Miracle-dz/UniFAR-FTUs huggingface dataset:
Density functional studies of molecular magnets

After a general introduction into the field of molecular magnets the discussion focuses on a more specific description of their most important representative species, single‐molecule magnets incorporating transition metal ions. We overview traditional model approaches for the phenomenological description of such systems and outline some ways used to parameterize the corresponding models from experiment and from first‐principle calculations. The latter can be either multi‐determinantal quantum chemical schemes or those based on the density functional theory. In particular we discuss Heisenberg exchange parameters and magnetic anisotropy constants. As a practical example, an introduction into problems and properties of some single‐molecule magnets which gained much attention within last years, namely Mn12‐acetate, “Fe8” and “V15” systems, is given. This introduction into systems is followed by a critical comparison of calculation schemes based on the density functional theory that are particularly well suited for the study of molecular magnets. For the above systems we select some benchmark results, obtained by different methods. Finally, we outline our recent progress in the study of other single‐molecule magnets, including six‐membered “ferric wheels”, “ferric stars” and “Ni4” molecules, which we studied with the use of first‐principles methods Siesta and NRLMOL. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Recognizing and Predicting Neonatal Pain in Preterm Intensive Care Unit: a Study Protocol

A robust body of research reports that pain is an important determinant of neurodevelopmental outcome in sick preterm and term infants. The newborn patient is uniquely exposed to pain due to underdeveloped nociceptive modulation, high prevalence of painful procedures, and lack of effective methods to assess and predict pain intensity and duration. More than forty neonatal pain scales have been developed, which testifies to both the magnitude of the problem and the complexity of the task. Trained neural network models have been shown to effectively discriminate facial expressions and human body language. We propose the approach of combining the classification of facial and body images by neural networks with professional evaluation and objective data, e.g. patient data, pathology, and vital parameters. Such an approach would offer critical advantages over scaling tools, as images could be acquired sequentially, allowing continuous rather than intermittent monitoring, even in absence of a human supervisor, and enabling quantification of neonatal pain in the domains of time and intensity.
Microwave‐Assisted Fabrication of Superamphiphobic Surfaces on Aluminum Substrates

The field of superamphiphobic surface fabrication has evolved rapidly in the last decade; however, research on important issues such as sustainability and green chemistry procedures is still scarce. Herein, a simple method of microwave irradiation (MW) to minimize energy consumption during the preparation of superamphiphobic aluminum (Al) surfaces is reported. Al substrates are first etched in diluted HCl solutions to generate a microstructure and then irradiated in a commercial microwave unit for several time intervals, temperatures, and pressures. The surfaces are then coated with different compounds, and the wettability is tested with high and very‐low surface tension liquids. Optical profilometry and scanning electron microscopy images show that the density of hierarchical micro‐nanostructures increases with MW time, temperature, and pressure. At 170 °C and 7.9 bar, the surfaces present a high density of structures and re‐entrant topographies. The obtained coatings display excellent repellence to liquids with surface tensions as low as 27.5 mN m−1. X‐ray photoelectron spectroscopy data show the importance of efficient surface functionalization for the production of superamphiphobicity in Al substrates. The results show that MW irradiation of Al substrates can be a green and efficient method for fabricating superamphiphobic surfaces.
Qualitative Investigation into the Perception towards Compassionate Parenting among Parents of Autistic Children: Cross-Cultural Comparison between the UK and The Netherlands

Parenting a child with autism spectrum disorder is believed to present challenges that lead to increased levels of stress, as well as a reduction in the quality of the relationship between parent and child. This study aims to investigate parental perceptions toward a compassionate parenting style of parenting to better understand how this style may influence relationships and quality of life in parents. Parents from the United Kingdom (six parents) and the Netherlands (five parents) were invited take part in semi-structured interviews, whereby the data collected were subsequently analysed using thematic analysis. Data from both British and Dutch groups were overall similar to each other. Four themes were identified from the aggregated data: (a) “Parents believe compassionate parenting is important” (parents believed that compassion is an essential element of their parenting style and improves situational outcomes); (b) “Compassionate parenting de-escalates stressful situations” (compassionate parenting reduces stress and improves the quality of life); (c) “High pressure situations as a threat to practice compassion” (challenges and limitations to compassionate parenting style); and (d) “Greater public and professional awareness of autistic behaviours” (the general public and professional services often lack awareness to recognise autistic behaviour traits). Results are consistent with research examining the perceptions of parents of neurotypical children, in that a more compassionate approach to parenting is valued, as it is believed to create a greater connection with the child. Our findings inform researchers and educators as to what parents of children with ASD find useful, important, and worthwhile. Future research needs to investigate how compassionate parenting impacts autistic children’s quality of life.
Innovative Decentralized Configuration Design of Chipless RFID Tag: Toward a Cost-Effective and Efficient Code Density

In this article, a compact chipless RFID tag with a small size and high data density is proposed. The tag consists of nested octagonal loops arranged in a concentric configuration. Each two neighboring resonating elements are decentrally coupled by two connector lines at obverse sides. The small size of the tag is achieved through embedding multiple octagonal elements in a nested arrangement, which share the same side, and through connecting the neighboring elements. The tag configuration is designed and optimized to improve the resonating modes with respect to the number of resonating elements. The number of generated resonating modes (N) is mathematically obtained by N=2n-1, such (n) is the resonating elements number. An 11-bits data capacity is presented in the proposed tag within a physical dimension of <inline-formula> <tex-math notation="LaTeX">$10\times10$ </tex-math></inline-formula> mm2, resulting high data density of 11 b/cm2. The proposed tag is realized on Rogers RT/Duroid 5880 substrate having substrate height h=0.508 mm, relative permittivity <inline-formula> <tex-math notation="LaTeX">$\epsilon _{r}=$ </tex-math></inline-formula> 2.2, and loss tangent <inline-formula> <tex-math notation="LaTeX">$\delta = 0.0009$ </tex-math></inline-formula>. The proposed tag is designed and simulated using CST Studio Suite ®. The tag’s performance is initially evaluated through simulation and analyzed for effectiveness. The tag is then fabricated and measured, and the results are compared to ensure agreement between simulation and measurement. The tag advantages are compact size, high data density, and improved resonating modes. The operating frequency range of the proposed tag is 7.5 GHz-15 GHz.
Optimizing LQG Controller for a Single-Phase Power Inverter in an AC Microgrid System

This article presents an optimization-based Linear Quadratic Gaussian (LQG) control application for controlling a single-phase power inverter in an ac micro-grid system. Several optimization techniques (e.g., genetic algorithm, particle swarm optimization, grey wolf optimization, pattern search optimization, and whale optimization) have been applied with two different objective functions (i.e., ITAE and RMSE) to prove the effectiveness of different optimizers for enhancing control performance. A comparative analysis between the different optimizers has been presented based on their optimization performance and controller performances. From the comparison presented grey wolf optimization outperforms the other studied optimizers with only 2.89% & 2.04% overshoots and 0.07 & 0.30% steady-state error with ITAE and RMSE objective functions respectively. The simulations and optimizations are conducted in MATLAB/ Simulink environment.
Toward a New Multirotor Design With Spatial Configuration and Tilted Rotors

In recent years, aerial interaction tasks increasingly use UAVs, and because of their intrinsic under-actuation, they are consequently limited in their motion. Therefor, there are three classes of systems to overcome the under-actuation problem such as, the non-flat multirotors, drone with tilted rotors and reconfigurable systems. This paper proposes generic modeling of a multirotor with a non-flat configuration. This model is derived by considering all physical and mechanical constraints. As a result, the body-fixed frame can be placed at any point in the vehicle and the rotors instead with varying tilt angles and arm lengths in any position in space. These specifications give a nonsymmetrical and spatial configuration to the multirotor with fully row rank control allocation matrix. A numerical simulation result was provided to show the effectiveness of our model.
Post-Acute SARS-CoV-2 Symptoms are Fewer, Less Intense Over Time in People Treated with Mono-Clonal Antibodies for Acute Infection

Introduction Many with post-acute SARS-CoV-2 (PASC) have persistent symptoms impacting physical and cognitive function, decreased health and health-related life quality. Monoclonal antibody (mAb) treatment was available to acutely infected patients which might improve these outcomes. Purpose To compare patient perception of PASC symptoms for those receiving bamlanivimab or casirivimab and imdevimab (mAbs) to those not receiving this treatment (non-mAbs). To compare changes between these groups in symptoms, function and quality of life over a 6-month follow-up. Patients and Methods Consented adults >28 days post-infection with positive SARS-CoV-2 qPCR or antigen test and SARS-CoV-2 infection between March of 2020 and July of 2022 were enrolled. This prospective, repeated measure observational study reports baseline through 6-month follow-up. Extensive sociodemographic data, detailed medical history, COVID-19 symptom history, and standardized measures of well-being, depression, anxiety, stigma, cognition, symptom assessment, distress, and health status were collected. Results 323 participants [101 mAb, 221 non-mAb, 52.7±15.5 years, 47.7% male, body mass index (BMI) 31.4±8.4] were analyzed. Fewer symptoms at baseline were reported in mAb versus non-mAb participants (1.06±1.31 vs 1.78±2.15, respectively p=0.0177) 6 months: (0.911±1.276 mAb vs.1.75±2.22 non-mAb, p=0.0427). Both groups showed significant within-group decreases in symptom number (52 to 21 mAb, 126 to 63 non-mAb) and symptom burden (p=0.0088 mAb, p<0.00001 non-mAb). mAb patients had significantly shorter infection-to-baseline interval (days) (120.4±55.3 mAb vs 194.0±89.3 non-mAb, p<0.00001); less frequent history of myocardial infarction (0.0 vs 3.9%, p=0.0464); headache (2.0% vs.11.8%, p=0.0046), rash (3.1% vs 9.9%, p=0.0377), and miscellaneous muscle complaints (2.0% vs 12.3%, p=0.0035), plus significantly better 6-month mood. (2.2% vs 13.2%, p=0.0390). Conclusion mAb treated participants had reduced symptom burden and consistently reported fewer symptoms than non-mAb at all time points despite less time since acute illness. Both groups reported a statistically significant decrease in symptoms by 6-month visit with no statistically significant differences between them at follow-up.
Effect of Home-Based Cardiac Rehabilitation Program on Self-Efficacy of Patients With Implantable Cardioverter Defibrillator

Introduction For more effective control and treatment of cardiac dysrhythmias caused by diseases, ischemia, or other causes, an implantable cardioverter defibrillator (ICD) is used. One of the effective ways for secondary prevention is the home-based cardiac rehabilitation (HBCR) which nurses have an effective role in its implementation. Objective The study aimed to investigate the effect of implementing HBCR programs on the self-efficacy of patients with ICD. Methods This is a semi-experimental study conducted on 70 patients who received ICD in Shahid Chamran Heart Center of Isfahan University of Medical Sciences (IUMS) in 2021. The patients were randomly assigned to intervention and control groups and were introduced to the practical concepts of HBCR during four training sessions. In the following, 3-month follow-up and trainings were continued by home visits, telephone follow-up, and use of social messaging networks due to the conditions of coronavirus disease 2019 (COVID-19) pandemic. The data were analyzed with SPSS/21. Results The findings showed that performing HBCR programs was effective in improving the self-efficacy of patients with ICDs. A significant trend in the implementation of the HBCR programs in two groups was shown using chi-square test and independent t-test and variance with repeated measurements (p < .001). There was no significant difference in self-efficacy score in both groups at the beginning of the study (p < .056). Conclusion Considering the effectiveness of HBCR programs on improving the self-efficacy of patients with ICDs, it can be used in the educational care programs of healthcare workers and in the strategic policies of health care services.
Approach for Solving Nonlinear Equation Group Based on Genetic Algorithm

For the existing problems of much computing and slow speed in solving nonlinear equation group by Newton iteration method and its transfigurations, a general genetic algorithm of seeking approximate solutions of nonlinear equation group is proposed. Having mainly adopted the idea of solving the minimum value of objective function and combined with the parallel search merit of genetic algorithm, the algorithm obtains fast convergence rate and high precision by selecting and setting appropriate parameters such as parent selection strategy, crossover operator, mutation operator, etc. The experimental results show that the method obviously is superior to conventional methods, and it has characteristics of rapid computation, high precision and well universality.
A Study of a Generalized Photovoltaic System with MPPT Using Perturb and Observer Algorithms under Varying Conditions

In recent years, renewable energy (RE) has shown promise as a sustainable solution to the rising energy demand worldwide. Photovoltaic (PV) technology has emerged as a highly viable RE alternative. The majority of PV schemes use specific PV models with specified parameters. This study proposes a PV model with generic specifications, a PV array, a DC/DC converter, a DC/AC inverter, maximum power point tracking (MPPT), and grid synchronization using a feedback control system under the MATLAB/Simulink environment. Various MPPT techniques have been adapted to track the PV’s maximum power point (MPP); however, there are various uncertainties. To address these challenges, this paper presented a perturb and observe (P&O) strategy to track the MPP of PV systems reliably. The MPP of a PV system varies according to meteorological order, such as solar radiation and cell temperature. The MPPT primarily gathers the maximum current and voltage of the PV array and provides them to the load using a boost converter. The MPPT performance and PV array attributes are analyzed during abrupt weather changes. Finally, a feedback controller is configured to perform synchronization of the inverter with the grid. The validity and reliability of the PV module using P&O methods provide a higher efficacy of MPPT under MATLAB/simulation. Finally, the presented results endorse the strength of the proposed technique.
Incidental Finding of Intrarenal Foreign Guidewire During Percutaneous Nephrolithotomy: A Case Report and Literature Review

Patient: Male, 54-year-old Final Diagnosis: Foreign body in the abdominal cavity Symptoms: Flank pain Clinical Procedure: — Specialty: Urology Objective: Challenging differential diagnosis Background: Percutaneous nephrolithotomy (PCNL) is indicated for large renal calculi (³2 cm) and is often the treatment of choice due to its high success rate. Guidewire fragmentation is a rare procedural accident that can occur in PCNL but may be missed. Retention of the fragment within the upper urinary tract can lead to further complications, such as recurrent nephrolithiasis or impairment of renal function. Case Report: We present the case of a 54-year-old man who experienced right flank pain for 5 days. His history was significant for recurrent nephrolithiasis, managed by PCNL in other hospitals. The most recent procedure was conducted 4 years ago, and his perioperative course was uneventful. Preoperative computed tomography revealed right renal calculi and a C-shaped foreign body. He was scheduled for an elective PCNL. The foreign body was intraoperatively identified as a guidewire fragment and removed. Conclusions: Currently, there is no standard management for intrarenal foreign bodies. Suspicion should be raised in young patients with recurrent stones within a short period of time. A thorough history on past urological interventions should be obtained. Symptoms can also have an insidious onset that could mimic nephrolithiasis or uri-nary tract infections. Extraction can be done via a standard minimally invasive approach. It is also the surgeon’s responsibility to check the integrity of intraoperative instruments so as to minimize risks of complication and reassure the patient.
ECG Data Visualization: Combining the power of Grafana and InfluxDB

One of the principal advantages of smart health systems is to provide a faster and more efficient diagnosis. In this context, data visualization is an effective way to represent data and help physicians to interpret a diagnostic test result. This paper focuses on how to better visualize health data under timevarying which is sorely needed in the analysis of sensitive data, such as electrocardiograph (ECG) signals. We propose an interactive data visualization method under data manipulation. The prototype was created using the InfluxDB database management system and the Grafana tool to store and visualize ECG signals, respectively. We also provide an empirical comparison of the proposed approach to the base methods of data visualization and draw useful conclusions upon their performance.
Numerical modelling of unsaturated MX-80 bentonite subjected to two different hydration paths and subsequent loading to high-pressures

MX-80 bentonite has been considered as a suitable material for the construction of engineered barriers employed in deep geological radioactive waste repositories. These barriers are generally formed of compacted unsaturated bentonite, the latter experiencing a slow saturation due to its low permeability whileinteracting with the surrounding groundwater. In order to verify the long-term safety requirements of engineered barriers, their response to hydration has to be carefully assessed. As part of the recent European project BEACON (Bentonite Mechanical Evolution), the behaviour of MX-80 bentonite subjected to different hydration paths was investigated in a number of laboratory and field experiments and numerical studies. This paper is concerned with numerical simulations of two laboratory experiments performed during the project, with the objective of examining the predictive capabilities of the proposed numerical modelling approach. The experiments were selected due to the granular state of bentonite at its placement in the testingapparatus, which differed from the large number of previous experiments conducted on specimens of compacted bentonite blocks. The paper provides a brief introduction to the adopted modelling framework, a summary of calibrated parameters for the hydro-mechanical constitutive modelling and the results of numerical simulations, concluding that a satisfactory numerical simulation of the experiments was achieved.
INTERRELATIONSHIPS BETWEEN MILK CONSTITUENTS, PROTEIN PROFILE, GENOTYPES OF KAPPA-CASEIN GENE AND ETHANOL STABILITY OF COW'S MILK

This study aimed to withstand some factors that may be associated with and affected the alcohol instability of milk. Both individual milk and EDTA whole blood were collected from 162 cows among 4 Holstein dairy farms that suffered from their milk rejection because of milk ethanol instability. Milk samples were subjected to the measurement of milk components, pH, somatic cell count, and total bacterial count. Thirty milk samples were subjected to the detection of AFM1. Three mixed rations from each farm were subjected to the detection of AFB1. Blood samples were subjected to genotyping of the kappa-casein gene. About 72.2% and 27.8% of samples were recorded as ethanol-stable and unstable milk. A significant reduction was observed in the protein, fat, TS, and pH of ethanol unstable versus stable milk while a significant increase in salts, SCC, and TBC was observed. A significant difference was observed in AFM1 in stable versus unstable milk. The concentration of AFB1 ranged from 18.58 ppb up to 34.58 ppb. A significant difference in protein fractions was observed. Genotyping of the kappa - casein revealed that 51, 87, and 24 cows were AA, AB, and BB genotypes. Significantly higher fat and TS percentages and a significantly lower TBC in animals with BB genotypes (p≤0.05) versus those of both AA and AB genotypes were detected. In conclusion, continuous monitoring of different milk composition parameters, udder health represented by TBC and SCC and aflatoxin load in animal feed can be the first steps toward the production of ethanol-stable milk.
Impact of combination methods on extreme precipitation projections

Abstract Climate change is expected to increase the frequency and intensity of extreme weather events. To properly assess the increased economical risk of these events, actuaries can gain in relying on expert models/opinions from multiple different sources, which requires the use of model combination techniques. From non-parametric to Bayesian approaches, different methods rely on varying assumptions potentially leading to very different results. In this paper, we apply multiple model combination methods to an ensemble of 24 experts in a pooling approach and use the differences in outputs from the different combinations to illustrate how one can gain additional insight from using multiple methods. The densities obtained from pooling in Montreal and Quebec City highlight the significant changes in higher quantiles obtained through different combination approaches. Areal reduction factor and quantile projected changes are used to show that consistency, or lack thereof, across approaches reflects the uncertainty of combination methods. This shows how an actuary using multiple expert models should consider more than one combination method to properly assess the impact of climate change on loss distributions, seeing as a single method can lead to overconfidence in projections.