Screening of suitable cationic dopants for solar absorber material CZTS/Se: A first principles study

The earth abundant and non-toxic solar absorber material kesterite Cu2ZnSn(S/Se)(4) has been studied to achieve high power conversion efficiency beyond various limitations, such as secondary phases, antisite defects, band gap adjustment and microstructure. To alleviate these hurdles, we employed screening based approach to find suitable cationic dopant that can promote the current density and the theoretical maximum upper limit of the energy conversion efficiency (P(%)) of CZTS/Se solar devices. For this task, the hybrid functional (Heyd, Scuseria and Ernzerhof, HSE06) were used to study the electronic and optical properties of cation (Al, Sb, Ga, Ba) doped CZTS/Se. Our in-depth investigation reveals that the Sb atom is suitable dopant of CZTS/CZTSe and also it has comparable bulk modulus as of pure material. The optical absorption coefficient of Sb doped CZTS/Se is considerably larger than the pure materials because of easy formation of visible range exciton due to the presence of defect state below the Fermi level, which leads to an increase in the current density and P(%). Our results demonstrate that the lower formation energy, preferable energy gap and excellent optical absorption of the Sb doped CZTS/Se make it potential component for relatively high efficient solar cells

Statistical tools for transgene copy number estimation based on real-time PCR

Background As compared with traditional transgene copy number detection technologies such as Southern blot analysis, real-time PCR provides a fast, inexpensive and high-throughput alternative. However, the real-time PCR based transgene copy number estimation tends to be ambiguous and subjective stemming from the lack of proper statistical analysis and data quality control to render a reliable estimation of copy number with a prediction value. Despite the recent progresses in statistical analysis of real-time PCR, few publications have integrated these advancements in real-time PCR based transgene copy number determination. Results Three experimental designs and four data quality control integrated statistical models are presented. For the first method, external calibration curves are established for the transgene based on serially-diluted templates. The Ct number from a control transgenic event and putative transgenic event are compared to derive the transgene copy number or zygosity estimation. Simple linear regression and two group T-test procedures were combined to model the data from this design. For the second experimental design, standard curves were generated for both an internal reference gene and the transgene, and the copy number of transgene was compared with that of internal reference gene. Multiple regression models and ANOVA models can be employed to analyze the data and perform quality control for this approach. In the third experimental design, transgene copy number is compared with reference gene without a standard curve, but rather, is based directly on fluorescence data. Two different multiple regression models were proposed to analyze the data based on two different approaches of amplification efficiency integration. Our results highlight the importance of proper statistical treatment and quality control integration in real-time PCR-based transgene copy number determination. Conclusion These statistical methods allow the real-time PCR-based transgene copy number estimation to be more reliable and precise with a proper statistical estimation. Proper confidence intervals are necessary for unambiguous prediction of trangene copy number. The four different statistical methods are compared for their advantages and disadvantages. Moreover, the statistical methods can also be applied for other real-time PCR-based quantification assays including transfection efficiency analysis and pathogen quantification

Comparative genome analysis of lignin biosynthesis gene families across the plant kingdom

<p>Abstract</p> <p>Background</p> <p>As a major component of plant cell wall, lignin plays important roles in mechanical support, water transport, and stress responses. As the main cause for the recalcitrance of plant cell wall, lignin modification has been a major task for bioenergy feedstock improvement. The study of the evolution and function of lignin biosynthesis genes thus has two-fold implications. First, the lignin biosynthesis pathway provides an excellent model to study the coordinative evolution of a biochemical pathway in plants. Second, understanding the function and evolution of lignin biosynthesis genes will guide us to develop better strategies for bioenergy feedstock improvement.</p> <p>Results</p> <p>We analyzed lignin biosynthesis genes from fourteen plant species and one symbiotic fungal species. Comprehensive comparative genome analysis was carried out to study the distribution, relatedness, and family expansion of the lignin biosynthesis genes across the plant kingdom. In addition, we also analyzed the comparative synteny map between rice and sorghum to study the evolution of lignin biosynthesis genes within the <it>Poaceae </it>family and the chromosome evolution between the two species. Comprehensive lignin biosynthesis gene expression analysis was performed in rice, poplar and <it>Arabidopsis</it>. The representative data from rice indicates that different fates of gene duplications exist for lignin biosynthesis genes. In addition, we also carried out the biomass composition analysis of nine <it>Arabidopsis </it>mutants with both MBMS analysis and traditional wet chemistry methods. The results were analyzed together with the genomics analysis.</p> <p>Conclusion</p> <p>The research revealed that, among the species analyzed, the complete lignin biosynthesis pathway first appeared in moss; the pathway is absent in green algae. The expansion of lignin biosynthesis gene families correlates with substrate diversity. In addition, we found that the expansion of the gene families mostly occurred after the divergence of monocots and dicots, with the exception of the C4H gene family. Gene expression analysis revealed different fates of gene duplications, largely confirming plants are tolerant to gene dosage effects. The rapid expansion of lignin biosynthesis genes indicated that the translation of transgenic lignin modification strategies from model species to bioenergy feedstock might only be successful between the closely relevant species within the same family.</p

Anodic-oxide-induced intermixing in GaAs-AlGaAs quantum-well and quantum-wire structures

Anodic oxides of GaAs were shown to enhance the intermixing in GaAs-AlGaAs quantum wells (QW) during rapid thermal processing. Proximity of the anodic oxide to the QW has been shown to influence the photoluminescence (PL) energy shift due to intermixing. Anodic oxide induced intermixing has been used to enhance quantum-wire PL in the structures grown on V-groove patterned GaAs substrates. This has been attributed to enhanced lateral confinement in these structures. Injection of defects such as group-III vacancies or interstitials was considered to be driving force for the intermixing.published_or_final_versio

Social interaction, noise and antibiotic-mediated switches in the intestinal microbiota

The intestinal microbiota plays important roles in digestion and resistance against entero-pathogens. As with other ecosystems, its species composition is resilient against small disturbances but strong perturbations such as antibiotics can affect the consortium dramatically. Antibiotic cessation does not necessarily restore pre-treatment conditions and disturbed microbiota are often susceptible to pathogen invasion. Here we propose a mathematical model to explain how antibiotic-mediated switches in the microbiota composition can result from simple social interactions between antibiotic-tolerant and antibiotic-sensitive bacterial groups. We build a two-species (e.g. two functional-groups) model and identify regions of domination by antibiotic-sensitive or antibiotic-tolerant bacteria, as well as a region of multistability where domination by either group is possible. Using a new framework that we derived from statistical physics, we calculate the duration of each microbiota composition state. This is shown to depend on the balance between random fluctuations in the bacterial densities and the strength of microbial interactions. The singular value decomposition of recent metagenomic data confirms our assumption of grouping microbes as antibiotic-tolerant or antibiotic-sensitive in response to a single antibiotic. Our methodology can be extended to multiple bacterial groups and thus it provides an ecological formalism to help interpret the present surge in microbiome data.Comment: 20 pages, 5 figures accepted for publication in Plos Comp Bio. Supplementary video and information availabl

LES-based Study of the Roughness Effects on the Wake of a Circular Cylinder from Subcritical to Transcritical Reynolds Numbers

This paper investigates the effects of surface roughness on the flow past a circular cylinder at subcritical to transcritical Reynolds numbers. Large eddy simulations of the flow for sand grain roughness of size k/D = 0.02 are performed (D is the cylinder diameter). Results show that surface roughness triggers the transition to turbulence in the boundary layer at all Reynolds numbers, thus leading to an early separation caused by the increased momentum deficit, especially at transcritical Reynolds numbers. Even at subcritical Reynolds numbers, boundary layer instabilities are triggered in the roughness sublayer and eventually lead to the transition to turbulence. The early separation at transcritical Reynolds numbers leads to a wake topology similar to that of the subcritical regime, resulting in an increased drag coefficient and lower Strouhal number. Turbulent statistics in the wake are also affected by roughness; the Reynolds stresses are larger due to the increased turbulent kinetic energy production in the boundary layer and separated shear layers close to the cylinder shoulders.We acknowledge “Red Española de Surpercomputación” (RES) for awarding us access to the MareNostrum III machine based in Barcelona, Spain (Ref. FI-2015-2-0026 and FI-2015-3-0011). We also acknowledge PRACE for awarding us access to Fermi and Marconi Supercomputers at Cineca, Italy (Ref. 2015133120). Oriol Lehmkuhl acknowledges a PDJ 2014 Grant by AGAUR (Generalitat de Catalunya). Ugo Piomelli acknowledges the support of the Natural Sciences and Engineering Research Council (NSERC) of Canada under the Discovery Grant Programme (Grant No. RGPIN-2016-04391). Ricard Borrell acknowledges a Juan de la Cierva postdoctoral grant (IJCI-2014-21034). Ivette Rodriguez, Oriol Lehmkuhl, Ricard Borrell and Assensi Oliva acknowledge Ministerio de Economía y Competitividad, Secretaría de Estado de Investigación, Desarrollo e Innovación, Spain (ref. ENE2014-60577-R).Peer ReviewedPostprint (author's final draft

Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study

BACKGROUND: Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. RESULTS: The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. CONCLUSIONS: Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens

Higgs boson enhancement effects on squark-pair production at the LHC

We study the Higgs boson effects on third-generation squark-pair production in proton-proton collision at the CERN Large Hadron Collider (LHC), including \Stop \Stop^*, \Stop\Sbot^*, and \Sbot \Sbot^*. We found that substantial enhancement can be obtained through s-channel exchanges of Higgs bosons at large $\tan\beta$, at which the enhancement mainly comes from $b\bar b$, $b\bar c$, and $c\bar b$ initial states. We compute the complete set of electroweak (EW) contributions to all production channels. This completes previous computations in the literature. We found that the EW contributions can be significant and can reach up to 25% in more general scenarios and at the resonance of the heavy Higgs boson. The size of Higgs enhancement is comparable or even higher than the PDF uncertainties and so must be included in any reliable analysis. A full analytical computation of all the EW contributions is presented.Comment: 23 pages, 7 figures, 1 tabl

On the selection and design of proteins and peptide derivatives for the production of photoluminescent, red-emitting gold quantum clusters

Novel pathways of the synthesis of photoluminescent gold quantum clusters (AuQCs) using biomolecules as reactants provide biocompatible products for biological imaging techniques. In order to rationalize the rules for the preparation of red-emitting AuQCs in aqueous phase using proteins or peptides, the role of different organic structural units was investigated. Three systems were studied: proteins, peptides, and amino acid mixtures, respectively. We have found that cysteine and tyrosine are indispensable residues. The SH/S-S ratio in a single molecule is not a critical factor in the synthesis, but on the other hand, the stoichiometry of cysteine residues and the gold precursor is crucial. These observations indicate the importance of proper chemical behavior of all species in a wide size range extending from the atomic distances (in the AuI-S semi ring) to nanometer distances covering the larger sizes of proteins assuring the hierarchical structure of the whole self-assembled system