Field Method Research Articles

Allele ages provide limited information about the strength of negative selection.

For many problems in population genetics, it is useful to characterize the distribution of fitness effects (DFE) of de novo mutations among a certain class of sites. A DFE is typically estimated by fitting an observed site frequency spectrum (SFS) to an expected SFS given a hypothesized distribution of selection coefficients and demographic history. The development of tools to infer gene trees from haplotype alignments, along with ancient DNA resources, provides us with additional information about the frequency trajectories of segregating mutations. Here, we ask how useful this additional information is for learning about the DFE, using the joint distribution on allele frequency and age to summarize information about the trajectory. To this end, we introduce an accurate and efficient numerical method for computing the density on the age of a segregating variant found at a given sample frequency, given the strength of selection and an arbitrarily complex population size history. We then use this framework to show that the unconditional age distribution of negatively selected alleles is very closely approximated by re-weighting the neutral age distribution in terms of the negatively selected SFS, suggesting that allele ages provide little information about the DFE beyond that already contained in the present day frequency. To confirm this prediction, we extended the standard Poisson Random Field (PRF) method to incorporate the joint distribution of frequency and age in estimating selection coefficients, and test its performance using simulations. We find that when the full SFS is observed and the true allele ages are known, including ages in the estimation provides only small increases in the accuracy of estimated selection coefficients. However, if only sites with frequencies above a certain threshold are observed, then the true ages can provide substantial information about the selection coefficients, especially when the selection coefficient is large. When ages are estimated from haplotype data using state-of-the-art tools, uncertainty about the age abrogates most of the additional information in the fully observed SFS case, while the neutral prior assumed in these tools when estimating ages induces a downward bias in the case of the thresholded SFS.

The effect of meaning guidance approach on the ego identity of fencing players in the Kurdistan Region of Iraq

Logo counseling is one of the counseling schools, which is the human orientation that follows the applications of existential therapy, also it is considered as an effective method in psychological counseling and wider field than existential therapy because of its successfulness in developing technics in practicing counseling throughout the organization of human direction concern which study humans in terms of spiritual experience as well as biological and mental structure capable of growth, change and sublimation. (Frankl, 1976, 75). The study aims to identify the differences in self-efficiency, ego identity and lunge speed and accuracy for experiment and control groups in pre and post tests for sample players. The experiment approach is used in the study which appropriates with the nature of the research, the study population consists of senior fencing players in Kurdistan Region of (2020-2021) with a total number of (70) players distributed on (16) sport clubs, the researcher divided the population into two groups, first group for consists of (11) clubs used for scale development included (45) participants, second group included (5) clubs with (20) individuals. The researchers concludes that there is clear effect of logo counseling program prepared by researchers in developing self-efficiency and ego identity of experiment group, and there is a lack of psychological counseling instructions led to nonsignificant differences of control group individuals. In addition to the efficiency of self-efficiency scale for fencing players in Kurdistan Region – Iraq. Therefore, the researchers recommended conducting furthers for the same variables on older samples and for both genders in addition to supporting various curriculums and activities of ego identity while research one of the best methods contributes in improvement and development.

Lateral collision avoidance stability control study of intelligent vehicles on low adherence roads

To enhance lateral collision avoidance safety for intelligent vehicles on various road surfaces, this paper proposes a collision avoidance algorithm specifically designed for low-adhesion roads. The study begins by a fuzzy control lane change decision model that considers the relative state information between the ego vehicle and the front vehicle. Next, the environment risk potential field is modeled, with multiple lane change paths of varying parameters considered as candidate trajectories. Critical risks during vehicle steering are analyzed, leading to the design of a dynamic instability boundary risk point potential field. Trajectory optimization is then performed using the Particle Swarm Optimization (PSO) algorithm. Finally, a fuzzy PID controller is developed to track the optimal trajectory. Simulation results demonstrate that, compared to the traditional artificial potential field method, the proposed collision avoidance algorithm provides better lateral stability in the planned paths. Additionally, the fuzzy PID controller designed in this study outperforms the Quantitative Feedback Theory (QFT) controller in terms of tracking accuracy.

A short review of the sustainable utilization of coal gangue in environmental applications.

The production of coal gangue, a by-product of coal mining and washing, is rapidly increasing due to growing energy consumption. As the accumulated coal gangue has not been appropriately utilized, this has resulted in a squander of resources, waste disposal problems, and environmental pollution issues. However, coal gangue, a form of solid waste, exhibits various potential applications in the field of recycling. Currently, the processing capacity and utilization rate of coal gangue are insufficient to meet the demands of global low-carbon environmental protection. As such, this paper provides a detailed overview of the physical and chemical properties of coal gangue and its resource utilization methods in the environmental field, particularly in soil remediation, soil reclamation, the preparation of adsorbents for heavy metals, dyes, and CO2, and as catalysts for organic degradation and catalytic cracking. This review highlights the significance of coal gangue classification according to its properties for the comprehensive utilization of gangue. Additionally, we briefly introduce and discuss suggestions for future directions of research and development in this area. Nevertheless, with regard to the environmental impact of secondary pollution and the efficiency of coal gangue utilization, there remain numerous obstacles that hinder future research. This review is expected to provide significant insights into the development of coal gangue utilization strategies, potentially facilitating the efficient and practical large-scale management of solid waste.

Presenting a Qualitative Model for the Implementation of Transformational Leadership in the Form of an Interactive Leadership Framework (Case Study: Hospitals in Zanjan Province)

Background: The method of choosing the leadership style of an organization is very important in the success of the organization in gaining a competitive advantage in society, and on the other hand, the method of managing and creating change and innovation is also considered necessary for the success of the organization as these factors dynamically affect each other. Some create obstacles on the way and some strengthen each other. Methods: The statistical population considered for this research in the qualitative part included participants, some of whom were academic professors, and some were managers of high managerial and organizational levels who were proficient in management topics in medical sciences hospitals. In terms of method, this research had a mixed approach. In other words, a combination of quantitative and qualitative methods was used. In data collection, in general, documentary studies and field method using MAXQDA software were used. Results: The results of the evaluation showed that the observed correlation between the examined components and the transformative leadership variable was completely significant. Therefore, it was concluded that the model examined in this research had a sufficient level of significance to be used as a guide to increase the transformation of the organization by relying on the role of interactive leadership in the hospitals of Zanjan province. Conclusion: One of the important and influential factors of an organization's success is how to apply management and effective leadership styles of managers of that organization. There are managers who can choose different styles in directing human resources. Their appropriate behavior patterns in any organization cause strong morale and motivation among employees, -and subsequently, increase the motivation of employees, their level of satisfaction and the level of productivity.

Comparison of Collision Avoidance Algorithms for Unmanned Surface Vehicle Through Free-Running Test: Collision Risk Index, Artificial Potential Field, and Safety Zone

This paper details the development of a collision avoidance algorithm for unmanned surface vehicles (USVs) and its validation using free-running tests. The USV, designed as a catamaran, incorporates a variety of sensors for its guidance, navigation, and control system. It performs turning maneuvers using thrusters positioned on the port and starboard sides. The robot operating system is used to streamline communication, transmitting data such as position, orientation, and situational information from diverse sensors. Using the collision risk index (CRI) method, the algorithm calculates risk based on the distance to obstacles and the angle to the desired waypoint, directing the USV on a path with minimized risk. Noise within the data captured by the two-dimensional light detection and ranging system is filtered out using the k-dimensional tree and Euclidean distance methods, ensuring single obstacles are distinctly identified. To assess the efficacy of the CRI-based collision avoidance algorithm, it was benchmarked against other algorithms rooted in the artificial potential field and safety zone methods within an artificial tank setting. The results highlight the CRI method’s superior time efficiency and optimality in comparison to its counterparts.

Mathematical model of transient processes of DC motor with permanent-magnet excitation

Permanet magnet DC motors ( PM DCM) have an advantage over electromagnetically excited commutator motors due to their better energy performance. The application of analytical methods to study PM DCM requires significant simplifications, and the use of field methods is quite labour-intensive. In our opinion, the use of electric and magnetic circuit methods makes it possible to achieve the accuracy of calculating the PM DCM that is sufficient for engineering needs. The purpose of the article is to develop a mathematical model of transient processes in PM DCM based on the use of the theory of electric and magnetic circuits. The article proposes an equivalent scheme for the magnetic circuit of PM DCM and a system of equations describing it. There are given equations for transient processes in PM DCM and an algorithm for their solution, which involves the integration of the solution of the system of equations of the magnetic state at each step. The proposed mathematical model of transient processes in PM DCM can be used to analyze these processes, as well as in design.

Market Preparedness for Policy Interventions towards Domestic Sustainable Markets: A study on Thai Rice Supply Chain

Climate change is a critical global issue affecting environments, economies, and societies. Sustainable development, which meets current needs without compromising future generation emerged in the 1987 Brundtland Report, requiring transformation across sectors, including business, where sustainability must be central. Integrating sustainability into market strategies allows businesses to attract environmentally conscious consumers, differentiate in a competitive market, and contribute to a sustainable future. This paper examines the Thai rice supply chain using Fairtrade as a voluntary sustainability standard, exploring consumer awareness, factors influencing sustainable market practices, and market readiness for sustainable products in the Global South. Based on the research project conducted in Thailand by engaging university students by Fairtrade International, it uses desk and field methods to assess the Thai rice supply chain, Thai rice market, and Thai customers. The study is indicative of the market readiness for sustainable products and recommends that state policies are synonymous with established private sustainable standards to strengthen domestic sustainable market ecosystem.

THE IMPACT OF AI TOWARDS STUDENT’S SECOND LANGUAGE ACQUITITION

The rapid advancements in Artificial Intelligence (AI) technology have introduced transformative methods in various fields, including second language acquisition (SLA). This study aims to examine the impact of AI-based tools and platforms on the process of learning a second language, focusing on their effectiveness, challenges, and pedagogical implications. The research employs a qualitative descriptive methodology, incorporating a thorough review of relevant literature and case studies. Data collection involves analyzing academic journals, reports, and practical use cases of AI-based language learning applications such as Duolingo and Babbel. Thematic analysis is utilized to organize data into core themes, including the personalization of learning, feedback mechanisms, and cultural context adaptation. The findings reveal that AI provides significant benefits in SLA by enabling personalized learning experiences and offering instant, adaptive feedback tailored to individual learners. However, challenges such as the inability of AI to fully understand cultural nuances and ethical concerns surrounding data privacy persist. These insights underline the need for strategic integration of AI in education, emphasizing a balance between technological potential and the human aspects of language learning. This study contributes to the growing body of research on AI in education, offering practical recommendations for educators, policymakers, and developers to harness AI's potential effectively in enhancing second language acquisition.

Research on multiple quadrotor UAV formation obstacle avoidance based on finite-time consensus

Abstract Aiming at the problem of fast and consensus obstacle avoidance of multiple unmanned aerial systems in undirected network, a multi-quadrotor unmanned aerial vehicles UAVs (QUAVs) finite-time consensus obstacle avoidance algorithm is proposed. In this paper, multi-QUAVs establish communication through the leader-following method, and the formation is led by the leader to fly to the target position automatically and avoid obstacles autonomously through the improved artificial potential field method. The finite-time consensus protocol controls multi-QUAVs to form a desired formation quickly, considering the existence of communication and input delay, and rigorously proves the convergence of the proposed protocol. A trajectory segmentation strategy is added to the improved artificial potential field method to reduce trajectory loss and improve the task execution efficiency. The simulation results show that multi-QUAVs can be assembled to form the desired formation quickly, and the QUAV formation can avoid obstacles and maintain the formation unchanged while avoiding obstacles.

A Comparative Study of Isogeometric Analysis for Topology Optimzation Based on the Level Set and the Phase Field Methods

A Comparative Study of Isogeometric Analysis for Topology Optimzation Based on the Level Set and the Phase Field Methods

Evaluation of the dynamics of nutrients and potentially toxic elements along a major river in Ethiopia using multivariate statistical techniques: Implications of possible co-occurrences

This study utilized established field and laboratory methods and multivariate statistical tools to evaluate the nutrient and potentially toxic elements (PTEs) distribution, identify possible sources, and determine potential co-existence in the Awash River. The levels of soluble reactive phosphorus (SRP), total phosphorus (TP), NO3-N, Mn, Ni, Cr, and Cu generally increased downstream in the upper Awash, with the highest respective values of 0.70, 1.34, 1.19, 1.58, 1.03, 0.85, and 0.11 mg L−1 at the inlet to Lake Koka. Sites found downstream of the inflow of Lake Beseka and Metehara town showed the highest levels of Fe, B, Zn, and dissolved silica. Principal components and correlation analysis findings revealed strong associations (r ≥ 0.80, p < 0.05) between nutrient parameters (SRP, TP, and NO3-N) and PTEs (Cu, Ni, Mn, and Cr), implying common origins and potential co-occurrences. The potential co-occurrences of these parameters may strengthen their potential individual impacts due to complex interactions.

Grain structure control of TC11 alloy in laser direct energy deposition by a static magnetic field

This paper describes a novel in-situ adjustment method of static magnetic field (SMF) for laser additive manufacturing, which realizes the change of grain morphology and weave structure without changing the composition and performing post-processing. The TC11 alloy was prepared by laser direct energy deposition (LDED) under static SMF. The results show that a transverse static SMF of 0.5 T effectively suppresses the tendency of columnar crystals to grow continuously along the build direction and the dominant weaving direction of <0001> texture, and reduces the anisotropy of the TC11 alloy.

A Curriculum-Style Self-Training Approach for Source-Free Semantic Segmentation.

Source-free domain adaptation has developed rapidly in recent years, where the well-trained source model is adapted to the target domain instead of the source data, offering the potential for privacy concerns and intellectual property protection. However, a number of feature alignment techniques in prior domain adaptation methods are not feasible in this challenging problem setting. Thereby, we resort to probing inherent domain-invariant feature learning and propose a curriculum-style self-training approach for source-free domain adaptive semantic segmentation. In particular, we introduce a curriculum-style entropy minimization method to explore the implicit knowledge from the source model, which fits the trained source model to the target data using certain information from easy-to-hard predictions. We then train the segmentation network by the proposed complementary curriculum-style self-training, which utilizes the negative and positive pseudo labels following the curriculum-learning manner. Although negative pseudo-labels with high uncertainty cannot be identified with the correct labels, they can definitely indicate absent classes. Moreover, we employ an information propagation scheme to further reduce the intra-domain discrepancy within the target domain, which could act as a standard post-processing method for the domain adaptation field. Furthermore, we extend the proposed method to a more challenging black-box source model scenario where only the source model's predictions are available. Extensive experiments validate that our method yields state-of-the-art performance on source-free semantic segmentation tasks for both synthetic-to-real and adverse conditions datasets.

Research on seismic characteristics of supercharged boiler based on measured boundary

Supercharged boilers are susceptible to seismic impact loads, which can cause severe structural responses and exceed their ultimate bearing capacity. Compared with the traditional simplified structural model for earthquake resistance research in cold state, this paper establishes a real and complete three-dimensional physical model of the supercharged boiler base, and uses the reverse calculation method to obtain the boundary conditions of the boiler based on the temperature of the experimental measurement points. The temperature field and pressure field of the boiler are reconstructed, combined with the coupling method of thermal mechanical solid multiple physical fields. Using time-domain data of peak acceleration in various directions under typical earthquakes as external input loads, this study explores the seismic characteristics of boilers in the X, Y, and Z directions using time-domain analysis methods, and clarifies the vibration response mechanism in the stress concentration area of the tube sheet. The results show that the measurement and simulation error of the temperature of the inner and outer walls of the drum is 0.10 %; The individual effects of thermal stress and mechanical stress account for 107.56 % and 66.46 % of the total stress, respectively. Thermal stress plays a dominant role, while mechanical stress produces impedance effects; Under the action of an earthquake, the tube sheet undergoes reciprocating oscillation motion, and the impedance effect generated by the flexibility of the tube bundle gradually attenuates. The local stress in the X and Y directions increases by 7.70–8.27 MPa, while the local stress concentration phenomenon occurs in the Z direction due to low damping and stiffness.

Oscillatory responses of a spatially random seabed in the vicinity of structures: Validation and application of the integrated CFD-SFEM

A comprehensive examination of the wave-induced oscillatory response of seabeds around structures is of great significance for ensuring the safe operation of marine engineering projects and enhancing the efficiency of marine resource development. Soil properties in nature exhibit spatial variability due to various geological processes, which should be considered in seabed stability analysis. An integrated CFD-SFEM is proposed for spatially heterogeneous seabeds, incorporating multi-physical solvers for nonlinear wave motion and poroelastic seabed response within a unified framework through a one-way coupling procedure. The wave sub-model for nonlinear fluid flow is based on RANS equations, with an internal wave-maker and absorbing layers realized by employing a momentum source function and damping source terms. The spatially heterogeneous seabed sub-model is based on Biot’s poroelastic theory and the random field method. We have implemented the integrated model and automated the iterative algorithm for MCS using MATLAB codes, assisted by the LiveLink platform. The proposed method has been validated from various perspectives and applied to a study of soil response around a partially buried pipeline to demonstrate its practical utility. This study offers a novel framework and perspective for the probabilistic evaluation of oscillatory responses in spatially varied seabeds surrounding structures.

Data-driven model assessment: A comparative study for ship response determination

Several machine learning approaches to determine ship responses via data-driven models have been applied. Input features and parameters used relied on time-series analyses obtained from computational-fluid-dynamics approach. As inputs into the data-driven model, the heave and pitch motions of a ship advancing in irregular, i.e., natural seaway were considered. By using different models in the framework of machine learning, required computation for the associated ship motions may be avoided, thus reducing the computational effort to forecast ship motions. Comparative predictions with numerical simulations revealed that the deep-neural-network method for training in auto-machine-learning instructions yielded the highest accuracy in heave motion, resulting in a non-normalized mean-absolute-error of 0.74, against the corresponding error of 1.07 from numerical computations, whereas the method trained with the tree-based models (the extreme gradient boosting and the Hist gradient boosting regressor) predicted less accurate motions for the tested ship. The model trained with the random forest regressor exhibited an error of 1.10. Numerical simulation based on a field method proved to be the most suitable choice for pitch motion. Despite the few samples available to train the regressors, results demonstrated that the measured data was sufficient to assess the developed data-driven model for ship response determination.

A nonlocal macro-meso-scale damage model based modeling for crack propagation in ferroelectric materials

The accurate simulation of crack growth for ferroelectric materials plays a crucial role in the application of ferroelectric materials in electronic devices. In recent years, a nonlocal macro-meso-scale consistent damage (NMMD) model has been proposed for simulating the crack propagation in brittle materials, which offers the advantage of higher efficiency compared to the phase-field method. Different from the phase field method, this model does not need to solve the phase field equation at the same time. Therefore, the degree of freedom in solving can be reduced, thereby reducing the computational workload. In this paper, the authors proposed a new integration strategy for microscopic damage and devised a simple and efficient implementation of the NMMD model for the modelling of quasi-static fracture in the general purpose commercial software developer, COMSOL Multiphysics based on the finite element method (FEM) and studied the crack propagation for ferroelectric materials under the applied stress and electric fields. Different from the original NMMD model, only the tensile stress induced geometric damage is accounted for crack propagation by using the decomposition of elastic strain energy. The effects of different crack-face conditions, electrical boundary conditions and the electromechanical loading for crack growth of ferroelectric materials have been considered in our FEM simulation are discussed in this work.

Phase separation behavior of polymer modified asphalt by molecular dynamics and phase field method: A Review

Phase separation behavior of polymer modified asphalt by molecular dynamics and phase field method: A Review

Application of the River Habitat Survey Method in the Assessment of the Human Pressure Within the Lowland River Catchment: The Mollusc Biodiversity Versus Habitat Features

The objectives of our study were to analyse the degree of human pressure within the lowland river catchment in relation to the mollusc communities and to assess the usefulness of the River Habitat Survey as a field method in determining the human pressure in the mollusc biodiversity context. The River Habitat Survey (RHS), an essential method for hydromorphological studies of rivers under the requirements of the European Union Water Framework Directive, was applied. This study showed that the diversity of molluscs was impacted by several environmental factors acting simultaneously, including pH, concentration of ammonium nitrogen in water, and the habitat features depending on the degree of human pressure on the river. The result of the RHS method confirmed that the occurrence of molluscs including Unio crassus and Pseudanodonta complanata, the endangered species on a global scale, was associated with the extensive presence of several natural habitat features in the river channel. The RHS method proved to be an indispensable tool for assessing the relationships between the diversity of aquatic organisms and the degree of habitat anthropogenic modification of river environments. It seems innovative and necessary, especially in restoring the natural character of rivers.