Explore the vast range of titles available.

High-fidelity 3D reconstruction of human-sized objects typically requires multi-sensor scanning systems that are expensive, complex, and rely on proprietary hardware configurations. Existing low-cost approaches often rely on handheld scanning, which is inherently unstructured and operator-dependent, leading to inconsistent coverage and variable reconstruction quality. This limitation necessitates the need for a controlled, repeatable, and affordable scanning method that can generate high-quality data without requiring multi-sensor hardware or external tracking markers. This study presents a marker-less scanning platform designed for human-scale reconstruction. The system consists of a single structured-light sensor mounted on a vertical linear actuator, synchronised with a motorised turntable that rotates the subject. This constrained kinematic setup ensures a repeatable cylindrical acquisition trajectory. To address the geometric ambiguity often found in vertical translational symmetry (i.e., where distinct elevation steps appear identical), the system employs a sensor-assisted initialisation strategy, where feedback from the rotary encoder and linear drive serves as constraints for the registration pipeline. The captured frames are reconstructed into a complete model through a two-step Iterative Closest Point (ICP) procedure that eliminates the vertical drift and model collapse (often referred to as “telescoping”) common in unconstrained scanning. To evaluate system performance, a modular anthropometric benchmark object representing a human-sized target (1.6 m) was scanned. The reconstructed model was assessed in terms of surface coverage and volumetric fidelity relative to a CAD reference. The results demonstrate high sampling stability, achieving a mean surface density of 0.760points/mm2 on front-facing surfaces. Geometric deviation analysis revealed a mean signed error of −1.54 mm (σ= 2.27 mm), corresponding to a relative volumetric error of approximately 0.096% over the full vertical span. These findings confirm that a single-sensor system, when guided by precise kinematics, can mitigate the non-linear bending and drift artefacts of handheld acquisition, providing an accessible yet rigorously accurate alternative to industrial multi-sensor systems.

Wearable motion capture gloves enable the precise analysis of hand and finger movements for a variety of uses, including robotic surgery, rehabilitation, and most commonly, virtual augmentation. However, many motion capture gloves restrict natural hand movement with a closed-palm design, including fabric over the palm and fingers. In order to alleviate slippage, improve comfort, reduce sizing issues, and eliminate movement restrictions, this paper presents a new low-cost data glove with an innovative open-palm and finger-free design. The new design improves usability and overall functionality by addressing the limitations of traditional closed-palm designs. It is especially beneficial in capturing movements in fields such as physical therapy and robotic surgery. The new glove incorporates resistive flex sensors (RFSs) at each finger and an inertial measurement unit (IMU) at the wrist joint to measure wrist flexion, extension, ulnar and radial deviation, and rotation. Initially the sensors were tested individually for drift, synchronisation delays, and linearity. The results show a drift of 6.60°/h in the IMU and no drift in the RFSs. There was a 0.06 s delay in the data captured by the IMU compared to the RFSs. The glove’s performance was tested with a collaborate robot testing setup. In static conditions, it was found that the IMU had a worst case error across three trials of 7.01° and a mean absolute error (MAE) averaged over three trials of 4.85°, while RFSs had a worst case error of 3.77° and a MAE of 1.25° averaged over all five RFSs used. There was no clear correlation between measurement error and speed. Overall, the new glove design proved to accurately measure joint angles.

Inertial Measurement Units (IMUs) are beneficial for motion tracking as, in contrast to most optical motion capture systems, IMU systems do not require a dedicated lab. However, IMUs are affected by electromagnetic noise and may exhibit drift over time; it is therefore common practice to compare their performance to another system of high accuracy before use. The 3-Space IMUs have only been validated in two previous studies with limited testing protocols. This study utilized an IRB 2600 industrial robot to evaluate the performance of the IMUs for the three sensor fusion methods provided in the 3-Space software. Testing consisted of programmed motion sequences including 360° rotations and linear translations of 800 mm in opposite directions for each axis at three different velocities, as well as static trials. The magnetometer was disabled to assess the accuracy of the IMUs in an environment containing electromagnetic noise. The Root-Mean-Square Error (RMSE) of the sensor orientation ranged between 0.2° and 12.5° across trials; average drift was 0.4°. The performance of the three filters was determined to be comparable. This study demonstrates that the 3-Space sensors may be utilized in an environment containing metal or electromagnetic noise with a RMSE below 10° in most cases.

BackgroundThe repetitive and forceful motions used by operating surgeons increase the risk of developing musculoskeletal disorders. Most ergonomists consider the surgical environment to be incredibly harsh for its workers. Traditional Laparoscopic Surgery (TLS) in particular has a number of physical and mental challenges associated with it, and while Robotic-Assisted Laparoscopic Surgery (RALS) provides several features that improve upon TLS, some surgeons have still reported musculoskeletal symptoms they attribute to RALS. In this paper, we endeavored to systematically review muscle activation for both TLS and RALS, to compare the modalities and present the results as a meta-analysis.MethodsA literature search was conducted using Pubmed, Embase, and Cochrane databases in November 2018 with the following inclusion criteria: full text was available in English, the paper contained original data, EMG was one of the primary measurement techniques, and the paper included EMG data for both TLS and RALS. Results from studies were compared using standardized mean difference analysis.ResultsA total of 379 papers were found, and through screening ten were selected for inclusion. Sample populations ranged from 1 to 31 surgeons, and a variety of study designs and metrics were used between studies. The biceps were the only muscle group that consistently and significantly demonstrated lower muscle activation for RALS for all included studies.ConclusionsThe results may support the belief that RALS is ergonomically superior to TLS, shown through generally lower muscle activation scores. However, these results must be interpreted with caution due to the heterogeneity between the studies and multiple potential sources for bias within studies. This analysis would be strengthened with a higher number of homogenous, high-quality studies examining larger sample sizes.

A tool called LARCalc, for calculating the radiological consequences of accidental large scale nuclear power plant releases based on estimates of 137 Cs ground deposition, is presented. LARCalc is based on a previously developed models that has been further developed and packaged into an easy-to-use decision support tool for training of decision makers. The software visualises the radiological impact of accidental nuclear power plant releases and the effects of various protective measures. It is thus intended as a rapid alternative for planning protective measures in emergency preparedness management. The tool predicts projected cumulative effective dose, projected lifetime attributable cancer risk, and residual dose for some default accidental release scenarios. Furthermore, it can predict the residual dose and avertable cumulative lifetime attributable risk (LAR) resulting from various protective measures such as evacuation and decontamination. It can also be used to predict the avertable collective dose and the increase in cancer incidence within the specified population. This study presents the theoretical models and updates to the previous models, and examples of different nuclear fallout scenarios and subsequent protective actions to illustrate the potential use of LARCalc.

Decontamination of urban areas may be necessary in the case of extensive fallout of radioactive material after a nuclear accident, as removal of contaminated soil and vegetation will significantly reduce doses for the residents in an area affected by fallout. Experience from Japan shows that cleanup operations of urban areas may take years despite investment in ample resources. The time delay between the initial fallout and completion of the decontamination measures allows natural and physical processes to affect the results. The efficiency of the decontamination will therefore depend significantly on time. Radioecological modeling and computer simulation of urban topography with one-story houses were applied in this study to estimate action-influenced time-integrated dose reductions ( TDR ) of contaminated topsoil removal as a function of time after the fallout. Results indicate that the TDR decreases gradually after the fallout depending on the vertical migration rate of radiocesium and, to some extent, the initial 134 Cs/ 137 Cs ratio. Delaying the topsoil removal from 1 to 10 years will result in a TDR decrease by more than a factor of two. Removing the topsoil within one year after fallout results typically in an averted effective dose between 34 and 80 mSv per MBq m −2 deposition of 137 Cs for residents in wooden houses. The corresponding values for residents in brick houses are about 50% lower due to higher shielding. Additional modeling is needed to estimate how age and sex influence the averted detriment to affected cohorts. In addition, more in-depth knowledge of how the efficiency of topsoil removal in practice compares with hypothetical models and the effect of incomplete removal of radiocesium is needed to improve calculations of TDR values.

Vertical farming has been proposed as a solution for diminishing arable land as it significantly reduces the footprint of farming. Most contemporary solutions use a low level of automation; however, automation of vertical farming is currently attracting attention from researchers. This paper introduces a conceptual design for an autonomous vertical farm where the main novelty is the self-assembling feature. The proposed system is designed to be installed and used by a non-specialist. The system is designed for cost minimisation, using one set of resources moved by a robot arm to service the plants. These resources include sensors, a depth camera, and the required farming tools. The farm has the capacity of self-powering, greenhouse conversion, data sharing and learning, and several other features. The paper provides the conceptual design in addition to an analysis of the dimensioning of the robot arm, time studies for operation, and an analysis of the self-powering ability.

The effect of age and gender in risk estimates related to long-term residence in areas contaminated by nuclear power plant fallout was evaluated by applying the lifetime attributable risk (LAR) concept to an existing exposure model that was previously used for cumulative effective dose estimates. In this study, we investigated the influence of age distribution on the number of cancer cases by applying five different age distributions from nuclear power-producing countries (India, Japan, South Korea, and the United States), and Egypt because of intentions to develop nuclear power. The model was also used to estimate the effective dose and gender-specific LAR as a function of time after fallout for the offspring of the population living in 137Cs fallout areas. The principal findings of this study are that the LAR of cancer incidence (excluding non-fatal skin cancers) over 70 y is about 4.5 times higher for newborn females (5.4% per MBq m-2 of initial 137Cs ground deposition) than the corresponding values for 30 y old women (1.2% per MBq m-2 137Cs deposition). The cumulative LAR for newborn males is more than 3 times higher (3.2% versus 1.0% per MBq m-2 137Cs deposition). The model predicts a generally higher LAR for women until 50 y of age, after which the gender difference converges. Furthermore, the detriment for newborns in the fallout areas initially decreases rapidly (about threefold during the first decade) and then decreases gradually with an approximate half-time of 10-12 y after the first decade. The age distribution of the exposed cohort has a decisive impact on the average risk estimates, and in our model, these are up to about 65% higher in countries with high birth rates compared to low birth rates. This trend implies larger average lifetime attributable risks in countries with a highly proportional younger population. In conclusion, the large dispersion (up to a factor of 4 between newborns and 30 y olds) in the lifetime detriment per unit ground deposition of 137Cs over gender and age in connection with accidental nuclear releases justifies the effort in developing risk models that account for the higher radiation sensitivity in younger populations.

The radiological consequences of a nuclear power plant (NPP) accident, resulting in the release of radionuclides to the environment, will depend largely on the mitigating actions instigated shortly after the accident. It is therefore important to make predictions of the radiation dose to the affected population, from external as well as internal exposure, soon after an accident, despite the fact that data are scarce. The aim of this study was to develop a model for the prediction of the cumulative effective dose up to 84 years of age based on the ground deposition of 137Cs that is determined soon after fallout. The model accounts for different assumptions regarding external and internal dose contributions, and the model parameters in this study were chosen to reflect various mitigating actions. Furthermore, the relative importance of these parameters was determined by sensitivity analysis. To the best of our knowledge, this model is unique as it allows quantification of both the external and the internal effective dose using only a fallout map of 137Cs after a nuclear power plant accident. The cumulative effective dose over a period of 50 years following the accident per unit 137Cs deposited was found to range from 0.14 mSv/kBq m-2 to 1.5 mSv/kBq m-2, depending on the mitigating actions undertaken. According to the sensitivity analysis, the most important parameters governing the cumulative effective dose to various adult populations during 50 years after the fallout appear to be: the correlation factor between the local areal deposition of 137Cs and the maximum initial ambient dose rate; the maximum transfer from regional average fallout on the ground to body burden; the local areal deposition of 137Cs; and the regional average 137Cs deposition. Therefore, it is important that mapping of local 137Cs deposition is carried out immediately after fallout from a nuclear power plant accident, followed by calculations of radiation doses for different scenarios using well-known parameters, in order to identify the most efficient mitigation strategies. Given this 137Cs mapping, we believe our model is a valuable tool for long-term radiological assessment in the early phase after NPP accidents.

Learning from Demonstration (LfD) enables robots to acquire manipulation skills by observing human actions. However, existing methods often face challenges such as high computational cost, limited generalizability, and a loss of key interaction details. This study presents a compact representation for interaction recognition in LfD that encodes human–object interactions using 2D wrist trajectories and 3D object poses. A lightweight extraction pipeline combines MediaPipe-based wrist tracking with FoundationPose-based 6-DoF object estimation to obtain these trajectories directly from RGB-D video without specialized sensors or heavy preprocessing. Experiments on the GRAB and FPHA datasets show that the representation effectively captures task-relevant interactions, achieving 94.6% accuracy on GRAB and 96.0% on FPHA with well-calibrated probability predictions. Both Bidirectional Long Short-Term Memory (Bi-LSTM) with attention and Transformer architectures deliver consistent performance, confirming robustness and generalizability. The method achieves sub-second inference, a memory footprint under 1 GB, and reliable operation on both GPU and CPU platforms, enabling deployment on edge devices such as NVIDIA Jetson. By bridging pose-based and object-centric paradigms, this approach offers a compact and efficient foundation for scalable robot learning while preserving essential spatiotemporal dynamics.