Additivity Rule Research Articles

Study of electron interaction with halogenated anaesthetic molecules in gas phase at 50 eV electron energy

Abstract This study addresses the environmental concerns associated with halogenated anesthetic gases, specifically halothane, sevoflurane, and isoflurane, due to their contributions to global warming and ozone depletion. Using a combination of experimental and theoretical approaches, we analyzed elastic electron scattering properties of these compounds in the gaseous phase at an electron energy of 50 eV. The experimental data were gathered using a crossed-beam setup equipped with an electron gun and channeltron detection, with argon serving as the reference gas in a relative-flow method to calibrate the absolute cross-section measurements. Theoretical calculations were performed using the Independent Atom Model with Screening Corrected Additivity Rule (IAM-SCAR+I), which includes interference effects to compare with experimental results effectively. These findings enhance understanding of the scattering dynamics of these anesthetics, highlighting their atmospheric implications and potential environmental impacts.

Variable droop gain frequency supporting control with maximum rotor kinetic energy utilization for wind-storage system

To address the emerging frequency stability issue brought by the large replacement of synchronous generators with renewable generations, wind turbine generators are required to possess frequency-supporting capability. However, existing frequency-supporting control strategies lack the assessment of the frequency support capability of wind turbine generators, leading to degraded control performance under various situations. Aiming to solve this problem, this paper proposes a variable-droop-gain control for wind turbine generators with maximum rotor kinetic energy utilization. Firstly, an analytical relationship was established between droop gain, disturbance scale, and rotor speed. Subsequently, the released energy of the wind turbine generator is evaluated, which equals the difference in the rotor kinetic energy under the initial and the post-disturbance steady-state rotor speed. It was proved that the released kinetic energy cannot exceed a certain proportion of total rotor kinetic energy. Accordingly, a variable initial gain scheme is proposed, which determines the initial droop gain as per the disturbance scale for maximizing the kinetic energy release of wind turbines. Moreover, an additional real-time droop gain adjustment rule is added to prevent the over-deceleration of wind turbines. The simulation results show that the proposed scheme may provide the maximum KE release and effectively improve the system frequency nadir while ensuring the safe operation of wind turbine generators.

Fuzzy Method for Preliminary Classification of the Micro-Electromechanical Systems Data

Data of micro-electromechanical systems (sensors) are widely used in modern multipurpose intellectual environments, autonomous mobile robots and automated systems possessing intellectual components. Since the amount of data delivered by the sensors is rather considerable and their significance varies we propose a fuzzy method of the data preliminary classification aimed at selection of the data important for the planning and control decisions while meaningless data or data that do not contain new information are discarded. As a result the amount of the resource intensive intellectual processing and the workload in the network infrastructure could be reduced significantly. The paper presents the analysis for the preliminary classification problem, the abstract model of a sensor and classification method. The method is based on the delay which is controlled by multiplicative decrease additive increase rule and expresses the expectation of the context uncertainty. The delay decreases if the variables measured by the sensor presumably change and increases if it keep its value. Numerical examples are presented as well. They consider the set of mount chest accelerometer uncalibrated measurements. We compare source data set and set of the selected values formed by an algorithm implementing fuzzy preliminary classification. Several metrics were used to compare the selected values with the source data and with CMA filter as well.

Speed of sound measurements of binary n-octane+ ethylcyclohexane mixture at liquid-gas phase transition curve

Bio-jet fuel is a key element in the aviation industry to reduce operating costs and environmental impacts. Bio-jet fuel is a complex mixture of four hydrocarbons (n-alkanes, isoalkanes, cycloalkanes and aromatics). In the present work, the speed of sound in pure n-octane, ethylcyclohexane, and their mixtures with six selected compositions of (0.3004, 0.4191, 0.4999, 0.5538, 0.6991, and 0.7852 mole fraction of ethylcyclohexane) has been measured along the l-G saturation curve in the temperature ranges from (286 to 443) K using the pulse method with a constant (acoustic) sounding base. The combined expanded absolute and relative uncertainties (0.95 level of confidence, k = 2) of the temperature, concentration, and speed of sound measurements are estimated to be 20 mK, 0.0006 mole fraction, and 0.2 %, respectively. The measured speed of sound data together with our previous reported density data for the pure component (ethylcyclohexane) and the mixture were used to calculate derived thermodynamic properties, such as isentropic compressibility kS and heat capacity ratios CPCV as a function of temperature along the l-G saturation curve for the pure components and the mixture for selected concentration of x = 0.8 mole fraction of ethylcyclohexane. The deviation of the measured speed of sound data for the mixture from the linear additive rule has been determined using the pure component data.

Theoretical basics of the self-learning system of intelligent locomotive decision support systems

Analysis of works in the field of artificial intelligence allows to make an assumption that today there is a sufficiently developed theoretical basis for the development of intelligent control systems for locomotive control. This will minimize the risks associated with the human factor on the railways. The paper presents the theoretical rationale for the development of a knowledge base for intelligent locomotive control systems. The approach and structure of the self-learning system of intelligent DSS is proposed, the advantage of which is the presence of a fuzzy classifier that works according to the set criteria and determines a fuzzy image of the current train situation. Learning a fuzzy classifier consists in finding a vector K that minimizes the distance between the results of logical inference and experimental data from the sample. The knowledge base is implemented using linguistic variables formalized by methods of fuzzy logic. The use of linguistic values makes it possible to design the base using the usual language of communication, which greatly simplifies both the design process itself and the analysis of the system's performance. Also, the knowledge base has the possibility of constant self-improvement. This happens in two ways. The first is by adding new rules to the knowledge base in case the current situation does not match the existing ones in the base, in which case an additional rule is created and checked for adequacy. The second way is a mechanism for ranking rules in the knowledge base. If the control action of the locomotive driver coincided with the recommendation of DSS in the current situation, then the rating of this recommendation (rule) increases, and in the future the rule selection algorithm will choose one or another control action for the current situation that has the highest rating (that is, it has already been verified several times person). The experiment has shown that the use of intelligent DSS has positive results. On average, the DSS made the correct train control decisions faster than the locomotive driver.

Improving Performance of Cluster Heads Selection in DEC Protocol Using K-Means Algorithm for WSN.

Wireless sensor networks (WSN) have found more and more applications in remote control and monitoring systems. Energy management in the network is crucial because all nodes in the WSN are energy constrained. Therefore, the design and implementation of WSN protocols that reduce energy depletion in the network is still an open scientific problem. In this paper, we propose a new clustering protocol that combines DEC (deterministic energy-efficient clustering) protocol with K-means clustering, called DEC-KM (deterministic energy-efficient clustering protocol with K-means). DEC is a very energy-efficient clustering protocol that outperforms its predecessors, such as LEACH and SEP. K-means ensures more effective clustering and shorter data transmission distances within the network. The shorter distances improve the network's lifetime and stability and reduce power consumption. Additional heuristic rules in DEC-KM ensure improved cluster head selection, taking into account node energy level and position and minimising the risk of premature cluster head exhaustion. The simulation results for the DEC-KM protocol using MATLAB show that cluster heads have shorter distances to nodes in cluster areas than for the original DEC protocol. The proposed protocol ensures reduced energy consumption, outperforms the standard DEC, and extends the stability period and lifetime of the network.

Look Beyond Additivity and Extensivity of Entropy for Black Hole and Cosmological Horizons.

We present a comparative analysis of the plethora of nonextensive and/or nonadditive entropies which go beyond the standard Boltzmann-Gibbs formulation. After defining the basic notions of additivity, extensivity, and composability, we discuss the properties of these entropies and their mutual relations, if they exist. The results are presented in two informative tables that are of strong interest to the gravity and cosmology community in the context of the recently intensively explored horizon entropies for black hole and cosmological models. Gravitational systems admit long-range interactions, which usually lead to a break of the standard additivity rule for thermodynamic systems composed of subsystems in Boltzmann-Gibbs thermodynamics. The features of additivity, extensivity, and composability are listed systematically. A brief discussion on the validity of the notion of equilibrium temperature for nonextensive systems is also presented.

Evaluating non-linear optical behavior in ionic liquids: Combining ab-initio polarizability with additivity rule

In the field of non-linear Optics, the additivity rule, which both experimental and theoretical researchers utilize, provides a simple and reliable method for calculating polarizability. However, this model neglects crucial factors, such as the solvent, the interaction distance, and external optical fields, leading to inaccurate results. In this study, the role of these parameters on the non-linear optical behavior of the ionic liquid BMIM+⋯BF4−, a system extensively studied for its intriguing non-linear optical properties, is investigated. To do that, first-principles calculations based on the density functional theory are developed; the Lennard-Jones potential is used as the reference model. The results of this study reveal the significant influence of the solvent on the second- and third-order non-linear optical responses, which are strongly affected by ion interactions, underscoring the limitations of the additivity rule in terms of molecular polarizability. The EFISHG values for each solvent are inversely proportional to the dielectric constant; for all considered solvents, it observed a clear dependence of polarizability values on the external field, ranging from 1.675 to 1.638× 10−23 esu. It was also found high sensitivity of the static polarizability to changes in the interaction distance and the solvent choice, ranging from 1.57 to 2.05× 10−30 esu, while considering the additivity rule, this parameter changed to 1.59× 10−30 esu. This information can serve as a reference for both theoretical and experimental researchers.

Impact of implicit vs. explicit Instructions on tactical performance in under-20 soccer players.

This study aimed to verify whether implicit and explicit informational constraints generate differences in tactical performance and behavior in U-20 national-level soccer players. Thirty-two under-20 male athletes from two clubs participated. Four 4-a-side small-sided games (SSG) protocols were used: R1 - explicit rule for high-press marking, R2 - implicit rule for high-press marking, R3 - game with both previous rules simultaneous and FR - free game, without additional rules. SSGs comprised 4 vs. 4+ goalkeepers games on a 42 m × 29 m field. Position data from 10 Hz Global Positioning System (GPS) devices were used to evaluate individual and collective tactical behavior (spatial occupation metrics) and performance (interpersonal coordination). MANOVA was used for normally distributed variables, and Friedman's with Dunn or Bonferroni post hoc was used for variables without normal distribution. For SEI, an ANOVA was used with Bonferroni post hoc. The R1 protocol showed higher SEI, length, width, and LpWratio than the FR protocol (p = 0.009). There was an effect of the different protocols in SEI values (p < 0.001). Under the explicit rule, players also showed the highest in-phase interpersonal coordination values (p < 0.001). Providing players with explicit tactical instructions improves tactical performance acutely for high-pressing defensive actions.

Rapidly destructive hip osteoarthritis: a diagnosis not to miss.

This review illustrates the imaging features of rapidly destructive hip osteoarthritis (RDHO) across different imaging modalities. RDHO is a rare joint disease of unknown aetiology resulting in rapid deterioration of the hip joints. Patients often present with severe hip pain and can progress to complete joint destruction in 6 months to 3 years causing disability. Since its clinical and imaging features often overlap with other conditions, the diagnosis is easily missed in daily practice. The purpose of this paper is to outline the characteristic imaging features of RDHO, aiming to enhance awareness of this disease entity and promote timely treatment for patients. Sequential radiographs are particularly important in demonstrating the rapid progression of radiographic findings and with the early recognition of characteristic features, diagnosis can be made to avoid treatment delay. Although CT scan is not necessary for diagnosis, it is useful in evaluating the extent of joint destruction and guiding surgical planning. MRI can provide additional information and rule out other pathologies with similar symptoms. Overall, radiographs, CT and MRI are common modalities used in the evaluation of RDHO.

Stepwise Construction and Integration of Ecological Network in Resource-Based Regions: A Case Study on Liaoning Province, China

Ecological networks are an effective strategy to maintain regional ecological security. However, current research on ecological network construction in areas with large-scale resource extraction is limited. Moreover, classic ecological network construction methods do not perform satisfactorily when implemented in heavily damaged mining landscapes. Taking the example of Liaoning Province, China, a framework for stepwise renewal of ecological networks was proposed, which integrates basic ecological sources and other sources that include mining areas. The framework was based on multi-source ecological environment monitoring data, and all potential ecological sources were extracted and screened using an MSPA model and the area threshold method. Further, ecological sources were classified into two types and three levels based on the influence of abandoned mines and the characteristics of ecosystem services in the ecological sources. Ecological corridors were extracted using the MCR model. An ecological corridor optimization process based on combining the gravity model with addition and removal rules of corridors was proposed. The results indicated that the basic ecological network in Liaoning Province included 101 ecological sources and 162 ecological corridors, and the supplementary ecological network included 28 ecological sources and 67 ecological corridors. The ecological sources were divided into two types, and corridors were divided into three types. The basic ecological network exhibited a spatial distribution of discrete connections in the west and close connections in the east. Changes in ecological network topological indicators indicated that a supplementary ecological network strengthened the structural performance of the regional ecological network, expanding spatial coverage, filling hollow areas, and enriching local details of the regional ecological network. Regulation strategies were proposed for ecological sources with different connection modes. The number of ecological sources implementing restrictive development, pattern optimization, and protective development were 101, 12, and 16, respectively. This paper provides a constructing framework of ecological networks adapted for resource-based regions. This method can support decisions for the environmental governance of mines, thus contributing to a balance between resource exploitation and ecological protection in regions.

IMPLEMENTASI PERATURAN PRESIDEN NO 72 TAHUN 2021 TENTANG PERCEPATAN PENURUNAN STUNTING DI KABUPATEN KEPULAUAN MENTAWAI

This research aims to determine the implementation of Presidential Regulation No. 72 of 2021 concerning the Acceleration of Reducing Stunting in the Mentawai Islands Regency, especially in the Betumonga area. This research is motivated by stunting problems which are increasing in the Mentawai Islands Regency, especially in the Betumonga Area. This research uses qualitative methods by conducting field surveys and interviews with related parties such as service staff and local service heads. Based on the results of interviews using the theory presented by Marile a Grindle, the results obtained from the implementation of Presidential Decree number 72 of 2021 concerning the acceleration of stunting reduction in the Mentawai Islands Regency in the Betumonga area can be said to have been implemented well out of a total of 105 achievement indicators in Presidential Decree number 72 of 2021, 27 indicators which is not fulfilled properly and there are only 80 indicators that are fulfilled. achievement indicators that have not met targets. 27 indicators that have not been met, several indicators that are not yet close to the development line and are not in line with the targets for 2024 in the Betumonga area, the government has made efforts to overcome the problem of stunting, but the community still sometimes does not want to accept the reality and some still refuse to handle stunting prevention. The research results show that this incident is caused by the need for sustainable programs, especially in remote areas that are difficult to reach due to their wide reach so that access to transportation is limited. The implementation of Presidential Decree number 72 of 2021 in the Mentawai Islands Regency requires additional rules or efforts in handling stunting cases related to the determinant factors that cause stunting for families at risk of stunting, especially in special cases such as the Betumonga area as well as additional regulations for preventing stunting.

LORE++: Logical location regression network for table structure recognition with pre-training

Table structure recognition (TSR) aims at extracting tables in images into machine-understandable formats. Current approaches address this issue by either predicting the adjacency of detected cells or direct generation of structural sequences. Nonetheless, these approaches either count on additional heuristic rules for post-processing, or involve the generation of extremely long-range sequences that lead to computational intricacy. In this paper, We redefine TSR as a LOgical location REgression paradigm, which effectively captures inherent logical dependencies and constraints among table cells. Correspondingly, we propose LORE, a novel approach for TSR. LORE simultaneously predicts accurate geometric coordinates of table cells and the logical structures of the entire table. Our proposed LORE is conceptually simpler, easier to train, and more accurate than other TSR paradigms. Moreover, to enhance the model’s spatial and logical representation capabilities, we propose two pre-training tasks, resulting in an upgraded version named LORE++. The incorporation of pre-training is proven to enjoy significant advantages, leading to a substantial enhancement in terms of accuracy, generalization, and few-shot capability compared to its predecessor. Experiments on standard benchmarks demonstrate the superiority of LORE++, which highlights the potential and promising prospect of the logical location regression paradigm for TSR.

Higher-derivative relations between scalars and gluons

We extend the covariant color-kinematics duality introduced by Cheung and Mangan to effective field theories. We focus in particular on relations between the effective field theories of gluons only and of gluons coupled to bi-adjoint scalars. Maps are established between their respective equations of motion and between their tree-level scattering amplitudes. An additional rule for the replacement of flavor structures by kinematic factors realizes the map between higher-derivative amplitudes. As an example of new relations, the pure-gluon amplitudes of mass dimension up to eight, featuring insertions of the F3 and F4 operators which satisfy the traditional color-kinematics duality, can be generated at all multiplicities from just renormalizable amplitudes of gluons and bi-adjoint scalars. We also obtain closed-form expressions for the kinematic numerators of the dimension-six gluon effective field theory, which are valid in D space-time dimensions. Finally, we find strong evidence that this extended covariant color-kinematics duality relates the (DF)2+YM(+ϕ3) theories which, at low energies, generate infinite towers of operators satisfying the traditional color-kinematics duality, beyond aforementioned F3 and F4 ones.

Thermodynamic circuits: Association of devices in stationary nonequilibrium.

For a circuit made of thermodynamic devices in stationary nonequilibrium, we determine the mean currents (of energy, matter, charge, etc.) exchanged with external reservoirs driving the circuit out of equilibrium. Starting from the conductance matrix describing the nonlinear current-force characteristics of each device, we obtain the conductance matrix of the composite device. This generalizes the rule of resistance addition (serial association) or conductance addition (parallel association) in stationary out-of-equilibrium thermodynamics and for multiple coupled potentials and currents of different natures. Our work emphasizes the pivotal role of conservation laws when creating circuits of complex devices. Finally, two examples illustrate among others the determination of the conservation laws for the serial and parallel associations of thermodynamic devices.

Pajak Karbon dan Dilema Pembangunan Ekonomi Indonesia: Pembelajaran dari Negara Lain

Indonesia issued a regulation on carbon tax through article 13 of Law No. 7 on the Harmonization of Tax Regulations (HPP) in 2021 following the number of countries that have implemented carbon pricing mechanisms in facing the challenge of climate change. In addition to the policy formulation process full of pros and cons, the policy was actually postponed until 2015. Learning from the experience of other countries, the implementation of carbon taxes does not always succeed in reducing emissions or household budgets. The facts show that economic development and environmental control often do not occur at the same time. Additional rules, government commitment and cooperation from every relevant stakeholder are needed as well as supervision from the community in the implementation of article 13 of the HPP Law.

Phase-field simulation study on dendritic growth behavior during bilateral directional solidification

The directional solidification technique can uniform the crystal growth direction within the material, but does not remove the lateral side branches of the axial main arm during the growth process. The influence of such lateral side branches existing in the directionally solidified dendritic organisation on the mechanical properties of the material cannot be neglected. In this paper, based on the Kim-Kim-Suzuki (KKS) phase-field model, the competitive behaviour of lateral secondary dendrites between the two main arms under different boundary conditions and non-synchronous growth conditions is investigated for Fe-0.5 %C alloys. In addition, the diffusion and enrichment rules of solutes are analysed by the distribution of solutes. The results show that the molten pool is spherical without external force, and the size distribution of the molten pool is as follows: dendrite tip collision zone > dendrite root > dendrite wall, and the solute segregation rule is the same; The spacing of the main arms has little effect on the concentration values between the dendrites, and the solutes are very symmetrically over the entire computational region; The dendrite tip interface concentration during the stable phase of dendrite growth is 0.89 %. Without considering the initial liquid-phase concentration, the concentration in the collision zone at the dendrite tip is approximately twice the concentration at the tip of the dendrite in the stable period, which is 1.28 %, when the bilateral dendrites are encountered. Dendrites always collide preferentially on the centreline of the included angle under non-parallel conditions, and solute-enriched zones also occur on the centreline of the included angle; During the curved surface bilaterally directional solidification process, when the left and right sides have the same shape of surfaces, the solute enrichment at the end of solidification is on the centreline. For the case of a single planar boundary, the solute-enriched region is influenced by the curved surface and is similar to the initial curved surface profile.

Determination of Partial Propagation Velocity and Partial Isentropic Compressibility Coefficient in Water-Ethanol System.

This study introduces an innovative approach to the layered model, emphasizing the physical-chemical characterization of miscible liquid systems through ultrasonic techniques, with a specific focus on the water-ethanol system used in pharmaceutical formulations. Traditional characterization methods, while effective, face challenges due to the complex nature of solutions, such as the need for large pressure variations and strict temperature control. The proposed approach integrates partial molar volumes and partial propagation velocity functions into the layered model, enabling a nuanced understanding of miscibility and interactions. Ultrasonic techniques are used to calculate the isentropic compressibility coefficient for each component of the mixture as well as the total value using an additive mixing rule. Unlike conventional methods, this technique uses tabulated and experimental data to estimate the propagation velocity in the mixture, leading to a more precise computation of the isentropic compressibility coefficient. The results indicate a significant improvement in predicting the behavior of the water-ethanol system compared to the classical layered model. The methodology demonstrates the potential to provide new physicochemical insights that can be applied to other miscible systems beyond water-ethanol. This research has implications for improving the efficiency and accuracy of liquid medication formulations in the pharmaceutical industry.

The interplay between spatial and non-spatial grouping cues over approximate number perception.

Humans and animals share the cognitive ability to quickly extract approximate number information from sets. Main psychophysical models suggest that visual approximate numerosity relies on segmented units, which can be affected by Gestalt rules. Indeed, arrays containing spatial grouping cues, such as connectedness, closure, and even symmetry, are underestimated compared to ungrouped arrays with equal low-level features. Recent evidence suggests that non-spatial cues, such as color-similarity, also trigger numerosity underestimation. However, in natural vision, several grouping cues may coexist in the scene. Notably, conjunction of grouping cues (color and closure) reduces perceived numerosity following an additive rule. To test whether the conjunction-effect holds for other Gestalt cues, we investigated the effect of connectedness and symmetry over numerosity perception both in isolation and, critically, in conjunction with luminance similarity. Participants performed a comparison-task between a reference and a test stimulus varying in numerosity. In Experiment 1, test stimuli contained two isolated groupings (connectedness or luminance), a conjunction (connectedness and luminance), and a neutral condition (no groupings). Results show that point of subjective equality was higher in both isolated grouping conditions compared to the neutral condition. Furthermore, in the conjunction condition, the biases from isolated grouping cues added linearly, resulting in a numerosity underestimation equal to the sum of the isolated biases. In Experiment 2 we found that conjunction of symmetry and luminance followed the same additive rule. These findings strongly suggest that both spatial and non-spatial isolated cues affect numerosity perception. Crucially, we show that their conjunction effect extends to symmetry and connectedness.

Multi-arm multi-stage (MAMS) randomised selection designs: impact of treatment selection rules on the operating characteristics

BackgroundMulti-arm multi-stage (MAMS) randomised trial designs have been proposed to evaluate multiple research questions in the confirmatory setting. In designs with several interventions, such as the 8-arm 3-stage ROSSINI-2 trial for preventing surgical wound infection, there are likely to be strict limits on the number of individuals that can be recruited or the funds available to support the protocol. These limitations may mean that not all research treatments can continue to accrue the required sample size for the definitive analysis of the primary outcome measure at the final stage. In these cases, an additional treatment selection rule can be applied at the early stages of the trial to restrict the maximum number of research arms that can progress to the subsequent stage(s).This article provides guidelines on how to implement treatment selection within the MAMS framework. It explores the impact of treatment selection rules, interim lack-of-benefit stopping boundaries and the timing of treatment selection on the operating characteristics of the MAMS selection design.MethodsWe outline the steps to design a MAMS selection trial. Extensive simulation studies are used to explore the maximum/expected sample sizes, familywise type I error rate (FWER), and overall power of the design under both binding and non-binding interim stopping boundaries for lack-of-benefit.ResultsPre-specification of a treatment selection rule reduces the maximum sample size by approximately 25% in our simulations. The familywise type I error rate of a MAMS selection design is smaller than that of the standard MAMS design with similar design specifications without the additional treatment selection rule. In designs with strict selection rules - for example, when only one research arm is selected from 7 arms - the final stage significance levels can be relaxed for the primary analyses to ensure that the overall type I error for the trial is not underspent. When conducting treatment selection from several treatment arms, it is important to select a large enough subset of research arms (that is, more than one research arm) at early stages to maintain the overall power at the pre-specified level.ConclusionsMulti-arm multi-stage selection designs gain efficiency over the standard MAMS design by reducing the overall sample size. Diligent pre-specification of the treatment selection rule, final stage significance level and interim stopping boundaries for lack-of-benefit are key to controlling the operating characteristics of a MAMS selection design. We provide guidance on these design features to ensure control of the operating characteristics.