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Vehicles can be classified by configuration as either bonnet-type or cab-over type according to engine location. Compared to bonnet-type, the front compartment of cab-over type vehicles is considerably shorter; thus, it may be less likely to absorb the energy generated in a collision, and in turn be unable to prevent deformation of the occupant space and protect occupants from injury. This study was a cohort study involving 943 occupants of mini-vehicles who were injured in frontal collision accidents between 2001 and 2015 and transferred to Ohta Nishinouchi Hospital. The vehicle configuration was divided into bonnet-type and cab-over type (i.e., truck-type and wagon-type). The tested outcomes were anatomical-specific severe injury of the pelvis and extremities, the head and neck, the abdomen, and the chest. To estimate adjusted odds ratios (AOR) for associations between vehicle configuration and anatomical-specific severe injury, we fitted generalized estimating equations for each outcome. Compared with bonnet-type vehicles, a greater risk of serious pelvis and extremities injury was found for both truck (AOR: 2.21; 95% Confidence Interval [95% CI]: 1.22–4.00) and wagon-type vehicles (AOR: 3.43; 95%CI 1.60–7.39). For serious head and neck injury, truck-type vehicles were associated with greater risk (AOR: 2.04; 95% CI: 1.10–3.79) than bonnet-type vehicles, whereas wagon-type vehicles were not. Compared with the occupants of bonnet-type vehicles, cab-over type vehicle occupants were more likely to have serious pelvis and extremities injury during frontal collisions. Additionally, truck-type vehicle occupants were more likely to have serious head and neck injury than bonnet-type vehicle occupants. These findings are expected to promote safer behaviors for vehicle occupants and the automobile industry. [ABSTRACT FROM AUTHOR]

Linkage of medical databases, including insurer claims and electronic health records (EHRs), is increasingly common. However, few studies have investigated the behavior and output of linkage software. To determine how linkage quality is affected by different algorithms, blocking variables, methods for string matching and weight determination, and decision rules, we compared the performance of 4 nonproprietary linkage software packages linking patient identifiers from noninteroperable inpatient and outpatient EHRs. We linked datasets using first and last name, gender, and date of birth (DOB). We evaluated DOB and year of birth (YOB) as blocking variables and used exact and inexact matching methods. We compared the weights assigned to record pairs and evaluated how matching weights corresponded to a gold standard, medical record number. Deduplicated datasets contained 69,523 inpatient and 176,154 outpatient records, respectively. Linkage runs blocking on DOB produced weights ranging in number from 8 for exact matching to 64,273 for inexact matching. Linkage runs blocking on YOB produced 8 to 916,806 weights. Exact matching matched record pairs with identical test characteristics (sensitivity 90.48%, specificity 99.78%) for the highest ranked group, but algorithms differentially prioritized certain variables. Inexact matching behaved more variably, leading to dramatic differences in sensitivity (range 0.04–93.36%) and positive predictive value (PPV) (range 86.67–97.35%), even for the most highly ranked record pairs. Blocking on DOB led to higher PPV of highly ranked record pairs. An ensemble approach based on averaging scaled matching weights led to modestly improved accuracy. In summary, we found few differences in the rankings of record pairs with the highest matching weights across 4 linkage packages. Performance was more consistent for exact string matching than for inexact string matching. Most methods and software packages performed similarly when comparing matching accuracy with the gold standard. In some settings, an ensemble matching approach may outperform individual linkage algorithms. [ABSTRACT FROM AUTHOR]

Bovine milk extracellular vesicles (EVs) attract research interest as carriers of biologically active cargo including miRNA from donor to recipient cells to facilitate intercellular communication. Since toxicity of edible milk seems to be negligible, milk EVs are applicable to use for therapeutics in human medicine. Casein separation is an important step in obtaining pure EVs from milk, and recent studies reported that adding hydrochloric acid (HCl) and acetic acid (AA) to milk accelerates casein aggregation and precipitation to facilitate EV isolation and purification; however, the effects of acidification on EVs remain unclear. In this study, we evaluated the acidification effects on milk-derived EVs with that by standard ultracentrifugation (UC). We separated casein from milk by either UC method or treatment with HCl or AA, followed by evaluation of EVs in milk serum (whey) by transmission electron microcopy (TEM), spectrophotometry, and tunable resistive pulse sensing analysis to determine EVs morphology, protein concentration, and EVs size and concentration, respectively. Moreover, we used anti-CD9, -CD63, -CD81, -MFG-E8, -HSP70, and -Alix antibodies for the detection of EVs surface and internal marker proteins by western blot (WB). Morphological features of EVs were spherical shape and similar structure was observed in isolated EVs by TEM. However, some of the EVs isolated by HCl and AA had shown rough surface. Although protein concentration was higher in whey obtained by UC, EV concentration was significantly higher in whey following acid treatment. Moreover, although all of the targeted EVs-marker-proteins were detected by WB, HCl- or AA-treatments partially degraded CD9 and CD81. These findings indicated that acid treatment successfully separated casein from milk to allow efficient EV isolation and purification but resulted in partial degradation of EV-surface proteins. Our results suggest that following acid treatment, appropriate EV-surface-marker antibodies should be used for accurate assess the obtained EVs for downstream applications. This study describes the acidification effects on EVs isolated from bovine milk for the first time. [ABSTRACT FROM AUTHOR]

Stochastic mechanistic epidemiological models largely contribute to better understand pathogen emergence and spread, and assess control strategies at various scales (from within-host to transnational scale). However, developing realistic models which involve multi-disciplinary knowledge integration faces three major challenges in predictive epidemiology: lack of readability once translated into simulation code, low reproducibility and reusability, and long development time compared to outbreak time scale. We introduce here EMULSION, an artificial intelligence-based software intended to address those issues and help modellers focus on model design rather than programming. EMULSION defines a domain-specific language to make all components of an epidemiological model (structure, processes, parameters…) explicit as a structured text file. This file is readable by scientists from other fields (epidemiologists, biologists, economists), who can contribute to validate or revise assumptions at any stage of model development. It is then automatically processed by EMULSION generic simulation engine, preventing any discrepancy between model description and implementation. The modelling language and simulation architecture both rely on the combination of advanced artificial intelligence methods (knowledge representation and multi-level agent-based simulation), allowing several modelling paradigms (from compartment- to individual-based models) at several scales (up to metapopulation). The flexibility of EMULSION and its capability to support iterative modelling are illustrated here through examples of progressive complexity, including late revisions of core model assumptions. EMULSION is also currently used to model the spread of several diseases in real pathosystems. EMULSION provides a command-line tool for checking models, producing model diagrams, running simulations, and plotting outputs. Written in Python 3, EMULSION runs on Linux, MacOS, and Windows. It is released under Apache-2.0 license. A comprehensive documentation with installation instructions, a tutorial and many examples are available from: . [ABSTRACT FROM AUTHOR]

Magnetic loops are one of the most popular and used traffic sensors because of their widely extended technology and simple mode of operation. Nevertheless, very simple models have been traditionally used to simulate the effect of the passage of vehicles on these loops. In general, vehicles have been considered simple rectangular metal plates located parallel to the ground plane at a certain height close to the vehicle chassis. However, with such a simple model, it is not possible to carry out a rigorous study to assess the performance of different models of vehicles with the aim of obtaining basic parameters such as the vehicle type, its speed or its direction in traffic. For this reason and because computer simulation and analysis have emerged as a priority in intelligent transportation systems (ITS), this paper aims to present a more complex vehicle model capable of characterizing vehicles as multiple metal plates of different sizes and heights, which will provide better results in virtual simulation environments. This type of modeling will be useful when reproducing the actual behavior of systems installed on roads based on inductive loops and will also facilitate vehicle classification and the extraction of basic traffic parameters. [ABSTRACT FROM AUTHOR]

Due to the rapid technological evolution and communications accessibility, data generated from different sources of information show an exponential growth behavior. That is, volume of data samples that need to be analyzed are getting larger, so the methods for its processing have to adapt to this condition, focusing mainly on ensuring the computation is efficient, especially when the analysis tools are based on computational intelligence techniques. As we know, if you do not have a good control of the handling of the volume of the data, some techniques that are based on learning iterative processes could represent an excessive load of computation and could take a prohibitive time in trying to find a solution that could not come close to desired. There are learning methods known as full batch, online and mini-batch, and they represent a good strategy to this problem since they are oriented to the processing of data according to the size or volume of available data samples that require analysis. In this first approach, synthetic datasets with a small and medium volume were used, since the main objective is to define its implementation and in experimentation phase through regression analysis obtain information that allows us to assess the performance and behavior of different learning methods under distinct conditions. To carry out this study, a Mamdani based neuro-fuzzy system with center-of-sets defuzzification with support of multiple inputs and outputs was designed and implemented that had the flexibility to use any of the three learning methods, which were implemented within the training process. Finally, results show that the learning method with best performances was Mini-Batch when compared to full batch and online learning methods. The results obtained by mini-batch learning method are as follows; mean correlation coefficient with 0.8268 and coefficient of determination with 0.7444, and is also the method with better control of the dispersion between the results obtained from the 30 experiments executed per each dataset processed. [ABSTRACT FROM AUTHOR]

Objectives: Currently used risk scores for type 2 diabetes mellitus (T2DM) clearly underestimate cardiovascular risk in type 1 diabetes (T1DM). Hence, there is a need to develop novel and specific risk-estimation tools for this population. We aimed to assess the relationship between the Steno Type 1 Risk Engine (ST1RE) and arterial stiffness (AS), and to identify potential cut-off points of interest in clinical practice. Design and methods: A total of 179 patients with T1DM (50.8% men, mean age 41.2±13.1 years), without established cardiovascular disease, were evaluated for clinical and anthropometric data (including classical cardiovascular risk factors), and AS measured by aortic pulse-wave velocity (aPWV). The ST1RE was used to estimate 10-year cardiovascular risk and patients were classified into 3 groups: low- (<10%; n = 105), moderate- (10–20%; n = 53) and high-risk (≥20%; n = 21). Results: When compared with the low- and moderate-risk groups, patients in the high-risk group were older, had higher prevalence of hypertension, dyslipidemia and insulin-resistance, and had higher body-mass index and HbA1c. aPWV increased in parallel with estimated cardiovascular risk (6.4±1.0, 8.4±1.3 and 10.3±2.6m/s; p<0.001). As an evaluation of model performance, the C-statistic of aPWV was 0.914 (95% confidence interval [CI]:0.873–0.950) for predicting moderate/high-risk and 0.879 (95%CI:0.809–0.948) for high-risk, according to the ST1RE. The best cut-off points of aPWV were 7.3m/s (sensitivity:86%, specificity:83%) and 8.7m/s (sensitivity:76%, specificity:86%) for moderate/high- and high-risk, respectively. Conclusions: AS is highly correlated with the scores obtained from the ST1RE. We have identified two cut-off points of AS that can clearly discriminate moderate/high- and high-risk T1DM patients, which could be of great value in clinical practice. [ABSTRACT FROM AUTHOR]

An accurate estimate of limb position is necessary for movement planning, before and after motor learning. Where we localize our unseen hand after a reach depends on felt hand position, or proprioception, but in studies and theories on motor adaptation this is quite often neglected in favour of predicted sensory consequences based on efference copies of motor commands. Both sources of information should contribute, so here we set out to further investigate how much of hand localization depends on proprioception and how much on predicted sensory consequences. We use a training paradigm combining robot controlled hand movements with rotated visual feedback that eliminates the possibility to update predicted sensory consequences (‘exposure training’), but still recalibrates proprioception, as well as a classic training paradigm with self-generated movements in another set of participants. After each kind of training we measure participants’ hand location estimates based on both efference-based predictions and afferent proprioceptive signals with self-generated hand movements (‘active localization’) as well as based on proprioception only with robot-generated movements (‘passive localization’). In the exposure training group, we find indistinguishable shifts in passive and active hand localization, but after classic training, active localization shifts more than passive, indicating a contribution from updated predicted sensory consequences. Both changes in open-loop reaches and hand localization are only slightly smaller after exposure training as compared to after classic training, confirming that proprioception plays a large role in estimating limb position and in planning movements, even after adaptation. (data: , preprint: ) [ABSTRACT FROM AUTHOR]

Many studies on collective animal behavior seek to identify the individual rules that underlie collective patterns. However, it was not until the recent advancements of micro-electronic and embedded systems that scientists were able to create mixed groups of sensor-rich robots and animals and study collective interactions from the within a bio-hybrid group. In recent work, scientists showed that a robot-controlled lure is capable of influencing the collective decisions of zebrafish Danio rerio shoals moving in a ring and a two-room setup. Here, we study a closely related topic, that is, the collective behavior patterns that emerge when different behavioral models are reproduced through the use of a robotic lure. We design a behavioral model that alternates between obeying and disobeying the collective motion decisions in order to become socially accepted by the shoal members. Subsequently, we compare it against two extreme cases: a reactive and an imposing decision model. For this, we use spatial, directional and information theoretic metrics to measure the degree of integration of the robotic agent. We show that our model leads to similar information flow as in freely roaming shoals of zebrafish and exhibits leadership skills more often than the open-loop models. Thus, in order for the robot to achieve higher degrees of integration in the zebrafish shoal, it must, like any other shoal member, be bidirectionally involved in the decision making process. These findings provide insight on the ability to form mixed societies of animals and robots and yield promising results on the degree to which a robot can influence the collective decision making. [ABSTRACT FROM AUTHOR]

Recent technical developments have resulted in robotic-assisted pedicle screw placement techniques. However, the use of robotic-assisted navigational techniques is still subject to controversy. This study aims to assess the accuracy and safety of a self-developed navigation system, the point spine navigation system (PSNS), for robotic-assisted pedicle screw placement surgery. Fifty-nine pedicle screws were implanted in three porcine vertebrae at the T6–T10 and L1–L5 levels, with the assistance of the PSNS. The navigation and planning system provides virtual surgical guide images, including sagittal, coronal, axial, oblique planes, and customized three-dimensional reconstructions for each vertebra to establish accurate pedicle screw trajectories and placement tracts. After pedicle screw placement, post-operative spiral computer tomographic scans were performed and screws were evaluated using the Gertzbein–Robbins classification. Differences between the actual pedicle screw position and pre-operative planning paths, including the angle, shortest distance, and entry trajectory were recorded. The 59 pedicle screw placements were all within a safe zone, and there was no spinal canal perforation or any other damage under postoperative computed tomography image data. Fifty-one screws were categorized as group A, seven screws were noted as group B, and one screw was identified as group E under the Gertzbein–Robbins classification. The mean entry point deviation was 2.71 ± 1.72°, mean trajectory distance was 1.56 ± 0.66 mm, and average shortest distance between two paths was 0.96 ± 0.73 mm. Pedicle placement remains a challenging procedure with high reported incidences of nerve and vascular injuries. The implementation of a robotic-assisted navigational system yields an acceptable level of accuracy and safety for the pedicle screw placement surgery. [ABSTRACT FROM AUTHOR]

This study compares husbands' and wives' views on the person in a couple who should be responsible for preparing for hurricane hazards; it also examines whether the varying levels of agreement reached by husbands and wives regarding this responsibility are associated with actual preparedness behaviors. An online survey targeting married, heterosexual couples living in Sarasota County, Florida, USA was sent out between March and May, 2015. Both the husbands and the wives were asked to fill out the survey. A total of 170 surveys were used for analysis. Results suggested that husbands and wives felt that they had shared responsibility for most of the 19 preparedness behaviors considered. However, a few stereotypically masculine preparedness behaviors were found to typically fall to husbands. Husbands' and wives' views of perceived responsibility were not statistically different, but husbands tended to favor individual responsibility, while wives tended to favor joint responsibility. Higher levels of agreement were significantly associated with greater engagement in planning-related preparedness behaviors. Policy implications are discussed. [ABSTRACT FROM AUTHOR]

This paper presents an evaluation of the effectiveness of two types of deceleration markings on freeways in China: fishbone-shaped (FS) markings and edge-rate (ER) markings. An actual 4-lane, 6-km long freeway in Province Hebei was created in a driving simulator and used for the experiments. Three scenarios of deceleration markings were adopted: one without markings, one with FS markings, and the third with ER markings. For each scenario, three traffic flow levels were adopted (low, medium, and heavy). The appropriate dimensions of deceleration markings were first established using relevant design guidelines and then used to develop the simulation scenarios using Multigen Creator software. Sixty drivers carried out the simulation experiments with eye tracker equipment. The adequacy of deceleration markings was analyzed with respect to speed, perceived distance, pupil diameter, and geometric parameters. The results showed that both types of deceleration markings made a certain effect on vehicle speed, drivers’visual behavior, and mental characteristics. However, the effect of the FS markings was more pronounced than that of the ER marking. Specifically, the FS markings showed a speed reduction of 12.3 km/h to 15.2 km/h and a perceived distance of 70 m to 90 m, compared with 6.7 km/h to 9.9 km/h and 40 m to 60 m, respectively, for the ER markings. Application comments of the results are provided in the conclusion. [ABSTRACT FROM AUTHOR]

Awareness of task demands is often used during rehabilitation and sports training by providing instructions which appears to accelerate learning and improve performance through explicit motor learning. However, the effects of awareness of perturbations on the changes in estimates of hand position resulting from motor learning are not well understood. In this study, people adapted their reaches to a visuomotor rotation while either receiving instructions on the nature of the perturbation, experiencing a large rotation, or both to generate awareness of the perturbation and increase the contribution of explicit learning. We found that instructions and/or larger rotations allowed people to activate or deactivate part of the learned strategy at will and elicited explicit changes in open-loop reaches, while a small rotation without instructions did not. However, these differences in awareness, and even manipulations of awareness and perturbation size, did not appear to affect learning-induced changes in hand-localization estimates. This was true when estimates of the adapted hand location reflected changes in proprioception, produced when the hand was displaced by a robot, and also when hand location estimates were based on efferent-based predictions of self-generated hand movements. In other words, visuomotor adaptation led to significant shifts in predicted and perceived hand location that were not modulated by either instruction or perturbation size. Our results indicate that not all outcomes of motor learning benefit from an explicit awareness of the task. Particularly, proprioceptive recalibration and the updating of predicted sensory consequences appear to be largely implicit. (data: , preprint: ) [ABSTRACT FROM AUTHOR]

Background: New developments, based on the concept of wearable soft-robotic devices, make it possible to support impaired hand function during the performance of daily activities and intensive task-specific training. The wearable soft-robotic ironHand glove is such a system that supports grip strength during the performance of daily activities and hand training exercises at home. Design: This pilot randomized controlled clinical study explored the effect of prolonged use of the assistive ironHand glove during daily activities at home, in comparison to its use as a trainings tool at home, on functional performance of the hand. Methods: In total, 91 older adults with self-perceived decline of hand function participated in this study. They were randomly assigned to a 4-weeks intervention of either assistive or therapeutic ironHand use, or control group (received no additional exercise or treatment). All participants performed a maximal pinch grip test, Box and Blocks test (BBT), Jebsen-Taylor Hand Function Test (JTHFT) at baseline and after 4-weeks of intervention. Only participants of the assistive and therapeutic group completed the System Usability Scale (SUS) after the intervention period. Results: Participants of the assistive and therapeutic group reported high scores on the SUS (mean = 73, SEM = 2). The therapeutic group showed improvements in unsupported handgrip strength (mean Δ = 3) and pinch strength (mean Δ = 0.5) after 4 weeks of ironHand use (p≤0.039). Scores on the BBT and JTHFT improved not only after 4 weeks of ironHand use (assistive and therapeutic), but also in the control group. Only handgrip strength improved more in the therapeutic group compared to the assistive and control group. No significant correlations were found between changes in performance and assistive or therapeutic ironHand use (p≥0.062). Conclusion: This study showed that support of the wearable soft-robotic ironHand system either as assistive device or as training tool may be a promising way to counter functional hand function decline associated with ageing. [ABSTRACT FROM AUTHOR]

To demonstrate the feasibility of robotic middle ear access in a clinical setting, nine adult patients with severe-to-profound hearing loss indicated for cochlear implantation were included in this clinical trial. A keyhole access tunnel to the tympanic cavity and targeting the round window was planned based on preoperatively acquired computed tomography image data and robotically drilled to the level of the facial recess. Intraoperative imaging was performed to confirm sufficient distance of the drilling trajectory to relevant anatomy. Robotic drilling continued toward the round window. The cochlear access was manually created by the surgeon. Electrode arrays were inserted through the keyhole tunnel under microscopic supervision via a tympanomeatal flap. All patients were successfully implanted with a cochlear implant. In 9 of 9 patients the robotic drilling was planned and performed to the level of the facial recess. In 3 patients, the procedure was reverted to a conventional approach for safety reasons. No change in facial nerve function compared to baseline measurements was observed. Robotic keyhole access for cochlear implantation is feasible. Further improvements to workflow complexity, duration of surgery, and usability including safety assessments are required to enable wider adoption of the procedure. [ABSTRACT FROM AUTHOR]

The robustness of motor outputs to muscle dysfunction has been investigated using musculoskeletal modeling, but with conflicting results owing to differences in model complexity and motor tasks. Our objective was to systematically study how the number of kinematic degrees of freedom, and the number of independent muscle actuators alter the robustness of motor output to muscle dysfunction. We took a detailed musculoskeletal model of the human leg and systematically varied the model complexity to create six models with either 3 or 7 kinematic degrees of freedom and either 14, 26, or 43 muscle actuators. We tested the redundancy of each model by quantifying the reduction in sagittal plane feasible force set area when a single muscle was removed. The robustness of feasible force set area to the loss of any single muscle, i.e. general single muscle loss increased with the number of independent muscles and decreased with the number of kinematic degrees of freedom, with the robust area varying from 1% and 52% of the intact feasible force set area. The maximum sensitivity of the feasible force set to the loss of any single muscle varied from 75% to 26% of the intact feasible force set area as the number of muscles increased. Additionally, the ranges of feasible muscle activation for maximum force production were largely unconstrained in many cases, indicating ample musculoskeletal redundancy even for maximal forces. We propose that ratio of muscles to kinematic degrees of freedom can be used as a rule of thumb for estimating musculoskeletal redundancy in both simulated and real biomechanical systems. [ABSTRACT FROM AUTHOR]

Humans can easily describe, imagine, and, crucially, predict a wide variety of behaviors of liquids—splashing, squirting, gushing, sloshing, soaking, dripping, draining, trickling, pooling, and pouring—despite tremendous variability in their material and dynamical properties. Here we propose and test a computational model of how people perceive and predict these liquid dynamics, based on coarse approximate simulations of fluids as collections of interacting particles. Our model is analogous to a “game engine in the head”, drawing on techniques for interactive simulations (as in video games) that optimize for efficiency and natural appearance rather than physical accuracy. In two behavioral experiments, we found that the model accurately captured people’s predictions about how liquids flow among complex solid obstacles, and was significantly better than two alternatives based on simple heuristics and deep neural networks. Our model was also able to explain how people’s predictions varied as a function of the liquids’ properties (e.g., viscosity and stickiness). Together, the model and empirical results extend the recent proposal that human physical scene understanding for the dynamics of rigid, solid objects can be supported by approximate probabilistic simulation, to the more complex and unexplored domain of fluid dynamics. [ABSTRACT FROM AUTHOR]

When the unmanned aerial vehicle (UAV) is used for aerial spraying, the downwash airflow generated by the UAV rotor will interact with the crop canopy and form a conical vortex shape in the crop plant. The size of the vortex will directly affect the outcome of the spraying operation. Six one-way spraying were performed by the UAV in a rice field with different but random flying altitude and velocities within the optimal operational range to form different vortex patterns. The spraying reagent was clear water, which was collected by water sensitive paper (WSP), and then the WSP was analyzed to study the droplets deposition effects in different vortex states. The results showed that the formation of the vortex significantly influenced the droplet deposition. To be specific, the droplet deposition amount in the obvious-vortex (OV) state was about 1.5 times of that in the small-scale (SV) vortex state, and 7 times of that in the non-vortex (NV) state. In the OV state, the droplets mainly deposited directly below and on both sides of the route. The deposition amount, coverage rate and droplet size increased from top to bottom of the crops with the deposition amount, coverage rate, and volume median diameter (VMD) ranging 0.204–0.470 μL/cm2, 3.31%-7.41%, and 306–367μm, respectively. In the SV state, droplets mainly deposited in the vortex area directly below the route. The deposition amount in the downwind direction was bigger than that in the upwind direction. The maximum of deposition amount, coverage rate and droplet size were found in the middle layer of the crops, the range are 0.177–0.334μL/cm2, 2.71%-5.30%, 295–370μm, respectively. In the NV state, the droplet mainly performed drifting motion, and the average droplet deposition amount in the downwind non-effective region was 29.4 times of that in the upwind non-effective region and 8.7 times of the effective vortex region directly below the route. The maximum of deposition amount, coverage rate and droplet size appeared in the upper layer of the crop, the range are 0.006–0.132μL/cm2, 0.17%-1.82%, 120–309μm, respectively, and almost no droplet deposited in the middle and lower part of the crop. The coefficient of variation (CV) of the droplet deposition amount was less than 40% in the state of obvious-vortex and small-scale vortex, and the worst penetration appeared in the non-vortex amounting to 65.97%. This work offers a basis for improving the spraying performance of UAV. [ABSTRACT FROM AUTHOR]

The primary objective of the study was to determine the effect of process conditions on extraction efficiency and the total amount of released polyphenols and antioxidant activity (AA) in black chokeberry juice. The study samples were fruits of black chokeberry (Aronia melanocarpa (Michx.) Elliott) cv. Galicjanka. In the study, two kinds of presses—piston press and twin gear juice extractor—were used, and two raw material pretreatment methods—freezing and thawing and enzymatic liquefaction—were applied. The study showed that pressing efficiency depends on the design of press and the nature of pretreatment. The highest pressing efficiency was obtained using the twin gear juice extractor. Enzymatic liquefaction of shredded fruits significantly increased the efficiency of pressing by the piston press. The type of press and the pretreatment method used had an effect on the quality traits of the extracted juices. The highest content of soluble solids was obtained for fruits not subjected to any pretreatment and pressed using the twin gear press. The highest total phenolic content was obtained in juice extracted using the piston press from shredded fruits subjected to enzymatic treatment at 45°C. A higher total phenolic content was also a characteristic of juice obtained from fruits not subjected to any pretreatment and extracted using the twin gear press. The capacity of the black chokeberry juices for free radical quenching oscillated around the level of approximately 90%. The study showed that the application of suitable processing methods is necessary for the acquisition of products with desirable quality traits. [ABSTRACT FROM AUTHOR]

The snow crab (Chioneocetes opilio) fishery in the Barents Sea is carried out by large offshore vessels, as the fishing grounds are located far from shore and the gear must be transported back and forth over long distances. Therefore, fishers use stackable conical pots that allow large numbers of pots to be carried on deck for each trip. One of the drawbacks of using stackable pots is that the entrance is at the vertex of the conical pot, which fishers claim does not provide the desired fishing efficiency. Thus, the goal of this study was to determine whether a different pot design would improve the catch efficiency of snow crabs. We investigated the efficiency of a new type of pot called the moon pot, which provides continuous increased bait odour intensity as snow crabs make their way towards the entrance of the pot. This alteration was expected to increase catch efficiency compared to that of the conical pots used by the fleet today. However, experimental fishing results showed that the modified pots had significantly lower catch efficiency than the standard conical pots, as only ~66% of the number of crabs caught by the conical pots were caught in the moon pots. The main reason for this reduced catch efficiency likely was the initial steepness of the moon pot, which may have made it difficult for crabs to reach the pot entrance. These results demonstrated that pot design can dramatically affect catch efficiency of snow crabs. [ABSTRACT FROM AUTHOR]

The Complexity-entropy causality plane (CECP) is a parsimonious representation space for time series. It has only two dimensions: normalized permutation entropy () and Jensen-Shannon complexity () of a time series. This two-dimensional representation allows for detection of slow or rapid drifts in the condition of mechanical components monitored through sensor measurements. The CECP representation can be used for both predictive analytics and visual monitoring of changes in component condition. This method requires minimal pre-processing of raw signals. Furthermore, it is insensitive to noise, stationarity, and trends. These desirable properties make CECP a good candidate for machine condition monitoring and fault diagnostics. In this work we study the effectiveness of CECP on three rotary component condition assessment applications. We use CECP representation of vibration signals to differentiate various machine component health conditions for rotary machine components, namely roller bearing and gears. The results confirm that the CECP representation is able to detect, with high accuracy, changes in underlying dynamics of machine component degradation states. From class separability perspective, the CECP representation is able to generate linearly separable classes for the classification of different fault states. This classification performance improves with increasing signal length. For signal length of 16,384 data points, the fault classification accuracy varies from 90% to 100% for bearing applications, and from 85% to 100% for gear applications. We observed that the optimum parameter for CECP representatino depends on the application. For bearing applications we found that embedding dimension D = 4, 5, 6, and embedding delay τ = 1, 2, 3 are suitable for good fault classification. For gear applications we find that embedding dimension D = 4, 5, and embedding delay τ = 1, 5 are suitable for fault classification. [ABSTRACT FROM AUTHOR]

Bioinformatics research is frequently performed using complex workflows with multiple steps, fans, merges, and conditionals. This complexity makes management of the workflow difficult on a computer cluster, especially when running in parallel on large batches of data: hundreds or thousands of samples at a time. Scientific workflow management systems could help with that. Many are now being proposed, but is there yet the “best” workflow management system for bioinformatics? Such a system would need to satisfy numerous, sometimes conflicting requirements: from ease of use, to seamless deployment at peta- and exa-scale, and portability to the cloud. We evaluated Swift/T as a candidate for such role by implementing a primary genomic variant calling workflow in the Swift/T language, focusing on workflow management, performance and scalability issues that arise from production-grade big data genomic analyses. In the process we introduced novel features into the language, which are now part of its open repository. Additionally, we formalized a set of design criteria for quality, robust, maintainable workflows that must function at-scale in a production setting, such as a large genomic sequencing facility or a major hospital system. The use of Swift/T conveys two key advantages. (1) It operates transparently in multiple cluster scheduling environments (PBS Torque, SLURM, Cray aprun environment, etc.), thus a single workflow is trivially portable across numerous clusters. (2) The leaf functions of Swift/T permit developers to easily swap executables in and out of the workflow, which makes it easy to maintain and to request resources optimal for each stage of the pipeline. While Swift/T’s data-level parallelism eliminates the need to code parallel analysis of multiple samples, it does make debugging more difficult, as is common for implicitly parallel code. Nonetheless, the language gives users a powerful and portable way to scale up analyses in many computing architectures. The code for our implementation of a variant calling workflow using Swift/T can be found on GitHub at , with full documentation provided at . [ABSTRACT FROM AUTHOR]

Numerical simulations have been used in this paper to study the propulsion device of a wave glider based on an oscillating hydrofoil, in which the profile of the pitching and heaving motion have been prescribed for the sake of simplicity. A grid model for a two-dimensional NACA0012 hydrofoil was built by using the dynamic and moving mesh technology of the Computational Fluid Dynamics (CFD) software FLUENT and the corresponding mathematical model has also been established. First, for the sinusoidal pitching, the effects of the pitching amplitude and the reduced frequency were investigated. As the reduced frequency increased, both the mean output power coefficient and the optimal pitching amplitude increased. Then non-sinusoidal pitching was studied, with a gradual change from a sinusoid to a square wave as the value of β was increased from 1. It was found that when the pitching amplitude was small, the trapezoidal pitching profile could indeed improve the mean output power coefficient of the flapping foil. However, when the pitching amplitude was larger than the optimal value, the non-sinusoidal pitching motion negatively contributed to the propulsion performance. Finally, the overall results suggested that a trapezoidal-like pitching profile was effective for the oscillating foil of a wave glider when the pitching amplitude was less than the optimal value. [ABSTRACT FROM AUTHOR]

Humanoid robots will become part of our everyday lives. They have biologically inspired features and psychologically complex properties. How will children interpret these ambiguous objects, discriminating between living and nonliving kinds? Do the biologically and psychologically inspired characteristics affect children’s understanding of the robots? How firm is the distinction that children make between living and nonliving objects? To address these questions, 120 children ranging three to five years initially viewed video clips that depicted humanoid robots interacting with a human experimenter on two different dimensions (mobility and, psychologically contingent behavior). The subjects then answered simple questions that probed their animacy judgments and property projections about the robot. The results showed that children’s animacy assessments about humanoid robots differed by age. When judging the robot’s life status, its mobility was important for four-year-olds and, the psychological contingency for five-year-olds. In terms of the robot’s reasoning abilities, the majority of four-year-old children clearly understood biological properties, regardless of the robots’ features. However, when reasoning about psychological properties, even five-year-olds occasionally relied on robots’ features such as their contingent behaviors. Moreover, the children attributed some but not all animate properties to the robots. Although rent findings show that children possess naïve theories, they do not seem to have a consistent and logical theory of “aliveness,” and they apparently develop the concept of a robot by acquiring knowledge about how this boundary object differs from living entities. [ABSTRACT FROM AUTHOR]

Technological breakthroughs in the past two decades have ushered in a new era of biomedical research, turning it into an information-rich and technology-driven science. This scientific revolution, though evident to the research community, remains opaque to nonacademic audiences. Such knowledge gaps are likely to persist without revised strategies for science education and public outreach. To address this challenge, we developed a unique outreach program to actively engage over 100 high-school students in the investigation of multidrug-resistant bacteria. Our program uses robotic automation and interactive web-based tools to bridge geographical distances, scale up the number of participants, and reduce overall cost. Students and teachers demonstrated high engagement and interest throughout the project and valued its unique approach. This educational model can be leveraged to advance the massive open online courses movement that is already transforming science education. [ABSTRACT FROM AUTHOR]

Object handovers between humans are common in our daily life but the mechanisms underlying handovers are still largely unclear. A good understanding of these mechanisms is important not only for a better understanding of human social behaviors, but also for the prospect of an automatized society in which machines will need to perform similar objects exchanges with humans. In this paper, we analyzed how humans determine the location of object transfer during handovers- to determine whether they can predict the preferred handover location of a partner, the variation of this prediction in 3D space, and to examine how much of a role vision plays in the whole process. For this we developed a paradigm that allows us to compare handovers by humans with and without on-line visual feedback. Our results show that humans have the surprising ability to modulate their handover location according to partners they have just met such that the resulting handover errors are in the order of few centimeters, even in the absence of vision. The handover errors are least along the axis joining the two partners, suggesting a limited role for visual feedback in this direction. Finally, we show that the handover locations are explained very well by a linear model considering the heights, genders and social dominances of the two partners, and the distance between them. We developed separate models for the behavior of ‘givers’ and ‘receivers’ and discuss how the behavior of the same individual changes depending on his role in the handover. [ABSTRACT FROM AUTHOR]

Since biotechnological research becomes more and more important for industrial applications, there is an increasing need for scalable and controllable laboratory procedures. A widely used approach in biotechnological research to improve the performance of a process is to vary the growth rates in order to find the right balance between growth and the production. This can be achieved by the application of a suitable feeding strategy. During this initial bioprocess development, it is beneficial to have at hand cheap and easy setups that work in parallel (e.g. in shaking flasks). Unfortunately, there is a gap between these easy setups and defined and controllable processes, which are necessary for up-scaling to an industrial relevant volume. One prerequisite to test and evaluate different process strategies apart from batch-mode is the availability of pump systems that allow for defined feeding profiles in shaking flasks. To our knowledge, there is no suitable dosing device on the market which fulfils the requirements of being cheap, precise, programmable, and parallelizable. Commercially available dosing units are either already integrated in bioreactors and therefore inflexible, or not programmable, or expensive, or a combination of those. Here, we present a LEGO-MINDSTORMS-based syringe pump, which has the potential of being widely used in daily laboratory routine due to its low price, programmability, and parallelisability. The acquisition costs do not exceed 350 € for up to four dosing units, that are independently controllable with one EV3 block. The system covers flow rates ranging from 0.7 μL min-1 up to 210 mL min-1 with a reliable flux. One dosing unit can convey at maximum a volume of 20 mL (using all 4 units even up to 80 mL in total) over the whole process time. The design of the dosing unit enables the user to perform experiments with up to four different growth rates in parallel (each measured in triplicates) per EV3-block used. We estimate, that the LEGO-MINDSTORMS-based dosing unit with 12 syringes in parallel is reducing the costs up to 50-fold compared to a trivial version of a commercial pump system (~1500 €) which fits the same requirements. Using the pump, we set the growth rates of a E. coli HMS174/DE3 culture to values between 0.1 and 0.4 h-1 with a standard deviation of at best 0.35% and an average discrepancy of 13.2%. Additionally, we determined the energy demand of a culture for the maintenance of the pTRA-51hd plasmid by quantifying the changes in biomass yield with different growth rates set. Around 25% of total substrate taken up is used for plasmid maintenance. To present possible applications and show the flexibility of the system, we applied a constant feed to perform microencapsulation of Pseudomonas putida and an individual dosing profile for the purification of a his-tagged eGFP via IMAC. This smart and versatile dosing unit, which is ready-to-use without any prior knowledge in electronics and control, is affordable for everyone and due to its flexibility and broad application range a valuable addition to the laboratory routine. [ABSTRACT FROM AUTHOR]

Behavior is characterized by sequences of goal oriented conducts, such as food uptake, socializing and resting. Classically, one would define for each task a corresponding satisfaction level, with the agent engaging, at a given time, in the activity having the lowest satisfaction level. Alternatively, one may consider that the agent follows the overarching objective to generate sequences of distinct activities. To achieve a balanced distribution of activities would then be the primary goal, and not to master a specific task. In this setting the agent would show two types of behaviors, task-oriented and task-searching phases, with the latter interseeding the former. We study the emergence of autonomous task switching for the case of a simulated robot arm. Grasping one of several moving objects corresponds in this setting to a specific activity. Overall, the arm should follow a given object temporarily and then move away, in order to search for a new target and reengage. We show that this behavior can be generated robustly when modeling the arm as an adaptive dynamical system. The dissipation function is in this approach time dependent. The arm is in a dissipative state when searching for a nearby object, dissipating energy on approach. Once close, the dissipation function starts to increase, with the eventual sign change implying that the arm will take up energy and wander off. The resulting explorative state ends when the dissipation function becomes again negative and the arm selects a new target. We believe that our approach may be generalized to generate self-organized sequences of activities in general. [ABSTRACT FROM AUTHOR]

Technology evolution describes a change in a technology performance over time. The modeling of technology evolution is crucial for designers, entrepreneurs, and government officials to set reasonable R&D targets, invest in promising technology, and develop effective incentive policies. Scientists and engineers have developed several mathematical functions such as logistic function and exponential function (Moore’s Law) to model technology evolution. However, these models focus on how a technology evolves in isolation and do not consider how the technology interacts with other technologies. Here, we extend the Lotka-Volterra equations from community ecology to model a technology ecosystem with system, component, and fundamental layers. We model the technology ecosystem of passenger aircraft using the Lotka-Volterra equations. The results show limited trickle-down effect in the technology ecosystem, where we refer to the impact from an upper layer technology to a lower layer technology as a trickle-down effect. The limited trickle-down effect suggests that the advance of the system technology (passenger aircraft) is not able to automatically promote the performance of the component technology (turbofan aero-engine) and the fundamental technology (engine blade superalloy) that constitute the system. Our research warns that it may not be effective to maintain the prosperity of a technology ecosystem through government incentives on system technologies only. Decision makers should consider supporting the innovations of key component or fundamental technologies. [ABSTRACT FROM AUTHOR]

A robust and stratified pre-clinical natural knee model, which has the capability to more appropriately simulate the biomechanical environment in vivo, will deliver more efficient and reliable assessment of soft tissue interventions before clinical studies. In order to simulate the biomechanical function of the natural knee without the natural ligaments in place, there is a requirement to develop appropriate spring constraints for the natural knee model. Therefore, this study was to investigate the effect of spring constraints on the function and output of the natural porcine knee model, and determine the spring constraint which most closely replicated the function of the natural ligaments. Two linear compression springs with stiffnesses of 9 N/mm (spring-9) and 20 N/mm (spring-20) were set at different free lengths in the anterior-posterior (A/P) axis in a natural knee simulator. The kinematic (A/P displacement) and tribological properties (shear force) output of the simulator were compared at different spring settings. The most appropriate spring setting was determined by comparing the A/P displacement and shear force output at different spring settings with those of the all ligaments model. Spring-9 with a free length of 4 mm showed the minimal difference (-0.03±0.68 mm) in A/P displacement output and spring-20 with a free length of 5 mm showed the minimal difference (-0.10±0.73 mm) in A/P displacement output compared to the all ligament control. There was no statistical difference between the two minimal differences either in A/P displacement or in shear force (paired t-test, p = 0.58, and p = 0.68 respectively) when both spring settings matched most closely to the A/P kinematics of the intact knee. This indicated that both conditions were appropriate spring constraints settings in the A/P direction for the natural porcine knee model. [ABSTRACT FROM AUTHOR]

The inclusion of an allograft wedge during medial opening wedge high tibial osteotomy has been shown to lead to satisfactory time-to-union in larger corrections (>10°). Such large corrections are associated with greater incidences of intraoperative hinge fracture and reduced construct stability. The purpose of this study was to investigate the biomechanical stability that an allograft wedge brings to an osteotomy. Ten medium-size fourth generation artificial sawbone tibiae underwent 12 mm biplanar medial opening wedge high tibial osteotomy with a standard Tomofix plate. Five tibiae had an allograft wedge inserted into the osteotomy gap prior to plate fixation (allograft group). The gap in the remaining tibiae was left unfilled (control group). Each group underwent static compression testing and cyclical fatigue testing until failure of the osteotomy. Peak force, valgus malrotation, number of cycles, displacement and stiffness around the tibial head were analysed. Intraoperative hinge fractures occurred in all specimens. Under static compression, the allograft group withstood higher peak forces (6.01 kN) compared with the control group (5.12 kN). Valgus malrotation was lower, and stiffness was higher, in the allograft group. During cyclical fatigue testing, results within the allograft group were more consistent than within the control group. This may indicate more predictable results in large osteotomies with an allograft. Tibial osteotomies with allograft wedges appear beneficial for larger corrections, and in cases of intraoperative hinge fracture, due to the added construct stability they provide, and the consistency of results compared with tibial osteotomies without a graft. [ABSTRACT FROM AUTHOR]

Hyaluronic acid injections have been a mainstay of arthritis treatment for decades. However, much controversy remains about their clinical efficacy and their potential mechanism of action. This approach to arthritis therapy is often called viscosupplementation, a term which is rooted in the elevated viscosity of the injected solutions. This terminology also suggests a mechanical pathway of action and further implies that their efficacy is dependent on viscosity. Notably, previous studies of the relationship between viscous properties of hyaluronic acid solutions and their clinical efficacy have not been definitive. Recently we developed an experimental and analytical framework for studying cartilage lubrication that captures the Stribeck-like behavior of cartilage in an elastoviscous transition curve. Here we apply this framework to study the lubricating behavior of six hyaluronan products currently used for injectable arthritis therapy in the US. Despite the fact that the source and chemical modifications endow these products with a range of lubricating properties, we show that the lubricating effect of all of these materials can be described by this Stribeck-like elastoviscous transition. Fitting this data to the elastoviscous transition model enables the calculation of effective lubricating viscosities for each material, which differ substantially from the viscosities measured using standard rheometry. Further we show that while data from standard rheometry are poor predictors of clinical performance of these materials, measurements of friction coefficient and effective lubricating viscosity correlate well (R2 = 0.77; p < 0.005) with assessments of improved clinical function reported previously. This approach offers both a novel method that can be used to evaluate potential clinical efficacy of hyaluronic acid formulations and provide new insight on their mode of action. [ABSTRACT FROM AUTHOR]

Animal movement encodes information that is meaningfully interpreted by natural counterparts. This is a behavior that roboticists are trying to replicate in artificial systems but that is not well understood even in natural systems. This paper presents a count on the cardinality of a discretized posture space—an aspect of expressivity—of articulated platforms. The paper uses an information-theoretic measure, Shannon entropy, to create observations analogous to Moore’s Law, providing a measure that complements traditional measures of the capacity of robots. This analysis, applied to a variety of natural and artificial systems, shows trends in increasing capacity in both internal and external complexity for natural systems while artificial, robotic systems have increased significantly in the capacity of computational (internal) states but remained more or less constant in mechanical (external) state capacity. The quantitative measure proposed in this paper provides an additional lens through which to compare natural and artificial systems. [ABSTRACT FROM AUTHOR]

In this paper, we propose an Emotional Trigger System to impart an automatic emotion expression ability within the humanoid robot REN-XIN, in which the Emotional Trigger is an emotion classification model trained from our proposed Word Mover’s Distance(WMD) based algorithm. Due to the long time delay of the WMD-based Emotional Trigger System, we propose an enhanced Emotional Trigger System to enable a smooth interaction with the robot in which the Emotional Trigger is replaced by a conventional convolution neural network and a long short term memory network (CNN_LSTM)-based deep neural network. In our experiments, the CNN_LSTM based model only need 10 milliseconds or less to finish the classification without a decrease in accuracy, while the WMD-based model needed approximately 6-8 seconds to give a result. In this paper, the experiments are conducted based on the same sub-data sets of the Chinese emotional corpus(Ren_CECps) used in former WMD experiments: one comprises 50% data for training and 50% for testing(1v1 experiment), and the other comprises 80% data for training and 20% for testing(4v1 experiment). The experiments are conducted using WMD, CNN_LSTM, CNN and LSTM. The results show that CNN_LSTM obtains the best F1 score (0.35) in the 1v1 experiment and almost the same accuracy of F1 scores (0.366 vs 0.367) achieved by WMD in the 4v1 experiment. Finally, we present demonstration videos with the same scenario to show the performance of robot control driven by CNN_LSTM-based Emotional Trigger System and WMD-based Emotional Trigger System. To improve the comparison, total manual-control performance is also recorded. [ABSTRACT FROM AUTHOR]

Complex Regional Pain Syndrome (CRPS) is characterized by pain, motor and inflammatory symptoms usually affecting one limb. Cognitive difficulties have been reported to affect patients’ ability to represent, perceive and use their affected limb. It is debated whether these difficulties result from deficits in controlling goal-directed movements in space or from a learned strategy to protect the affected limb. In order to dissociate the two hypotheses, patients with upper-limb CRPS were asked to move with their unaffected hand towards visual targets projected at different positions on a horizontal semi-reflexive mirror. By means of a robotic handle placed below the screen, they were asked to move a cursor, to reach and cross lines at their estimated midpoint. In some of the stimulation series, the affected hand was placed below the mirror so that some lines appeared projected onto that hand. Vision of the hands and the robotic handle was preserved or prevented by opening or closing a shutter below the mirror. Lines were displayed on the mirror according to which part of the body was affected (ispi- vs. contralateral) and the actual position of the affected hand (inside vs. outside the workspace). Comparatively to control participants, CRPS patients generally biased their estimation by bisecting the lines towards their left side, irrelative of which part of the body was affected and the position of the affected hand, both in ipsi- and contralateral space, with only a few exceptions. Our results are in line with previous studies having described a visuospatial deficit in CRPS patients and discard the explanation of observed symptoms in terms of learned nonuse strategies, as only the unaffected hand was used to perform the task. It is suggested that CRPS patients can display difficulties to perform tasks requesting visuo-motor coordination, reflecting the complex cortical reorganization occurring in CRPS. [ABSTRACT FROM AUTHOR]

In recent years, safety issues surrounding robots have increased in importance, as more robots are in close contact with humans, both in industrial fields and elsewhere. Safety standards for industrial robots operating in specific spaces have been established, but no such standards have been specified for collaborative and service robots. To establish safety standards for such robots, we assessed pressure pain thresholds for collisions between humans and robots, under the assumption that the pain threshold is lower than the mild injury threshold. The pressure pain threshold for collision with a robot was measured in 90 male Korean adults using a homemade collision system. The pain thresholds were measured three times at 15 sites, including the forehead. The highest threshold was 196.1 ± 85.8 N/cm2 at the back of the hand, and the lowest was 65.1 ± 22.6 N/cm2 at an arm nerve. Moderate thresholds, i.e., 100–120 N/cm2, were noted on the forehead, neck muscle, ball of the thumb, and shin. The thresholds of participants < 30 years of age were lower, by 3–33%, than those of participants aged > 30 years. Thresholds differed by body mass index only at certain sites, including the shoulder joint, neck, and back of the hand. The pressure pain threshold depended on individual characteristics, body site, and age. The threshold relevant to potential human-robot collisions was determined to be between 65.1 ± 22.6 and 196.1 ± 85.8 N/cm2. [ABSTRACT FROM AUTHOR]

In the carrier-based coverage repair problem, a single mobile robot replaces damaged sensors by picking up spare ones in the region of interest or carrying them from a base station in wireless sensor and robot networks. The objective is to find the shortest path of the robot. The problem is an extension of the traveling salesman problem (TSP). Thus, it is also called the one-commodity traveling salesman problem with selective pickup and delivery (1-TSP-SELPD). In order to solve this problem in a larger sensor distribution scenario more efficiently, we propose a two-stage approach in this paper. In the first stage, the mature and effective Lin–Kernighan–Helsgaun (LKH) algorithm is used to form a Hamiltonian cycle for all delivery nodes, which is regarded as a heuristic for the second stage. In the second stage, elliptical regions are set for selecting pickup nodes‚ and an edge-ordered list (candidate edge list, CEL) is constructed to provide major axes for the ellipses. The process of selecting pickup nodes and constructing the CEL is repeated until all the delivery nodes are visited. The final CEL stores a feasible solution. To update it, three operations—expansion, extension, and constriction—are applied to the CEL. The experimental results show that the proposed method reduces the computing time and achieves better results in higher-dimensional problems, which may facilitate the provision of solutions for more complicated sensor networks and can contribute to the development of effective and efficient algorithms for the one-commodity pickup-and-delivery traveling salesman problem (1-PDTSP). [ABSTRACT FROM AUTHOR]

A reasonable micro-pits texture has been initially proved that it can improve friction characteristics between wood and cemented carbide surface and reduce surface friction coefficient. In order to study the cutting performance of the micro-texture when it is applied to the cutting tool for cutting wood more effectively, this paper selected micro-pit texture for studying influence of surface micro-texture cutting tool on wood cutting performance and cutting temperature, finding that when micro-pit cemented carbide cutting tool is adopted for turning the northeast China ash (Fraxinus spp.), it can reduce cutting force of turning and surface friction coefficient between rake face and cuttings. Moreover, for type A and type B cutting tools, when the texture parameters are that the diameter of the micro-pit is 80μm, the depth of the micro pit is: 10μm, area occupancy is 20% and the diameter of the micro-pit is 120μm, the depth of the micro-pit is 10μm and the area occupancy is 20%, the effect generated is the best. When a texture cutting tool is used for cutting, the decrease of the highest temperature in the cutting area is not very great, but the average temperature in the cutting area changes a lot, which is mainly caused by that micro-texture is processed at a position of the rake face close to the main cutting edge and that the highest temperature of cutting is mainly generated on the contact point between tool tip and wood. A reasonable micro-texture parameter can form a layer of liquid lubricating film on the up and down contact surfaces such that the direct contact between cemented carbide and northeast China ash is changed into indirect contact between lubricating films formed by the liquid so as to reduce the surface friction coefficient. [ABSTRACT FROM AUTHOR]

Food production in conventional agriculture faces numerous challenges such as reducing waste, meeting demand, maintaining flavor, and providing nutrition. Contained environments under artificial climate control, or cyber-agriculture, could in principle be used to meet many of these challenges. Through such environments, phenotypic expression of the plant—mass, edible yield, flavor, and nutrients—can be actuated through a “climate recipe,” where light, water, nutrients, temperature, and other climate and ecological variables are optimized to achieve a desired result. This paper describes a method for doing this optimization for the desired result of flavor by combining cyber-agriculture, metabolomic phenotype (chemotype) measurements, and machine learning. In a pilot experiment, (1) environmental conditions, i.e. photoperiod and ultraviolet (UV) light (known to affect production of flavor-active molecules in edible plants) were applied under different regimes to basil plants (Ocimum basilicum) growing inside a hydroponic farm with an open-source design; (2) flavor-active volatile molecules were measured in each plant using gas chromatography-mass spectrometry (GC-MS); and (3) symbolic regression was used to construct a surrogate model of this chemistry from the input environmental variables, and this model was used to discover new combinations of photoperiod and UV light to increase this chemistry. These new combinations, or climate recipes, were then implemented in the hydroponic farm, and several of them resulted in a marked increase in volatiles over control. The process also led to two important insights: it demonstrated a “dilution effect”, i.e. a negative correlation between weight and desirable chemical species, and it discovered the surprising effect that a 24-hour photoperiod of photosynthetic-active radiation, the equivalent of all-day light, induces the most flavor molecule production in basil. In this manner, surrogate optimization through machine learning can be used to discover effective recipes for cyber-agriculture that would be difficult and time-consuming to find using hand-designed experiments. [ABSTRACT FROM AUTHOR]

In the study of balance and postural control the (Single) Inverted Pendulum model (SIP) has been taken for a long time as an acceptable paradigm, with the implicit assumption that only ankle rotations are relevant for describing and explaining sway movements. However, more recent kinematic analysis of quiet standing revealed that hip motion cannot be neglected at all and that ankle-hip oscillatory patterns are characterized by complex in-phase and anti-phase interactions, suggesting that the SIP model should be substituted by a DIP (Double Inverted Pendulum) model. It was also suggested that DIP control could be characterized as a kind of optimal bi-axial active controller whose goal is minimizing the acceleration of the global CoM (Center of Mass). We propose here an alternative where active feedback control is applied in an intermittent manner only to the ankle joint, whereas the hip joint is stabilized by a passive stiffness mechanism. The active control impulses are delivered to the ankle joint as a function of the delayed state vector (tilt rotation angle + tilt rotational speed) of a Virtual Inverted Pendulum (VIP), namely a pendulum that links the ankle to the CoM, embedded in the real DIP. Simulations of such DIP/VIP model, with the hybrid control mechanism, show that it can reproduce the in-phase/anti-phase interaction patterns of the two joints described by several experimental studies. Moreover, the simulations demonstrate that the DIP/VIP model can also reproduce the measured minimization of the CoM acceleration, as an indirect biomechanical consequence of the dynamic interaction between the active control of the ankle joint and the passive control of the hip joint. We suggest that although the SIP model is literally false, because it ignores the ankle-hip coordination, it is functionally correct and practically acceptable for experimental studies that focus on the postural oscillations of the CoM. [ABSTRACT FROM AUTHOR]

This study introduces a new method to understand how added load affects human performance across a broad range of athletic tasks (ten obstacles) embedded in an outdoor obstacle course. The method employs an array of wearable inertial measurement units (IMUs) to wirelessly record the movements of major body segments to derive obstacle-specific metrics of performance. The effects of load are demonstrated on (N = 22) participants who each complete the obstacle course under four conditions including unloaded (twice) and with loads of 15% and 30% of their body weight (a total of 88 trials across the group of participants). The IMU-derived performance metrics reveal marked degradations in performance with increasing load across eight of the ten obstacles. Overall, this study demonstrates the significant potential in using this wearable technology to evaluate human performance across multiple tasks and, simultaneously, the adverse effects of body-borne loads on performance. The study addresses a major need of military organizations worldwide that frequently employ standardized obstacle courses to understand how added loads influence warfighter performance. Importantly, the findings and conclusions drawn from IMU data would not be possible using traditional timing metrics used to evaluate task performance. [ABSTRACT FROM AUTHOR]

Vocal fold fibroblasts (VFF) constitute the main cell type of the vocal fold’s lamina propria, produce the extracellular matrix and thereby determine the tissue characteristics. To study VFF behavior under in vitro conditions it is important to mimic the dynamic environment of the in vivo state. The aim of our study was to develop and validate a novel phonomimetic bioreactor system mainly based on commercially available components. The use of cell culture dishes with flexible silicone bottoms in combination with a suitable loudspeaker made it possible to expose the cells to various kinds of phonatory stimuli. The fundamental vibration characteristics of silicone membranes were investigated with and without cell culture medium by laser Doppler vibrometry. Human VFF were seeded in flexible-bottomed plates and placed in a custom-made housing containing a loudspeaker. After the cells were exposed to a predefined audio stimulation protocol, cell viability was assessed and gene as well as protein expression levels were compared to static controls. Laser Doppler vibrometry revealed that addition of cell culture medium changed the resonance frequencies of vibrating membranes. Gene expression of hyaluronan synthase 2, collagen III, fibronectin and TGFβ-1 was significantly upregulated in VFF exposed to vibration, compared to static control. Vibration also significantly upregulated collagen I gene and protein expression. We present a new type of phonomimetic bioreactor. Compared to previous models, our device is easy to assemble and cost-effective, yet can provide a wide spectrum of phonatory stimuli based on the entire dynamic range of the human voice. Gene expression data of VFF cultured in our phonomimetic bioreactor show a significant effect of vibration on ECM metabolism, which illustrates the efficacy of our device. [ABSTRACT FROM AUTHOR]

A fundamental question in human motor neuroscience is to determine how the nervous system generates goal-directed movements despite inherent physiological noise and redundancy. Walking exhibits considerable variability and equifinality of task solutions. Existing models of bipedal walking do not yet achieve both continuous dynamic balance control and the equifinality of foot placement humans exhibit. Appropriate computational models are critical to disambiguate the numerous possibilities of how to regulate stepping movements to achieve different walking goals. Here, we extend a theoretical and computational Goal Equivalent Manifold (GEM) framework to generate predictive models, each posing a different experimentally testable hypothesis. These models regulate stepping movements to achieve any of three hypothesized goals, either alone or in combination: maintain lateral position, maintain lateral speed or “heading”, and/or maintain step width. We compared model predictions against human experimental data. Uni-objective control models demonstrated clear redundancy between stepping variables, but could not replicate human stepping dynamics. Most multi-objective control models that balanced maintaining two of the three hypothesized goals also failed to replicate human stepping dynamics. However, multi-objective models that strongly prioritized regulating step width over lateral position did successfully replicate all of the relevant step-to-step dynamics observed in humans. Independent analyses confirmed this control was consistent with linear error correction and replicated step-to-step dynamics of individual foot placements. Thus, the regulation of lateral stepping movements is inherently multi-objective and balances task-specific trade-offs between competing task goals. To determine how people walk in their environment requires understanding both walking biomechanics and how the nervous system regulates movements from step-to-step. Analogous to mechanical “templates” of locomotor biomechanics, our models serve as “control templates” for how humans regulate stepping movements from each step to the next. These control templates are symbiotic with well-established mechanical templates, providing complimentary insights into walking regulation. [ABSTRACT FROM AUTHOR]

The plasticity of the human nervous system allows us to acquire an open-ended repository of sensorimotor skills in adulthood, such as the mastery of tools, musical instruments or sports. How novel sensorimotor skills are learned from scratch is yet largely unknown. In particular, the so-called inverse mapping from goal states to motor states is underdetermined because a goal can often be achieved by many different movements (motor redundancy). How humans learn to resolve motor redundancy and by which principles they explore high-dimensional motor spaces has hardly been investigated. To study this question, we trained human participants in an unfamiliar and redundant visually-guided manual control task. We qualitatively compare the experimental results with simulation results from a population of artificial agents that learned the same task by Goal Babbling, which is an inverse-model learning approach for robotics. In Goal Babbling, goal-related feedback guides motor exploration and thereby enables robots to learn an inverse model directly from scratch, without having to learn a forward model first. In the human experiment, we tested whether different initial conditions (starting positions of the hand) influence the acquisition of motor synergies, which we identified by Principal Component Analysis in the motor space. The results show that the human participants’ solutions are spatially biased towards the different starting positions in motor space and are marked by a gradual co-learning of synergies and task success, similar to the dynamics of motor learning by Goal Babbling. However, there are also differences between human learning and the Goal Babbling simulations, as humans tend to predominantly use Degrees of Freedom that do not have a large effect on the hand position, whereas in Goal Babbling, Degrees of Freedom with a large effect on hand position are used predominantly. We conclude that humans use goal-related feedback to constrain motor exploration and resolve motor redundancy when learning a new sensorimotor mapping, but in a manner that differs from the current implementation of Goal Babbling due to different constraints on motor exploration. [ABSTRACT FROM AUTHOR]

Gender disparity in science, technology, engineering, and math (STEM) fields is an on-going challenge. Gender bias is one of the possible mechanisms leading to such disparities and has been extensively studied. Previous work showed that there was a gender bias in how students perceived the competence of their peers in undergraduate biology courses. We examined whether there was a similar gender bias in a mechanical engineering course. We conducted the study in two offerings of the course, which used different instructional practices. We found no gender bias in peer perceptions of competence in either of the offerings. However, we did see that the offerings’ different instructional practices affected aspects of classroom climate, including: the number of peers who were perceived to be particularly knowledgeable, the richness of the associated network of connections between students, students’ familiarity with each other, and their perceptions about the course environment. These results suggest that negative bias against female students in peer perception is not universal, either across institutions or across STEM fields, and that instructional methods may have an impact on classroom climate. [ABSTRACT FROM AUTHOR]

We propose a method for evolving neural network controllers robust with respect to variations of the environmental conditions (i.e. that can operate effectively in new conditions immediately, without the need to adapt to variations). The method specifies how the fitness of candidate solutions can be evaluated, how the environmental conditions should vary during the course of the evolutionary process, which algorithm can be used, and how the best solution can be identified. The obtained results show how the method proposed is effective and computational tractable. It allows to improve performance on an extended version of the double-pole balancing problem, outperform the best available human-designed controllers on a car racing problem, and generate effective solutions for a swarm robotic problem. The comparison of different algorithms indicates that the CMA-ES and xNES methods, that operate by optimizing a distribution of parameters, represent the best options for the evolution of robust neural network controllers. [ABSTRACT FROM AUTHOR]

Computationally intensive disciplines such as computational biology often require use of a variety of tools implemented in different scripting languages and analysis of large data sets using high-performance computing systems. Although scientific workflow systems can powerfully organize and execute large-scale data-analysis processes, creating and maintaining such workflows usually comes with nontrivial learning curves and engineering overhead, making them cumbersome to use for everyday data exploration and prototyping. To bridge the gap between interactive analysis and workflow systems, we developed Script of Scripts (SoS), an interactive data-analysis platform and workflow system with a strong emphasis on readability, practicality, and reproducibility in daily computational research. For exploratory analysis, SoS has a multilanguage scripting format that centralizes otherwise-scattered scripts and creates dynamic reports for publication and sharing. As a workflow engine, SoS provides an intuitive syntax for creating workflows in process-oriented, outcome-oriented, and mixed styles, as well as a unified interface for executing and managing tasks on a variety of computing platforms with automatic synchronization of files among isolated file systems. As illustrated herein by real-world examples, SoS is both an interactive analysis tool and pipeline platform suitable for different stages of method development and data-analysis projects. In particular, SoS can be easily adopted in existing data analysis routines to substantially improve organization, readability, and cross-platform computation management of research projects. [ABSTRACT FROM AUTHOR]

Aims: Currently minimal research has quantified physical requirement differences in match-play between youth and senior Australian football players. The aim of the current research was to describe and compare the movement profiles and energy cost of youth, sub-elite and elite senior Australian football match-play. Methods: Fifty-seven Australian footballers playing in an elite senior 20, sub-elite senior 16 and elite youth competition 21 participated in this study. Distance, speed based indices and metabolic power measures recording via Global Positioning System (GPS) devices were compared across three competition tiers. Kicks and handballs were collected via a commercial statistics provider (Champion Data) and compared across the competition tiers. Results: Youth players recorded less field time (elite: ES = 1.37/sub-elite: ES = 1.68), total distance (elite: ES = 1.64 /sub-elite: ES = 1.55) and high speed running (elite: ES = 0.90/sub-elite: ES = 0.26) compared to the elite and sub-elite players. The average energy cost of elite (ES = 2.19) and sub-elite (ES = 1.58) match-play was significantly higher that youth match-play. Conclusions: A progressive increase regarding physical demands was evident across AF competition tiers. The findings suggest that sub-elite match-play can provide a viable pathway for youth players to develop physical capacity and technical skills before transitioning to elite senior match-play. [ABSTRACT FROM AUTHOR]

The “noisy labeler problem” in crowdsourced data has attracted great attention in recent years, with important ramifications in citizen science, where non-experts must produce high-quality data. Particularly relevant to citizen science is dynamic task allocation, in which the level of agreement among labelers can be progressively updated through the information-theoretic notion of entropy. Under dynamic task allocation, we hypothesized that providing volunteers with an “I don’t know” option would contribute to enhancing data quality, by introducing further, useful information about the level of agreement among volunteers. We investigated the influence of an “I don’t know” option on the data quality in a citizen science project that entailed classifying the image of a highly polluted canal into “threat” or “no threat” to the environment. Our results show that an “I don’t know” option can enhance accuracy, compared to the case without the option; such an improvement mostly affects the true negative rather than the true positive rate. In an information-theoretic sense, these seemingly meaningless blank votes constitute a meaningful piece of information to help enhance accuracy of data in citizen science. [ABSTRACT FROM AUTHOR]

Acetozolamide-ACZ, carbonic anhydrase inhibitor- is still the most effective systemic drug for glaucoma treatment. Due to its limited ocular bioavailability, topical formulations are not available yet. This study introduces within the framework of nanotechnology three nanopreparations of acetozolamide for topical application, one of them is liposomal phospholipid vehicle and the other two preparations are propolis and Punica granatum (pomegranate). The hypotensive effect of these different nanopreparations in lowering the increased intraocular pressure that was induced in experimental rabbits is monitored for 130 hrs. Structural characteristics of the optic nerve dissected from all involved groups were studied by Fourier transfrom infrared spectroscopy. The obtained results indicate the impact of the topically applied acetozolamide nanopreparations in lowering the intraocular pressure to its normotensive control value. On the other hand, the optic nerve characteristics were found to be dependent on the way acetozolamide introduced. Glaucoma affects structural components that contain OH group and increases β-turns of the protein secondary structure while, reducing the content of both α-helix and Turns. In the same context, liposomal-acetozolamide and propolis nanopreparations protecting the optic nerve protein secondary structure from these changes associated with glaucoma. [ABSTRACT FROM AUTHOR]