FUZZY SUBSETS OF THE PHENOTYPES OF F2-OFFSPRING

This paper presents a connection between fuzzy sets, biological inheritance and hyperstructures in which we consider the set of phenotypes of the second generation $F_{2}$ in different types of inheritance, define fuzzy subsets of it and construct a sequence of join spaces associated to each of its types

3D Geographical routing in wireless sensor networks

In this paper, we present a novel 3D geographical routing algorithm (3DGR) that makes use of the position information to route packets from sources to destinations with high path quality and reliability. The locality and high scalability of this algorithm make it suitable for wireless sensor networks. It provides high adaptability to changes in topology and recovery of link failures which increases its reliability. We also incorporate the battery-aware energy efficient schemes to increase the overall lifetime of the network. To reduce latency, a method of keeping a small record of recent paths is used. We also show that location errors still result in good performance of our algorithm while the same assumptions might yield to bad performance or even complete failures in others. Simulation results show that the power consumption and delay using 3DGR are close to optimal obtainable based on full knowledge of the network

HYPERHROUPS AND Hv-GROUPS ASSOCIATED TO ELEMENTS WITH FOUR OXIDATION STATES

The theory of hyperstructures is of great importance due to its connections to various fields of Science. $H_v$-structures are hyperstructures where the equality is replaced by the nonempty intersection. This class of the hyperstructures is very large so one can use it in order to define several objects that they are not possible to be defined in the classical hyperstructure theory. This paper attempts an exposition of the connection between hyperstructure ($H_v$-structure) theory and certain type of chemical reactions. In this regard, we consider elements with four oxidation states and investigate their mathematical structures

Some factors affecting agricultural production .and productivity in Iraq including selected climate variables and crops

In this study of factors affecting Iraqi agricultural production and productivity, it has been found essential to deal both with socioeconomic and technical factors on the one hand and environmental conditons on the other. The ultimate objective of this study is to assess the impact of selected climatic factors on the production and productivity of some principal crops. Such assessment, however, cannot be achieved in isolation from the influence of the socio-economic and technical factors. Considerable variability over time of the latter factors, caused by specific institutional changes such as the land reform of 1958, resulted in changes in agricultural conditions as a whole. Therefore, in Chapters Two to Nine are examined the national and regional conditions of Iraqi agriculture during the 1950-1975 period, i.e. planning and investment, land utilization, land tenure system and land reform, agricultural cooperatives and other organizations, new input factors including farm machinery and, finally, water resources and irrigation methods. The inescapable conclusion of this section of the study is that there were no significant medium or long-term improvement trends in the yields of principal crops despite varying but considerable additional inputs and planning attention. Moreover, the controls exerted by climate and weather appear crucial factors in both the irrigated and rainfed area. In Chapters Ten and Eleven we therefore turn to a direct examination of climatic and weather factors. In Chapters Twelve and Thirteen a study is made of the relationship between selected weather variables, i.e. rainfall, temperature and relative humidity, and wheat and barley yield. These two crops were chosen because of their importance to Iraqi agriculture as a whole, and in particular to the rainfed area of northern Iraq where environmental modifications by man are least strong. The first point appearing from this analysis shows that yields of these two crops are significantly affected by climatic and weather factors during specific periods within the growing season. The significance of statistical correlations between yields and certain critical climatic factors appear sufficiently valid for crop forecasting with a certain degree of accuracy. As a by-product of this analysis, it appears that there was a significant dislocation period following the implementation of land reform measures. In conclusion, it is clear that agricultural production and productivity must be dealt with in the context of a whole set of factors, socio-economic, technical and environmental, if significant developments in agriculture and rural welfare are to be achieved

NeutroOrderedAlgebra: Applications to Semigroups

Starting with a partial order on a NeutroAlgebra, we get a NeutroStructure. The latter if it satisfies the conditions of NeutroOrder, it becomes a NeutroOrderedAlgebra. In this paper, we apply our new defined notion to semigroups by studying NeutroOrderedSemigroups. More precisely, we define some related terms like NeutrosOrderedSemigroup, NeutroOrderedIdeal, NeutroOrderedFilter, NeutroOrderedHomomorphism, etc., illustrate them via some examples, and study some of their properties

Extraction, Purification and Characterization (A) of Arginine Deiminase Enzyme from a Local Higher Productive Isolation of Enterococcus faecium M1

Arginine deiminase (ADI) enzyme was extracted from Enterococcus faecium M1 isolate and lysozyme was efficient in bacterial cell lyses more than Triton-X100 and Glass beads.ADI was more active in the range of (50-80%) ammonium sulfate saturations. After purification by anion exchange and gel filtration chromatography the specific activity of ADI reached to 59.2 U/mg protein with 11.23 folds and 42.93% yield. The purity of enzyme was estimated by Native-PAGE electrophoresis under non denatured conditions. The whole average molecular weight of ADI was 186 KDa, included two non- identical bands on SDS- PAGE, one of them had 52 KDa and the other had40 KDa. By concluding, ADI may contain four polypeptide subunits (tetrarmeric enzyme). Optimum pH for enzyme activity was ranged between (6.5 to 7.5) with maximum activity at pH 7.0 and still active over a wide range of pH values (4.0-10), ADI was more stable at pH level (6.0-7.5) with full remaining activity. By concluding, the maximum activity and stability of ADI in neutral pH encouraged us to use it as anticancer treatment agent and for other applications in human body. Keywords: Arginine deiminase, E. faecium M1, Extraction, Purification, Characterization (A)

Single valued neutrosophic (M; n)-ideals of ordered Semirings

The aim of this paper is to combine the innovative concept of single valued neutrosophic sets and ordered semirings. It studies ordered semirings by the properties of their single valued neutrosphic subsets. In this regard, we define single valued neutrosophic (m; n)-ideals (SVN-(m; n)-ideals) of ordered semirings. First, we illustrate our new definition by non-trivial examples. Second, we study these SVN-(m; n)-ideals under different operations of SVNS. Finally, we find a relationship between the (m; n)-ideals of ordered semirings and level sets by finding a necessary and sufficient condition for an SVNS of an ordered semiring R to be an SVN-(m; n)-ideal of R

Contrastive Learning of Auditory Representations

Learning rich visual representations using contrastive self-supervised learning has been extremely successful. However, it is still a major question whether we could use a similar approach to learn more efficient auditory and audio-visual representations. In this thesis, we expand on prior self-supervised methods to learn better auditory and audio-visual representations. We introduce various data augmentations suitable for auditory and audio-visual data and evaluate their impact on predictive performance, and demonstrate that training with both supervised and contrastive losses simultaneously improves the learned representations compared to self-supervised pre-training followed by supervised fine-tuning. We illustrate that by combining all these methods and with substantially less labeled data, our framework achieves significant improvement on prediction performance compared to the supervised approach. Moreover, compared to the self-supervised approach, our framework converges faster with significantly better representations