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As a significant branch of production scheduling problem, the Flexibility Job Shop Scheduling Problem (FJSP) is a typical NP-hard problem. Most conventional flexible workshop scheduling primarily focuses on performance aspects involving production efficiency such as time and quality. In recent years, due to increased energy costs and environmental pollution, 'low-carbon scheduling' has garnered attention as a new scheduling paradigm among scholars and engineers. This paper investigates a low-carbon flexible Job shop scheduling problem, proposing a Grey Wolf Optimization algorithm (SC-GWO), aiming to minimize the sum of carbon emission costs and makespan costs. This algorithm employs the Grey Wolf Algorithm (GWO) as the fundamental optimization method, adaptively choosing between global and local searches based on the dispersion degree of individuals. Firstly, integrating the Sine Cosine Algorithm (SCA), the sinusoidal cosine search mechanism is applied to GWO to enhance its local search capability. Secondly, a new leader selection mechanism is introduced to prevent leaders from falling into local optima, thus improving the algorithm's global exploration capability. Utilizing a nonlinear convergence factor strategy controls the global exploration and local exploitation capabilities in different algorithm stages, enhancing optimization accuracy and accelerating convergence, achieving a dynamic balance between the two. Finally, validation of the SC-GWO algorithm's ability to solve low-carbon scheduling problems in flexible job shop scheduling instances is conducted. Experimental results demonstrate the superior performance of SC-GWO in solving low-carbon flexible workshop scheduling instances. Comparative experiments against four other advanced algorithms on 22 classic benchmark test functions confirm SC-GWO's better convergence. Through standard test functions like Bandimarte instances applied to solve FJSP, experimental results showcase the excellent optimization performance of SC-GWO. Compared to HGWO and GWO, the makespan time is reduced by 22.25% and 39.27%, respectively. The proposed SC-GWO algorithm demonstrates favorable solving effects on flexible job shop scheduling instances, meeting actual production scheduling needs. [ABSTRACT FROM AUTHOR]

This study explores the impacts of global warming on the reproductive efforts of Posidonia oceanica, a key seagrass species endemic to the Mediterranean Sea. By analyzing data from five areas in Sardinia in February 2023, we have investigated the relationship between thermal descriptors and P. oceanica flowering and fruiting variables. In fact, whether climate change has been affected the distribution of seagrasses by changing their reproductive efforts is still controversial and our findings contribute to this ongoing debate, highlighting a noticeable increase in reproductive events potentially affected by rising temperature. Overall, mean summer sea surface temperature (SST) was positively associated to inflorescence density, presence of living fruits and fruit size; living fruits and fruit size were also influenced positively by the maximum SST within 3 months before sampling (November–February). Both flowering and fruiting were negatively affected by the maximum SST within 1 month before inflorescence observation and mean winter SST, respectively, suggesting that P. oceanica reproductive effort depends on the duration and the temporal context in which the anomaly occurs. However, the high variability between meadows of the same area highlights the need of future studies to focus on the uncertainties related to local factors. [ABSTRACT FROM AUTHOR]

Halophilic and halotolerant microorganisms have a high biotechnological potential. They are producers of biologically active substances, stress-protective agents, hydrolytic enzymes, and are used for environmental bioremediation. At the same time, the characterization of novel halotolerant bacteria and determination of their salt tolerance strategies are important basic problems. The present work reports the isolation of a new strain, MX2, from the salt well brine of the Yakshinskoe potassium−magnesium salt deposit. The isolate was an aerobic, gram-positive, nonmotile bacterium that did not form spores. The cell morphology varied from cocci to short rods capable of producing V-shaped forms. The colonies on agar were circular, with an entire edge and raised center, glistening and orange. Bacteria of strain MX2 were halotolerant microorganisms capable of growing at NaCl concentrations up to 9%. The genome of strain MX2 was sequenced. Its estimated size was 3 747 717 bp, and the number of protein-coding genes was 3562. Strain MX2 was identified as belonging to the species Dietzia maris based on analysis of the 16S rRNA, gyrB, rpoB, recA, and ppk gene sequences and using time-of-flight mass spectrometry (MALDI-TOF-MS). D. maris MX2 had complete metabolic pathways for the synthesis of ectoine, hydroxyectoine, and trehalose, as well as the transport systems for ectoine, hydroxyectoine, trehalose, glycerol, glycerol-3-phosphate, L-proline, and glycine-betaine. Thus, to ensure the osmotic balance, D. maris MX2 used the strategy of accumulating compatible organic solutes. [ABSTRACT FROM AUTHOR]

In recent decades agricultural decision-making system has played a vital role in the field monitoring process. For these emerging technologies like the Internet of Things (IoT), artificial intelligence (AI), and wireless sensors are utilized for precise data extraction and analysis. However numerous techniques are developed for increasing agricultural production and enhancing operational efficiency. But still, they possess various challenges like lack of accuracy, increased power utilization, and costs. Insects and pathogens cause plant diseases that reduce productivity if not diagnosed at a proper time. Thus this paper develops Deep Q Rapidly-exploring Random tree-based Adaptive Fire hawk (DQRR-AFH) for diagnosing leaf diseases and monitoring them. It comprises various phases including data acquisition; Image processing, segmentation, feature extraction, and classification. Further, the classification is performed by exploring random trees, and the hyperparameters are tuned via the Adaptive Fire Hawk Optimizer algorithm is utilized to enhance the efficiency of the model. The proposed method monitors the soil moisture content and prevents cotton leaf diseases by spraying chemicals on the plants. Multiple cotton leaf images are obtained to verify the performance with various metrics. Compared to conventional methods such as WL-CNN, ECPRC, and DT, the proposed model achieved exceptional performance with an accuracy of 98.88%, precision of 97%, and an F1-score of 99.21%. [ABSTRACT FROM AUTHOR]

Background and Aims: Roots are of critical importance to plants due to their role in absorbing soil water and nutrients and adapting to ever-changing environmental conditions. Grazing changes plant and soil conditions and can affect root growth and resource utilization strategies. However, it is still unclear how grazing intensity affects plant root traits in desert steppes, especially by altering soil resource availability.Here, we studied the effect of four levels of grazing intensity, including no grazing (CK), light grazing (LG), moderate grazing (MG), and heavy grazing (HG), on the root traits of Stipa breviflora and soil physical, chemical, and microbial properties in a desert steppe dominated by S. breviflora under in Siziwang Banner, Inner Mongolia, China.Compared to the CK treatment, all grazing treatments significantly reduced root diameter, and increased root length density and root-to-shoot ratio, but did not affect root nitrogen concentration and tissue density. The light grazing treatment significantly increased the root fractal dimension, root fractal abundance, and root biomass. The heavy grazing treatment significantly increased specific root length and root fractal abundance. Principal component analysis revealed that grazing influenced the root-mycorrhizal “collaboration” gradient, shifting root resources utilization strategies from “outsourcing” in the CK to “do-it-yourself” in the grazed plots. Structural equation modeling showed that shifts in root traits were mainly associated with changes in soil pH, ammonium nitrogen availability, and microbial diversity under grazing.Under increasing grazing intensity, S. breviflora adapted to higher soil pH and lower nitrogen availability by producing longer, thinner, more branching roots and a “do-it-yourself” strategy. Our results suggest that changes in root traits play a very important role in the adaption of a dominant desert steppe plant to grazing intensity.Methods: Roots are of critical importance to plants due to their role in absorbing soil water and nutrients and adapting to ever-changing environmental conditions. Grazing changes plant and soil conditions and can affect root growth and resource utilization strategies. However, it is still unclear how grazing intensity affects plant root traits in desert steppes, especially by altering soil resource availability.Here, we studied the effect of four levels of grazing intensity, including no grazing (CK), light grazing (LG), moderate grazing (MG), and heavy grazing (HG), on the root traits of Stipa breviflora and soil physical, chemical, and microbial properties in a desert steppe dominated by S. breviflora under in Siziwang Banner, Inner Mongolia, China.Compared to the CK treatment, all grazing treatments significantly reduced root diameter, and increased root length density and root-to-shoot ratio, but did not affect root nitrogen concentration and tissue density. The light grazing treatment significantly increased the root fractal dimension, root fractal abundance, and root biomass. The heavy grazing treatment significantly increased specific root length and root fractal abundance. Principal component analysis revealed that grazing influenced the root-mycorrhizal “collaboration” gradient, shifting root resources utilization strategies from “outsourcing” in the CK to “do-it-yourself” in the grazed plots. Structural equation modeling showed that shifts in root traits were mainly associated with changes in soil pH, ammonium nitrogen availability, and microbial diversity under grazing.Under increasing grazing intensity, S. breviflora adapted to higher soil pH and lower nitrogen availability by producing longer, thinner, more branching roots and a “do-it-yourself” strategy. Our results suggest that changes in root traits play a very important role in the adaption of a dominant desert steppe plant to grazing intensity.Results: Roots are of critical importance to plants due to their role in absorbing soil water and nutrients and adapting to ever-changing environmental conditions. Grazing changes plant and soil conditions and can affect root growth and resource utilization strategies. However, it is still unclear how grazing intensity affects plant root traits in desert steppes, especially by altering soil resource availability.Here, we studied the effect of four levels of grazing intensity, including no grazing (CK), light grazing (LG), moderate grazing (MG), and heavy grazing (HG), on the root traits of Stipa breviflora and soil physical, chemical, and microbial properties in a desert steppe dominated by S. breviflora under in Siziwang Banner, Inner Mongolia, China.Compared to the CK treatment, all grazing treatments significantly reduced root diameter, and increased root length density and root-to-shoot ratio, but did not affect root nitrogen concentration and tissue density. The light grazing treatment significantly increased the root fractal dimension, root fractal abundance, and root biomass. The heavy grazing treatment significantly increased specific root length and root fractal abundance. Principal component analysis revealed that grazing influenced the root-mycorrhizal “collaboration” gradient, shifting root resources utilization strategies from “outsourcing” in the CK to “do-it-yourself” in the grazed plots. Structural equation modeling showed that shifts in root traits were mainly associated with changes in soil pH, ammonium nitrogen availability, and microbial diversity under grazing.Under increasing grazing intensity, S. breviflora adapted to higher soil pH and lower nitrogen availability by producing longer, thinner, more branching roots and a “do-it-yourself” strategy. Our results suggest that changes in root traits play a very important role in the adaption of a dominant desert steppe plant to grazing intensity.Conclusions: Roots are of critical importance to plants due to their role in absorbing soil water and nutrients and adapting to ever-changing environmental conditions. Grazing changes plant and soil conditions and can affect root growth and resource utilization strategies. However, it is still unclear how grazing intensity affects plant root traits in desert steppes, especially by altering soil resource availability.Here, we studied the effect of four levels of grazing intensity, including no grazing (CK), light grazing (LG), moderate grazing (MG), and heavy grazing (HG), on the root traits of Stipa breviflora and soil physical, chemical, and microbial properties in a desert steppe dominated by S. breviflora under in Siziwang Banner, Inner Mongolia, China.Compared to the CK treatment, all grazing treatments significantly reduced root diameter, and increased root length density and root-to-shoot ratio, but did not affect root nitrogen concentration and tissue density. The light grazing treatment significantly increased the root fractal dimension, root fractal abundance, and root biomass. The heavy grazing treatment significantly increased specific root length and root fractal abundance. Principal component analysis revealed that grazing influenced the root-mycorrhizal “collaboration” gradient, shifting root resources utilization strategies from “outsourcing” in the CK to “do-it-yourself” in the grazed plots. Structural equation modeling showed that shifts in root traits were mainly associated with changes in soil pH, ammonium nitrogen availability, and microbial diversity under grazing.Under increasing grazing intensity, S. breviflora adapted to higher soil pH and lower nitrogen availability by producing longer, thinner, more branching roots and a “do-it-yourself” strategy. Our results suggest that changes in root traits play a very important role in the adaption of a dominant desert steppe plant to grazing intensity. [ABSTRACT FROM AUTHOR]

The geographic distribution of the common viper, Vipera berus (L. 1758), was believed to be limited in the north and northeast by an assumed lack of hibernacula with temperatures exceeding 0°C, because the species is not freeze-tolerant. To test this hypothesis, we measured in the laboratory the cold resistance of vipers that inhabit Kizhi Island (Lake Onega, Karelia, Russian North), and compared the results obtained with the temperatures in the hibernacula and soils of the region. Freezing of the adults happened at an average temperature of −3.0°C (ranging from −2 to −3.9°C). Vipera berus failed to tolerate complete freezing, but could withstand short-term (1–8 hours) partial freezing. At subzero temperatures (−2 to −2.2°C), animals remained supercooled for 23–121 days. Vipers remained active at temperatures dropping down to −1.5°C, moving in experimental containers; this possibly happens in overwintering places as well. Our study allows us to conclude that the species' ability to withstand long-term supercooling (up to four months) is one of the key determinants of the adaptive strategy of the common viper in cold regions. The critical temperature of the species in overwintering sites must be considered to be not 0°C, but −2°C. This threshold temperature can be a factor limiting the geographic distribution of V. berus. Temperatures in hibernacules on Kizhi Island (heapes of stones) and also possibly in all soils of Karelia are favorable for the species' overwintering, leading to its great abundance levels. [ABSTRACT FROM AUTHOR]

Inverse kinematic solution is a critical procedure for the control of manipulators; however, only a small number of manipulators that meet certain conditions have closed-form solutions. In this paper, the conventional solution was replaced by the optimization process of a proposed fitness function. The fitness function aims to obtain a set of accurate joint angles for the desired position and orientation of the end effector. The function is based on forward kinematics; hence, this approach can avoid singularities and be suitable for solving many manipulators. For solving this optimization problem, particle swarm optimization algorithm was chosen as the basis due to its easy principle and excellent performance. To enhance the performance of the algorithm in searching global optimum, an adaptive inertia weight strategy applied to adjust the velocity of particles was proposed. Besides, for particles, to avoid trapping in local optimum at the boundary, a special boundary treatment was presented. In this study, two serial robotic manipulators were used to test the performance of adaptive particle swarm optimization (APSO). Meanwhile, several powerful PSO variants improved from disparate methods were selected to compare with APSO. The experimental results demonstrate that the proposed fitness function with APSO can solve the inverse kinematic problem of multi-DOF manipulators efficiently and accurately. [ABSTRACT FROM AUTHOR]

This systematic review of research on adaptive learning used a strategic search process to synthesize research on adaptive learning based on publication trends, instructional context, research methodology components, research focus, adaptive strategies, and technologies. A total of 61 articles on adaptive learning were analyzed to describe the current state of research and identify gaps in the literature. Descriptive characteristics were recorded, including publication patterns, instructional context, and research methodology components. The count of adaptive learning articles published fluctuated across the decade and peaked in 2015. During this time, the largest concentration of adaptive learning articles appeared in Computers and Education. The majority of the studies occurred in higher education in Taiwan and the United States, with the highest concentration in the computer science discipline. The research focus, adaptive strategies, and adaptive technologies used in these studies were also reviewed. The research was aligned with various instructional design phases, with more studies examining design and development, and implementation and evaluation. For examining adaptive strategies, the authors examined both adaptive sources based on learner model and adaptive targets based on content and instructional model. Learning style was the most observed learner characteristic, while adaptive feedback and adaptive navigation were the most investigated adaptive targets. This study has implications for adaptive learning designers and future researchers regarding the gaps in adaptive learning research. Future studies might focus on the increasing availability and capacities of adaptive learning as a learning technology to assist individual learning and personalized growth. [ABSTRACT FROM AUTHOR]

Craniometric features (measurements, indexes) in several species of the genus Sylvaemus (S. sylvaticus, S. flavicollis, and S. uralensis from Eastern Europe and some adjacent territories, as well as S. ponticus and S. witherbyi from the Caucasus) have been studied using multivariate statistical analysis. For the first time, craniometric characters of the genus Sylvaemus are considered in relation to the feeding ecology of species. A total of 614 skulls were studied. Based on original material, discriminant keys have been developed using skull measurements. The keys appear to be suitable for the diagnostics of the studied Sylvaemus species, including sibling ones. The largest skulls are shown to be characteristic of S.flavicollis, and the smallest ones, of S. uralensis. Cluster analysis of the absolute measurements of the skull cumulative selection has revealed the greatest isolation of S. flavicollis and the similarity of coexisting but phylogenetically remote S. ponticus and S. witherbyi. Factor analysis showed that, within the genus Sylvaemus, the general sizes are less essential than the characters related to food smashing (the length of the lower jaw and rostrum, the width of the occipital part of the skull), and possibly also to the thickness of the incisors. Comparative analyses of the relative skull measurements (the indexes related to the food preferences of the animals, granivory or folivory) allow us to conclude that the food adaptations to granivory in the structure of the skull and teeth increase in the series S. uralensis–S. sylvaticus–S. witherbyi–S. flavicollis–S. ponticus. The cranial evolution in species within the genus Sylvaemus is suggested to have been directed to increased adaptations in the mechanisms in seed peeling and processing. [ABSTRACT FROM AUTHOR]

We consider the moving element search problem with the minimum total cardinality of tests. As a search space, we consider the set of integer points of a segment of length n. We prove that the total test cardinality of an asymptotically optimal adaptive strategy is n + 2 n . [ABSTRACT FROM AUTHOR]

Constrained optimization problems (COPs) are most commonly encountered problems in science and engineering design field. To solve such kind of problem effectively, in this paper, we put forward a new approach named CAMDE which integrates adaptive differential evolution (DE) with new multi-population-based mutation operators. In CAMDE, some inferior solutions with low objective values are maintained in an external population. During mutation process, this external population is combined with main population to generate promising progress directions toward optimal region. Furthermore, DE's control parameters F and CR are adaptively adjusted according to the statistical information learnt from the previous searches in generating improved solutions. The advantageous performance of CAMDE is validated by comparisons with some representatives of state of the art in constrained optimization over 24 test instances. Moreover, four widely used constrained mechanical engineering problems are selected to validate the search ability of CAMDE for real-world problems. The performance results show that CAMDE is an effective approach to solving COPs, which is basically enabled by the integration of multi-population-based mutation operators and adaptive control strategy for DE's control parameters. [ABSTRACT FROM AUTHOR]

Optimization techniques combined with uncertainty quantification are computationally expensive for robust aerodynamic optimization due to expensive CFD costs. Surrogate model technology can be used to improve the efficiency of robust optimization. In this paper, non-intrusive polynomial chaos method and Kriging model are used to construct a surrogate model that associate stochastic aerodynamic statistics with airfoil shapes. Then, global search algorithm is used to optimize the model to obtain optimal airfoil fast. However, optimization results always depend on the approximation accuracy of the surrogate model. Actually, it is difficult to achieve a high accuracy of the model in the whole design space. Therefore, we introduce the idea of adaptive strategy to robust aerodynamic optimization and propose an adaptive stochastic optimization framework. The surrogate model is updated adaptively by increasing training airfoils according to historical optimization results to guarantee the accuracy near the optimal design point, which can greatly reduce the number of training airfoils. The proposed method is applied to a robust aerodynamic shape optimization for drag minimization considering uncertainty of Mach number in transonic region. It can be concluded that the proposed method can obtain better optimal results more efficiently than the traditional robust optimization method and global surrogate model method. [ABSTRACT FROM AUTHOR]

In this paper, the problem of exponential lag synchronization for a class of neural networks with mixed delays including discrete and distributed delays is investigated via adaptive intermittent control. Based on piecewise analytic method, some sufficient conditions for globally exponential lag synchronization are established through constructing a piecewise continuous auxiliary function. It is noted that both the control periods and the control widths in our adaptive intermittent control strategy are allowed to be nonidentical, which extends the scope of application of periodically intermittent control with fixed both control period and control width employed widely in previous works. Moreover, it is shown that the derived globally exponential lag synchronization criteria are related to the control rates rather than the control periods, which facilitates the choice of the control periods for practical problems. Finally, a numerical example is given to illustrate the correctness of the obtained theoretical results. [ABSTRACT FROM AUTHOR]

Female birds can potentially utilise various mechanisms, such as intraclutch egg size variation (ICESV), to modulate offspring quality. If this represents an 'adaptive' strategy allowing females to adjust reproductive effort after laying of the first egg, as information on resources becomes more predictable later in the laying sequence, then we would predict that ICESV would vary with ecological context, e.g. in 'good' versus 'bad' years. Here, in European Starlings ( Sturnus vulgaris), we tested specific predictions that (1) females would lay relatively small last laid eggs in 'poor' years (with early laying and below-average breeding productivity); and (2) that ICESV would be lower in good years (late laying, above-average productivity) so that late-hatched chicks would not be disadvantaged. At the individual level we predicted (3) that repeatability of ICESV would be low if females adjusted this in relation to the environment in different years; and (4) that within-individual variation in ICESV should correlate with the number, and timing, of loss of chicks. Mean ICESV averaged −1.9% (measured as last egg mass relative to mean egg mass), typical of other hole-nesting passerines. However, our results did not support any of our hypotheses: (1) although there was annual variation in ICESV, in all years egg mass decreased through the laying sequence; (2) annual variation in ICESV was not consistent with variation in phenology or breeding productivity among years; (3) marked individual variation in ICESV (last laid egg varied from −20 to +10% relative to mean egg mass within clutches) was repeatable, i.e. individual females did not adjust ICESV in subsequent breeding attempts; and (4) variation in the magnitude of ICESV, alone and combined with hatching asynchrony, did not predict early brood loss. Our study suggests that ICESV is a relatively inflexible component of an individual female's phenotype that might contribute to variation in individual quality. [ABSTRACT FROM AUTHOR]

A wide range of applications in engineering and scientific computing are based on the sparse matrix computation. There exist a variety of data representations to keep the non-zero elements in sparse matrices, and each representation favors some matrices while not working well for some others. The existing studies tend to process all types of applications, e.g., the most popular application which is matrix-vector multiplication, with different sparse matrix structures using a fixed representation. While Graphics Processing Units (GPUs) have evolved into a very attractive platform for general purpose computations, most of the existing works on sparse matrix-vector multiplication (SpMV, for short) consider CPUs. In this work, we design and implement an adaptive GPU-based SpMV scheme that selects the best format for the input matrix having the configuration and characteristics of GPUs in mind. We study the effect of various parameters and different settings on the performance of SpMV applications when employing different data representations. We then employ an adaptive scheme to execute different sparse matrix applications using proper sparse matrix representation formats. Evaluation results show that our run-time adaptive scheme properly adapts to different applications by selecting an appropriate representation for each input sparse matrix. The preliminary results show that our adaptive scheme improves the performance of sparse matrix multiplications by 2.1 $$\times $$ for single-precision and 1.6 $$\times $$ for double-precision formats, on average. [ABSTRACT FROM AUTHOR]

This study concerns with a trust-region-based method for solving unconstrained optimization problems. The approach takes the advantages of the compact limited memory BFGS updating formula together with an appropriate adaptive radius strategy. In our approach, the adaptive technique leads us to decrease the number of subproblems solving, while utilizing the structure of limited memory quasi-Newton formulas helps to handle large-scale problems. Theoretical analysis indicates that the new approach preserves the global convergence to a fi rst-order stationary point under classical assumptions. Moreover, the superlinear and the quadratic convergence rates are also established under suitable conditions. Preliminary numerical experiments show the effectiveness of the proposed approach for solving large-scale unconstrained optimization problems. [ABSTRACT FROM AUTHOR]

Model Order Reduction (MOR) methods are employed in many fields of Engineering in order to reduce the processing time of complex computational simulations. A usual approach to achieve this is the application of Galerkin projection to generate representative subspaces (reduced spaces). However, when strong nonlinearities in a dynamical system are present and this technique is employed several times along the simulation, it can be very inefficient. This work proposes a new adaptive strategy, which ensures low computational cost and small error to deal with this problem. This work also presents a new method to select snapshots named Proper Snapshot Selection (PSS). The objective of the PSS is to obtain a good balance between accuracy and computational cost by improving the adaptive strategy through a better snapshot selection in real time (online analysis). With this method, it is possible a substantial reduction of the subspace, keeping the quality of the model without the use of the Proper Orthogonal Decomposition (POD). [ABSTRACT FROM AUTHOR]

Nitrogen (N) and phosphorus (P) are the most important nutrients involved in plant reproduction and typically the most limiting in terrestrial ecosystems. The natural soil fertility gradient of the Hawaiian archipelago, in which younger islands are N limited and older islands are P limited, provides a model system to examine questions regarding allocation of nutrients. Using fertilized plots (+N or +P) at the extreme sites of the Hawaiian archipelago, vegetative productivity (e.g., net primary productivity, growth, and litterfall) and foliar nutrient responses have previously been studied for the dominant canopy tree, Metrosideros polymorpha. Here, we investigated whether the reproductive response of M. polymorpha mirrors the previously found vegetative productivity and foliar nutrient responses, by quantifying: (1) inflorescence and seed productivity, and (2) nutrient concentration of reproductive structures. Fertilization with N and P did not significantly affect the productivity of inflorescences or seeds, or seed viability at either site. However, nutrient concentrations increased after fertilization; %P increased in inflorescences in the +P treatment at the P-limited site. Seeds and inflorescences generally contained higher nutrient concentrations than leaves at both sites. Unlike foliar data, reproductive strategies of M. polymorpha differed depending on soil nutrient limitation with emphasis on quality (higher seed viability/greater nutrient concentrations) at the P-limited site. We suggest that in response to P additions M. polymorpha employs a nutrient conservation strategy for its inflorescences and an investment strategy for its seeds. Examining N and P simultaneously challenges a basic assumption that reproductive allocation follows a similar pattern to the often measured aboveground productivity. [ABSTRACT FROM AUTHOR]

Providing adaptive strategies to offset functional limitation is common therapeutic practice with frail older adults in home care or rehabilitation. This study examines modifiable factors that influence the use of two types of adaptive strategies, environmental (assistive technology, home modifications) and behavioral (energy conservation, performance techniques). The sample included 154 functionally vulnerable elders, aged 70 years or older, who participated in a randomized trial that was implemented to improve daily function. Strategy use scores reflected the percentage of strategies utilized of those introduced in intervention. Hierarchical regression analyses revealed that a person’s enhanced readiness to change predicted environmental strategy use, whereas living alone and a person’s desire to learn new mobility skills predicted behavioral strategy use. Higher education was associated with behavioral strategy use for Whites but not for non-Whites, most of whom were African American. Other participant demographic and health related characteristics were not predictive of either strategy type. Findings show that predictors differ for each type of adaptive strategy, suggesting that training for use be tailored to strategy type and individual characteristics. [ABSTRACT FROM AUTHOR]

Adolescent idiopathic scoliosis (AIS) is characterized by morphological trunk modifications acting on body mass distribution. Some specific biomechanical strategies during postural regulation have been reported. Given that spinal deformity is three-dimensional, some strategy analysis resulting from different stepping directions should lead to a better understanding of the dynamic adaptation of behaviour. The aim of this study is to identify dynamic strategies of AIS patients stepping in lateral and forward directions. Ten AIS patients with a right thoracic curve and 15 controlled volunteers have been tested. Ground reaction forces (GRF) have been recorded for right-limb stepping and for left-limb stepping associated to forward and lateral directions. Force amplitudes, corresponding occurrences, impulses of stepping phases and an asymmetry index have been computed. Asymmetry and variability increased in the AIS group, compared to the control group, whatever the stepping direction is. Asymmetry for AIS patients systematically provides an increased left initiation GRF compared to a right initiation. Nevertheless, for both groups, lateral initiation shows the largest asymmetry index reported for a forward initiation. More precisely, adaptive dynamic strategies for the AIS group have been characterized by an asymmetry between right and left limbs for lateral and forward initiation. These results can be explained by the influence of scoliosis pathology on dynamic movements due to spinal deformity. A right thoracic curve leads to an extra weight on the limb, which needs to be moved; consequently, stepping initiation with the right limb was more challenging for patients than stepping with the left limb. For the AIS group, the observed variability can also depend on the ontogenesis of adaptive strategies. Lateral step initiation has to be considered as the most relevant paradigm to study scoliosis and may also serve as a clinical basis for treatment to analyse the dynamic postural control and asymmetry strategies of the scoliosis patient. [ABSTRACT FROM AUTHOR]

In Part I, a finite element model of surface tension has been discussed and used to solve some quasi-static problems. The quasi-static analysis is often required to find not only the initial shape of the liquid but also the static equilibrium state of a liquid body before a dynamic analysis can be carried out. In general, natural and industrial processes in which surface tension force is dominant are of dynamic nature. In this second part of this work, the dynamic effects will be included in the finite element model described in Part I. A fully Lagrangian finite element method is used to solve the free surface flow problem and Newtonian constitutive equations describing the fluid behaviour are approximated over a finite time interval. As a result the momentum equations are function of nodal position instead of velocities. The resulting ordinary differential equation is integrated using Newmark algorithm. To avoid overly distorted elements an adaptive remeshing strategy is adopted. The adaptive strategy employs a remeshing indicator based on viscous dissipation functional and incorporates an appropriate transfer operator. The validation of the model is performed by comparing the finite element solutions to available analytical solutions of a droplet oscillations and experimental results pertaining to stretching of a liquid bridge. [ABSTRACT FROM AUTHOR]

Sphingomonads are isolated at exceptionally high frequency from organic polluted environments and assumed to be more hydrophobic than other Gram-negative bacteria. However, the potential roles of cell-surface hydrophobicity (CSH) in the cell survival in polluted environment, as well as the mechanisms underlying the CSH of sphingomonads, remain unclear. Sphingobium hydrophobicum C1T is a highly hydrophobic sphingomonad isolated from electronic-waste contaminated sediment. In this study, we found that exposure to the typical pollutants in electronic-waste contaminated sediment, such as the heavy metal ion Pb and the organic compound deca-brominated diphenyl ether (deca-BDE), resulted in the development of even higher CSH of the hydrophobic strain C1T; but no significant change was observed in the low CSH of its hydrophilic variant C2. The hydrophobic strain C1T achieved higher biomass yield in standing conditions and adsorbed more amounts of hydrophobic deca-BDE than its hydrophilic variant C2, suggesting that the high CSH potentially enhanced the adaptation of hydrophobic strain to colonize in sediment and adsorb hydrophobic nutrients. The identification of the bacterial cell-surface constituents showed that the high CSH of S. hydrophobicum was contributed greatly by outer-membrane proteins, particularly membrane transporters functioning as enhancers for nutrient uptake and stress sustainment. This study will enhance our understanding of the adaptive strategies of sphingomonads in contaminated environments. It will be of great importance to enhance the CSH of sphingomonads and utilize them in cleaning up the environment from organic pollution.Sphingomonads are isolated at exceptionally high frequency from organic polluted environments and assumed to be more hydrophobic than other Gram-negative bacteria. However, the potential roles of cell-surface hydrophobicity (CSH) in the cell survival in polluted environment, as well as the mechanisms underlying the CSH of sphingomonads, remain unclear. Sphingobium hydrophobicum C1T is a highly hydrophobic sphingomonad isolated from electronic-waste contaminated sediment. In this study, we found that exposure to the typical pollutants in electronic-waste contaminated sediment, such as the heavy metal ion Pb and the organic compound deca-brominated diphenyl ether (deca-BDE), resulted in the development of even higher CSH of the hydrophobic strain C1T; but no significant change was observed in the low CSH of its hydrophilic variant C2. The hydrophobic strain C1T achieved higher biomass yield in standing conditions and adsorbed more amounts of hydrophobic deca-BDE than its hydrophilic variant C2, suggesting that the high CSH potentially enhanced the adaptation of hydrophobic strain to colonize in sediment and adsorb hydrophobic nutrients. The identification of the bacterial cell-surface constituents showed that the high CSH of S. hydrophobicum was contributed greatly by outer-membrane proteins, particularly membrane transporters functioning as enhancers for nutrient uptake and stress sustainment. This study will enhance our understanding of the adaptive strategies of sphingomonads in contaminated environments. It will be of great importance to enhance the CSH of sphingomonads and utilize them in cleaning up the environment from organic pollution.Sphingomonads are isolated at exceptionally high frequency from organic polluted environments and assumed to be more hydrophobic than other Gram-negative bacteria. However, the potential roles of cell-surface hydrophobicity (CSH) in the cell survival in polluted environment, as well as the mechanisms underlying the CSH of sphingomonads, remain unclear. Sphingobium hydrophobicum C1T is a highly hydrophobic sphingomonad isolated from electronic-waste contaminated sediment. In this study, we found that exposure to the typical pollutants in electronic-waste contaminated sediment, such as the heavy metal ion Pb and the organic compound deca-brominated diphenyl ether (deca-BDE), resulted in the development of even higher CSH of the hydrophobic strain C1T; but no significant change was observed in the low CSH of its hydrophilic variant C2. The hydrophobic strain C1T achieved higher biomass yield in standing conditions and adsorbed more amounts of hydrophobic deca-BDE than its hydrophilic variant C2, suggesting that the high CSH potentially enhanced the adaptation of hydrophobic strain to colonize in sediment and adsorb hydrophobic nutrients. The identification of the bacterial cell-surface constituents showed that the high CSH of S. hydrophobicum was contributed greatly by outer-membrane proteins, particularly membrane transporters functioning as enhancers for nutrient uptake and stress sustainment. This study will enhance our understanding of the adaptive strategies of sphingomonads in contaminated environments. It will be of great importance to enhance the CSH of sphingomonads and utilize them in cleaning up the environment from organic pollution.Sphingomonads are isolated at exceptionally high frequency from organic polluted environments and assumed to be more hydrophobic than other Gram-negative bacteria. However, the potential roles of cell-surface hydrophobicity (CSH) in the cell survival in polluted environment, as well as the mechanisms underlying the CSH of sphingomonads, remain unclear. Sphingobium hydrophobicum C1T is a highly hydrophobic sphingomonad isolated from electronic-waste contaminated sediment. In this study, we found that exposure to the typical pollutants in electronic-waste contaminated sediment, such as the heavy metal ion Pb and the organic compound deca-brominated diphenyl ether (deca-BDE), resulted in the development of even higher CSH of the hydrophobic strain C1T; but no significant change was observed in the low CSH of its hydrophilic variant C2. The hydrophobic strain C1T achieved higher biomass yield in standing conditions and adsorbed more amounts of hydrophobic deca-BDE than its hydrophilic variant C2, suggesting that the high CSH potentially enhanced the adaptation of hydrophobic strain to colonize in sediment and adsorb hydrophobic nutrients. The identification of the bacterial cell-surface constituents showed that the high CSH of S. hydrophobicum was contributed greatly by outer-membrane proteins, particularly membrane transporters functioning as enhancers for nutrient uptake and stress sustainment. This study will enhance our understanding of the adaptive strategies of sphingomonads in contaminated environments. It will be of great importance to enhance the CSH of sphingomonads and utilize them in cleaning up the environment from organic pollution.Sphingomonads are isolated at exceptionally high frequency from organic polluted environments and assumed to be more hydrophobic than other Gram-negative bacteria. However, the potential roles of cell-surface hydrophobicity (CSH) in the cell survival in polluted environment, as well as the mechanisms underlying the CSH of sphingomonads, remain unclear. Sphingobium hydrophobicum C1T is a highly hydrophobic sphingomonad isolated from electronic-waste contaminated sediment. In this study, we found that exposure to the typical pollutants in electronic-waste contaminated sediment, such as the heavy metal ion Pb and the organic compound deca-brominated diphenyl ether (deca-BDE), resulted in the development of even higher CSH of the hydrophobic strain C1T; but no significant change was observed in the low CSH of its hydrophilic variant C2. The hydrophobic strain C1T achieved higher biomass yield in standing conditions and adsorbed more amounts of hydrophobic deca-BDE than its hydrophilic variant C2, suggesting that the high CSH potentially enhanced the adaptation of hydrophobic strain to colonize in sediment and adsorb hydrophobic nutrients. The identification of the bacterial cell-surface constituents showed that the high CSH of S. hydrophobicum was contributed greatly by outer-membrane proteins, particularly membrane transporters functioning as enhancers for nutrient uptake and stress sustainment. This study will enhance our understanding of the adaptive strategies of sphingomonads in contaminated environments. It will be of great importance to enhance the CSH of sphingomonads and utilize them in cleaning up the environment from organic pollution.Sphingomonads are isolated at exceptionally high frequency from organic polluted environments and assumed to be more hydrophobic than other Gram-negative bacteria. However, the potential roles of cell-surface hydrophobicity (CSH) in the cell survival in polluted environment, as well as the mechanisms underlying the CSH of sphingomonads, remain unclear. Sphingobium hydrophobicum C1T is a highly hydrophobic sphingomonad isolated from electronic-waste contaminated sediment. In this study, we found that exposure to the typical pollutants in electronic-waste contaminated sediment, such as the heavy metal ion Pb and the organic compound deca-brominated diphenyl ether (deca-BDE), resulted in the development of even higher CSH of the hydrophobic strain C1T; but no significant change was observed in the low CSH of its hydrophilic variant C2. The hydrophobic strain C1T achieved higher biomass yield in standing conditions and adsorbed more amounts of hydrophobic deca-BDE than its hydrophilic variant C2, suggesting that the high CSH potentially enhanced the adaptation of hydrophobic strain to colonize in sediment and adsorb hydrophobic nutrients. The identification of the bacterial cell-surface constituents showed that the high CSH of S. hydrophobicum was contributed greatly by outer-membrane proteins, particularly membrane transporters functioning as enhancers for nutrient uptake and stress sustainment. This study will enhance our understanding of the adaptive strategies of sphingomonads in contaminated environments. It will be of great importance to enhance the CSH of sphingomonads and utilize them in cleaning up the environment from organic pollution.Sphingomonads are isolated at exceptionally high frequency from organic polluted environments and assumed to be more hydrophobic than other Gram-negative bacteria. However, the potential roles of cell-surface hydrophobicity (CSH) in the cell survival in polluted environment, as well as the mechanisms underlying the CSH of sphingomonads, remain unclear. Sphingobium hydrophobicum C1T is a highly hydrophobic sphingomonad isolated from electronic-waste contaminated sediment. In this study, we found that exposure to the typical pollutants in electronic-waste contaminated sediment, such as the heavy metal ion Pb and the organic compound deca-brominated diphenyl ether (deca-BDE), resulted in the development of even higher CSH of the hydrophobic strain C1T; but no significant change was observed in the low CSH of its hydrophilic variant C2. The hydrophobic strain C1T achieved higher biomass yield in standing conditions and adsorbed more amounts of hydrophobic deca-BDE than its hydrophilic variant C2, suggesting that the high CSH potentially enhanced the adaptation of hydrophobic strain to colonize in sediment and adsorb hydrophobic nutrients. The identification of the bacterial cell-surface constituents showed that the high CSH of S. hydrophobicum was contributed greatly by outer-membrane proteins, particularly membrane transporters functioning as enhancers for nutrient uptake and stress sustainment. This study will enhance our understanding of the adaptive strategies of sphingomonads in contaminated environments. It will be of great importance to enhance the CSH of sphingomonads and utilize them in cleaning up the environment from organic pollution.Sphingomonads are isolated at exceptionally high frequency from organic polluted environments and assumed to be more hydrophobic than other Gram-negative bacteria. However, the potential roles of cell-surface hydrophobicity (CSH) in the cell survival in polluted environment, as well as the mechanisms underlying the CSH of sphingomonads, remain unclear. Sphingobium hydrophobicum C1T is a highly hydrophobic sphingomonad isolated from electronic-waste contaminated sediment. In this study, we found that exposure to the typical pollutants in electronic-waste contaminated sediment, such as the heavy metal ion Pb and the organic compound deca-brominated diphenyl ether (deca-BDE), resulted in the development of even higher CSH of the hydrophobic strain C1T; but no significant change was observed in the low CSH of its hydrophilic variant C2. The hydrophobic strain C1T achieved higher biomass yield in standing conditions and adsorbed more amounts of hydrophobic deca-BDE than its hydrophilic variant C2, suggesting that the high CSH potentially enhanced the adaptation of hydrophobic strain to colonize in sediment and adsorb hydrophobic nutrients. The identification of the bacterial cell-surface constituents showed that the high CSH of S. hydrophobicum was contributed greatly by outer-membrane proteins, particularly membrane transporters functioning as enhancers for nutrient uptake and stress sustainment. This study will enhance our understanding of the adaptive strategies of sphingomonads in contaminated environments. It will be of great importance to enhance the CSH of sphingomonads and utilize them in cleaning up the environment from organic pollution.Sphingomonads are isolated at exceptionally high frequency from organic polluted environments and assumed to be more hydrophobic than other Gram-negative bacteria. However, the potential roles of cell-surface hydrophobicity (CSH) in the cell survival in polluted environment, as well as the mechanisms underlying the CSH of sphingomonads, remain unclear. Sphingobium hydrophobicum C1T is a highly hydrophobic sphingomonad isolated from electronic-waste contaminated sediment. In this study, we found that exposure to the typical pollutants in electronic-waste contaminated sediment, such as the heavy metal ion Pb and the organic compound deca-brominated diphenyl ether (deca-BDE), resulted in the development of even higher CSH of the hydrophobic strain C1T; but no significant change was observed in the low CSH of its hydrophilic variant C2. The hydrophobic strain C1T achieved higher biomass yield in standing conditions and adsorbed more amounts of hydrophobic deca-BDE than its hydrophilic variant C2, suggesting that the high CSH potentially enhanced the adaptation of hydrophobic strain to colonize in sediment and adsorb hydrophobic nutrients. The identification of the bacterial cell-surface constituents showed that the high CSH of S. hydrophobicum was contributed greatly by outer-membrane proteins, particularly membrane transporters functioning as enhancers for nutrient uptake and stress sustainment. This study will enhance our understanding of the adaptive strategies of sphingomonads in contaminated environments. It will be of great importance to enhance the CSH of sphingomonads and utilize them in cleaning up the environment from organic pollution.Sphingomonads are isolated at exceptionally high frequency from organic polluted environments and assumed to be more hydrophobic than other Gram-negative bacteria. However, the potential roles of cell-surface hydrophobicity (CSH) in the cell survival in polluted environment, as well as the mechanisms underlying the CSH of sphingomonads, remain unclear. Sphingobium hydrophobicum C1T is a highly hydrophobic sphingomonad isolated from electronic-waste contaminated sediment. In this study, we found that exposure to the typical pollutants in electronic-waste contaminated sediment, such as the heavy metal ion Pb and the organic compound deca-brominated diphenyl ether (deca-BDE), resulted in the development of even higher CSH of the hydrophobic strain C1T; but no significant change was observed in the low CSH of its hydrophilic variant C2. The hydrophobic strain C1T achieved higher biomass yield in standing conditions and adsorbed more amounts of hydrophobic deca-BDE than its hydrophilic variant C2, suggesting that the high CSH potentially enhanced the adaptation of hydrophobic strain to colonize in sediment and adsorb hydrophobic nutrients. The identification of the bacterial cell-surface constituents showed that the high CSH of S. hydrophobicum was contributed greatly by outer-membrane proteins, particularly membrane transporters functioning as enhancers for nutrient uptake and stress sustainment. This study will enhance our understanding of the adaptive strategies of sphingomonads in contaminated environments. It will be of great importance to enhance the CSH of sphingomonads and utilize them in cleaning up the environment from organic pollution.Sphingomonads are isolated at exceptionally high frequency from organic polluted environments and assumed to be more hydrophobic than other Gram-negative bacteria. However, the potential roles of cell-surface hydrophobicity (CSH) in the cell survival in polluted environment, as well as the mechanisms underlying the CSH of sphingomonads, remain unclear. Sphingobium hydrophobicum C1T is a highly hydrophobic sphingomonad isolated from electronic-waste contaminated sediment. In this study, we found that exposure to the typical pollutants in electronic-waste contaminated sediment, such as the heavy metal ion Pb and the organic compound deca-brominated diphenyl ether (deca-BDE), resulted in the development of even higher CSH of the hydrophobic strain C1T; but no significant change was observed in the low CSH of its hydrophilic variant C2. The hydrophobic strain C1T achieved higher biomass yield in standing conditions and adsorbed more amounts of hydrophobic deca-BDE than its hydrophilic variant C2, suggesting that the high CSH potentially enhanced the adaptation of hydrophobic strain to colonize in sediment and adsorb hydrophobic nutrients. The identification of the bacterial cell-surface constituents showed that the high CSH of S. hydrophobicum was contributed greatly by outer-membrane proteins, particularly membrane transporters functioning as enhancers for nutrient uptake and stress sustainment. This study will enhance our understanding of the adaptive strategies of sphingomonads in contaminated environments. It will be of great importance to enhance the CSH of sphingomonads and utilize them in cleaning up the environment from organic pollution. [ABSTRACT FROM AUTHOR]