A framework for the selection of the right nuclear power plant

Civil nuclear reactors are used for the production of electrical energy. In the nuclear industry vendors propose several nuclear reactor designs with a size from 35–45 MWe up to 1600–1700 MWe. The choice of the right design is a multidimensional problem since a utility has to include not only financial factors as levelised cost of electricity (LCOE) and internal rate of return (IRR), but also the so called “external factors” like the required spinning reserve, the impact on local industry and the social acceptability. Therefore it is necessary to balance advantages and disadvantages of each design during the entire life cycle of the plant, usually 40–60 years. In the scientific literature there are several techniques for solving this multidimensional problem. Unfortunately it does not seem possible to apply these methodologies as they are, since the problem is too complex and it is difficult to provide consistent and trustworthy expert judgments. This paper fills the gap, proposing a two-step framework to choosing the best nuclear reactor at the pre-feasibility study phase. The paper shows in detail how to use the methodology, comparing the choice of a small-medium reactor (SMR) with a large reactor (LR), characterised, according to the International Atomic Energy Agency (2006), by an electrical output respectively lower and higher than 700 MWe

Bio-Inspired Preparation of Clay–Hexacyanoferrate Composite Hydrogels as Super Adsorbents for Cs+

A facile and low-cost fabrication route, inspired by the adhesive proteins secreted by mussels, has been developed to prepare a clay-based composite hydrogel (DHG(Cu)) containing hexacyanoferrate (HCF) nanoparticles for the selective removal of Cs+ from contaminated water. Initially, montmorillonite was exfoliated prior to coating with a thin layer of polydopamine (PDOPA) via the self-polymerization of dopamine. Mixing the composite (D-clay) with the HCF precursor, followed by the addition of copper ions, led to the self-assembly of the polymer-coated exfoliated clay nanosheets into a three-dimensional network and in situ growth of KCuHCF nanoparticles embedded within the gel structure. Analytical characterization verified the fabrication route and KCuHCF immobilization by a copper–ligand complexation. Rheology testing revealed the composite hydrogel to be elastic under low strain and exhibited reversible, self-healing behavior following high strain deformation, providing a good retention of KCuHCF nanoparticles in the membrane. The adsorbent DHG(Cu) showed a superior Cs+ adsorption capacity (∼173 mg/g), with the performance maintained over a wide pH range, and an excellent selectivity for Cs+ when dispersed in seawater at low concentrations of 0.2 ppm. On the basis of its excellent mechanico-chemical properties, the fabricated hydrogel was tested as a membrane in column filtration, showing excellent removal of Cs+ from Milli-Q water and seawater, with the performance only limited by the fluid residence time. For comparison, the study also considered other composite hydrogels, which were fabricated as intermediates of DHG(Cu) or fabricated with Fe3+ as the cross-linker and reactant for HCF nanoparticle synthesis

Geometric frustration in the myosin superlattice of vertebrate muscle

Geometric frustration results from an incompatibility between minimum energy arrangements and the geometry of a system, and gives rise to interesting and novel phenomena. Here, we report geometric frustration in a native biological macromolecular system---vertebrate muscle. We analyse the disorder in the myosin filament rotations in the myofibrils of vertebrate striated (skeletal and cardiac) muscle, as seen in thin-section electron micrographs, and show that the distribution of rotations corresponds to an archetypical geometrically frustrated system---the triangular Ising antiferromagnet. Spatial correlations are evident out to at least six lattice spacings. The results demonstrate that geometric frustration can drive the development of structure in complex biological systems, and may have implications for the nature of the actin--myosin interactions involved in muscle contraction. Identification of the distribution of myosin filament rotations with an Ising model allows the extensive results on the latter to be applied to this system. It shows how local interactions (between adjacent myosin filaments) can determine long-range order and, conversely, how observations of long-range order (such as patterns seen in electron micrographs) can be used to estimate the energetics of these local interactions. Furthermore, since diffraction by a disordered system is a function of the second-order statistics, the derived correlations allow more accurate diffraction calculations, which can aid in interpretation of X-ray diffraction data from muscle specimens for structural analysis

Enhanced stochastic optimization algorithm for finding effective multi-target therapeutics

<p>Abstract</p> <p>Background</p> <p>For treating a complex disease such as cancer, we need effective means to control the biological network that underlies the disease. However, biological networks are typically robust to external perturbations, making it difficult to beneficially alter the network dynamics by controlling a single target. In fact, multi-target therapeutics is often more effective compared to monotherapies, and combinatory drugs are commonly used these days for treating various diseases. A practical challenge in combination therapy is that the number of possible drug combinations increases exponentially, which makes the prediction of the optimal drug combination a difficult combinatorial optimization problem. Recently, a stochastic optimization algorithm called the Gur Game algorithm was proposed for drug optimization, which was shown to be very efficient in finding potent drug combinations.</p> <p>Results</p> <p>In this paper, we propose a novel stochastic optimization algorithm that can be used for effective optimization of combinatory drugs. The proposed algorithm analyzes how the concentration change of a specific drug affects the overall drug response, thereby making an informed guess on how the concentration should be updated to improve the drug response. We evaluated the performance of the proposed algorithm based on various drug response functions, and compared it with the Gur Game algorithm.</p> <p>Conclusions</p> <p>Numerical experiments clearly show that the proposed algorithm significantly outperforms the original Gur Game algorithm, in terms of reliability and efficiency. This enhanced optimization algorithm can provide an effective framework for identifying potent drug combinations that lead to optimal drug response.</p

Clinical utility of WHO-recommended screening tools and development and validation of novel clinical prediction models for pulmonary tuberculosis screening among outpatients living with HIV: an individual participant data meta-analysis

BACKGROUND: The World Health Organization (WHO) recommends that outpatient people living with HIV (PLHIV) undergo tuberculosis screening with the WHO four-symptom screen (W4SS) or C-reactive protein (CRP) (5 mg·L-1 cut-off) followed by confirmatory testing if screen positive. We conducted an individual participant data meta-analysis to determine the performance of WHO-recommended screening tools and two newly developed clinical prediction models (CPMs). METHODS: Following a systematic review, we identified studies that recruited adult outpatient PLHIV irrespective of tuberculosis signs and symptoms or with a positive W4SS, evaluated CRP and collected sputum for culture. We used logistic regression to develop an extended CPM (which included CRP and other predictors) and a CRP-only CPM. We used internal-external cross-validation to evaluate performance. RESULTS: We pooled data from eight cohorts (n=4315 participants). The extended CPM had excellent discrimination (C-statistic 0.81); the CRP-only CPM had similar discrimination. The C-statistics for WHO-recommended tools were lower. Both CPMs had equivalent or higher net benefit compared with the WHO-recommended tools. Compared with both CPMs, CRP (5 mg·L-1 cut-off) had equivalent net benefit across a clinically useful range of threshold probabilities, while the W4SS had a lower net benefit. The W4SS would capture 91% of tuberculosis cases and require confirmatory testing for 78% of participants. CRP (5 mg·L-1 cut-off), the extended CPM (4.2% threshold) and the CRP-only CPM (3.6% threshold) would capture similar percentages of cases but reduce confirmatory tests required by 24, 27 and 36%, respectively. CONCLUSIONS: CRP sets the standard for tuberculosis screening among outpatient PLHIV. The choice between using CRP at 5 mg·L-1 cut-off or in a CPM depends on available resources

Prediction of peptide and protein propensity for amyloid formation

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔGº values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation

A Preliminary Study on Robot-Assisted Ankle Rehabilitation for the Treatment of Drop Foot

This paper involves the use of a compliant ankle rehabilitation robot (CARR) for the treatment of drop foot. The robot has a bio-inspired design by employing four Festo Fluidic muscles (FFMs) that mimic skeletal muscles actuating three rotational degrees of freedom (DOFs). A trajectory tracking controller was developed in joint task space to track the predefined trajectory of the end effector. This controller was achieved by controlling individual FFM length based on inverse kinematics. Three patients with drop foot participated in a preliminary study to evaluate the potential of the CARR for clinical applications. Ankle stretching exercises along ankle dorsiflexion and plantarflexion (DP) were delivered for treating drop foot. All patients gave positive feedback in using this ankle robot for the treatment of drop foot, although some limitations exist. The proposed controller showed satisfactory accuracy in trajectory tracking, with all root mean square deviation (RMSD) values no greater than 0.0335 rad and normalized root mean square deviation (NRMSD) values less than 6.7%. These preliminary findings support the potentials of the CARR for clinical applications. Future work will investigate the effectiveness of the robot for treating drop foot on a large sample of subjects

Dengue virus neutralizing antibody levels associated with protection from infection in Thai cluster studies

BACKGROUND: Long-term homologous and temporary heterologous protection from dengue virus (DENV) infection may be mediated by neutralizing antibodies. However, neutralizing antibody titers (NTs) have not been clearly associated with protection from infection. METHODOLOGY/PRINCIPAL FINDINGS: Data from two geographic cluster studies conducted in Kamphaeng Phet, Thailand were used for this analysis. In the first study (2004-2007), cluster investigations of 100-meter radius were triggered by DENV-infected index cases from a concurrent prospective cohort. Subjects between 6 months and 15 years old were evaluated for DENV infection at days 0 and 15 by DENV PCR and IgM ELISA. In the second study (2009-2012), clusters of 200-meter radius were triggered by DENV-infected index cases admitted to the provincial hospital. Subjects of any age 6 months and older were evaluated for DENV infection at days 0 and 14. In both studies, subjects who were DENV PCR positive at day 14/15 were considered to have been susceptible on day 0. Comparison subjects from houses in which someone had documented DENV infection, but the subject remained DENV negative at days 0 and 14/15, were considered non-susceptible. Day 0 samples were presumed to be from just before virus exposure, and underwent plaque reduction neutralization testing (PRNT). Seventeen susceptible (six DENV-1, five DENV-2, and six DENV-4), and 32 non-susceptible (13 exposed to DENV-1, 10 DENV-2, and 9 DENV-4) subjects were evaluated. Comparing subjects exposed to the same serotype, receiver operating characteristic (ROC) curves identified homotypic PRNT titers of 11, 323 and 16 for DENV-1, -2 and -4, respectively, to differentiate susceptible from non-susceptible subjects. CONCLUSIONS/SIGNIFICANCE: PRNT titers were associated with protection from infection by DENV-1, -2 and -4. Protective NTs appeared to be serotype-dependent and may be higher for DENV-2 than other serotypes. These findings are relevant for both dengue epidemiology studies and vaccine development efforts

Tear fluid biomarkers in ocular and systemic disease: potential use for predictive, preventive and personalised medicine

In the field of predictive, preventive and personalised medicine, researchers are keen to identify novel and reliable ways to predict and diagnose disease, as well as to monitor patient response to therapeutic agents. In the last decade alone, the sensitivity of profiling technologies has undergone huge improvements in detection sensitivity, thus allowing quantification of minute samples, for example body fluids that were previously difficult to assay. As a consequence, there has been a huge increase in tear fluid investigation, predominantly in the field of ocular surface disease. As tears are a more accessible and less complex body fluid (than serum or plasma) and sampling is much less invasive, research is starting to focus on how disease processes affect the proteomic, lipidomic and metabolomic composition of the tear film. By determining compositional changes to tear profiles, crucial pathways in disease progression may be identified, allowing for more predictive and personalised therapy of the individual. This article will provide an overview of the various putative tear fluid biomarkers that have been identified to date, ranging from ocular surface disease and retinopathies to cancer and multiple sclerosis. Putative tear fluid biomarkers of ocular disorders, as well as the more recent field of systemic disease biomarkers, will be shown

An approach for particle sinking velocity measurements in the 3–400 μm size range and considerations on the effect of temperature on sinking rates

The flux of organic particles below the mixed layer is one major pathway of carbon from the surface into the deep ocean. The magnitude of this export flux depends on two major processes—remineralization rates and sinking velocities. Here, we present an efficient method to measure sinking velocities of particles in the size range from approximately 3–400 μm by means of video microscopy (FlowCAM®). The method allows rapid measurement and automated analysis of mixed samples and was tested with polystyrene beads, different phytoplankton species, and sediment trap material. Sinking velocities of polystyrene beads were close to theoretical values calculated from Stokes’ Law. Sinking velocities of the investigated phytoplankton species were in reasonable agreement with published literature values and sinking velocities of material collected in sediment trap increased with particle size. Temperature had a strong effect on sinking velocities due to its influence on seawater viscosity and density. An increase in 9 °C led to a measured increase in sinking velocities of ~40 %. According to this temperature effect, an average temperature increase in 2 °C as projected for the sea surface by the end of this century could increase sinking velocities by about 6 % which might have feedbacks on carbon export into the deep ocean