Semiactive Virtual Control Method for Robots with Regenerative Energy-Storing Joints

A framework for modeling and control is introduced for robotic manipulators with a number of energetically self-contained semiactive joints. The control approach consists of three steps. First, a virtual control design is conducted by any suitable means, assuming a fully-actuated system. Then, virtual control inputs are matched by a parameter modulation law. Finally, the storage dynamics are shaped using design parameters. Storage dynamics coincide with the system\u27s internal dynamics under exact virtual control matching. An internal energy balance equation and associated self-powered operation condition are given for the semiactive joints. This condition is a structural characteristic of the system and independent of the control law. Moreover, the internal energy balance equation is independent of the energy storage parameter (capacitance), which adds flexibility to the approach. An external energy balance equation is also given that can be used to calculate the work required from the active joints. A simulation example using a 3-dof prosthesis test robot illustrates the concepts

Human Urine as a Noninvasive Source of Kidney Cells

Urine represents an unlimited source of patient-specific kidney cells that can be harvested noninvasively. Urine derived podocytes and proximal tubule cells have been used to study disease mechanisms and to screen for novel drug therapies in a variety of human kidney disorders. The urinary kidney stem/progenitor cells and extracellular vesicles, instead, might be promising for therapeutic treatments of kidney injury. The greatest advantages of urine as a source of viable cells are the easy collection and less complicated ethical issues. However, extensive characterization and in vivo studies still have to be performed before the clinical use of urinederived kidney progenitors

Standardization proposal of soft tissue artefact description for data sharing in human motion measurements

Soft tissue artefact (STA) represents one of the main obstacles for obtaining accurate and reliable skeletal kinematics from motion capture. Many studies have addressed this issue, yet there is no consensus on the best available bone pose estimator and the expected errors associated with relevant results. Furthermore, results obtained by different authors are difficult to compare due to the high variability and specificity of the phenomenon and the different metrics used to represent these data. Therefore, the aim of this study was twofold: firstly, to propose standards for description of STA; and secondly, to provide illustrative STA data samples for body segments in the upper and lower extremities and for a range of motor tasks specifically, level walking, stair ascent, sit-to-stand, hip- and knee-joint functional movements, cutting motion, running, hopping, arm elevation and functional upper-limb movements. The STA dataset includes motion of the skin markers measured in vivo and ex vivo using stereophotogrammetry as well as motion of the underlying bones measured using invasive or bio-imaging techniques (i.e., X-ray fluoroscopy or MRI). The data are accompanied by a detailed description of the methods used for their acquisition, with information given about their quality as well as characterization of the STA using the proposed standards. The availability of open-access and standard-format STA data will be useful for the evaluation and development of bone pose estimators thus contributing to the advancement of three-dimensional human movement analysis and its translation into the clinical practice and other applications

A Vulnerability Assessment of Fish and Invertebrates to Climate Change on the Northeast U.S. Continental Shelf

Climate change and decadal variability are impacting marine fish and invertebrate species worldwide and these impacts will continue for the foreseeable future. Quantitative approaches have been developed to examine climate impacts on productivity, abundance, and distribution of various marine fish and invertebrate species. However, it is difficult to apply these approaches to large numbers of species owing to the lack of mechanistic understanding sufficient for quantitative analyses, as well as the lack of scientific infrastructure to support these more detailed studies. Vulnerability assessments provide a framework for evaluating climate impacts over a broad range of species with existing information. These methods combine the exposure of a species to a stressor (climate change and decadal variability) and the sensitivity of species to the stressor. These two components are then combined to estimate an overall vulnerability. Quantitative data are used when available, but qualitative information and expert opinion are used when quantitative data is lacking. Here we conduct a climate vulnerability assessment on 82 fish and invertebrate species in the Northeast U.S. Shelf including exploited, forage, and protected species. We define climate vulnerability as the extent to which abundance or productivity of a species in the region could be impacted by climate change and decadal variability. We find that the overall climate vulnerability is high to very high for approximately half the species assessed; diadromous and benthic invertebrate species exhibit the greatest vulnerability. In addition, the majority of species included in the assessment have a high potential for a change in distribution in response to projected changes in climate. Negative effects of climate change are expected for approximately half of the species assessed, but some species are expected to be positively affected (e.g., increase in productivity or move into the region). These results will inform research and management activities related to understanding and adapting marine fisheries management and conservation to climate change and decadal variability

Genomic analyses in Cornelia de Lange Syndrome and related diagnoses: Novel candidate genes, <scp>genotype–phenotype</scp> correlations and common mechanisms

Cornelia de Lange Syndrome (CdLS) is a rare, dominantly inherited multisystem developmental disorder characterized by highly variable manifestations of growth and developmental delays, upper limb involvement, hypertrichosis, cardiac, gastrointestinal, craniofacial, and other systemic features. Pathogenic variants in genes encoding cohesin complex structural subunits and regulatory proteins (NIPBL, SMC1A, SMC3, HDAC8, and RAD21) are the major pathogenic contributors to CdLS. Heterozygous or hemizygous variants in the genes encoding these five proteins have been found to be contributory to CdLS, with variants in NIPBL accounting for the majority (&gt;60%) of cases, and the only gene identified to date that results in the severe or classic form of CdLS when mutated. Pathogenic variants in cohesin genes other than NIPBL tend to result in a less severe phenotype. Causative variants in additional genes, such as ANKRD11, EP300, AFF4, TAF1, and BRD4, can cause a CdLS‐like phenotype. The common role that these genes, and others, play as critical regulators of developmental transcriptional control has led to the conditions they cause being referred to as disorders of transcriptional regulation (or “DTRs”). Here, we report the results of a comprehensive molecular analysis in a cohort of 716 probands with typical and atypical CdLS in order to delineate the genetic contribution of causative variants in cohesin complex genes as well as novel candidate genes, genotype–phenotype correlations, and the utility of genome sequencing in understanding the mutational landscape in this population

Phenotypic spectrum and transcriptomic profile associated with germline variants in TRAF7

PURPOSE: Somatic variants in tumor necrosis factor receptor-associated factor 7 (TRAF7) cause meningioma, while germline variants have recently been identified in seven patients with developmental delay and cardiac, facial, and digital anomalies. We aimed to define the clinical and mutational spectrum associated with TRAF7 germline variants in a large series of patients, and to determine the molecular effects of the variants through transcriptomic analysis of patient fibroblasts. METHODS: We performed exome, targeted capture, and Sanger sequencing of patients with undiagnosed developmental disorders, in multiple independent diagnostic or research centers. Phenotypic and mutational comparisons were facilitated through data exchange platforms. Whole-transcriptome sequencing was performed on RNA from patient- and control-derived fibroblasts. RESULTS: We identified heterozygous missense variants in TRAF7 as the cause of a developmental delay-malformation syndrome in 45 patients. Major features include a recognizable facial gestalt (characterized in particular by blepharophimosis), short neck, pectus carinatum, digital deviations, and patent ductus arteriosus. Almost all variants occur in the WD40 repeats and most are recurrent. Several differentially expressed genes were identified in patient fibroblasts. CONCLUSION: We provide the first large-scale analysis of the clinical and mutational spectrum associated with the TRAF7 developmental syndrome, and we shed light on its molecular etiology through transcriptome studies

Semiactive Virtual Control Method for Robots with Regenerative Energy-Storing Joints

A framework for modeling and control is introduced for robotic manipulators with a number of energetically self-contained semiactive joints. The control approach consists of three steps. First, a virtual control design is conducted by any suitable means, assuming a fullyactuated system. Then, virtual control inputs are matched by a parameter modulation law. Finally, the storage dynamics are shaped using design parameters. Storage dynamics coincide with the system’s internal dynamics under exact virtual control matching. An internal energy balance equation and associated self-powered operation condition are given for the semiactive joints. This condition is a structural characteristic of the system and independent of the control law. Moreover, the internal energy balance equation is independent of the energy storage parameter (capacitance), which adds flexibility to the approach. An external energy balance equation is also given that can be used to calculate the work required from the active joints. A simulation example using a 3-dof prosthesis test robot illustrates the concepts

Evolutionary Optimization of Ground Reaction Force for a Prosthetic Leg Testing Robot

Transfemoral amputees modify their gait in order to compensate for their prosthetic leg. This compensation causes harmful secondary physical conditions due to an over-dependence on the intact limb and deficiencies of the prosthesis. Even with more advanced prostheses, amputees still have to alter their gait to compensate for the prosthesis. We present a novel way to quantify how much an amputee has to compensate for a prosthetic leg. We train a newly-developed prosthetic leg testing robot to walk with a prosthesis using an evolutionary algorithm called biogeography-based optimization (BBO). The robot is initially commanded to follow able-bodied hip and thigh trajectories, and BBO then modifies these reference inputs. We adjust the reference inputs to minimize the error between the ground reaction force (GRF) of able-bodied gait data, and that of the robot while walking with the prosthesis. Experimental results show a 62% decrease in the GRF error, effectively demonstrating the robot\u27s compensation for the prosthesis

Evolutionary Optimization of Ground Reaction Force for a Prosthetic Leg Testing Robot

Transfemoral amputees modify their gait in order to compensate for their prosthetic leg. This compensation causes harmful secondary physical conditions due to an over-dependence on the intact limb and deficiencies of the prosthesis. Even with more advanced prostheses, amputees still have to alter their gait to compensate for the prosthesis. We present a novel way to quantify how much an amputee has to compensate for a prosthetic leg. We train a newly-developed prosthetic leg testing robot to walk with a prosthesis using an evolutionary algorithm called biogeography-based optimization (BBO). The robot is initially commanded to follow able-bodied hip and thigh trajectories, and BBO then modifies these reference inputs. We adjust the reference inputs to minimize the error between the ground reaction force (GRF) of able-bodied gait data, and that of the robot while walking with the prosthesis. Experimental results show a 62% decrease in the GRF error, effectively demonstrating the robot\u27s compensation for the prosthesis

Multi-Objective Optimization of Impedance Parameters in a Prosthesis Test Robot

We design a control system for a prosthesis test robot that was previously developed for transfemoral prosthesis design and test. The robot’s control system aims to mimic human walking in the sagittal plane. It has been seen in previous work that trajectory control alone fails to produce human-like forces. Therefore, we utilize an impedance controller to achieve reasonable tracking of motion and force simultaneously. However, these objectives conflict. Impedance control design can therefore be viewed as a multi-objective optimization problem. We use an evolutionary multi-objective strategy called Multi-Objective Invasive Weed Optimization (MOIWO) to design the impedance controller. The multi-objective optimization problem admits a set of equally valid alternative solutions known as the Pareto optimal set. We use a pseudo weight vector approach to select a single solution from the Pareto optimal set. Simulation results show that a solution that is selected for pure motion tracking performs very accurate motion tracking (RMS error of 0.06 cm) but fails to produce the desired forces (RMS error of 70% peak load). On the other hand, a solution that is selected for pure force tracking successfully tracks the desired force (RMS error of 12.7% peak load) at the expense of motion trajectory errors (RMS error of 4.5 cm). Copyright © 2015 by ASM