Time-sensitive Behavior Research Articles

Focus on user micro multi-behavioral states: Time-sensitive User Behavior Conversion Prediction and Multi-view Reinforcement Learning Based Recommendation Approach

In recommender systems, user behavior conversion implies user interest drifts and behavior patterns. However, current research has paid little attention to the correlation between target behavior conversion rate and user behavior patterns, and the impact of highly time-sensitive multi-behavior analysis on target behavior conversion rate is neglected. Meanwhile, compared to normal behavior conversions, user deviant behavior conversions are seldom studied. The behavior conversion rate that balances normal behavior patterns and deviant behavior patterns can more accurately reflect user interest drifts and real-time needs, thereby improving recommendation performance. Based on the above motivations, we propose a Time-sensitive Behavior Conversion Prediction and Multi-view Reinforcement Learning Based Recommendation Approach (TCMR), aiming to achieve more accurate and adaptive recommendations by analyzing user interest drifts, demand timings and behavior stability. First, we construct a hyper-behavior spatial model of highly collaborative temporal signals, and propose a subnet collaborative method to obtain normal behavior patterns, in which, core subnet, similarity subnet and behavior subnet are extracted from the hyper-behavior spatial model. Subsequently, we design a multi-level user behavior trajectory tree to perceive potential user deviant behaviors by comparing behavior conversions within the single behavior modality and across different behavior modality. By integrating normal behaviors and deviant behaviors, we evaluate user interest drifts, demand timings, and behavior stability, and ultimately obtain a prediction of behavior conversion rate. Finally, a multi-perspective asynchronous reinforcement learning is proposed, enabling TCMR to provide recommendations by considering multiple user perspectives and purposes. Experimental results demonstrate that TCMR exhibits superior recommendation performance and effectiveness.

A Calculus for the Specification, Design, and Verification of Distributed Concurrent Systems

A calculus for the specification and verification of distributed concurrent interactive real time systems is introduced. Systems are specified by their interface behavior formalized by interface predicates and interface assertions. System designs in terms of architectures of distributed networks of interactive systems are constructed by concurrent composition of subsystems. The specification of system designs is calculated from the specifications of their subsystems. Verification is done by proof rules which are based on the concepts of causality and realizability justified by the operational model in terms of generalized Moore machines, Moore machines not restricted to finite state spaces. The calculus supports interface specification and reasoning both about untimed as well as timed distributed concurrent systems. This includes the design of cyber-physical systems. Real-time is used, in particular, to specify time sensitive behavior and to prove properties related to causality and realizability, properties which hold for all Moore machines. On this basis, a calculus is worked out and illustrated by small examples. The calculus is shown to be sound and relatively complete.

Kindness: Definitions and a pilot study for the development of a kindness scale in healthcare.

Empathy and compassion currently receive the most attention in healthcare with respect to the medical humanities and while these skills are important for any clinician to learn, they are complex and can be daunting to healthcare trainees when first encountered. Kindness is a simple, time-sensitive behavior not yet well characterized in the healthcare setting. With this study, we aim to clearly define it as well as investigate a few common examples of kindness that might be used to create a scale for use in the healthcare setting. A literature search was performed to rigorously define kindness. A kindness scale based on this definition was then compiled and administered to 45 patients across three outpatient clinical settings to evaluate the association between several actions and the patient's perception of kindness. Kind actions are small, take little effort, and are short in duration to their intended effect. We define kindness as an action that benefits another, as perceived by the recipient of the kind action. The results from our clinical study indicate several actions such as greeting the patient with a smile, asking questions about the patient's daily life, listening carefully, and appearing interested in the patient have a moderate strength correlation to a perception of kindness. The physician being perceived as kind also had a weak-moderate strength correlation to the patient subjectively reporting improvement after their visit. Definitions in the medical humanities are important as they guide the scales used to measure them. This article defines kindness and describes some examples of its manifestation in the healthcare setting. Our study indicates that performing kind actions may improve a patient's subjective perception of their care, however, future studies are needed to evaluate whether this benefit extends to health outcomes as has been demonstrated for skills such as empathy and good communication. "Constant kindness can accomplish much. As the sun makes ice melt, kindness causes misunderstanding, mistrust, and hostility to evaporate." ~Albert Schweitzer.

Changes in Magnitude and Variability of Corticospinal Excitability During Rewarded Time-Sensitive Behavior.

Reward expectation and time estimation are important for behavior and affect corticospinal excitability. This study investigated changes in corticospinal excitability during rewarded time-sensitive behavioral tasks. The rewarded time-sensitive task comprised three fixed-ratio (FR) schedules: FRA contained a reward stimulus after every response, FRB after every two responses, and FRC after every four responses. The participants were instructed to press a left button with the index finger as quickly as possible in response to the appearance of a red circle. Just after the left button press, the word “10-yen” (approximately $0.1) or “no pay” was presented as feedback. Then, the participant had to mentally estimate/wait for 2.5 s from pressing the left button to pressing the right button. One second after the reward stimulus, transcranial magnetic stimulation (TMS) was delivered to the primary motor cortex at the hotspot of the first dorsal interosseous (FDI) muscle. Each participant received items corresponding to the total monetary reward accumulated at the end of the experiment. The variability of motor evoked potential (MEP) amplitudes transformed from a random process during the resting state into an autoregressive process during the rewarded time-sensitive behavioral task. Additionally, the random variation of MEP amplitudes in the FRC, FRB, and FRA schedules increased in a stepwise fashion. However, the magnitude of MEP amplitudes significantly increased for the FRB and FRC schedules compared to the FRA schedule. The time estimation lag was negative for the three FR schedules but there was no difference among the three FR schedules. The magnitude of corticospinal excitability increased in low reward probability, whereas the variability of corticospinal excitability transformed into an autoregressive process in high reward probability. These results imply that the magnitude and variability of expectation-related corticospinal excitabilities can be differentially altered by reward probability.

Experimental study on strain and deformation monitoring of asphalt structures using embedded fiber optic sensor

True strain distribution measurement has been accomplished with the use of Brillouin scattering in optical fibers. Therefore, the application of fiber optic sensors in civil engineering has recently increased, especially in concrete and earth structures. Asphalt structures have unique advantages in terms of flexibility and water sealing, but they present difficulties in embedding sensors because of the temperature- and time-sensitive behavior of asphalt mixtures. Over the transition temperature, the transferred stress from a loaded asphalt structure to an embedded sensor is drastically decreased, leading to inferior sensitivity of the sensor due to the low elastic modulus of asphalt. This paper presents experimental evidence that a flexible fiber optic sensor can contribute to strain and deformation monitoring for an asphalt structure even if the elastic modulus of asphalt is varied by temperature. Based on investigations on both prism specimens and a paved cantilever with the developed sensor coated with polyethylene, it can be stated that the sensor directly monitors asphalt behavior over a wide range of temperatures. According to the results of another test on a full-sized asphalt-layered slope constructed with heavy machinery, the sensor survived and successfully detected the change in strain caused by the force on the surface of the structure. Furthermore, a post-processing method of measurement to stabilize data fluctuations derived from skewed initial pre-tensioning on the sensor is proposed and evaluated.

A novel system for collecting longitudinal self-reported dietary consumption information: The internet data logger (iDL)

As diet has been considered as the major exposure pathway for toxic chemicals, such as heavy metals and pesticides, we have developed a web-based questionnaire system, the internet data logger (iDL), in order to facilitate the collection of detailed self-recording of standardized daily dietary consumption. An iDL prototype optimized for hand-held devices was tested in the on-going Children's Pesticide Exposure Study (CPES) in Atlanta, GA in which 15 consecutive days of dietary consumption information were recorded by 11 children or their parents and transmitted to a server via broadband wireless internet connection. Participants spent an average of 6.2 min in day 1 to enter a meal into iDL and approximately 4 min per meal for the remaining 14 study days. Approximately 75% of 446 total meals were entered into iDL on the date of consumption. A within-person comparison revealed that many food items recorded on paper diary were later classified as "unknown" according to iDL standards due to the lack of detailed information provided by the participants. The development of iDL represents a novel and pioneering tool, which integrates dietary data collection, transmission, and management in a real-time and automated manner. iDL provides the needed flexibility and mobility for research focused on collecting not only dietary consumption data but also other time-sensitive behavior data. This study has demonstrated that iDL can be deployed to collect long-term dietary consumption information in a population-based study, though future modifications/enhancements will undoubtedly improve its usability and application.

Cumulative blood oxygenation-level-dependent signal changes support the ‘time accumulator’ hypothesis

We studied time-related changes in the blood oxygenation-level-dependent signal during a time reproduction task. Nine healthy study participants retained and reproduced stimuli of varying durations in the multi-second range. During the encoding phase of the task, activity in the left dorsolateral prefrontal cortex inversely correlated with the interval duration, while an adjacent region in the dorsolateral prefrontal cortex showed positive correlation with duration in the reproduction phase. Cumulative signal increase during the reproduction phase, as found in the primary motor and supplementary motor areas, may also reflect the time-sensitive behavior. Signal accumulation in the right caudate nucleus is in agreement with presumed role of basal ganglia in time perception. These results support the 'time accumulator' hypothesis.