Value-added strategies for the sustainable handling, disposal, or value-added use of copper smelter and refinery wastes

Metallurgical plants constituting of smelters and refineries recover metals (i.e., copper) from mineral deposits. Copper production generates several waste streams of which slag, sludge and dust are generated in the largest quantities. The need to eliminate or at least reduce their adverse effects on the environment call for developing methods for recovering valuable components such as copper, zinc and iron through their selective separation from toxic components present in the waste (mainly arsenic and lead). This can be achieved through hydrometallurgical methods (leaching with organic and inorganic media), techniques facilitating mobility of elements (roasting with leaching) and biological processes (bioleaching). The valorization of metallurgical waste as a source of fertilizer micronutrients can be a sustainable and value-added direction of its management. This review presents ways of useful-metals recovery from the copper smelter and refinery wastes, including selective separation of valuable metals. The novelty of this review is a demonstration of the application potential of recovered components from metallurgical waste in the agricultural sector.

Biofortification of edible plants with selenium and iodine - A systematic literature review

Soil depletion with absorbed forms of microelements is a realistic problem leading to the formation of many human, plant, animal diseases related with micronutrient deficiencies. Searching for new ways to solve this problem is a crucial for the agro-chemical approach to food production. There are many research papers on plant micronutrient fertilization. However, there is still a lack of systematic review of the literature, which summarizes the most recent knowledge on biofortification of food of plant origin with microelements. This work is a systematic review which presents the various methodologies and compares the results of the applied doses and types of fertilizer formulation with the yield and micronutrient content of edible parts of plants. The PRISMA protocol-based review of the most recent literature data from the last 5 years (2015-2020) concerns enrichment of plants with selenium and iodine. These elements, in contrast to other microelements (zinc, manganese, iron, copper and others) are given to plants most often in anionic form: selenium - SeO₃^2- and SeO₄^2-, iodine - I^- and IO₃^-, making them a separate subgroup of microelements. The review focuses on original research papers (not reviews), collected in 3 popular scientific databases: Scopus, Web of Knowledge, PubMed. This study shows how to effectively cope with hidden hunger taking into account the significance of optimized fertilization. Based on the collected data, the best method of micronutrients administration an integrated fortification strategy for selected trace elements and prospects in research/action development was proposed. It was found that the best way to enrich plants with selenium is foliar fertilization with Se(VI), in increased doses. The effectiveness of fortification is supported by the balanced nutrients fertilization, the presence of microorganisms and selection of plant varieties. Foliar fertilization, in increased doses with iodide (I^-) is in turn an effective way to enrich plants with iodine.

Sustainable valorisation pathways mitigating environmental pollution from brewers' spent grains

In this work, valorisation pathways of brewers' spent grains (BSG) towards biofuels production under the biorefinery concept were studied utilizing experimental data that provide a common base for straightforward comparison. The dehydration and the recovery of used oil, bioethanol and biogas from BSG were studied. The process units involved were thoroughly investigated and optimized. The oil extraction efficiency reached up to 70% using solid-liquid extraction process with hexane as solvent. The optimal ethanol yield achieved was 45% after the application of acid pretreatment, enzymatic hydrolysis with CellicCTec2 and fermentation with S. Cerevisiae. As far as biogas potential is concerned, the raw BSG, defatted BSG and stillage presented values equal to 379 ± 19, 235 ± 21 and 168 ± 39 mL biogas/g for respectively. Through the combination of the proposed schemes, three biorefinery scenarios were set up able to produce biodiesel, bioethanol and/or biogas. Material flow diagrams were set up in order to assess these schemes. Given that BSG could ensure 'green' energy production in the range of 4.5-7.0 million MJ/y if the European BSG potential is fully valorised, BSG could substantially contribute to the biofuel energy strategy.

Biosorption as a method of biowaste valorization to feed additives: RSM optimization

The aim of this work was to prepare an innovative microelemental feed additive for laying hens, based on waste biomass from the agricultural sector (alfalfa and goldenrod after CO₂ extraction in supercritical state). The process was optimized by Response Surface Methodology (RSM) and the most favourable enrichment conditions were selected for Cu(II), Mn(II) and Zn(II) ions: pH - 5, sorbate concentration of Cu(II), Mn(II), Zn(II) - 10.0 mg/L for alfalfa and 10.7 mg/L for goldenrod and biomass dose - 0.1 g/L. Physicochemical properties of biomass were studied and functional groups involved in the binding of Cu(II), Mn(II), Zn(II) ions were determined (mainly carboxylic and hydroxylic groups). An interesting and unique element of this work is the verification of the properties of prepared feed additives in conditions simulating the digestive tract of animals. The release of components in solutions simulating conditions in the intestine and stomach (pH 11 and pH 1) was tested (in vitro tests). The best desorption results were achieved at a strongly acidic pH which corresponds to the stomach environment: 9.80, 14.4% Cu(II), 69.0, 66.9% (Zn), 46.5, 31.9 Mn(II) for alfalfa and goldenrod, respectively. It was concluded that the biomass enriched with micronutrients in biosorption has the potential as a feed additive for sustainable agriculture.

Real-Time Prediction of Joint Forces by Motion Capture and Machine Learning

Conventional biomechanical modelling approaches involve the solution of large systems of equations that encode the complex mathematical representation of human motion and skeletal structure. To improve stability and computational speed, being a common bottleneck in current approaches, we apply machine learning to train surrogate models and to predict in near real-time, previously calculated medial and lateral knee contact forces (KCFs) of 54 young and elderly participants during treadmill walking in a speed range of 3 to 7 km/h. Predictions are obtained by fusing optical motion capture and musculoskeletal modeling-derived kinematic and force variables, into regression models using artificial neural networks (ANNs) and support vector regression (SVR). Training schemes included either data from all subjects (LeaveTrialsOut) or only from a portion of them (LeaveSubjectsOut), in combination with inclusion of ground reaction forces (GRFs) in the dataset or not. Results identify ANNs as the best-performing predictor of KCFs, both in terms of Pearson R (0.89-0.98 for LeaveTrialsOut and 0.45-0.85 for LeaveSubjectsOut) and percentage normalized root mean square error (0.67-2.35 for LeaveTrialsOut and 1.6-5.39 for LeaveSubjectsOut). When GRFs were omitted from the dataset, no substantial decrease in prediction power of both models was observed. Our findings showcase the strength of ANNs to predict simultaneously multi-component KCF during walking at different speeds-even in the absence of GRFs-particularly applicable in real-time applications that make use of knee loading conditions to guide and treat patients.

Efficient removal of mercury (II) from water by use of cryogels and comparison to commercial adsorbents under environmentally relevant conditions

Mercury is a toxic element, which can be found in air, water and soil in several inorganic and organic forms. Mercury pollution comes from a variety of industrial sources, including vinyl-chloride, pulp and paper, fertilizers and pharmaceuticals industry, gold mining and cement production. Gels have increasingly attracted the interest over the past decades and one of the investigated applications is the fast removal of organic substances, metals and other cations and anions from water. In this work, two types of cryogels were synthesized at sub-zero temperature by free-radical polymerization technique, characterized by using a set of complimentary methods and used for the removal of mercury from aqueous solutions of different chemistry. Kinetics and equilibrium studies were performed in ultra-pure water solutions in order to study the mechanisms in the presence nitrate and chloride ions. The cryogels exhibited excellent efficiency towards mercury removal from all model solutions. Moreover, the cryogels were tested in different water matrixes (tap, river and sea water) and compared to commercial adsorbents (activated carbon, strong acid resin and zeolite Y). Cryogels were able to remove mercury much faster than commercial adsorbents with the exception of seawater where activated carbon was superior.

A Review on Finite Element Modeling and Simulation of the Anterior Cruciate Ligament Reconstruction

The anterior cruciate ligament (ACL) constitutes one of the most important stabilizing tissues of the knee joint whose rapture is very prevalent. ACL reconstruction (ACLR) from a graft is a surgery which yields the best outcome. Taking into account the complicated nature of this operation and the high cost of experiments, finite element (FE) simulations can become a valuable tool for evaluating the surgery in a pre-clinical setting. The present study summarizes, for the first time, the current advancement in ACLR in both clinical and computational level. It also emphasizes on the material modeling and properties of the most popular grafts as well as modeling of different surgery techniques. It can be concluded that more effort is needed to be put toward more realistic simulation of the surgery, including also the use of two bundles for graft representation, graft pretension and artificial grafts. Furthermore, muscles and synovial fluid need to be included, while patellofemoral joint is an important bone that is rarely used. More realistic models are also required for soft tissues, as most articles used isotropic linear elastic models and springs. In summary, accurate and realistic FE analysis in conjunction with multidisciplinary collaboration could contribute to ACLR improvement provided that several important aspects are carefully considered.

Endoscopic Treatment of Posterior Ankle Impingement Secondary to Os Trigonum in Recreational Athletes

Background:

The os trigonum (OT)—the most common accessory bone of the foot—although usually asymptomatic, may cause posterior ankle impingement syndrome (PAIS), which may be a severely debilitating problem for recreational or competitive athletes. The aim of the present study was to evaluate effectiveness of posterior ankle arthroscopy and to assess the outcome in the treatment of PAIS secondary to OT impingement or OT fractures within a group of young athletes and their return to previous sports level.

Methods:

From 2011 to 2018, a retrospective review of 81 recreational athletes of mean age 27.8 years was performed. All patients were diagnosed with PAIS due to OT pathology and were operated on endoscopically with resection of the OT. Pre- and postoperative clinical evaluation were performed at 3 months, 1 year, and 2 years based on visual analog scale (VAS), ankle range of motion (ROM), American Orthopaedic Foot & Ankle Society (AOFAS) hindfoot score, and the Foot & Ankle Disability Index (FADI) scores, in a follow-up of at least 2 years.

Results:

VAS score was significantly improved from an average of 7.5 (5-9) preoperatively to 1.9 (1-3) at 3 months postoperatively and to 0.6 (0-2) and 0.3 (0 -1) at 1 and 2 years postoperatively. Ankle ROM was significantly improved from an average of 24.8 (10-35) preoperatively to 58.0 (50-65) at 3 months postoperatively and to 64.0 (50-65) at 1 year and 64.7 (60-65) at 2 years postoperatively. AOFAS and FADI scores were significantly improved from 39.4 (18-55) and 49.7 (42.3-62.5) preoperatively to 85.2 (74-89) and 87.3 (81.7-88.5) postoperatively at 3 months to 97.7 (85-100) and 97.9 (93.3-100) postoperatively at 1 year, respectively (P < .001). Only 5 patients dropped to a lower activity level. There were 5 complications (4 transient).

Conclusion:

Endoscopic treatment of PAIS due to OT pathology demonstrated excellent results. Posterior ankle arthroscopy was an effective treatment and allowed for a prompt return to a high activity level of their athletic performance.

Level of Evidence:

Level IV, therapeutic study / retrospective case series.

Circular bio-economy via energy transition supported by Fuzzy Cognitive Map modeling towards sustainable low-carbon environment

Several energy transition plans attempt to establish low-carbon practices towards a circular bio-economy in order to reduce greenhouse gas emissions. However, most actions only try to assuage the impacts of climate change without improving the resource flows generated by human activities. In this paper, we propose a semi-quantitative assessment of the impacts of biowaste-based energy transition by engaging all relevant social stakeholders' evaluation in the strategic plan. This holistic approach models a Decision Support System (DSS) to effectively evaluate the interplay of local and sectoral low-carbon actions. Regional energy alliances and stakeholders are used for participatory modeling to promote the buildup of the learning base of this DSS. The core pillar of the DSS involves the application of advanced features of soft computing for the development of a Fuzzy Cognitive Map (FCM) that elicits the inter-causalities of the critical factors affecting the energy transitions towards bio-economy options. The concepts participating in the map are established by experts, and their interrelations via a learning process that utilizes survey statistics. The strands of research include scenarios to highlight the effect of energy provision to urbanization and the increase of urban actors (social, technological, political) in influencing the decision making related to low-carbon policies. Particularly, we study a use case of a Greek region that, despite its munificent agricultural production, also disclosures a stimulated manufacturing economy sector. The proposed decision making tool uses analytics and optimization algorithms to guide competent authorities and decision makers to sustainable energy transitioning towards decarbonization.

Deep CNN Sparse Coding for Real Time Inhaler Sounds Classification

Effective management of chronic constrictive pulmonary conditions lies in proper and timely administration of medication. As a series of studies indicates, medication adherence can effectively be monitored by successfully identifying actions performed by patients during inhaler usage. This study focuses on the recognition of inhaler audio events during usage of pressurized metered dose inhalers (pMDI). Aiming at real-time performance, we investigate deep sparse coding techniques including convolutional filter pruning, scalar pruning and vector quantization, for different convolutional neural network (CNN) architectures. The recognition performance has been assessed on three healthy subjects following both within and across subjects modeling strategies. The selected CNN architecture classified drug actuation, inhalation and exhalation events, with 100%, 92.6% and 97.9% accuracy, respectively, when assessed in a leave-one-subject-out cross-validation setting. Moreover, sparse coding of the same architecture with an increasing compression rate from 1 to 7 resulted in only a small decrease in classification accuracy (from 95.7% to 94.5%), obtained by random (subject-agnostic) cross-validation. A more thorough assessment on a larger dataset, including recordings of subjects with multiple respiratory disease manifestations, is still required in order to better evaluate the method’s generalization ability and robustness.

FrailSafe: An ICT Platform for Unobtrusive Sensing of Multi-Domain Frailty for Personalized Interventions

The implications of frailty in older adults' health status and autonomy necessitates the understanding and effective management of this widespread condition as a priority for modern societies. Despite its importance, we still stand far from early detection, effective management and prevention of frailty. One of the most important reasons for this is the lack of sensitive instruments able to early identify frailty and pre-frailty conditions. The FrailSafe system provides a novel approach to this complex, medical, social and public health problem. It aspires to identify the most important components of frailty, construct cumulative metrics serving as biomarkers, and apply this knowledge and expertise for self-management and prevention. This paper presents a high-level overview of the FrailSafe system architecture providing details on the monitoring sensors and devices, the software front-ends for the interaction of the users with the system, as well as the back-end part including the data analysis and decision support modules. Data storage, remote processing and security issues are also discussed. The evaluation of the system by older individuals from 3 different countries highlighted the potential of frailty prediction strategies based on information and communication technology (ICT).

Controlled release micronutrient fertilizers for precision agriculture - A review

The rapid growth of the global population and the resulting need to ensure sufficient food safety in highly productive agricultural practices. Intensive cultivation of plants contributes to the impoverishment of soils and thus forces farmers to apply intensive fertilization with microelements. Precise fertilization techniques are the future of agriculture, in which nutrients are supplied in controlled way with minimized losses to the environment, caused by leaching to groundwater. Kinetics of nutrients release should be thus adjusted to plant requirements and kinetics of uptake by the plant. The paper presents current achievements in the field of fertilizers with controlled release of microelements, which, apart from the main fertilizer components, are also very significant for proper plant growth. Fertilizers are divided into four basic groups, which include low-solubility fertilizers, fertilizers with external coating, bio-based and nano-fertilizers. Despite structural differences, all groups show properties of controlled microelement release. The paper presents new fertilization technologies with consideration of their influence on the environment.

AVATREE: An open-source computational modelling framework modelling Anatomically Valid Airway TREE conformations

This paper presents AVATREE, a computational modelling framework that generates Anatomically Valid Airway tree conformations and provides capabilities for simulation of broncho-constriction apparent in obstructive pulmonary conditions. Such conformations are obtained from the personalized 3D geometry generated from computed tomography (CT) data through image segmentation. The patient-specific representation of the bronchial tree structure is extended beyond the visible airway generation depth using a knowledge-based technique built from morphometric studies. Additional functionalities of AVATREE include visualization of spatial probability maps for the airway generations projected on the CT imaging data, and visualization of the airway tree based on local structure properties. Furthermore, the proposed toolbox supports the simulation of broncho-constriction apparent in pulmonary diseases, such as chronic obstructive pulmonary disease (COPD) and asthma. AVATREE is provided as an open-source toolbox in C++ and is supported by a graphical user interface integrating the modelling functionalities. It can be exploited in studies of gas flow, gas mixing, ventilation patterns and particle deposition in the pulmonary system, with the aim to improve clinical decision making.

Bio-based fertilizers: A practical approach towards circular economy

Although for the past 100 years, fertilizer technologies have increasingly used renewable resources, the majority of manufactured products are still based on mineral deposits and fossil fuels. The European Commission has set a goal of 30% reduction of non-renewable resources in fertilizer production. This can only be accomplished if there are incentives for wastes valorization and fines for making use of non-renewable raw materials. This will enable the reduction of eutrophication of surface waters due to the presence of nitrogen and phosphorus, originating from agricultural fields fertilizers. The use of biological waste is a practical solution to recover valuable fertilizer components. In order to effectively implement technologies based on biological resources, it is necessary to construct small wastes solubilization or fertilizer installations at the site of waste generation, which will solve the problem of waste transport or sanitary hazards.

Exploring social determinants of municipal solid waste management: survey processing with fuzzy logic and self-organized maps

In the present study, the establishment of decision-making criteria and a novel and robust interdisciplinary approach for systematically characterizing effects of uncertainties in social determinants of municipal solid waste management using an important fuzzy logic methodology is demonstrated. The primary goal is to highlight the social benefits of this waste management option such as job creation, hygiene and health protection, and working safety as well as to indicate certain side effects occurring during waste processing (odor and leachate production, social trust). The current research is based on a social survey in an agro-industrial region, Thessaly, Greece, and indicates a set of diversified key factors that are related to public acceptance of municipal waste management schemes. These features are input to Kohonen Self-Organized Maps (a special type of Artificial Neural Networks) for clustering residents according to their social perception and attitudes in terms of solid waste collecting and recycling. Both analyses highlight the environmental concern, social perception, hygiene and health, economic status, and lifestyle as the primary social determinants in affecting the public attitudes towards recycling. In both cases, these soft computing techniques seem to outperform the classical statistical and logical regression methodologies and become very promising in accurately predicting waste management practice and possibly other environmental behaviors.

The "COFFEE BIN" concept: centralized collection and torrefaction of spent coffee grounds

Spent coffee grounds are the moist solid residues of coffee brewing and in most cases, the disposal is done without any intermediate valorization actions for materials and energy recovery. State-of-the-art applications include extraction of the liquids and application of high-temperature pyrolysis. Both strategies have significant potential but have also some disadvantages (extensive pre-treatment, high costs) when applied on a large scale. This study highlights the lack of mild pyrolysis valorization strategies and presents the idea of the "COFFEE BIN." Separated spent coffee grounds are collected, dried, and thermally treated. The optimal pyrolysis conditions were identified and product characteristics and the mass balances were assessed. Elemental analysis, thermogravimetric analysis, physisorption analysis and higher heating value (HHV) determination was performed for the characterization of the carbonaceous products. The torrefied coffee grounds returned solid yields from 78 to 83%, which are significantly higher than in other cases of conventional biomass and heating values of 24-25 MJ/kg. Higher temperature pyrolysis did not sustain the advantage of increased returned mass yields and the adsorbance potential of all the carbonaceous products was lower than 25 cm³/g. The study highlighted that spent coffee grounds-due to the nature of their production process via roasting-can be suitable for torrefaction because of the high recovered solid yield and the high energy density. The results will be used for the development of a collection scheme for spent coffee grounds in a big municipality of Athens (Greece).

Assessing the alteration of physicochemical characteristics in composted organic waste in a prototype decentralized composting facility

This article presents the pilot experience of an integrated biowaste management system developed in Tinos island, Greece, which promoted source separation and decentralized composting in a prototype unit. This system was introduced as a new-to-the-area of implementation and innovation, since landfilling of mixed municipal solid waste has been the common practice in Tinos island, as in many other areas of insular and mainland Greece. The biowaste management system was implemented through a bring scheme that aimed at motivating the public to separate at source the organic fraction of MSW. The system was monitored on an input-output basis of critical parameters used to assess the purity of separately collected biowaste, the treatment efficiency of the prototype unit, the quality characteristics of compost produced, and public's awareness and participation. Results showed that biowaste source separation was practiced effectively by citizens, giving high-purity feed (> 98%). Compost samples were examined in comparison with the proposed EU End-of-Waste (EoW) quality criteria and fulfilled the requirements set. More specifically, the average values of compost samples regarding heavy metal content were 72% lower than the EoW limit value for Cd, 43% lower for Ni, 38% lower for Pd, 24% lower for Cu, and 36% lower for Zn. Examined composts also met the EoW criteria for phytotoxicity and pathogenic or parasitic microorganisms, while they showed an approx. 15% decrease in initial organic matter content. Moreover, this study analyzed the carbon balances and the degree that composting can sequestrate carbon. Overall, this study demonstrated that the development and operation of on-island, decentralized composting, when properly practiced, is a sustainable option in order for islands and remote areas to adopt a closed loop approach to the biowaste management problem, in line with the circular economy principles.

Large Osteochondral Lesions of the Talus Treated With Autologous Bone Graft and Periosteum Transfer

Background:

The treatment of large osteochondral lesions of the talus (OLTs) is challenging due to the poor intrinsic reparative capability of the damaged articular cartilage. Autologous transfer of bone and periosteum has been used successfully in the treatment of large defects in animals, and therefore it was believed that this technique might show similar results in humans. The purpose of this study was to assess the outcome of an innovative technique for autologous transplantation of cancellous tibial graft with periosteal transfer in large OLTs.

Methods:

Forty-one patients (22 females, 19 males), with a mean age of 34.9 years (range, 18-72 years), with a large OLT (>200 mm²) were treated with autologous bone graft and periosteum transfer. OLTs averaging 310 mm² were identified on a preoperative computed tomography scan. The procedure consisted of malleolar osteotomy, curettage of sclerotic bone, autologous bone graft from the proximal tibia, and transfixion of periosteum over the graft. Outcome measures, including the pain visual analog scale (VAS), ankle range of motion (ROM), American Orthopaedic Foot & Ankle Society (AOFAS) score, and Foot & Ankle Disability Index (FADI), were compared between preoperative and 1 and 2 years following surgery.

Results:

There were significant improvements in VAS pain score from 7.7 before surgery to 1.1 at 1 year after surgery and 0.4 at 2 years or more after surgery. The AOFAS and FADI scores were also significantly improved from 40.3 and 53.3 preoperatively to 95 and 93.2 postoperatively at 1 year and 95 and 93.2 at 2 or more years postoperatively, respectively. Postoperative complications included 2 patients who required removal of medial malleolar osteotomy tension bands due to symptomatic hardware. There were no nonunions or malunions of the osteotomies and no donor site complications.

Conclusion:

Autologous bone graft and periosteum transfer was an effective treatment for large OLTs leading to significant decreases in pain and improvement in functional scores at more than 2 years after surgery.

Level of Evidence:

Level IV, retrospective case series.

Feature Preserving Mesh Denoising Based on Graph Spectral Processing

The increasing interest for reliable generation of large scale scenes and objects has facilitated several real-time applications. Although the resolution of the new generation geometry scanners are constantly improving, the output models, are inevitably noisy, requiring sophisticated approaches that remove noise while preserving sharp features. Moreover, we no longer deal exclusively with individual shapes, but with entire scenes resulting in a sequence of 3D surfaces that are affected by noise with different characteristics due to variable environmental factors (e.g., lighting conditions, orientation of the scanning device). In this work, we introduce a novel coarse-to-fine graph spectral processing approach that exploits the fact that the sharp features reside in a low dimensional structure hidden in the noisy 3D dataset. In the coarse step, the mesh is processed in parts, using a model based Bayesian learning method that identifies the noise level in each part and the subspace where the features lie. In the feature-aware fine step, we iteratively smooth face normals and vertices, while preserving geometric features. Extensive evaluation studies carried out under a broad set of complex noise patterns verify the superiority of our approach as compared to the state-of-the-art schemes, in terms of reconstruction quality and computational complexity.

Integrating an openEHR-based personalized virtual model for the ageing population within HBase

Background

Frailty is a common clinical syndrome in ageing population that carries an increased risk for adverse health outcomes including falls, hospitalization, disability, and mortality. As these outcomes affect the health and social care planning, during the last years there is a tendency of investing in monitoring and preventing strategies. Although a number of electronic health record (EHR) systems have been developed, including personalized virtual patient models, there are limited ageing population oriented systems.

Methods

We exploit the openEHR framework for the representation of frailty in ageing population in order to attain semantic interoperability, and we present the methodology for adoption or development of archetypes. We also propose a framework for a one-to-one mapping between openEHR archetypes and a column-family NoSQL database (HBase) aiming at the integration of existing and newly developed archetypes into it.

Results

The requirement analysis of our study resulted in the definition of 22 coherent and clinically meaningful parameters for the description of frailty in older adults. The implemented openEHR methodology led to the direct use of 22 archetypes, the modification and reuse of two archetypes, and the development of 28 new archetypes. Additionally, the mapping procedure led to two different HBase tables for the storage of the data.

Conclusions

In this work, an openEHR-based virtual patient model has been designed and integrated into an HBase storage system, exploiting the advantages of the underlying technologies. This framework can serve as a base for the development of a decision support system using the openEHR’s Guideline Definition Language in the future.

Modeling musculoskeletal kinematic and dynamic redundancy using null space projection

The coordination of the human musculoskeletal system is deeply influenced by its redundant structure, in both kinematic and dynamic terms. Noticing a lack of a relevant, thorough treatment in the literature, we formally address the issue in order to understand and quantify factors affecting the motor coordination. We employed well-established techniques from linear algebra and projection operators to extend the underlying kinematic and dynamic relations by modeling the redundancy effects in null space. We distinguish three types of operational spaces, namely task, joint and muscle space, which are directly associated with the physiological factors of the system. A method for consistently quantifying the redundancy on multiple levels in the entire space of feasible solutions is also presented. We evaluate the proposed muscle space projection on segmental level reflexes and the computation of the feasible muscle forces for arbitrary movements. The former proves to be a convenient representation for interfacing with segmental level models or implementing controllers for tendon driven robots, while the latter enables the identification of force variability and correlations between muscle groups, attributed to the system’s redundancy. Furthermore, the usefulness of the proposed framework is demonstrated in the context of estimating the bounds of the joint reaction loads, where we show that misinterpretation of the results is possible if the null space forces are ignored. This work presents a theoretical analysis of the redundancy problem, facilitating application in a broad range of fields related to motor coordination, as it provides the groundwork for null space characterization. The proposed framework rigorously accounts for the effects of kinematic and dynamic redundancy, incorporating it directly into the underlying equations using the notion of null space projection, leading to a complete description of the system.