Attitude Determination Research Articles

RFX-mod2 diagnostic capability enhancements for the exploration of multi-magnetic-configurations

Abstract The RFX-mod2 device, the upgraded version of the previous RFX-mod with a modified magnetic boundary, is presently under realization and will start to be operated in 2025. Significant upgrades of the diagnostic capabilities have been proposed and are under development. These include a largely increased number of in-vessel magnetic and electrostatic sensors, a new fast reciprocating manipulator for the exploration of the edge plasma in a wide range of experimental conditions, the improved Thomson scattering and soft X-ray diagnostics system for a detailed determination of the behavior of the electron temperature profile, new dedicated systems for the space and time resolved analysis of X-ray spectra and neutron rate, a reflectometric diagnostic for real-time determination of plasma position, two diagnostics devoted to the imaging of light impurities and influxes behavior along with arrays of halo current sensors. These diagnostic upgrades will be accompanied by a significant effort to improve the control of the electron density and of the impurity influxes by means of proper treatment of plasma facing components with in-vessel fixed electrodes distributed over the first wall. The described advancements will allow a deeper understanding of physics phenomena in the wide variety of magnetic configurations, including the tokamak, the reversed-field pinch and the Ultra-low q, which can be produced in RFX-mod2 thanks to its flexibility and unique MHD control capabilities.

Thermal design and experimental verification of the space ultraviolet wide field of view multi-channel scanning imager

In order to ensure the optimal imaging quality of the space ultraviolet wide field of view multi-channel scanning imager, it is imperative to conduct a comprehensive investigation into the thermal control system. First, we shall present the structure and performance index of the imager. The determination of the heat dissipation surface's position follows an analysis of the imager's exterior heat discharge. Subsequently, the thermal control design for every individual component of the imager is determined, considering the challenges associated with thermal management. The accuracy of the initial thermal design is verified by doing thermal simulation studies. Subsequently, the thermal equilibrium test was performed. The test results reveal that the temperature of the lens assembly varied between 20.0 °C and 25.6 °C, the horizontal bracket ranged from 19.7 °C to 21.7 °C, the vertical bracket exhibited temperatures between 11.2 °C and 15.4 °C, the U-frame experienced temperatures ranging from 15.1 °C to 17.4 °C, the motor showed temperatures between 6.6 °C and 26.3 °C, the detector recorded temperatures between 21.4 °C and 25.9 °C, and the high voltage module exhibited temperatures ranging from 8.9 °C to 19.9 °C. The temperature of each component is within the designated thermal control range. Extensive evidence has been presented to demonstrate the effectiveness and precision of thermal design.

Simultaneous measurements for fast neutron flux and tritium production rate using pulse shape discrimination and single crystal CVD diamond detector

This paper presents the development of a simultaneous measurement method for fast neutron energy spectra and tritium production rates within mixed radiation fields using a single crystal chemical vapour deposition diamond detector combined with a lithium fluoride (LiF) foil. The method involves the separation of pulses with rectangular shapes and the determination of the depth position within the single crystal diamond (SCD) struck by fast neutrons or nuclear reaction products including recoil tritons from the LiF foil based on pulse width, extracting pulse events occurred at the specific bulk region and the surface region of the SCD. Subsequently, unfolding techniques were employed to analyse the energy deposition spectrum of pulses at the specific bulk region which are induced only by fast neutrons, allowing the deduction of the fast neutron energy spectrum. To evaluate the tritium production rate, the energy deposition spectrum of pulses from events occurring at the SCD surface facing the LiF foil was analysed. By estimating the energy deposition spectrum solely induced by fast neutrons striking the SCD surface and subtracting it from the energy deposition spectrum of events at the SCD surface, the contribution of energetic ions, such as recoil tritons generated by the 6Li(n,α)3H reaction in the LiF foil, was determined. The fast neutron flux and tritium production rate obtained through this study were consistent with particle transport calculations, demonstrating the successful development of a method suitable for performance testing of fusion reactor blankets.

Determinants of Parental Attitudes towards Children’s Vaccination in Lithuania: An Online Survey

Background: Data from recent years show that the COVID-19 pandemic has significantly reduced the scope of child immunisation worldwide. If the numbers continue to fall, we may have a vaccination crisis. In order to understand the local factors of this phenomenon, we studied parents‘ viewpoint towards childhood vaccination in Lithuania. Therefore, the aim of our study was to determine the impact of parental attitudes on children’s vaccination.Materials and Methods: A web-based cross-sectional study was made in Lithuania from October 20th to November 3rd, 2020, using Google Forms. An anonymous questionnaire included both quantitative and qualitative questions. The questionnaire was distributed to the general population in Lithuania via social media and a snowball sampling. Only parents who have at least one child under 18 years old were involved in the study. We analysed the parents’ attitudes towards vaccination by their socioeconomic and demographic determinants using MS Excel and OpenEpi tools. The respondents were considered vaccine supporters if they vaccinated all their children with state-reimbursed vaccines or only vaccinated some of their children, and vaccine sceptics if they did not vaccinate their children with state-reimbursed vaccines.Results: The population of our research consisted of 775 parents. There were more males against vaccination than females, respectively, 59.6% and 33.2%. 65.0% of all respondents stated that they vaccinated their children with the full course of vaccines, while the remaining 35.0% did not vaccinate. University-level education dominated in both pro-vaccine and anti-vaccine groups. We found that 16.9% of parents who were unvaccinated as children themselves tend not to vaccinate their children. However, in the pro-vaxx group, only 0.7% of parents were unvaccinated during childhood. 50.8% of vaccine sceptics were not fully informed by healthcare professionals about the benefits and risks of vaccination, while only 31.6% of vaccine supporters were not informed. Social environment did not have an impact on the decision whether to vaccinate or not to vaccinate a child among both vaccine advocates and vaccine deniers (accordingly, 51.2% and 42.9%). 29.3% of respondents stated that the cost of paid vaccinations was too high. Open-text survey responses gave us more in-depth insight about the parental decision-making process. Protection of children and society from infectious diseases (31.7%) was mentioned as the main reason for vaccination. Whereas vaccine-hesitant parents were mostly concerned about already-occurring side effects or their risk (43.4%).Conclusions: Our findings confirmed that vaccine hesitancy was associated with not being vaccinated in childhood themselves, lack of information from medical practitioners and male gender. The price of vaccines also had an impact on immunisation rates – more than one-third of the vaccine supporting parents indicated that the cost of paid vaccinations was too high. The main incentive for vaccine compliance was parents’ desire to protect their children and society from infectious diseases. Whereas vaccine-hesitant parents were mostly concerned about already occurring side effects or their risk. There was no consensus, whether vaccination of children should be mandatory in Lithuania, as the answers to the question were almost evenly distributed. The formation of parents‘ attitudes towards children‘s vaccination is a complex process that is determined by parents‘ attitudes towards the health care system, lack of trust in doctors, and gaps in communication about the benefits and risks of vaccination. All of this information should be taken into account in health policy-making.

Joint Determination of Nurse and Patient Bed Positions in an Inpatient Unit Considering Equity in Visibility

Layout design is considered a crucial aspect of healthcare architecture, and its goal is to allow easy access to essential hospital services and effective patient care. Literature suggests that modifying or redesigning the inpatient unit layout is one of the ways to maximize patient visibility in an inpatient layout. However, prior work has been descriptive in nature and limited in their ability to derive optimal layouts. To fill this gap, we propose a non-linear optimization model that optimizes both equity and effectiveness in visibility by jointly determining the optimal location of two nurses and patient bed positions in multiple rooms. The bi-objective model is then converted into a single objective model utilizing the ε-constrained method, with equity in the objective function and effectiveness as a constraint. Patient visibility is estimated using a ray-casting algorithm that also considers nurses’ line of sight, door positions, and obstruction levels. A progressive refinement algorithm embedded in the Particle Swarm Optimization framework is proposed to efficiently solve this model. Our results suggest that optimizing bed position in conjunction with nurse position can enhance equity by over 45.2% compared to just optimizing the nurse position. Similarly, angular layouts proved superior to linear layout by up to 53% in patient equity. We also notice that increasing spatial distance between nurses in angular layouts can further increase equity. Our approach provides valuable insights and can serve as a benchmark tool for hospitals looking to improve the design of their inpatient units that promote patient safety and high-quality care.

An enhanced direct position determination of non-circular sources via sparse Bayesian inference and grid refinement strategy

In this study, an off-grid sparse Bayesian inference (OGSBI) based direct position determination (DPD) algorithm is investigated. Existing SBI-based DPD algorithms are confronted with the challenge of excessive computational loads and lack of consideration for non-circular (NC) signals. To address these limitations, we present an enhanced OGSBI-based DPD algorithm for multiple non-circular sources. By utilizing the conjugate information of the NC signals, we expand the dimensionality of the data matrix to achieve a significant improvement in the localization performance. Additionally, a grid refinement strategy is developed to alleviate the computational loads, which involves an initial search to determine the approximate source locations, followed by fine localization using a denser grid. Moreover, the computational complexity and Cramér-Rao lower bound are derived to provide a comprehensive analysis of the proposed algorithm. Numerical simulations demonstrate the superiority of the proposed algorithm in terms of both localization accuracy and computational efficiency.

Perilaku Toxic Masculinity di Kalangan Pelajar SMK

Toxic masculinity behavior has become one of the examples of emerging reality in society. It talks about how a teenager male is bound to a long-formed social construction against the determination of attitudes and behaviors that men should be carrying out. Like a man should be strong, not crying, and so on. This study aims to identify toxic masculinity behavior that occurs among SMK students. The method used is qualitative research with a case study approach that is reviewed from Berger and Luckmann's theory of social reality construction and supported by Raewyn Connell's hegemonic masculinity theory. Subjects in this study were students of SMK Bina Karya 1 Karawang who consisted of five informants (three perpetrators and two victims) and selected on the basis of certain criteria. The data collection techniques used are observations, interviews and documentation.The results show that toxic masculinity in reality is based on three stages: externalization, objectification and internalization. At the externalization stage, the role of the family as well as the infancy of the informant becomes an important stage in the formation of their character as a man. Then at the objectivization stage, individuals begin to interact and see the reality that exists in their social environment through the meaning created for men. Lastly, the stage of internalization in which individuals embody existing subjectivity and become part of the members of society as a male.

Determinants of Knowledge, Attitudes, and Practices among Young Adults Type 2 Diabetes Patients in Selected Tertiary Hospitals in Shandong Province, China

Objective: The purpose of this study is to understand the current situation of knowledge, attitude, and practice of self-management in young patients with type 2 diabetes mellitus (T2DM) and to explore the relationship between general conditions (personal, social, and environment, clinical factors) and their knowledge, attitude, and practices (KAP) of diabetes self-management, This aims to provide patients with high-quality nursing care management and services, as well as to provide relevant recommendations for effective self-management. Methods: This study is a descriptive correlational study that used the purposive sampling method to investigate 359 patients with T2DM aged 18–25 years in four designated tertiary hospitals in Shandong Province. Results: Knowledge of self-management was correlated with sex, age, education level, occupation and work situation, monthly household income, medical payment method, family and friend support, frequency of diabetes health education, and diabetes complications. The attitude subscale was correlated with sex, age, education level, work situation, and family and friend support. The practice subscale was associated with age, education level, work situation, family and friend support, frequency of diabetes health education, and HbA1c values. Conclusion: Young adults aged 18–25 with T2DM have positive attitudes towards diabetes self-management, but there are still deficiencies in knowledge acquisition and behavioral practice. The KAP of self-management of diabetes is influenced by personal factors such as sex, age, and education level, and socio-environmental factors such as family income and family or friends’ social support. Additionally, clinical factors such as complications and HbA1c values significantly impacted the patient’s disease self-management ability.

Attitude to Co-Administration of Influenza and COVID-19 Vaccines among Pregnant Women Exploring the Health Action Process Approach Model

Respiratory tract diseases caused by influenza virus and SARS-CoV-2 can represent a serious threat to the health of pregnant women. Immunological remodulation for fetus tolerance and physiological changes in the gestational chamber expose both mother and child to fearful complications and a high risk of hospitalization. Vaccines to protect pregnant women from influenza and COVID-19 are strongly recommended and vaccine co-administration could be advantageous to increase coverage of both vaccines. The attitude to accept both vaccines is affected by several factors: social, cultural, and cognitive-behavioral. In Palermo, Italy, during the 2021–2022 influenza season, a cross-sectional study was conducted to evaluate pregnant women’s intention to adhere to co-administration of influenza and COVID-19 vaccines. The determinants of vaccination attitude were investigated through the administration of a questionnaire and the Health Action Process Approach theory was adopted to explore the cognitive behavioral aspects. Overall, 120 pregnant women were enrolled; mean age 32 years, 98.2% (n = 118) of Italian nationality and 25.2% (n = 30) with obstetric or pathological conditions of pregnancy at risk. Factors significantly associated with the attitude to co-administration of influenza and COVID-19 vaccines among pregnant women were: high level of education (OR = 13.96; p < 0.001), positive outcome expectations (OR = 2.84; p < 0.001), and self-efficacy (OR = 3.1; p < 0.001). Effective strategies to promote the co-administration of the influenza vaccine and the COVID-19 vaccine should be based on the communication of the benefits and positive outcomes of vaccine co-administration and on the adequate information of pregnant women.

Refractive index measurement using virtual—apparent image coincidence approach

Abstract In this study, we explore novel approaches to determining the index of refraction for various mediums by leveraging virtual images. We introduce a simplified yet effective method that utilizes apparent object positions resulting from light bending in a medium. Our focus lies in measuring the refractive index of liquids without the need for a microscope, emphasizing the measurement of real and apparent depths through the coincidence of virtual and apparent images. Comparative analysis with established techniques reveals the precision of our results, with accurate determinations of object and image positions. Through the collection and graphing of paired data, we calculate the refractive indices of water, vegetable oil, and ethanol. Our findings underscore the significance of this scientific methodology, offering time-efficient, implementable, and easily comprehensible procedures. We posit that this study holds promise for educational applications at various levels. Moreover, we propose extending our methodology to transparent solid materials, thereby broadening its potential applications.

Planar Tetranuclear Uranium Hydride Cluster Supported by ansa‐Bis(cyclopentadienyl) Ligands

Polynuclear metal hydride clusters play important roles in various catalytic processes, with most of the reported polynuclear metal hydride clusters adopting a polyhedral three‐dimensional structure. Herein, we report the first example of a planar tetranuclear uranium hydride cluster [(CpCMe2CMe2Cp)U]4(μ2‐H)4(μ3‐H)4 (U4H8). It was synthesized by reacting an ansa‐bis(cyclopentadienyl) ligand‐supported uranium chloride precursor [(CpCMe2CMe2Cp)U]3(μ2‐Cl)3(μ3‐Cl)2 with NaHBEt3. The presence of hydrides in U4H8 was confirmed by NMR spectroscopy and its reactivity with phenol and carbon tetrachloride. DFT calculations also facilitated the determination of the hydrides' positions in U4H8, featuring four bridging μ2‐H ligands and four face‐capping μ3‐H ligands, with the four U centers arranged in a rhombic geometry. The U4H8 represents not only the first example of planar polynuclear actinide metal hydride cluster but also the uranium hydride cluster with the highest nuclearity reported to date.

Planar Tetranuclear Uranium Hydride Cluster Supported by ansa-Bis(cyclopentadienyl) Ligands.

Polynuclear metal hydride clusters play important roles in various catalytic processes, with most of the reported polynuclear metal hydride clusters adopting a polyhedral three-dimensional structure. Herein, we report the first example of a planar tetranuclear uranium hydride cluster [(CpCMe2CMe2Cp)U]4(μ2-H)4(μ3-H)4 (U4H8). It was synthesized by reacting an ansa-bis(cyclopentadienyl) ligand-supported uranium chloride precursor [(CpCMe2CMe2Cp)U]3(μ2-Cl)3(μ3-Cl)2 with NaHBEt3. The presence of hydrides in U4H8 was confirmed by NMR spectroscopy and its reactivity with phenol and carbon tetrachloride. DFT calculations also facilitated the determination of the hydrides' positions in U4H8, featuring four bridging μ2-H ligands and four face-capping μ3-H ligands, with the four U centers arranged in a rhombic geometry. The U4H8 represents not only the first example of planar polynuclear actinide metal hydride cluster but also the uranium hydride cluster with the highest nuclearity reported to date.

Deep learning-based spatiotemporal multi-event reconstruction for delay line detectors

Accurate observation of two or more particles within a very narrow time window has always been a challenge in modern physics. It creates the possibility of correlation experiments, such as the ground-breaking Hanbury Brown–Twiss experiment, leading to new physical insights. For low-energy electrons, one possibility is to use a Microchannel plate with subsequent delay lines for the readout of the incident particle hits, a setup called a Delay Line Detector. The spatial and temporal coordinates of more than one particle can be fully reconstructed outside a region called the dead radius. For interesting events, where two electrons are close in space and time, the determination of the individual positions of the electrons requires elaborate peak finding algorithms. While classical methods work well with single particle hits, they fail to identify and reconstruct events caused by multiple nearby particles. To address this challenge, we present a new spatiotemporal machine learning model to identify and reconstruct the position and time of such multi-hit particle signals. This model achieves a much better resolution for nearby particle hits compared to the classical approach, removing some of the artifacts and reducing the dead radius a factor of eight. We show that machine learning models can be effective in improving the spatiotemporal performance of delay line detectors.

First implementation of an innovative infra‐red camera system integrated into a mobile CBCT scanner for applicator tracking in brachytherapy—Initial performance characterization

AbstractPurposeTo enable a real‐time applicator guidance for brachytherapy, we used for the first time infra‐red tracking cameras (OptiTrack, USA) integrated into a mobile cone‐beam computed tomography (CBCT) scanner (medPhoton, Austria). We provide the first description of this prototype and its performance evaluation.MethodsWe performed assessments of camera calibration and camera‐CBCT registration using a geometric calibration phantom. For this purpose, we first evaluated the effects of intrinsic parameters such as camera temperature or gantry rotations on the tracked marker positions. Afterward, calibrations with various settings (sample number, field of view coverage, calibration directions, calibration distances, and lighting conditions) were performed to identify the requirements for achieving maximum tracking accuracy based on an in‐house phantom. The corresponding effects on camera‐CBCT registration were determined as well by comparing tracked marker positions to the positions determined via CBCT. Long‐term stability was assessed by comparing tracking and a ground‐truth on a weekly basis for 6 weeks.ResultsRobust tracking with positional drifts of 0.02 ± 0.01 mm was feasible using the system after a warm‐up period of 90 min. However, gantry rotations affected the tracking and led to inaccuracies of up to 0.70 mm. We identified that 4000 samples and full coverage were required to ensure a robust determination of marker positions and camera‐CBCT registration with geometric deviations of 0.18 ± 0.03 mm and 0.42 ± 0.07 mm, respectively. Long‐term stability showed deviations of more than two standard deviations from the initial calibration after 3 weeks.ConclusionWe implemented for the first time a standalone combined camera‐CBCT system for tracking in brachytherapy. The system showed high potential for establishing corresponding workflows.

Employees’ Motivation as A Determinant of Work Attitude and Performance in Elizade University

Employees’ motivation as a determinant of work attitude and performance of employees of Elizade University, Ilara-Mokin, Ondo State, Nigeria was examined in this study. Regardless of rank, age, job, gender, or educational background, employers have defined employee motivation as instruments and strategies used to affect the work attitude and performance of employees at various levels of the organisation. Purposive sampling technique was adopted in selecting Elizade University, Ilara-Mokin in Ondo state out of the 111 private universities in Nigeria. Self-structured questionnaire named Employees Motivation, Work Attitude and Performance (EMWAAPQ) was used for primary data collection. The collected data underwent analysis, focusing on the descriptive examination of demographic information. To test the two hypotheses formulated for this study, Pearson correlation and linear regression analyses were conducted. The scrutiny of all hypotheses adhered to a significance level of 0.05 alpha. The study revealed a positive correlation between employees’ motivation and employee attitudes within the institution (r=0.205**, n=181, p<0.05). Furthermore, this study established that both intrinsic and extrinsic motivation significantly influence employee performance (R2=0.136=13.6% of the variance). The implication is that organizations should prioritize employee well-being, with a particular emphasis on fostering motivation among staff. Therefore, to sustain and enhance productivity, the study recommends the implementation of comprehensive compensation packages, encompassing both monetary and non-monetary benefits.

Innovative Exploration of a Bio-Inspired Sensor Fusion Algorithm: Enhancing Micro Satellite Functionality through Touretsky's Decentralized Neural Networks

Insect-inspired sensor fusion algorithms have presented a promising avenue in the development of robust and efficient systems, owing to the insects' ability to process numerous streams of noisy sensory data. The ring attractor neural network architecture has been identified as a noteworthy model for the optimal integration of diverse insect sensors. Expanding on this, our research presents an innovative bio-inspired ring attractor neural network architecture designed to augment the performance of microsatellite attitude determination systems through the fusion of data from multiple gyroscopic sensors.Extensive simulations using a nonlinear model of the microsatellite, while incorporating specific navigational disturbances, have been conducted to ascertain the viability and effectiveness of this approach. The results obtained have been superior to those of alternative methodologies, thus highlighting the potential of our proposed bio-inspired fusion technique. The findings indicate that this approach could significantly improve the accuracy and robustness of microsatellite systems across a wide range of applications.

Motivation for COVID-19 Vaccination: Applying a Self-Determination Theory Perspective to a Global Health Crisis

Examining the spectrum of vaccine attitudes within the general public, spanning from hesitancy to confidence, is pivotal in addressing the challenges posed by the COVID-19 pandemic. Despite widespread campaigns advocating for vaccine uptake, a proportion of the population harbour reservations about the safety and efficacy of vaccines. This study seeks to explore the determinants of vaccine attitudes in Canada, leveraging key concepts from the well-established Self-Determination Theory (SDT), including basic psychological needs and the quality of an individual’s motivation. During a crucial juncture in the COVID-19 pandemic (December 2021), 292 participants were recruited and completed an online survey assessing levels of satisfaction/frustration of basic psychological needs (sense of autonomy, relatedness, and competence), vaccine attitudes (confidence and hesitancy), and motivation towards vaccination (controlled and autonomous). Two mediation models were employed to examine whether autonomous-controlled motivation mediated the relationship between need satisfaction-frustration and vaccine attitudes. Model 1 revealed a full mediating effect, indicating that need satisfaction influenced vaccine confidence only through autonomous motivation (ab1 = 0.09, SE = 0.04, z = 2.19, 95 % CI [0.01, 0.18]). Meanwhile, Model 2 demonstrated that need frustration was associated with vaccine hesitancy partially through controlled motivation (ab2 = 0.05, SE = 0.02, z = 2.54, 95 % CI [0.02, 0.10]). These findings underscore the applicability of SDT in investigating the motivational mechanisms that shape vaccine attitudes. Recognizing psychosocial factors, including the balance of basic needs and quality of motivations, may be integral to informing effective public health strategies.

Cramér-Rao Lower Bound for Magnetic Field Localization around Elementary Structures.

The determination of a mobile terminal's position with high accuracy and ubiquitous coverage is still challenging. Global satellite navigation systems (GNSSs) provide sufficient accuracy in areas with a clear view to the sky. For GNSS-denied environments like indoors, complementary positioning technologies are required. A promising approach is to use the Earth's magnetic field for positioning. In open areas, the Earth's magnetic field is almost homogeneous, which makes it possible to determine the orientation of a mobile device using a compass. In more complex environments like indoors, ferromagnetic materials cause distortions of the Earth's magnetic field. A compass usually fails in such areas. However, these magnetic distortions are location dependent and therefore can be used for positioning. In this paper, we investigate the influence of elementary structures, in particular a sphere and a cylinder, on the achievable accuracy of magnetic positioning methods. In a first step, we analytically calculate the magnetic field around a sphere and a cylinder in an outer homogeneous magnetic field. Assuming a noisy magnetic field sensor, we investigate the achievable positioning accuracy when observing these resulting fields. For our analysis, we calculate the Cramér-Rao lower bound, which is a fundamental lower bound on the variance of an unbiased estimator. The results of our investigations show the dependency of the positioning error variance on the magnetic sensor properties, in particular the sensor noise variance and the material properties, i.e., the relative permeability of the sphere with respect to the cylinder and the location of the sensor relative to the sphere with respect to the cylinder. The insights provided in this work make it possible to evaluate experimental results from a theoretical perspective.

Vehicle Position Detection Based on Machine Learning Algorithms in Dynamic Wireless Charging.

Dynamic wireless charging (DWC) has emerged as a viable approach to mitigate range anxiety by ensuring continuous and uninterrupted charging for electric vehicles in motion. DWC systems rely on the length of the transmitter, which can be categorized into long-track transmitters and segmented coil arrays. The segmented coil array, favored for its heightened efficiency and reduced electromagnetic interference, stands out as the preferred option. However, in such DWC systems, the need arises to detect the vehicle's position, specifically to activate the transmitter coils aligned with the receiver pad and de-energize uncoupled transmitter coils. This paper introduces various machine learning algorithms for precise vehicle position determination, accommodating diverse ground clearances of electric vehicles and various speeds. Through testing eight different machine learning algorithms and comparing the results, the random forest algorithm emerged as superior, displaying the lowest error in predicting the actual position.

A molecular mechanics implementation of the cyclic cluster model

Abstract The implementation of the cyclic cluster model (CCM) for molecular mechanics is presented in the framework of the computational chemistry program deMon2k. Because the CCM is particularly well-suited for the description of periodic systems with defects, it can be used for periodic QM/MM approaches where the non-periodic QM part is treated as a defect in a periodic MM surrounding. To this end, we present here the explicit formulae for the evaluation of the Ewald sum and its first- and second-order derivatives as implemented in deMon2k. The outlined implementation was tested in molecular dynamics (MD) simulations and periodic structure optimization calculations. MD simulations of an argon system were carried out using the Nosé-Hoover chain (NHC) thermostat and the Martyna-Tobias-Klein (MTK) barostat to control the temperature and pressure of the system, respectively. For the validation of CCM structure optimization a set of molecular crystals were optimized using the Ewald method for the evaluation of the electrostatic interactions. Two optimization procedures for the determination of the atomic positions and CCM cell parameters were tested. Our results show that the simultaneous optimization of the atomic positions and cell parameters is most efficient.