Definition Of Parameters Research Articles

Analysis of economic crises at enterprises: from classical theories to innovative solutions

The article is devoted to a comprehensive analysis of economic crises at enterprises arising as a result of various internal and external factors that affect their stability and competitiveness. The author examines the polysemantic nature of the concept of «crisis», analyzing it in the context of various scientific disciplines and approaches. Special attention is paid to the dualistic approach to the crisis, where it is considered as a phenomenon that simultaneously carries threats and opportunities for development. The article provides a retrospective review of approaches to the study of crisis phenomena, starting from the cyclical approach, which interprets the crisis as a natural stage of the economic cycle, to modern system-synergistic methodologies, which consider the crisis as a prerequisite for self-organization and development of the enterprise. The conducted analysis of literary sources confirms the need to integrate various approaches for complex anti-crisis management at enterprises. The work also identifies unresolved aspects of the problem, including early diagnosis of crises, integration of anti-crisis tools, and the impact of digitalization on crisis processes. The article emphasizes the importance of flexible and adaptive diagnostic models capable of responding effectively to rapid changes in the business environment. The scientific novelty consists in proposing an action algorithm for diagnosing the crisis state of enterprises, based on the definition and analysis of key parameters that reflect the economic health of the business. The author emphasizes the need for a deep understanding of the specifics of each enterprise for successful anti-crisis management and the potential use of crisis phenomena to achieve new heights of development.The variety of interpretations of this term indicates its complexity and multifacetedness, which requires special attention to specify the meaning of the concept not only in the economic context, but also at the level of enterprises, underlines the relevance of this topic.

Biofilm Growth in Porous Media Well Approximated by Fractal Multirate Mass Transfer With Advective‐Diffusive Solute Exchange

AbstractBiofilm growth in porous media changes not only the hydrodynamic properties of the medium (reduction in porosity and permeability, and increase in dispersivity), but also the transport itself (breakthrough curves display increasingly fast first arrivals and long tails). These features are well reproduced by multicontinuum models (Multi‐Rate Mass Transfer, MRMT) which can be used to describe reactive transport in heterogeneous porous media and facilitate the simulation of reactions that are localized within biofilms. Here, we present a conceptual and numerical model of biochemical reactive transport with dynamic biofilm growth based on MRMT formulations. Mass exchange between mobile water and immobile biofilm aggregates is represented by a memory function, which simplifies definition of MRMT parameters. We successfully tested this model on two sets of laboratory data and found that (a) a basic model based on the growth of uniformly sized biofilm aggregates fails to reproduce laboratory tracer tests and rate of biofilm growth, while a fractal growth model, which we obtain by integrating the memory functions of biofilm aggregates with a power law distribution, does; (b) the biofilm memory function evolves as the biofilm grows; and (c) the early time portion of eluted volume tracer breakthrough curves are independent of flow rate, whereas the tail becomes heavier when the flow rate is decreased, which implies that both advection controlled and diffusion controlled mass exchange coexist in biofilms. These findings imply that porous media biofilms are essentially different from those developing in human tissues or open spaces.

Identifying patterns in the structural-phase transformations when processing oxide doped waste with the use of carbon reducer

The object of this study is the structural and phase transformations during the carbon reduction of tungsten high-speed steel slag in order to obtain a resource-saving alloying additive. The problem is the loss of precious elements when obtaining and using alloying material from man-made raw materials. Solving the problem is related to the definition of technological parameters to enable the reduction of losses of the corresponding elements. As a result of increasing the degree of scale reduction from 33 % to 72 % and 85 %, the strengthening of the manifestation of the solid solution of carbon and alloying elements in α-Fe relative to FeWO4, FeO and Fe3O4 was revealed. Fe3C, WC, W2C, FeW3C, Fe3W3C, Fe6W6C, VC, V2C, Cr3C2, Cr7C3 and Cr23C6 also appeared. Along with this, rounded and multifaceted particles with different chemical composition and the formation of a spongy microstructure were found. It was established that the most acceptable degree of recovery is 85 %. But achieving a recovery rate of 72 % is also sufficient. This is explained by the fact that the residual carbon in the carbides provides an increased reducing capacity, which is realized during the further reduction of oxides in the liquid metal during alloying. The spongy microstructure results in faster dissolution in contrast to standard ferroalloys, which provides a reduction in melting time while reducing spent resources. No phases with an increased tendency to sublimation were found in the obtained alloying material. That is, no additional conditions are needed that restrain the loss of alloying elements during evaporation with a gaseous phase, which provides an increase in the degree of extraction of the corresponding elements. The properties of the resulting alloying material make it possible to use it in metallurgical production when smelting alloyed steel grades in an electric arc furnace, the composition of which does not have strict restrictions on the carbon content

An analytical approach for evaluation of conveyor exit strategies in open-pit mines

Transportation is the most expensive task in deep open-pit mining operations. An In-Pit Crushing and Conveying (IPCC) system, as an alternative to the conventional shovel-truck system, requires precise planning to avoid wasting high capital expenditures on trucks. The decision to fit a conveyor system into the pit design is challenging and needs to be addressed in the literature. Further optimisation of the IPCC system requires choosing an appropriate conveyor exit strategy. Conveyor exit schemes include a Dedicated Ramp Slot (DRS), an Existing Ramping System, an inclined tunnel and High-Angle Conveyors (HAC). This paper provides an analytical approach to compare the cost of different conveyor exit strategies in open-pit mines. The results indicate that for a depth up to 100 m, the Present Value of Cost (PVC) for the DRS is the least. For the cases deeper than 300 m, the HAC has the least PVC. Sensitivity analysis showed that for the depths between 100 and 300 m, a more accurate and detailed definition of parameters is needed. Besides, in most cases, the HAC provides the lowest payback period and the highest internal rate of return among the alternatives.

A survey on management practices of hypotension in preterm neonates: an Indian perspective.

Hypotension is a common entity in the neonatal intensive care unit (NICU) and is reported in 24%-50% of preterm infants with birth weight less than 1,500 g. Rapid diagnosis and aggressive management is crucial to reduce its detrimental effects on end-organs especially the brain. Physicians often rely on blood pressure alone as a reliable indicator of tissue perfusion, but variations exist in the definition of this crucial parameter. There are also practice variations in the use of diagnostic tools and management modalities among physicians. A physician-based cross-sectional survey of management practices of hypotension in preterm neonates in Indian NICUs was conducted using an online survey tool. The questionnaire addressed diagnostic criteria used, utility of echocardiography for the assessment of hypotension, and management strategies used, such as volume expansion, inotropes and steroids. Three hundred and twenty physicians, working predominantly in Level III NICUs, responded to the survey. The practice of delayed cord clamping was followed in the units of 78% respondents. Only 44% respondents had an institutional written protocol for the management of hypotension. The criteria for the diagnosis of hypotension varied, with 52% using mean blood pressure (BP) less than gestational age as the criteria. Capillary refill time, blood pressure and heart rate were the most common clinical criteria used. 85% respondents used echocardiography in the NICU, but only 73% utilised it for assessment of a hypotensive neonate. Physicians preferred a 'volume-inotrope-echo-steroid' strategy, with 85% respondents using volume expansion. Dopamine was the preferred first line inotrope, followed by norepinephrine and low-dose epinephrine. This survey reflects significant variations in practice amongst neonatal physicians in India. Bedside targeted echocardiography needs to be better utilised as a vital tool to determine the pathophysiology of disease and hemodynamic monitoring in the management of hypotension in neonates. While further research is needed on outcome-oriented objectives, awareness and dissemination of already existing guidelines would be useful to standardize clinical practice.

A Study on the Production-Inventory Problem with Omni-Channel and Advance Sales Based on the Brand Owner’s Perspective

This study explores a supply chain product-inventory problem with advance sales under the omni-channel strategies (physical and online sales channels) based on the brand owner’s business model and develops corresponding models that have not been proposed in previous studies. In addition, because the brand owner is a member of the supply chain, and has different handling methods for defective products or products returned by customers in various retail channels, defective products or returned products are included in the supply chain models to comply with actual operating conditions and fill the research gap in the handling of defective/returned products. Regarding the mathematical model’s development, we first clarify the definition of model parameters and relevant data collection, and then establish the production-inventory models with omni-channel strategies and advance sales. The primary objective is to determine the optimal production, delivery, and replenishment decisions of the manufacturer, physical agent, and online e-commerce company in order to maximize the joint total profits of the entire supply chain system. Further, this study takes the supply chain system of mobile game steering wheel products as an example, uses data consistent with the actual situation to demonstrate the optimal solutions of the models, and conducts sensitivity analysis for the proposed model. The findings reveal that increased demand shortens the replenishment cycle and raises order quantity and shipment frequency in the physical channel, similar to the online channel during normal sales. However, during the online pre-order period, higher demand reduces order quantity and cycle length but still increases shipment frequency. Rising ordering or fixed shipping costs lead to higher order quantity and cycle length in both channels, but variable shipping costs in the online channel reduce them. Market price increases boost order quantity and frequency in the online channel, while customer return rates significantly impact inventory decisions.

НЕЙРОМЕРЕЖЕВІ МАТЕМАТИЧНІ МОДЕЛІ ЛЮДИНОМАШИННОГО СПІЛКУВАННЯ ТА РОЗПІЗНАВАННЯ

The study is devoted to the neural network interpretation of the task of human-machine communication and recognition by multiple criteria, considered as a task of assignment. The main goal is to reduce this problem to a standard form, where the number of criteria groups is equal to the number of ranked documents. The study defined the architecture of a neural network and proposed the use of a network of binary neurons, which is a matrix of a certain dimension. The proposed ranking model is based on a neural network that contains arbitrary feedback. This allows the excitation to be transmitted back to the neuron, which contributes to the repeated performance of its function. However, in dynamic neural networks instability occurs, which is manifested in a random change in the states of neurons without reaching stationary states. The question of stability of the dynamics of such systems remains open. The considered discrete Hopfield neural network has the following characteristics: one layer of elements, each element is connected to all others, but not to itself; only one element is updated per stage; elements are updated in random order, but each is updated with the same frequency; the output function is binary (value "0" or "1"). A Hopfield neural network is recurrent: the output of the network is reused as input until a steady state is reached. After starting, the neural network changes its state, gradually moving to a stable mode, which allows identifying a plan for evaluating the process of human-machine communication according to a set of criteria. Random search procedures are used to refine the results. The proposed energy function is minimized to ensure that the constraints are met and the problem is solved. The constructed function reaches a minimum only in the states corresponding to the assignment plans. The definition of the network parameters is carried out by comparing the obtained functions with the energy function in general form. The practical implementation of the model demonstrated that Hopfield's neural network can be successfully applied to document ranking in human-machine communication and recognition systems, providing high accuracy and efficiency in solving ranking problems.

Nonparametric and Continuous Variable-Based Stratigraphic Modelling from Sparse Boreholes using Signed Distance Function and Bayesian Compressive Sensing

An accurate stochastic interpretation of subsurface stratigraphy with quantified uncertainty can benefit the subsequent risk management of geotechnical infrastructure. Traditional approaches to developing geological cross-sections from sparse boreholes typically require the calibration or definition of empirical model parameters and functions, which may introduce subjectivity and bias. In this study, a non-parametric and continuous variable-based spatial predictor that leverages the signed distance function and Bayesian compressive sensing (BCS) is proposed for subsurface stratigraphic modelling. The proposed method transforms sparse categorical borehole data from a low-dimensional space into continuous variables in a high-dimensional space, enabling a comprehensive representation of more implicit characteristics of intricate geological patterns. This transformation facilitates the use of the continuous-variable-based BCS for non-parametric spatial prediction. The most probable geological cross-section and uncertainty qualification plot are derived after transforming spatially interpreted fields of continuous variables back into soil types. The performance of the proposed method is demonstrated using synthetic and real-world cases. Results indicate that the proposed approach can handle intricate stratigraphic scenarios characterized by complex geological structures, such as crossed-inclined, folded, inclined-folded, and interbedded strata, in a data-driven and non-parametric manner. The advantages of the proposed method over existing spatial predictors for developing geological cross-sections are also demonstrated.

Rainwater harvesting through roofs and stormwater harvesting through pervious pavements: A Life Cycle Assessment and decision-making comparison

Water consumption and the building sector are among the top contributors to environmental impacts worldwide. Also, sustainable practices have been constantly encouraged in both sectors to mitigate water scarcity and provide resilience to cities. Thus, studies that provide an environmental assessment and discuss the decision-making process are essential for enabling the augmentation of sustainable practices. This research aims to contribute to the discussion on sustainability by conducting a Life Cycle Assessment (LCA) of Sustainable Urban Drainage Systems (SUDS) examples. LCA is the main methodology applied to perform environmental comparisons. First, a thorough inventory was obtained from previous works with different alternatives for water management within a university building, including drainage, paving and water supply functions. The inventory contemplates alternatives using rainwater and stormwater harvesting for non-potable water supply, including pervious pavements. Such alternatives were compared with Brazil's usual water supply systems, aiming at diminishing the total environmental burden. The methodology aspects of LCA were also regarded, such as an uncertainty assessment and a quality matrix of the processes used. Midpoint and endpoint categories were also regarded with their decision-making and uncertainty analysis. The main result is the understanding of the trade-offs between the proposed systems, with a significant reduction in water stress obtained in the alternative scenarios. However, such a decrease is accompanied by a slight increase in some impact categories. Rainwater harvesting through roofs is the most environmentally friendly alternative, although the Cultural Theory parameter definition impacts on the sustainability ranking. Alternative sustainable systems for water management still need validation in terms of LCA, while decision-making for sustainable and resilient cities also requires a robust scientific basis. Thus, in conclusion, alternative systems such as SUDS were obtained to be more sustainable than conventional paving, drainage and water supply in the case study, and the understanding of different benefits found in the LCA is important to the decision-making process.

Investigation of block interleavers in OFDM radio communication systems with convolutional encoding in multipath channels with fast fading

Noise immunity codecs are good at correcting single errors. Group errors often occur in multipath radio channels with fading. Interleaving is used to convert group errors into single errors. Matching the interleaver structure with the signal and code parameters allows the interleaver to work efficiently. Optimization of the interleaver parameters depending on the characteristics of the communication channel increases the efficiency of the interleaver. The purpose of the work is to determine the parameters of block interleavers for an OFDM radio communication system with convolutional coding in conditions of signal scattering in time and frequency. A model of a channel with two beams and Rayleigh fades is considered. The influence of interleaver parameters on the noise immunity of the OFDM radio communication system depending on the channel parameters (fading rate, multipath interval) has been analyzed. Block deterministic and pseudorandom interleavers are considered. With magnification lengths the interleaver increases noise immunity of the communication system. But at the same time, the delay in transmitting the message increases. The optimal length has been determined, providing a compromise between delay and noise immunity. This length is determined depending on the coherence time of the channel. The number of rows of the matrix interleaver is depending on the decoding depth. This is the number of rows provides better noise immunity at optimal length. But sometimes the optimal length is too long. Therefore a function has been introduced that characterizes the minimum distance between bits in the “time-frequency-code” space at the input of the interleaver. The distance between the bits in the time domain is normalized for the coherence time of the channel. The distance between the bits in the frequency domain is calculated as a normalized deviation from the oscillation period in the signal power spectrum at the output of a channel with two beams. The distance between the bits in the “code space” is calculated as the distance normalized the effective decoding depth of the code used. Given the function describes optimal and critical values well parameters of deterministic interleavers of any length. Deterministic interleavers have a higher probability of error per bit than random interleavers. The definition of parameters using the proposed function allows the deterministic interleaver to work with the same low the probability of error per bit as well as random interleavers.

Mathematical softgauges for material ratio parameters

Editors of surface texture analysis software need to validate their parameter calculations, ideally in an implementation-independent way. Today, there is no universal reference method for validating parameter compliance and more specifically with regard to material ratio parameters, Rk parameters, and volume parameters that are based on the Abbott curve. Several years ago, at Digital Surf, we developed parameter validation methods that are based on mathematics. A mathematical softgauge, defined by an equation, is injected through the mathematical parameter definition, to obtain a mathematical true value of the parameter value. In a parallel path, a discrete softgauge, derived from the mathematical softgauge, is injected through an algorithm and the resulting value is compared to the approximated true value. This method makes it possible to check the accuracy of an algorithm for calculating a particular parameter. For this study, two families of mathematical softgauges were specifically designed to test material ratio parameters. More precisely, the two main goals of this study are, (1) to advocate an algorithm validation approach that is independent from any software implementation, and (2) to obtain true values for all parameters based on the Abbott curve.

Modeling of micromorphic continuum based on a heterogeneous microscale

Generalized continuum theories have emerged as a promising solution for the limitations of traditional continuum mechanics in fully describing the behavior of materials in which the influence of the microstructure is not negligible. The macroscopic response of quasi-brittle material, for example, is closely tied to its heterogeneous microstructure and the simplifying hypothesis of classical theory is insufficient to address all the phenomena involved. By incorporating a length scale associated to the microscale, generalized continua can handle localization issues in quasi-brittle materials represented as elastic-degrading media. An important drawback that greatly limits the applicability of such generalized models is the definition of the numerous elastic parameters. Taking into account the micromorphic theory, 18 constants are required for the description of an isotropic medium. In this paper, a numerical approach for determining the micromorphic constitutive relations, previously applied only for a homogeneous medium, is detailed based on the homogenization of a heterogeneous microscale. The microstructure formed by aggregates and matrix considered in the finer-scale is generated by the take-and-place algorithm and its behavior is described by a classical continuum. An analysis is here conducted in order to understand the effect of different characteristics of the finer-scale, as mesh, microcontinuum size, and heterogeneity distribution, on the resulting macroscopic micromorphic constitutive relations. Afterwards, a simulation is presented wherein the localization phenomenon is detected and a damage model specifically proposed for the micromorphic continuum is employed. This work could lead to models that are able to capture the microstructure influence, often disregarded when modeling quasi-brittle media, within the framework of generalized continuum theory, while also addressing the challenge of defining the elastic parameters.

Histological Scoring Systems for the Assessment of the Degree of Lung Injury in Rats

Acute respiratory distress syndrome (ARDS) is a serious pulmonary reaction with well-defined clinical parameters in humans triggered by many causes besides bacterial and viral pneumonia. However, there is no definitive definition of ARDS parameters in the experimental animal model. With its 2010 workshop report, the American Thoracic Society defined the main histopathological features that determine the presence of ARDS in laboratory animals, such as changes in parenchymal tissue, altered integrity of the alveolar capillary barrier, inflammation, and abnormal lung function. Understanding these parameters, scoring tissue lesions is used to convert observational pathological data into semi-quantitative or quantitative data for statistical analysis and improved precision.

Physical description and model validation of welded joint fatigue damage evolution

AbstractFor welded structures, the concept of damage is highly abstract and difficult to describe, leading to a lack of physical foundation and universality for existing fatigue damage accumulation models. A new fatigue damage parameter definition based on remaining bearing capacity is proposed in this paper, which is constructed by the equivalent stress on the remaining bearing surface and the equivalent stress intensity factors along the crack front curve. Tension and three‐point bending fatigue tests under two‐level loading block sequences were conducted, and the real fatigue damage evolution processes were obtained by combining measured crack front information and FEA simulation. Five damage accumulation models were utilized to estimate the fatigue damage evolution processes of the two specimens. Results show that there are differences in describing the damage evolution processes and predicting the early fatigue lives. The Rege model is most consistent with the measured data, demonstrating its applicability and effectiveness.

Circular code identified by the codon usage

Since 1996, circular codes in genes have been identified thanks to the development of 6 statistical approaches: trinucleotide frequencies per frame (Arquès and Michel, 1996), correlation functions per frame (Arquès and Michel, 1997), frame permuted trinucleotide frequencies (Frey and Michel, 2003, 2006), advanced statistical functions at the gene population level (Michel, 2015) and at the gene level (Michel, 2017). All these 3-frame statistical methods analyse the trinucleotide information in the 3 frames of genes: the reading frame and the 2 shifted frames. Notably, codon usage does not allow for the identification of circular codes (Michel, 2020). This has been a long-standing problem since 1996, hindering biologists’ access to circular code theory.By considering circular code conditions resulting from code theory, particularly the concept of permutation class, and building upon previous statistical work, a new statistical approach based solely on the codon usage, i.e. a 1-frame statistical method, surprisingly reveals the maximal C3 self-complementary trinucleotide circular code X in bacterial genes and in average (bacterial, archaeal, eukaryotic) genes, and almost in archaeal genes. Additionally, a new parameter definition indicates that bacterial and archaeal genes exhibit codon usage dispersion of the same order of magnitude, but significantly higher than that observed in eukaryotic genes. This statistical finding may explain the greater variability of codes in eukaryotic genes compared to bacterial and archaeal genes, an issue that has been open for many years. Finally, biologists can now search for new (variant) circular codes at both the genome level (across all genes in a given genome) and the gene level using only codon usage, without the need for analysing the shifted frames.

A systematic evaluation of DEM input parameters measurement and calibration

Rotary drums are widely used in industry, however, determining granular dynamics within them is still a complex task, thus remaining a focal point of research over the years. In this context, experimental techniques require numerical support to obtain data that is not easily acquired experimentally. One well-established numerical technique for studying particulate systems is the Lagrangian approach embed with Discrete Element Method (DEM). Although, DEM has limitations related to the definition of input parameters. It is crucial that DEM input parameters be measured and/or calibrated to reliably represent the granular behavior. These parameters are related to particle properties such as density, Young’s modulus, Poisson’s ratio, among others, and particle interactions, such as coefficients of restitution, static friction, and rolling friction. This study explores the experimental determination of interaction parameters preceding the acquisition of DEM input parameters in a rotary drum. Statistical analysis highlights the importance of each parameter and their combined interactions with the static angle of repose. The granular materials used were: soybeans, glass beads, polyacetal, 6 mm steel, and 4 mm steel. The coefficient of restitution was determined via free-fall methodology using equipment that verifies particle trajectory, static friction coefficient through equilibrium between weight and resistance forces, rolling friction coefficient using a launching device on surfaces of different roughness, and static angle of repose in a rectangular box with sections where particles rested. After removing the partition, angles were measured at both top and bottom sections. Regression techniques using a neural network created in Python were employed for both measurements. Experimental investigations and numerical simulations using DEM indicated that the coefficient of restitution depends on the thickness and type of material of the flat surfaces, showing an asymptotic behavior with increasing surface thickness. The static friction coefficient increased on rougher surfaces and in particles with greater imperfections. Rolling friction coefficient also increased on rough surfaces. Analysis of the angle of repose revealed that granular properties influence the response, such as static and rolling friction coefficients, whereas the coefficient of restitution had no significant influence. Neural network correlation coefficients exceeded 0.95, indicating a strong association between the variables. Our findings revealed that mathematical models can be used in conjunction with static repose angle experiments to calibrate DEM parameters for more robust and complex simulations. This research also quantifies and provides insights into the interactions between DEM parameters in direct measurement experiments, promoting more efficient calibration for future research.

First order phase transition with the functional renormalization group method

The renormalization group method, more specifically the Wegner-Houghton equation, is used to find first order phase transitions in a simple scalar field theory with a polynomial potential. An improved definition of the running parameters allows us to explore the renormalization group flow down to the IR endpoint and to locate phase transitions. Beyond the expected first order transition further radiative correction generated first and second order transitions are found. The phase diagram is reviewed by a Monte-Carlo simulation of the lattice regulated version of the theory but the serious slow down of the convergence prevents us from obtaining conclusive results from the simulation. Published by the American Physical Society 2024

Tutorial on phantoms for photoacoustic imaging applications.

Photoacoustic imaging (PAI) is an emerging technology that holds high promise in a wide range of clinical applications, but standardized methods for system testing are lacking, impeding objective device performance evaluation, calibration, and inter-device comparisons. To address this shortfall, this tutorial offers readers structured guidance in developing tissue-mimicking phantoms for photoacoustic applications with potential extensions to certain acoustic and optical imaging applications. The tutorial review aims to summarize recommendations on phantom development for PAI applications to harmonize efforts in standardization and system calibration in the field. The International Photoacoustic Standardization Consortium has conducted a consensus exercise to define recommendations for the development of tissue-mimicking phantoms in PAI. Recommendations on phantom development are summarized in seven defined steps, expanding from (1)general understanding of the imaging modality, definition of (2)relevant terminology and parameters and (3)phantom purposes, recommendation of (4)basic material properties, (5)material characterization methods, and (6)phantom design to (7)reproducibility efforts. The tutorial offers a comprehensive framework for the development of tissue-mimicking phantoms in PAI to streamline efforts in system testing and push forward the advancement and translation of the technology.

Microscopic derivation of the generalized collective Hamiltonian

The nucleus in the center-of-mass frame is described by 3A−3 independent coordinates, including three Euler angles and three variables ρ,β,andγ to describe orientation, size, and shape of the nuclear inertia ellipsoid as well as 3A−9 generalized Euler angles to describe internal motion of the nucleons. Based on the idea that the incompressible nucleus has constant density, we suggest a definition of the deformation parameter β. It allows us to derive the Hamiltonian, which describes large-amplitude collective motions. At β≪1 it reduces to a sum of the Bohr Hamiltonian and the Hamiltonian of monopole ρ vibrations. As a result of straightforward calculations we obtain explicit expressions for all the inertial parameters as functions of the variables ρ,β,andγ. Published by the American Physical Society 2024

Regional Truck Travel Characteristics Analysis and Freight Volume Estimation: Support for the Sustainable Development of Freight

In the field of freight transport, the goal of sustainable development requires us to improve the efficiency of freight transport while reducing its negative impact on the environment, such as reducing carbon emissions and noise pollution. There is no doubt that changes in freight characteristics and volumes are compatible with the objectives of sustainable development. Thus, mining the travel distribution and freight volume of trucks has an important supporting role in the freight transport industry. In terms of truck travel, most of the traditional approaches are based on the subjective definition of parameters from the trajectory data to obtain trips for certain vehicle types. As for freight volume, it is mostly estimated through manual surveys, which are heavy and inaccurate. In this study, a data-driven approach is adopted to obtain trips from the trajectory data of heavy trucks. Combined with the traffic percentage of different vehicle types collected by highway traffic survey stations, the trips of heavy trucks are extended to all trucks. The inter-city and intra-city freight volumes are estimated based on the average truck loads collected at the motorway entrance. The results show a higher proportion of intra-city trips by trucks in port cities and a higher proportion of inter-city trips by trucks in inland cities. Truck loading and unloading times are focused in the early morning or at night, and freight demand in Shandong Province is more concentrated in the south. These results would provide strong support for optimizing freight structures, improving transportation efficiency, and reducing transportation costs.