Feedforward backpropagation, genetic algorithm approaches for predicting reference evapotranspiration

Water scarcity is a global concern, as the demand for water is increasing tremendously and poor management of water resources will accelerates dramatically the depletion of available water. The precise prediction of evapotranspiration (ET), that consumes almost 100% of the supplied irrigation water, is one of the goals that should be adopted in order to avoid more squandering of water especially in arid and semiarid regions. The capabilities of feedforward backpropagation neural networks (FFBP) in predicting reference evapotranspiration (ET0) are evaluated in this paper in comparison with the empirical FAO Penman-Monteith (P-M) equation, later a model of FFBP+Genetic Algorithm (GA) is implemented for the same evaluation purpose. The study location is the main station in Iraq, namely Baghdad Station. Records of weather variables from the related meteorological station, including monthly mean records of maximum air temperature (Tmax), minimum air temperature (Tmin), sunshine hours (Rn), relative humidity (Rh) and wind speed (U2), from the related meteorological station are used in the prediction of ET0 values. The performance of both simulation models were evaluated using statistical coefficients such as the root of mean squared error (RMSE), mean absolute error (MAE) and coefficient of determination (R2). The results of both models are promising, however the hybrid model shows higher efficiency in predicting ET0 and could be recommended for modeling of ET0 in arid and semiarid regions

Analysis of simple sequence repeat markers linked with blast disease resistance genes in a segregating population of rice (Oryza sativa).

Among 120 simple sequence repeat (SSR) markers, 23 polymorphic markers were used to identify the segregation ratio in 320 individuals of an F(2) rice population derived from Pongsu Seribu 2, a resistant variety, and Mahsuri, a susceptible rice cultivar. For phenotypic study, the most virulent blast (Magnaporthe oryzae) pathotype, P7.2, was used in screening of F(2) population in order to understand the inheritance of blast resistance as well as linkage with SSR markers. Only 11 markers showed a good fit to the expected segregation ratio (1:2:1) for the single gene model (d.f. = 1.0, P < 0.05) in chi-square (χ(2)) analyses. In the phenotypic data analysis, the F(2) population segregated in a 3:1 (R:S) ratio for resistant and susceptible plants, respectively. Therefore, resistance to blast pathotype P7.2 in Pongsu Seribu 2 is most likely controlled by a single nuclear gene. The plants from F(2) lines that showed resistance to blast pathotype P7.2 were linked to six alleles of SSR markers, RM168 (116 bp), RM8225 (221 bp), RM1233 (175 bp), RM6836 (240 bp), RM5961 (129 bp), and RM413 (79 bp). These diagnostic markers could be used in marker assisted selection programs to develop a durable blast resistant variety

SSRs for marker assisted selection for blast resistance in rice (Oryza sativa L.).

Rice blast caused by the fungus Magnaporthe oryzae is one of the most devastating diseases of rice in nearly all rice growing areas of the world including Malaysia. To develop cultivars with resistance against different races of M. oryzae, availability of molecular markers along with marker-assisted selection strategies are essential. In this study, 11 polymorphic simple sequence repeat (SSR) markers with good fit of 1:2:1 ratio for single gene model in F2 population derived from the cross of Pongsu seribu 2 (Resistant) and Mahsuri (Susceptible) rice cultivars were analysed in 296 F3 families derived from individual F2 plants to investigate association with Pi gene conferring resistance to M. oryzae pathotype. Parents and progeny were grouped into two phenotypic classes based on their blast reactions. Chi-square test for the segregation of resistance and susceptibility in F3 generation fitted a ratio of approximately 3:1. Association of SSR markers with phenotypic trait in F3 families was identified by statistical analysis. Four SSR markers (RM413, RM5961, RM1233 and RM8225) were significantly associated with blast resistance to pathotype 7.2 of M. oryzae in rice (p ≤ 0.01). These four markers accounted for about 20% of total phenotypic variation. So, these markers were confirmed as suitable markers for use in marker-assisted selection and confirmation of blast resistance genes to develop rice cultivars with durable blast resistance in Malaysian rice breeding programmes

Quantification of the modification of cratonic lithospheric mantle by major tectono-magmatic events:A petrological and geochemical study of mantle xenoliths from the Tanzania Craton

Davies, G.R. [Promotor]Koornneef, J.M. [Copromotor

Supersymmetric CP Violation in B→Xsl+l−B \to X_s l^+ l^- in Minimal Supergravity Model

Direct CP asymmetries and the CP violating normal polarization of lepton in inclusive decay B \to X_s l^+ l^- are investigated in minimal supergravity model with CP violating phases. The contributions coming from exchanging neutral Higgs bosons are included. It is shown that the direct CP violation in branching ratio, A_{CP}^1, is of {\cal{O}}(10^{-3}) for l=e, \mu, \tau. The CP violating normal polarization for l=\mu can reach 0.5 percent when tan\beta is large (say, 36). For l=\tau and in the case of large \tan\beta, the direct CP violation in backward-forward asymmetry, A_{CP}^2, can reach one percent, the normal polarization of \tau can be as large as a few percent, and both are sensitive to the two CP violating phases, \phi_\mu and \phi_{A_0}, and consequently it could be possible to observe them (in particular, the normal polarization of \tau) in the future B factories.Comment: 14 pages, latex, 5 figure

Pengembangan Instrumen Penilaian Psikomotor pada Pembelajaran IPA Kelas V SD

Penelitian ini merupakan penelitian pengembangan. Tahap penelitian ini dibatasi sampai pada tahap perbaikan desain. Permasalahan dalam penelitian ini meliputi (1) bagaimanakah kondisi objektif instrumen penilaian psikomotor pada pembelajaran IPA di kelas V SDN 32 Kota Selatan? (2)&nbsp; bagaimanakah&nbsp; instrumen penilaian psikomotor pada pembelajaran IPA yang akan dikembangkan di kelas V SDN 32 Kota Selatan? dan (3) bagaimanakah kelayakan insrtuman penilaian psikomotor yang telah dikembangkan&nbsp; di SDN 32 Kota Selatan?. Objek dalam penelitian ini adalah Instrumen Penilaian Psikomotor pada pembelajaran IPA kelas V di SDN 32 Kota Selatan. Tehnik pengumpulan data yang peneliti gunakan yaitu tehnik wawancara, observasi, dan dokumentasi. Produk yang dihasilkan oleh peneliti dalam penelitian pengembangan ini berupa produk instrumen penilaian psikomotor pada pembelajaran IPA kelas V di SDN 32 Kota Selatan, yang didalamnya memuat sampul buku, kata pengantar, daftar isi, petunjuk Penggunaan, pembatas KD, lembar kerja peserta didik, instrumen penilaian, rubrik penilaian, portofolio dan daftar pustaka. Hasil penelitian pengembangan tersebut divalidasi oleh ahli materi dan memperoleh skor hasil validasi 85,71 dan untuk ahli media memperoleh skor 96,47. Hasil rekapitulasi skor validasi dari 2 validator memperoleh skor keseluruhan 91,09. Berdasarkan hasil penelitian dapat disimpulkan bahwa instrumen penilaian psikomotor pada pembelajaran IPA yang dikembangkan sangat layak digunakan serta dapat dilanjutkan ketahap selanjutnya. &nbsp

Industry 4.0 readiness models: A systematic literature review of model dimensions

It is critical for organizations to self-assess their Industry 4.0 readiness to survive and thrive in the age of the Fourth Industrial Revolution. Thereon, conceptualization or development of an Industry 4.0 readiness model with the fundamental model dimensions is needed. This paper used a systematic literature review (SLR) methodology with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and content analysis strategy to review 97 papers in peer-reviewed academic journals and industry reports published from 2000 to 2019. The review identifies 30 Industry 4.0 readiness models with 158 unique model dimensions. Based on this review, there are two theoretical contributions. First, this paper proposes six dimensions (Technology, People, Strategy, Leadership, Process and Innovation) that can be considered as the most important dimensions for organizations. Second, this review reveals that 70 (44%) out of total 158 total unique dimensions on Industry 4.0 pertain to the assessment of technology alone. This establishes that organizations need to largely improve on their technology readiness, to strengthen their Industry 4.0 readiness. In summary, these six most common dimensions, and in particular, the dominance of the technology dimension provides a research agenda for future research on Industry 4.0 readines