Electrostatic Cleaning System Integrated with Thunderon Brush for Lunar Dust Mitigation

Detrimental effects of lunar dust on space hardware, spacesuits, and astronauts’ health have been already identified during Apollo missions. Developing effective dust mitigation technologies is critically important for successful space exploration and related missions in NASA applications. In this study, an electrostatic cleaning system (ECS) integrated with a negatively ionized Thunderon brush was developed to mitigate small-sized lunar dust particles with diameters ranging from 0.04 µm to 35 µm, and the mean and median size of 7 µm and 5 µm, respectively. It was found that the frequency pulses of the negative ion generator caused particles to stick to the Thunderon bristles and repel between the pulses. The brush was used manually to ensure that particles were removed from areas where the ECS failed to mitigate the lunar simulant. The acquired data demonstrated that the developed system removed over 91-96% of the lunar dust particles. The present study was performed as a proof-of-concept to enhance the cleaning performance of ECSs by integrating a brushing process. Suggestions were made to further improve the performance of the developed technology through future research.

Recycling of Sintered NdFeB Magnet Waste via Oxidative Roasting and Selective Leaching

Neodymium-iron-boron (NdFeB) magnets classified as high-power magnets are widely used in various applications such as automotive, electrical and medical devices. Because significant amounts of rare earth metals will be subjected to shortages in the future, therefore domestic NdFeB magnet waste recycling should therefore be developed in order to reduce social and environmental impacts towards a circular economy. Each type of wastes has different characteristics and compositions. As a result, these directly affect recycling efficiency as well as types and purity of the recyclable products. This research, therefore, focused on the recycling of manufacturing NdFeB magnet waste obtained from the sintering stage of magnet production and the waste contained 23.6% Nd, 60.3% Fe and 0.261% B in order to recover high purity neodymium oxide (Nd2O3) using hybrid metallurgical process via oxidative roasting and selective leaching techniques. The sintered NdFeB waste was first ground to under 70 mesh prior to oxidative roasting at 550–800 oC to enable selective leaching of neodymium in the subsequent leaching step using H2SO4 at 2.5 M over 24 h. The leachate was then subjected to drying and roasting at 700–800 oC prior to precipitation by oxalic acid and calcination to obtain Nd2O3 as the recycling product. According to XRD analyses, it was found that increasing oxidative roasting temperature led to an increasing amount of hematite (Fe2O3) as the main composition with a smaller amount of magnetite (Fe3O4) found. Peaks of Nd2O3 were also observed in a lesser amount. Furthermore, neodymium iron oxide (NdFeO3) was present and its XRD peaks were pronounced at higher oxidative roasting temperatures. When proceeded to acid leaching and drying, iron sulfate and neodymium sulfate were mainly obtained. After the roasting step prior to water leaching, iron sulfate was converted to form Fe2O3 as the main compound, while neodymium sulfate remained in the ingredient. However, a small amount of Fe3O4 was still detected by XRD. The higher roasting temperature at 800 oC resulted in a greater Fe2O3 to Nd2(SO4)3 ratio, indicating a more effective roasting temperature. Iron oxides were subsequently water leached and filtered out while the solution contained mainly neodymium sulfate. Therefore, low oxidative roasting temperature not exceeding 600 oC followed by acid leaching and roasting at 800 oC gave the optimum condition for further steps of precipitation and calcination to finally achieve Nd2O3.

Modern Tragic Substance in O’Neill’s Desire under the Elms and Mourning Becomes Electra

The position Eugene O’Neill occupies in the history of American drama is undisputable. Critics have agreed that the American theatre was waiting for O’Neill to give it substance, character, and value. The American dramatist continues to be considered as a major influence on the body of dramatic repertoire across the globe. The American theatre before O’Neill knew playwrights who were mostly viewed as entertainers. The serious drama had to wait until O’Neill started his career with expressionistic and social drama. His breakthrough, however, came in 1925 when he published Desire Under the Elms, described as the first important tragedy to be written in America. Mourning Becomes Electra, published in 1931, further reinforced the reputation of Eugene O’Neill and was described as his 'magnum opus'. Aspiring to portray the essence of life and man’s innermost conflicts, O’Neill turned to the classical model, rather than to social realistic drama, to create modern tragedies with the aid of the then-new science of psychology. The present paper aims to undertake an in-depth study of how overtones from classical tragedies by the classical masters Aeschylus, Sophocles, and Euripides resonate through O’Neill’s two plays. The paper shows how leaning on classical themes and concepts interpreted in terms of psychological forces have added depth and tragic substance to a modern milieu and produced masterpieces of dramaturgy.

Nascent Federalism in Nepal: An Observational Review in Its Evolution

Nepal practiced a centralized unitary governing system for long and has gone through the federal system after the promulgation of the new constitution on 20 September 2015. There is a big paradigm shift in terms of governance after it. Now, there are three levels of governments, one federal government in the center, seven provincial governments and 753 local governments. Federalism refers to a political governing system with multiple tiers of government working together with coordination. It is preferred for self and shared rule. Though it has opened the door for rights of the people, political stability, state restructuring, and sustainable peace and development, there are many prospects and challenges for its proper implementation. This research analyzes the discourses of federalism implementation in Nepal with special reference to one of seven provinces, Gandaki. Federalism is a new phenomenon in Nepali politics and informed debates on it are required for its right evolution. This research will add value in this regard. Moreover, tracking its evolution and the exploration of the attitudes and behaviors of key actors and stakeholders in a new experiment of a new governing system is also important. The administrative and political system of Gandaki province in terms of service delivery and development will critically be examined. Besides demonstrating the performances of the provincial government and assembly, it will analyze the inter-governmental relation of Gandaki with the other two tiers of government. For this research, people from provincial and local governments (elected representatives and government employees), provincial assembly members, academicians, civil society leaders and journalists are being interviewed. The interview findings will be analyzed by supplementing with published documents. Just going into the federal structure is not the solution. As in the case of other provincial governments, Gandaki also had to start from scratch. It gradually took a shape of government and has been functioning sluggishly. The provincial government has many challenges ahead, which has badly hindered its plans and actions. Additionally, fundamental laws, infrastructures and human resources are found to be insufficient at the sub-national level. Lack of clarity in the jurisdiction is another main challenge. The Nepali Constitution assumes cooperation, coexistence and coordination as the fundamental principles of federalism which, unfortunately, appear to be lacking among the three tiers of government despite their efforts. Though the devolution of power to sub-national governments is essential for the successful implementation of federalism, it has apparently been delayed due to the centralized mentality of bureaucracy as well as a political leader. This research will highlight the reasons for the delay in the implementation of federalism. There might be multiple underlying reasons for the slow pace of implementation of federalism and identifying them is very tough. Moreover, the federal spirit is found to be absent in the main players of today's political system, which is a big irony. So, there are some doubts about whether the federal system in Nepal is just a keepsake or a substantive achievement.

The Importance of Compulsory Pre-School Education from the Parents’ Perspective in the Czech Republic

The study deals with the presentation of the results of quantitatively oriented research. The research was conducted as part of a questionnaire survey with the aim to find out what are the attitudes of parents to compulsory preschool education in the Czech Republic. This research presents results from the area of importance of compulsory pre-school education from the parents’ perspective. The research method was a questionnaire, which was distributed to respondents through an online platform. The research involved 107 parents, who answered a total of 36 questions that found out their attitudes to last year’s compulsory preschool attendance. The results show that compulsory pre-school attendance has increased the importance of pre-school education. However, the results also show that the compulsory last year of preschool education is not more important according to parents than in previous years. Most participants consider compulsory pre-school attendance to be important and are happy that their child attends it. The results reveal the fact that the introduction of compulsory pre-school attendance has contributed to the importance of parents’ perceptions of pre-primary education.

Scenario and Decision Analysis for Solar Energy in Egypt by 2035 Using Dynamic Bayesian Network

Bayesian networks are now considered to be a promising tool in the field of energy with different applications. In this study, the aim was to indicate the states of a previous constructed Bayesian network related to the solar energy in Egypt and the factors affecting its market share, depending on the followed data distribution type for each factor, and using either the Z-distribution approach or the Chebyshev’s inequality theorem. Later on, the separate and the conditional probabilities of the states of each factor in the Bayesian network were derived, either from the collected and scrapped historical data or from estimations and past studies. Results showed that we could use the constructed model for scenario and decision analysis concerning forecasting the total percentage of the market share of the solar energy in Egypt by 2035 and using it as a stable renewable source for generating any type of energy needed. Also, it proved that whenever the use of the solar energy increases, the total costs decreases. Furthermore, we have identified different scenarios, such as the best, worst, 50/50, and most likely one, in terms of the expected changes in the percentage of the solar energy market share. The best scenario showed an 85% probability that the market share of the solar energy in Egypt will exceed 10% of the total energy market, while the worst scenario showed only a 24% probability that the market share of the solar energy in Egypt will exceed 10% of the total energy market. Furthermore, we applied policy analysis to check the effect of changing the controllable (decision) variable’s states acting as different scenarios, to show how it would affect the target nodes in the model. Additionally, the best environmental and economical scenarios were developed to show how other factors are expected to be, in order to affect the model positively. Additional evidence and derived probabilities were added for the weather dynamic nodes whose states depend on time, during the process of converting the Bayesian network into a dynamic Bayesian network.

Supplementary Cementitious Materials as Sustainable Partial Replacement for Cement in the Building Industry

Cement is the most extensively used construction material due to its strength and versatility of use. However, the production of Portland cement has become unsustainable because of high energy usage, reduction of natural non-renewable resources and emissions of greenhouse gases. Production of cement contributes to anthropogenic greenhouse gases emissions annually. The growing concerns for the environment resulting from this constant and excessive use of cement has therefore raised the need for more green materials and technology. The use of supplementary cementitious materials (SCMs) is considered as one of the many alternatives suited to address this issue and serve as a sustainable partial replacement for cement in construction. This paper will examine the reuse of these waste materials to partially replace Portland cement. It provides a critical review of literature analysing various supplementary cementitious materials which are applicable in the building industry as either partial replacement for cement or aggregates. These materials have been grouped based on source into industrial wastes, domestic/general wastes, and agricultural wastes. The reuse of these waste materials could potentially reduce the negative effects of cement production and reduce landfills which constitute an environmental nuisance. This paper seeks to inform building industry professionals and researchers in the field on the applicability of these waste materials in construction.

Gaits Stability Analysis for a Pneumatic Quadruped Robot Using Reinforcement Learning

Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Spexin and Fetuin A in Morbid Obese Children

Spexin, expressed in the central nervous system, has attracted much interest in feeding behavior, obesity, diabetes, energy metabolism and cardiovascular functions. Fetuin A is known as the negative acute phase reactant synthesized in the liver. Eosinophils are early indicators of cardiometabolic complications. Patients with elevated platelet count, associated with hypercoagulable state in the body, are also more liable to cardiovascular diseases (CVDs). In this study, the aim is to examine the profiles of spexin and fetuin A concomitant with the course of variations detected in eosinophil as well as platelet counts in morbid obese children. 34 children with normal-body mass index (N-BMI) and 51 morbid obese (MO) children participated in the study. Written-informed consent forms were obtained prior to the study. Institutional ethics committee approved the study protocol. Age- and sex-adjusted BMI percentile tables prepared by World Health Organization were used to classify healthy and obese children. Mean age ± SEM of the children were 9.3 ± 0.6 years and 10.7 ± 0.5 years in N-BMI and MO groups, respectively. Anthropometric measurements of the children were taken. BMI values were calculated from weight and height values. Blood samples were obtained after an overnight fasting. Routine hematologic and biochemical tests were performed. Within this context, fasting blood glucose (FBG), insulin (INS), triglycerides (TRG), high density lipoprotein-cholesterol (HDL-C) concentrations were measured. Homeostatic model assessment for insulin resistance (HOMA-IR) values were calculated. Spexin and fetuin A levels were determined by enzyme-linked immunosorbent assay. Data were evaluated from the statistical point of view. Statistically significant differences were found between groups in terms of BMI, fat mass index, INS, HOMA-IR and HDL-C. In MO group, all parameters increased as HDL-C decreased. Elevated concentrations in MO group were detected in eosinophils (p < 0.05) and platelets (p > 0.05). Fetuin A levels decreased in MO group (p > 0.05). However, decrease was statistically significant in spexin levels for this group (p < 0.05). In conclusion, these results have suggested that increases in eosinophils and platelets exhibit behavior as cardiovascular risk factors. Decreased fetuin A behaved as a risk factor suitable to increased risk for cardiovascular problems associated with the severity of obesity. Along with increased eosinophils, increased platelets and decreased fetuin A, decreased spexin was the parameter, which reflects best its possible participation in the early development of CVD risk in MO children.

Hematologic Inflammatory Markers and Inflammation-Related Hepatokines in Pediatric Obesity

Obesity in children particularly draws attention, because it may threaten the individual’s future life due to many chronic diseases it may lead to. Most of these diseases including obesity itself altogether are related to inflammation. For this reason, inflammation-related parameters gain importance. Within this context, complete blood cell counts, ratios or indices derived from these counts have recently found some platform to be used as inflammatory markers. So far, mostly adipokines were investigated within the field of obesity. Metabolic inflammation is closely associated with cellular dysfunction. In this study, hematologic inflammatory markers and cytokines produced predominantly by the liver (fibroblast growth factor-21 (FGF-21) and fetuin A) were investigated in pediatric obesity. Two groups were constituted from 76 obese children based on World Health Organization criteria. Group 1 was composed of children, whose age- and sex-adjusted body mass index (BMI) percentiles were between 95 and 99. Group 2 consists of children, who are above 99th percentile. The first and the latter groups were defined as obese (OB) and morbid obese (MO). Anthropometric measurements of the children were performed. Informed consent forms and the approval of the institutional ethics committee were obtained. Blood cell counts and ratios were determined by automated hematology analyzer. The related ratios and indexes were calculated. Statistical evaluation of the data was performed by SPSS program. There was no statistically significant difference in terms of neutrophil-to lymphocyte ratio, monocyte-to-high density lipoprotein cholesterol ratio and platelet-to-lymphocyte ratio between the groups. Mean platelet volume and platelet distribution width values were decreased (p < 0.05), total platelet count, red cell distribution width (RDW) and systemic immune inflammation index values were increased (p < 0.01) in MO group. Both hepatokines were increased in the same group, however increases were not statistically significant. In this group, also a strong correlation was calculated between FGF-21 and RDW when controlled by age, hematocrit, iron and ferritin (r = 0.425; p < 0.01). In conclusion, the association between RDW, a hematologic inflammatory marker, and FGF-21, an inflammation-related hepatokine, found in MO group is an important finding discriminating between OB and MO children. This association is even more powerful when controlled by age and iron-related parameters.

Scholar Index for Research Performance Evaluation Using Multiple Criteria Decision Making Analysis

This paper aims to present an objective quantitative methodology on how to evaluate individual’s scholarly research output using multiple criteria decision analysis. A multiple criteria decision making analysis (MCDMA) methodological process is adopted to build a multiple criteria evaluation model. With the introduction of the scholar index, which gives significant information about a researcher's productivity and the scholarly impact of his or her publications in a single number (s is the number of publications with at least s citations); cumulative research citation index; the scholar index is included in the citation databases to cover the multidimensional complexity of scholarly research performance and to undertake objective evaluations with scholar index. The scholar index, one of publication activity indexes, is analyzed by considering it to be the most appropriate sciencemetric indicator which allows to smooth over many drawbacks of scholarly output assessment by mere calculation of the number of publications (quantity) and citations (quality). Hence, this study includes a set of indicators-based scholar index to be used for evaluating scholarly researchers. Google Scholar open science database was used to assess and discuss scholarly productivity and impact of researchers. Based on the experiment of computing the scholar index, and its derivative indexes for a set of researchers on open research database platform, quantitative methods of assessing scholarly research output were successfully considered to rank researchers. The proposed methodology considers the ranking, and the selection of data on which a scholarly research performance evaluation was based, the analysis of the data, and the presentation of the multiple criteria analysis results.

Heavy Deformation and High-Temperature Annealing Microstructure and Texture Studies of TaHfNbZrTi Equiatomic Refractory High Entropy Alloy

The refractory alloys are crucial for high-temperature applications to improve performance and reduce cost. They are used in several applications such as aerospace, outer space, military and defense, nuclear powerplants, automobiles, and industry. The conventional refractory alloys show greater stability at high temperatures and in contrast they have operational limitations due to their low melting temperatures. However, there is a huge requirement to improve the refractory alloys’ operational temperatures and replace the conventional alloys. The newly emerging refractory high entropy alloys (RHEAs) could be alternative materials for conventional refractory alloys and fulfill the demands and requirements of various practical applications in the future. The RHEA TaHfNbZrTi was prepared through an arc melting process. The annealing behavior of severely deformed equiatomic RHEATaHfNbZrTi has been investigated. To obtain deformed condition, the alloy is cold-rolled to 90% thickness reduction and then subjected to an annealing process to observe recrystallization and microstructural evolution in the range of 800 °C to 1400 °C temperatures. The cold-rolled – 90% condition shows the presence of microstructural heterogeneity. The annealing microstructure of 800 °C temperature reveals that partial recrystallization and further annealing treatment carried out annealing treatment in the range of 850 °C to 1400 °C temperatures exhibits completely recrystallized microstructures, followed by coarsening with a degree of annealing temperature. The deformed and annealed conditions featured the development of body-centered cubic (BCC) fiber textures. The experimental investigation of heavy deformation and followed by high-temperature annealing up to 1400 °C temperature will contribute to the understanding of microstructure and texture evolution of emerging RHEAs.

Assessing and Evaluating the Course Outcomes of Control Systems Course Mapping Complex Engineering Problem Solving Issues and Associated Knowledge Profiles with the Program Outcomes

In the current context, the engineering program educators need to think about how to develop the concepts and complex engineering problem-solving skills through various complex engineering activities by the undergraduate engineering students in various engineering courses. But most of them are facing challenges to assess and evaluate these skills of their students. In this study, detailed assessment and evaluation methods for the undergraduate Electrical and Electronic Engineering (EEE) program are stated using the Outcome-Based Education (OBE) approach. For this purpose, a final year course titled control systems has been selected. The assessment and evaluation approach, course contents, course objectives, course outcomes (COs), and their mapping to the program outcomes (POs) with complex engineering problems and activities via the knowledge profiles, performance indicators, rubrics of assessment, CO and PO attainment data, and other statistics, are reported for a student-cohort of control systems course registered by the students of BSc in EEE program in Spring 2021 Semester at the EEE Department of Southeast University (SEU). It is found that the target benchmark was achieved by the students of that course. Several recommendations for the continuous quality improvement (CQI) process are also provided.

Destination Port Detection for Vessels: An Analytic Tool for Optimizing Port Authorities Resources

Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages Automatic Identification System (AIS) messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring AIS messages. Our RRo method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measures to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Frechet Distance (DFD), Dynamic Time ´ Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an f-measure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Evaluation of Corrosion in Steel Reinforced Concrete with Brick Waste

The massive demolition of old buildings in recent years has generated tons of waste, especially brick waste. Thus, a concern of recent research is the use of this waste for the production of environmentally friendly concrete. At the same time, corrosion of the reinforcement steel rebar in classical concrete is a current problem. In this context, in the present paper a study was carried out on the corrosion of metal reinforcement in cement mortars with added brick waste. The corrosion process was analyzed on four compositions of mortars without and with 15%, 25% and 35% brick waste replacing the sand. The brick waste has majority content in SiO2, Al2O3, FeO3 and CaO. The grain size distribution of brick waste was close to that of the sand (dmax = 2 mm). The preparation method of the samples was similar to ordinary mortars. The corrosion action on the rebar in concrete, at different brick waste concentrations, was investigated by electrochemical measurements (polarization curves and electrochemical impedance spectroscopy (EIS)) at 1 month and 26 months. The results obtained at 26 months revealed that the addition of the brick waste in mortar improved the anticorrosion properties in the case of all samples compared with the etalon mortar. The best results were obtained in the case of the sample with 15% brick waste (the efficiency was ≈ 90%). The corrosion intermediary layer formed on the rebar surface was evidenced by SEM-EDX.

Stop Consonants in Chinese and Slovak: Contrastive Analysis by Using Praat

The acquisition of the correct pronunciation in Chinese is closely linked to the initial phase of the study. Based on the contrastive analysis, we determine the differences in the pronunciation of stop consonants in Chinese and Slovak taking into consideration the place and manner of articulation to gain a better understanding of the students' main difficulties in the process of acquiring correct pronunciation of Chinese stop consonants. We employ the software Praat for the analysis of the recorded samples with an emphasis on the pronunciation of the students with a varying command of Chinese. The comparison of the voice onset time (VOT) length for the individual consonants in the students' pronunciation and the pronunciation of the native speaker exposes the differences between the correct pronunciation and the deviant pronunciation of the students.

IntelligentLogger: A Heavy-Duty Vehicles Fleet Management System Based on IoT and Smart Prediction Techniques

Both daily and long-term management of a heavy-duty vehicles and construction machinery fleet is an extremely complicated and hard to solve issue. This is mainly due to the diversity of the fleet vehicles – machinery, which concerns not only the vehicle types, but also their age/efficiency, as well as the fleet volume, which is often of the order of hundreds or even thousands of vehicles/machineries. In the present paper we present “InteligentLogger”, a holistic heavy-duty fleet management system covering a wide range of diverse fleet vehicles. This is based on specifically designed hardware and software for the automated vehicle health status and operational cost monitoring, for smart maintenance. InteligentLogger is characterized by high adaptability that permits to be tailored to practically any heavy-duty vehicle/machinery (of different technologies -modern or legacy- and of dissimilar uses). Contrary to conventional logistic systems, which are characterized by raised operational costs and often errors, InteligentLogger provides a cost-effective and reliable integrated solution for the e-management and e-maintenance of the fleet members. The InteligentLogger system offers the following unique features that guarantee successful heavy-duty vehicles/machineries fleet management: (a) Recording and storage of operating data of motorized construction machinery, in a reliable way and in real time, using specifically designed Internet of Things (IoT) sensor nodes that communicate through the available network infrastructures, e.g., 3G/LTE; (b) Use on any machine, regardless of its age, in a universal way; (c) Flexibility and complete customization both in terms of data collection, integration with 3rd party systems, as well as in terms of processing and drawing conclusions; (d) Validation, error reporting & correction, as well as update of the system’s database; (e) Artificial intelligence (AI) software, for processing information in real time, identifying out-of-normal behavior and generating alerts; (f) A MicroStrategy based enterprise BI, for modeling information and producing reports, dashboards, and alerts focusing on vehicles– machinery optimal usage, as well as maintenance and scraping policies; (g) Modular structure that allows low implementation costs in the basic fully functional version, but offers scalability without requiring a complete system upgrade.

Threshold Concepts in TESOL: A Thematic Analysis of Disciplinary Guiding Principles

The notion of Threshold Concepts has offered a fertile new perspective on the transformative effects of mastery of particular concepts on student understanding of subject matter and their developing identities as inductees into disciplinary discourse communities. Only by successfully traversing essential knowledge thresholds can neophytes achieve the more sophisticated understandings of subject matter possessed by mature members of a discipline. This paper uses thematic analysis of disciplinary guiding principles to identify nine candidate Threshold Concepts that appear to underpin effective TESOL practice. The relationship between these candidate TESOL Threshold Concepts, TESOL principles, and TESOL instructional techniques appears to be amenable to a schematic representation based on superordinate categories of TESOL practitioner concern and, as such, offers an alternative to the view of Threshold Concepts as a privileged subset of disciplinary core concepts. The paper concludes by exploring the potential of a Threshold Concepts framework to productively inform TESOL initial teacher education (ITE) and in-service education and training (INSET).

Recycling Behavior in a Multicultural Urban Area in Sweden

Alabastern, a multicultural rental housing area in the Växjö city of Sweden, was identified as poor at recycling household waste compared to other housing areas in the town. In this paper, a qualitative and quantitative analysis is conducted to understand the underlying causes of waste recycling behavior of the tenants. Results showed that majority of the studied participants perceived themselves to be environmentally friendly. They reported that they recycled household waste quite often, but it was the other tenants who did not sort their waste properly. The respondents identified the causes of the improper waste recycling as lack of attitude and awareness, limitation of communication, sense of insecurity, lack of means to transport bulky waste, limitation of the recycling room, and inadequate action by the housing company Växjöbostäder.

6D Posture Estimation of Road Vehicles from Color Images

Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.