Increased upper-limb sensory attenuation with age

The pressure of our own finger on the arm feels differently than the same pressure exerted by an external agent: the latter involves just touch, whereas the former involves a combination of touch and predictive output from the internal model of the body. This internal model predicts the movement of our own finger and hence the intensity of the sensation of the finger press is decreased. A decrease in intensity of the self-produced stimulus is called sensory attenuation. It has been reported that, due to decreased proprioception with age and an increased reliance on the prediction of the internal model, sensory attenuation is increased in older adults. In this study, we used a force-matching paradigm to test if sensory attenuation is also present over the arm and if aging increases sensory attenuation. We demonstrated that, while both young and older adults overestimate a self-produced force, older adults overestimate it even more showing an increased sensory attenuation. In addition, we also found that both younger and older adults self-produce higher forces when activating the homologous muscles of the upper limb. While this is traditionally viewed as evidence for an increased reliance on internal model function in older adults because of decreased proprioception, proprioception appeared unimpaired in our older participants. This begs the question of whether an age-related decrease in proprioception is really responsible for the increased sensory attenuation observed in older people.

Sentinel-2 Time Series Analysis for Identification of Underutilized Land in Europe

Biomass and bioenergy play a central role in Europe’s Green Transition. Currently, biomass is representing half of the renewable energy sources used. While the role of renewables in the energy mix is undisputed, there have been many controversial discussions on the use of biomass for energy due to the “food versus fuel” debate. Using previously underutilized lands for bioenergy is one possibility to prevent this discussion. This study supports the attempts to increase biomass for bioenergy through the provision of improved methods to identify underutilized lands in Europe. We employ advanced analysis methods based on time series modelling using Sentinel-2 (S2) data from 2017 to 2019 in order to distinguish utilized from underutilized land in twelve study areas in different bio-geographical regions (BGR) across Europe. The calculated parameters of the computed model function combined with temporal statistics were used to train a random forest classifier (RF). The achieved overall accuracies (OA) per study area vary between 80.25 and 96.76%, with confidence intervals (CI) ranging between 1.77% and 6.28% at a 95% confidence level. All in all, nearly 500,000 ha of underutilized land potentially available for agricultural bioenergy production were identified in this study, with the greatest amount mapped in Eastern Europe.

Divide and Conquer: A Quick Scheme for Symbolic Regression

Symbolic regression (SR), as a special machine learning method, can produce mathematical models with explicit expressions. It has received increasing attention in recent years. However, finding a concise, accurate expression is still challenging because of its huge search space. In this work, a divide and conquer (D&C) scheme is proposed. It tries to divide the search space into a number of orthogonal sub-spaces based on the separability feature inferred from the sample data (dividing process). For each sub-space, a sub-function is learned (conquering process). The target model function is then reconstructed with the sub-functions according to their separability patterns. To this end, a separability pattern detecting technique, bi-correlation test (Bi-CT), is also proposed. Note that the sub-functions could be determined by any of the existing SR methods, which makes D&C easy to use. The D&C powered SR has been tested on many symbolic regression problems, and the study shows that D&C can help SR to get the target function more quickly and reliably.

Optimization of twisted blade of pump as turbine based on high dimensional surrogate model

In order to improve the operation efficiency of the twisted blade pump as turbine (PAT), a medium specific speed PAT was selected as the research object. The variables of the twisted blade plane blade profile were defined, the twisted blade was transformed into three plane blade profiles, and the blade profiles were parameterized by MATLAB 9.7 software. MATLAB 9.7, CFturbo 2020 and Fluent 19.2 were used to build the support vector machine-high dimensional model representation (SVM-HDMR) surrogate model function for efficiency optimization of PAT. Genetic algorithm was run on MATLAB 9.7 to optimize the surrogate model function, and the optimized blade profiles were fed back. The optimization results were verified by numerical simulation and experiment. The results show that the simulation efficiency of the PAT after optimization at the design operating point is 3.51% higher than the efficiency of the PAT before optimization, and the output power is increased by 5.3%. The test efficiency of the PAT after optimization at the design operating point is 3.4% higher than the efficiency of the PAT before optimization, and the output power is increased by 5.1%.

Performance of Unit Trust Funds between Conventional and Islamic Funds in Malaysia using Data Envelopment Analysis

This study aims to analyse the current performance of unit trust funds between conventional and Islamic funds using data envelopment analysis because most Malaysians are incapable to distinguish between conventional and Islamic unit trust funds performances since they tend to assume both funds perform similarly. This paper uses 20 authorised funds by the Securities Commission Malaysia (SC) for three years by using trailing data that consists of volatility element as input and total return as output. Indeed, the funds selected do not mix asset classes of funds, instead relying solely on equity funds to create a fair and reasonable ranking. The study employs Data Envelopment Analysis by testing two different models, namely Charnes, Cooper, and Rhodes input oriented (CCR-I) model and Banker, Charnes, and Cooper input oriented (BCC-I) model. The use of two models in this study is to ensure that the results of the ranking analysis are more accurate and precise. Both models employ the input-oriented model function as a means of maximising efficiency in order to increase the number of fairies. The efficiency of Islamic funds is more consistent than that of conventional funds for both models, as several Islamic funds maintain their position at the top of the efficient rank. However, there is a significant increase in conventional funds because 80% of the selected conventional funds that are not efficient in the CCR-I model achieve the efficiency level in the BCC-I model. As a result, there are four unit trust funds that are consistent in occupying efficiency level when tested for both CCR-I model and BCC-I model whereby three out of four are Islamic funds while the other is conventional fund. The Islamic funds consist of Apex Dana Aslah, BIMB i Growth Fund, and Maybank Malaysia Growth-I Fund while KAF Tactical Fund is conventional fund. Ultimately, it is concluded that Islamic funds perform better than conventional funds in Malaysia for the 3 years period ending 31 March 2021.

Recovering multiple fractional orders in time-fractional diffusion in an unknown medium

In this work, we investigate an inverse problem of recovering multiple orders in a time-fractional diffusion model from the data observed at one single point on the boundary. We prove the unique recovery of the orders together with their weights, which does not require a full knowledge of the domain or medium properties, e.g. diffusion and potential coefficients, initial condition and source in the model. The proof is based on Laplace transform and asymptotic expansion. Furthermore, inspired by the analysis, we propose a numerical procedure for recovering these parameters based on a nonlinear least-squares fitting with either fractional polynomials or rational approximations as the model function, and provide numerical experiments to illustrate the approach for small time t .

Brand Endorsers with Role Model Function

Social media influencers (SMIs) are taking on new roles in the communication environment of their followers as persuasive agents, opinion leaders, brand endorsers, and role models. Taking a look from the perspective of SMIs as agents in the persuasion attempt and their advertising literacy, our study has three aims. First, we provide insight into SMIs‘ self-perception as opinion-leading brand endorsers. Second, we discuss the extent to which SMIs use this awareness of and knowledge about their role model function for their particular young followers. Finally, we show how SMIs actively construct their media persona and how their relationship with their followers is based around this identity. The results from 15 semi-structured, guideline-based interviews conducted in 2019 with German SMIs working in different subject areas (e.g., fitness, fashion, travel, and family) show that SMIs are advertising literate. SMIs are aware of their multiple roles (understanding of one‘s roles: conceptional dimension), and reflect about their media persona‘s role model function (role interpretation: attitudinal dimension). Therefore, the majority of SMIs create their content and their media persona, as well as actively construct their relationship to their followers, based on their knowledge and awareness (role construction: performance dimension).

Function of Production, Capital, Labor and Government Policy in The Coal Mining Sector - Case Study of an Indonesian Coal Mining Company

This study aims to determine the effect of labor, capital, and government policies on coal output and the scale of coal business results of PT Indo Tambangraya Megah Tbk. The new thing from this research is the Cobb-Douglas production function which usually uses labor and capital variables, but in this study, it has been expanded by adding policy variable in the form of Law No. 4 of 2009 regarding Mineral and Coal Mining, which is not yet present in other studies. The research method is linear regression using the Cobb-Douglas model function. The results showed that labor did not significantly influence coal production. Capital has a significant effect on model 2 and policy has a significant effect on model 3. The coal mining business of PT Indo Tambangraya Megah Tbk is in decreasing return to scale because if the three variables are combined, it will be worth -0.24. This condition occurs because the additional output produced is smaller than the additional input (δ% output <δ% input).

Design of English reading and learning management system in college education based on artificial intelligence

English reading learning in college education is an efficient means of English learning. However, most of the current English reading learning platforms in colleges and universities only put different English books on the platform in electronic form for students to read, which leads to blindness of reading. Based on artificial intelligence algorithms, this paper builds model function modules according to the needs of English reading and learning management in college education and implements system functions based on artificial intelligence algorithms. Moreover, according to the above design principles of personalized learning model and the characteristics of personalized network learning, this paper designs a personalized learning system based on meaningful learning theory. In addition, this article verifies and analyzes the model performance. The research results show that the model proposed in this paper has a certain effect.

144 The Effect of Pre-farrow Meal Time on Onset of Parturition in Swine

Genetic selection for increased litter size has resulted in a concomitant increase in stillborn rates in modern genetic lines. In commercial farms, pre-parturient sows are typically fed during daytime hours with a high percentage of farrowings occurring unassisted overnight. Therefore, the objective of this study was to determine if feeding time can influence the onset of parturition to better align with farm staff hours and increase available assistance. A total of 1,016 sows were used in a commercial farm in Nebraska, USA, to determine the impact of pre-farrow meal time on onset of parturition. Sows were assigned to either control (0700) or alternative (0200) feeding treatments upon entry to farrowing room (~d112 of gestation) and all sows received 2.23 kg daily. Daily feeding time and quantity was controlled with the use of electronic feeders (Gestal SOLO; JYGA Technologies, Inc.). Farrowings had 24 hr monitoring with traits recorded including onset (ON), duration (DUR), piglet interval (PI), and stillborn percentage (SB). The linear model function (lm) in RStudio was used for regression estimates. Alternative sows farrowed earlier (P &lt; 0.05; 1204 vs. 1256 hr) than control-fed sows. Alternative sows also tended to have shorter DUR (P &lt; 0.10; 6.05 vs. 6.19 hr) and narrower PI times (P &lt; 0.10; 22.98 vs. 24.13 min) than control-fed sows. Stillborn percentage decreased (P &lt; 0.05; 8.53 vs. 9.68%) in alternative sows compared to control-fed sows. Combining ON and DUR, we calculated farrowing completion. Alternative fed sows finished parturition earlier (P &lt; 0.05; 1813 vs. 1929 hr) than control fed sows. These results suggest that the alternative strategy can result in earlier onsets, shorter piglet interval and farrowing duration, and a lower stillborn rate when compared to those fed the control strategy and should especially be of interest to farms without labor for 24hr farrowing assistance.