Flood-tolerant rice reduces yield variability and raises expected yield, differentially benefitting socially disadvantaged groups.

Approximately 30% of the cultivated rice area in India is prone to crop damage from prolonged flooding. We use a randomized field experiment in 128 villages of Orissa India to show that Swarna-Sub1, a recently released submergence-tolerant rice variety, has significant positive impacts on rice yield when fields are submerged for 7 to 14 days with no yield penalty without flooding. We estimate that Swarna-Sub1 offers an approximate 45% increase in yields over the current popular variety when fields are submerged for 10 days. We show additionally that low-lying areas prone to flooding tend to be more heavily occupied by people belonging to lower caste social groups. Thus, a policy relevant implication of our findings is that flood-tolerant rice can deliver both efficiency gains, through reduced yield variability and higher expected yield, and equity gains in disproportionately benefiting the most marginal group of farmers

Bacteriological profile of wound infections and antimicrobial resistance in selected gram-negative bacteria

Background: Managing wound infections is a challenging task. Understanding their resistance pattern is an essential step at reducing its burden in hospital settings. Objective: To determine the bacteriological diversity of wound infections and the antimicrobial resistance exhibited by a selected Gram-negative bacterium in the Aljouf region of Saudi Arabia. Methods: The study retrospectively analysed the antibiograms of wound infections from hospitalized patients for the year 2019. The European Centre for Disease Control guidelines were adopted for the classification of resistant bacteria. Multidrug-, extensive drug-, and carbapenem-resistant isolates are presented as frequencies and percentages. Results: A total of 295 non-duplicate wound swab antibiograms were retrieved, 64.4% (190) and 35.6% (105) isolates were Gram-negative and Gram-positive bacterial infections respectively. Predominant pathogens included Staphylococcus species 21.0% (62), E. coli 16.3% (48) and K. pneumoniae 13.5% (40). 148 (77.9%), 42 (22.1%) and 43 (22.6%) of the Gram-negative isolates were multidrug-, extensively drug- and carbapenem-resistant. The antibiotic resistance exhibited by gram-negative bacteria was 43.4% (234/539), 59.1% (224/379) and 53.7% (101/188) towards carbapenems, 3rd - and 4th – generation cephalosporins. Conclusions: The majority of wound infections are caused by multidrug-, extensively drug- and carbapenem-resistant Gram-negative bacteria. Further studies should focus on the molecular basis of this resistance. Keywords: Wound infections; hospital; Gram-negative bacteria; antibiograms; multidrug-resistance; E. coli

Evaluating multiple causes of persistent low microwave backscatter from Amazon forests after the 2005 drought

Amazonia has experienced large-scale regional droughts that affect forest productivity and biomass stocks. Space-borne remote sensing provides basin-wide data on impacts of meteorological anomalies, an important complement to relatively limited ground observations across the Amazon’s vast and remote humid tropical forests. Morning overpass QuikScat Ku-band microwave backscatter from the forest canopy was anomalously low during the 2005 drought, relative to the full instrument record of 1999–2009, and low morning backscatter persisted for 2006–2009, after which the instrument failed. The persistent low backscatter has been suggested to be indicative of increased forest vulnerability to future drought. To better ascribe the cause of the low post-drought backscatter, we analyzed multiyear, gridded remote sensing data sets of precipitation, land surface temperature, forest cover and forest cover loss, and microwave backscatter over the 2005 drought region in the southwestern Amazon Basin (4°-12°S, 66°-76°W) and in adjacent 8°x10° regions to the north and east. We found moderate to weak correlations with the spatial distribution of persistent low backscatter for variables related to three groups of forest impacts: the 2005 drought itself, loss of forest cover, and warmer and drier dry seasons in the post-drought vs. the pre-drought years. However, these variables explained only about one quarter of the variability in depressed backscatter across the southwestern drought region. Our findings indicate that drought impact is a complex phenomenon and that better understanding can only come from more extensive ground data and/or analysis of frequent, spatially-comprehensive, high-resolution data or imagery before and after droughts

Screening of Soybean (Glycine Max (L.) Merrill) Genotypes for Resistance to Rust, Yellow Mosaic and Pod Shattering

Applied optic

Kerr-Schild type initial data for black holes with angular momenta

Generalizing previous work we propose how to superpose spinning black holes in a Kerr-Schild initial slice. This superposition satisfies several physically meaningful limits, including the close and the far ones. Further we consider the close limit of two black holes with opposite angular momenta and explicitly solve the constraint equations in this case. Evolving the resulting initial data with a linear code, we compute the radiated energy as a function of the masses and the angular momenta of the black holes.Comment: 13 pages, 3 figures. Revised version. To appear in Classical and Quantum Gravit

Comment on ``Cosmological Gamma Ray Bursts and the Highest Energy Cosmic Rays''

In a letter with the above title, published some time ago in PRL, Waxman made the interesting suggestion that cosmological gamma ray bursts (GRBs) are the source of the ultra high energy cosmic rays (UHECR). This has also been proposed independently by Milgrom and Usov and by Vietri. However, recent observations of GRBs and their afterglows and in particular recent data from the Akeno Great Air Shwoer Array (AGASA) on UHECR rule out extragalactic GRBs as the source of UHECR.Comment: Comment on a letter with the above title published by E. Waxman in PRL 75, 386 (1995). Submitted for publication in PRL/Comment

E-Learner Recommendation Model Based on Level of Learning Outcomes Achievement

Students in any learning environment differ in their level of knowledge, achieved learning outcomes, learning style, preferences, misunderstand and attempts in solving and addressing problems when their expectations are not met. When a student searches the web as an attempt to solve a problem, he suffers from the large number of resources which are, in most cases, not related to his “needs”, or may be related but complex and advance. The result of his search might make him more confused, scattered, depressed and finally result in wasting his time which – in some cases -may have negative effects on his achievements. From here comes the need for an intelligent learning system that can guide studentsbased on their needs. This research attempts to design and build an educational recommender system for a web-based learning environment in order to generate meaningful recommendations of the most interested and relevant learning materials that suit students’ needs based on their profiles1 . This can be achieved by accessing students’ history, exploring their learning navigation patterns and making use of similar students’ experiences and their success stories. The study proposed a design for a hybrid recommender system architecture which consists of two recommendation approaches: the content and collaborative filtering. The study concentrates on the collaborative recommender engine which will recommend learning materials based on students’ level of knowledge, looking at active students' profiles, and achievements in both learning outcomes and learning outcomes levels making use of similar students’ success stories and reflecting their good experience on active student who are in the same level of knowledge. The design of the collaborative recommender engine includes the “learning” module from which the engine learns past students’ access pattern and the “advising” module from which the engine reflects the experience of similar success stories on active students. The content base recommender engine with its suggested stages is considered as future work, the research used the k-mean cluster algorithm to find out similar students where five distance function are used: Euclidean, Correlation. Jaccard,cosine and Manhattan. The cosine function shows to be the most accurate distance function with the minimum SSE but the highest processing time that doesn’t differ a lot when compared the rest functions. The best number of clusters for the selected dataset was determined using three methods Elbow, Gap-statistic and average Silhouette approach where the best number of cluster shows to be three. The research used the two result rating matrices of similar good and good students with Learnings material in order to calculate learning material weights and rank them based on highest weights which results in a final recommendation list

A mechanism linking Id2-TGFβ crosstalk to reversible adaptive plasticity in neuroblastoma

The ability of high-risk neuroblastoma to survive unfavorable growth conditions and multimodal therapy has produced an elusive childhood cancer with remarkably poor prognosis. A novel phenomenon enabling neuroblastoma to survive selection pressure is its capacity for reversible adaptive plasticity. This plasticity allows cells to transition between highly proliferative anchorage dependent (AD) and slow growing, anoikis-resistant anchorage independent (AI) phenotypes. Both phenotypes are present in established mouse and human tumors. The differential gene expression profile of the two cellular phenotypes in the mouse Neuro2a cell line delineated pathways of proliferation in AD cells or tyrosine kinase activation/ apoptosis inhibition in AI cells. A 20 fold overexpression of inhibitor of differentiation 2 (Id2) was identified in AD cells while up-regulation of genes involved in anoikis resistance like PI3K/Akt, Erk, Bcl2 and integrins was observed in AI cells. Similarly, differential expression of Id2 and other genes of interest were also observed in the AD and AI phenotypes of human neuroblastoma cell lines, SK-N-SH and IMR-32; as well as in primary human tumor specimens. Forced down-regulation of Id2 in AD cells or overexpression in AI cells induced the cells to gain characteristics of the other phenotype. Id2 binds both TGFβ and Smad2/3 and appears critical for maintaining the proliferative phenotype at least partially through negative regulation of the TGFβ/Smad pathway. Simultaneously targeting the differential molecular pathways governing reversible adaptive plasticity resulted in 50% cure of microscopic disease and delayed tumor growth in established mouse neuroblastoma tumors. We present a mechanism that accounts for reversible adaptive plasticity and a molecular basis for combined targeted therapies in neuroblastoma