The critical role of water in spider silk and its consequence for protein mechanics

Due to its remarkable mechanical and biological properties, there is considerable interest in understanding, and replicating, spider silk's stress-processing mechanisms and structure-function relationships. Here, we investigate the role of water in the nanoscale mechanics of the different regions in the spider silk fibre, and their relative contributions to stress processing. We propose that the inner core region, rich in spidroin II, retains water due to its inherent disorder, thereby providing a mechanism to dissipate energy as it breaks a sacrificial amide-water bond and gains order under strain, forming a stronger amide-amide bond. The spidroin I-rich outer core is more ordered under ambient conditions and is inherently stiffer and stronger, yet does not on its own provide high toughness. The markedly different interactions of the two proteins with water, and their distribution across the fibre, produce a stiffness differential and provide a balance between stiffness, strength and toughness under ambient conditions. Under wet conditions, this balance is destroyed as the stiff outer core material reverts to the behaviour of the inner core.

An Integrated Assessment Of The Suitability Of Domestic Solar Still As A Viable Safe Water Technology For India

Improving access to safe drinking water can result in multi-dimensional impacts on people's livelihood. This has been aptly reflected in the Millennium Development Goals (MDG) as one of the major objectives. Despite the availability of diverse and complex set of technologies for water purification, pragmatic and cost-effective use of the same is impeding the use of available sources of water. Hence, in country like India simple low-energy technologies such as solar still are likely to succeed. Solar stills would suffice the basic minimum drinking water requirements of man. Solar stills use sunlight, to kill or inactivate many, if not all, of the pathogens found in water. This paper provides an integrated assessment of the suitability of domestic solar still as a viable safe water technology for India. Also an attempt has been made to critically assess the operational feasibility and costs incurred for using this technology in rural India.

Fuzzy optimization model for water quality management of a river system - Closure

A fuzzy waste-load allocation model, FWLAM, is developed for water quality management of a river system using fuzzy multiple-objective optimization. An important feature of this model is its capability to incorporate the aspirations and conflicting objectives of the pollution control agency and dischargers. The vagueness associated with specifying the water quality criteria and fraction removal levels is modeled in a fuzzy framework. The goals related to the pollution control agency and dischargers are expressed as fuzzy sets. The membership functions of these fuzzy sets are considered to represent the variation of satisfaction levels of the pollution control agency and dischargers in attaining their respective goals. Two formulations—namely, the MAX-MIN and MAX-BIAS formulations—are proposed for FWLAM. The MAX-MIN formulation maximizes the minimum satisfaction level in the system. The MAX-BIAS formulation maximizes a bias measure, giving a solution that favors the dischargers. Maximization of the bias measure attempts to keep the satisfaction levels of the dischargers away from the minimum satisfaction level and that of the pollution control agency close to the minimum satisfaction level. Most of the conventional water quality management models use waste treatment cost curves that are uncertain and nonlinear. Unlike such models, FWLAM avoids the use of cost curves. Further, the model provides the flexibility for the pollution control agency and dischargers to specify their aspirations independently.

Fuzzy Logic-Based Approaches in Water Resource System Modelling

Recent research in modelling uncertainty in water resource systems has highlighted the use of fuzzy logic-based approaches. A number of research contributions exist in the literature that deal with uncertainty in water resource systems including fuzziness, subjectivity, imprecision and lack of adequate data. This chapter presents a broad overview of the fuzzy logic-based approaches adopted in addressing uncertainty in water resource systems modelling. Applications of fuzzy rule-based systems and fuzzy optimisation are then discussed. Perspectives on the scope for further research are presented.

Evaluation of ion exchange as a pre-treatment option for coal seam gas water

The Coal Seam Gas (CSG) industry in Australia has grown significantly in recent years. During the gas extraction process, water is also recovered which is brackish in character. In order to facilitate beneficial reuse of the water, the CSG industry has primarily invested in Reverse Osmosis (RO) as the primary method for associated water desalination. However, the presence of alkaline earth ions in the water combined with the inherent alkalinity of the water may result in RO membrane scaling. Consequently, weak acid cation (WAC) synthetic ion exchange resins were investigated as a potential solution to this potential problem. It was shown that resins were indeed highly efficient at treating single and multi-component solutions of alkaline earth ions. The interaction of the ions with the resin was found to be considerably more complex that previously reported.

Metal-Ion-Dependent Oxidative DNA Cleavage by Transition Metal Complexes of a New Water-Soluble Salen Derivative

A new water-soluble, salen [salen = bis(salicylidene) ethylenediamine]-based ligand, 3 was developed. Two of the metal complexes of this ligand, i.e., 3a, [Mn(III)] and 3b, [Ni(II)], in the presence of cooxidant magnesium monoperoxyphthalate (MMPP) cleaved plasmid DNA pTZ19R efficiently and rapidly at a concentration similar to 1 mu M. In contrast, under comparable conditions, other metal complexes 3c, [Cu(II)] or 3d, [Cr(III)] could not induce any significant DNA nicking. The findings with Ni(II) complex suggest that the DNA cleavage processes can be modulated by the disposition of charges around the ligand.

Carbon nanodot decorated graphitic carbon nitride: New insights into the enhanced photocatalytic water splitting from ab initio studies

Interfacing carbon nanodots (C-dots) with graphitic carbon nitride (g-C3N4) produces a metal-free system that has recently demonstrated significant enhancement of photo-catalytic performance for water splitting into hydrogen [Science, 2015, 347, 970–974]. However, the underlying photo-catalytic mechanism is not fully established. Herein, we have carried out density functional theory (DFT) calculations to study the interactions between g-C3N4 and trigonal/hexagonal shaped C-dots. We find that hybrid C-dots/g-C3N4 can form a type-II van der Waals heterojunction, leading to significant reduction of band gap. The C-dot decorated g-C3N4 enhances the separation of photogenerated electron and hole pairs and the composite's visible light response. Interestingly, the band alignment of C-dots and g-C3N4 calculated by the hybrid functional method indicates that C-dots act as a spectral sensitizer in hybrid C-dots/g-C3N4 for water splitting. Our results offer new theoretical insights into this metal-free photocatalyst for water splitting.

X-ray diffraction of permalloy nanoparticles fabricated by laser ablation in water

Permalloy (NiFeMo) nanoparticles were fabricated by laser ablation of bulk material in water with a UV pulsed laser. Transmission electron microscope images showed that approximately spherical particles about 50 nm in diameter were formed in the ablation process. All diffraction peaks corresponding to the bulk material were present in the nanoparticles. In addition to these peaks several new peaks were observed in the nanoparticles, which were attributed to nickel oxide.

Dynamical Transition of Water in the Grooves of DNA Duplex at Low Temperature

At low temperature (below its freezing/melting temperature), liquid water under confinement is known to exhibit anomalous dynamical features. Here we study structure and dynamics of water in the grooves of a long DNA duplex using molecular dynamics simulations with TIP5P potential at low temperature. We find signatures of a dynamical transition in both translational and orientational dynamics of water molecules in both the major and the minor grooves of a DNA duplex. The transition occurs at a slightly higher temperature (TGL ≈ 255 K) than the temperature at which the bulk water is found to undergo a dynamical transition, which for the TIP5P potential is at 247 K. Groove water, however, exhibits markedly different temperature dependence of its properties from the bulk. Entropy calculations reveal that the minor groove water is ordered even at room temperature, and the transition at T ≈ 255 K can be characterized as a strong-to-strong dynamical transition. Confinement of water in the grooves of DNA favors the formation of a low density four-coordinated state (as a consequence of enthalpy−entropy balance) that makes the liquid−liquid transition stronger. The low temperature water is characterized by pronounced tetrahedral order, as manifested in the sharp rise near 109° in the O−O−O angle distribution. We find that the Adams−Gibbs relation between configurational entropy and translational diffusion holds quite well when the two quantities are plotted together in a master plot for different region of aqueous DNA duplex (bulk, major, and minor grooves) at different temperatures. The activation energy for the transfer of water molecules between different regions of DNA is found to be weakly dependent on temperature.

Security issues for future intelligent transport systems

Cooperative Intelligent Transportation Systems (C-ITS) allow in-vehicle systems, and ultimately the driver, to enhance their awareness of their surroundings by enabling communication between vehicles and road infrastructure. C-ITS are widely considered as the next major step in driving assistance systems, aiming at increasing safety, comfort and mobility for drivers. However, any communicating systems are subjected to security threats. A key component for providing secure communications at a large scale is a Public Key Infrastructure (PKI). Due to the safety-critical nature of Vehicle-to-Vehicle (V2V) communications, a C-ITS PKI has functional, performance and scalability requirements that differ from traditional non-automotive environments. This paper identifies and defines the key functional and security requirements for C-ITS PKI systems and analyses proposed C-ITS PKI standards against these requirements. In particular, the proposed US and European C-ITS PKI systems are identified as being too complex and not scalable. The paper also highlights various privacy, security and scalability concerns that should be considered for a secure C-ITS PKI solution in the Australian transport landscape.

Intelligent thermal energy meter cum controller for solar water heating systems

A microcontroller based, thermal energy meter cum controller (TEMC) suitable for solar thermal systems has been developed. It monitors solar radiation, ambient temperature, fluid flow rate, and temperature of fluid at various locations of the system and computes the energy transfer rate. It also controls the operation of the fluid-circulating pump depending on the temperature difference across the solar collector field. The accuracy of energy measurement is +/-1.5%. The instrument has been tested in a solar water heating system. Its operation became automatic with savings in electrical energy consumption of pump by 30% on cloudy days.

On the nature of power flow equations in security analysis

The power system network is assumed to be in steady-state even during low frequency transients. However, depending on generator dynamics, and toad and control characteristics, the system model and the nature of power flow equations can vary The nature of power flow equations describing the system during a contingency is investigated in detail. It is shown that under some mild assumptions on load-voltage characteristics, the power flow equations can be decoupled in an exact manner. When the generator dynamics are considered, the solutions for the load voltages are exact if load nodes are not directly connected to each other

Rank regression analysis of correlated water quality data from South East Queensland

With growing population and fast urbanization in Australia, it is a challenging task to maintain our water quality. It is essential to develop an appropriate statistical methodology in analyzing water quality data in order to draw valid conclusions and hence provide useful advices in water management. This paper is to develop robust rank-based procedures for analyzing nonnormally distributed data collected over time at different sites. To take account of temporal correlations of the observations within sites, we consider the optimally combined estimating functions proposed by Wang and Zhu (Biometrika, 93:459-464, 2006) which leads to more efficient parameter estimation. Furthermore, we apply the induced smoothing method to reduce the computational burden. Smoothing leads to easy calculation of the parameter estimates and their variance-covariance matrix. Analysis of water quality data from Total Iron and Total Cyanophytes shows the differences between the traditional generalized linear mixed models and rank regression models. Our analysis also demonstrates the advantages of the rank regression models for analyzing nonnormal data.

Wavelet-based multiresolution analysis of Wivenhoe Dam water temperatures

Water temperature measurements from Wivenhoe Dam offer a unique opportunity for studying fluctuations of temperatures in a subtropical dam as a function of time and depth. Cursory examination of the data indicate a complicated structure across both time and depth. We propose simplifying the task of describing these data by breaking the time series at each depth into physically meaningful components that individually capture daily, subannual, and annual (DSA) variations. Precise definitions for each component are formulated in terms of a wavelet-based multiresolution analysis. The DSA components are approximately pairwise uncorrelated within a given depth and between different depths. They also satisfy an additive property in that their sum is exactly equal to the original time series. Each component is based upon a set of coefficients that decomposes the sample variance of each time series exactly across time and that can be used to study both time-varying variances of water temperature at each depth and time-varying correlations between temperatures at different depths. Each DSA component is amenable for studying a certain aspect of the relationship between the series at different depths. The daily component in general is weakly correlated between depths, including those that are adjacent to one another. The subannual component quantifies seasonal effects and in particular isolates phenomena associated with the thermocline, thus simplifying its study across time. The annual component can be used for a trend analysis. The descriptive analysis provided by the DSA decomposition is a useful precursor to a more formal statistical analysis.

Nonparametric rank regression for analyzing water quality concentration data with multiple detection limits

Environmental data usually include measurements, such as water quality data, which fall below detection limits, because of limitations of the instruments or of certain analytical methods used. The fact that some responses are not detected needs to be properly taken into account in statistical analysis of such data. However, it is well-known that it is challenging to analyze a data set with detection limits, and we often have to rely on the traditional parametric methods or simple imputation methods. Distributional assumptions can lead to biased inference and justification of distributions is often not possible when the data are correlated and there is a large proportion of data below detection limits. The extent of bias is usually unknown. To draw valid conclusions and hence provide useful advice for environmental management authorities, it is essential to develop and apply an appropriate statistical methodology. This paper proposes rank-based procedures for analyzing non-normally distributed data collected at different sites over a period of time in the presence of multiple detection limits. To take account of temporal correlations within each site, we propose an optimal linear combination of estimating functions and apply the induced smoothing method to reduce the computational burden. Finally, we apply the proposed method to the water quality data collected at Susquehanna River Basin in United States of America, which dearly demonstrates the advantages of the rank regression models.