Decay Function Research Articles

Notes on demand: Conceptual and empirical benefits of applying Rachlin's discounting equation to demand data.

Howard Rachlin wrote extensively on how value diminishes in a hyperbolic form, and he contributed to understanding choice processes between different commodities as a molar pattern of behavior. The field of behavioral economic demand has been dominated by exponential decay functions, indicating that decreases in consumption of a commodity are best fit by exponential functions. Because of the success of Rachlin's equation at describing how hyperbolic decay affects the value of a commodity across various factors (e.g., delay, probability, social distance), we attempted to extend his equation to behavioral economic demand data for alcohol and opioids. Rachlin's discounting equation was applied to estimate consumption on alcohol purchase task data and nonhuman drug demand data. We compared results of his equation to the exponentiated demand equation using both a mixed-effects modeling approach and a two-stage approach. Rachlin's equation provided better fits to consumption data than the exponentiated equation for both mixed-effects and two-stage modeling. We also found that traditional demand metrics, such as Pmax, can be derived analytically when using Rachlin's equation. Certain metrics derived from Rachlin's equation appeared to be related to clinical covariates in ways similar to the exponentiated equation. Rachlin's equation better described demand data than did the exponentiated equation, indicating that demand for a commodity may decrease hyperbolically rather than exponentially. Other benefits of his equation are that it does not have the same pitfalls as the current exponential equations and is relatively straightforward in its conceptualization when applied to demand data. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Height to diameter ratio model of Larix gmelinii in Daxing'anling Mountains, China

Based on data from 56 plots of natural Larix gmelinii forest in Cuigang Forest Farm of Daxing'anling Mountains, we constructed the height to diameter ratio (HDR) model of L. gmelinii with exponential decay function as the base model. We used the tree classification as dummy variables and the method of reparameterization. The aim was to provide scientific evidence for evaluating the stability of different grades of L. gmelinii trees and stands in Daxing'anling Mountains. The results showed that except for diameter at breast height, the dominant height, dominant diameter, individual tree competition index all had significant correlations with the HDR. The involvement of these variables significantly improved the fitted accuracy of the generalized HDR model, with the adjustment coefficients, root mean square error and mean absolute error being 0.5130, 0.1703 m·cm-1 and 0.1281 m·cm-1, respectively. When the tree classification as a dummy variable was added to parameters 0 and 2 of the generalized model, the fitting effect of the model was further improved. The three above-mentioned statistics were 0.5171, 0.1696 m·cm-1 and 0.1277 m·cm-1, respectively. Through comparative analysis, the generalized HDR model with tree classification as dummy variable had the best fitting effect, which was superior to the basic model, and had higher prediction precision and adaptability.

The biological functions of nonsense-mediated mRNA decay in plants: RNA quality control and beyond.

Nonsense-mediated mRNA decay (NMD) is an evolutionarily conserved quality control pathway that inhibits the expression of transcripts containing premature termination codon. Transcriptome and phenotypic studies across a range of organisms indicate roles of NMD beyond RNA quality control and imply its involvement in regulating gene expression in a wide range of physiological processes. Studies in moss Physcomitrella patens and Arabidopsis thaliana have shown that NMD is also important in plants where it contributes to the regulation of pathogen defence, hormonal signalling, circadian clock, reproduction and gene evolution. Here, we provide up to date overview of the biological functions of NMD in plants. In addition, we discuss several biological processes where NMD factors implement their function through NMD-independent mechanisms.

An Analytical Solution to the One-Dimensional Unsteady Temperature Field near the Newtonian Cooling Boundary

One-dimensional heat-conduction models in a semi-infinite domain, although forced convection obeys Newton’s law of cooling, are challenging to solve using standard integral transformation methods when the boundary condition φ(t) is an exponential decay function. In this study, a general theoretical solution was established using Fourier transform, but φ(t) was not directly present in the transformation processes, and φ(t) was substituted into the general theoretical solution to obtain the corresponding analytical solution. Additionally, the specific solutions and corresponding mathematical meanings were discussed. Moreover, numerical verification and sensitivity analysis were applied to the proposed model. The results showed that T(x,t) was directly proportional to the thermal diffusivity (a) and was inversely proportional to calculation distance (x) and the coefficient of cooling ratio (λ). The analytical solution was more sensitive to the thermal diffusivity than other factors, and the highest relative error between numerical and analytical solutions was roughly 4% under the condition of 2a and λ. Furthermore, T(x,t) grew nonlinearly as the material’s thermal diffusivity or cooling ratio coefficient changed. Finally, the analytical solution was applied for parameter calculation and verification in a case study, providing the reference basis for numerical calculation under specific complex boundaries, especially for the study of related problems in the fields of fluid dynamics and peridynamics with the heat-conduction equation.

Association of walkability and NO2 with metabolic syndrome: A cohort study in China

BackgroundEpidemiological studies have reported an association between traffic-related pollution with risk of metabolic syndrome (MetS). However, evidence from prospective studies on the association of walkability and nitrogen dioxide (NO2) with MetS is still scarce. We, therefore, aimed to evaluate the association of long-term exposure to NO2 and walkability with hazards of incident MetS. MethodsA total of 17,965 participants without MetS diagnosed within one year at baseline were included in our study from a population-based prospective cohort in Yinzhou District, Ningbo, Zhejiang Province, China. Participants were followed up by the regional Health Information System (HIS) until December 15, 2021. MetS was defined based on the criteria of Chinese Diabetes Society (CDS2004). We used walkscore tools, calculating with amenity categories and decay functions, and spatial–temporal land-use regression (LUR) models to estimate walkability and NO2 concentrations. We used Cox proportional hazards regression models to examine the association of walkability and NO2 with hazards of MetS incidence reporting with hazard ratios (HRs) and 95% confidence intervals (CIs). ResultsOverall, we followed up 77,303 person-years and identified 4040 incident cases of MetS in the entire cohort. Higher walkability was inversely associated with incident MetS (HR = 0.94, 95 % CI: 0.91–0.99), whereas NO2 was positively associated with MetS incidence (HR = 1.07, 95 %CI: 1.00–1.15) per interquartile range increment in two-exposure models. Furthermore, we found a significant multiplicative interaction between walkability and NO2. Stronger associations were observed for NO2 and incident MetS among men, smokers, drinkers and participants who aged < 60 years and had higher levels of income. ConclusionIn summary, we found living in areas with lower walkability and higher concentrations of NO2 were associated with increased incidence of MetS. The beneficial effect of higher walkability may be attenuated by exposure to NO2.

DHOSGR: lncRNA-disease Association Prediction Based on Decay High-order Similarity and Graph-regularized Matrix Completion

Background: It has been shown in numerous recent studies that long non-coding RNAs (lncRNAs) play a vital role in the regulation of various biological processes, as well as serve as a basis for understanding the causes of human illnesses. Thus, many researchers have developed matrix completion approaches to infer lncRNA–disease connections and enhance prediction performance by using similarity information. Objective: Most matrix completion approaches are solely based on the first-order or second-order similarity between nodes, and higher-order similarity is rarely considered. In view of this, we developed a computational method to incorporate higher-order similarity information into the similarity network with different weights using a decay function designed by a random walk with restart (DHOSGR). Methods: First, considering that the information will decay as the distance increases during network propagation, we defined a novel decay high-order similarity by combining the similarity matrix and its high-order similarity information through a decay function to construct a similarity network. Then, we applied the similarity network to the objective function as a graph regularization term. Finally, a proximal splitting algorithm was used to perform matrix completion to infer relationships between diseases and lncRNAs. Results: In the experiment, DHOSGR achieves a superior performance in leave-one-out cross validation (LOOCV) and 100 times 5-fold cross validation (5-fold-CV), with AUC values of 0.9459 and 0.9334±0.0016, respectively, which are better than other five previous models. Moreover, case studies of three diseases (leukemia, lymphoma, and squamous cell carcinoma) demonstrated that DHOSGR can reliably predict associated lncRNAs. Conclusion: DHOSGR can serve as a high efficiency calculation model for predicting lncRNA-disease associations.

Finite-Time Rapid Global Sliding-Mode Control for Quadrotor Trajectory Tracking

To enhance the position and attitude-control of quadrotor for trajectory tracking, we propose a fast decay function utilizing exponential property to improve the performance of global sliding-mode control, allowing the initial value to quickly reach equilibrium. The main research is focused on deriving the finite settling time using the proposed decay function and presenting a detailed calculation process, instead of making a simple modification to a monotonic exponential-decay function. Moreover, we adopt an adaptive control law to ensure the robustness of the quadrotor, even without knowing the upper bound for disturbances. In addition, we perform time-varying mass simulations because the quadrotor’s load mass may change during maneuvering. Furthermore, using the Lyapunov function, the stability of the entire closed-loop system is ensured by the step-by-step stabilization of each subsystem. The simulation results show that the rapid global sliding-mode control (RGSMC) we designed is more effective than the conventional global sliding-mode control and adaptive sliding mode control with respect to stabilization and tracking against external disturbances. Hence, the fast decay property of the proposed global function is verified.

Performance Evaluation of Time-based Recommendation System in Collaborative Filtering Technique

The Collaborative Filtering (CF) technique is the most common neighbourhood-based recommendation strategy, that provides personalized recommendation to a user for the items using a similarity measure. Hence, the selection of the appropriate similarity measure becomes crucial in the CF based recommendation system. The traditional similarity measures merely focus only on the historical ratings provided by the users to compute the similarity, completely ignoring the fact that preferences change over a period of time. Considering this, the paper aims to develop an effective Recommendation System that uses temporal information to capture the changes in the preferences over a period of time. For this, the existing exponential and power time decay functions are integrated with Cosine, Pearson Correlation, and Gower's similarity measures to compute similarity. The similarity is computed at the similarity computation and prediction levels of recommendation processes. Experimental findings in terms of MAE and RMSE on the MovieLens-100k demonstrate that performance of Gower's coefficient is better when applied with the exponential function at the similarity computation level of the recommendation process.

可変高度のUAVセンシングにおける森林地表付近の減衰率特性を考慮した放射線マッピング

Changing amount of radiation dose has been a great concern by citizens near the difficult-to-return area after the Fukushima Daiichi nuclear disaster. Rigorous assessment of public safety including inaccessible forest areas at a meter level is one of the keys in the disaster recovery plan. Each measurement point near the ground surface in UAV-based sensing is exposed from the effects of radiation emission from various angles in the fields including forest and plain, and thus acquisition of the attenuation coefficients on site is not realistic by simply using the spatial integration of point-kernels or exponential decay functions. The proposed method in this paper utilizes the vertical and horizontal distance correction. The field test at a residence in the forests near the difficult-to-return area was performed, and in this area we found the improvement of 42% in RMSE (root mean squared error) from the results of a base model. Importantly, the experimental result suggested that the proposed method has the potential to efficiently accept using the different measurement data, both measured points near the ground surface and the flight heights during the UAV sensing.

UV germicidal rays working with timer and motion sensors

As a result of coronavirus (COVID-19) epidemic, the public has become actively involved in bodily sanitation. The “New Normal” lifestyle now focuses on cleanliness and disinfection to prevent the spread of germs. This research designed and programmed a microcontroller for a UVC disinfection system using an Arduino board as an open-source electronic platform operated with a motion sensor (PIR) and timer control module (RTC). The optical properties of an 8 Watt (W) UVC source were measured. The four UVC sources investigated had wavelengths ranging from 251 to 577 nm. A UVC wavelength of 251 nm eradicates germs but also destroys tissues and is harmful to humans. Experimental result showed that UVC intensity decreased with distance from the source according to the exponential decay function. A control system, installed inside a building to kill germs when there are no humans or pets, can control UVC light source operation with a maximum power of 2kW. Operational time can be adjusted by setting on the control case, while as an additional level of safety, the system can be turned off if a motion sensor detects movement. Movement detection distance at an angle of -90 to 90 degrees was recorded. Result gave 11 m detection distance at an angle of 0 degrees, with more than 3 m detection distance at -45 to 45 degrees, as suitable for installation above a door. This timer and motion sensor-operated UV germicidal ray system can be safely deployed to keep rooms germs free.

Study of Flow Field Characteristics During the Impact of a High-pressure Gas Jet on a Bulk-loaded Liquid

A visual experiment platform for high-pressure gas jet impacting the bulk-loaded liquid was designed and built in order to investigate the real law of the interaction between the high-pressure gas jet and the liquid medium during the liquid-balance launch of rocket launcher. The experiments of single-phase gas jet injection and the high-pressure gas jet at different temperatures impacting the bulk-loaded liquid were carried out, and the effects of gas temperature on the characteristics of the gas-liquid flow field have been revealed. The results show that the turbulent mixing between the high-pressure gas jet and the liquid medium leads to the appearance of pressure fluctuations in the gas chamber connected to the nozzle. The higher the gas temperature, the greater the amplitude of the pressure fluctuations. Under the impact of high-pressure gas jet, a gas cavity with an arc-shaped head is formed inside the bulk-loaded liquid. The higher the gas temperature, the faster and more unstable the development of the gas cavity and the flow field. The displacement equation of the gas cavity confirms to the first-order exponential decay function, and the error between the fitting value of the established mathematical model and the measured value is within 2%.

An exact solution of heat and mass transfer analysis on hydrodynamic magneto nanofluid over an infinite inclined plate using Caputo fractional derivative model

&lt;abstract&gt; &lt;p&gt;This paper presents the problem modeled using Caputo fractional derivatives with an accurate study of the MHD unsteady flow of Nanofluid through an inclined plate with the mass diffusion effect in association with the energy equation. H&lt;sub&gt;2&lt;/sub&gt;O is thought to be a base liquid with clay nanoparticles floating in it in a uniform way. Bousinessq's approach is used in the momentum equation for pressure gradient. The nondimensional fluid temperature, species concentration, and fluid transport are derived together with Jacob Fourier sine and Laplace transforms Techniques in terms of exponential decay function, whose inverse is computed further in terms of Mittag-Leffler function. The impact of various physical quantities interpreted with fractional order of the Caputo derivatives. The obtained temperature, transport, and species concentration profiles show behaviours for $0 &amp;lt; \mathtt{α} &amp;lt; 1$ where $\mathtt{α} $ is the fractional parameter. Numerical calculations have been carried out for the rate of heat transmission and the Sherwood number is swotted to be put in the form of tables. The parameters for the magnetic field and the angle of inclination slow down the boundary layer of momentum. The distributions of velocity, temperature, and concentration expand more rapidly for higher values of the fractional parameter. Additionally, it is revealed that for the volume fraction of nanofluids, the concentration profiles behave in the opposite manner. The limiting case solutions also presented on flow field of governing model.&lt;/p&gt; &lt;/abstract&gt;

Influence and optimization of long-time superfine grinding on the physicochemical features of green tea powder

Superfine grinding is a crucial step in green tea powder (GTP) processing. In this work, the time-resolved changes of physicochemical properties (physical properties, main active components, etc.) of GTPs were investigated, and ball milling time (BMT) for tea grinding was optimized. Variable importance in projection was used to evaluate the importance of modification of each physicochemical parameter on BMT, and a multi-objective fuzzy optimization model was used to obtain the optimal BMT. The BMT range was 2–30 h, and the results showed that BMT had a significant influence on the physicochemical properties of GTP. The mean particle size decreased from 257 to 10.6 μm and the color became lighter as the BMT increased. The main active components decreased markedly when BMT increased form 18–24 h. Mean particle size and color difference dramatically correlated with BMT and could be described by a one-phase exponential decay function. The optimal BMT was 18 h and high quality GTP could be obtained under this condition with small particle size, bright green color and rich in theanine and total tea polyphenols (TTPs).

Ultrafast Photocarrier Dynamics in Vertically Aligned SnS2 Nanoflakes Probing with Transient Terahertz Spectroscopy.

By employing optical pump Terahertz (THz) probe spectroscopy, ultrafast photocarrier dynamics of a two-dimensional (2D) semiconductor, SnS2 nanoflake film, has been investigated systematically at room temperature. The dynamics of photoexcitation is strongly related to the density of edge sites and defects in the SnS2 nanoflakes, which is controllable by adjusting the height of vertically aligned SnS2 during chemical vapor deposition growth. After photoexcitation at 400 nm, the transient THz photoconductivity response of the films can be well fitted with bi-exponential decay function. The fast and slow processes are shorter in the thinner film than in the thicker sample, and both components are independent on the pump fluence. Hereby, we propose that edge-site trapping as well as defect-assisted electron-hole recombination are responsible for the fast and slow decay progress, respectively. Our experimental results demonstrate that the edge sites and defects in SnS2 nanoflakes play a dominant role in photocarrier relaxation, which is crucial in understanding the photoelectrochemical performance of SnS2 nanoflakes.

Evaluation of scintillation properties of Mg4(Ta,Nb)2O9 single crystals

Mg4(Ta,Nb)2O9 single crystals were synthesized by the floating zone method, and the photoluminescence and scintillation properties were evaluated. Under X-ray irradiation, Mg4Ta2O9 single crystal showed an emission peak at 350 nm, while Nb-contained ones showed an emission peak at 400 nm. The decay curves were approximated by one exponential decay function, which indicated the decay time in μs order. Among the samples, Mg4Ta1.5Nb0.5O9 showed the highest light yield of 22,000 ph/MeV and the lowest afterglow levels of ∼10 ppm.

Correlated barrier charge hopping and non-Debye relaxation in columbite MnNb2O6

A comprehensive study on the mechanism of ac-charge transport and dielectric relaxation in the MnNb2O6 columbite system has been reported. Thermally driven, Arrhenius-like behaviour of the ac-conductivity is predominant at temperatures above 300 K in the frequency range 50 Hz–5 MHz with activation energies lying between 0.45 and 0.38 eV. Besides, a quadratically decreasing trend in the activation energy is evident as given by: = A + Bf + Cf 2 with the constants A (0.413 eV), B (0.023 eV Hz−1) and C (−0.004 eV Hz−2). The measured data is analysed using the Double power law to explain the dispersive behaviour of electrical conductivity. These studies also provide evidence for the correlated-barrier hopping (CBH) conduction mechanism of charge carriers for temperatures in the range 173–473 K. Further, the temperature dependence of frequency exponent, s(T) displays two distinct regions both of which are associated with the CBH mechanism with slopes K−1 and K−1 in Region-I (173–300 K) and the slope K−1 with non-linear variation of s 2 in Region-II (300–473 K). However, the second region is more dominated by thermally activated Arrhenius-like behaviour. The dynamical response of complex electric modulus spectra and the corresponding analysis using Kohlrausch-Williams-Watts method reveals the presence of a non-Debye type relaxation process with decay function exponent β lying between 0.794 and 0.840. This inference of the non-Debye type relaxation process is further supported by depressed semicircles in Nyquist plots and the higher magnitude of full width half maximum (FWHM) (≈1.44 decades) of the normalized master cusp vs compared to the FWHM ( = 1.14 decades) for ideal Debye behaviour. Both short-range and long-range conductivity regions are ubiquitous in with a pronounced distribution of relaxation times (s) with temperature. This study further leads to the estimation of activation energy of charge carriers, E M = 0.44 eV which is in consonance with .

An Approach to Accurate Ship Image Recognition in a Complex Maritime Transportation Environment

In order to monitor traffic in congested waters, permanent video stations are now commonly used on interior riverbank bases. It is frequently challenging to identify ships properly and effectively in such images because of the intricate backdrop scenery and overlap between ships brought on by the fixed camera location. This work proposes Ship R-CNN(SR-CNN), a Faster R-CNN-based ship target identification algorithm with improved feature fusion and non-maximum suppression (NMS). The SR-CNN approach can produce more accurate target prediction frames for prediction frames with distance intersection over union (DIOU) larger than a specific threshold in the same class weighted by confidence scores, which can enhance the model’s detection ability in ship-dense conditions. The SR-CNN approach in NMS replaces the intersection over union (IOU) filtering criterion, which solely takes into account the overlap of prediction frames, while DIOU, also takes into account the centroid distance. The screening procedure in NMS, which is based on a greedy method, is then improved by the SR-CNN technique by including a confidence decay function. In order to generate more precise target prediction frames and enhance the model’s detection performance in ship-dense scenarios, the proposed SR-CNN technique weights prediction frames in the same class with DIOU greater than a predetermined threshold by the confidence score. Additionally, the SR-CNN methodology uses two feature weighting methods based on the channel domain attention mechanism and regularized weights to provide a more appropriate feature fusion for the issue of a difficult ship from background differentiation in busy waters. By gathering images of ship monitoring, a ship dataset is created to conduct comparative testing. The experimental results demonstrate that, when compared to the three traditional two-stage target detection algorithms Faster R-CNN, Cascade R-CNN, and Libra R-CNN, this paper’s algorithm Ship R-CNN can effectively identify ship targets in the complex background of far-shore scenes where the distinction between the complex background and the ship targets is low. The suggested approach can enhance detection and decrease misses for small ship targets where it is challenging to distinguish between ship targets and complex background objects in a far-shore setting.

How South Asian Economies Managed Their Trade Risks Collaboratively ? A Study

South Asian economies, including India, witnessed a considerable GDP decline in the past few years. According to reliable published resources for the fiscal year Q4-2020, India’s GDP growth was as low as 3.1% on average over the previous 11 years. This empirical work was built upon the fundamental volatility model (using a 2-asset portfolio case). It comprised the exponential decay function on annual figures from 1976–2019 of overall trade, exports, and imports from five South Asian countries, namely Bangladesh, India, Nepal, Pakistan, and Sri Lanka (Bhutan was excluded due to paucity of data). For empirical justification of spillover effects and shock persistence, two exogenous macroeconomic factors, namely, the inflation percentage (CPI) and population rates, were also taken into account. The broad outcomes were mainly two. Firstly, there was a greater positive impact on time-varying trade-volatility shock persistence levels due to time-varying exogenous factors like inflation and population volatility. The second outcome is that portfolio or joint probabilities “reduce” such an impact, that is, time-varying portfolio volatility of the inflation rate and population rate did not reduce the shock persistence of time-varying trade volatility across the nations studied.

Stimulus decay functions in action control

When facing particular combinations of stimuli and responses, people create temporary event-files integrating the corresponding stimulus and response features. Subsequent repetition of one or more of these features retrieves the entire event-file, which impairs performance if not all features are repeated (partial-repetition costs). In the literature, different decay functions have been reported presumably dependent on the type of feature that is repeated (e.g. target vs. distractor features). Here, we use a variant of the S1R1-S2R2 and distractor-response binding task and analyze for the first time target-based and distractor-based event-file decay functions within the same task and sample. While we found evidence for decay functions and also stronger retrieval due to target than distractor repetitions, slopes of the decay functions were comparable suggesting that the decay process itself is equal irrespective of the type of stimulus feature that is repeated. Our study thereby confirms overarching approaches that summarize paradigm specific findings with the same set of core processes.

Contractor Recommendation Model Using Credit Networking and Collaborative Filtering

The credit of contractors in the construction market directly affects the cooperative intentions of owners. Although previous scholars have attempted to use credit to select appropriate contractors, they have rarely considered the trust relationship between decision-making and former owners. This work introduces and verifies a credit network recommendation model based on a collaborative filtering algorithm. The contractor’s credit established based on this model serves as a viable method for owners to select efficient contractors. The application of the model includes relevant information collection, neighbor set formation, contractor’s credit evaluation, and recommendation list formation, among which the neighbor set of the owner is used to calculate the comprehensive trust degree of the decision-making owner to the former owner. A time decay function is adopted to correct the difference in the trust relationship between an owner and a contractor introduced over time. To verify the feasibility of this model, an actual scenario was simulated, and the results obtained via simulations were compared and found to be consistent. Thus, a contractor with a high credit can be recommended to the decision-making owner. This approach is crucial for promoting contractors’ credit and conducive to the healthy development of the construction market.