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Psychological Research Apr 2023The ability to learn and reproduce sequences is fundamental to every-day life, and deficits in sequential learning are associated with developmental disorders such as...
The ability to learn and reproduce sequences is fundamental to every-day life, and deficits in sequential learning are associated with developmental disorders such as specific language impairment. Individual differences in sequential learning are usually investigated using the serial reaction time task (SRTT), wherein a participant responds to a series of regularly timed, seemingly random visual cues that in fact follow a repeating deterministic structure. Although manipulating inter-cue interval timing has been shown to adversely affect sequential learning, the role of metre (the patterning of salience across time) remains unexplored within the regularly timed, visual SRTT. The current experiment consists of an SRTT adapted to include task-irrelevant auditory rhythms conferring a sense of metre. We predicted that (1) participants' (n = 41) reaction times would reflect the auditory metric structure; (2) that disrupting the correspondence between the learned visual sequence and auditory metre would impede performance; and (3) that individual differences in sensitivity to rhythm would predict the magnitude of these effects. Altering the relationship via a phase shift between the trained visual sequence and auditory metre slowed reaction times. Sensitivity to rhythm was predictive of reaction times over all. In an exploratory analysis, we, moreover, found that approximately half of participants made systematically different responses to visual cues on the basis of the cues' position within the auditory metre. We demonstrate the influence of auditory temporal structures on visuomotor sequential learning in a widely used task where metre and timing are rarely considered. The current results indicate sensitivity to metre as a possible latent factor underpinning individual differences in SRTT performance.
Topics: Humans; Psychomotor Performance; Learning; Reaction Time; Task Performance and Analysis; Cues; Serial Learning
PubMed: 35690927
DOI: 10.1007/s00426-022-01690-y -
Frontiers in Plant Science 2022To solve multiple problems, such as the poor seeding process stability in the conventional finger-clip precision corn seed metering device and the inability to monitor...
To solve multiple problems, such as the poor seeding process stability in the conventional finger-clip precision corn seed metering device and the inability to monitor the seeding effect, a long-belt finger-clip precision seed metering device was optimized and designed. The overall structure and working principle were described, and the mechanism of smooth transport and delivery was analyzed. A diffuse reflection photoelectric sensor and rectangular optical fiber sensor were used to monitor the number of corn seeds in the seeding process, and the states of multiple and miss seeding were calculated. A corn seeding quality monitoring system was designed. In this study, the seed metering performance of the long-belt finger-clip precision seed metering device was compared to that of the conventional finger-clip precision corn seed metering device. It was shown that the reseeding index, the miss-seeding index and the coefficient of variation can be effectively reduced with increasing seed metering tray speed. At the maximum speed of 65r/min, the qualified index increased from 75.75 to 84.70%, the reseeding index decreased from 13.66 to 8.49%, the miss-seeding index decreased from 10.59 to 6.81%, and the coefficient of variation decreased from 20.69 to 6.83%. The variations of these four evaluation parameters with the seed metering tray rotating speed were analyzed. Furthermore, the effects of the seeding frequency and seeding speed on the four evaluation parameters were studied through single factor and variance analyses. The results showed that the relative errors of the qualified index, the reseeding index, the miss-seeding index and the seeding amount increased gradually with the increase in the seed metering tray rotating speed, and the monitoring accuracy of the sensor decreased gradually. The accuracy of sensor monitoring decreased with increasing seeding frequency and seeding speed. This study provides an optimized scheme for the smooth delivery and movement of conventional seed metering devices and provides a technical reference for the development and design of monitoring systems with multiple index and the miss-seeding index of seed metering devices.
PubMed: 35154226
DOI: 10.3389/fpls.2022.814747 -
Sensors (Basel, Switzerland) May 2024Dissolved Oxygen (DO) in water enables marine life. Measuring the prevalence of DO in a body of water is an important part of sustainability efforts because low oxygen...
Dissolved Oxygen (DO) in water enables marine life. Measuring the prevalence of DO in a body of water is an important part of sustainability efforts because low oxygen levels are a primary indicator of contamination and distress in bodies of water. Therefore, aquariums and aquaculture of all types are in need of near real-time dissolved oxygen monitoring and spend a lot of money on purchasing and maintaining DO meters that are either expensive, inefficient, or manually operated-in which case they also need to ensure that manual readings are taken frequently which is time consuming. Hence a cost-effective and sustainable automated Internet of Things (IoT) system for this task is necessary and long overdue. DOxy, is such an IoT system under research and development at Santa Clara University's Ethical, Pragmatic, and Intelligent Computing (EPIC) Laboratory which utilizes cost-effective, accessible, and sustainable Sensing Units (SUs) for measuring the dissolved oxygen levels present in bodies of water which send their readings to a web based cloud infrastructure for storage, analysis, and visualization. DOxy's SUs are equipped with a High-sensitivity Pulse Oximeter meant for measuring dissolved oxygen levels in human blood, not water. Hence a number of parallel readings of water samples were gathered by both the High-sensitivity Pulse Oximeter and a standard dissolved oxygen meter. Then, two approaches for relating the readings were investigated. In the first, various machine learning models were trained and tested to produce a dynamic mapping of sensor readings to actual DO values. In the second, curve-fitting models were used to produce a successful conversion formula usable in the DOxy SUs offline. Both proved successful in producing accurate results.
PubMed: 38794107
DOI: 10.3390/s24103253 -
Journal of Cleaner Production Sep 2022Social distancing policies (SDPs) implemented worldwide in response to COVID-19 pandemic have led to spatiotemporal variations in water demand and wastewater flow,...
Social distancing policies (SDPs) implemented worldwide in response to COVID-19 pandemic have led to spatiotemporal variations in water demand and wastewater flow, creating potential operational and service-related quality issues in water-sector infrastructure. Understanding water-demand variations is especially challenging in contexts with limited availability of smart meter infrastructure, hindering utilities' ability to respond in real time to identified system vulnerabilities. Leveraging water and wastewater infrastructures' interdependencies, this study proposes the use of high-granular wastewater-flow data as a proxy to understand both water and wastewater systems' behaviors during active SDPs. Enabled by a random-effects model of wastewater flow in an urban metropolitan city in Texas, we explore the impacts of various SDPs (e.g., stay home-work safe, reopening phases) using daily flow data gathered between March 19, 2019, and December 31, 2020. Results indicate an increase in residential flow that offset a decrease in nonresidential flow, demonstrating a spatial redistribution of wastewater flow during the stay home-work safe period. Our results show that the three reopening phases had statistically significant relationships to wastewater flow. While this yielded only marginal net effects on overall wastewater flow, it serves as an indicator of behavioral changes in water demand at sub-system spatial scales given demand-flow interdependencies. Our assessment should enable utilities without smart meters in their water system to proactively target their operational response during pandemics, such as (1) monitoring wastewater-flow velocity to alleviate potential blockages in sewer pipes in case of decreased flows, and (2) closely investigating any consequential water-quality problems due to decreased demands.
PubMed: 35813609
DOI: 10.1016/j.jclepro.2022.132962 -
Toxins May 2021Risks of sociality, including competition and conspecific aggression, are particularly pronounced in venomous invertebrates such as arachnids. Spiders show a wide range... (Review)
Review
Risks of sociality, including competition and conspecific aggression, are particularly pronounced in venomous invertebrates such as arachnids. Spiders show a wide range of sociality, with differing levels of cannibalism and other types of social aggression. To have the greatest chance of surviving interactions with conspecifics, spiders must learn to assess and respond to risk. One of the major ways risk assessment is studied in spiders is via venom metering, in which spiders choose how much venom to use based on prey and predator characteristics. While venom metering in response to prey acquisition and predator defense is well-studied, less is known about its use in conspecific interactions. Here we argue that due to the wide range of both sociality and venom found in spiders, they are poised to be an excellent system for testing questions regarding whether and how venom use relates to the evolution of social behavior and, in return, whether social behavior influences venom use and evolution. We focus primarily on the widow spiders, , as a strong model for testing these hypotheses. Given that successful responses to risk are vital for maintaining sociality, comparative analysis of spider taxa in which venom metering and sociality vary can provide valuable insights into the evolution and maintenance of social behavior under risk.
Topics: Animals; Cannibalism; Courtship; Risk Assessment; Social Behavior; Social Learning; Spider Venoms; Spiders
PubMed: 34071320
DOI: 10.3390/toxins13060388 -
Sensors (Basel, Switzerland) Nov 2022In a smart grid communication network, positioning key devices (routers and gateways) is an NP-Hard problem as the number of candidate topologies grows exponentially...
In a smart grid communication network, positioning key devices (routers and gateways) is an NP-Hard problem as the number of candidate topologies grows exponentially according to the number of poles and smart meters. The different terrain profiles impose distinct communication losses between a smart meter and a key device position. Additionally, the communication topology must consider the position of previously installed distribution automation devices (DAs) to support the power grid remote operation. We introduce the heuristic method AIDA (AI-driven AMI network planning with DA-based information and a link-specific propagation model) to evaluate the connectivity condition between the meters and key devices. It also uses the link-received power calculated for the edges of a Minimum Spanning Tree to propose a simplified multihop analysis. The AIDA method proposes a balance between complexity and efficiency, eliminating the need for empirical terrain characterization. Using a spanning tree to characterize the connectivity topology between meters and routers, we suggest a heuristic approach capable of alleviating complexity and facilitating scalability. In our research, the interest is in proposing a method for positioning communication devices that presents a good trade-off between network coverage and the number of communication devices. The existing literature explores the theme by presenting different techniques for ideal device placement. Still rare are the references that meticulously explore real large-scale scenarios or the communication feasibility between meters and key devices, considering the detailed topography between the devices. The main contributions of this work include: (1) The presentation of an efficient AMI planning method with a large-scale focus; (2) The use of a propagation model that does not depend on an empirical terrain classification; and (3) The use of a heuristic approach based on a spanning tree, capable of evaluating a smaller number of connections and, even so, proposing a topology that uses fewer router and gateway positions compared to an approach that makes general terrain classification. Experiments in four real large-scale scenarios, totaling over 230,000 smart meters, demonstrate that AIDA can efficiently provide high-quality connectivity demanding a reduced number of devices. Additional experiments comparing AIDA's detailed terrain-based propagation model to the Erceg-SUI Path Loss model suggest that AIDA can reach the smart meter's coverage with a fewer router positions.
Topics: Electricity
PubMed: 36501807
DOI: 10.3390/s22239105 -
Sensors (Basel, Switzerland) Oct 2022The built-in relay in a meter is a key control component of a smart meter, and its reliability determines whether the user can use electricity safely and smoothly. In...
The built-in relay in a meter is a key control component of a smart meter, and its reliability determines whether the user can use electricity safely and smoothly. In this paper, the degradation characteristics of the arc-burning energy are enhanced by the method of K-means clustering to replace degradation data, such as the overtravel time, release time, and other data. In existing methods, the meter needs to be disassembled to describe the degradation trend of the meter relay. The proposed method is combined with a bidirectional long short-term memory (Bi-LSTM) neural network to predict the degradation trend of the relay's performance. In this paper, K-means clustering is used to enhance the extraction of arc energy data features, and then the arc energy data obtained from the reliability lifetime test is assessed to predict the degradation trend of the meter relay by means of a bidirectional LSTM.
Topics: Reproducibility of Results; Neural Networks, Computer; Cluster Analysis; Electricity
PubMed: 36365847
DOI: 10.3390/s22218149 -
Journal of Dairy Science Aug 2020Commonly used lactose assays [enzymatic spectrophotometric absorbance (EZA) and HPLC] for dairy ingredients are relatively expensive and time consuming. A blood glucose...
Commonly used lactose assays [enzymatic spectrophotometric absorbance (EZA) and HPLC] for dairy ingredients are relatively expensive and time consuming. A blood glucose meter (BGM)-based method has successfully been documented as a rapid lactose assay in milk. However, the BGM-based method has not been evaluated in dairy ingredients. The objective of this study was to evaluate the BGM-based lactose analysis method in whey-derived (WD) and skim milk-derived (SMD) ingredients. The study was carried out in 4 phases. In phase 1, the effect of pH and lactose concentrations on the BGM reading was investigated using a factorial design with 2 factors: pH (6.02-7.50) and lactose (0.2 or 0.4%). We found that BGM readings were significantly affected by lower pH values at both lactose levels. In phase 2, the effect of total solids and ingredient type was investigated using a factorial design with 2 factors: ingredient type (WD or SMD) and total solids (0-8%). It was observed that the BGM reading was significantly affected by ingredient type and total solids. Phase 3 involved developing a linear relationship between the BGM reading and the EZA reference method to ascertain the accuracy of the proposed BGM method. Different ingredient types (WD or SMD) and non-lactose solids (0.5-27%) model ingredient dilutions prepared over a range of lactose contents (0.08-0.62%) were measured using the BGM and EZA methods. The average absolute percentage bias difference between the BGM method and EZA reference method results for these model dilutions was found to be between 2.2 and 7.3%. In phase 4, 15 samples procured from commercial sources ranging from 0.01 to 81.9% lactose were evaluated using the BGM method and EZA reference method. The average absolute percentage bias difference for lactose results between the 2 methods ranged from 3.6 to 5.0% and 5.3 to 9.7% for well-performing and poorly performing meters, respectively. Overall, the BGM method is a promising tool for rapid and low-cost analysis of lactose in both high-lactose and low-lactose dairy ingredients.
Topics: Animals; Biosensing Techniques; Blood Glucose; Cattle; Dairy Products; Lactose; Milk; Whey; Whey Proteins
PubMed: 32505394
DOI: 10.3168/jds.2019-17903 -
Journal of Vascular Surgery Jan 2021The 6-minute walk test is a common outcome measure in clinical trials of people with lower extremity peripheral artery disease (PAD). However, what constitutes a... (Observational Study)
Observational Study
OBJECTIVE
The 6-minute walk test is a common outcome measure in clinical trials of people with lower extremity peripheral artery disease (PAD). However, what constitutes a meaningful change in the 6-minute walk distance has not been well defined for people with PAD. The present study related the change in the 6-minute walk distance to the degree of participant-reported improvement or decline in the 6-minute walk distance to define a meaningful change in the 6-minute walk distance for those with PAD.
METHODS
Participants with PAD from three observational longitudinal studies completed the walking impairment questionnaire (WIQ) distance score and 6-minute walk at baseline and 1 year later. The WIQ distance score measures participants' perceived difficulty walking seven different distances without stopping (ranging from walking around the home to walking 5 blocks) on a 0 to 4 Likert scale, with 0 representing an inability to walk the distance and 4 representing no difficulty. The mean changes in the 6-minute walk distance corresponding to the participants' report of no change, 1-unit change, or 2-unit change, respectively, in the Likert scale score between the baseline and 1-year follow-up measures were calculated for each WIQ distance.
RESULTS
A total of 777 participants with PAD (mean age, 71.2 ± 8.8 years; mean baseline 6-minute walk distance, 350.1 ± 118.1 meters) completed 5439 questions about their difficulty walking each WIQ distance at baseline and follow-up. Participants with PAD who reported no change in their difficulty in walking each WIQ distance between baseline and follow-up had a decline of 7.2 meters (95% confidence interval [CI], -11.6 to -2.8 meters) in the 6-minute walk test. Relative to those reporting no change in difficulty walking, the participants reporting 1- and 2-point improvements in walking ability showed 6-minute walk distance improvements of 7.8 meters (95% CI, -0.3 to 15.9 meters) and 20.1 meters (95% CI, 1.1-39.2 meters), respectively. Relative to those reporting no change in walking difficulty, those reporting 1- and 2-point declines in perceived walking difficulty showed declines of -11.2 meters (95% CI, -19.0 to -3.4 meters) and -23.8 meters (95% CI, -37.4 to -10.3 meters) in the 6-minute walk distance.
CONCLUSIONS
Among people with PAD, ∼8- and ∼20-meter improvements in the 6-minute walk distance represent small and large improvements in walking ability, respectively. People with PAD who reported no change in their ability to walk distances over 1 year simultaneously declined by a mean of 7 meters in the 6-minute walk test. These findings will be useful for interpreting the results from randomized trials of interventions to improve the walking performance of people with PAD.
Topics: Aged; Female; Follow-Up Studies; Humans; Leg; Male; Peripheral Arterial Disease; Surveys and Questionnaires; Walk Test; Walking
PubMed: 32335305
DOI: 10.1016/j.jvs.2020.03.052 -
Annual International Conference of the... Nov 2021A Conducted Electrical Weapon (CEW) deploys 2, or more, probes to conduct current via the body to induce motor-nerve mediated muscle contractions, but the inter-probe...
INTRODUCTION
A Conducted Electrical Weapon (CEW) deploys 2, or more, probes to conduct current via the body to induce motor-nerve mediated muscle contractions, but the inter-probe resistances can vary and this can affect charge delivery. For this reason, newer generation CEWs such as the TASER X3, X2 and X26P models have feed-forward control circuits to keep the delivered charge constant regardless of impedance. Our main goal was to explore the load limits for this "charge metering" system. A secondary goal was to evaluate the reliability of the "Pulse Log" stored data to estimate the load resistance.
METHODS
We tested 10 units each of the X2 (double shot), X26P, and X26P+ (single-shot) CEW models. We used non-inductive high-voltage resistor assemblies of 50, 200, 400, 600, 1k, 2.5k, 3.5k, 5k, and 10k Ω, a shorted output (nominal 0 Ω), and arcing open-circuits. The Pulse Log data were downloaded to provide the charge value and stimulation and arc voltages for each of the pulses in a 5 s standard discharge cycle.
RESULTS
The average reported raw charge was 65.4 ± 0.2 µC for load resistances < 1 kΩ consistent with specifications for the operation of the feed-forward design. At load resistances ≥ 1 kΩ, the raw charge decreased with increasing load values. Analyses of the Pulse Logs, using a 2-piece multiple regression model, were used to predict all resistances. For the resistance range of 0 - 1 kΩ the average error was 53 Ω; for 1 kΩ - 10 kΩ it was 16%. Muzzle arcing can be detected with a model combining parameter variability and arcing voltage.
CONCLUSIONS
The X2, X26P, and X26P+ electrical weapons deliver an average charge of 65 µC with a load resistance < 1 kΩ. For loads ≥ 1 kΩ, the metered charge decreased with increasing loads. The stored pulse-log data for the delivered charge and arc voltage allowed for methodologically-reliable forensic analysis of the load resistance with useful accuracy.
Topics: Electric Impedance; Electricity; Heart Rate; Humans; Reproducibility of Results; Weapons
PubMed: 34891513
DOI: 10.1109/EMBC46164.2021.9630202