Search Results (43)

Durable plastics are a sustainability challenge for healthcare products. Orthopedic products are regulated with strict specifications for human tissue interactions. Healthcare engineers and managers select plastic to meet the full range of material properties. Plastic is plentiful, low cost, and reliable, with established supply chains. Used plastic products can be discarded using existing waste management systems with low externality costs for orthopedic businesses. However, plastic is produced from fossil petroleum, raising issues for sustainability commitments of healthcare product companies. Barriers to the transition away from single-use plastic toward circular systems and bio-based healthcare products have been studied, but the transition is a goal that has yet to be realized. This research article reports on a transition engineering design sprint with a medium-sized orthopedic company specializing in orthoses for children and teenagers. The design sprint process engages company experts with systems perspectives on the role of unsustainable plastic in orthopedic healthcare and illuminates opportunities for capturing value in business transition. Two system transition project concepts were co-developed. The first concept is a plastics value map that aims to converge the satisfaction of essential needs with the usefulness of plastics under the limitations of a biophysically constrained future economy. The second concept is an orthopedics library data system concept that would allow reusing of fit-for-purpose used products and to inform the refurbishment of used products. In addition to an explanation of the design of the two concepts, the article presents reflections of co-design stakeholders on the usefulness and usability of the concepts. The article provides a real-world application of the co-design processes in transition engineering and the reflection by the company on the value of the results. The results indicate that the co-designed concepts could enable the company to address its sustainability aspirations and potentially resolve the dissonance of sustainability and business viability. Full article

An integrated structural optimization strategy was produced in this study for direct-drive electrical generator structures of offshore wind turbines, implementing a design for an additive manufacturing approach, and using generative design techniques. Direct-drive configurations are widely implemented on offshore wind energy systems due to their high efficiency, reliability, and structural simplicity. However, the greatest challenge associated with these types of machines is the structural optimization of the electrical generator due to the demanding operating conditions. An integrated structural optimization strategy was developed to assess a 100-kW permanent magnet direct-drive generator structure. Generated topologies were evaluated by performing finite element analyses and a metal additive manufacturing process simulation. This novel approach assembles a vast amount of structural information to produce a fit-for-purpose, adaptative, optimization strategy, combining data from static structural analyses, modal analyses, and manufacturing analyses to automatically generate an efficient model through a generative iterative process. The results obtained in this study demonstrate the importance of developing an integrated structural optimization strategy at an early phase of a large-scale project. By considering the typical working condition loads and the machine’s dynamic behavior through the structure’s natural frequencies during the optimization process coupled with a design for an additive manufacturing approach, the operational range of the wind turbine was maximized, the overall costs were reduced, and production times were significantly diminished. Integrating the constraints associated with the additive manufacturing process into the design stage produced high-efficiency results with over 23% in weight reduction when compared with conventional structural optimization techniques. Full article

Spatial information about plant health and productivity are essential when assessing the progress towards Sustainable Development Goals such as life on land and zero hunger. Plant health and productivity are strongly linked to a plant’s phenological progress. Remote sensing, and since the launch of Sentinel-1 (S1), specifically, radar-based frameworks have been studied for the purpose of monitoring phenological development. This study produces insights into how crop phenology shapes S1 signatures of PolSAR features and InSAR coherence of wheat, canola, sugar beet. and potato across multiple years and orbits. Hereby, differently smoothed time series and a base line of growing degree days are stacked to estimate the patterns of occurrence of extreme values and break points. These patterns are then linked to in situ observations of phenological developments. The comparison of patterns across multiple orbits and years reveals that a single optimized fit hampers the tracking capacities of an entire season monitoring framework, as does the sole reliance on extreme values. VV and VH backscatter intensities outperform all other features, but certain combinations of phenological stage and crop type are better covered by a complementary set of PolSAR features and coherence. With regard to PolSAR features, alpha and entropy can be replaced by the cross-polarization ratio for tracking certain stages. Moreover, a range of moderate incidence angles is better suited for monitoring crop phenology. Also, wheat and canola are favored by a late afternoon overpass. In sum, this study provides insights into phenological developments at the landscape level that can be of further use when investigating spatial and temporal variations within the landscape. Full article

The National Oceanic and Atmospheric Administration’s (NOAA) Center for Satellite Applications and Research (STAR) facilitates and enables societal benefits from satellite oceanography, supporting operational and experimental satellite missions, developing new and improved ocean observing capabilities, engaging users by developing and distributing fit-for-purpose data, applications, tools, and services, and curating, translating, and integrating diverse data products into information that supports informed decision making. STAR research, development, and application efforts span from passive visible, infrared, and microwave observations to active altimetry, scatterometry, and synthetic aperture radar (SAR) observations. These efforts directly support NOAA’s operational geostationary (GEO) and low Earth orbit (LEO) missions with calibration/validation and retrieval algorithm development, implementation, maintenance, and anomaly resolution, as well as leverage the broader international constellation of environmental satellites for NOAA’s benefit. STAR’s satellite data products and services enable research, assessments, applications, and, ultimately, decision making for understanding, predicting, managing, and protecting ocean and coastal resources, as well as assessing impacts of change on the environment, ecosystems, and climate. STAR leads the NOAA Coral Reef Watch and CoastWatch/OceanWatch/PolarWatch Programs, helping people access and utilize global and regional satellite data for ocean, coastal, and ecosystem applications. Full article

Coffee production faces major sustainability issues and consumers increasingly look to choose certified coffee as awareness grows. While consumers’ understanding of sustainability issues is limited, independent voluntary certification schemes such as Fairtrade, Rainforest Alliance, and certified organic—three high-profile schemes—can play a role in future-proofing coffee production through standard-setting. These schemes can also inform consumers about sustainability issues from economic, environmental, and social perspectives, thus driving up demand for sustainably grown coffee, and supporting an enabling environment for farmers and coffee-producing countries to improve the status quo. Sustainably grown coffee ensures that farmers sustain production while protecting the environment and the income that farmers rely on to maintain their livelihood. Based on a thematic analysis and synthesis of previous studies, this paper examines the social, economic, and environmental effects of voluntary certification schemes for coffee production. It evaluates the current state of coffee production and explores how certification schemes can be effective in encouraging more sustainable practices among producers. Three major voluntary certification schemes are evaluated to identify the impacts on producers, including key barriers and enablers to comply with sustainability standards and to determine how fit-for-purpose certification schemes are in assuring future sustainable coffee production. Full article

In the semiconductor manufacturing industry, achieving high yields constitutes one of the pivotal factors for sustaining market competitiveness. When confronting the substantial volume of high-dimensional, non-linear, and imbalanced data generated during semiconductor manufacturing processes, it becomes imperative to transcend traditional approaches and incorporate machine learning methodologies. By employing non-linear classification models, one can achieve more real-time anomaly detection, subsequently facilitating a deeper analysis of the fundamental causes behind anomalies. Given the considerable dimensionality of production line data in semiconductor manufacturing, there arises a necessity for dimensionality reduction to mitigate noise and reduce computational costs within the data. Feature selection stands out as one of the primary methodologies for achieving data dimensionality reduction. Utilizing wrapper-based heuristics algorithms, although characterized by high time complexity, often yields favorable performance in specific cases. If further combined into hybrid methodologies, they can concurrently satisfy data quality and computational cost considerations. Accordingly, this study proposes a two-stage feature selection model. Initially, redundant features are eliminated using mutual information to reduce the feature space. Subsequently, a Simplified Swarm Optimization algorithm is employed to design a unique fitness function aimed at selecting the optimal feature subset from candidate features. Finally, support vector machines are utilized as the classification model for validation purposes. For practical cases, it is evident that the feature selection method proposed in this study achieves superior classification accuracy with fewer features in the context of wafer anomaly classification problems. Furthermore, its performance on public datasets further substantiates the effectiveness and generalization capability of the proposed approach. Full article

Biomass productivity is of great significance for the evaluation of forest quality, which is important for the improvement of forest management. We propose the computational methods of biomass potential productivity (BPP) and biomass realistic productivity (BRP), both of which provide reliable practical guides for predicting forest growth under multi-aged, multi-species, and multi-layered canopy conditions. We used 2222 national forest inventory plots that were measured in four consecutive periods in the Jilin Province for this purpose. We analyzed and verified the computational methods of BPP based on the BRP and evaluated its practical significance. The results showed that growth models of the stand height, stand basal area, and stand biomass of four forest types (pure larch forest, larch broadleaf mixed forest, Mongolian oak pure forest, and Mongolian oak broadleaf mixed forest) fit adequately, BPP was greater than BRP, and this difference decreased with an increasing stand age, suggesting that the potential productivity of the middle-aged and young forest was higher than that of the mature forest, although the difference is minimal. In addition, the realistic productivity of stands with better site quality was close to the potential productivity, which is consistent with the biological significance of the potential productivity of the biomass. The degree of difference between the potential productivity of the biomass and the realistic productivity of biomass also decreases with the decline in site quality, and it can be termed as the potentially improved stand biomass. The BPP model was able to perform well in both the pure and mixed forests. The BRP not only verifies the rationality of the BPP but can be also used to quantify the forest site quality, which is helpful for evaluating forest growth and informed decision making in forestry. Full article

Recent EU circular economy, bioeconomy policies and the New Green Deal promote the recycling of organic wastes into soil improvers and fertilisers, thereby reducing the use of mineral fertilisers. This has renewed interest in the use of compost and digestate as fertilisers. At the same time, the Russian invasion of Ukraine has strengthened the demand for sustainable domestic fertilisers to guarantee the security of supply. It is now more important than ever that quality standards in Ireland are fit for the purpose of aiding the sustainable local production of fertilisers. Quality standards for compost and digestate ensure and protect the environment. This study collated the results of the analysis of Irish compost and digestate samples and made comparisons of the Irish data to databases, reports and standards from other countries, including the EU Fertiliser Products Regulation 2019/1009. This paper, therefore, provides comprehensive information on heavy metal, stability and phytotoxicity standards from a number of European and other countries. In addition, it includes actual data on these parameters from Ireland and a few European countries. From this collation and comparison process, we propose to update the heavy metals and stability limits in the Irish compost standard (IS 441) and heavy metals and stability limits in a new digestate standard (whole, liquid and fibre). Our methodology and collated data can be used as templates for countries, especially in Europe, which have not developed their own standards. Having an updated compost quality standard supports the development of a circular economy while still respecting the precautionary principle of avoiding pollution when compost and digestate are used on the soil. Full article

Offshore wind energy installations in coastal areas have grown massively over the last decade. This development comes with a large number of technological, environmental, economic, and scientific challenges, which need to be addressed to make the use of offshore wind energy sustainable. One important component in these optimization activities is suitable information from observations and numerical models. The purpose of this study is to analyze the gaps that exist in the present monitoring systems and their respective integration with models. This paper is the second part of two manuscripts and uses results from the first part about the requirements for different application fields. The present solutions to provide measurements for the required information products are described for several European countries with growing offshore wind operations. The gaps are then identified and discussed in different contexts, like technology evolution, trans-European monitoring and modeling initiatives, legal aspects, and cooperation between industry and science. The monitoring gaps are further quantified in terms of missing observed quantities, spatial coverage, accuracy, and continuity. Strategies to fill the gaps are discussed, and respective recommendations are provided. The study shows that there are significant information deficiencies that need to be addressed to ensure the economical and environmentally friendly growth of the offshore wind farm sector. It was also found that many of these gaps are related to insufficient information about connectivities, e.g., concerning the interactions of wind farms from different countries or the coupling between physical and biological processes. Full article

Purpose: Gene therapy actually seems to have promising results in the treatment of Leber Congenital Amaurosis and some different inherited retinal diseases (IRDs); the primary goal of this strategy is to change gene defects with a wild-type gene without defects in a DNA sequence to achieve partial recovery of the photoreceptor function and, consequently, partially restore lost retinal functions. This approach led to the introduction of a new drug (voretigene neparvovec-rzyl) for replacement of the RPE65 gene in patients affected by Leber Congenital Amaurosis (LCA); however, the treatment results are inconstant and with variable long-lasting effects due to a lack of correctly evaluating the anatomical and functional conditions of residual photoreceptors. These variabilities may also be related to host immunoreactive reactions towards the Adenovirus-associated vector. A broad spectrum of retinal dystrophies frequently generates doubt as to whether the disease or the patient is a good candidate for a successful gene treatment, because, very often, different diseases share similar genetic characteristics, causing an inconstant genotype/phenotype correlation between clinical characteristics also within the same family. For example, mutations on the RPE65 gene cause Leber Congenital Amaurosis (LCA) but also some forms of Retinitis Pigmentosa (RP), Bardet Biedl Syndrome (BBS), Congenital Stationary Night Blindness (CSNB) and Usher syndrome (USH), with a very wide spectrum of clinical manifestations. These confusing elements are due to the different pathways in which the product protein (retinoid isomer-hydrolase) is involved and, consequently, the overlapping metabolism in retinal function. Considering this point and the cost of the drug (over USD one hundred thousand), it would be mandatory to follow guidelines or algorithms to assess the best-fitting disease and candidate patients to maximize the output. Unfortunately, at the moment, there are no suggestions regarding who to treat with gene therapy. Moreover, gene therapy might be helpful in other forms of inherited retinal dystrophies, with more frequent incidence of the disease and better functional conditions (actually, gene therapy is proposed only for patients with poor vision, considering possible side effects due to the treatment procedures), in which this approach leads to better function and, hopefully, visual restoration. But, in this view, who might be a disease candidate or patient to undergo gene therapy, in relationship to the onset of clinical trials for several different forms of IRD? Further, what is the gold standard for tests able to correctly select the patient? Our work aims to evaluate clinical considerations on instrumental morphofunctional tests to assess candidate subjects for treatment and correlate them with clinical and genetic defect analysis that, often, is not correspondent. We try to define which parameters are an essential and indispensable part of the clinical rationale to select patients with IRDs for gene therapy. This review will describe a series of models used to characterize retinal morphology and function from tests, such as optical coherence tomography (OCT) and electrophysiological evaluation (ERG), and its evaluation as a primary outcome in clinical trials. A secondary aim is to propose an ancillary clinical classification of IRDs and their accessibility based on gene therapy’s current state of the art. Material and Methods: OCT, ERG, and visual field examinations were performed in different forms of IRDs, classified based on clinical and retinal conditions; compared to the gene defect classification, we utilized a diagnostic algorithm for the clinical classification based on morphofunctional information of the retina of patients, which could significantly improve diagnostic accuracy and, consequently, help the ophthalmologist to make a correct diagnosis to achieve optimal clinical results. These considerations are very helpful in selecting IRD patients who might respond to gene therapy with possible therapeutic success and filter out those in which treatment has a lower chance or no chance of positive results due to bad retinal conditions, avoiding time-consuming patient management with unsatisfactory results. Full article

The rapid expansion of offshore wind farms (OWFs) in European seas is accompanied by many challenges, including efficient and safe operation and maintenance, environmental protection, and biodiversity conservation. Effective decision-making for industry and environmental agencies relies on timely, multi-disciplinary marine data to assess the current state and predict the future state of the marine system. Due to high connectivity in space (land–estuarial–coastal sea), socioeconomic (multi-sectoral and cross-board), and environmental and ecological processes in sea areas containing OWFs, marine observations should be fit for purpose in relation to multiple OWF applications. This study represents an effort to map the major observation requirements (Part-I), identify observation gaps, and recommend solutions to fill those gaps (Part-II) in order to address multi-dimension challenges for the OWF industry. In Part-I, six targeted areas are selected, including OWF operation and maintenance, protection of submarine cables, wake and lee effects, transport and security, contamination, and ecological impact assessments. For each application area, key information products are identified, and integrated modeling–monitoring solutions for generating the information products are proposed based on current state-of-the-art methods. The observation requirements for these solutions, in terms of variables and spatial and temporal sampling needs, are therefore identified. Full article

The study uses the Theory of Planned Behavior and the Influence of Information System Success to understand how users respond to the technology used for teaching and learning. The study intends to look at the relationship between the Information System Success model and Theory of Planned Behavior variables on utilizing the Zoom application by elementary education teachers, as well as how teachers’ satisfaction and intention to use technology affect the usage of technology. The primary approach for gathering data involved distributing the Influence of Information System Success model and Theory of Planned Behavior theories questionnaire survey to teachers in elementary education. A total of 219 elementary school teachers in Saudi Arabia who prepared for their online classes participated in the survey for this research. According to the study’s findings, behavioral intentions for using Zoom for educational purposes and user satisfaction have a strong positive association. Additionally, there is a strong association between other variables and users’ intention to use and satisfaction with the product (i.e., perceived technology fit, educational system quality, information quality, attitude towards using Zoom in elementary education, perceived behavioral control, and subjective norm). The findings also show that data points are favorably connected with the teachers’ satisfaction and intention for using the Zoom factors of the Information System Success model and Theory of Planned Behavior theories, despite the fact that there is no connection between both the attitudes towards utilizing Zoom and the behavioral intention to use Zoom for teaching elementary education students. Full article

Breast-Implant-Associated Anaplastic Large-Cell Lymphoma (BIA-ALCL) is a rare low-incidence type of T-cell non-Hodgkin lymphoma, arising in the capsule around breast implants, and predominantly associated with the use of macro-textured breast implants. The purpose of this study was to use an evidence-based approach to systematically identify clinical studies comparing smooth and textured breast implants in women with regard to the risk of developing BIA-ALCL. Methods: A literature search in PubMed in April 2023 and the article reference list of the French National Agency of Medicine and Health Products decision from 2019 were screened for applicable studies. Only clinical studies where the Jones surface classification could be applied (required information: breast implant manufacturer) for comparison of smooth and textured breast implants were considered. Results: From a total of 224 studies, no articles were included due to the lack of fit to the strict inclusion criteria. Conclusions: Based on the scanned and included literature, implant surface types in relation to the incidence of BIA-ALCL were not evaluated in clinical studies and data from evidence-based clinical sources plays a minor to no role in this context. An international database that combines breast implant-related data from (national, opt-out) medical device registries is, therefore, the best available option to obtain relevant long-term breast implant surveillance data on BIA-ALCL. Full article

Social networking influencers are those who use images, videos, and other updates on social media platforms to affect consumers’ impressions of a company or product. The purpose of this study is to assess the present status of social networking sites and the online purchase intentions of consumers. This research paper is an attempt to identify the effect of various attributes of social networking that influence credibility and brand image, eventually leading to the purchase intention of consumers in Delhi NCR (National Capital Region), India. The data were collected using Google Forms via an online questionnaire with a sample size of 262 respondents. A convenient sampling technique was used; structure equation modeling (SEM), convergent and discriminant validity, and model fitness were achieved through Smart PLS 3. This study’s findings reveal that expertise, information quality, and trustworthiness have significant positive effects on credibility and brand image, as well as a significant positive indirect effect on online purchase intention. Other factors, such as entertainment, attractiveness, and likability, have no significant effect on credibility and brand image. The credibility of social networking and brand image mediate the positive relationship between information quality, expertise, trustworthiness, and consumer online purchase intention. On the other hand, the credibility of social networking and brand image mediate the lack of a positive relationship between likability, attractiveness, entertainment, and consumer online purchase intention. Full article

In the response surface methodology (RSM), the designed experiment helps create interfactor orthogonality and interpretable response models for the purpose of process and design optimization. However, along with the development of data-recording technology, observational data have emerged as an alternative to experimental data, and they contain potential information on design/process parameters (as factors) and product characteristics that are useful for RSM analysis. Recent studies in various fields have proposed modifications to the standard RSM procedures to adopt observational data and attain considerable results despite some limitations. This paper aims to explore various methods to incorporate observational data in the RSM through a systematic literature review. More than 400 papers were retrieved from the Scopus database, and 83 were selected and carefully reviewed. To adopt observational data, modifications to the procedures of RSM analysis include the design of the experiment (DoE), response modeling, and design/process optimization. The proposed approaches were then mapped to capture the sequence of the modified RSM analysis. The findings highlight the novelty of observational-data-based RSM (RSM-OD) for generating reproducible results involving the discussion of the treatments for observational data as an alternative to the DoE, the refinement of the RSM model to fit the data, and the adaptation of the optimization technique. Future potential research, such as the improvement of factor orthogonality and RSM model modifications, is also discussed. Full article