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Abstract Higher-order interactions shape collective dynamics, but how they affect transitions between different states in swarmalator systems is yet to be determined. To that effect, we here study an analytically tractable swarmalator model that incorporates both pairwise and higher-order interactions, resulting in four distinct collective states: async, phase wave, mixed, and sync states. We show that even a minute fraction of higher-order interactions induces abrupt transitions from the async state to the phase wave and the sync state. We also show that higher-order interactions facilitate an abrupt transition from the phase wave to the sync state bypassing the intermediate mixed state. Moreover, elevated levels of higher-order interactions can sustain the presence of phase wave and sync state, even when pairwise interactions lean towards repulsion. The insights gained from these findings unveil self-organizing processes that hold the potential to explain sudden transitions between various collective states in numerous real-world systems.

The current study was designed to investigate the consequences of rice cooking and soaking of cooked rice (CR) with or without arsenic (As) contaminated water on As and Fe (iron) transfer to the human body along with associated health risk assessment using additive main-effects and multiplicative interaction (AMMI) and Monte Carlo Simulation model. In comparison to raw rice, As content in cooked rice (CR) and soaked cooked rice (SCR) enhanced significantly (at p

Abstract We study the intricate interplay between ecological and evolutionary processes through the lens of the prisoner’s dilemma game. But while previous studies on cooperation amongst selfish individuals often assume instantaneous interactions, we take into consideration delays to investigate how these might affect the causes underlying prosocial behavior. Through analytical calculations and numerical simulations, we demonstrate that delays can lead to oscillations, and by incorporating also the ecological variable of altruistic free space and the evolutionary strategy of punishment, we explore how these factors impact population and community dynamics. Depending on the parameter values and the initial fraction of each strategy, the studied eco-evolutionary model can mimic a cyclic dominance system and even exhibit chaotic behavior, thereby highlighting the importance of complex dynamics for the effective management and conservation of ecological communities. Our research thus contributes to the broader understanding of group decision-making and the emergence of moral behavior in multidimensional social systems.

The growing population is driving up the demand for food, but the inadequate efficiency of traditional fertilizers is constraining crop production. Nanotechnology-based fertilizers represent a novel strategy for boosting agricultural output and show great potential as viable options in the fertilizer industry, as they can significantly enhance nutrient retention and promote optimal growth. Very recently, slow and controlled release nanofertilizers have evolved through the development of nanocomposites or coating techniques with the aid of various chemical entities. These types of slow release nanofertilizers are more effective than normal nanofertilizers as these fertilizers deliver nutrients in a controlled manner and can be regulated by various environmental and physical stimuli (pH, temperature, humidity, etc.). Their nutrient use efficiency (NUE) is also far better than the normal nanoparticles (individual nanoparticles like iron, zinc, copper nanoparticles etc.), as these nanocomposites demonstrate zero or very little nutrient leaching. Utilizing controlled release fertilizers mitigates nutrient loss from volatilization and leaching and offers a meticulously tailored nutrient release system harmonizing with the objective of sustainable agriculture. Therefore, this review article provides insights into slow and controlled release nanofertilizers, including preparation approaches, nutrient-release techniques, analytical detection methods, current status, role in crop improvement, commercial viability, and future perspectives.

Agricultural productivity is constantly being forced to maintain yield stability to feed the enormously growing world population. However, shrinking arable and nutrient-deprived soil and abiotic and biotic stressor (s) in different magnitudes put additional challenges to achieving global food security. Though well-defined, the concept of macro, micronutrients, and beneficial elements is from a plant nutritional perspective. Among various micronutrients, selenium (Se) is essential in small amounts for the life cycle of organisms, including crops. Selenium has the potential to improve soil health, leading to the improvement of productivity and crop quality. However, Se possesses an immense encouraging phenomenon when supplied within the threshold limit, also having wide variations. The supplementation of Se has exhibited promising outcomes in lessening biotic and abiotic stress in various crops. Besides, bulk form, nano-Se, and biogenic-Se also revealed some merits and limitations. Literature suggests that the possibilities of biogenic-Se in stress alleviation and fortifying foods are encouraging. In this article, apart from adopting a combination of a conventional extensive review of the literature and bibliometric analysis, the authors have assessed the journey of Se in the “soil to spoon” perspective in a diverse agroecosystem to highlight the research gap area. There is no doubt that the time has come to seriously consider the tag of beneficial elements associated with Se, especially in the drastic global climate change era.

Synchronization has received a lot of attention from the scientific community for systems evolving on static networks or higher-order structures, such as hypergraphs and simplicial complexes. In many relevant real-world applications, the latter are not static but do evolve in time, in this work we thus discuss the impact of the time-varying nature of higher-order structures in the emergence of global synchronization. To achieve this goal, we extend the master stability formalism to account, in a general way, for the additional contributions arising from the time evolution of the higher-order structure supporting the dynamical systems. The theory is successfully challenged against two illustrative examples, the Stuart–Landau nonlinear oscillator and the Lorenz chaotic oscillator.

One of the famous economic models in game theory is the duopoly Stackelberg model, in which a leader and a follower firm manufacture a single product in the market. Their goal is to obtain the maximum profit while competing with each other. The desired dynamics for a firm in a market is the convergence to its Nash equilibrium, but the dynamics of real-world markets are not always steady and can result in unpredictable market changes that exhibit chaotic behaviors. On the other hand, to approach reality more, the two firms in the market can be considered heterogeneous. The leader firm is bounded rationale, and the follower firm is adaptable. Modifying the cost function that affects the firms' profit by adding the marginal cost term is another step toward reality. We propose a Stackelberg model with heterogeneous players and marginal costs, which exhibits chaotic behavior. This model's equilibrium points, including the Nash equilibrium, are calculated by the backward induction method, and their stability analyses are obtained. The influence of changing each model parameter on the consequent dynamics is investigated through one-dimensional and two-dimensional bifurcation diagrams, Lyapunov exponents spectra, and Kaplan-Yorke dimension. Eventually, using a combination of state feedback and parameter adjustment methods, the chaotic solutions of the model are successfully tamed, and the model converges to its Nash equilibrium.

Heterogeneity among interacting units plays an important role in numerous biological and man-made complex systems. While the impacts of heterogeneity on synchronization, in terms of structural mismatch of the layers in multiplex networks, has been studied thoroughly, its influence on intralayer synchronization, in terms of parameter mismatch among the layers, has not been adequately investigated. Here, we study the intralayer synchrony in multiplex networks, where the layers are different from one other, due to parameter mismatch in their local dynamics. In such a multiplex network, the intralayer coupling strength for the emergence of intralayer synchronization decreases upon the introduction of impurity among the layers, which is caused by a parameter mismatch in their local dynamics. Furthermore, the area of occurrence of intralayer synchronization also widens with increasing mismatch. We analytically derive a condition under which the intralayer synchronous solution exists, and we even sustain its stability. We also prove that, in spite of the mismatch among the layers, all the layers of the multiplex network synchronize simultaneously. Our results indicate that a multiplex network with mismatched layers can induce synchrony more easily than a multiplex network with identical layers.

Numerous applications in agriculture, climate, ecology, hydrology, and the environment are severely constrained by the lack of detailed information on soil texture. The purpose of this study was to predict soil particle-size fractions (PSF) in the Ri-Bhoi district of Meghalaya state, India, using a random forest model (RF). For the modeling of soil particle-size fractions, we employed 95 soil profiles (456 depth-wise layers) gathered from a recent national land resource inventory as well as currently accessible environmental variables. Sand, silt, and clay content were predicted using the Random Forest model at varied depths of 0–5, 5–15, 30–60, 60–100, and 100–200 cm. Our results showed the R2 for sand was found to be 0.30 (0–5 cm), 0.28 (5–15 cm), and 0.21 (15–30 cm). For the sand, silt, and clay fractions, respectively, the concordance correlation coefficient (CCC) was found to be greater in the 0–30 cm, 0–60 cm, and 0–15 cm depths. When there is a reasonably close monitoring of the coverage probability with a confidence level along the 1:1 line, prediction interval coverage probability (PICP) gives a decent indicator of what to anticipate. The most crucial variables for the prediction of sand and silt were channel network base level (CNBL) and LS-Factor, whereas Min Temperature of Coldest Month (°C) (BIO6) was discovered for clay prediction. For all three soil texture fractions, the range between the 5% lower and 95% higher prediction bounds was large, indicating that the existing spatial predictions may be improved. The maps of soil texture were significantly more precise, and they accurately depicted the spatial variations of particle-size fractions. Additionally, there is still a need to investigate novel methodologies for extensive digital soil mapping, which will be very advantageous for many international initiatives.

In network analysis, links depict the connections between each pair of network nodes. However, such pairwise connections fail to consider the interactions among more agents, which may be indirectly connected. Such non-pairwise or higher-order connections can be signified by involving simplicial complexes. The higher-order connections become even more noteworthy when it comes to neuronal network synchronization, an emerging phenomenon responsible for the many biological processes in real-world phenomena. However, involving higher-order interactions may considerably increase the computational costs. To confound this issue, map-based models are more suitable since they are faster, simpler, more flexible, and computationally more optimal. Therefore, this paper addresses the impact of pairwise and non-pairwise neuronal interactions on the synchronization state of 10 coupled memristive Hindmarsh–Rose neuron maps. To this aim, electrical, inner linking, and chemical synaptic functions are considered as two- and three-body interactions in three homogeneous and two heterogeneous cases. The results show that through chemical pairwise and non-pairwise synapses, the neurons achieve synchrony with the weakest coupling strengths.

Arsenic contamination in the rice agro-ecosystem, its consequent spread into the food chain, and its adverse impact are a global concern. However, assessment of the impact of arsenic contamination on the qualitative aspect of rice in the post-harvest phase has not been attempted. We laid down this particular experiment with the aim to assess how arsenic contamination influences the grain quality attributes and other elemental profiles of four popular rice varieties. The entire field study was conducted in the lower Indo-Gangetic plain from genotype (four) and environment (14 locations) interaction point of view, using the additive main effects and multiplicative interaction model. Our findings indicate that grain arsenic content can influence the grain quality attributes and other elemental profiles in a low to highly significant manner. Amylose content (r = 0.753), cooking time (r = 0.706), and gruel solid loss (r = 0.672, 0.721) were found to be positively correlated with grain arsenic content in high-yielding varieties. Noteworthy variations in micronutrient content like iron (6.63–9.23 mg kg−1), zinc (3.15–5.54 mg kg−1), and copper (2.04–3.86 mg kg−1) as well as soil properties are also visible. Moreover, indigenous rice varieties respond differently than high-yielding varieties. Besides these, a pronounced impact of gene/variety and environment interaction can be seen. The findings clearly indicate that the qualitative aspect of rice is also prone to As contamination. These outcomes will attract the attention of policy-makers and researchers to develop rice varieties that have desirable quality attributes appropriate for the arsenic-contaminated regions of the world for sustainable rice production.

A field experiment was conducted during 2015–16 and 2016–17 to assess the system productivity, energetics and economics of weed management practices in soybean (Glycine max L.)-wheat (Triticum aestivum L.) cropping system at ICAR-Directorate of Weed Research, Jabalpur, Madhya Pradesh. The experiment comprised 10 treatments having combinations of sole and sequential application of pre-emergence and post-emergence herbicides in both the crops, and their integration with hand weeding undertaken in randomized block design replicated thrice. The highest system productivity (8.04 t/ha) was obtained by employing two hand weedings, sequential application of pendimethalin followed by (fb) imazethapyr in soybean and pendimethalin fb mesosulfuron + iodosulfuron in wheat as well as by integrating either pre or post-emergence herbicides with one hand weeding. Among weed management practices, energy requirement was lowest in sole post-emergence herbicide treatment, however, integration of manual weeding required maximum energy. The energy input for hand weeding was a major share of integrated weed management practices, and it varied from 54–83% of the total treatment energy. Due to requirement of less energy for sole post-emergence herbicides, energy output, net energy return and energy ratio were the maximum. Total output energy was higher (258×103 MJ/ ha) in post-emergence herbicide fb hand weeding treatment because of higher system productivity (7.29 t/ha), and this treatment was more energy efficient and gave the highest economic returns among the weed management practices. The highest benefit: cost ratio (3.10) was obtained by the application of post-emergence herbicides in both the crops.

Background: Surgical extraction of mandibular third molars is an important and one of the most frequently performed operative procedures in dentistry. There are a variety of postoperative complications that may follow this procedure. These include pain, trismus, infection, dry socket, or alveolar osteitis. Numerous techniques have been used for reducing these morbid conditions. These range from flap designs, suture placement, use of various irrigating solutions, etc., Aim: The present study aimed to compare the effectiveness of three irrigating solutions: Ozonated water, normal saline, and povidone-iodine in reducing postoperative complications following surgical removal of impacted mandibular third molars. Materials and Methods: A total of 100 study participants formed the sample size of this study. Study subjects were categorized into three groups: Group I (third molar surgeries using ozonated water), Group II (third molar surgeries with normal saline irrigation), and Group III (third molar surgeries using povidone-iodine irrigation). Parameters studied postoperatively were alveolar osteitis (dry socket), pain, trismus, and infection after a week interval. All data obtained were entered in Microsoft Excel 2007 worksheets and Analysis of Variance (ANOVA) as a statistical tool was employed. A P value of < 0.01 was considered statistically significant. Results: It was found that ozonated water provided the best statistically proven results with comparison to normal saline and povidone-iodine in reducing the incidence of alveolar osteitis or dry socket and pain. No statistically significant difference was observed in the incidence of trismus and infection rate among three studied groups. Conclusion: Ozonated water is the best irrigating solution when compared to normal saline and povidone-iodine in terms of reduction in pain and dry socket after a 1-week duration.

Synthetic fertilizer and herbicides encompass the largest share in nutrient and weed management on food grain crops that create serious environmental issues. Integrated nutrient and non-chemical weed management approaches may help to reduce the chemical load in the environment, maintaining higher weed control efficiency and yield. A field experiment was conducted for two consecutive monsoon seasons during 2015 and 2016 in farm fields to develop a profitable and sustainable rice production system through integrated nutrient and weed management practices. A varied combination of nutrients either alone or integrated with chemical and non-chemical weed management were tested on transplanted rice in a factorial randomized block design with three replications. The results showed that the integration of concentrated organic manures with chemical fertilizer effectively inhibited weed growth and nutrient removal. Integration of nutrient and weed management practices significantly enhanced 9% biomass growth, 10% yield of the rice crop along with 3-7% higher nutrient uptake. Brassicaceous seed meal (BSM) and neem cake also had some influence on weed suppression and economic return. Thus, the integrated nutrient and weed management practices in rice cultivation might be an effective way to achieve economic sustainability and efficient rice cultivation in eastern India. Shortages of farmyard manure and vermicompost could be supplemented by BSM and neem cake in the integrated module.

Most environments favor defection over cooperation due to natural selection. Nonetheless, the emergence of cooperation is omnipresent in many biological, social, and economic systems, quite contrary to the well-celebrated Darwinian theory of evolution. Much research has been devoted to better understanding how and why cooperation persists among self-interested individuals despite their competition for limited resources. Here we go beyond a single social dilemma since individuals usually encounter various social challenges. In particular, we propose and study a mathematical model incorporating both the prisoner's dilemma and the snowdrift game. We further extend this model by considering ecological signatures like mutation and selfless one-sided contribution of altruist free space. The nonlinear evolutionary dynamics that results from these upgrades offer a broader range of equilibrium outcomes, and it also often favors cooperation over defection. With the help of analytical and numerical calculations, our theoretical model sheds light on the mechanisms that maintain biodiversity, and it helps to explain the evolution of social order in human societies.

Arsenic (As) contamination of the rice agro-ecosystem is a major concern for rice farmers of South East Asia as it imposes a serious threat to human and animal life; thus, there is an unrelenting need to explore the ways by which arsenic stress mitigation could be achieved. In the present investigation, we explore the effect of zinc (Zn2+) supplementation using the seed priming technique for the mitigation of As-induced stress responses in developing rice seedlings. In addition to the physiological and biochemical attributes, we also studied the interactive effect of Zn2+ in regulating As-induced changes by targeting antioxidant enzymes using a computational approach. Our findings suggest that Zn2+ and As can effectively modulate redox homeostasis by limiting ROS production and thereby confer protection against oxidative stress. The results also show that As had a significant impact on seedling growth, which was restored by Zn2+ and also minimized the As uptake. A remarkable outcome of the present investigation is that the varietal difference was significant in determining the efficacy of the Zn2+ priming. Further, based on the findings of computational studies, we observed differences in the surface overlap of the antioxidant target enzymes of rice, indicating that the Zn2+ might have foiled the interaction of As with the enzymes. This is undoubtedly a fascinating approach that interprets the mode of action of the antioxidative enzymes under the metal/metalloid-tempted stress condition in rice by pointing at designated targets. The results of the current investigation are rationally significant and may be the pioneering beginning of an exciting and useful method of integrating physiological and biochemical analysis together with a computational modelling approach for evaluating the stress modulating effects of Zn2+ seed priming on As-induced responses in developing rice seedlings.

We report the impact of drought stress on pearl millet during the early seedling stage and its survival mechanism. Drought stress imposed for a period of 7, 14 and 21 days showed considerable changes in morphophysiological attributes, which were evident by a decline in seedling elongation, fresh and dry biomass, and relative water content (RWC) and degradation of chlorophyll pigment. Besides this, visible chlorosis lesions were observed in leaves as compared to the control. As compared to the respective controls, a nearly 60% decline in chlorophyll content was recorded after 14 and 21 days of drought stress. In both root and shoot, drought stress raised the reactive oxygen species (ROS) levels. Both H2O2 and O2●− levels were significantly elevated along with a significant increase in lipid peroxidation in both roots and shoots, which clearly indicated ROS-induced oxidative stress. Concomitant with the increase in ROS levels and malondialdehyde (MDA) content in roots, membrane integrity was also lost, which clearly indicated ROS-induced peroxidation of membrane lipids. The activities of antioxidant enzymes and levels of non-enzymatic antioxidants were significant (p ≤ 0.001). After 7, 14 and 21 days of drought stress, activities of all the antioxidant enzymes viz., catalase (CAT), guaiacol peroxidase (GPX), superoxide dismutase (SOD) and glutathione reductase (GR) were inhibited, clearly indicating a loss of antioxidant defense machinery. Likewise, the levels of ascorbate (AsA) and reduced glutathione (GSH) levels declined significantly (p ≤ 0.01). Our results reveal that, being tolerant to arid climatic conditions, pearl millet is highly susceptible to drought stress at the early seedling stage.

Defining nutrient management zones (MZs) is crucial for the implementation of site-specific management. The determination of MZs is based on several factors, including crop, soil, climate, and terrain characteristics. This study aims to delineate MZs by means of geostatistical and fuzzy clustering algorithms considering remotely sensed and laboratory data and, subsequently, to compare the zone maps in the north-eastern Himalayan region of India. For this study, 896 grid-wise representative soil samples (0–25 cm depth) were collected from the study area (1615 km2). The soils were analysed for soil reaction (pH), soil organic carbon and available macro (N, P and K) and micronutrients (Fe, Mn, Zn and Cu). The predicted soil maps were developed using regression kriging, where 28 digital elevation model-derived terrain attributes and two vegetation derivatives were used as environmental covariates. The coefficient of determination (R2) and root mean square error were used to evaluate the model’s performance. The predicted soil parameters were accurate, and regression kriging identified the highest variability for the majority of the soil variables. Further, to define the management zones, the geographically weighted principal component analysis and possibilistic fuzzy c-means clustering method were employed, based on which the optimum clusters were identified by employing fuzzy performance index and normalized classification entropy. The management zones were constructed considering the total pixel points of 30 m spatial resolution (17, 86,985 data points). The area was divided into four distinct zones, which could be differently managed. MZ 1 covers the maximum (43.3%), followed by MZ 2 (29.4%), MZ 3 (27.0%) and MZ 4 (0.3%). The MZs map thus would not only serve as a guide for judicious location-specific nutrient management, but would also help the policymakers to bring sustainable changes in the north-eastern Himalayan region of India.

The present study investigates the potential ameliorative role of seven secondary metabolites, viz., ascorbate (AsA), reduced glutathione (GSH), jasmonic acid (JA), salicylic acid (SA), serotonin (5-HT), indole–3–acetic acid (IAA) and gibberellic acid (GA3), for mitigation of aluminium (Al3+) and manganese (Mn2+) stress associated with acidic soils in rice, maize and wheat. The dehydroascorbate reductase (DHAR) and mono-dehydroascorbate reductase (MDHAR) of the cereals were used as model targets, and the analysis was performed using computational tools. Molecular docking approach was employed to evaluate the interaction of these ions (Al3+ and Mn2+) and the metabolites at the active sites of the two target enzymes. The results indicate that the ions potentially interact with the active sites of these enzymes and conceivably influence the AsA–GSH cycle. The metabolites showed strong interactions at the active sites of the enzymes. When the electrostatic surfaces of the metabolites and the ions were generated, it revealed that the surfaces overlap in the case of DHAR of rice and wheat, and MDHAR of rice. Thus, it was hypothesized that the metabolites may prevent the interaction of ions with the enzymes. This is an interesting approach to decipher the mechanism of action of secondary metabolites against the metal or metalloid - induced stress responses in cereals by aiming at specific targets. The findings of the present study are reasonably significant and may be the beginning of an interesting and useful approach towards comprehending the role of secondary metabolites for stress amelioration and mitigation in cereals grown under acidic soil conditions.

Swarmalators are entities with the simultaneous presence of swarming and synchronization that reveal emergent collective behavior due to the fascinating bidirectional interplay between phase and spatial dynamics. Although different coupling topologies have already been considered, here we introduce time-varying competitive phase interaction among swarmalators where the underlying connectivity for attractive and repulsive coupling varies depending on the vision (sensing) radius. Apart from investigating some fundamental properties like conservation of center of position and collision avoidance, we also scrutinize the cases of extreme limits of vision radius. The concurrence of attractive–repulsive competitive phase coupling allows the exploration of diverse asymptotic states, like static π , and mixed phase wave states, and we explore the feasible routes of those states through a detailed numerical analysis. In sole presence of attractive local coupling, we reveal the occurrence of static cluster synchronization where the number of clusters depends crucially on the initial distribution of positions and phases of each swarmalator. In addition, we analytically calculate the sufficient condition for the emergence of the static synchronization state. We further report the appearance of the static ring phase wave state and evaluate its radius theoretically. Finally, we validate our findings using Stuart–Landau oscillators to describe the phase dynamics of swarmalators subject to attractive local coupling.

Relay synchronization in multi-layer networks implies inter-layer synchronization between two indirectly connected layers through a relay layer. In this work, we study the relay synchronization in a three-layer multiplex network by introducing degree-based weighting mechanisms. The mechanism of within-layer connectivity may be hubs-repelling or hubs-attracting whenever low-degree or high-degree nodes receive strong influence. We adjust the remote layers to hubs-attracting coupling, whereas the relay layer may be unweighted, hubs-repelling, or hubs-attracting network. We establish that relay synchronization is improved when the relay layer is hubs-repelling compared to the other cases. We determine analytically necessary stability conditions of relay synchronization state using the master stability function approach. Finally, we explore the relation between synchronization and the topological property of the relay layer. We find that a higher clustering coefficient hinders synchronizability, and vice versa. We also look into the intra-layer synchronization in the proposed weighted triplex network and establish that intra-layer synchronization occurs in a wider range when relay layer is hubs-attracting.

Abstract Chimera states, namely complex spatiotemporal patterns that consist of coexisting domains of spatially coherent and incoherent dynamics, are investigated in a network of coupled identical oscillators. These intriguing spatiotemporal patterns were first reported in nonlocally coupled phase oscillators, and it was shown that such mixed type behavior occurs only for specific initial conditions in nonlocally and globally coupled networks. The influence of initial conditions on chimera states has remained a fundamental problem since their discovery. In this report, we investigate the robustness of chimera states together with incoherent and coherent states in dependence on the initial conditions. For this, we use the basin stability method which is related to the volume of the basin of attraction, and we consider nonlocally and globally coupled time-delayed Mackey-Glass oscillators as example. Previously, it was shown that the existence of chimera states can be characterized by mean phase velocity and a statistical measure, such as the strength of incoherence, by using well prepared initial conditions. Here we show further how the coexistence of different dynamical states can be identified and quantified by means of the basin stability measure over a wide range of the parameter space.

Sustainability and climate change are the two major challenges to the agricultural production system. The trade-off between them is essential for higher profitability. The energy assessment is essential for judging the sustainability and vulnerability of a production system. Besides, nutrient management and weed management are equally imperative to sustainability. Thus, the present study was executed to assess the energy balance, key energy indicators and profitability of rice–maize–green gram system under different nutrient and weed management practices. Application of Brassicaceous seed meal (BSM) along with mineral fertilizer attributed the highest rice (5.62 t ha−1) and maize (6.48 t ha−1) yield which was 11.6%, 8.3% and 3.7% in maize and 10.0%, 6.2% and 8.7% in rice for the conjoint application with vermicompost, farmyard manure (FYM) and neem cake, respectively. Moreover, BSM recorded the highest net energy gain, energy use efficiency and energy efficiency ratio and the lowest specific energy in all the crops. Application of pre-emergence herbicides followed by hoeing was found to be best in all respects including yield, profitability, energy use efficiency, energy effectiveness, etc. The appropriate combination of integrated nutrient management with BSM and pre-emergence herbicide application followed by hoeing provided an additional advantage not only in terms of yield but also an efficient use of energy, profitability and environmental safety. BSM and neem cake could be the alternative organic manure in the integrated nutrient-cum-weed management module and they could be able to compensate the paucity of FYM and vermicompost in the country.

Increasing productivity of maize while decreasing production costs and maintaining soil health are emerging challenges for the rice–maize system in South Asia. A range of integrated nutrient and weed management practices were tested in winter maize for their effects on yield, profitability, and soil health. The nutrient management treatments were a partial substitution of nitrogen with bulky (Farmyard manure; vermicompost) and concentrated organic manures (Brassicaceous seed meal, BSM; neem cake), whereas weed management practices compared chemical controls only versus an integrated approach. The N supplementation through BSM diminished the weed growth by reducing weed N uptake, and enhanced the maize crop uptake of nutrients. As compared to the sole chemical approach, atrazine-applied pre-emergence followed by hoeing reduced weed density by 58 and 67% in years 1 and 2, respectively. The N supplementation through BSM resulted in the maximum yield of maize grain (6.13 and 6.50 t ha−1 in year 1 and year 2, respectively) and this treatment increased yield in year 2 compared to N application through synthetic fertilizer. Hoeing in conjugation with herbicide enhanced the maize grain yield by 9% over herbicide alone. The maximum net return and economic efficiency were achieved with the application of BSM for N supplementation, together with the integrated weed management practice.

Declining rate of productivity and environmental sustainability is forcing growers to use organic manures as a source of nutrient supplement in maize farming. However, weed is a major constraint to maize production. A field study was carried out over two seasons to evaluate various integrated nutrient and weed management practices in hybrid maize. The treatment combinations comprised of supplementation of inorganic fertilizer (25% nitrogen) through bulky (Farmyard manure and vermicompost) and concentrated (Brassicaceous seed meal (BSM) and neem cake (NC)) organic manures and different mode of weed management practices like chemical (atrazine 1000 g ha−1) and integrated approach (atrazine 1000 g ha−1 followed by mechanical weeding). Repeated supplementation of nitrogen through concentrated organic manures reduced the density and biomass accumulation of most dominant weed species, Anagalis arvensis by releasing allelochemicals into the soil. But organic manures had no significant impact on restricting the growth of bold seeded weeds like Vicia hirsuta and weed propagated through tubers i.e., Cyperus rotundus in maize. By restricting the weed growth and nutrient removal by most dominating weeds, application of BSM enhanced the growth and yield of maize crop. Repeated addition of organic manures (BSM) enhanced the maize grain yield by 19% over sole chemical fertilizer in the second year of study. Application of atrazine as pre-emergence (PRE) herbicide significantly reduced the density of A. arvensis, whereas integration of mechanical weeding following herbicide controlled those weeds which were not usually controlled with the application of atrazine. As a result, atrazine at PRE followed by mechanical weeding produced the highest maize grain yield 6.81 and 7.10 t/ha in the first year and second year of study, respectively.

Evolutionary game theory in the realm of network science appeals to a lot of research communities, as it constitutes a popular theoretical framework for studying the evolution of cooperation in social dilemmas. Recent research has shown that cooperation is markedly more resistant in interdependent networks, where traditional network reciprocity can be further enhanced due to various forms of interdependence between different network layers. However, the role of mobility in interdependent networks is yet to gain its well-deserved attention. Here we consider an interdependent network model, where individuals in each layer follow different evolutionary games, and where each player is considered as a mobile agent that can move locally inside its own layer to improve its fitness. Probabilistically, we also consider an imitation possibility from a neighbor on the other layer. We show that, by considering migration and stochastic imitation, further fascinating gateways to cooperation on interdependent networks can be observed. Notably, cooperation can be promoted on both layers, even if cooperation without interdependence would be improbable on one of the layers due to adverse conditions. Our results provide a rationale for engineering better social systems at the interface of networks and human decision making under testing dilemmas.

Interactions amongst agents frequently exist only at particular moments in time, depending on their closeness in space and movement parameters. Here we propose a minimal model of moving agents where the network of contacts changes over time due to their motion. In particular, agents interact based on their proximity in a two-dimensional space, but only if they belong to the same fixed interaction zones. Our research reveals the emergence of global synchronization if all the interaction zones are attractive. However, if some of the interaction zones are repulsive, they deflect synchrony and lead to short-lasting but recurrent deviations that constitute extreme events in the network. We use two paradigmatic oscillators for the description of the agent dynamics to demonstrate our findings numerically, and we also provide an analytical formulation to describe the emergence of complete synchrony and the thresholds that distinguish extreme events from other intermittent states based on the peak-over-threshold approach.

In direct seeded rice (DSR) cultivation, weed is the major constraint mainly due to absence of puddling in field. The yield loss due to weed interference is huge, may be up to 100%. In this perspective, the present experiment was conducted to study the efficacy of selected herbicides, and to predict the rice yield using artificial neural network (ANN) models. The dry weight and density of weeds were recorded at different growth stages and consequently herbicidal efficacy was evaluated. Experimental results revealed that pre-emergence (PRE) herbicide effectively controlled the germination of grassy weeds. Application bispyribac-sodium as post-emergence (POST) following PRE herbicides (clomazone or pendimethalin) or as tank-mixture with clomazone effectively reduced the density and biomass accumulation of diverse weed flora in DSR. Herbicidal treatments improved the plant height, yield attributes and grain yield (2.7 to 5.5 times) over weedy check. The sensitivity of the best ANN model clearly depicts that the weed control index (WCI) of herbicides was most important than their weed control efficiency (WCE). Besides, the early control of weeds is a better prescription to improve rice yield. Differences in sensitivity values of WCI and WCE across the crop growth stages also suggest that at 15, 30 and 60 days after sowing, herbicides most effectively controlled sedges, broad leaves and grasses, respectively. Based on the grain yield and herbicidal WCE, it can be concluded that the combined application of pendimethalin or clomazone as PRE followed by bispyribac-sodium as POST or tank-mixture of clomazone + bispyribac sodium can effectively control different weed flushes throughout the crop growth period in DSR.

We propose a nonlinear active observer based generalized synchronization scheme for multiparameter estimation in time-delayed systems with periodic time delay. A sufficient condition for parameter estimation is derived using Krasovskii-Lyapunov theory. The suggested tool proves to be globally and asymptotically stable by means of Krasovskii-Lyapunov method. With this effective method, parameter identification and generalized synchronization of modulated time-delayed systems with all the system parameters unknown, can be achieved simultaneously. We restrict our study for multiple parameter estimation in modulated time-delayed systems with single state variable only. Theoretical proof and numerical simulation demonstrate the effectiveness and feasibility of the proposed technique. The block diagram of electronic circuit for multiple time delay system shows that the method is easily applicable in practical communication problems.