Real Experiments Research Articles

Real experience of caregivers of patients with HIV/AIDS from the perspective of iceberg theory: a qualitative research

ObjectiveThis study aimed to investigate the caregiving behaviours and supportive needs of caregivers of patients with HIV/AIDS and provide a basis for healthcare institutions to carry out caregiver interventions.DesignA purposive...

Development and assessment of a virtual escape-room game for teaching industrial bioprocesses.

This article presents a study on the implementation of a virtual escape-room game as a novel teaching methodology in biochemistry education. The game aimed to engage students in producing monoclonal antibodies against SARS-CoV-2 while reinforcing theoretical concepts and fostering teamwork. Three versions of the game were tested, incorporating modifications to address student feedback on and improve the overall experience. The study employed a satisfaction survey to gather insights from students regarding their perception of the game. Results showed that the implementation of answer flexibility using RegEx had a significant positive impact on student satisfaction and motivation. The introduction of RegEx allowed for a more realistic and immersive gaming experience, as students could provide varied answers while still being evaluated correctly. Overall, the findings highlight the effectiveness of the game's design, the suitability of the Google Forms platform for distance learning, and the importance of incorporating answer flexibility through RegEx. These results provide valuable guidance for educators seeking to enhance student engagement and satisfaction through the use of escape-room games in biochemistry education.

Mechanistic analysis of acid gas storage and oil recovery in naturally fractured reservoirs using single matrix block approach

AbstractThe objective of this study is to assess the storage of acid gas, containing CO2 and H2S, in a depleted naturally fractured reservoir (NFR) using single matrix block (SMB) approach. The acid gas dissolution in oil is considered by Peng‐Robinson equation of state and compositional simulation. The PHREEQC package is used to determine acid gas solubility in formation brine. Three types of acid gases with different compositions are used for this study and their swelling behavior and miscibility in relation to the reservoir oil are analyzed. An SMB model, with a matrix block surrounded by fractures, is constructed, and validated for simulation of a real experiment. The simulation is conducted for synthetic and real reservoir fluids when the oil is in its residual saturation. A sensitivity analysis is performed to study the effects of key parameters, such as acid gas composition, reservoir pressure, permeability, porosity and matrix height on the storage capacity and oil recovery factor. The matrix has a volume of 27 m3 and about half of acid gas storage is achieved in the first 5 years while the simulations are run for 30 years. The results show that up to 90% of remained oil is recoverable, and more than 0.67 kmol of acid gas per cubic meter of matrix is stored whether matrix contains a real oil or a synthetic one. Higher storage is achieved for higher matrix porosities and heights and large H2S proportion in acid gas. In all cases about 10% of acid gas is trapped in water and the remaining 90% is dissolved in oil. The mineral trapping was more active in CO2‐rich acid gases. While about 10 kg of the matrix rock was dissolved in the acidic brine when the acid gas contained H2S, the amount of the dissolved minerals in acidic brine resulted from the injection of CO2‐rich acid gas was more than 16 kg. Finally, this study gives a comparative analysis of the storage performance of acid gas mixture and pure CO2. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd.

Long-Term Efficacy and Safety of Guselkumab in Psoriasis Patients Who Failed Anti-IL17: A Two-Year Real-Life Study

Guselkumab is the first approved human IgG1λ monoclonal antibody selectively targeting the p19 subunit of interleukin (IL)-23. Despite its effectiveness and safety, which have been widely reported by clinical trials and real-life experiences, data regarding its use on patients who previously failed anti-IL17 are limited or characterized by a reduced follow-up period. These data are essential to guide clinicians in biologic switching, considering that anti-IL23 and anti-IL17 partially share their therapeutic targets, as well as some patients who may have to interrupt treatment with anti-IL17 for loss of efficacy over time or the development of adverse events (AEs). In this context, we performed a retrospective study with the aim of evaluating the long-term use (2 years) of guselkumab in psoriasis patients who previously failed at least one anti-IL17 in a real-life setting, also focusing attention on psoriasis located in difficult-to-treat areas (the scalp, palms or soles, fingernails, genitals). A total of 61 patients (35 male, 57.4%; mean age 57.6 ± 8.8 years) were enrolled. Of these, 30 (49.2%) patients failed secukinumab, 21 (34.4%) failed ixekizumab, 7 (11.5%) failed brodalumab, and 3 (4.9%) failed both secukinumab and ixekizumab. At the baseline, the mean PASI and BSA were 12.8 ± 8.4 and 24.5 ± 26.6, respectively. During week 16, PASI90 and PASI100 responses were achieved by 60.7% and 37.7% of patients, respectively, which continued to improve up to week 104 (PASI90: 73.8%, PASI100: 59.0%). Clinical improvement in difficult-to-treat areas was detected as well. In particular, a slower improvement for fingernails and the palmoplantar region was reported compared to scalp and genital psoriasis at week 16. However, no differences were found following 28 weeks of therapy. Primary and secondary inefficacy were reported by 1 (1.6%) and 5 (8.2%) patients. As regards safety, no severe AEs were collected.

Similarity indicator and CG-CGAN prediction model for remaining useful life of rolling bearings

To tackle the challenges of performing early fault warning and improving the prediction accuracy for the remaining useful life (RUL) of rolling bearings, this paper proposes a similarity health indicator and a predictive model of CG-conditional generative adversarial network (CGAN), which relies on a CGAN that combines one-dimensional convolutional neural network (CNN) with a bidirectional gate recurrent unit (Bi-GRU). This framework provides a comprehensive theoretical foundation for RUL prediction of rolling bearings. The similarity health indicator allows for early fault warning of rolling bearings without expert knowledge. Within the CGAN framework, the inclusion of constraints guides the generation of samples in a more targeted manner. Additionally, the proposed CG-CGAN model incorporates Bi-GRU to consider both forward and backward information, thus improving the precision of RUL forecasting. Firstly, the similarity indicator between the vibration signals of the rolling bearing over its full life span and the standard vibration signals (healthy status) is calculated. This indicator helps to determine the early deterioration points of the rolling bearings. Secondly, the feature matrix composed of traditional health indicators and similarity health indicator, is utilized to train and test the proposed CG-CGAN model for RUL prediction. Finally, to corroborate the efficacy of the proposed method, two sets of real experiment data of rolling bearing accelerated life from the Intelligent Maintenance Systems (IMS) are utilized. Experimental findings substantiate that the proposed similarity health indicator offers early fault alerts and precisely delineates the performance diminution of the rolling bearing. Furthermore, the put-forward CG-CGAN model achieves high-precision RUL prediction of rolling bearing.

Locally Self-Adjustive Smoothing for Measurement Noise Reduction with Application to Automated Peak Detection.

Smoothing is a widely used approach for measurement noise reduction in spectral analysis. However, it suffers from signal distortion caused by peak suppression. A locally self-adjustive smoothing method is developed that retains sharp peaks and less distorted signals. The proposed method uses only one parameter that determines the global smoothness of data, while balancing the local smoothness using the data itself. Simulation and real experiments in comparison with existing convolution-based smoothing methods indicate both qualitatively and quantitatively improved noise reduction performance in practical scenarios. We also discuss parameter selection and demonstrate an application for the automated smoothing and detection of a given number of peaks from noisy measurement data.

Unveiling Socioeconomic Disparities: Understanding Pregnancy Awareness and Family Well-being among Middle-Late Adolescent Mothers across Diverse Socioeconomic Strata in Urban Manila, Philippines

This research study examines the real-life experiences of adolescent mothers within the age group of 13-17 years old (middle adolescence) to 18-21 years old (late adolescence), coming from middle and low socioeconomic backgrounds. Using different qualitative research techniques, this study aims to uncover unique obstacles, coping strategies, and support networks encountered by teenage mothers from different economic strata. A total of 6 teenage mothers from middle-class (n=3) and low-income (n=3) settings is conducted to gather their stories and perspectives. Thematic analysis is employed to discern common threads and distinctions between the two groups, creating themes to categorize the similarities between their responses. The outcomes of this inquiry offer valuable insights into how socioeconomic status intersects with teenage parenthood, underscoring four significant factors that emerged through the data analysis: Support Systems, Educational and Career Trajectory, Family Dynamics and Expectations, and Awareness and Perception. Having identified these themes can design a path towards creating customized interventions and support mechanisms for both vulnerable demographics while advocating for more inclusive and educational programs in raising awareness and removing the stereotypes about teenage pregnancy. For future researchers interested in studying the real-life experiences of adolescent mothers from different economic backgrounds, it is essential to consider the myriad of factors that shape their lives. These factors include race, culture, and geographical location, all of which intersect with their socioeconomic status to influence their experiences.

Open educational resource case studies: responding to nursing student educational needs in the moment

BackgroundThe purpose of this paper is to share the pedagogical innovation of using open educational resource (OER) inclusive case studies in the classroom to respond to immediate student learning needs and augment the theory-to-practice gap that exists in undergraduate education. InnovationStudents were introduced to case studies as an OER as a weekly activity. The initial case studies were rooted in educators’ real-life experiences and nursing practice. As courses evolved, if there was an emerging trend in healthcare or a component of a concept, model, or theory that students were challenged with, subsequent case studies were edited to suit learning needs. ImplicationsWhen used intentionally, case studies can be responsive to student needs in the moment as OERs can facilitate a smoother transition of theory into practice. ConclusionThis collaborative initiative can inspire other educators and institutions to bridge the theory-to-practice gap, improving the quality of care for patients, using a similar approach.

A Cascaded GRU-Based Stereoscopic Matching Network for Precise Plank Measurement

Abstract Wooden plank images in industrial measurements often contain numerous textureless areas. Furthermore, due to the thin plate structure, the three-dimensional disparity of these planks is predominantly confined to a narrow range. Consequently, achieving accurate three-dimensional matching of wooden plank images has consistently presented a challenging task within the industry. In recent years, deep learning has progressively supplanted traditional stereo matching methods due to its inherent advantages, including rapid inference and end-to-end processing. Nonetheless, the acquisition of datasets for stereo matching networks poses an additional challenge, primarily attributable to the difficulty in obtaining accurate disparity data. Thus, this paper presents a novel stereo matching method incorporating three key innovations. Firstly, an enhanced Gated Recurrent Unit(GRU) network is introduced, accompanied by a redesigned structure to achieve higher matching accuracy. Secondly, an efficient preprocessing module is proposed, aimed at improving the algorithm's efficiency. Lastly, in response to the challenges posed by datasets acquisition, we innovatively employed image simulation software to obtain a high-quality simulated dataset of wooden planks. To assess the feasibility of our approach, we conducted both simulated and real experiments. The experiments results clearly exhibit the superiority of our method when compared to existing approaches in terms of both stability and accuracy. In the simulation experiment, our method attained a bad1.0 score of 2.1% (compared to the baseline method's 9.76%); In the real experiment, our method achieved an average error of 0.104mm (compared to the baseline method's 0.268mm). It is worth noting that our study aims to address the challenge of acquiring datasets for deep learning and bridging the gap between simulated and real data, resulting in increased applicability of deep learning in more industrial measurement domains.

Distributed Optimal Solutions for Multiagent Pursuit-Evasion Games for Capture and Formation Control

In this paper, distributed optimal solutions are designed for networked multiagent pursuit-evasion (MPE) games for capture and formation control. In the games, the pursuers aim to minimize the distance from their target evaders while the evaders attempt to maximize it, and at the same time, all players desire to maintain cohesion with their teammates. The goals of agents are obviously reflected in the obtained optimal control strategies which consist of an attracting term and/or a repelling term. Nash equilibrium is obtained by means of optimal strategies using the solutions of the HJI equations. Furthermore, three scenarios are considered in the MPE game: one-pursuer-one-evader, multiple-pursuer-one-evader, and multiple-pursuer-multiple-evader, where sufficient conditions are given for pursuers in achieving exponential capture or formation control with ultimate zero or bounded errors. It is shown that the conditions depend on the structure of the communication graph, the parameters in the controllers, and the expected formation configurations. Finally, both simulations and real flight experiments successfully demonstrate the effectiveness of the proposed strategies.

Autobiographical phenomenology of memories of fiction

ABSTRACT Most autobiographical memories are based on real-life experiences, but memories of fiction have many similarities to real-life autobiographical memories. However, the phenomenological nature of this similarity, the potential differences between media types, and the role of individual differences need further investigation. Based on previous findings, we expected differences between media types on emotional intensity, sensory vividness, and confidence about the recall. To provide insight into these issues, we collected one real-life autobiographical memory and one memory of fiction (book, film, or video game) from 291 participants. We asked them to rate their memories phenomenologically. The participants also provided information regarding their motivations for engaging with fictional stories. Our results show phenomenological differences in several dimensions between media types and differences in the similarity of media types to real-life memories. While absorption seems to be a good predictor for immersion, escapism tendency is a motivation to engage with fiction frequently.

PENGARUH MODEL PEMBELAJARAN CONTEXTUAL TEACHING AND LEARNING (CTL) TERHADAP KEMAMPUAN PEMAHAMAN KONSEP MATEMATIS SISWA PADA MATERI DIMENSI TIGA

This research aims to determine whether there is an influence of the CTL learning model on students' ability to understand mathematical concepts in three-dimensional material. This research approach is a quantitative approach with a quasi-experimental type of research. The population of this study was class XII of SMA Negeri 1 Teluk Dalam in the 2023/2024 academic year, consisting of 262 students. Samples were taken using the Cluster Random Sampling technique, namely class XII Science-Melati (Experiment) 34 students and XII Science-Teratai (Control) 26 students. The instrument used is a test of students' ability to understand mathematical concepts in three-dimensional material. The results of research data processing showed that the average Pretest score for the experimental class was 65.59 and the control class was 65.38 and the Posttest for the experimental class was 72.03 and the control class was 66.12. Hypothesis testing using the Independent-Samples T Test shows that the sig (2-tiled) value is 0.048 < 0.05, meaning there is a significant difference in the posttest scores for the two classes. It was concluded that the CTL learning model influenced students' ability to understand mathematical concepts in three-dimensional material. This is influenced by students who play an active role in discovering concepts of learning material through real experience and collaboration in discussions with friends and teachers. Researchers suggest (1) The CTL learning model is an alternative for teachers to build students' ability to understand mathematical concepts (2) Students are advised to seek and build understanding of learning material through their knowledge of the real world (3) The results of this research should be taken into consideration by researchers Next in choosing a learning model.

Estimates of constants in the limit theorems for chaotic dynamical systems

In a vast area of probabilistic limit theorems for dynamical systems with chaotic behaviors always only functional form (exponential, power, etc.) of the asymptotic laws and of convergence rates were studied. However, for basically all applications, e.g., for computer simulations, development of algorithms to study chaotic dynamical systems numerically, as well as for design and analysis of real (e.g., in physics) experiments, the exact values (or at least estimates) of constants (parameters) of the functions, which appear in the asymptotic laws and rates of convergence, are of primary interest. In this paper, we provide such estimates of constants (parameters) in the central limit theorem, large deviations principle, law of large numbers and the rate of correlations decay for strongly chaotic dynamical systems.

Development of a Novel, Reusable Task Trainer for Foreign Body Removal and Abscess Incision and Drainage.

Cutaneous abscess incision and drainage and foreign body removal are 2 common procedures in a variety of outpatient settings. The goal of this project was to create a novel, clean, reusable task trainer that could more accurately reproduce all the steps necessary to perform cutaneous abscess drainage or foreign body removal including ultrasound to identify the abscess cavity or foreign body. The novel task trainer was constructed using silicone for both the base and the top skin. Toothpaste mixed with saline was used for the abscess material as this produced an ultrasound image that mimicked purulent material. A piece of a metal paper clip was imbedded in the top skin to mimic a cutaneous foreign body. Physician assistant (PA) students given a didactic lecture then used the novel task trainer as part of a clinical skills course. After the activity, the PA students were asked to voluntarily complete a brief preretrospective/postretrospective survey comprised 8 questions that addressed their self-perceived knowledge and skills using a 5-point Likert scale. Survey data from an initial cohort of PA students at one university show effectiveness of the models when used with the associated curriculum. This study demonstrates the feasibility of constructing a practical, low-cost, non-animal-based task trainer for the purpose of training incision and drainage of cutaneous abscesses and removal of cutaneous foreign bodies. This novel task trainer allows for ultrasound skill development and provides realistic imaging experience.

MUSEUM DAN SEKOLAH: SINERGI KEBIJAKAN DEMOKRATISASI KEBUDAYAAN MELALUI PROGRAM PEMBELAJARAN SENI DAN BUDAYA DI KOTA LA ROCHELLE - PRANCIS

Our article describes the relationship between museums and schools as a policy of democratisation of French culture, a policy that has encouraged the ministry of education and the ministry of culture to work together in designing arts and cultural learning programmes in museums and in schools. The case study of the implementation of the national policy of democratisation of culture by the municipality of La Rochelle is an important consideration that can help us to understand how the locality of public policy implementation in France can contribute specific characteristics to the cultural development and management of museums and schools. Arts and culture learning in museums aims to bring students into direct contact with museum collections. The aim is to give students real-life experiences, encouraging them to easily express or talk about them, both in the classroom and beyond. Learning in museums is designed to build sensitivity to emotions and impressions that arise when dealing directly with museum objects, when looking at the shape, colour or material of museum objects. Students will comment and express their experiences. This is the virtue of the learning process.

Concept of a Peripheral-Free Electrified Monorail System (PEMS) for Flexible Material Handling in Intralogistics

With the emergence of Industry 4.0 in intralogistics, the need for flexible material handling solutions is increasing. While conventional conveyor systems are often too inflexible to meet changing requirements. Automated guided vehicles offer an answer, additional solutions are required for companies relying on already busy and crowded shop floors. This paper presents a concept for a periphery-free electrified monorail system (PEMS) that enables flexible material transport with minimal floor requirements. The PEMS is based on classic electrified monorail technology, and requires no additional peripheral devices within the rail system. Installation and maintenance costs are kept to a minimum through simplified branching elements and a battery-powered energy supply for the vehicles. The modular design of the rail elements further allows transport on standardized Euro-pallets. Moreover, a taxonomy for evaluating the passivity of branching elements of electrified monorail systems is introduced. The functionality of the PEMS was validated by conducting real experiments using a prototype, The results show that the PEMS provides high flexibility in terms of layout design and usage, allowing for fast adaption to the changing requirements of intralogistics.

A Critical Review of Human Jaw Biomechanical Modeling

The human jaw is a complex biomechanical system involving different anatomical components and an articulated muscular system devoted to its dynamical activation. The numerous actions exerted by the mandible, such as talking, eating or chewing, make its biomechanical comprehension absolutely indispensable. To date, even if research on this topic has achieved interesting outcomes using in vitro testing, thanks to the development of new apparatus and methods capable of performing more and more realistic experiments, theoretical modeling is still worthy of investigation. In light of this, nowadays, the Finite Element Method (FEM) approach constitutes certainly the most common tool adopted to investigate particular issues concerning stress–strain characterization of the human jaw. In addition, kinematics analyses, both direct and inverse, are also diffuse and reported in the literature. This manuscript aimed to propose a critical review of the most recurrent biomechanical models of the human mandible to give readers a comprehensive overview on the topic. In light of this, the numerical approaches, providing interesting outcomes, such as muscular activation profiles, condylar forces and stress–strain fields for the human oral cavity, are mainly differentiated between according to the joint degrees of freedom, the analytical descriptions of the muscular forces, the boundary conditions imposed, the kind of task and mandible anatomical structure modeling.

Dynamic path planning for mobile robots based on artificial potential field enhanced improved multiobjective snake optimization (APF‐IMOSO)

AbstractWith the widespread adoption of mobile robots, effective path planning has become increasingly critical. Although traditional search methods have been extensively utilized, meta‐heuristic algorithms have gained popularity owing to their efficiency and problem‐specific heuristics. However, challenges remain in terms of premature convergence and lack of solution diversity. To address these issues, this paper proposes a novel artificial potential field enhanced improved multiobjective snake optimization algorithm (APF‐IMOSO). This paper presents four key enhancements to the snake optimizer to significantly improve its performance. Additionally, it introduces four fitness functions focused on optimizing path length, safety (evaluated via artificial potential field method), energy consumption, and time efficiency. The results of simulation and experiment in four scenarios including static and dynamic highlight APF‐IMOSO's advantages, delivering improvements of 8.02%, 7.61%, 50.71%, and 12.74% in path length, safety, energy efficiency, and time‐savings, respectively, over the original snake optimization algorithm. Compared with other advanced meta‐heuristics, APF‐IMOSO also excels in these indexes. Real robot experiments show an average path length error of 1.19% across four scenarios. The results reveal that APF‐IMOSO can generate multiple viable collision‐free paths in complex environments under various constraints, showcasing its potential for use in dynamic path planning within the realm of robot navigation.

LIVED EXPERIENCES OF DANGEROUS DRUG USERS IN THEIR SOCIAL CAPITAL: A NARRATIVE INQUIRY

In this study, the exploration of the phenomenon is through qualitative design. It intended to discover the real-life experiences of the dangerous drug user with their social capital. With the data from the participants, it provides the themes under the major theme created from life course theory. This concludes that social capital is significant either too dangerous drug use and be cured once the individual has the disorder. Therefore, recommendations are solely base to the life trend of dangerous drug users within the social capital. KEYWORDS: Dangerous drugs, Experiences, Social Capital, Users

LIVED EXPERIENCES OF DANGEROUS DRUG USERS IN THEIR SOCIAL CAPITAL: A NARRATIVE INQUIRY

In this study, the exploration of the phenomenon is through qualitative design. It intended to discover the real-life experiences of the dangerous drug user with their social capital. With the data from the participants, it provides the themes under the major theme created from life course theory. This concludes that social capital is significant either too dangerous drug use and be cured once the individual has the disorder. Therefore, recommendations are solely base to the life trend of dangerous drug users within the social capital. KEYWORDS: Dangerous drugs, Experiences, Social Capital, Users