspect were considered as the spatial variables, and the longitude, latitude, and height of sampling points were recorded by GPS, but the slope and slope aspect of sampling points were taken from the production maps of slope and direction. They were extracted from the digital elevation model (DEM) map. The changes in accuracy measurement indices show the variation in the estimated soil salinity and pH against different inputs of the support vector regression (SVR) model. In the case of salinity, analyzing only the aspect of slope has been able to increase the accuracy of the measurement indices, the reduction rate of RMSE, RRMSE, and Var from the previous optimal state without decomposition to decomposition state is three, four, and 20%, respectively, and the rate of the residual predictive deviation (RPD) increase is equal to four percent. Based on the values of the accuracy measurement indices, PCA can increase the accuracy of the estimated values. The box plot of data related to the use of principal component analysis has become closer to the box plot of the observation data compared to the case where only the decomposition method was used. This problem shows the increase in accuracy with a combination of the MODWT spectral approach and the PCA data reduction method. Conclusion In recent years, there has been an increasing demand for soil spatial distribution information in environmental decision-making and land use management. One of the issues that can affect the accuracy of spatial modeling of soil properties is the spatial information increase of input variables to the model. Modeling sub-series of input variables with sub-series of soil properties and finally the sum of estimated sub-series of soil properties could not increase the accuracy of estimated values. Series decomposition could increase the accuracy of estimates. The factors that can affect the accuracy of the proposed method for determining the spatial changes of soil properties include the type of input variables, the type of used model in the modeling process, the use of the appropriate method in spectral analysis, and determining the effective factors in the decomposition method. Therefore, the combination of spectral analysis and artificial intelligence as an effective option can increase the accuracy of the spatial distribution of soil properties. [ABSTRACT FROM AUTHOR]

The improper treatment of crop straw not only leads to resource wastage but also adversely impacts the ecological environment. However, the application of microorganisms can accelerate the decomposition of crop straw and improve its utilization. In this study, cellulose-degrading microbial strains were isolated from naturally decayed corn straw and screened using Congo red staining, along with assessing variations in carboxymethyl cellulase (CMCase) activity, filter paper enzyme (FPase) activity and β-glucosidase (β-Gase) activity, as well as the degradation rate. The eight strains, namely Neurospora intermedia isolate 29 (A1), Streptomyces isolate FFJC33 (A2), Gibberella moniliformis isolate FKCB-009 (A3), Fusarium fujikuroi isolate EFS3(2) (A4), Fusarium Fujikuroi isolate FZ04 (A5), Lysine bacillus macroides strain LNHL43 (B1), Bacillus subtilis strain MPF30 (B2) and Paenibacilli lautus strain ALEB-P1 (C), were identified and selected for microbial strain consortium design based on their high activities of CMCase, FPase and β-Gase. The fungi, bacteria and actinomycete strains were combined without antagonistic effects on corn straw decomposition. The results showed the A2B2 combination had a significantly higher FPase at 55.44 U/mL and β-Gase at 25.73 U/mL than the other two strain combinations (p < 0.05). Additionally, the degradation rate of this combination was 40.33%, which was considerably higher than that of the other strains/consortia. The strain combination A4B2C also had superior enzyme activity, including CMCase with a value of 35.03 U/mL, FPase with a value of 63.59 U/mL and β-Gase with a value of 26.15 U/mL, which were significantly different to those of the other three strain combinations (p < 0.05). Furthermore, seven single microbial strains with high cellulase activities were selected to construct various microbial consortiums for in situ composting in order to evaluate their potential. Taken as a whole, the results of composting, including temperature, moisture content, pH, E4/E6 value and seed germination index, indicated that the microbial strain consortium consisting of Neurospora intermediate isolate 29, Fusarium fujikuroi isolate EFS3(2), Fusarium fujikuroi isolate FZ04, Lysinibacillus macrolides, Lysinibacillus sphaericus, Bacillus subtilis and Paenibacillus lautus was advantageous for corn straw decomposition and yielded high-quality compost. The screened flora was able to effectively degrade corn straw. This study provides a novel solution for the construction of a microbial consortium for the composting of corn straw. [ABSTRACT FROM AUTHOR]

Dissolved organic matter (DOM) plays a significant role in the nutrient supply, energy flow, and pollutant transportation in the wetland ecosystem. However, little is known about the effect of the decomposition of different organic materials in alpine wetland water on the DOM characteristics. By conducting a 90-day decomposition experiment with the addition of different organic materials (peat soil, yak manure, and plant litter) alone or their combinations into alpine wetland water, we characterized the water DOM using three-dimension excitation-emission matrix spectroscopy. The results showed that the decomposition of organic materials significantly affected the chemical properties, sources, humification degree, and composition of the water DOM. The decomposition increased dissolved organic carbon and dissolved total nitrogen in the water. For most of the water samples, a fluorescence index ranging from 1.4 to 1.7 and a biological index of less than 0.8 may indicate that both autochthonous and allochthonous sources contributed to the water DOM, which may primarily rely on allochthonous sources. UVA (37.55–46.81% of total fluorescent components) and UVC fulvic-like substances (29.91–35.53% of total fluorescent components) dominated the water DOM compositions. Among the treatments, additions of peat soil and yak manure led to the highest and the lowest humification degree of the water DOM, respectively. For the treatment of the combination decomposition of all three organic materials, the yak manure may stimulate microbial activity and facilitate the decomposition of plant litter and peat soil and, therefore, boost the humic-like substances in the water DOM. These findings may help the development of wetland biomass management with the objective of maintaining alpine wetland ecosystem services. [ABSTRACT FROM AUTHOR]

Background To explore temporal trends and determine driving factors of age-related macular degeneration (AMD) burden in older adults aged 60–89 years at global, regional and national levels from 1990 to 2019. Methods Prevalence and years lived with disability (YLDs) were extracted. Joinpoint regression analysis was adopted to calculate average annual percentage change and to identify the year with the most significant changes. Global trends were stratified by sex, age and sociodemographic index, and regional and national trends were explored. Decomposition analysis was conducted to determine what extent the forces of population size, age structure and epidemiologic change driving alterations of AMD burden. Results Globally, prevalence rate slightly increased whereas YLDs rate decreased. The year 2005 marked a turning point where both prevalence and YLDs started to decline. Regionally, Western Sub-Saharan Africa had the highest prevalence and YLDs rates in 2019, with East Asia experiencing the most notable rise in prevalence from 1990 to 2019. Global decomposition revealed that the increased case number was primarily driven by population growth and ageing, and epidemiological change was only detected to lessen but far from offset these impacts. Conclusions Although there was only slight increase or even decrease in prevalence and YLDs rates of AMD in older adults, the case number still nearly doubled, which may be primarily attributed to population growth and ageing, coupled with the emerging growing pattern of prevalence rate from 2015, collectively suggesting a huge challenge in control and management of AMD. [ABSTRACT FROM AUTHOR]

Let C be a set of n axis-aligned cubes of arbitrary sizes in R 3 in general position. Let U : = U (C) be their union, and let κ be the number of vertices on ∂ U ; κ can vary between O(1) and Θ (n 2) . We present a partition of cl (R 3 \ U) into O (κ log 4 n) axis-aligned boxes with pairwise-disjoint interiors that can be computed in O (n log 2 n + κ log 6 n) time if the faces of ∂ U are pre-computed. We also show that a partition of size O (σ log 4 n + κ log 2 n) , where σ is the number of input cubes that appear on ∂ U , can be computed in O (n log 2 n + σ log 8 n + κ log 6 n) time if the faces of ∂ U are pre-computed. The complexity and runtime bounds improve to O (n log n) if all cubes in C are congruent and the faces of ∂ U are pre-computed. Finally, we show that if C is a set of arbitrary axis-aligned boxes in R 3 , then a partition of cl (R 3 \ U) into O (n 3 / 2 + κ) boxes can be computed in time O ((n 3 / 2 + κ) log n) , where κ is, as above, the number of vertices in U (C) , which now can vary between O(1) and Θ (n 3) . [ABSTRACT FROM AUTHOR]

This article introduces a Wasserstein distance‐based distributionally robust optimization model to address the transmission expansion planning considering renewable‐based microgrids (MGs) under the impact of uncertainties. The primary objective of the presented methodology is to devise a robust expansion strategy that accounts for both long‐term uncertainty and short‐term variability over the planning horizon from the perspective of a central planner. In this framework, the central planner fosters the construction of appropriate transmission lines and the deployment of optimal MG‐based generating units among profit‐driven private investors. The Wasserstein distance uncertainty set is used to characterize the long‐term uncertainty associated with future load demand. Short‐term uncertainties, stemming from variations in load demands and production levels of stochastic units, are modeled through operating conditions. To ensure the tractability of the proposed planning model, the authors introduce a decomposition framework embedded with a modified application of Bender's method. To validate the efficiency and highlight the potential benefits of the proposed expansion planning methodology, two case studies based on simplified IEEE 6‐bus and IEEE 118‐bus systems are included. These case studies assess the effectiveness of the presented approach, its ability to navigate uncertainties, and its capacity to effectively optimize expansion decisions. [ABSTRACT FROM AUTHOR]

Termites—one of the most abundant animal groups in tropical ecosystems—are vital in nutrient recycling, contributing significantly to maintaining ecosystem functioning. However, how selective they are in their litter food choice, and whether they prefer nutritious or less nutritious litter substrates, are still important unresolved questions.Here, we test the effect of litter traits on the removal of litter by fungus‐growing termites, a dominant group of macrodetritivores in the Serengeti‐Mara ecosystem. We used metal‐mesh litterbags to measure the mass loss of stem and leaf litter from 23 grass species after an incubation period of 61 days.Sheeting—soil deposits indicating termite presence—strongly increased with tannin and phenolic compounds, especially in leaf litter (R2 = 0.54), where highly aromatic species like Cymbopogon caesius and Bothriochloa insculpta exhibited the highest sheeting rates. Litterbags with sheeting displayed 66% higher mass loss on average compared to those without. Once termites had selected the substrate, mass loss increased consistently irrespective of litter traits.Quantifying the combined effects of sheeting frequency and differential mass loss, we found that fungus‐growing termites predominantly increased the mass loss of high‐nutrient litter. This was mainly due to additional mass loss in leaf litter, not stem litter, with tannin concentration being the primary predictor of enhanced overall decomposition by termites. This suggests termites ameliorate the otherwise adverse influence of plant secondary compounds on litter decomposition.Synthesis: Our results support the idea that fungus‐growing termites are generalists, as termites collected organic substrates with varying quality. The strong effect of phenolic compounds on sheeting rate implies that secondary compounds play an important role in termite substrate selection. The selective removal of substrates high in secondary compounds suggests fungus‐growing termites lift important constraints to microbial breakdown, potentially enhancing ecosystem‐level carbon and nutrient recycling rates. Termites play crucial roles in recycling organic matter across tropical biomes and our study highlights that the role of secondary compounds in their selection and detection in decomposition studies needs more attention [ABSTRACT FROM AUTHOR]

Accurate daily streamflow forecasts remain challenging in arid regions. A Bayesian model averaging (BMA) ensemble learning strategy was proposed to forecast 1-, 2-, and 3-day-ahead streamflow in Dunhuang Oasis, northwest China. The efficiency of BMA was compared with four decomposition-based machine learning and deep learning models. Satisfactory forecasts were achieved with all proposed models at all lead times; however, based on Nash-Sutcliffe efficiency values of 0.976, 0.967, and 0.957, BMA achieved the greatest accuracy for 1-, 2-, and 3-day-ahead streamflow forecasts, respectively. Uncertainty analysis confirmed the reliability of BMA in yielding consistently accurate streamflow forecasts. Thus, BMA could provide an efficient alternative approach to multistep-ahead daily streamflow forecasting. The incorporation of data decomposition techniques (e.g. variational mode decomposition) and deep learning algorithms (e.g. deep belief network) into BMA may provide worthy technical references for supervised learning of streamflow systems in data-scarce regions. [ABSTRACT FROM AUTHOR]

Flow lines are often used to perform assembly operations in multi-stage processes. During these assembly operations, components that are relatively small, compared to the work pieces travelling down the flow line, are mounted to the work pieces at a given stage. Those components, or more generally, any kind of auxiliary material, are provisioned to the corresponding production stage in a repetitive but not necessarily deterministic manner using a certain delivery frequency, each time filling the local storage up to a predetermined order-up-to level. Just like random processing times, machine failures, and repairs, the randomness of the provisioning process can impact the long-term throughput of such a flow line. In this paper, we develop a fast and accurate analytical performance evaluation method to estimate the long-term throughput of a Markovian flow line of this type for the practically important case of limited buffer capacities between the production stages. We first give an exact characterization of a two-machine line of that type and show how to determine system state probabilities and aggregate performance measures. Furthermore, we show how to use this two-machine model as the building block of an approximate decomposition approach for longer flow lines. As opposed to previous decomposition approaches, even the state space of the two-machine lines can become so large that an exact solution of the Markov chains can become impractical. We hence show how to set up, train, and use an artificial neural network to replace the Markov chain solver embedded in the decomposition approach, which then leads to an accurate and extremely fast flow line evaluation tool. The proposed methodology is evaluated by a comparison with simulation results and used to characterize the structural patterns describing the behaviour of flow lines of this type. The method can be used to systematically consider the combined impact of the delivery frequency and the local order-up-to levels for the auxiliary material when designing a flow line of this type. [ABSTRACT FROM AUTHOR]

Measuring the chemical traits of leaf litter is important for understanding plants' influence on nutrient cycles, including through nutrient resorption and litter decomposition, but conventional leaf trait measurements are often destructive and labor-intensive. Here, we develop and evaluate the performance of partial least-squares regression models that use reflectance spectra of intact or ground leaves to estimate leaf litter traits, including carbon and nitrogen concentration, carbon fractions, and leaf mass per area (LMA). Our analyses included more than 300 samples of senesced foliage from 11 species of temperate trees, including both needleleaf and broadleaf species. Across all samples, we could predict each trait with moderate-to-high accuracy from both intact-leaf litter spectra (validation R2 = 0.543–0.941; %root mean squared error (RMSE) = 7.49–18.5) and ground-leaf litter spectra (validation R2 = 0.491–0.946; %RMSE = 7.00–19.5). Notably, intact-leaf spectra yielded better predictions of LMA. Our results support the feasibility of building models to estimate multiple chemical traits from leaf litter of a range of species. In particular, intact-leaf spectral models allow non-destructive trait estimation in a matter of seconds, which could enable researchers to measure the same leaves over time in studies of nutrient resorption. [ABSTRACT FROM AUTHOR]

This study presents a simple, low-cost, and efficient route to obtain zinc oxide by adopting the thermal decomposition method of zinc acetate at 300 (Gr@ZnO_300), 400 (Gr@ZnO_400), 500 (Gr@ZnO_500), and 600 °C (Gr@ZnO_600) for 1 h. The diffraction patterns collected for the samples indicated the majority formation of the hexagonal phase (P63mc) for zinc oxide and residual amounts for graphitic carbon, which has a hexagonal structure of space group P63/mmc. The images collected by scanning electron microscopy (SEM) revealed the formation of sub-microcrystals with elongated rod-shaped morphology, with dimensions between 0.223 and 1.09 μm. The optical and colourimetric properties of the obtained materials indicate the presence of graphitic carbon in the samples, corroborating the analysis by XRD and Raman spectroscopy, with an optical bandgap close to 3.21 eV, and energies of the valence (EVB) and conduction (ECB) bands of 2.89 eV and −0.31 eV, respectively. The photocatalytic performance at 20 min of exposure time under UV light of all prepared samples in the decolourisation of rhodamine B (RhB) dye solutions follows the order Gr@ZnO_300 (95.6%) > Gr@ZnO_600 (92.8%) > Gr@ZnO_400 (84.0%) > Gr@ZnO_500 (78.1%), where the photocatalytic performance of Gr@ZnO_300 sample was 16.5 times more effective than the photolysis test. Moreover, the results confirmed that the best performance was archived at pH = 10, and the holes (h+) and superoxide (O2•−) radicals are the main species involved in the discolouration of RhB dye molecules in an aqueous medium. Finally, the reusability experiment shows high stability of the Gr@ZnO_300 sample as a solid photocatalyst and cycling capability, which obtained total discolouration of RhB of a solution under five cycling experiments of 60 min of exposure to UV light at room temperature. [ABSTRACT FROM AUTHOR]

While the product and labour market imperfections reveal efficiency losses, they may influence technology adoption and its change, raising the endogeneity issue of productivity and efficiency estimates. Using a two-step approach, this work offers the endogeneity-corrected stochastic frontier for such a contemporaneous relation and accounts for efficiency and productivity losses due to market imperfections. A modified frontier function, defined as the residue per capital unit, has been drawn from the Cobb–Douglas function to estimate the terms containing the product and labour market imperfections along with other factors capturing the levels of technology, scale and technical efficiency. First, a standard frontier panel model estimates technology and technical efficiency terms with a proxy function in polynomials of market imperfection terms used for the contemporaneous relation, and then a GMM approach applies to the residue to estimate the parameters containing market imperfections. The estimated results using the three-digit industries across 17 major Indian states for 2008–2016 reveal a strong presence of product and labour market imperfections and associated efficiency losses. The efficiency in the product market has been lower and has further deteriorated in most industries, but not in the labour market. [ABSTRACT FROM AUTHOR]

As electronic waste poses environmental challenges, exploring eco-friendly alternatives becomes imperative. In this review, the introduction reveals the disposal problem of existing printed circuit boards (PCBs) and the potential impacts of implementing biodegradable PCBs towards the United Nations Sustainable Development Goals. Various biodegradable materials, including polylactic acid, cellulose/cellulose acetate, silk proteins, gelatin, polyvinyl alcohol, mycelium, and wood, were evaluated for their properties and suitability in PCB manufacturing. Each material is scrutinised for its suitability in creating environmentally friendly circuit boards. The study meticulously analyses these biodegradable PCBs' electrical, mechanical, thermal and decomposition properties, providing insights into their performance under various conditions. The article also explores different fabrication methods and their advantages and limitations for manufacturing biodegradable PCBs. Solvent and non-solvent based decomposition of the biodegradable PCBs were revealed. The research outcome on a balance between hygroscopic property and degradability of biodegradable PCBs is revealed. The narrative extends to encompass the challenges and issues associated with the Design-for-Manufacturing processes and life cycle assessment of biodegradable PCBs, shedding light on potential hurdles and areas for improvement. The article concludes with a forward-looking perspective on the future of biodegradable printed circuit boards, environmentally friendly fire-retardants, a proposal for alternative standards for biodegradable PCBs, and their increasing role in sustainable electronics. [ABSTRACT FROM AUTHOR]

The motherhood wage penalty is often cited as a contributor towards the gender earnings gap. A common explanation involves women's labor supply reductions after having children. Yet, the literature says little about whether mothers' labor supply reductions are entirely voluntary. This study utilizes two US longitudinal panels to measure children's impact on parent job loss. Mothers are significantly more likely than fathers to involuntarily lose their jobs. The gap is substantial, persists over time, is robust to various model specifications, exists among a host of demographic sub-samples, and is driven by gender differences in characteristic effects rather than levels. [ABSTRACT FROM AUTHOR]

One of the fundamental parameters of drugs and pharmaceutical products is, in addition to their physiological effects, also their shelf-life. Even pharmaceuticals are subject to the effects of time, which gradually degrades and deteriorates them. This results in a reduction or even a serious change in the effects, or the development of toxicity. Therefore, the determination of the shelf-life of any drug or pharmaceutical product is of paramount importance. Unused drugs or pharmaceutical products after the expiry date have to be disposed of in a costly manner, which means financial losses and also imposes an unnecessary burden on the environment. There has recently been considerable discussion about the possible extension of the shelf-life of pharmaceuticals. The results of analyses of the historical remains of pharmaceuticals play an important role in this discussion. Therefore, an overview of recent results in this field is given here. In the first part, the review focuses on historical medicinal preparations (from antiquity to the early 19th century), which represent interesting, valuable, and often unique material for the study of the stability of medicinal substances over a long period (despite the uncertainty we have about their initial composition). The second part of the review gives an overview of articles on the stability of modern medicinal products, mostly already industrially produced. [ABSTRACT FROM AUTHOR]

Plastic production on a commercial scale began in the 1950s, reaching an annual production of 460 million metric tons in 2019. The global release of 22% of produced plastics into the environment has raised concerns about their potential environmental impacts, particularly on aquatic ecosystems. Here, we quantify and categorize plastic debris found along Richland Creek, a small, heavily forested watershed in western North Carolina, USA. Plastics within the riparian zone of seven 50 m reaches of Richland Creek and its tributaries were sampled two or three times. The 1737 pieces of collected plastic debris were returned to the lab where they were measured and categorized. A small-scale laboratory study using seven of the items collected was performed to determine their ability to break down into microplastics (particles < 5 mm in size). The majority (76%) of collected items were made of either plastic film (particularly bags and food wrappers, 43%) or hard plastics (e.g., bottles, 2%). However, when viewed on a surface area basis, films and synthetic fabrics (e.g., clothing, sleeping bags) equally dominated. Roughly three-quarters of the items collected had a width less than 10 cm, due primarily to the fragmentation of the original items; over two-thirds of the collected items were fragmented. Items composed of foams and films exhibited the highest fragmentation rates, 93% and 86%, respectively. Most collected plastics were domestic in nature, and the number of items increased downstream through more developed areas. Laboratory studies showed that plastic debris has a propensity to break down into microplastics. We believe the data collected here should be replicated in other streams, as these freshwater environments are the source of plastics that eventually enter the oceans. [ABSTRACT FROM AUTHOR]