Adjusting N, K, Mg and Cu Rates for Improvement of Fertilizer N Use Efficiency in Rice Production in Malaysia

The largest rice growing area of Malaysia is located in the Muda Irrigation Scheme. Recent investigations showed that N use efficiency by rice crop is very low in many locations of this Irrigation Scheme due to Cu and Mg deficiency. It is important to increase N use efficiency in rice culture in order to increase yield through better fertilizer management. Three laboratory, three greenhouse and one field experiments were carried out to determine the possible mechanisms for improvement of fertilizer N use efficiency in rice production. Potassium, Mg and Cu status of different rice soils were determined. Deficiencies of K, Mg and Cu were found in 5, 4 and 7 soils, respectively. Three laboratory experiments were carried out on adsorption of K, Mg and Cu in different rice soils. The data indicated that adsorption of K, Mg and Cu depends on soil pH. The first greenhouse experiment was conducted to evaluate the effects of N and Cu fertilization on rice yield and fertilizer N use efficiency in rice culture. Nitrogen was applied as 1 5N labelled urea. Estimated grain yield response to added N was quadratic in nature. Copper effect was not significant on grain yield. Effects of N and Cu were not significant on recovery (%) of fertilizer N. The second greenhouse experiment was conducted to evaluate the effects of N and Mg fertil ization on rice yield and fertilizer N use efficiency in rice culture. Nitrogen was applied as 1 5N labelled urea. Grain yield increased significantly due to N and Mg application. Fertilizer N uptake and recovery increased significantly with increasing Mg rates. These findings suggest that there is a prospect to increase grain yield and fertilizer N use efficiency by Mg application in Mg deficient soils. The third greenhouse experiment was conducted to evaluate the effects of K and Mg fertilization on yield, and K and Mg uptake by rice. Grain yield, K and Mg uptake increased significantly due to Mg fertilization whereas the effect of K was not significant. The field experiment was conducted to evaluate the effects Cu and Mg application on grain yield and agronomic efficiency of added N. Grain yield and agronomic efficiency of added N increased significantly due to Cu or Mg application. These findings suggest that combined application of Cu and Mg both at 10 kg ha-1 along with 120 kg N ha-1 can increase grain yield of rice by 24% in soils deficient in both Cu and Mg

A methodology for probabilistic aircraft technology assessment and selection under uncertainty

The high degree of complexity and uncertainty associated with aerospace engineering applications has driven designers and engineers towards the use of probabilistic and statistical analysis tools in order to understand and design for that uncertainty. As a result, probabilistic methods have permeated the aerospace field to the extent that single point deterministic designs are no longer credible, particularly in systems analysis, performance assessment, technology impact quantification, etc. However, as statistics theory is not the primary focus of most aerospace practitioners, incorrect assumptions and flawed methods are often unknowingly used in design. A common assumption of probabilistic assessments in the field of aerospace is the independence of random variables. These random variables represent design variables, noise variables, technology impacts, etc., which can be difficult to correlate but do have underlying relationships. The justification for the assumed independence is usually not discussed in the literature even though this can have a substantial effect on probabilistic assessment and uncertainty quantification results. In other cases the dependence between random variables is acknowledged but intentionally ignored on the basis of difficulty in characterizing underlying random variable relationships, a strong bias towards methodological simplicity and low computational expense, and the expectation of modest strength in random variable dependence. Probabilistic assessments also yield large amounts of data which is not effectively used due to the sheer volume of data and poor traceability to the drivers of uncertainty. The literature shows optimization techniques are resorted to in order to select from competing alternatives in multiobjective spaces, however, these techniques generally do not handle uncertainty well. The motivating question is, how can improvements be made to the probabilistic assessment process for aircraft technology assessments that capture technology impact tradeoffs and dependencies, and ultimately enable decision makers to make an axiomatic and rational selection under uncertainty? This question leads to the research objective of this work which is to develop a methodology ``to quantify and characterize aviation's environmental impact, uncertainties, and the trade-offs and interdependencies among various impacts'' \cite{Council2010}, in order to assess and select future aircraft technologies. Copula theory is suggested to address the problem of assumed independence on the input side of probabilistic assessments in aerospace applications. Copulas are functions that can be used to define probabilistic relationships between random variables. They are well documented in the literature and have been used in many fields such as the statistics, finance, and insurance industries. They can be used to quantify complex relationships, even if that is only qualitatively or notionally understood. In this way a designer's knowledge regarding uncertainty can be better represented and propagated to system level metrics through the probabilistic assessment. Utility theory is proposed as a solution to the challenge of effectively using output data from probabilistic assessments. Utility theory is a powerful tool used in economics, marketing, psychiatry, etc., to express preferences among competing alternatives. Utility theory can provide combined valuation to each alternative in a multiobjective design space while incorporating the uncertainty associated with each alternative. This can enable designers to rationally and axiomatically make selections consistent with their preferences, between complex solutions with varying degrees of uncertainty. This work provides an introduction to copula and utility theories for the aerospace audience. It also demonstrates how these theories can be applied in canonical problems to bridge gaps currently found in the literature with regards to probabilistic assessments of aircraft technologies. The key contributions of this research are (1) an Archimedean copula selection tree enabling practitioners to rapidly translate their qualitative understanding of dependence into copula families that can represent it quantitatively (2) estimation of the quantified effect of using copulas to capture probabilistic dependence in three representative aerospace applications (3) an expected utility formulation for axiomatically ranking and selecting aircraft technology packages under uncertainty and (4) a strategic elicitation procedure for multiattribute utility functions that does not need assumptions of independence conditions on preferences between the attributes. The proposed FAAST methodology is shown as an encompassing framework for the aircraft technology assessment and selection problem that fills capability gaps from the literature and supports the decision maker in a rational and axiomatic manner.Ph.D

A 15N tracer study to evaluate the effects of nitrogen and copper fertilization on fertilizer nitrogen efficiency in rice production

In the study of the effects of nitrogen and copper fertilization on rice yield when four rates of N (0, 60, 120 and 180 kg N/ha) as 15N labelled urea and three rates of Cu (0, 5 and 10 kg Cu/ha) were applied, grain yield increased significantly with increasing N rates upto 120 kg N/ha. The recovery of fertilizer N was around 40% irrespective of N and Cu rates. Copper application at 10 kg/ha increased grain yield by 0.53 t/ha insignificantly. Cu content in the straw was below the critical deficiency level of 6 mg/kg. Thus higher rate of Cu fertilizer (above 10 kg/ha) in soil increase rice yield and fertilizer N efficiency if Cu is applied as basal. Alternately, Cu may be applied as foliar spray on standing crop to avoid Cu adsorption in the soil

Study of Fractional Differential Equations Emerging in the Theory of Chemical Graphs: A Robust Approach

The study of the interconnections between chemical systems is known as chemical graph theory. Through the use of star graphs, a limited group of researchers has examined the space of possible solutions for boundary-value problems. They recognized that for their strategy to function, they needed a core node related to other nodes but not to itself; as a result, they opted to use star graphs. In this sense, the graphs of neopentane will be helpful in extending the scope of our technique. It has the CAS number 463-82-1 and the chemical formula C5H12, and it is a component of a petrochemical precursor. In order to determine whether or not the suggested boundary-value problems on these graphs have any known solutions, we use the theorems developed by Schaefer and Krasnoselskii on fixed points. In addition, we illustrate our preliminary results with the help of an example that we present

Effect of storage methods on viability of some hepatic enzymes in farm animals

In the course of a study of serum hepatic enzymes in the ruminants with storage effect was discovered, whose serum contained an Alanine transaminase (ALT), Aspartate transaminase (AST), Alkaline phosphatase (ALP) which was indistinguishable from sheep, cattle, and goats. However, the fundamental storage study of these enzymes is poorly understood in farm animals. Therefore this paper was aimed to determine the relations of two storage methods. The same enzyme was demonstrated in high concentration in the cattle and its linear decreases during storage over 8 weeks in all three animals tested. This single case demonstrates the possibility that elevated serum alkaline phosphatase in animals with -20 oC can be of neoplastic rather than of hepatic storage at 5 oC

Computational modeling of animal behavior in T-mazes: Insights from machine learning

This study investigates the intricacies of animal decision-making in T-maze environments through a synergistic approach combining computational modeling and machine learning techniques. Focusing on the binary decision-making process in T-mazes, we examine how animals navigate choices between two paths. Our research employs a mathematical model tailored to the decision-making behavior of fish, offering analytical insights into their complex behavioral patterns. To complement this, we apply advanced machine learning algorithms, specifically Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and a hybrid approach involving Principal Component Analysis (PCA) for dimensionality reduction followed by SVM for classification to analyze behavioral data from zebrafish and rats. The above techniques result in high predictive accuracies, approximately 98.07% for zebrafish and 98.15% for rats, underscoring the efficacy of computational methods in decoding animal behavior in controlled experiments. This study not only deepens our understanding of animal cognitive processes but also showcases the pivotal role of computational modeling and machine learning in elucidating the dynamics of behavioral science

The existence and uniqueness of solutions to a functional equation arising in psychological learning theory

The paradigm of choice practice represents the psychological theory of learning in the development of moral judgment. It is concerned with evaluating the implications of several choices and selecting one of them to implement. The goal of this work is to provide a generic functional equation to observe the behavior of animals in such circumstances. Our suggested functional equation can be employed to describe several well-known psychology and learning theories. The fixed point theorem proposed by Banach is utilized to show that the solution of a given functional problem exists and is unique. In addition, the stability of the given functional equation's solution is discussed in terms of the Hyers-Ulam and Hyers-Ulam-Rassias results. Furthermore, two examples are provided to highlight the relevance of the significant outcomes in the context of the literature

Mathematical modelling of a rumour spreading with the attitude of adjusting mechanisms

With the advent of the internet, social media of Facebook and Twitter, as well as the communication technology of WhatsApp and Telegram, the speed and scope of the rumour dissemination has been expanded. Understanding the characterization of rumour dissemination and how it spreads can help in mitigation measures to avoid the spread of the rumour. Therefore, it is crucial to propose a mathematical model, and in particular this paper is concerned with the epidemic model to understand the dissemination of the rumour in social network. The mechanism of rumour propagation is behaving like infectious diseases spread; hence this research adopted the epidemiological model approach. In this network, the compartment is divided into susceptible, ignorant, propagation and stiflers. The basic influence number, the equilibrium points of rumour-free and the endemic equilibrium state were obtained and discussed. For the local stability, the Next Generation Matrix was used. Numerical simulation is performed to understand the dynamics of the spread of rumour in a population or social networks, its impact in a population, and adjusting mechanisms in curbing the spread of rumour

Feedbacks between sea-floor spreading, trade winds and precipitation in the Southern Red Sea

Feedbacks between climatic and geological processes are highly controversial and testing them is a key challenge in Earth sciences. The Great Escarpment of the Arabian Red Sea margin has several features that make it a useful natural laboratory for studying the effect of surface processes on deep Earth. These include strong orographic rainfall, convex channel profiles versus concave swath profiles on the west side of the divide, morphological disequilibrium in fluvial channels, and systematic morphological changes from north to south that relate to depth changes of the central Red Sea. Here we show that these features are well interpreted with a cycle that initiated with the onset of spreading in the Red Sea and involves feedbacks between orographic precipitation, tectonic deformation, mid-ocean spreading and coastal magmatism. It appears that the feedback is enhanced by the moist easterly trade winds that initiated largely contemporaneously with sea floor spreading in the Red Sea