Problems In Field Research Articles

Principle of corresponding states of particle gases for passenger flights

Passenger flight delays in civil aviation systems cause much harm to people’s daily lives. Recent works confirmed that the simple laws of delays emerge from the complex interactions of the systems’ elements, the patterns of which can be traced by the actual operations of passenger flights. Figuring out the underlying mechanism of the collective behaviours of flights is required to capture the law of delays, and to alleviate them. In the present work, based on the historical records of the United States from 1995 to 2020, we propose state equations to describe the motion of Arrival/Departure(AD) type flights by considering the attractions from airports and air routes together with the repulsions between flights. We erect the universal gaseous constant R by removing the intercepts representing the systemic errors. With the linear relationship between the number of air routes and the mole number, we calculate the critical thermodynamic quantities. Introducing the reduced ones with them, we generalize the principle of corresponding states of passenger flight particle gases. According to it, we think increasing the number of AD type flights between airports would be a proper strategy for alleviating flight delays. We hope the general ideas presented here can stimulate much more work in civil aviation and be used to solve practical problems in other fields.

Ziauddin Sardar’s Critism of Modern Science

Abstract: The difference between modern Western science and Islamic science has differency from various aspects to produce several problems in the ontological field, axiological field, and epistemological field. A Pakistani-born scholar in the field of science, Ziauddin Sardar came up with an idea and movement to present Islamic science. This paper is written using the analytical-descriptive method, which analyzes and describes the weaknesses and shortcomings of modern western science against the needs of society, especially Muslims. The purpose of this paper is to reveal the problems of modern science and how Ziauddin Sardar's arguments and opinions on modern science. So that this paper produces a breakthrough in the integration of science by Ziauddin Sardar who tries to balance Western science with Islamic science that suits the needs of Muslims, and Islamic science whose scope is broad to all humanity and its civilization.

Sub-minute carbonization of polymer/carbon nanotube films by microwave induction heating for ultrafast preparation of hard carbon anodes for sodium-ion batteries

Hard carbons (HCs) are excellent anode materials for sodium-ion batteries (SIBs). However, the carbonization and granulation of HC powders involve complex processes and require considerable energy. Here, we developed a facile method for manufacturing HC anodes for SIBs via a novel microwave induction heating (MIH) process for polymer/single-walled carbon nanotube (SWCNT) films. Numerical simulations solving electromagnetic field and heat transfer problems revealed the MIH mechanism; the electric current induced by the applied microwave enables direct Joule heating of the SWCNT networks in the composite film. Consequently, the composite films could be heated to the target temperatures (800–1400 °C) and free-standing HC/SWCNT anodes could be prepared by applying MIH for only 30 s. Comparative analyses confirmed that ultrafast MIH is a reliable technique for producing HC anodes and can replace conventional carbonization processes which require a high-temperature furnace. Moreover, the HC/SWCNT anodes prepared by the ultrafast MIH were successfully applied to the SIB full cells. Finally, the feasibility of MIH for scalable roll-to-roll production of HC anodes was verified through local heating tests using a circular sheet larger than a resonator.

Determination of target site mutations and detoxification enzymes in the abamectin resistance of spider mite Tetranychus urticae collected from cotton fields of Türkiye

The two-spotted spider mite, Tetranychus urticae (Koch, 1836) (Acari: Tetranychidae) causes significant problems in cotton fields. The pest has developed resistance to abamectin, which is used intensely against spider mite populations. A discriminating dose was applied to T. urticae populations collected from Aydın, Adana, Şanlıurfa, and Diyarbakır provinces between 2019 and 2021, where there is significant cotton production and intensive acaricide applications. Populations with a mortality rate of less than 80% at the discriminating dose applied to field populations were included in the bioassay study. Then, the 10 most resistant populations were determined based on their LC50 and LC90 values. It was observed that there was high resistance (HR) in two T. urticae populations collected from Diyarbakır (DIY28 and DIY2) with LC50 values of 24.5 and 33.81 mg L-1, respectively 113 and 156-fold and one population collected from the province of Aydın (AYD4) LC50 value of 23.5 mg L-1 and 109-fold. As a result of the comparisons with a susceptible population in biochemical studies, it was determined that the carboxylesterase (CarE) enzyme of these populations (except for SAN6, SAN7, SAN8, ADA9, and ADA11) had more than 2-fold higher activity compared to the glutathione enzyme (GST), and they were in statistically different groups. When the GST enzyme activities were examined, it was found that the enzyme activities were generally low, except for the ADA11 and ADA16 populations (3.73 and 2.3-fold). In terms of the target site resistance, it was observed that there was no target site mutation (G314D and I321T-G326E) in the glutamate-gated chloride channels (Units GluCl 1 and 3) in these highest 10 resistant populations. It can be said that the resistance levels determined for abamectin from the obtained populations were determined to be low. In brief, out of the total 44 populations brought in and tested, only 30 populations were considered resistant with a mortality rate below 80% after the applied discriminating dose. It was determined that 6.8% of these 30 populations had HR, 31.8% had medium resistance (MR), and 29.5% had low resistance (LR). When examining by regions, it was found that high resistance populations were more prevalent in Diyarbakır and Aydın (15.4% and 10%, respectively) provinces, while the highest percentage of MR populations was found in Şanlıurfa, at 90%. Abamectin still acts as an effective acaricide. However, it is recommended to use acaricides with different modes of action to prevent possible emergence of resistance cases.

Development of an efficient novel method for coronary artery disease prediction using machine learning and deep learning techniques.

Heart disease is a severe health issue that results in high fatality rates worldwide. Identifying cardiovascular diseases such as coronary artery disease (CAD) and heart attacks through repetitive clinical data analysis is a significant task. Detecting heart disease in its early stages can save lives. The most lethal cardiovascular condition is CAD, which develops over time due to plaque buildup in coronary arteries, causing incomplete blood flow obstruction. Machine Learning (ML) is progressively used in the medical sector to detect CAD disease. The primary aim of this work is to deliver a state-of-the-art approach to enhancing CAD prediction accuracy by using a DL algorithm in a classification context. A unique ML technique is proposed in this study to predict CAD disease accurately using a deep learning algorithm in a classification context. An ensemble voting classifier classification model is developed based on various methods such as Naïve Bayes (NB), Logistic Regression (LR), Decision Tree (DT), XGBoost, Random Forest (RF), Convolutional Neural Network (CNN), Support Vector Machine (SVM), K Nearest Neighbor (KNN), Bidirectional LSTM and Long Short-Term Memory (LSTM). The performance of the ensemble models and a novel model are compared in this study. The Alizadeh Sani dataset, which consists of a random sample of 216 cases with CAD, is used in this study. Synthetic Minority Over Sampling Technique (SMOTE) is used to address the issue of imbalanced datasets, and the Chi-square test is used for feature selection optimization. Performance is assessed using various assessment methodologies, such as confusion matrix, accuracy, recall, precision, f1-score, and auc-roc. When a novel algorithm achieves the highest accuracy relative to other algorithms, it demonstrates its effectiveness in several ways, including superior performance, robustness, generalization capability, efficiency, innovative approaches, and benchmarking against baselines. These characteristics collectively contribute to establishing the novel algorithm as a promising solution for addressing the target problem in machine learning and related fields. Implementing the novel model in this study significantly improved performance, achieving a prediction accuracy rate of 92% in the detection of CAD. These findings are competitive and on par with the top outcomes among other methods.

The role of exposure to nature in perceived stress by veterinary students

Veterinary school is intense and represents a challenging time for students, and increasingly, veterinary students are being diagnosed with a variety of concerning mental health issues including stress, anxiety, and depression, often resulting in poor academic performance. Because of the disproportionately high risk of mental health problems in the veterinary field, it is important that students learn, understand, and utilize simple and effective techniques to cope with stress, and demands of the profession. Spending time in natural environments such as outdoor parks, green spaces, and urban forests is an effective strategy for improving mental health. In this study, we examined the self-reported effects of repeated, structured time in a nature-based intervention, vs a control group of veterinary students. Participants reported significantly lower perceived stress levels compared to a control group. Students overwhelmingly reported that they would recommend this stress reduction technique to their classmates, and they stated that they planned to continue spending time in nature to improve their mindset and reduce stress in the future.

DEVELOPMENT OF INTERACTIVE TEACHING MATERIALS WITH RME-BASED ISPRING SUITE TO IMPROVE STUDENTS' CREATIVE THINKING SKILLS

With the use of the RME-based iSpring suite, this project creates interactive teaching resources to enhance students' capacity for creative thought. Students' low capacity for creative thought, low levels of desire, low levels of activity, and low levels of involvement in the learning process are the field's problems. In order to address these issues, interactive instructional resources were created. With the help of RME-based ispring suites, interactive teaching materials will be created that are valid, useful in the educational process, and will enhance students' capacity for creative thought. 4D (define, design, development, disseminate) is the development model that is employed. Pretest-poste instruments, student response questionnaires, and validation sheets are used in data gathering procedures. Analysis methods include the paired sample t-test, validity test, and practicality test, n-gain test. With a score of 3.41, the validity test results indicate that the product is already in the legitimate category. According to the analysis of the practicality test results, the produced product already has a score of 3.43, placing it in the extremely practical category. It is established by the paired sample t-test that capacity differences exist between pre- and post-use of interactive training resources. Moreover, improving pupils' capacity for creative thought is known to fall into the effective group based on the results of the n-gain test. In order for the RME-based iSpring suite of interactive teaching resources to be generally appropriate for use in the learning process

The Theoretical, Field and Educational Problems of the Arab Researcher A Case Study of the Algerian Researcher in Information and Communication Sciences Specialty

Social human research and studies are of particular importance as they are considered the only scientific and methodologically accepted way to achieve objective facts that can contribute to the progress and prosperity of society and find solutions to its issues. However, conducting these researches encounter a number of methodological, field, administrative, social and even human difficulties. Indeed, there is no methodological part of any fieldwork that has not mentioned the problems experienced by the researcher while doing his or her scientific fieldwork, but the types of challenges differ from one society to another. This research paper seeks to know the researcher’s legal status and track his or her relationship to field research by understanding the privacy of the community in terms of carrying out research and also determining the researcher’s position in the digital world

Interaction of the population with authorities using digital technologies: sociological analysis

In the modern world new formats of civil participation for the population are emerging, associated with the use of innovative technologies. The problem of introducing and developing digital services into the public administration system at all levels of government is urgent. Experts argue that digitalization will ensure an increase in the level of efficiency in the provision of public services to the population. The problematic field of research is the level of involvement of the population in interaction with government structures in the digital space. Mastering the information environment requires certain competencies that are not developed immediately. The speed of mastering such competencies depends on many factors, including the understanding of the need for their constant use. The goal of the research is to determine the attitude of the regional population towards digital technologies used for interaction between citizens and government agencies.Today, comprehensive sociological research on this topic is required. When working on a scientific article, methods of sociocultural analysis, document analysis, and empirical collection of primary information in the form of a survey were used. The main conclusion is that for the effective development of digital interaction between the population and the authorities, it is necessary not only to introduce, but also to increase the level of trust of citizens in the digital resources of the state.

Energy‐based PINNs for solving coupled field problems: Concepts and application to the multi‐objective optimal design of an induction heater

AbstractPhysics‐informed neural networks (PINNs) are neural networks (NNs) that directly encode model equations, like Partial Differential Equations (PDEs), in the network itself. While most of the PINN algorithms in the literature minimize the local residual of the governing equations, there are energy‐based approaches that take a different path by minimizing the variational energy of the model. It is shown that in the case of the steady thermal equation weakly coupled to magnetic equation, the energy‐based approach displays multiple advantages compared to the standard residual‐based PINN: it is more computationally efficient, it requires a lower order of derivatives to compute, and it involves less hyperparameters. The analyzed benchmark problems are the single‐ and multi‐objective optimal design of an inductor for the controlled heating of a graphite plate. The optimized device is designed by involving a multi‐physics problem: a time‐harmonic magnetic problem and a steady thermal problem. For the former, a deep neural network solving the direct problem is supervisedly trained on Finite Element Analysis (FEA) data. In turn, the solution of the latter relies on a hypernetwork that takes as input the inductor geometry parameters and outputs the model weights of an energy‐based PINN (or ePINN). Eventually, the ePINN predicts the temperature field within the graphite plate.

Simple double shooting approach with bisection for FRCM reinforced curved masonry prisms subjected to shear

In this study, curved masonry pillars reinforced with FRCM subjected to standard shear tests are analyzed through a novel mono-dimensional model, where failure is governed by Mode II. Three approaches with different accuracy are proposed: i) the first, where the outer matrix is neglected; ii) the second, where the inner matrix is assumed rigid; and iii) the third which considers both matrix layers. Matrix and fiber are assumed subjected to a monoaxial state of stress and exchange tangential stresses at the interfaces. The load is applied by incrementing the displacement at the free fiber edge. Material properties of matrix, fiber and interfaces are assumed constant on small portions of the bonded length. Non-linearity is considered penalizing the elastic modulus using the results of the previous time step. The substrate is assumed rigid. The substrate curvature influence is manifested through interface normal stresses, incorporated into the bond-slip constitutive behavior via the Mohr-Coulomb law. The normal stresses can be determined by enforcing radial equilibrium. For the first two models, the field problem is constituted by a system of two 2nd order differential equations into two variables, namely the displacement of the inner (or outer) layer of mortar and of the fiber textile. A 1D shooting is employed, after having converted the boundary value problem (BVP) into an initial value one (IVP), being the latter fully explicit. For the third model, the field problem is constituted by a system of three 2nd order differential equations, and an additional displacement variable is introduced, necessitating a 2D shooting. The validation is carried out through comparisons with existing experimental data. Good predictions of the load-slip curves, for different strengthening configurations (extrados and intrados with two curvature radii), are observed. In addition, an insight into local stress distributions and material degradation for matrix layers and interfaces is obtained.

КРАТКИЙ ОБЗОР ВОЗМОЖНОСТЕЙ СОВРЕМЕННЫХ БЕСПИЛОТНЫХ ЛЕТАТЕЛЬНЫХ АППАРАТОВ ПРИ РЕШЕНИИ ЗАДАЧ ПО ОБЕСПЕЧЕНИЮ БЕЗОПАСНОСТИ

A brief analysis and generalization of the possibilities of using modern unmanned aerial vehicles in solving security problems in various fields of human activity is given. The advantages and disadvantages of modern unmanned aircraft systems are noted. Particular emphasis in the description is placed on the promising development of the capabilities of unmanned aerial vehicles. It was noted that until 2030 in the Russian Federation it is planned to invest 560 billion rubles in the development of unmanned aerial systems.

Antibacterial and Biofilm Removal Strategies Based on Micro/Nanomotors in the Biomedical Field.

Bacterial infection, which can trigger varieties of diseases and tens of thousands of deaths each year, poses serious threats to human health. Particularly, the new dilemma caused by biofilms is gradually becoming a severe and tough problem in the biomedical field. Thus, the strategies to address these problems are considered an urgent task at present. Micro/nanomotors (MNMs), also named micro/nanoscale robots, are mostly driven by chemical energy or external field, exhibiting strong diffusion and self-propulsion in the liquid media, which has the potential for antibacterial applications. In particular, when MNMs are assembled in swarms, they become robust and efficient for biofilm removal. However, there is a lack of comprehensive review discussing the progress in this aspect. Bearing it in mind and based on our own research experience in this regard, the studies on MNMs driven by different mechanisms orchestrated for antibacterial activity and biofilm removal are timely and concisely summarized and discussed in this work, aiming to show the advantages of MNMs brought to this field. In addition, an outlook was proposed, hoping to provide the fundamental guidance for future development in this area.

Modified crayfish optimization algorithm with adaptive spiral elite greedy opposition-based learning and search-hide strategy for global optimization

Abstract Crayfish optimization algorithm (COA) is a novel bionic metaheuristic algorithm with high convergence speed and solution accuracy. However, in some complex optimization problems and real application scenarios, the performance of COA is not satisfactory. In order to overcome the challenges encountered by COA, such as being stuck in the local optimal and insufficient search range, this paper proposes four improvement strategies: search-hide, adaptive spiral elite greedy opposition-based learning, competition-elimination, and chaos mutation. To evaluate the convergence accuracy, speed, and robustness of the modified crayfish optimization algorithm (MCOA), some simulation comparison experiments of 10 algorithms are conducted. Experimental results show that the MCOA achieved the minor Friedman test value in 23 test functions, CEC2014 and CEC2020, and achieved average superiority rates of 80.97%, 72.59%, and 71.11% in the WT, respectively. In addition, MCOA shows high applicability and progressiveness in five engineering problems in actual industrial field. Moreover, MCOA achieved 80% and 100% superiority rate against COA on CEC2020 and the fixed-dimension function of 23 benchmark test functions. Finally, MCOA owns better convergence and population diversity.

Numerical Analysis of Stainless Steel of Crevice Corrosion Initiation Behavior with Varying External Potentials and Initial Crevice Gaps

The potential, current density, pH, and crevice profile distribution within the crevice structure of stainless steel in seawater were numerically analyzed. The crevice corrosion phenomena were mathematically modeled with the initial boundary value problem of diffusion and static electrical field, respectively. This initial boundary value problem was discretized using a finite difference method. The predicts of the crevice corrosion behaviors, set for various external potentials and initial crevice gaps, were classified into three categories: the pitting type, the active type, and no corrosion. The pitting type crevice corrosion was predicted to occur in conditions where the external potentials were noble and the initial crevice gaps were narrow. The active type crevice corrosion was predicted to occur in conditions where the external potentials were less noble and the initial crevice gaps were narrow. The range of external potential conditions where crevice corrosion was predicted not to occur increased in conditions with wide initial crevice gaps. Crevice corrosion was predicted to occur at all external potentials in conditions where the initial crevice gaps were 2 μm or less.

Resonancelike emergence of chaos in complex networks of damped-driven nonlinear systems.

Characterizing the emergence of chaotic dynamics of complex networks is an essential task in nonlinear science with potential important applications in many fields such as neural control engineering, microgrid technologies, and ecological networks. Here, we solve a critical outstanding problem in this multidisciplinary research field: the emergence and persistence of spatiotemporal chaos in complex networks of damped-driven nonlinear oscillators in the significant weak-coupling regime, while they exhibit regular behavior when uncoupled. By developing a comprehensive theory with the aid of standard analytical methods, a hierarchy of lower-dimensional effective models, and extensive numerical simulations, we uncover and characterize the basic physical mechanisms concerning both heterogeneity-induced and impulse-induced emergence, enhancement, and suppression of chaos in starlike and scale-free networks of periodically driven, dissipative nonlinear oscillators.

A critical take on the role of random and local search-oriented components of modern computational intelligence-based optimization algorithms

The concept of computational intelligence (CI)-based optimization algorithms emerged in the early 1960s as a more practical approach to the contemporary derivate-based approaches. This paved the way for many modern algorithms to arise with an unprecedented growth rate in recent years, each claiming to have a novel and present a profound breakthrough in the field. That said, many have raised concerns about the performance of these algorithms and even identified fundamental flaws that could potentially undermine the integrity of their results. On that note, the premise of this study was to replicate some of the more prevalent, fundamental components of these algorithms in an abstract format as a measure to observe their behavior in an isolated environment. Six pseudo algorithms were designed to create a spectrum of intelligence behavior ranging from absolute randomness to local search-oriented computational architecture. These were then used to solve a set of centered and non-centered benchmark suites to see if statistically different patterns would emerge. The obtained result clearly highlighted that the algorithm’s performance would suffer significantly as these benchmarks got more intricate. This is not just in terms of the number of dimensions in the search space but also the mathematical structure of the benchmark. The implication is that, in some cases, sheer processing resources can mask the algorithm’s lack of sufficient intelligence. But as importantly, this study attempted to identify some mechanics and concepts that could potentially cause or amplify this problem. For instance, the excessive use of greedy strategy, a prevalent measure embedded in many modern CI-based algorithms, has been identified as potentially one of these reasons. The result, however, highlights a more fundamental problem in the CI-based optimization field. That is, these algorithms are often treated as a black box. This perception cultivated the culture of not exploring the underlying structure of these algorithms as long as they were deemed capable of generating acceptable results, which permits similar biases to go undetected.

Cryptanalysis of the cryptosystems based on the generalized hidden discrete logarithm problem

In this paper, we will solve an important form of hidden discrete logarithm problem (HDLP) and a generalized form of HDLP (GHDLP) over non-commutative associative algebras (FNAAs). We will reduce them to discrete logarithm problem (DLP) in a finite field through analyzing the eigenvalues of the representation matrix. Through the analysis of computational complexity, we will show that HDLP and GHDLP are not good improvements of DLP. With all the instruments in hand, we will break a series of corresponding schemes. Thus, we can conclude that all ideas of constructing cryptographic schemes based on the two solved problems are of no practical significance.

APPLICATION OF ETHNOPEDAGOGICAL MODULE IN NATURAL SCIENCES BASED ON LOCAL WISDOM TOWARDS LEARNING INDEPENDENCE IN THEMATIC LEARNING

This research aims to determine students' responses to the implementation of ethnopedagogical modules in science-based on local wisdom in thematic learning towards learning independence. The research was conducted at SD Negeri 1 Muara Satu, Lhokseumawe City. Field problems found that during the learning process in both elementary schools, thematic learning had not been linked with ethnopedagogy based on local wisdom. Consequently, students lacked learning independence at school. The research type used was a pre-experimental design, labeled as such because it was not a full-fledged experimental study. The research design used was the One-Group Posttest Design, an experiment conducted with only one group without a comparison group. The sample in this study was a fifth-grade class with 114 students, selected using purposive sampling technique. This instrument aimed to assess students' learning independence after using the teaching module. The research results indicate that the implementation of the Ethnopedagogical Module, which smoothly integrates local wisdom and cultural contexts into science education, results in enthusiastic student engagement and contextualized learning experiences. This is evidenced by the results of the student learning independence test indicators, with the highest scores found in the research results for the learning independence variable in the indicator of having a competitive drive to advance. The overall sample obtained an average score of 83.2 in the category of excellent.

Spatial Ability of Students in Solving Unit Cube Problem

This study aims to expose the ability of high school students in solving field problems three. The intended third field is the cube. This article uses a qualitative approach with in-depth interviews was conducted for 4 weeks. Data collection techniques in this study consisted of observation, interviews, tests and documentation. The interview guidelines and test in the form of planes three which aim to determine visual spatial abilities have been validated by 2 experts in the fields of mathematics and mathematics education. The research subjects were 11th grade students majoring in Science at SMAN 3 Blitar who had taken subject matter in Planes three. Based on the analysis, it can be concluded that in solving the cube problem in accordance with the spatial abilities of the subject there are several stages: the observation of the image, imagining, relating to the term from other concepts and solving the problem.