Quantitative Relation Research Articles

The Opportunity of Cyanobacterial Sludge and Bagasse Biomass Energy in the Biggest Change in a Century

Through orthogonal test and single factor experiment, biochar (BC) was ready by exploitation cyanobacterial sludge and bagasse to explore the potential of changing completely different energy at different carbonization temperatures and the result of Cr(VI) removal by BC. Biochar was prepared from dried cyanobacterial sludge and bagasse under 500 °C, 400 °C and 300 °C at 3.0 h, 2.5 h and 2.0 h under high temperature limited oxygen, respectively. Orthogonal experiments were used to conduct L9(34) three-factor and three-level experiments. Combined with single factor experiments, the optimal combination conditions for Cr(VI) removal were explored. Solid-state energy mainly was in the form of biochar yield. Higher temperature and content of biochar from bagasse had lower solid-state energy by biochar yield (44.00%±0.35%). Cyanobacterial sludge has wide application prospect and nice potential and application prospect in energy conversion. The dismissal of Cr(VI) with biochar was the primary to extend, and so decrease with the rise of charring temperature. The highest expulsion of Cr(VI) was attained once the mass quantitative relation of mixed biochar was 3:1. With a charring time of 2.5 hours, a charring temperature of 400 °C, and a biochar mass quantitative relation of 3:1, up to 98% of Cr(VI) was removed most effectively. Medium temperature biochar and biochar prepared from the mixture of cyanobacteria sludge and bagasse are beneficial to the production of solid energy. Cyanobacterial sludge-based biochar has broad application prospects, especially in energy conversion. In the orthogonal experiment, the sequence of influences of various factors on Cr(VI) removal rate was as follows: carbonation temperature > carbonation time > biochar ratio. The following were the ideal conditions for removing Cr(VI) from biochar: acieration temperature (400 °C), acieration time (2.5 hours), and biochar mass-quantity ratio of 3:1.

A prediction tool for maintenance costs estimation during the design process of a ship engine room

When dealing with maintenance in ships engine room, the space available around machinery and systems (clearance) plays an important role and may significantly affect the cost of the maintenance intervention. In a first part of a current research study Gualeni et al. (Ship Technol Res, 10.1080/09377255.2021.2020949, 2022), a quantitative relation between the maintenance costs increment due to the clearance reduction is determined, using a Bayesian approach to General Linear Model (GLM), with reference to a single item/component of a larger system Sánchez-Herguedas et al. (Reliability Eng Syst Saf 207: 107394, 2021). This paper represents the second part of the activity and it enforces a systemic view over the whole machinery or system Sanders and Klein (Proc Comput Sci 8:413–419, 2012). The aim is to identify not only the relation between maintenance costs and clearance reduction, but also how the clearance reductions of the single components/items interact and affect the whole system/machinery accessibility and maintainability, meant as relevant emerging properties.The system emerging properties are investigated through the design and application of a Hidden Markov Model Salvatier et al. (Peer J Comput Sci 2: e55, 2016); i.e., the system is modeled by a Markov process with unobservable states. The sequence of states is the maintainability of the system (which incorporates each one of the single components) while the evidence is the increase in cost of maintenance related to the space reduction.By predicting a sequence of states, it is therefore possible to predict the interactions between the system components clearances and determine how the emerging maintainability property is affected by the engine room design.

Computational Modelling of Quantifier Use: Corpus, Models, and Evaluation

A prominent strand of work in formal semantics investigates the ways in which human languages quantify the elements of a set, as when we say All A are B, Few A are B, and so on. Building on a growing body of empirical studies that shed light on the meaning and the use of quantifiers, we extend this line of work by computationally modelling how human speakers textually describe complex scenes in which quantitative relations play an important role. To this end, we conduct a series of elicitation experiments in which human speakers were asked to perform a linguistic task that invites the use of quantified expressions. The experiments result in a corpus, called QTUNA, made up of short texts that contain a large variety of quantified expressions. We analyse QTUNA, summarise our findings, and explain how we design computational models of human quantifier use accordingly. Finally, we evaluate these models in accordance with QTUNA.

Protein Is an Intelligent Micelle.

Interpreting biological phenomena at the molecular and cellular levels reveals the ways in which information that is specific to living organisms is processed: from the genetic record contained in a strand of DNA, to the translation process, and then to the construction of proteins that carry the flow and processing of information as well as reveal evolutionary mechanisms. The processing of a surprisingly small amount of information, i.e., in the range of 1 GB, contains the record of human DNA that is used in the construction of the highly complex system that is the human body. This shows that what is important is not the quantity of information but rather its skillful use-in other words, this facilitates proper processing. This paper describes the quantitative relations that characterize information during the successive steps of the "biological dogma", illustrating a transition from the recording of information in a DNA strand to the production of proteins exhibiting a defined specificity. It is this that is encoded in the form of information and that determines the unique activity, i.e., the measure of a protein's "intelligence". In a situation of information deficit at the transformation stage of a primary protein structure to a tertiary or quaternary structure, a particular role is served by the environment as a supplier of complementary information, thus leading to the achievement of a structure that guarantees the fulfillment of a specified function. Its quantitative evaluation is possible via using a "fuzzy oil drop" (FOD), particularly with respect to its modified version. This can be achieved when taking into account the participation of an environment other than water in the construction of a specific 3D structure (FOD-M). The next step of information processing on the higher organizational level is the construction of the proteome, where the interrelationship between different functional tasks and organism requirements can be generally characterized by homeostasis. An open system that maintains the stability of all components can be achieved exclusively in a condition of automatic control that is realized by negative feedback loops. This suggests a hypothesis of proteome construction that is based on the system of negative feedback loops. The purpose of this paper is the analysis of information flow in organisms with a particular emphasis on the role of proteins in this process. This paper also presents a model introducing the component of changed conditions and its influence on the protein folding process-since the specificity of proteins is coded in their structure.

Hybrid event-triggered synchronization control of delayed chaotic neural networks against communication delay and random data loss

This paper investigates the network-based synchronization control of delayed chaotic neural networks. A new hybrid event-triggered communication scheme, which consists of fixed and dynamic triggering conditions, is presented to handle the random loss of triggered sampled-data. Under this scheme, a quantitative relation between the allowable data loss probability and the fixed triggering interval can be revealed. The synchronous error system is modeled by a multi-constrained system affected by nonlinear terms, piecewise input delay, stochastic update input and reset states. By using the boundary information and interrelation of both communication delay and input delay, a binary quadratic convex lemma and a tailored discontinuous augmented Lyapunov-Krasovskii functional approach are proposed to exploit delay-dependent synchronization criteria with less conservatism. Simulation results are provided for checking the merits of the obtained criteria.

Mesoscale simulation investigation of droplet impacting behaviors on cylindrical surfaces

Understanding and controlling the impacting behaviors of droplets on cylindrical surfaces is a key issue for the design of the process intensification in chemical reaction engineering. In the work, the mesoscale dynamics simulation is performed to systematically investigate the effect of impact conditions on the droplet impacting behaviors. As a result, five impacting modes have been distinguished and the competition mechanisms between the impact parameters are revealed. High impact velocity and low liquid viscosity benefit to the spreading and dispersion of impacting droplets, while the increase of surface wettability can promote and inhibit droplet spreading at low and high velocities, respectively. Besides, the machine-learning models are developed to build the quantitative relation between the impacting behaviors and the impact conditions. The machine-learning models can predict droplets impacting behaviors in experiment and simulation, which is of great importance in relevant chemical engineering applications.

Early-age hydration mechanism of ternary binders: Quantitative relation between microstructure evolution and strength build-up

The goal of this study is to develop a better understanding of the working mechanisms of CACC$ acceleration of OPC in the first hour and establish a quantitative link between the progress of hydration, strength build-up and associated microstructure evolution. Monitoring the progress of reaction using isothermal calorimetry in the first few minutes of hydration is difficult owing to the limitations associated with the measurement method. We have developed a method to correct the heat data in the first minutes, which along with ICP data of elements Ca, Al and S, enables a quantification of the amounts of various phases dissolving and/or precipitating at different times after acceleration. It is concluded that strength build-up is directly proportional to heat of hydration up to a certain point, irrespective of accelerator dosage. However, beyond this point, there is a change of mechanism which is likely attributed to physical effects rather than chemical ones. Additionally, it was also found that the amount of available CA controls the rate of reaction and that the impact of CAC addition to OPC follows a decay function type heat release.

Entanglement-interference complementarity and experimental demonstration in a superconducting circuit

Quantum entanglement between an interfering particle and a detector for acquiring the which-path information plays a central role for enforcing Bohr’s complementarity principle. However, the quantitative relation between this entanglement and the fringe visibility remains untouched upon for an initial mixed state. Here we find an equality for quantifying this relation. Our equality characterizes how well the interference pattern can be preserved when an interfering particle, initially carrying a definite amount of coherence, is entangled, to a certain degree, with a which-path detector. This equality provides a connection between entanglement and interference in the unified framework of coherence, revealing the quantitative entanglement-interference complementarity. We experimentally demonstrate this relation with a superconducting circuit, where a resonator serves as a which-path detector for an interfering qubit. The measured fringe visibility of the qubit’s Ramsey signal and the qubit-resonator entanglement exhibit a complementary relation, in well agreement with the theoretical prediction.

A Deep Reinforcement Learning-Based Intelligent Grid-Forming Inverter for Inertia Synthesis by Impedance Emulation

In this letter, impedance emulation is exploited for synthesizing inertia in autonomous microgrids. An intelligent grid-forming inverter (GFI) is proposed that facilitates sufficient degrees of freedom for adaptive impedance shaping. The latter adaptively changes the effective bandwidth of the inverter's voltage controller, in response to disturbances for inertia synthesis. Deep reinforcement learning is utilized to tackle the lack of explicit quantitative relation between impedance shaping and inertia. Simulation results prove the effectiveness of the method.

SAR-AD Method to Characterize Eight SARA Fractions in Various Vacuum Residues and Follow Their Transformations Occurring during Hydrocracking and Pyrolysis

Model compounds were used to provide some chemical boundaries for the eight-fraction SAR-ADTM characterization method for heavy oils. It was found that the Saturates fraction consists of linear and highly cyclic alkanes; the Aro-1 fraction consists of molecules with a single aromatic ring; the Aro-2 fraction consists of mostly 2 and 3-ring fused aromatic molecules, the pericondensed 4-ring molecule pyrene, and molecules with 3–5 rings that are not fused; and the Aro-3 fraction consists of 4-membered linear and catacondensed aromatics, larger pericondensed aromatics, and large polycyclic aromatic hydrocarbons. The Resins fraction consists of mostly fused aromatic ring systems containing polar functional groups and metallated polar vanadium oxide porphyrin compounds, and the Asphaltene fraction consists of both island- and archipelago-type structures with a broad range of molecular weight variation, aromaticity, and heteroatom contents. The behavior of the eight SAR-ADTM fractions during hydrocracking and pyrolysis was investigated, and quantitative relations were established. Intercriteria analysis and evaluation of SAR-ADTM data of hydrocracked vacuum residue and sediment formation rate in commercial ebullated bed vacuum residue hydrocracking were performed. It showed that total asphaltene content, toluene-soluble asphaltenes, and colloidal instability index contribute to sediment formation, while Resins and Cyclohexane-soluble asphaltenes had no statistically meaningful relation to sediment formation for the studied range of operation conditions.

Determining Tipping Points and Responses of Macroinvertebrate Traits to Abiotic Factors in Support of River Management.

Although the trait concept is increasingly used in research, quantitative relations that can support in determining ecological tipping points and serve as a basis for environmental standards are lacking. This study determines changes in trait abundance along a gradient of flow velocity, turbidity and elevation, and develops trait-response curves, which facilitate the identification of ecological tipping points. Aquatic macroinvertebrates and abiotic conditions were determined at 88 different locations in the streams of the Guayas basin. After trait information collection, a set of trait diversity metrics were calculated. Negative binomial regression and linear regression were applied to relate the abundance of each trait and trait diversity metrics, respectively, to flow velocity, turbidity and elevation. Tipping points for each environmental variable in relation to traits were identified using the segmented regression method. The abundance of most traits increased with increasing velocity, while they decreased with increasing turbidity. The negative binomial regression models revealed that from a flow velocity higher than 0.5 m/s, a substantial increase in abundance occurs for several traits, and this is even more substantially noticed at values higher than 1 m/s. Furthermore, significant tipping points were also identified for elevation, wherein an abrupt decline in trait richness was observed below 22 m a.s.l., implying the need to focus water management in these altitudinal regions. Turbidity is potentially caused by erosion; thus, measures that can reduce or limit erosion within the basin should be implemented. Our findings suggest that measures mitigating the issues related to turbidity and flow velocity may lead to better aquatic ecosystem functioning. This quantitative information related to flow velocity might serve as a good basis to determine ecological flow requirements and illustrates the major impacts that hydropower dams can have in fast-running river systems. These quantitative relations between invertebrate traits and environmental conditions, as well as related tipping points, provide a basis to determine critical targets for aquatic ecosystem management, achieve improved ecosystem functioning and warrant trait diversity.

A quantitative evaluation model of outdoor dynamic thermal comfort and adaptation: A year-long longitudinal field study

The understanding of human outdoor thermal comfort demand and thermal adaptation contributes to sustainable urban design as well as city resilience in the context of human health and wellbeing. Humans' past thermal experience influence their outdoor thermal comfort. However, the quantitative relationship between the past thermal experience and outdoor thermal comfort is still not clear. This study aims to reveal quantitative relations of the impact of people's past thermal experience on adaptive thermal comfort and to develop a new outdoor adaptive thermal comfort model. A year-long longitudinal questionnaire survey along with a combination of outdoor thermal environment campaigns was carried out in Chongqing, China. It began on August 15, 2020, and finished on August 19, 2021. Through the analysis of 2240 valid responses to the questionnaire survey, the outdoor thermal adaptation characteristic and dynamic thermal comfort evaluation of the respondents were revealed. The results show that the quantified temperature of past outdoor thermal experience is the quadratic correlation with the thermal sensitivity coefficient and deviation constant, and the linear correlated with outdoor thermal demands. Based on the quantitative analysis, a new outdoor adaptive thermal comfort model has been developed as a function of the exponentially weighted sum of historical mean air temperature series (MeanTrm). The outdoor adaptive thermal comfort zones by 80% and 90% satisfactions thereby have been first drawn based on the Universal Thermal Climate Index (UTCI). The study developed a methodology for the evaluation of dynamic outdoor thermal comfort which can be used for different climate regions.

Multi-Fractal Weibull Adaptive Model for the Remaining Useful Life Prediction of Electric Vehicle Lithium Batteries.

In this paper, an adaptive remaining useful life prediction model is proposed for electric vehicle lithium batteries. Capacity degradation of the electric car lithium batteries is modeled by the multi-fractal Weibull motion. The varying degree of long-range dependence and the 1/f characteristics in the frequency domain are also analyzed. The age and state-dependent degradation model is derived, with the associated adaptive drift and diffusion coefficients. The adaptive mechanism considers the quantitative relations between the drift and diffusion coefficients. The unit-to-unit variability is considered a random variable. To facilitate the application, the convergence of the RUL prediction model is proved. Replacement of the lithium battery in the electric car is recommended according to the remaining useful life prediction results. The effectiveness of the proposed model is shown in the case study.

Trading with the crowd

AbstractWe formulate and solve a multi‐player stochastic differential game between financial agents who seek to cost‐efficiently liquidate their position in a risky asset in the presence of jointly aggregated transient price impact, along with taking into account a common general price predicting signal. The unique Nash‐equilibrium strategies reveal how each agent's liquidation policy adjusts the predictive trading signal to the aggregated transient price impact induced by all other agents. This unfolds a quantitative relation between trading signals and the order flow in crowded markets. We also formulate and solve the corresponding mean field game in the limit of infinitely many agents. We prove that the equilibrium trading speed and the value function of an agent in the finite N‐player game converges to the corresponding trading speed and value function in the mean field game at rate . In addition, we prove that the mean field optimal strategy provides an approximate Nash‐equilibrium for the finite‐player game.

Accelerated discovery of high-performance Al-Si-Mg-Sc casting alloys by integrating active learning with high-throughput CALPHAD calculations

ABSTRACT Scandium is the best alloying element to improve the mechanical properties of industrial Al-Si-Mg casting alloys. Most literature reports devote to exploring/designing optimal Sc additions in different commercial Al-Si-Mg casting alloys with well-defined compositions. However, no attempt to optimize the contents of Si, Mg, and Sc has been made due to the great challenge of simultaneous screening in high-dimensional composition space with limited experimental data. In this paper, a novel alloy design strategy was proposed and successfully applied to accelerate the discovery of hypoeutectic Al-Si-Mg-Sc casting alloys over high-dimensional composition space. Firstly, high-throughput CALculation of PHAse Diagrams (CALPHAD) solidification simulations of ocean of hypoeutectic Al-Si-Mg-Sc casting alloys over a wide composition range were performed to establish the quantitative relation ‘composition-process-microstructure’. Secondly, the relation ‘microstructure-mechanical properties’ of Al-Si-Mg-Sc hypoeutectic casting alloys was acquired using the active learning technique supported by key experiments designed by CALPHAD and Bayesian optimization samplings. After a benchmark in A356-xSc alloys, such a strategy was utilized to design the high-performance hypoeutectic Al-xSi-yMg alloys with optimal Sc additions that were later experimentally validated. Finally, the present strategy was successfully extended to screen the optimal contents of Si, Mg, and Sc over high-dimensional hypoeutectic Al-xSi-yMg-zSc composition space. It is anticipated that the proposed strategy integrating active learning with high-throughput CALPHAD simulations and key experiments should be generally applicable to the efficient design of high-performance multi-component materials over high-dimensional composition space.

Crystalline silica particle functionalized by PEG for its collision-enhanced detection at ultramicroelectrode

Detecting individual particulate matter is highly significant in many areas, such as mine safety, environment, and human health. The analytical method based on single entity electrochemistry (SEE) has shown great potential in detecting, counting, and measuring individual particles, especially conductive metals or carbon particles, based on their unique charge transfer reactions at an ultramicroelectrode (UME). In this study, we report an innovative SEE method for improving the sensitivity of the detection of electrochemical inert crystalline silica particles by functionalizing silica particles with polyethylene glycol (PEG) molecules. The PEG surface functionalization of the silica was characterized by Fourier-transform infrared (FTIR) spectroscopy and X-ray photoelectron spectroscopy (XPS) techniques. The morphology of silica particles was characterized by a scanning electron microscope (SEM), and a transmission electron microscope (TEM) was employed to calibrate size distribution and determine the elemental composition of silica particles. The surface charges of silica particles were measured by dynamic light scattering techniques. The collision behaviors of crystalline silica particles with UME were investigated by cyclic voltammetric experiments, which are rarely reported in the literature. The crystalline silica particles were detected based on electrochemically blocking the flux of the redox mediator at the surface of UME, which showed significant signal amplification in the proposed method. Our method was demonstrated for detecting crystalline silica functionalized with or without PEG, acquiring the limit of quantification (LOQ) values of 0.391 μM (23.45 μg/L) and 0.824 μM (49.45 μg/L), respectively, which confirmed that a more than two times improvement in LOQ could be achieved over the PEG functionalized silica particles. We further presented a theoretical model using finite element simulations with COMSOL Multiphysics. We deduced a quantitative relation between the distribution of the current step size and the size distribution of silica particles. Therefore, the reported method here provides a paradigm for SEE-based detection of electrochemically inert crystalline silica particles, which extends the previous report substantially concerning particle detection.

Experimental and numerical investigations on damage evolution of concrete under sulfate attack and freeze-thaw cycles

The macro-microstructure tests of concrete under the alternating action of salt freezing (ASF) were conducted to investigate the macro-mechanical properties and microstructure pore evolution patterns of concrete. Combined with CT scanning and 3D pore model reconstructing technologies, we present the evolution equation of concrete porosity and the quantitative relation between the fractal dimension of concrete pores and the macroscopic strength under the ASF. Then, a macro-microscopic damage evolution model of concrete was proposed to study the structural performance evaluation of an aqueduct. The results show that the compressive strength (fc), splitting tensile strength (ft), and relative dynamic modulus (Erd) of concrete specimens under the ASF show a decreasing trend as a whole, and the mechanical properties of concrete gradually decrease with the increase of sulfate solution concentration. With the increase of the cycles of salt freezing alternation, the pore fractal dimension of the concrete gradually decreases and the porosity gradually increases. After the cycle of 8 times, the pore fractal dimension decreases by 6.06%, and the porosity increases by 7.30% compared with the initial state. The porosity of concrete is negatively correlated with the strength, while the fractal dimension of the pore structure is positively correlated with the strength. When the ASF reaches 8 times, the maximum compressive stress and tensile stress of the groove body are 9.48 MPa and 3.13 MPa, respectively, which appear at the ends of the lower chord. The displacements of the bottom and side wall plates are 0.384 mm and 3.289 mm, respectively. The penetrating cracks appear at the junction, and the structure severely deteriorates.

Experimental investigation on decomposition characteristics of doxycycline in wastewater using hydrothermal treatment: Exploring the way to complete decomposition

Doxycycline is widely found in medical and aquaculture wastewater, posing a great threat to the ecological environment. In this study, the doxycycline was decomposed by hydrothermal method, and its decomposition properties and paths were analyzed. By using univariate experimental method, the influence of hydrothermal temperature (100–340 °C), hydrothermal time (30–120 min) and mass concentration (1–4 wt%) on the decomposition rate of doxycycline, chemical oxygen demand and nitrogen distribution in the product were studied, and the Pearson correlation coefficient of chemical oxygen demand, Total nitrogen and doxycycline removal rate was obtained. The results showed that the removal rate of doxycycline increased with the hydrothermal temperature, decreased with the reactant concentration, and increased first and then decreased with the hydrothermal time. The quantitative relation between the removal rate of doxycycline and operation conditions (temperature, time, and concentration) was obtained by using the response surface method, and the optimization conditions of the hydrothermal decomposition of doxycycline were gotten. The averaged removal rate of doxycycline reached 99.5% at temperature of 260 °C, reaction time of 102.2 min, and mass concentration of 1.4 wt%. Finally, the liquid chromatography and mass spectrometry were used for quantitative and qualitative analysis of liquid products, and three potential hydrothermal decomposition routes of doxycycline were proposed. This study will lay the foundation for the hydrothermal treatment of medical and aquaculture wastewater containing antibiotics.

Study on pressure pulsations and transient fluid forces in centrifugal pump under different degrees of cavitation

At the early stage of cavitation, the external characteristics and vibration noise of centrifugal pump have not changed significantly, but the flow conditions in the pump have changed markedly. In order to carry out in-depth study on the change characteristics of the flow conditions in centrifugal pump under different degrees of cavitation at the early stage of cavitation, in this paper, the quantitative relation between cavitation degree and pressure pulsation and fluid force was established by means of numerical calculation combined with test and by analyzing the changes in pressure pulsations and fluid forces in the pump under different degrees of cavitation degree. Studies have shown that the pressure pulsation amplitude and range value at the main frequency (shaft frequency and blade frequency) increases with the cavitation degree. The RMS value of pressure pulsation in each frequency band is positively correlated with cavitation development. In case of severe cavitation, the pressure pulsations in high frequency bands are greatly affected by cavitation. The radial force on pump volute and impeller fluctuates more significantly with the increase of cavitation degree.

Approximate reciprocal relationship between two cause-specific hazard ratios in COVID-19 data with mutually exclusive events.

COVID-19 survival data presents a special situation where not only the time-to-event period is short, but also the two events or outcome types, death and release from hospital, are mutually exclusive, leading to two cause-specific hazard ratios (csHR d and csHR r ). The eventual mortality/release outcome is also analyzed by logistic regression to obtain odds-ratio (OR). We have the following three empirical observations: (1) The magnitude of OR is an upper limit of the csHR d : |log(OR)| ≥ |log(csHR d )|. This relationship between OR and HR might be understood from the definition of the two quantities; (2) csHR d and csHR r point in opposite directions: log(csHR d ) ⋅ log(csHR r ) < 0; This relation is a direct consequence of the nature of the two events; and (3) there is a tendency for a reciprocal relation between csHR d and csHR r : csHR d ∼ 1/csHR r . Though an approximate reciprocal trend between the two hazard ratios is in indication that the same factor causing faster death also lead to slow recovery by a similar mechanism, and vice versa, a quantitative relation between csHR d and csHR r in this context is not obvious. These results may help future analyses of data from COVID-19 or other similar diseases, in particular if the deceased patients are lacking, whereas surviving patients are abundant.