Practical Method Research Articles

A Prioritization Method for Sustainable Food Waste Reduction Practices

A Prioritization Method for Sustainable Food Waste Reduction Practices

Action observation with motor simulation of reactive stepping: A randomized study in older adults with a history of falls

BackgroundPerturbation-based training improves reactive stepping responses to prevent falling following a loss-of-balance. As there is currently no safe and feasible method for home-based practice, this randomized study investigated whether action observation with motor simulation (AOMS) of balance recovery improves reactive stepping in older adults with a history of falls. Additionally, we evaluated whether effects differ between AOMS of a human actor in the same experimental context or of an avatar in a virtual world. MethodsSeventy participants with a history of falls (68.3 ± 5.2y/o;52f) were subjected to 20 balance perturbations eliciting backward reactive steps. The AOMS group was tested after simulation of 20 reactive steps demonstrated by either a human actor (HumanAOMS) or a virtual avatar (AvatarAOMS). The control group was tested without prior observation. The primary outcome was reactive step quality, quantified as the leg angle at stepping-foot contact. ResultsDifferences between groups in the first perturbation trial were not significant. Upon repeated trials, both AOMS groups improved reactive step quality substantially faster than the control group. AOMS participants required on average five repetitions to achieve a reactive step quality that was no longer different from final performance in the last trial, whereas the control group needed ten. Both HumanAOMS and AvatarAOMS yielded similar gains. ConclusionsThe lack of effect in the first trial suggests that AOMS alone may not be sufficient for preventing real-life falls in this population. A next step would be to investigate whether this could be achieved by combining brief real perturbation practice with AOMS.

Exploring Asthma Mechanism of Belamcanda Chinensis by "Dose-effect Weighted Coefficient" Network Pharmacology and Experiment Validation.

Asthma is a chronic inflammatory disease of the airways that seriously endangers human health. Belamcanda chinensis (BC), a traditional Chinese medicine, has been used to counteract asthma as it has been shown to possess anti-inflammatory and regulatory immunity properties. The study aimed to investigate the mechanisms of action of BC in the treatment of asthma; a "dose-effect weighted coefficient" network pharmacology method was established to predict potential active compounds. Information on the components and content of BC was obtained by UPLC-QEOrbitrap- MS spectrometry. Based on BC content, oral bioavailability, and molecular docking binding energy, dose-effect weighting coefficients were constructed. With the degree greater than average as the index, a protein-protein interaction (PPI) database was used to obtain the core key targets for asthma under dose-effect weighting. GO function and KEGG pathway analyses of the core targets were performed using DAVID software. Finally, MTT and ELISA assays were used to assess the effects of active components on 16HBE cell proliferation. The experimental results using the 16HBE model demonstrated BC to have a potential protective effect on asthma. Network pharmacology showed SYK, AKT1, and ALOX5 to be the main key targets, and Fc epsilon RI as the promising signaling pathway. Eight components, such as tectoridin, mangiferin, luteolin, and isovitexin were the main active compounds, Finally, we analyzed the LPS-induced 16HBE proliferation of each active ingredient. Based on the activity verification study, all five predicted components promoted the proliferation of 16HBE cells. These five compounds can be used as potential quality markers for asthma. This study provides a virtual and practical method for the simple and rapid screening of active ingredients in natural products.

Clinical application of targeted next-generation sequencing utilizing bronchoalveolar lavage fluid in thoracic surgery ICU patients with suspected pulmonary infections.

The aim of this prospective study was to evaluate the diagnostic value of targeted next-generation sequencing (tNGS) in identifying pathogens from bronchoalveolar lavage fluid (BALF) in thoracic surgery ICU patients, offering additional diagnostic methods for clinical practice. We collected clinical data from patients with suspected pulmonary infections in the thoracic surgery ICU of the Second Affiliated Hospital of Air Force Medical University. A total of 50 patients were enrolled in this study. Traditional pathogen detection (TPD), involving culture and loop-mediated isothermal amplification assays for 12 pathogens, along with tNGS, was employed for pathogen identification in BALF samples. Our findings demonstrated that the positive rate of tNGS was significantly greater than that of TPD (96%vs. 68%). Among the 50 samples analyzed, tNGS identified a total of 165 pathogens, whereas TPD detected only 48 pathogens. The TPD method primarily detected bacteria and fungi, whereas tNGS exhibited broader capabilities, identifying 104 cases with bacteria, 19 with fungi, 34 with DNA viruses, and 8 with RNA viruses. Notably, tNGS displayed enhanced efficiency in detecting atypical pathogens such as fungi, DNA viruses and RNA viruses. Furthermore, compared with TPD, tNGS demonstrated superior sensitivity (95.83%vs. 68.75%). tNGS technology, characterized by its high sensitivity, specificity, and cost-effectiveness, holds great promise as a reliable diagnostic tool for assessing pulmonary infections in the thoracic surgery ICU patients.

Eco-Friendly Cinematic Practices: The Sustainable Use of Film Costumes

The film industry is a powerful medium for cultural storytelling and entertainment, yet it is associated with significant environmental challenges. Among these, the lifecycle of movie costumes—from design and production to disposal—remains a critical yet underexplored area. Costumes often involve resource-intensive processes and generate substantial waste. This paper examines the method for sustainable practices in the design, production, and reuse of movie costumes, highlighting strategies such as upcycling, rental systems, the adoption of eco-friendly materials, and the integration of digital technologies. By embedding circular economy principles into costume production, the industry can balance creativity with environmental responsibility, showcasing a blueprint for eco-conscious filmmaking.

Estimation of Physico-Chemical Properties of Soil Using Machine Learning

This study leverages soil images to determine its physico-chemical characteristics from two locations in Benue State, North-Central Nigeria: Vandeikya (7.099653°, 8.572102°) and Konshisha (6.783539°, 9.069549°). Practical alternatives to traditional soil quality estimation methods, often costly and inaccessible in resource-poor regions, were implemented. The study integrates Machine Learning (ML) and Deep Learning (DL) techniques with soil image analysis, employing image feature extraction through Gray-Level Co-occurrence Matrix (GLCM) and Gabor filters to enhance the feature space across 1,388 samples (each consisting of 600g of soil) and 16 properties. We evaluated different models, including Support Vector Regression (SVR), a Convolutional Neural Network (CNN), an optimized CNN using Grid Search, and a stacked ML-CNN approach. The models were assessed on their ability to predict soil properties while minimizing error rates. The SVR model showed limited predictive performance, with its best results yielding slightly over 40% R² and negative scores for physical properties. The CNN model performed better but had feature scores below 80% R². The optimized CNN model surpassed 90% R² and reduced MAE by more than 50% for several properties. The stacked ML-CNN model further improved these metrics, demonstrating the effectiveness of the integrated approach. This research highlights the potential for using machine learning and image-based analysis as a scalable, cost-effective alternative to conventional soil testing, offering practical solutions for regions where conventional measurement tools are scarce. Integration with historical soil data might also open new possibilities for enhancing the accuracy and applicability of these methods for broader soil management practices.

Career studies as self-making and life designing

Advocates of career studies in higher education propose teaching undergraduate students about careers, the labour marketand employability. According to McCash (2008), exploration and research about careers should empower students by helpingthem to focus on ‘life purposes and meanings and the more prosaic matters of achieving these ends’ (p. 6). The recent International Career Studies Symposium, held at the University of Reading, sought to elaborate the content of a career studies curriculum and demonstrate ways of teaching ‘career.’ As a participant in this symposium, I asserted that career construction theory offers to a career studies curriculum a model for conceptualising and understanding work lives (Savickas, 2005). Furthermore, it emphasises the importance of a curriculum space for studying the self and a practical method for self-making and life designing (Savickas et al., in press).

Co-Learning Scenarios with the Community: Democratic Practices In and Out of the Design Studio

Design education is characterised by its experiential and practice-oriented approach, emphasising active engagement with projects. The pedagogical focus is on developing individual styles, professional stances, and a receptive attitude towards novel experiences, aligning with the evolving landscape of the design profession. This study explores community engagement in student projects as a means to establish a co-deciding and co-learning infrastructure in the design studio. This participative and democratic approach challenges traditional hierarchies in higher education, transforms the student-instructor relationship, and aligns educational practices with the evolving requirements of the design profession. The study investigates students' insights into co-learning with the community through scenario-building. A workshop conducted with twelve fourth-year undergraduate industrial design students and the thematic analysis of the findings revealed that educational community engagement projects employing inclusionary methods motivate students and foster a positive attitude towards shifting power relations within a democratic design studio structure. The findings also highlight the need for a clear focus, a set of principles for successful engagement, and conflict resolution in the co-learning process, as well as the generative potential of scenario-building as a method for inclusive practices.

Application‐Based Review of Soft Computational Methods to Enhance Industrial Practices Abetted by the Patent Landscape Analysis

ABSTRACTSoft computing is a collective methodology that touches all engineering and technology fields owing to its easiness in solving various problems while comparing the conventional methods. Many analytical methods are taken over by this soft computing technique and resolve it accurately and the soft computing has given a paradigm shift. The flexibility in soft computing results in swift knowledge acquisition processing and the information supply renders versatile and affordable technological system. Besides, the accuracy with which the soft computing technique predicts the parameters has transformed the industrial productivity to a whole new level. The interest of this article focuses on versatile applications of SC methods to forecast the technological changes which intend to reorient the progress of various industries, and this is ascertained by a patent landscape analysis. The patent landscape revealed the players who are in the segment consistently and this also provides how this field moves on in the future and who could be a dominant country for a specific technology. Alongside, the accuracy of the soft computing method for a particular practice has also been mentioned indicating the feasibility of the technique. The novel part of this article lies in patent landscape analysis compared with the other data while the other part is the discussion of application of computational techniques to various industrial practices. The progress of various engineering applications integrating them with the patent landscape analysis must be envisaged for a better understanding of the future of all these applications resulting in an improved productivity.

EDNA-Based Survey of Fish Species in Water Bodies Using Loop-Mediated Isothermal Amplification (LAMP) for Application of Developing Automatic Sampler.

The monitoring of species in a habitat is important to ensure biological diversity. Environmental DNA (eDNA) can infer the presence-absence of species and enable rapid action to avoid threatening factors in ecosystems in the case of non-indigenous species. Loop-mediated isothermal amplification (LAMP) assays for molecular amplification are rapidly gaining popularity in species detection, but LAMP remains an underutilized method for eDNA-based monitoring practices. The most effective combination for successful species monitoring may be the collection of eDNA or biological traces collected by nanofiltration followed by LAMP-based species detection initiatives. Here, we used LAMP analysis to detect the eDNA of Esox lucius (Northern Pike), Anguilla anguilla (European Eel), and Salmo salar (Atlantic Salmon) in Borre Lake and in the Drammen River. The selection of species is based on the categories of regionally invasive species, endangered species, and species of least concern. Two target genes were considered for each species and LAMP primers were designed. Our study showed that LAMP is an effective tool for discovering specific fish eDNA (analysis) to maintain aquatic ecosystems.

Tracing the Evolution of Information Transparency for OpenAI’s GPT Models through a Biographical Approach

Information transparency, the open disclosure of information about models, is crucial for proactively evaluating the potential societal harm of large language models (LLMs) and developing effective risk mitigation measures. Adapting the biographies of artifacts and practices (BOAP) method from science and technology studies, this study analyzes the evolution of information transparency within OpenAI’s Generative Pre-trained Transformers (GPT) model reports and usage policies from its inception in 2018 to GPT-4, one of today’s most capable LLMs. To assess the breadth and depth of transparency practices, we develop a 9-dimensional, 3-level analytical framework to evaluate the comprehensiveness and accessibility of information disclosed to various stakeholders. Findings suggest that while model limitations and downstream usages are increasingly clarified, model development processes have become more opaque. Transparency remains minimal in certain aspects, such as model explainability and real-world evidence of LLM impacts, and the discussions on safety measures such as technical interventions and regulation pipelines lack in-depth details. The findings emphasize the need for enhanced transparency to foster accountability and ensure responsible technological innovations.

Strategi Guru Tahfidz dalam Memperbaiki Bacaan Al-Qur’an di Taman Pendidikan Al-Qur’an (TPA) Ar-Rasyid Kota Tanjungpinang Kepulauan Riau

This research was conducted at the Ar-Rasyid Al-Qur'an Education Park (TPA), Tanjungpinang City, Riau Islands, to overcome problems in learning the Al-Qur'an, especially the pronunciation of hijaiyah letters, recognition of dignity, and the science of recitation. Teachers try to guide children in reading the Koran correctly, assisted by the cooperation of parents at home. The teacher uses the question and answer method to motivate students to understand and instill the laws of recitation. This research is qualitative field research with descriptive methods. Data was collected through interviews, observation and documentation, then analyzed using the steps of collecting, editing, presenting data and drawing conclusions. Data validity testing was carried out through triangulation. The research results show that the tahfidz teacher's strategy in improving Al-Qur'an reading includes utilizing time to read the Al-Qur'an before learning, muroja'ah strategies, and implementing systematic learning procedures. Teachers also carry out final assessments every semester. Implementation techniques include the jama' method for collective memorization and the Iqra' method for reading practice. The Tahfidz teacher evaluation strategy shows the existence of supporting factors and investors, such as laziness and donor coordination between the head of the foundation, teachers and students. The solutions implemented include good time management, motivation and support from TPA, teachers and parents so that students are more enthusiastic about learning the Koran at TPA Ar-Rasyid.

Determination of MYD88 and CXCR4 Mutations for Clinical Detection and Their Significance in Waldenström Macroglobulinemia.

This study aims to explore the incidence and clinical features of MYD88 and CXCR4 mutations in patients with Waldenström macroglobulinemia (WM) and determine the optimal method for routine clinical practice. Additionally, we seek to evaluate the prognostic significance of these features across various therapeutic backgrounds [the cytotoxic group, the rituximab/bortezomib-based group, and the Bruton tyrosine kinase inhibitor (BTKi) group]. A total of 385 symptomatic patients with WM were analyzed for MYD88 and CXCR4 mutations using Sanger sequencing, next-generation sequencing, allele-specific qPCR (AS-PCR), and/or droplet digital PCR (ddPCR). The overall MYD88 mutation rate was 87.8%, relatively lower than that in the Western cohort. Both AS-PCR and ddPCR demonstrated high sensitivity in unsorted samples, detecting 98.5% and 97.7% of mutations, respectively, including those with low tumor burdens. The total CXCR4 mutation rate was 30.9%, with next-generation sequencing exhibiting the highest sensitivity of 78.0%. CXCR4 mutation was significantly linked to shorter OS only within the BTKi treatment group. The multivariate analysis indicated that MYD88 and CXCR4 mutations were not independent prognostic factors in the non-BTKi group when considering the International Prognostic Scoring System for Waldenström macroglobulinemia (IPSSWM) clinical staging. However, in the BTKi treatment group, these mutations emerged as independent adverse prognostic factors, overshadowing the prognostic significance of the IPSSWM classification (MYD88: HR, 0.229; P = 0.030; CXCR4: HR, 3.349; P = 0.012). Testing for MYD88 mutations using AS-PCR or ddPCR in unsorted samples is viable for routine clinical practice. Under BTKi treatment, MYD88 and CXCR4 mutations hold greater prognostic importance than IPSSWM staging in WM.

Self-management of long-term conditions: a district nursing perspective of patient engagement.

The UK has a growing ageing population with increased prevalence of long-term conditions. It has the potential to overwhelm the country's healthcare system. The COVID-19 pandemic and its risk of transmission provided an opportunity for people with long-term conditions to focus on self-care and for district nurses to promote self-management. Self-management strategies, such as digital technology, motivational interviewing, social prescribing and shared decision-making can assist them in planning a whole-population approach towards managing physical and mental wellbeing. For this to become a reality, investment is needed to educate the patients, their carers, district nurses, multidisciplinary teams and to ensure the sustainability of self-care methods for future practice.

Cavitation state recognition method of centrifugal pump based on multi-dimensional feature fusion and convolutional gate recurrent unit

The rapid and accurate recognition of cavitation in centrifugal pumps has become essential for improving production efficiency and ensuring machinery longevity. To address the limitations of existing methods in terms of applicability, accuracy, and efficiency, a new method based on multi-dimensional feature fusion and convolutional gate recurrent unit (MCGN) was proposed. Experimental monitoring of cavitation of centrifugal pumps was conducted. Five signals at different water temperatures and operating frequencies were collected. Key modulating features were extracted by time-frequency analysis and principal component analysis. The multi-dimensional features are fused by one and two dimensional convolutional neural networks. The cavitation state label was used to label the sample set by cavitation number, net positive suction head, and cavitation evolution images captured by high-speed cameras. Finally, the neural network based on the convolutional gate recurrent unit was used to classify the cavitation state of the centrifugal pump. The experimental results demonstrate that the proposed method achieves recognition accuracies exceeding 98% for vibration signals, noise signals, outlet pressure pulsation signals, and torque signals. Compared with the short-time Fourier transform-autoencoder model, MCGN model can improve the recognition accuracy by 4.03%, computation efficiency by 20%, and loss by 87%. These advances underscore the potential of the method in monitoring and maintenance practices for centrifugal pumps.

Unsupervised CT Metal Artifact Reduction by Plugging Diffusion Priors in Dual Domains.

During the process of computed tomography (CT), metallic implants often cause disruptive artifacts in the reconstructed images, impeding accurate diagnosis. Many supervised deep learning-based approaches have been proposed for metal artifact reduction (MAR). However, these methods heavily rely on training with paired simulated data, which are challenging to acquire. This limitation can lead to decreased performance when applying these methods in clinical practice. Existing unsupervised MAR methods, whether based on learning or not, typically work within a single domain, either in the image domain or the sinogram domain. In this paper, we propose an unsupervised MAR method based on the diffusion model, a generative model with a high capacity to represent data distributions. Specifically, we first train a diffusion model using CT images without metal artifacts. Subsequently, we iteratively introduce the diffusion priors in both the sinogram domain and image domain to restore the degraded portions caused by metal artifacts. Besides, we design temporally dynamic weight masks for the image-domian fusion. The dual-domain processing empowers our approach to outperform existing unsupervised MAR methods, including another MAR method based on diffusion model. The effectiveness has been qualitatively and quantitatively validated on synthetic datasets. Moreover, our method demonstrates superior visual results among both supervised and unsupervised methods on clinical datasets. Codes are available in github.com/DeepXuan/DuDoDp-MAR.

The effect of virtual reality glasses used in dental treatment on anxiety and fear in children: A randomized controlled study

IntroductionVirtual reality glasses can be used as a distraction method in dental practices for children. This study was carried out to evaluate the effect of virtual reality glasses used during tooth extraction and extirpation treatment under local anesthesia on anxiety and fear in children aged 7–10 years. MethodsThis study is a randomized controlled trial. The sample of the study consisted of 120 seven to ten-year-old children, including 60 in the EG and 60 in the CG, who received tooth extraction and extirpation treatment in the pediatric dental clinic. Data collection tools included the Children's Fear Scale, the Child Anxiety Scale-State. Data were analyzed using the Chi-square test, t-test, Shapiro-Wilk, mean and percentage distributions. ResultsThe assessments made by the researcher and the children indicated a statistically significant difference between experimental and control groups in terms of their mean anxiety and fear scores following tooth extraction and extirpation treatment (p < 0.001). After tooth extraction and extirpation treatment, it was determined that the children in the EG had lower mean anxiety and fear scores than the children in the CG. ConclusionIt was found that virtual reality glasses used during tooth extraction and extirpation treatment in children aged 7–10 years were effective in reducing their anxiety and fear levels. Virtual reality glasses can be used as a distracting method to relieve children's anxiety and fears during dental treatment procedures.

MENANAMKAN MINAT LITERASI (BACA TULIS) SEJAK DINI DI SDN NAGACIPTA 02

Lack of facilities and infrastructure that can support students’ reading activities, as well as lack of support and motivation for students. In the teaching and learning process, teachers also have not implemented innovative and interesting teaching, especially in teaching reading to students from the lower grades, resulting in a lack of interest and interest among students in literacy activities. The purpose of this writing is to explain the importance of literacy in the quality of human resources who are able to compete and keep up with current developments. The implementation method applied was socialization to students at SDN Nagacipta 02 with the theme of instilling an interest in literacy (reading and writing) from an early age, using the flashcards method for reading practice. This activity was held at SDN Nagacipta 02 which is located in Nagacipta Village, Serang Baru District on February 27 2024. The results of this program can be seen in the increased interest of students in reading. When running the program in class 2 and class 4, students appear to be able to participate in the learning process with enthusiasm and full of activity, this can be seen when running the program in class 2 using the flashcards method and for class 4 students it can also foster a sense of cooperation between classmates. Through group work in creative activities to decorate literacy trees. Because motivation and support both in terms of facilities and infrastructure, as well as the ability to package innovative teaching and learning processes can have a big impact on the growth of students’ interest in the learning process, which will influence the achievement of learning goals.

Testing of parenteral drug products for visible particles: comparison of the Ph. Eur. method with an alternative method using polarised light

ObjectivesParenteral drug products should be essentially free from visible particulate contamination. To ensure this, every batch produced must be subject to a 100% visual inspection. Monograph 2.9.20 of the European...

Development of a three-dimensional printed model from a digital impression of a real patient for aesthetic dentistry undergraduate teaching.

The acquisition of skills and manual dexterity in aesthetic dentistry in undergraduate teaching requires preclinical practices with simulation that should approximate real clinical situations. We will present a digital procedure for the creation of three-dimensional (3D) resin models adapted to the practices of the Aesthetic Dentistry course. Stereolithography or Standard Tesellation Language (STL) files of a real patient were previously obtained with a 3-shape intraoral scanner. Using the Exocad computer programme for dental prosthesis design, various modifications were made, such as incisor rotation, surface alterations imitating dysplasias or erosions, the creation of diastemas, or even changes in tooth size. The virtual model was printed in resin for use by students. Once the practices were finished, the students and the teachers evaluated the use of the 3D printed models. The result is the typodont model, in which seven laboratory sessions took place: 1-Restoration of conoid tooth morphology, 2-Cervical abrasion/ erosion restoration, 3-Direct Composite Veneer, 4-Aesthetic correction in a tooth with rotation, 5-Diastem closure, 6-Occlusal abrasions/ erosion, and 7-Maryland bridge. 90.48% of the students evaluated the designed 3D model as the best method for laboratory practice compared to other methods, obtaining a general assessment of 8.3 out of 10. The method used has provided a reproducible standard analog model for direct aesthetic dental restoration practice, with a good assessment by students and teachers.