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This report provides an overview of the approaches and methods of measuring the impact of human activities on biodiversity. Measuring these impact still has numerous challenges. First, biodiversity is hard to capture with one single indicator, because it has many dimensions. Second, monitoring biodiversity is often expensive and remains a challenge. Third, the causal relationships between human activities and biodiversity are often unknown. Thus, the result of current impact models for biodiversity are based on many assumptions. Fourth, there is no consensus on how biodiversity should be included in the decision-making of companies and nations. There are experiments with biodiversity accounting at company and nation level but the methods need to be developed further. This report concludes with a number of recommendations for future research and policy., Dit rapport geeft een overzicht van de aanpakken en methodes waarmee je de impact van menselijk handelen op de biodiversiteit kunt meten. Daarbij zijn nog veel uitdagingen te overwinnen. Ten eerste is biodiversiteit een begrip dat moeilijk te vangen is in één indicator, omdat het een begrip met meerdere dimensies is. Ten tweede is het monitoren van biodiversiteit vaak kostbaar en een uitdaging. Ten derde zijn de causale relaties tussen menselijk handelen en biodiversiteit ook onbekend. Dat heeft invloed op de resultaten van de impactmodellen voor biodiversiteit. Ten vierde is er geen consensus over hoe (de waarde) van biodiversiteit meegenomen zou moeten worden in de besluitvorming van bedrijven of overheden. Met biodiversiteitsaccounting wordt geëxperimenteerd, maar de methodes moeten nog verder ontwikkeld worden om er een gangbare methode van te maken. Dit rapport besluit met een aantal aanbevelingen voor toekomstig onderzoek en beleid.

The concept of a Positive Energy District (PED) has become a vital component of the efforts to accelerate the transition to zero carbon emissions and climate-neutral living environments. Research is shifting its focus from energy-efficient single buildings to districts, where the aim is to achieve a positive energy balance across a given time period. Various innovation projects, programs, and activities have produced abundant insights into how to implement and operate PEDs. However, there is still no agreed way of determining what constitutes a PED for the purpose of identifying and evaluating its various elements. This paper thus sets out to create a process for characterizing PEDs. First, nineteen different elements of a PED were identified. Then, two AI techniques, machine learning (ML) and natural language processing (NLP), were introduced and examined to determine their potential for modeling, extracting, and mapping the elements of a PED. Lastly, state-of-the-art research papers were reviewed to identify any contribution they can make to the determination of the effectiveness of the ML and NLP models. The results suggest that both ML and NLP possess significant potential for modeling most of the identified elements in various areas, such as optimization, control, design, and stakeholder mapping. This potential is realized through the utilization of vast amounts of data, enabling these models to generate accurate and useful insights for PED planning and implementation. Several practical strategies have been identified to enhance the characterization of PEDs. These include a clear definition and quantification of the elements, the utilization of urban-scale energy modeling techniques, and the development of user-friendly interfaces capable of presenting model insights in an accessible manner. Thus, developing a holistic approach that integrates existing and novel techniques for PED characterization is essential to achieve sustainable and resilient urban environm

In 2018, EU launched the programme “Positive energy districts and neighbourhoods for sustainable urban development” with an aim to support the planning, deployment and replication of 100 Positive energy districts (PEDs) by 2025. This is an ambitious target considering the various challenges on implementing PEDs. This paper, based on literature review, provides an overview on the challenges and possibilities on the three main components of PEDs; energy production, energy efficiency and energy flexibility.

The Dutch Government targets to reduce CO2 emissions by 49% in 2030, and to virtually net zero CO2 emissions by 2050, in order to combat climate change. The building and construction sector can contribute significantly to this goal by applying bio-based and circular building products. By using sustainably sourced bio-based materials, CO2 which has been taken up recently from the atmosphere will be stored as biogenic carbon1 in materials for as long as these are incorporated in a building and eventually in subsequent recycled products. This storage of biogenic carbon actually means a temporary yet long term negative greenhouse gas (GHG) emission, thus buying time to transform our society into a virtually GHG emission neutral economy and creating space to reach climate goals. However, the value of long term biogenic carbon storage is not included in standard LCA standards and guidelines, nor credited when determining the environmental impact of buildings (in Dutch ‘Milieu Prestatie Gebouwen’, MPG).2 The objective of this study is to review scientific approaches for quantifying the effect of biogenic carbon storage in building materials on global warming potential (GWP), which is the LCA impact parameter for climate change, and to draft a generally applicable methodology to valorise the GWP benefit of materials in durable building applications, in-line with the Determination Method (see footnote). The GWP benefit arises from the long term reduction of CO2 concentration in the atmosphere, which is a result of (most recent) sequestration of CO2 from the atmosphere as biogenic carbon in plant materials and subsequent long term application of this material in e.g. buildings. Therefore, all long term biogenic carbon storage presents a GWP benefit. The different scientific approaches for determining the effect of biogenic carbon storage on GWP described in literature exhibit only small differences for the GWP benefit at given storage times. The ‘dynamic LCA method’ is the mo

Study Design: Methodological, observational clinical study.Purpose: This study aimed to develop a virtual screening test to detect scoliosis risk initially by parents without the need for medical visit during the coronavirus disease 2019 pandemic.Overview of Literature. The scoliosis screening program has been implemented to early detect scoliosis. Unfortunately, access to health professionals was limited during the pandemic. However, during this tirpe, interest in telemedicine has increased remarkably. Recently, mobile applications related to postural analysis were developed, but one permits evaluation by parents. Methods: Researchers developed the Scoliosis Tele-Screening Test (STS-Test which included drawing-based images of body asym metries, to assess the stoliosis-associated risk factors. The STS-Test was shared on social networks, allowing the parents to evaluate their children. After test completion, the risk score was generated automatically, and children with medium and high risks were then advised for medical consultation for further evaluation. The test accuracy and consistency between the clinician and parents were also analyzed.Results: Of the 865 tested children, 358 (41.4%) consulted clinicians to confirm their STS Test results. Scoliosis was then confirmed in 91 children (25.4%) The parents were able to detect asymmetry in 50% of the lumbar/thoracolumbar curvatures and 82% of the thoracic curvatures In addition, the forward bend test revealed favorable agreement between parents and clinicians (-0.809, p<1.0006). Internal consistency of the esthetic deformities domain in the STS-Test was also excellent (a-0.901). This tool was 94.97% accurate, 83.51% sensitive, and 98.87% specific. Conclusions: The STS lest is a new parent-friendly, virtual cost-effective reshit-oriented, and reliable tool for scoliosis screening. It allows parents to actively participate in the early, NA

Purpose: This paper studies a 3-dimensional pallet loading problem considering interlock stacking pattern, box dimensions, humidity, and storage time, where overlapping and overhanging are not allowed. Despite the importance of this problem in the literature, our work provides the first method that considers the environmental conditions such as 1) storage time and 2) humidity, and their tremendous impacts on the strength of the boxes, as has been observed widely in the DHL supply chain. Design/methodology/approach: This paper proposes a two-phase heuristic algorithm to solve a 3-dimensional pallet loading problem under real conditions (relative humidity, and storage time) considering interlock stacking patterns, where overlapping and overhanging are not allowed. In phase 1, the horizontal layer configuration is determined by block techniques. Three types of horizontal layers are created based on box dimensions perpendicular to the base. In phase 2, a novel mathematical model is propounded to improve the pallet volume utilization, and stability considering the pallet's maximum allowable height and weight, and the dynamic compression strength of boxes. The dynamic compression strength of boxes is calculated by the modified McKee formula. Two performance measures, pallet volume utilization and stability (load height), are utilized to evaluate the performance of the proposed heuristic algorithm in real-world instances (DHL Supply Chain). Findings: The results illustrated that the dynamic compression strength of boxes decreases as the relative humidity and storage time increase. The load height changes dynamically along with box dimensions, box alignment, direction, relative humidity, and storage time. Increasing relative humidity and storage time and applying an interlock stacking pattern reduce the pallet utilization, however, enhance the pallet stability. Finally, the proposed heuristic algorithm's efficacy increases as the identical boxes dimensions' heterogeneity in, Peer Reviewed

This study examines the commitments of an alternative teacher education program in linking theory and practice, one of the most prominent problems of the field. This qualitative phenomenological study drew from semi-structured interviews with seven faculty members and associate instructors, electronic surveys with seven program students, participant observation and field notes in seminar sessions, one program faculty meeting, and one community meeting, and curriculum materials. The findings suggest that the design of the program and the roles and (inter)actions of the stakeholders within the program created a dialectical interplay. Linked with this interplay, Teachers’ Society provided a setting for collaborative learning during which theory is extracted from experience.

The transition to a bioeconomy requires vast amounts of feedstock to serve a wide range of functionalities in a broad panel of applications in sectors as: construction, textile, paper, automotive, horticulture, and livestock farming. Herbaceous crops and residue streams like flax, hemp, miscanthus, cereal straw, reed and verge grass offer a wide range of characteristics which can serve multiple applications. This report analyses and explores the potential of production and valorisation of herbaceous feedstock in the Netherlands and eventually at regional level. An analysis is made of current production and applications of herbaceous crops and residue streams. Present supply and demand were matched by an evaluation of imports and exports. Circular economy policies, agendas and ambitions were reviewed for relevant topics: climate change, circular bioeconomy, regional development; and at 3 levels: EU, Netherlands and province of Gelderland. Also, important considerations regarding circularity and sustainability aspects of biobased value chains were discussed, with focus on construction and textiles sector. Further, potential future use in products, indication of demanded product volumes for most promising applications, and production of herbaceous feedstock in the Netherlands in 2050 were studied. An exercise to match estimated demand and required production area was performed, taking into consideration typical scale of conversion technologies related to product demand. Subsequently a SWOT analysis for use of each herbaceous feedstock for regional conversion into bio-based applications is carried out to identify the main points of attention and needs such as knowledge, infrastructure, collaborations, regulations and policies, technology for the valorisation of different feedstocks for different applications. Finally, recommendations are provided to next possible actions to materialise the transition to regional supply of herbaceous biomass for making bio-based products

Klimaatverandering is een grote uitdaging geworden op internationaal, Europees, nationaal en regionaal niveau. De gevolgen van klimaatverandering moeten worden beperkt door het voorkomen en verminderen van de uitstoot van broeikasgassen (BKG) in de atmosfeer. Er zijn verschillende beleids- en boekhoudkundige kaders ontwikkeld om dit te bewerkstelligen. Deze kaders stellen specifieke doelstellingen voor reductie van emissies van broeikasgassen of verhoogde vastlegging van CO2 vast en bieden een gestructureerde aanpak om dit probleem op te lossen. Dit rapport heeft tot doel om beleidsmedewerkers van het Nederlandse ministerie van Landbouw, Natuur en Voedselkwaliteit (LNV) te informeren over hoe een verhoging van het aanbod aan biomassa uit bosbouw en landbouw voor de productie van chemische stoffen en materialen binnen deze kaders worden meegenomen en meegewogen en kunnen worden ingezet voor het beperken van klimaatverandering een verhoging van het aanbod aan biomassa uit bosbouw en landbouw omvatten voor de productie van chemische stoffen en materialen die kunnen bijdragen aan vermindering van de uitstoot van broeikasgassen. Dit desktoponderzoek volgt een 'systeemperspectiefbenadering' om de rol die biobased materialen1 kunnen spelen bij het verminderen van de uitstoot van broeikasgassen te bestuderen. Deze benadering biedt inzicht in de verbanden tussen biobased producten, nationale broeikasgasinventarissen en wereldwijde afspraken. Begrip van deze verbanden en kennis over welke boekhoudmethoden voor broeikasgasemissies en -verwijderingen worden toegepast is noodzakelijk voor het identificeren van mogelijke nadelen en voor het ontwikkelen van toekomstige beleidsrichtlijnen. Na deze review concluderen we dat het belangrijk is om bekend te zijn met en de waarde te erkennen in de huidige bestaande boekhoudmethoden. De bestaande kaders missen echter nog belangrijke kenmerken die robuustere boekhoudmethoden voor koolstofvastlegging en -opslag in biobased materialen mogel

The systematic literature review of circular economy indicators at the micro level revealed that they are still at an early stage of development and so far, the specific considerations relevant for biobased systems is not sufficiently incorporated. Existing indicators provide good coverage of aspects related to the quantity of resource flows i.e., resource use efficiency and degree of recirculation. Yet, most indicators fail to include renewable resource share, cascading use, and organic recycling that are important characteristics of biobased systems. These characteristics were taken into consideration in a few recent papers focused on circularity measurement of biobased products. Still there are gaps especially related to assessing the functional use of resources and preservation of quality of recycled materials. This consideration is especially important to optimize cascading use of biomass. Besides quality, another aspect that deserves further attention is closing of the nutrient cycles. Further research is needed in the development of indicators addressing these gaps to extract the maximum potential of biological resources for circular economy. This will yield a monitoring framework based on a comprehensive set of circular economy indicators which can be used by businesses and policy makers to formulate targets for transition to a circular bioeconomy.

Early design decisions influence the performance of a building significantly. Yet, computational support for performance assessment during early design is very limited. This research proposes an analysis pipeline for the accurate and comprehensive assessment of building performance by integrating simulation-based analysis tools that perform daylighting, computational fluid dynamics, energy, and contaminant transport simulations, as well as wind tunnel testing that performs velocity and pressure measurements to generate wind pressure coefficients. The pipeline is implemented in three different ways: hybrid, model-based, and empirical workflows. The hybrid workflow combines computational fluid dynamics simulations and wind tunnel testing, while the model-based and empirical workflows utilize computational fluid dynamics simulations and wind tunnel testing, respectively. In the pipeline, computational fluid dynamics is used early on to evaluate a high number of alternatives, leading to the selection of a limited number of good-performing options. Following this, wind tunnel testing is used to “correct” the initial wind pressure coefficient results for increased accuracy. Therefore, a hybrid approach operating with high accuracy that can effectively explore the design search space is needed. The pipeline is tested on a hypothetical office building with different shading device configurations. The coupling of computational and physical testing methods in a hybrid workflow significantly enhanced the accuracy of airflow-related data, which is underestimated by 15.4% using the model-based workflow. Moreover, the hybrid workflow managed the complexity of the design search space by the assessment and elimination of different design alternatives by the stepwise simulation workflow. The inclusion of shading devices also improved the accuracy of airflow-related data. If the shading devices had not been modeled for the simulations and had not been tested, the results would hav

This paper proposes a new variable stiffness soft gripper that enables high-performance grasping tasks in industrial applications. The design of the proposed monolithic soft gripper includes a middle bellow and two side bellows (i.e., fingers). The positions of the fingers are regulated by adjusting the negative pressure in the middle bellow actuator via an on-off controller. The stiffness of the soft gripper is modulated by controlling the positive pressure in the fingers through the use of a proportional air-pressure regulator. It is experimentally shown that the proposed soft gripper can modulate its stiffness by 125% within 250ms. It is also shown that the variable stiffness soft gripper can help improve the safety and performance of grasping tasks in industrial applications., Comment: IEEE International Conference On Mechatronics - Loughborough, UK

Climate change has become an important challenge at International, European, National and Regional level. Mitigation of climate change by preventing and reducing the emission of greenhouse gases (GHG) into the atmosphere is needed to make the impacts of climate change less severe. To ensure this, different mitigation frameworks have been created. These frameworks set specific GHG reduction goals and provide a more structured approach to solve this problem. This report aims to provide information to the Dutch Ministry of Agriculture, Nature and Food Quality (LNV) on and how some climate change mitigation frameworks are including the increase forestry and agricultural biomass supply to produce chemicals and materials that can contribute to the reduction of GHG emission. This desktop research follows a ‘systems perspective approach’ to study the role of biobased materials’ 1 in the reduction of GHG emission. This approach allows the understanding of interactions between biobased products, national inventories and global agreements. Understanding these links and having knowledge on which GHG gases accounting methods are being applied is necessary for the identification of possible drawbacks and for the development of future policy guidelines. After this review, we conclude that it is important to be familiar with and recognize the value in current existing accounting methodologies. However, existing frameworks are still lacking important features which could enable more robust account methodologies for carbon sequestration and storage in biobased materials. At this moment in time, the European Commission is working on proposals like the ‘Carbon Farming framework’ and ‘carbon removals certification framework’ (December 2022) and introducing a ‘carbon storage products pool’, these proposals could play and important role on establishing clear accounting rules that connect the biomass production to biobased materials and its contribution to support National Policies towards

We have conducted a study to review and synthesize the current state of data availability for cradle-to-grave life-cycle emissions from major building technologies and electricity generation and storage technologies as specific to California as could be found. Results from 280 building technologies (120 unique) were organized across 9 categories and 27 subcategories. Many of the technologies in the list are common building materials, appliances, and process equipment used in the construction and operation of agricultural, residential, commercial, and industrial buildings. Target electricity generation technologies covered the GHG emissions from natural gas, solar, wind, geothermal, biomass and storage technologies for the California context. The search for relevant environmental impact data was in the form of Environmental Product Declarations (EPD) (if available), peer-reviewed journal articles, and publicly available reports from government and industry for each technology. In general, the “Building Materials” category in the building technologies area and “Wind Turbines” in the electricity generation and storage area have the most current and relevant data for California. However, we have identified several data gaps in our survey of the remaining categories. Due to lack of relevant data for California in building systems, there is an urgent need for policy makers and industry stakeholders to replicate policies such as AB 2446 to expand the coverage of availability of EPDs for products. Similarly, to achieve the SB 350 (Clean Energy and Pollution Reduction Act) goals and to support the state’s efforts to reduce GHG emissions by 80% below 1990 levels by the year 2050, we need to account for embodied emissions together with the other important life-cycle stages of renewable energy sources.

Infectious aerosol dispersion poses significant infection risks (i.e., COVID-19) in classrooms due to dense and long occupancy. Natural ventilation is an effective strategy to reduce airborne infection transmission. The building-related parameters, particularly openings, determine the natural ventilation effectiveness in reducing contaminant dispersion, necessitating an inquiry due to complex dispersion and airflow patterns. This paper investigates the correlation between window height, natural ventilation, and COVID-19 dispersion. A simulation pipeline involving a parametric 3D design environment, computational fluid dynamics (CFD), and energy simulations is developed and implemented on nine design scenarios representing different inlet-outlet heights of a free-running (no heating, cooling or mechanical ventilation) classroom. The inlet height and the inlet-outlet height difference have a considerable impact on indoor infection risk confirming that stack ventilation and the Bernoulli effect decrease indoor contaminant concentration. Proximity to openings does not ensure lower contamination levels. Proximity to the contaminant does not result in higher contamination levels.

Infectious aerosol dispersion poses significant infection risks (i.e., COVID-19) in classrooms due to dense and long occupancy. Natural ventilation is an effective strategy to reduce airborne infection transmission. The building-related parameters, particularly openings, determine the natural ventilation effectiveness in reducing contaminant dispersion, necessitating an inquiry due to complex dispersion and airflow patterns. This paper investigates the correlation between window height, natural ventilation, and COVID-19 dispersion. A simulation pipeline involving a parametric 3D design environment, computational fluid dynamics (CFD), and energy simulations is developed and implemented on nine design scenarios representing different inlet-outlet heights of a free-running (no heating, cooling or mechanical ventilation) classroom. The inlet height and the inlet-outlet height difference have a considerable impact on indoor infection risk confirming that stack ventilation and the Bernoulli effect decrease indoor contaminant concentration. Proximity to openings does not ensure lower contamination levels. Proximity to the contaminant does not result in higher contamination levels.

Protein alternatives are crucial for a sustainable food production in future. Cultured meat is presented as a good alternative for consumers who want to be more sustainable but do not wish to change their diet. To validate this sustainability claim, this report evaluates four LCA studies on cultured meat. When comparing overall environmental impact of cultured meat with conventional meat products and other meat substitutes, cultured meat was seen to perform significantly better than beef, favourable to pork, similar to chicken, and worse than plant-based alternatives considering current global average production impacts. It is important to realize that currently no commercial-scale cultured meat facility is operational. All LCA studies modelled a future facility, extrapolating scientific and small-scale facilities. Differences in system boundaries lead to high variability of environmental impact results for cultured meat among reviewed studies. The LCA system boundaries mostly include the cultivation-related processes, while product formulation and distribution are not taken into account. An important technical bottleneck that is not addressed are the large volumes of the fermenters and the extended cultivation times, which will need extraordinary sterility measures. The LCA overview shows that cultured meat production is energy intensive and that energy consumption have the highest contribution in the overall impact. Next, growth medium production showed significant contribution to impact, especially the amino acid production and recombinant protein production for growth factors. Sensitivity analysis of model parameters showed that parameter choices on cell density and medium use impacted the results most. Technically, the cultured meat industry is still very much in development. Obvious improvements that are needed are the reduction in energy, development of scaffolds, and lower medium cost, specifically in developing cheaper plant-based growth factors that are no

Lignocellulosic biomass is an underutilised renewable resource. Using this biomass for biobased applications is hampered by a lack of possibilities to efficiently link the biomass to markets which include both energy applications such as heat and electricity production, conversion to transport fuels and chemicals and materials. Siting conversion facilities near abundant biomass has the benefit of availability of low cost biomass, but the locations generally lack security of supply, availability of qualified personnel, and do not benefit from existing infrastructure and possibilities to add value to residues. Furthermore, the scale of conversion systems is limited by local cost of biomass supply. The development of real lignocellulosic commodities can connect biomass to markets and lower the opportunity costs of the commodities. The characteristics of real commodities are defined as follows: a commodity has to be easy to store, have a high (energy) density and be nutrient depleted. The commodity has to be uniform enough to be fungible. This will allow standardization of transport, contracting, insurance, conversion systems and development of functioning markets which includes high tradability and availability of financial instruments. Finally sustainability also has to be standardized. Several candidates as real commodities exist including wood pellets and pyrolysis oil. It is argued that only a few biomass commodities have to be defined that cover all lignocellulosic biomass types (wood, grass, straw, bagasse, processing residues, etc.) and also all applications such as heat, electricity, fuels, chemicals and materials. The standards have to be as wide as possible and avoid frivolous or unnecessary demands. To achieve this all stakeholders in the production chain (biomass producers, machine builders, regulators, insurers, bankers, transport, final users) have to be involved. This will require international collaboration else the potential lignocellulosic biomass wil

To support progress towards the transition to a circular economy, the ability to measure circularity is essential. The consideration of the role biobased products can play in this transition is however still largely lacking in the current development of circularity monitoring approaches. The first step in coming to a suitable monitoring framework for biobased products is to define circular economy principles. In this paper, specific characteristics of biobased products were considered in defining six circular economy principles for biobased products: (1). Reduce reliance on fossil resources, (2). Use resources efficiently, (3). Valorize waste and residues, (4). Regenerate, (5). Recirculate and (6). Extend the high-quality use of biomass. In order to evaluate the circularity performance of biobased products with respect to these principles, what needs to be measured was defined considering both intrinsic circularity and impact of this circularity. The intrinsic indicators provide a measure of success in implementation of these circularity principles, and the latter impacts of circularity, i.e., impact of closing the loops on accumulation of hazardous substances and impact of circularity on sustainability (environmental, economic and social). Yet, to unlock the potential of a sustainable circular bioeconomy, strong accompanying measures are required.

Plastic waste production increasingly causes environmental pollution. However, end-of-life (EoL) research often lacks detail and timeliness and fails to integrate the end-of-life option into a product’s life cycle in a systemic perspective. This study addresses these knowledge gaps, by applying an improved anticipatory consequential life cycle assessment (LCA) approach. Reuse, mechanical and chemical recycling options were compared for (biobased and fossil-based) high-density polyethylene (HDPE) and polyethylene terephthalate (PET) plastic shampoo bottles in the European context using three types of impact categories: climate change, fossil resource scarcity and mineral resources scarcity. The completeness and detail of EoL were increased by modelling the polymer reprocessing within the collection system including all transport distances, while timeliness was improved by implementing the data applicable for the time of implementation of EoL options in the future. The results show that the reuse option has the largest benefits on climate change impact, and on fossil and mineral resource scarcity for both HDPE and PET, for both biobased and fossil plastics. Furthermore, all EoL options cause a net reduction in all climate change, fossil and mineral resource scarcity thanks to the avoided impact of virgin plastic. Finally, the improved LCA approach, utilized in this study, includes plastic production, use and EoL in one assessment, and thus can provide valuable information for adjusting policy and regulations for plastic manufacturers in their production of new virgin plastic polymer, as it requires alignment with its use and EoL options.

Machine Learning-based supervised approaches require highly customized and fine-tuned methodologies to deliver outstanding performance. This paper presents a dataset-driven design and performance evaluation of a machine learning classifier for the network intrusion dataset UNSW-NB15. Analysis of the dataset suggests that it suffers from class representation imbalance and class overlap in the feature space. We employed ensemble methods using Balanced Bagging (BB), eXtreme Gradient Boosting (XGBoost), and Random Forest empowered by Hellinger Distance Decision Tree (RF-HDDT). BB and XGBoost are tuned to handle the imbalanced data, and Random Forest (RF) classifier is supplemented by the Hellinger metric to address the imbalance issue. Two new algorithms are proposed to address the class overlap issue in the dataset. These two algorithms are leveraged to help improve the performance of the testing dataset by modifying the final classification decision made by three base classifiers as part of the ensemble classifier which employs a majority vote combiner. The proposed design is evaluated for both binary and multi-category classification. Comparing the proposed model to those reported on the same dataset in the literature demonstrate that the proposed model outperforms others by a significant margin for both binary and multi-category classification cases.

The benefit of breast magnetic resonance imaging (MRI) in breast-conserving surgery (BCS) is unclear. Our study compared breast cancer patients with and without preoperative breast MRI and their long-term oncologic outcomes are reported. A total of 1378 BCS cases with early breast cancer between 1996 and 2017 were reviewed. Patients with carcinoma in situ or neoadjuvant treatment or having breast MRI after tumor excision were excluded. Of 1378 patients, 270 (19.5%) had preoperative MRI. There were no significant differences regarding T and N stage and molecular subtypes between the groups. Surgical margins were significantly wider in the breast MRI group. Five-year overall survival (OS) was 96.9% in the MRI group and 94.3% in the control group, and this difference was not significant (p=0.11). Five-year local-regional recurrence-free survival (LRFS) was not significantly different either (98.8% and 96.5%, respectively, p=0.41). When analyses were repeated only for patients with hormone receptor-negative or triple-negative breast cancer, there was still no significant difference in OS, LRFS, or disease-free survival. In conclusion, MRI does not seem necessary in all patients undergoing BCS. New prospective randomized controlled trials are needed to determine appropriate use of preoperative MRI and its effects on oncologic outcomes in early breast cancer patients., Koristi od magnetske rezonancije (MR) kod operativnog zahvata kojim dojka ostaje očuvana u većoj ili manjoj mjeri (breast-conserving surgery, BCS) ostaju nejasne. U ovoj studiji uspoređene su bolesnice s rakom dojke u kojih je napravljena prijeoperacijska MR i one bez MR (kontrolna skupina) te se navode njihovi dugoročni onkološki ishodi. Pregledani su podatci za 1378 žena s ranim rakom dojke podvrgnutih BCS između 1996. i 2017. godine. Bolesnice s karcinomom in situ ili neoadjuvantnim liječenjem ili pak one kod kojih je učinjena MR nakon ekscizije tumora nisu uključene u istraživanje. Od 1378 bolesnica prijeoperacijska MR učinjena je u njih 270 (19,5%). Nije bilo značajnih razlika između dviju skupina s obzirom na T i N stadij te molekularne podtipove karcinoma. Kirurške granice bile su značajno šire u skupini s MR. Petogodišnje ukupno preživljenje bilo je 96,9% u skupini s MR i 94,3% u kontrolnoj skupini; ova razlika nije bila značajna (p=0,11). Petogodišnje preživljenje bez lokalnog-regionalnog recidiva (local-regional recurrence-free survival, LRFS) također se nije značajno razlikovalo između dviju skupina (98,8% odnosno 96,5%, p=0,41). Kad su analize ponovljene samo za bolesnice s rakom dojke negativnim na receptore ili trostruko negativnim rakom dojke nisu utvrđene nikakve značajne razlike u ukupnom preživljenju, LRFS ili preživljenju bez bolesti. Zaključno, izgleda da MR nije potrebno raditi u svih bolesnica u kojih se planira BCS. Nova prospektivna randomizirana kontrolirana istraživanja su potrebna kako bi se utvrdila odgovarajuća primjena prijeoperacijske MR te njezini učinci na onkološke ishode u bolesnica s ranim rakom dojke.

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Biorefineries producing biobased chemical and material products are expected to be an important part of the biobased economy, as well as essential for the transition to a circular economy. A biorefinery classification system has been developed using the IEA Bioenergy Task 42 classification as basis to provide a standardized communication about biorefineries on the basis of four major elements: feedstocks, conversion processes, platforms and products. Based on this classification system, eleven umbrella biorefinery pathways have been identified (A-K). The platform(s) that arise from primary refining were used in distinguishing them. Each of these umbrella biorefinery pathways encompasses the different process variations of this pathway. The process variants show development of the pathways towards generation of multiple valuable products for multiple markets also considering higher-value valorization options of residues. This study can be used to help make decisions and take actions to accelerate biorefinery deployment in transitioning towards a circular biobased economy.

This article presents a life cycle assessment of bio-based polyethylene terephthalate (PET) bottles with a cradle to grave scope and provides a comparison with petrochemical PET bottles for 13 environmental impact categories. Besides the baseline bio-based PET bottles, which are produced from Brazilian sugarcane reflecting status-quo, two alternative hypothetical bio-based product systems were considered: European wheat straw and European crops market mix composed of maize, wheat and sugar beet. The land-use change (LUC) impacts were assessed based on a deterministic model. The end-of-life impact was assessed using the EASETECH model. Baseline bio-based PET bottles performed overall worse than conventional petrochemical PET bottles, offering only better performance (about 10%) in abiotic depletion (fossil fuels). Comparable performance is observed for climate change (2% difference without the LUC, and 7% with LUC impacts). Using European crops for ethanol production (alternative 1) instead of Brazilian sugarcane resulted in a worse environmental performance, due to lower yields attained compared to Brazilian sugarcane. When wheat straw was considered as biomass feedstock for ethanol production (alternative 2), similar environmental performance with petrochemical PET bottles was seen.

Formaldehyde-based adhesives are used in the forestry industry. This is because formaldehyde is inexpensive, easy to use and resistant to moisture; it also has particular mechanical effects. Formaldehyde has both advantages and disadvantages. It is known that various diseases such as lung cancer occur in humans as a result of the release of formaldehyde into the air during and after board production. In this study, a urea formaldehyde glue mixture was prepared by using four different fillers (extract of maritime pine (Pinus pinaster) and elm (Ulmus glabra) bark, extract of hazelnut (Corylus avellana) husk and acorn tannins) at two different ratios. The bonding shear strength of pine (Pinus sylvestris) and spruce (Picea orientalis) plywood produced with urea formaldehyde adhesive was tested according to EN 314-1 standard. All plywood, except the plywood with acorn tannin, met the requirements of the standard. A formaldehyde emission test of the plywood was carried out in accordance with EN 713-3 standard. With this approach, it is possible to quickly determine formaldehyde emissions. Experimental results were obtained for subsequent measurements, including chamber tests. It was observed that the elm bark extract reduced the formaldehyde emission of pine plywood by 40 %, while other fillers reduced it by 3-37 %., U drvoprerađivačkoj industriji upotrebljavaju se ljepila na bazi formaldehida zato što je taj aldehid jeftin, jednostavan za uporabu, otporan na vlagu i ima posebne mehaničke učinke. Formaldehid ima određenih prednosti i nedostataka. Poznato je da se u ljudi koji rade u drvoprerađivačkoj industriji pojavljuju različite bolesti poput raka pluća, što može biti posljedica ispuštanja formaldehida u zrak tijekom i nakon proizvodnje ploča. Za ovo je istraživanje pripremljena smjesa urea-formaldehidnog ljepila dodavanjem četiriju različitih punila: ekstrakta kore primorskog bora (Pinus pinaster) i brijesta (Ulmus glabra), ekstrakta ljuske lješnjaka (Corylus avellana) i tanina žira u dva različita omjera. Posmična čvrstoća furnirske ploče od borovine (Pinus sylvestris) i smrekovine (Picea orientalis), proizvedene uporabom urea-formaldehidnog ljepila, ispitana je prema normi EN 314-1. Sve furnirske ploče, osim onih s taninom iz žira, zadovoljile su zahtjeve norme. Ispitivanje emisije formaldehida iz furnirskih ploča provedeno je prema normi EN 713-3. Tim je pristupom moguće brzo odrediti emisije formaldehida. Dobiveni su eksperimentalni rezultati za naknadna mjerenja, uključujući ispitivanje u komori. Primijećeno je da je ekstrakt kore brijesta smanjio emisiju formaldehida furnirske ploče od borovine za 40 %, dok su ostala punila smanjila tu emisiju za 3 – 37 %.

Large quantities of biomass will be needed to feed the biobased economy. Use of crops and wood may cause (indirect) land use change related greenhouse gas emissions. Agro-residues could be an interesting alternative. However, several issues are hindering efficient application: High potassium and chlorine content and low bulk density are the most important issues. In this research, a series of processes is proposed to overcome these issues. Through a combination of extraction (to remove potassium and chlorine), steam treatment and pelleting, Clean Agro-Pellet Commodities(CAPCOMs) were produced. The pellets showed improved handling properties. Combustion tests showed improved ash melting behavior, reduced fouling of heat exchangers and low emissions of NOx and fines. Fermentation tests showed that pellets produced at low severity factors were easily hydrolized and fermented to produce ethanol at normal yields. Some inhibition was seen with undiluted hydrolysates. Based on the results a techno-economical evaluation showed that pellets from agro-residues could be produced and transported at a cost of around 6 EURO/GJHHV. Sustainability analysis revealed that pellets could be produced with GHG emissions of 3 to 6.4 kgCO2eq/GJLHV. Via the combination of processes described in this paper, a huge potential of nowadays unused biomass can be made applicable for the bioeconomy.

This report brings insights into the potential of valorising local lignocellulosic biomass of wood in the province of Gelderland at construction industry. The use of locally available wood can make a crucial contribution to the future mix of raw materials for the building industry. This is supportive of reaching targets to combat climate change and contributes to circular economy by storing carbon and reducing dependence on non-renewable sources. An analysis was made of the current situation in Gelderland, including the current use and availability of biobased materials, and a mapping of the various stakeholders along the value chain. Current policies influencing the use of biobased material in the construction sector were reviewed. Through a series of interviews of different actors along the value chain, the hurdles and gaps faced for the increased implementation of biobased building materials and for increasing the circularity of the building industry were identified. Furthermore, the current and potential availability of wood that can be sustainably sourced from the province of Gelderland was identified through a study with the EFISCEN Space forest resource model, combined with a literature review on the potential of different species to be used in the construction sector. Possibilities of matching the local wood species to the demands of the building applications were analysed. Finally, a SWOT analysis was carried out to identify the main issues and needs such as knowledge, infrastructure, chains, collaborations, policy, technology for the valorisation of local wood in the construction sector. Subsequently recommendations were provided for next possible actions and the role of the different actors in the chain to address these needs. Being the most wooded province of the country and hosting a significant construction industry, makes Gelderland an advantageous spot to explore this opportunity. Furthermore, the knowledge domain in the province and relevant nationa

This paper presents a visual analysis of the UNSW-NB25 computer network security or intrusion detection dataset in order to detect any issues inherent to this dataset which may require researchers to address before employing this dataset for data-driven model development such as a machine learning classifier. A number of data preprocessing algorithms are applied on the raw data to address common issues such as elimination of redundant features, conversion of nominal features into numerical format and scaling. PCA, t-SNE and K-means clustering algorithms are employed for developing the graphs and plots for visualization. Consequent analysis through visualization identified and illustrated two major problems as class imbalance and class overlap for this dataset. In conclusion, it is necessary to address these two problems of class imbalance and class overlap prior to employing this dataset for any classifier model development., Comment: 17 singled spaced pages, 2 tables and 12 figures

IEEE This paper presents a directly 3D printed soft monolithic robotic finger with embedded soft pneumatic sensing chambers (PSC) as position and touch sensors. The monolithic finger was fabricated using a low-cost and open-source fused deposition modeling (FDM) 3D printer that employs an off-the-shelf soft and flexible commercially available thermoplastic polyurethane (TPU). A single soft hinge with an embedded PSC was optimized using finite element modeling (FEM) and a hyperelastic material model to obtain a linear relationship between the internal change in the volume of its PSC and the corresponding input mechanical modality, to minimize its bending stiffness and to maximize its internal volume. The soft hinges with embedded PSCs have several advantages, such as fast response to very small changes in their internal volume (~0.0026ml/°), linearity, negligible hysteresis, repeatability, reliability, long lifetime and low power consumption. Also, the flexion of the soft robotic finger was predicted using a geometric model for use in real-time control. The real-time position and pressure/force control of the soft robotic finger were achieved using feedback signals from the soft hinges and the touch PSC embedded in the tip of the finger. This study contributes to the development of seamlessly embedding optimized sensing elements in the monolithic topology of a soft robotic system and controlling the robotic system using the feedback data provided by the sensing elements to validate their performance.

© 2020 IEEE. Soft robots require robust soft and flexible sensors that can undergo large deformations repeatedly. This work reports on soft robotic fingers with embedded soft pneumatic sensing chambers that are directly 3D printed without requiring postprocessing. A low-cost and open-source fused deposition modeling (FDM) 3D printer that employs an off-the-shelf soft thermoplastic poly(urethane) (TPU) was used to fabricate the monolithic fingers and sensing chambers. These pneumatic sensing chambers have multiple advantages including very fast response to any change in their internal volume, linearity, negligible hysteresis, repeatability, reliability, stability over time, long lifetime and very low power consumption. The performance of these chambers is accurately predicted, and their topologies are optimized using finite element modeling (FEM). Also, the flexion of the soft robotic finger is predicted using a geometric model for use in real-time position control. The position control of the soft robotic finger is achieved using feedback signals from the soft pneumatic sensing chambers embedded in the finger.

© 2020 IEEE. In this study, we propose, implement and test a compact pattern recognition (PR) based myoelectric control system to operate robotic prosthetic hands. Instead of using a bulky sensor configuration (8 or more sensors on the forearm) as most commercial or academic PR systems use, only two sEMG-IMU sensors are deployed on the forearm, consistent with the existing myoelectric hands' electrode configuration, to bring the ease of implementation and consequently improve its practical application. For maintaining the recognition performance as much as possible, two additional sEMG-IMU sensors are attached to the upper arm, which aims to collect more information of muscular activities for the benefits of classification but not affecting the existing forearm sockets of the prosthetic hand users. The offline analysis by using the data from 10 intact subjects and 10 transradial (i.e. below-elbow) amputees shows the comparable recognition performance using the proposed sensor configuration (2 + 2 sensors) and classification technique (Random Forest classifier) to that using the full pack of sensing system (10 sensors on the forearm + 2 sensors on the upper arm). In the online tests, the proposed PR system was employed to control the UoW/ACES soft robotic prosthetic hand to successfully and reliably perform seven common wrist/thumb movements for the activities of daily life (ADL).

The article is dealing with evaluation of four fruit maturity stages of 6 selected clones (LKL-3, LKL-14, LKL-19, LKL-33, LKL-96 and LKL-103) of Lonicera kamtschatica (Sevast.) Pojark in relation to total polyphenols, flavonoids content and antioxidant activity of berries. The experiment in 5 replications of each clones has been established in the conditions of Botanical Garden in Nitra (Slovak republic)in 2016. The results of analyses proved that in respect of the total polyphenols content (TPC), the content of flavonoids (FC) and the antioxidant activity the most valuable clones at the stage of full ripened fruit were following: LKL-14 ( 8.77; 2.57 g/kg FW; 9.07 g/kg), LKL-33 (6.77; 2.84 g/kg FW; 9.16 g/kg) and LKL -3 (8.19; 2.61 g/kg FW; 8.94 g/kg). The results of statistical analyses by one-way analysis of variance proved significant differences among assayed clones in total flavonoids and antioxidant activity of fruit but no differences among content of total polyphenols and assayed stages of fruit maturity.

This article reports a case study that examined the peace education practice of a 5th and 6th grade teacher at an independent, non-profit school in the Mid-western United States. The study used Paulo Freire’s (1970) conception of dialogue as its conceptual framework. After describing the study’s context and methods, we present data focusing on the teacher’s background and development as a peace educator, her teaching practices, and her relationships with her students, school and local community. We discuss Michelle’s interdisciplinary approach to peace education linked with her personal background and her use of dialogue as dynamic, fluid, and relational. Our analyses also prompted emergent themes for which we used curriculum theory to capture forms of integration between the personal and political dimensions of peace education, based on which, we propose an “integrated peace education.”

BACKGROUND: Lateralized dysfunction has been suggested in obsessive-compulsive disorder (OCD). However, it is currently unclear whether OCD is characterized by abnormal patterns of brain structural asymmetry. Here we carried out what is by far the largest study of brain structural asymmetry in OCD. METHODS: We studied a collection of 16 pediatric datasets (501 patients with OCD and 439 healthy control subjects), as well as 30 adult datasets (1777 patients and 1654 control subjects) from the OCD Working Group within the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Consortium. Asymmetries of the volumes of subcortical structures, and of measures of regional cortical thickness and surface areas, were assessed based on T1-weighted magnetic resonance imaging scans, using harmonized image analysis and quality control protocols. We investigated possible alterations of brain asymmetry in patients with OCD. We also explored potential associations of asymmetry with specific aspects of the disorder and medication status. RESULTS: In the pediatric datasets, the largest case-control differences were observed for volume asymmetry of the thalamus (more leftward; Cohen's d = 0.19) and the pallidum (less leftward; d = -0.21). Additional analyses suggested putative links between these asymmetry patterns and medication status, OCD severity, or anxiety and depression comorbidities. No significant case-control differences were found in the adult datasets. CONCLUSIONS: The results suggest subtle changes of the average asymmetry of subcortical structures in pediatric OCD, which are not detectable in adults with the disorder. These findings may reflect altered neurodevelopmental processes in OCD.

Objective: Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data. Methods: Structural T1-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures). Results: No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood. Conclusions: The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.

Woody biomass from landscape elements is currently primarily used for energy generation (heat and electricity). Developing high-value applications for this type of biomass is complicated, due to its relatively low quality, the lack of uniformity and the small volumes. This report identifies and quantifies current flows of woody biomass from landscape elements. Furthermore, the different applications for woody biomass are classified based on their functionality. The report also further examines the application of biomass for the production of lumber, pulpwood, monomers and for energy generation. Lastly, the report describes a framework for action, targeting producers, processors and buyers of woody biomass from landscape elements and involved governments, to further develop high-value applications of biomass., Hout uit het landschap wordt nu vooral voor energieproductie (elektriciteit en warmte) ingezet. Het is niet eenvoudig dit hout hoogwaardiger in te zetten onder meer door de relatief lage kwaliteit, de geringe uniformiteit en de geringe volumes. Dit rapport schetst een beeld van de huidige afzet van houtige biomassa uit landschap. Voorts wordt een classificatie geschetst van houttoepassingen naar functionaliteit en wordt ingegaan op de toepassing van hout als zaaghout, vezeltoepassingen, monomere toepassingen en energie-toepassingen. Tenslotte schetst het rapport een handelingsperspectief voor producenten, verwerkers en afnemers van hout uit landschap en betrokken overheden om te komen tot duurzamere toepassingen van dit hout.

This paper presents a biometric user authentication system based on an ensemble design that employs face and voice recognition classifiers. The design approach entails development and performance evaluation of individual classifiers for face and voice recognition and subsequent integration of the two within an ensemble framework. Performance evaluation employed three benchmark datasets, which are NIST Feret face, Yale Extended face, and ELSDSR voice. Performance evaluation of the ensemble design on the three benchmark datasets indicates that the bimodal authentication system offers significant improvements for accuracy, precision, true negative rate, and true positive rate metrics at or above 99% while generating minimal false positive and negative rates of less than 1%., Comment: 11 pages, 8 Figures and 14 Tables. Accepted for publication in Journal of Information Assurance and Security

This paper presents an approach for low-cost simulation modeling for application development for wireless sensor networks. Computational complexity of simulating wireless sensor networks can be very high and as such must be carefully managed. Application-level code prototyping with reasonable accuracy and fidelity can be accomplished through simulation that models only the effects of the wireless and distributed computations which materialize mainly as delay and drop for the messages being exchanged among the motes. This approach employs the abstraction that all physical or communication and protocol level operations can be represented in terms of their effects as message delay and drop at the application level for a wireless sensor network. This study proposes that idea of empirical modeling of delay and drop and employing those models to affect the reception times of wirelessly communicated messages. It further proposes the delay and drop to be modeled as random variables with probability distributions empirically approximated based on the data reported in the literature. The proposed approach is demonstrated through development of a neural network application with neurons distributed across the motes of a wireless sensor network. Delay and drop are incorporated into wireless communications, which carry neuron output values among motes. A set of classification data sets from the Machine Learning Repository are employed to demonstrate the performance of the proposed system in a comparative context with the similar studies in the literature. Results and findings indicate that the proposed approach of abstracting wireless sensor network operation in terms of message delay and drop at the application level is feasible to facilitate development of applications with competitive performance profiles while minimizing the spatio-temporal cost of simulation., Comment: 49 single-column and double spaced pages; 8 figures; and 10 tables

In this paper, we present a study that proposes a three-stage classifier model which employs a machine learning algorithm to develop an intrusion detection and identification system for tens of different types of attacks against industrial SCADA networks. The machine learning classifier is trained and tested on the data generated using the laboratory prototype of a gas pipeline SCADA network. The dataset consists of three attack groups and seven different attack classes or categories. The same dataset further provides signatures of 35 different types of sub-attacks which are related to those seven attack classes. The study entailed the design of three-stage machine learning classifier as a misuse intrusion detection system to detect and identify specifically each of the 35 attack subclasses. The first stage of the classifier decides if a record is associated with normal operation or an attack signature. If the record is found to belong to an attack signature, then in the second stage, it is classified into one of seven attack classes. Based on the identified attack class as determined by the output from the second stage classifier, the attack record is provided for a third stage sub-attack classification, where seven different classifiers are employed. The output from the third stage classifier identifies the sub-attack type to which the record belongs. Simulation results indicate that designs exploring specialization to domains or executing the classification in multiple stages versus single-stage designs are promising for problems where there are tens of classes. Comparison with studies in the literature also indicated that the multi-stage classifier performed markedly better., Comment: 24 single-column, double-spaced pages; 1 Figure; and 21 Tables

© 2020 IEEE. This work reports on soft pneumatic bending sensing chambers that are directly 3D printed without requiring any support material and postprocessing using a low-cost and open-source fused deposition modeling (FDM) 3D printer and a commercially available soft thermoplastic polyurethane (TPU). These bending sensing chambers have multiple advantages including very fast response to any change in their internal volume, linearity, negligible hysteresis, repeatability, reliability, stability over time, long lifetime and very low power consumption. The performance of these soft sensing chambers is accurately predicted and optimized using finite element modeling (FEM) and a hyperelastic material model for the TPU used for 3D printing. The soft sensing chambers are tailored to several soft robotic applications such as bending sensors for bilateral control of soft robotic fingers and structures and soft wearable gloves for remote control of soft monolithic robotic fingers and adaptive grippers.

Soft robots require seamless integration with sensors and actuators that are simple to manufacture at scale with low cost and minimum footprint. The sensor materials must be highly reliable, sensitive, and stable, and their mechanical features should match the sensing requirements of soft robots such as minimal response time and nonlinearity of hysteresis and relaxation. A resistive-type sensor based on the synthesis of poly(glycerol secabate) (PGS) with a foam-like structure and outstanding mechanical, electrical, and electromechanical properties is developed. These foam sensors present high sensitivity (gauge factor ≈ −9), very fast response (≤3 ms), negligible hysteresis, reliability, long lifetime (>1 200 000 cycles), and a pressure differential sensitivity of 34 Pa. They can accurately detect low and high frequency vibrations (up to 300 Hz) and small forces (200 mN) that cover the very low detection range of metallic strain gauges and the very large detection range of elastomeric strain sensors. These characteristics closely match those of the human fingertip, and hence pave the way toward tactile and compliant sensing elements embedded in prosthetic hands. Prospective applications for unexplored resistive-type sensors to meet the sensory requirements of soft robotic systems are demonstrated.

The thumb of a natural hand or a prosthetic hand plays a significant role in realizing a hand's grasping and manipulation activities. This requires that mechanical design of a prosthetic hand should allow its thumb to perform both abduction/adduction and flexion/extension in order to mimic a natural hand's grasping and manipulation abilities with a minimum number of actuators. In this letter, we propose a novel monolithic soft robotic thumb for an anthropomorphic and transradial prosthetic hand. The thumb and the whole prosthetic hand were fabricated using a low-cost three-dimensional printing technology, with sizes comparable to those of real human ones but with much lighter weights. Based on the concepts of soft robotics and underactuation, the thumb shows significant mechanical compliance and performs well in power grasps, precision grasps, and lateral grasps of different shaped and sized household objects. The soft thumb has two modes of operation based on an innovative and compact mechanism, and one actuator only offers grasping versatility (capable of both abduction/adduction and flexion/extension). This novel thumb minimizes the number of actuators and reduces the corresponding requirement on space consumption (for housing its actuators) and power consumption, which are favorable features to develop low-cost, low-power and low-weight prosthetic hands with intrinsic compliance.