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Numerical Simulation for Solving Fractional Riccati and Logistic Differential Equations as a Difference Equation
Get PDFIn this paper, we introduce a numerical treatment using the generalized Euler method (GEM) for the fractional (Caputo sense) Riccati and Logistic differential equations. In the proposed method, we invert the given model as a difference equation. We compare our numerical solutions with the exact solution and with those numerical solutions using the fourth-order Runge-Kutta method (RK4). The obtained numerical results of the two proposed problem models show the simplicity and efficiency of the proposed method
Root-mycorrhizae interactions contributed to organic carbon density in the sandy soil profiles of adapted grazing lands
No full textGrazing lands occupy a substantial area around the world and could serve as carbon sink if soil organic carbon sequestration potential is increased. In subtropical climates, grazing lands are more commonly situated on low productive sandy soil profiles with poor soil attributes for carbon sequestration. Soil acidity limits root and beneficial microbial interactions, both critical for increasing soil organic carbon (SOC) sequestration. Adapted grazing and forage (vegetation) management could help to improve root-microbe interactions and SOC stocks in the soil profile. The objective of this study was to quantify SOC density in the soil profile along with aboveground and belowground biomass pools, as influenced by long-term cattle grazing of different forage systems managed with or without inorganic nitrogen (iN) fertilization. The following treatments were implemented continuously for the last 30 years. Warm season perennial grass (C4, Cynodon dactylon) pastures were either over-sown with C3 ryegrass (Lolium multiforum; C4-C3G) or clover (Trifolium sp.; C4-C3L), in order to extend the grazing season into cool season months. Grass-based pastures (C4-C3G) were fertilized, called inorganic treatment (iN), while clover systems (C4-C3L called organic N) did not receive iN fertilization (oN). The two forage systems were further split to compare high and low grazing pressure (HG and LG). Forage, root and microbial biomass and SOC density were estimated from soil cores sampled separately during C4 and C3 grazing seasons. Results indicated that SOC density (Mg ha−1) at soil profile level (0–60 cm) was higher under low grazing pressure compared to high, and in iN fertilized compared to oN treatments. However, subsoil (20–60 cm) SOC stocks were significantly higher under oN compared to iN treatments. Forage biomass and root biomass were higher under iN and HG treatments, but arbuscular mycorrhizae (AM) biomass was decreased. There were no consistent trends for other microbial biomass pools in response to GP or N treatments. It can be concluded that higher SOC density in the surface and subsoil in response to GP and N management were largely due to differences in microbial biomass, but not plant biomass productivity. Among the belowground biomass pools, AM was most responsive to experimental factors and their interaction effects, and thus could be a reliable metric to optimize grazing and achieve stewardship goals
Metabolomes of sperm and seminal plasma associated with bull fertility
No full textBull fertility is crucial for efficient, profitable, and sustainable agriculture of cattle. Despite the fact that the uses of sperm from low fertility bulls cause millions of dollars economic losses, conventional methods available to accurately predict bull fertility are still of limited use. Although breeding bulls produce billions of sperm mostly with normal motility and morphology, some bulls are afflicted with poor fertility due to molecular or cellular defects in the sperm. Sperm functional genome including transcriptome, proteome, and metabolome influence bull fertility. Through high throughput screening methods of metabolomics, specific small molecules have been described both for seminal plasma and sperm. Compared to sperm, seminal plasma contains much higher numbers and levels of metabolites. Although the identities and functions of many of these metabolites are known, such knowledge is still yet to be generated for a greater number of metabolites of sperm and seminal plasma. Once validated as fertility markers, sperm, and seminal plasma metabolites can be used to evaluate semen quality and predict bull fertility, and/or used in assisted reproductive technologies. This review describes the possibility to use small molecules (in the review called metabolites) as fertility predictors
Augmentation of Electrical Power Laboratory Students Learning Experience Through Simulations Software Enhancements During COVID-19
Get PDFThe quest for experienced Electrical Power Engineers in today\u27s workforce is increasing as Supervision Control and Data Acquisition-Internet of Things (SCADA- IOT) systems continue to be integrated into the power grid, thus making the grid smarter. The overall electric power network is undergoing changes due to the industrial use of smart machines incorporating power electronics devices and the deployment of renewable energy resources such as photo-voltaic and wind power generators. The challenges that have been generated as a result of this power grid modernization require universities and technical education institutions to modify their power engineering curriculum to include more of engineering students\u27 hands-on practical laboratory experience.
Additionally, the onset of the COVID-19 pandemic at the beginning of the year 2020 has created the awareness of the importance of necessary changes in the way laboratory classes are taught to improve student\u27s learning experience as well as achieve the desired learning objectives before the students graduate into the industry. Face-to-face laboratory courses need to be modified to satisfy mandated COVID 19 social distancing and other requirements. While the quest for experienced Electrical Power Engineers in today\u27s workforce is increasing as Supervision Control and Data Acquisition-Internet of Things (SCADA- IOT) systems continue to be integrated into the power grid. The grid smarter recent COVID-19 based limitations imposed on face-to-face teaching is most likely to adversely affect adequate delivery of laboratory instructions to engineering students. This study focuses on an electrical power laboratory course conducted in the wake of the COVID-19 pandemic using Electro-Mechanical System (EMS), where experiments with simulations, practical modules implementation and Data Acquisition and Control Interface (DACI) method are utilized to enhance the Laboratory experience. Electromechanical Systems Simulation Software, a web-browser based application, is used in the EMS simulations.
The study examines the effectiveness of the simulations method together with remote practical demonstrations of power laboratory experiments. Every experiment conducted remotely to familiarize students with the operation of the power industry is accompanied by students\u27 computer simulations. The laboratory reports submitted by students are used to assess the result of the remote course delivery which is found to be satisfactory and more engaging to students than the traditional face-to-face teaching method
Fake News Detection in Social Media Using Machine Learning and Deep Learning
Get PDFFake news detection in social media is a process of detecting false information that is intentionally created to mislead readers. The spread of fake news may cause social, economic, and political turmoil if their proliferation is not prevented. However, fake news detection using machine learning faces many challenges. Datasets of fake news are usually unstructured and noisy. Fake news often mimics true news. In this study, a data preprocessing method is proposed for mitigating missing values in the datasets to enhance fake news detection accuracy. The experimental results show that Multi- Layer Perceptron (MLP) classifier combined with the proposed data preprocessing method outperforms the state-of-the-art methods.
Furthermore, to improve the early detection of rumors in social media, a time-series model is proposed for fake news detection in social media using Twitter data. With the proposed model, computational complexity has been reduced significantly in terms of machine learning models training and testing times while achieving similar results as state-of-the-art in the literature. Besides, the proposed method has a simplified feature extraction process, because only the temporal features of the Twitter data are used. Moreover, deep learning techniques are also applied to fake news detection. Experimental results demonstrate that deep learning methods outperformed traditional machine learning models. Specifically, the ensemble-based deep learning classification model achieved top performance
Disturbance Compensation Control of SCR Denitration based on Mutual Information and PID Neural Network
No full textThe Selective catalytic reduction (SCR) denitration system is very complex and has the characteristics of strong disturbance and uncertainty.Based on mutual information and PID neural network,a disturbance compensation control method for SCR denitration system was proposed in this paper.The disturbance observer was constructed by using the PID feedforward neural network to approximate the inverse of the controlled plant.The disturbance observer was used to compensate the control system in order to eliminate the disturbance in advance.The mutual information between observation disturbance and system disturbance was selected as the objective function,and the improved imperialist competitive algorithm was used to optimize the parameters of PID neural network.The robust PID controller was designed to overcome the uncertainty of the controlled plant.The simulation results show that the method has outstanding disturbance rejection performance and good robustness,and the control performance is better than that of the general PID control
Interface compositions as determinants of resveratrol stability in nanoemulsion delivery systems
No full textThe incorporation of hydrophobic ingredients, such as resveratrol (a fat-soluble phytochemical), in nanoemulsions can increase the water solubility and stability of these hydrophobic ingredients. The nanodelivery of resveratrol can result in a marked improvement in the bioavailability of this health-promoting ingredient. The current study hypothesized that resveratrol can bind to caprine casein, which may result in the preservation of the biological properties of resveratrol. The fluorescence spectra provided proof of this complex formation by demonstrating that resveratrol binds to caprine casein in the vicinity of tryptophan amino acid residues. The caprine casein/resveratrol complex is stabilized by hydrophobic interactions and hydrogen bonds. Hence, to study the rate of resveratrol degradation during processing/storage, resveratrol losses were determined by reversed-phase high performance liquid chromatography (RP-HPLC) in nanoemulsions stabilized by bovine and caprine caseins individually and in combination with polysorbate-20. At 48 h oxidation, 88.33% and 89.08% was left of resveratrol in the nanoemulsions stabilized by caprine casein (αs1-I)/polysorbate-20 complex and caprine (αs1-II)/polysorbate-20 complex, while there was less resveratrol left in the nanoemulsions stabilized by bovine casein/polysorbate-20 complex, suggesting that oxygen degradation was involved. The findings of this study are crucial for the food industry since they imply the potential use of caprine casein/polysorbate-20 complex to preserve the biological properties of resveratrol
Personal growth initiative and posttraumatic stress among survivors of transportation accidents: Mixture modeling indicating changes in group membership over time
No full textThe current study explored subgroups in reported personal growth initiative (PGI) and posttraumatic stress symptoms (PTSS) and examined the changes in class memberships among survivors of a transportation accident. Participants at Time 1 were 602 adults who reported directly experiencing a transportation accident within the past year (Mmonths = 6.36; SDmonths = 3.20). Of these participants, 171 adults completed the follow-up survey after 3 months (Time 2). Finite mixture modeling was conducted to identify the heterogeneity of PTSS in relation with PGI at each time point. At Time 1, a four-class model was the best-fitting model, and at Time 2, a three-class model was the best-fitting model. As hypothesized, when examined cross-sectionally, various subgroups were identified at each time point, finding subgroups with moderate to high levels of PGI but differing in their PTSS. However, when examining the longitudinal changes in class membership from Time 1 to Time 2, members of subgroups with higher PGI skills at Time 1 were more likely to be assigned to subgroups with lower PTSS at Time 2. The current study suggests a potential application of PGI skills in alleviating PTSS after a transportation accident and having a critical role in adjustment after hardship
Viral Dynamics of Delayed CTL-inclusive HIV-1 Infection Model With Both Virus-to-cell and Cell-to-cell Transmissions
Get PDFWe consider a mathematical model that describes a viral infection of HIV-1 with both virus-tocell and cell-to-cell transmission, CTL response immune and four distributed delays, describing intracellular delays and immune response delay. One of the main features of the model is that it includes a constant production rate of CTLs export from thymus, and an immune response delay. We derive the basic reproduction number and show that if the basic reproduction number is less than one, then the infection free equilibrium is globally asymptotically stable; whereas, if the basic reproduction number is greater than one, then there exist a chronic infection equilibrium, which is globally asymptotically stable in absence of immune response delay. Furthermore, for the special case with only immune response delay, we determine some conditions for stability switches of the chronic infection equilibrium. Numerical simulations indicate that the intracellular delays and immune response delay can stabilize and/or destabilize the chronic infection equilibrium
Some Summation Theorems for Clausen’s Hypergeometric Functions with Unit Argument
Get PDFMotivated by the work on hypergeometric summation theorems, we establish new summation formula for Clausen’s hypergeometric function with unit argument in terms of pi and natural logarithms of some rational and irrational numbers. For the application purpose, we derive some new and modified summation theorems for Clausen’s hypergeometric functions using our new formula