Pengaruh Kondisi Tanah Terhadap Kerusakan Jalan Menggunakan Metode (PCI) Tirto Rahhayu Landung Sari Desa Mulyoagung Kecamatan Dau Kabupaten Malang

Tanah adalah suatu himpunan mineral, bahan organik, dan endapan-endapan relatif lepas,salah satunya pada konstruksi jalan raya.tanah sebagai pondasi sangat berpengaruh terhadap kualitas pelayanan dan kondisi konstruksi jalan. Kondisi ini terjadi di Jalan Tirto Rahayu Landung Sari-Desa Mulyoagung Kecamatan Dau Kabupaten Malang yang merupakan obyek penelitian.Dari hasil penelitian yang dilakukan sepanjang 1000 m yang di bagi menjadi 200 m persegmen di Jalan Tirto Rahayu Landung Sari Desa Mulyoagung Kecamatan Dau Kabupaten Malang,kondisi jalan mengalami kerusakan.Hal ini dilihat dari kerusakan permukaan aspal yang terkelupas,retak, dan berlubang.Nilai rata-rata Pavement Condition Index (PCI) jalan Tirto Rahayu Landung Sari Desa Mulyoagung Kecanatan Dau Kabupaten Malang yaitu 44 Cukup (Fair),jenis tanah setelah di lakukan penelitian dan lolos ayakan 200 = 35% tanah berbutir sebagian besar lanau dan lempung.hasil analisa saringan lolos ayakan 200,20,dan 10 yaitu batu pecah,kerikil,dan pasir.hasil analisa kadar air rata-rata yaitu 54,05%,hasil rata-rata nilai plastisitas yaitu 1,1 % < 10 % sehingga rata-rata tingkat plastisitas segmen rendah dengan jenis tanah Lanau.hasil nilai rata-rata CBR dan DDT menggunakan alat DCP yaitu sebesar 2,43 % < 5 % dengan nilai DDT sebesar 3,36. jalan ini perlu dimasukan dalam program pemiliharaan secara berkala dan Pemilihan perkerasan dalam menggulangi kerusakan pada jalan ini yaitu menggunakan perkerasan lentu

A mutation-selection model of protein evolution underpersistent positive selection

We use first principles of population genetics to model the evolution of proteins under persistent positive selection (PPS). PPS may occur when organisms are subjected to persistent environmental change, during adaptive radiations, or in host-pathogen interactions. Our mutation-selection model indicates protein evolution under PPS is an irreversible Markov process, and thus proteins under PPS show a strongly asymmetrical distribution of selection coefficients among amino acid substitutions. Our model shows the criteria ω > 1 (where ω is the ratio of non-synonymous over synonymous codon substitution rates) to detect positive selection is conservative and indeed arbitrary, because in real proteins many mutations are highly deleterious and are removed by selection even at positively-selected sites. We use a penalized-likelihood implementation of the PPS model to successfully detect PPS in plant RuBisCO and influenza HA proteins. By directly estimating selection coefficients at protein sites, our inference procedure bypasses the need for using ω as a surrogate measure of selection and improves our ability to detect molecular adaptation in proteins

Evidence for entanglement at high temperatures in an engineered molecular magnet

The molecular compound [Fe$_{2}$($\mu_{2}$-oxo)(C$_{3}$H$_{4}$N$_{2}$)$_{6}$(C$_{2}$O$_{4}$)$_{2}$] was designed and synthesized for the first time and its structure was determined using single-crystal X-ray diffraction. The magnetic susceptibility of this compound was measured from 2 to 300 K. The analysis of the susceptibility data using protocols developed for other spin singlet ground-state systems indicates that the quantum entanglement would remain at temperatures up to 732 K, significantly above the highest entanglement temperature reported to date. The large gap between the ground state and the first-excited state (282 K) suggests that the spin system may be somewhat immune to decohering mechanisms. Our measurements strongly suggest that molecular magnets are promising candidate platforms for quantum information processing

Análise in silico de genes de Caseíno-quinases tipo I e II de Coffea arabica.

As proteínas quinases são enzimas fundamentais na transmissão de sinais intra e extracelulares de organismos eucariotos, incluindo organismos unicelulares, animais e plantas. Esta classe de enzimas é responsável pela regulação de inúmeros processos celulares, incluindo divisão celular, expressão gênica, desenvolvimento de tecidos, entre outros. No gênero Coffea, há pouca informação sobre as proteínas quinases e o papel que desempenham. Este trabalho tem como objetivo identificar genes semelhantes a caseíno-quinase tipo I e caseíno-quinase tipo II, através da análise in silico utilizando a base de dados do CafEST

Second Generation of 'Miranda Procedure' for CP Violation in Dalitz Studies of B (\& D \& \tau) Decays

The `Miranda Procedure' proposed for analyzing Dalitz plots for CP asymmetries in charged B and D decays in a model-independent manner is extended and refined. The complexity of CKM CP phenomenology through order $\lambda^6$ is needed in searches for New Dynamics (ND). Detailed analyses of three-body final states other great advantages: (i) They give us more powerful tools for deciding whether an observed CP asymmetry rep- resents the manifestation of ND and its features. (ii) Many advantages can already be obtained by the `Miranda Procedure' without construction of a detailed Dalitz plot de- scription. (iii) One studies CP asymmetries independent of production asymmetries. We illustrate the power of a second generation Miranda Procedure with examples with time integrated rates for $B_d/\bar B_d$ decays to final states $K_S\pi+\pi-$ as trial runs with comments on $B^{\pm} \to K^{\pm}\pi^+\pi^-/K^{\pm}K^+K^-$.Comment: 29 pages, 7 figure

Bayesian estimation of species divergence times using correlated quantitative characters

Discrete morphological data have been widely used to study species evolution, but the use of quantitative (or continuous) morphological characters is less common. Here, we implement a Bayesian method to estimate species divergence times using quantitative characters. Quantitative character evolution is modelled using Brownian diffusion with character correlation and character variation within populations. Through simulations, we demonstrate that ignoring the population variation (or population “noise”) and the correlation among characters leads to biased estimates of divergence times and rate, especially if the correlation and population noise are high. We apply our new method to the analysis of quantitative characters (cranium landmarks) and molecular data from carnivoran mammals. Our results show that time estimates are affected by whether the correlations and population noise are accounted for or ignored in the analysis. The estimates are also affected by the type of data analysed, with analyses of morphological characters only, molecular data only, or a combination of both; showing noticeable differences among the time estimates. Rate variation of morphological characters among the carnivoran species appears to be very high, with Bayesian model selection indicating that the independent-rates model fits the morphological data better than the autocorrelated-rates model. We suggest that using morphological continuous characters, together with molecular data, can bring a new perspective to the study of species evolution. Our new model is implemented in the MCMCtree computer program for Bayesian inference of divergence times