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Abstract This study examines the operational parameters of field-effect transistors (FETs) using single-gate (SG) and double-gate (DG) graphene nanoribbons (GNRs) within the analog/RF domain. A detailed exploration is conducted through an atomistic p z orbital model, derived from the Hamiltonian of graphene nanoribbons, employing the nonequilibrium Green’s function formalism (NEGF) for analysis. The atomic characteristics of the GNRFETs channel are accurately described by utilizing a tight-binding Hamiltonian with an atomistic p z orbital basis set. The primary focus of the analysis revolves around essential analog/RF parameters such as transconductance, transconductance generation factor (TGF), output resistance, early voltage, intrinsic gain, gate capacitance, cut-off frequency, and transit time. Furthermore, the study assesses the gain frequency product (GFP), transfer frequency product (TFP), and gain transfer frequency product (GTFP) to evaluate the balance between transistor efficiency, gain, and cut-off frequency. The research outcomes indicate that double-gate GNRFETs exhibit superior analog/RF performance in comparison to their single-gate counterparts. However, both types of devices demonstrate cut-off frequencies in the gigahertz range. The extensive data presented in this study provides valuable insights into the characteristics of SG and DG GNRFETs, particularly in terms of the figure-of-merit (FoM) for analog/RF performance, offering a comprehensive analysis of the trade-offs in analog applications. In addition, the analysis has been extended be performing a high-performance hybrid 6T static random-access memory (SRAM) to get the impact in their circuit level variation as well as improvement in their circuit performance.

Abstract Aviation emissions of soot and nitrogen oxides are strictly regulated as they adversely impact human health and the environment. Jet fuel combustion conditions that decrease one pollutant concentration increase the other. Although it is not impossible to achieve both low soot and NOx through clever design, it is hard to simultaneously reduce both. Although it is difficult to study such conditions due to high temperatures and gas flowrates of aircraft engines, recently it was shown that Enclosed Spray Combustion (ESC) of jet fuel results in soot with similar characteristics to that from aircrafts making ESC an attractive unit for studying aviation-like emissions. Furthermore, judicious swirl-injection of air downstream of the ESC burner drastically reduces soot emissions. Here the trade-off between NO and soot emissions during combustion of jet fuel is studied for the first time, to the best of our knowledge, accounting for the detailed structure of soot. Injecting air shortly after the ESC burner decreases soot but increases NO emissions, while such injection further downstream has the inverse outcome. This interplay between soot and NO emissions was correlated quantitatively with the gas temperature shortly after air injection. Consequently, combustion conditions for an optimal trade-off between soot and NO emissions for the ESC conditions studied here are identified that are at or below the lowest NOx emissions per unit mass of fuel from existing aircraft engines.

Abstract Electric vehicles are considered as an emerging solution to mitigate the environmental footprint of transportation sector. Therefore, researchers and automotive developers devote significant efforts to enhance the performance of electric vehicles to promote broader adoption of such technology. One of the critical challenges of the electric vehicle is limited battery lifetime and entailed range anxiety. In his context, development of counter-aging control strategies based on precise battery modeling is regarded as an emerging approach that has a significant potential to address battery degradation challenges. This paper presents a combined trade-off strategy to minimize battery degradation while maintaining acceptable driving performance and charge retention in electric vehicles. A battery aging model has been developed and integrated into a full vehicle model. An optimal control problem has been formulated to tackle the afore-mentioned challenges. Non-dominant sorting genetic algorithms have been implemented to yield the optimal solution through the Pareto-front of three contending objectives, based upon which an online simulation has been conducted considering three standard driving cycles. The results reveal the ability of the proposed strategy to prolong the life cycle of the battery and extend the driving range by 25 % and 8 % respectively with minimal influence of 0.6 % on the driveability.

Abstract XynR is a thermostable alkaline GH10 xylanase, for which we have previously examined the effects of saturation mutagenesis at position 315 on enzyme alkaliphily, and found that at pH 10, the activities of variants could be ordered as follows: T315Q > T315S = T315N > T315H = wild-type XynR (WT) > 15 other variants. In this study, we sought to elucidate the mechanisms underlying the variable activity of these different variants. Crystallographic analysis revealed that the Ca2+ ion near position 315 in WT was absent in the T315Q variant. We accordingly hypothesized that the enhancement of alkaliphily in T315Q, and probably also in the T315H, T315N, and T315S variants, could be ascribed to an activity-stability trade-off associated with a reduction in stability due to the lack of this Ca2+ ion. Consistent with expectations, the alkaline resistance of T315H, T315N, T315Q, and T315S, evaluated through the pH-dependence of stability at 0 mM CaCl2 under alkaline conditions, was found to be lower than that of WT: the residual activity at pH 11 of WT was 78% while those of T315H, T315N, T315Q, and T315S were 0, 9, 0, and 43%, respectively. In addition, the thermostabilities of these four variants, as assessed using the denaturing temperatures (T m) at 0 mM CaCl2 based on ellipticity at 222 nm in circular dichroism measurements, were lower than that of WT by 2–8 °C. Furthermore, the T m values of WT and variants at 5 mM CaCl2 were higher than those at 0 mM CaCl2 by 6–11 °C. Collectively, our findings in this study indicate that mutation of the T residue at position 315 of XynR to H, N, Q, and S causes an increase in the alkaliphily of this enzyme, thereby reducing its stability.

Abstract Trillium govanianum is traditionally used to treat innumerable alignments like sexual disorders, cancer, inflammation etc. Mainly rhizomes of T. govanianum have been explored for phytochemical profiling but comprehensive metabolomics of other parts has not been yet deeply investigated. Thus, current study was aimed for organs-specific (roots, rhizomes, rhizomatous buds, stems, leaves, and fruits) phytochemical profiling of T. govanianum via metabolomics approach. Targeted (steroidal saponins and free sugars) and non-targeted metabolomics were performed by UPLC-PDA/ELSD & UHPLC-Q-TOF-IMS. Among steroidal compounds, 20-hydroxyecdysone, pennogenin-3-O-β-chacotrioside, dioscin were found predominantly in all samples while diosgenin was identified only in rhizomes. Further, four free sugars viz. 2-deoxyribose (116.24 ± 1.26 mg/g: leaves), fructose (454.76 ± 12.14 mg/g: rhizomes), glucose (243.21 ± 7.53 mg/g: fruits), and galactose (69.06 ± 2.14 mg/g: fruits) were found significant in respective parts of T. govanianum. Elemental analysis of targeted samples was determined by atomic absorption spectrophotometer. Heavy metals (Cd, Hg, Pd, As) were absent while micro- (Mn, Na, Zn, Cu) and macro- (Ca, Fe, Mg, K) elements were found in all samples. Furthermore, UHPLC-Q-TOF-IMS had identified 103 metabolites based on their mass fragmentation patterns and 839 were tentatively predicted using METLIN database. The multivariate statistical analysis showed organs specific clustering and variance of metabolites. Apart from this, extracts were evaluated for in vitro anticholinesterase activity, and found potentials inhibitors with IC50 values 2.02 ± 0.15 to 27.65 ± 0.89 mg/mL and 3.58 ± 0.12 to 16.81 ± 2.48 mg/mL of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzyme, respectively. Thus, comprehensive metabolomics and anti-cholinesterase activity of different parts of T. govanianum would lay the foundation for improving medicinal importance and health benefits of T. govanianum.

Abstract The actualization of high strength and ductility in alloys, in addition to providing strong, formable materials, can lead to reduced weights in practical applications. However, increasing strength typically comes at the cost of lowering the ductility and vice-versa, referred to as the strength–ductility trade-off. In this work, we investigate the thermo-mechanical response of a 3-element multifunctional NiTi–Nb nanocomposite material that overcomes this trade-off, as it exhibits a high strength of 980 MPa and an ultrahigh ductility of 58% at fracture. The remarkable properties are attributed to the underlying microstructure of Nb nanofibers dispersed in an NiTi matrix. Deformation is accommodated via the shape memory transformation of the active NiTi matrix in concert with elastoplastic deformation of Nb nanofibers embedded within the matrix. Consequently, the material exhibits multifunctionality and recovers deformation during heating via the reversion of the stress-induced martensitic transformation in the NiTi matrix. The high strength and high ductility of this 3-element nanocomposite material puts it amongst the best performing high-entropy alloys (HEAs) that are typically made up of five or more elements.

Abstract Anguilliform swimmers, like eels or lampreys, are highly efficient swimmers. Key to understanding their performances is the relationship between the body’s kinematics and resulting swimming speed and efficiency. But, we cannot prescribe kinematics to living fish, and it is challenging to measure their power consumption. Here, we characterise the swimming speed and cost of transport of a free-swimming undulatory bio-inspired robot as we vary its kinematic parameters, including joint amplitude, body wavelength, and frequency. We identify a trade-off between speed and efficiency. Speed, in terms of stride length, increases for increasing maximum tail angle, described by the newly proposed specific tail amplitude and reaches a maximum value around the specific tail amplitude of unity. Efficiency, in terms of the cost of transport, is affected by the whole-body motion. Cost of transport decreases for increasing travelling wave-like kinematics, and lower specific tail amplitudes. Our results suggest that live eels tend to choose efficiency over speed and provide insights into the key characteristics affecting undulatory swimming performance.

Abstract Lodging of cereal crops significantly reduces grain yield and quality, making lodging resistance a prime target for breeding programs. However, lodging resistance among different rice (Oryza sativa L.) cultivars in the field remains largely unknown, as is the relationship between the major properties of culms such as their morphological and mechanical properties. Here, we investigated the morphological and mechanical properties of 12 rice cultivars by considering different internodes within culms. We detected variation in these two traits among cultivars: one set of cultivars had thicker but softer culms (thickness-type), while the other set of cultivars showed stiffer but thinner culms (stiffness-type). We designate this variation as a thickness-stiffness trade-off. We then constructed a mechanical model to dissect the mechanical and/or morphological constraints of rice culms subjected to their own weight (self-weight load). Through modeling, we discovered that ear weight and the morphology of the highest internode were important for reducing deflection, which may be important factors to achieve higher lodging resistance. The mechanical theory devised in this study could be used to predict the deflection of rice culms and may open new avenues for novel mechanics-based breeding techniques.

Abstract The analysis of the relationship between time and cost is a crucial aspect of construction project management. Various optimization techniques have been developed to solve time–cost trade-off problems. A hybrid multi-verse optimizer model (hDMVO) is introduced in this study, which combines the multi-verse optimizer (MVO) and the sine cosine algorithm (SCA) to address the discrete time–cost trade-off problem (DTCTP). The algorithm's optimality is evaluated by using 23 well-known benchmark test functions. The results demonstrate that hDMVO is competitive with MVO, SCA, the dragonfly algorithm and ant lion optimization. The performance of hDMVO is evaluated using four benchmark test problems of DTCTP, including two medium-scale instances (63 activities) and two large-scale instances (630 activities). The results indicate that hDMVO can provide superior solutions in the time–cost optimization of large-scale and complex projects compared to previous algorithms.

Abstract When exposed to perceptual and motor sequences, people are able to gradually identify patterns within and form a compact internal description of the sequence. One proposal of how sequences can be compressed is people’s ability to form chunks. We study people’s chunking behavior in a serial reaction time task. We relate chunk representation with sequence statistics and task demands, and propose a rational model of chunking that rearranges and concatenates its representation to jointly optimize for accuracy and speed. Our model predicts that participants should chunk more if chunks are indeed part of the generative model underlying a task and should, on average, learn longer chunks when optimizing for speed than optimizing for accuracy. We test these predictions in two experiments. In the first experiment, participants learn sequences with underlying chunks. In the second experiment, participants were instructed to act either as fast or as accurately as possible. The results of both experiments confirmed our model’s predictions. Taken together, these results shed new light on the benefits of chunking and pave the way for future studies on step-wise representation learning in structured domains.

Abstract Animals run robustly in diverse terrain. This locomotion robustness is puzzling because axon conduction velocity is limited to a few tens of meters per second. If reflex loops deliver sensory information with significant delays, one would expect a destabilizing effect on sensorimotor control. Hence, an alternative explanation describes a hierarchical structure of low-level adaptive mechanics and high-level sensorimotor control to help mitigate the effects of transmission delays. Motivated by the concept of an adaptive mechanism triggering an immediate response, we developed a tunable physical damper system. Our mechanism combines a tendon with adjustable slackness connected to a physical damper. The slack damper allows adjustment of damping force, onset timing, effective stroke, and energy dissipation. We characterize the slack damper mechanism mounted to a legged robot controlled in open-loop mode. The robot hops vertically and planarly over varying terrains and perturbations. During forward hopping, slack-based damping improves faster perturbation recovery (up to 170%) at higher energetic cost (27%). The tunable slack mechanism auto-engages the damper during perturbations, leading to a perturbation-trigger damping, improving robustness at a minimum energetic cost. With the results from the slack damper mechanism, we propose a new functional interpretation of animals’ redundant muscle tendons as tunable dampers.

Abstract This study presents the Slime Mold Algorithm (SMA) to solve the time—cost—quality trade-off problem in a construction project. The proposed SMA is a flexible and efficient algorithm in exploration and exploitation to reach the best optimal solution to process the input model’s data. This paper aims to discuss and solve the optimization problem and compare the evaluation with other algorithms such as Opposition-based Multiple Objective Differential Evolution, Non-dominated sorting genetic algorithm, Multiple objective particle swarm optimization, Multiple objective differential evolution and Chaotic initialized multiple objective differential evolution (CAMODE) to verify the efficiency and potential of the proposed algorithm. According to the analysis results, the SMA model generated a diversification measure for case studies, producing superior outcomes to those of previous algorithms.

Trillium govanianum is traditionally used to treat innumerable alignments like sexual disorders, cancer, inflammation etc. Mainly rhizomes of T. govanianum have been explored for phytochemical profiling but comprehensive metabolomics of other parts has not been yet deeply investigated. Thus, current study was aimed for organs-specific (roots, rhizomes, rhizomatous buds, stems, leaves, and fruits) phytochemical profiling of T. govanianum via metabolomics approach. Targeted (steroidal saponins and free sugars) and non-targeted metabolomics were performed by UPLC-PDA/ELSD & UHPLC-Q-TOF-IMS. Among steroidal compounds, 20-hydroxyecdysone, pennogenin-3-O-β-chacotrioside, dioscin were found predominantly in all samples while diosgenin was identified only in rhizomes. Further, four free sugars viz. 2-deoxyribose (116.24 ± 1.26 mg/g: leaves), fructose (454.76 ± 12.14 mg/g: rhizomes), glucose (243.21 ± 7.53 mg/g: fruits), and galactose (69.06 ± 2.14 mg/g: fruits) were found significant in respective parts of T. govanianum. Elemental analysis of targeted samples was determined by atomic absorption spectrophotometer. Heavy metals (Cd, Hg, Pd, As) were absent while micro- (Mn, Na, Zn, Cu) and macro- (Ca, Fe, Mg, K) elements were found in all samples. Furthermore, UHPLC-Q-TOF-IMS had identified 103 metabolites based on their mass fragmentation patterns and 839 were tentatively predicted using METLIN database. The multivariate statistical analysis showed organs specific clustering and variance of metabolites. Apart from this, extracts were evaluated for in vitro anticholinesterase activity, and found potentials inhibitors with IC 50 values 2.02 ± 0.15 to 27.65 ± 0.89 mg/mL and 3.58 ± 0.12 to 16.81 ± 2.48 mg/mL of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzyme, respectively. Thus, comprehensive metabolomics and anti-cholinesterase activity of different parts of T. govanianum would lay the foundation for improving medicinal importance and health benefits of T. govanianum., (© 2024. The Author(s).)

Abstract High strength steels are becoming more important than ever before for automotive applications to reduce the weight of automobiles and to ensure the safety of passengers. Since increased strength usually results in degraded formability, however, cold forming of high strength steels into final shapes remains a challenge to both automotive manufacturers and suppliers. Here we report novel alloy and processing design concepts that can impart high strength to cold-formable steels, which deviates from the traditional approach of improving the formability of high strength steels. Such designed steel subjected to a designed processing route shows an excellent combination of formability and strength as well as crashworthiness, which is crucial for the safety of passengers in the automobiles. The alloy and processing design concepts used in the present study are based on the utilization of thermally induced austenite to martensite transformation, which imparts high strength to cold-formable austenite by cryogenic treatment.

Abstract Artificial feedforward neural networks perform a wide variety of classification and function approximation tasks with high accuracy. Unlike their artificial counterparts, biological neural networks require a supply of adequate energy delivered to single neurons by a network of cerebral microvessels. Since energy is a limited resource, a natural question is whether the cerebrovascular network is capable of ensuring maximum performance of the neural network while consuming minimum energy? Should the cerebrovascular network also be trained, along with the neural network, to achieve such an optimum? In order to answer the above questions in a simplified modeling setting, we constructed an Artificial Neurovascular Network (ANVN) comprising a multilayered perceptron (MLP) connected to a vascular tree structure. The root node of the vascular tree structure is connected to an energy source, and the terminal nodes of the vascular tree supply energy to the hidden neurons of the MLP. The energy delivered by the terminal vascular nodes to the hidden neurons determines the biases of the hidden neurons. The “weights” on the branches of the vascular tree depict the energy distribution from the parent node to the child nodes. The vascular weights are updated by a kind of “backpropagation” of the energy demand error generated by the hidden neurons. We observed that higher performance was achieved at lower energy levels when the vascular network was also trained along with the neural network. This indicates that the vascular network needs to be trained to ensure efficient neural performance. We observed that below a certain network size, the energetic dynamics of the network in the per capita energy consumption vs. classification accuracy space approaches a fixed-point attractor for various initial conditions. Once the number of hidden neurons increases beyond a threshold, the fixed point appears to vanish, giving place to a line of attractors. The model also showed that when there is a limited resource, the energy consumption of neurons is strongly correlated to their individual contribution to the network’s performance.

Abstract Countries worldwide have adopted various strategies to minimize the socio-economic impact of the ongoing COVID-19 pandemic. Stringency of imposed measures universally reflects the standpoint from which protecting public health and avoiding damage to economy are seen as contradictory objectives. Based on epidemic trajectories of 25 highly developed countries and 10 US states in the (mobility reduction)–(reproduction number) plane we showed that delay in imposition of nation-wide quarantine elevates the number of infections and deaths, surge of which inevitably has to be suppressed by stringent and sustained lockdown. As a consequence, cumulative mobility reduction and population-normalized cumulative number of COVID-19-associated deaths are significantly correlated and this correlation increases with time. Overall, we demonstrated that, as long as epidemic suppression is the aim, the trade-off between the death toll and economic loss is illusory: high death toll correlates with deep and long-lasting lockdown causing a severe economic downturn.

Lodging of cereal crops significantly reduces grain yield and quality, making lodging resistance a prime target for breeding programs. However, lodging resistance among different rice (Oryza sativa L.) cultivars in the field remains largely unknown, as is the relationship between the major properties of culms such as their morphological and mechanical properties. Here, we investigated the morphological and mechanical properties of 12 rice cultivars by considering different internodes within culms. We detected variation in these two traits among cultivars: one set of cultivars had thicker but softer culms (thickness-type), while the other set of cultivars showed stiffer but thinner culms (stiffness-type). We designate this variation as a thickness-stiffness trade-off. We then constructed a mechanical model to dissect the mechanical and/or morphological constraints of rice culms subjected to their own weight (self-weight load). Through modeling, we discovered that ear weight and the morphology of the highest internode were important for reducing deflection, which may be important factors to achieve higher lodging resistance. The mechanical theory devised in this study could be used to predict the deflection of rice culms and may open new avenues for novel mechanics-based breeding techniques., (© 2023. The Author(s).)

Abstract In a volatile environment where rewards are uncertain, successful performance requires a delicate balance between exploitation of the best option and exploration of alternative choices. It has theoretically been proposed that dopamine contributes to the control of this exploration-exploitation trade-off, specifically that the higher the level of tonic dopamine, the more exploitation is favored. We demonstrate here that there is a formal relationship between the rescaling of dopamine positive reward prediction errors and the exploration-exploitation trade-off in simple non-stationary multi-armed bandit tasks. We further show in rats performing such a task that systemically antagonizing dopamine receptors greatly increases the number of random choices without affecting learning capacities. Simulations and comparison of a set of different computational models (an extended Q-learning model, a directed exploration model, and a meta-learning model) fitted on each individual confirm that, independently of the model, decreasing dopaminergic activity does not affect learning rate but is equivalent to an increase in random exploration rate. This study shows that dopamine could adapt the exploration-exploitation trade-off in decision-making when facing changing environmental contingencies.

Abstract The development of new materials with reduced noise and vibration levels is an active area of research due to concerns in various aspects of environmental noise pollution and its effects on health. Excessive vibrations also reduce the service live of the structures and limit the fields of their utilization. In oscillations, the viscoelastic moduli of a material are complex and it is their loss part – the product of the stiffness part and loss tangent – that is commonly viewed as a figure of merit in noise and vibration damping applications. The stiffness modulus and loss tangent are usually mutually exclusive properties so it is a technological challenge to develop materials that simultaneously combine high stiffness and high loss. Here we achieve this rare balance of properties by filling a solid polymer matrix with rigid inorganic spheres coated by a sub-micron layer of a viscoelastic material with a high level of internal friction. We demonstrate that this combination can be experimentally realised and that the analytically predicted behaviour is closely reproduced, thereby escaping the often termed ‘Ashby’ limit for mechanical stiffness/damping trade-off and offering a new route for manufacturing advanced composite structures with markedly reduced noise and vibration levels.

Abstract Investigating the expression of trade-offs between key life-history functions is central to our understanding of how these functions evolved and are maintained. However, detecting trade-offs can be challenging due to variation in resource availability, which masks trade-offs at the population level. Here, we investigated in the European earwig Forficula auricularia whether (1) weapon size trades off with three key immune parameters – hemocyte concentration, phenoloxidase and prophenoloxidase activity - and whether (2) expression and strength of these trade-offs depend on male body condition (body size) and/or change after an immune challenge. Our results partially confirmed condition dependent trade-offs between weapon size and immunity in male earwigs. Specifically, we found that after an immune challenge, weapon size trades off with hemocyte concentrations in low-condition, but not in good-condition males. Contrastingly, weapon size was independent of pre-challenge hemocyte concentration. We also found no trade-off between weapon size and phenoloxidase activity, independent of body condition and immune challenge. Overall, our study reveals that trade-offs with sexual traits may weaken or disappear in good-condition individuals. Given the importance of weapon size for male reproductive success, our results highlight how low-condition individuals may employ alternative life-history investment strategies to cope with resource limitation.

Abstract The Aral Sea, located in Central Asia, has undergone significant reduction in surface area owing to the combined impacts of climate change and human activities. This reduction has led to a regional ecological crisis and profound repercussions on ecosystem services. Investigating the spatiotemporal variations and synergistic trade-offs of ESs in the Aral Sea basin is crucial for fostering the integrated development of the region’s socioeconomic ecology. This study utilizes the Future Land-Use Simulation and InVEST models to analyze future land-use scenarios, integrating CMIP6 projections to assess the quality of four key ecosystem services: water production, soil conservation, carbon storage, and habitat quality over two timeframes: the historical period (1995–2020) and the projected future (2021–2100). Employing Spearman correlation, the study explores the trade-offs and synergies among these ecosystem services. Findings reveal that the primary forms of land-use change in the Aral Sea basin are the reduction in water area (− 49.59%) and the rapid expansion of urban areas (+ 504.65%). Temporally, habitat quality exhibits a declining trend, while carbon storage shows an increasing trend, and water production and soil retention fluctuate initially decreasing and then increasing. Spatially, water production and carbon storage demonstrate an increasing trend from the northwest to the southeast. Habitat quality exhibits a higher spatial pattern in the southeast and south, contrasting with lower spatial patterns in the north and west. Low-level soil conservation is predominantly distributed in the northwest, while medium to low-level soil conservation is prevalent in the east of the basin. The trade-off and synergy analysis indicates that between 1995 and 2020, a trade-off relationship existed between carbon storage and habitat quality and water production, whereas synergies were observed between soil conservation and carbon storage, water production and habitat quality, and soil conservation. The correlation between water production and soil conservation emerges as the strongest, whereas the correlation between carbon storage and habitat quality appears to be the weakest. The dynamic spatiotemporal changes, trade-offs, and collaborative relationships of ESs constitute major aspects of ecosystem service research, holding substantial implications for the effective management of the regional ecological environment.