Inherent Synergies Research Articles

Mixed methods research teams: leveraging integrative teamwork for addressing complex problems

Mixed methods research teams have garnered increased attention for their leveraging of diverse disciplinary and methodological expertise in pursuit of complex problems. We advance our theoretical viewpoint of integrative mixed methods research teamwork as necessary with empirical evidence demonstrating the equipping mixed methods researchers to study complex problems involving interacting systems and lacking known solutions. Integrative mixed methods research teamwork is distinguishable by the purposeful integration of qualitative and quantitative perspectives to generate novel outcomes that are greater than the sum of individual members’ contributions. Among the key dilemmas faced by mixed methods researchers wanting to work integratively within a team is the lack of practical guidance for how to get started, how to recognize the emergence of synergistic outcomes, and how to sustain a team’s integrative work. To begin addressing this gap, we describe three practical insights gleaned from examining our team interactions and outcomes using a reflection-in-action process during a recent empirical mixed methods case study of literacy practices. In our examination, we test the practical usefulness of a theoretical framework for demystifying the development of a mixed methods research team’s integrative capacity. Our insights contribute to refining teamwork practices by identifying enablers of integrative capacity and proposing ways to overcome hindrances that have not been previously elucidated. We argue that the capacity for integrative teamwork is essential for researchers employing mixed methods, allowing them to leverage inherent synergies when addressing complex problems.

A new "gold standard": Perturbative triples corrections in unitary coupled cluster theory and prospects for quantum computing.

A major difficulty in quantum simulation is the adequate treatment of a large collection of entangled particles, synonymous with electron correlation in electronic structure theory, with coupled cluster (CC) theory being the leading framework for dealing with this problem. Augmenting computationally affordable low-rank approximations in CC theory with a perturbative account of higher-rank excitations is a tractable and effective way of accounting for the missing electron correlation in those approximations. This is perhaps best exemplified by the "gold standard" CCSD(T) method, which bolsters the baseline CCSD with the effects of triple excitations using considerations from many-body perturbation theory (MBPT). Despite this established success, such a synergy between MBPT and the unitary analog of CC theory (UCC) has not been explored. In this work, we propose a similar approach wherein converged UCCSD amplitudes are leveraged to evaluate energy corrections associated with triple excitations, leading to the UCCSD[T] method. In terms of quantum computing, this correction represents an entirely classical post-processing step that improves the energy estimate by accounting for triple excitation effects without necessitating new quantum algorithm developments or increasing demand for quantum resources. The rationale behind this choice is shown to be rigorous by studying the properties of finite-order UCC energy functionals, and our efforts do not support the addition of the fifth-order contributions as in the (T) correction. We assess the performance of these approaches on a collection of small molecules and demonstrate the benefits of harnessing the inherent synergy between MBPT and UCC theories.

Visible-light-driven tetracycline hydrochloride degradation via ZnTi-LDHs/Ce2S3 Z-scheme heterojunctions: Performance and mechanistic analysis

The refractory and hard-to-dispose tetracycline hydrochloride (TC) poses an enormous threat to human health and the water environment. Herein, a novel Z-scheme ZnTi-LDHs/Ce2S3 heterojunction photocatalyst was successfully developed for TC degradation under visible light conditions. This sophisticated material demonstrated a remarkable degradation rate of 0.0124 min−1, marking a noteworthy advancement compared to ZnTi-LDHs, Ce2S3, and the commonly reported LDHs/LDHs-based composites, with an approximate one-order-of-magnitude improvement. The inherent synergy between Ce2S3 and LDHs manifested as a Z-scheme charge transfer channel, augmenting visible-light absorption, and fostering carrier separation. Both O2·- and h+ played critical roles in the TC degradation process, mediating reductive and oxidative pathways, respectively. ZnTi-LDHs/Ce2S3 demonstrated robust reusability and broad applicability for degrading diverse dyes and antibiotics. This work demonstrated a promising protocol for crafting efficient Z-scheme heterojunction photocatalysts based on LDHs and expanded our understanding and potential applications of photocatalytic degradation mechanisms for antibiotics.

Combining unsupervised, supervised and rule-based learning: the case of detecting patient allergies in electronic health records

BackgroundData mining of electronic health records (EHRs) has a huge potential for improving clinical decision support and to help healthcare deliver precision medicine. Unfortunately, the rule-based and machine learning-based approaches used for natural language processing (NLP) in healthcare today all struggle with various shortcomings related to performance, efficiency, or transparency.MethodsIn this paper, we address these issues by presenting a novel method for NLP that implements unsupervised learning of word embeddings, semi-supervised learning for simplified and accelerated clinical vocabulary and concept building, and deterministic rules for fine-grained control of information extraction. The clinical language is automatically learnt, and vocabulary, concepts, and rules supporting a variety of NLP downstream tasks can further be built with only minimal manual feature engineering and tagging required from clinical experts. Together, these steps create an open processing pipeline that gradually refines the data in a transparent way, which greatly improves the interpretable nature of our method. Data transformations are thus made transparent and predictions interpretable, which is imperative for healthcare. The combined method also has other advantages, like potentially being language independent, demanding few domain resources for maintenance, and able to cover misspellings, abbreviations, and acronyms. To test and evaluate the combined method, we have developed a clinical decision support system (CDSS) named Information System for Clinical Concept Searching (ICCS) that implements the method for clinical concept tagging, extraction, and classification.ResultsIn empirical studies the method shows high performance (recall 92.6%, precision 88.8%, F-measure 90.7%), and has demonstrated its value to clinical practice. Here we employ a real-life EHR-derived dataset to evaluate the method’s performance on the task of classification (i.e., detecting patient allergies) against a range of common supervised learning algorithms. The combined method achieves state-of-the-art performance compared to the alternative methods we evaluate. We also perform a qualitative analysis of common word embedding methods on the task of word similarity to examine their potential for supporting automatic feature engineering for clinical NLP tasks.ConclusionsBased on the promising results, we suggest more research should be aimed at exploiting the inherent synergies between unsupervised, supervised, and rule-based paradigms for clinical NLP.

The Untapped Potential of the Quadruple Aim of Primary Care to Foster a Culture of Health.

In 2015, the Robert Wood Johnson Foundation introduced the Culture of Health (CoH) action model to inform its grantmaking decisions in the United States. The essential principles of this model fall into four action dimensions: 1) making health a shared value, 2) fostering cross-sector collaboration, 3) creating more equitable communities, and 4) transforming healthcare systems. Although considerable success has been achieved since introduction of the CoH model, the pace of progress has been slower on the fourth dimension, since work in this area involves shifting mindsets from the acute care paradigm to one that focuses on prevention, by addressing the "upstream factors", including social and behavioral determinants impacting health. Moreover, despite its academic prominence, the CoH model remains restricted to the research realm, with limited translation to practice. By comparison, the Quadruple Aim (QA) is a four-dimensional framework that has been successfully translated into primary healthcare practice. Introduced in 2008, the QA entails the adoption of four principles in delivering healthcare: 1) improved patient experience, 2) population health, 3) lower costs, and 4) care team well-being, to achieve value in healthcare. The four principles of the QA could be viewed as analogous to the four principles of the CoH, given the inherent synergies in the underlying philosophy of the two frameworks. It is also noteworthy that both healthcare leadership (physician champions) and legislative reform had significant roles to play in the successful translation of the QA into mainstream practice. This in turn suggests that the primary healthcare system has potential to play an instrumental role in accelerating the pace of progress towards a culture of health by extending the scope of influence of the QA. This paper explores the inherent synergies between the QA and CoH models, and the untapped potential of the QA to foster a culture of health in the United States.

Approaches to Bio-Cultural Diversity in British Columbia

This paper highlights an action research project into some decolonizing practices for environmental learning in the Canadian context of the British Columbia (BC) curriculum through case study and focus groups with Indigenous educators. A key finding taken from these discussions is that educators must strive to learn with Indigenous people not about them as the process of decolonization is about acknowledging multiple knowledge and value systems. We hosted two consultations with groups of Indigenous knowledge holders in the process of our work. The first consisted of a purposeful sample of Indigenous educators and academics drawn from Coast Salish communities in and around urban regions in coastal British Columbia (N = 20), the second draws on a purposeful sample of rural Indigenous educators and academics drawn from the Okanagan valley and British Columbia Interior (N = 10). The vignettes we share focus on how educational policy can be infused with Indigenous knowledges and pedagogical perspectives and, respectively, how policy changes might inform instruction on climate change education and a variety of other environmental topics. The revised framework we produce will guide teachers in their educational planning and support the implementation of environmental learning in diverse subjects using the dual lenses of bio-cultural diversity and inquiry—teaching about the environment and Indigenous knowledges together as an organizing theme for all teaching and learning. Our work highlights key aspects of our research involving practicing teachers, academics, provincial Ministries of Education and Environment as well as the Canadian Commission for UNESCO. The research articulates several important bridge-building activities: one linking research and policy, one bridging theory with practice, and most importantly, one bridging the inherent synergies among Indigenous and environmental knowledges.

Delivering Tram-Based Boulevards: Learning from Opportunities and Challenges in Three European City Case Studies

Increasing calls for zero-carbon cities invite transformative solutions for people and places within our cities around the world. Key to the transformation is cities and regions shifting in mobility away from fossil-fuel based car-oriented solutions. The paper investigates a range of case studies where “tram-based boulevards” have been planned or implemented to provide such opportunities. The case studies share a common broader policy objective: to transform the car-oriented or car-saturated areas to an intensified urban template based on a critical presence of dedicated mid-tier transit infrastructure and active transport. “Trams”, or mid-tier, mid-capacity transit when combined with Transit oriented development (TOD) along whole corridors can provide transformative pathways towards zero-carbon outcomes as well as multiple, strong urban benefits. However, many successful or instructive examples of this practice from non-English speaking countries, particularly in Europe, are underdocumented in the international literature. The paper addresses this gap by investigating opportunities and challenges evident in a range of European case studies. These are explored for insight towards policy learning particularly in New World cities seeking to transform into a zero-carbon and more transit-oriented template: How can decision-makers avoid repeating the identified pitfalls, and instead focus on emulating the successful approaches and outcomes? We conclude the need for recognition of the inherent synergies between transport and land use settings in any endeavour, and their translation into policy priorities in both fields of planning. We also conclude the importance of decision makers proactively identifying and critically appraising specific opportunities for change, concerning funding, technology, public opinion, stakeholder alliances or market dynamics, and capitalising on them at suitable moments in time.

FogChain: A Blockchain-Based Peer-to-Peer Solar Power Trading System Powered by Fog AI

Microgrids, gaining traction from rising distributed generation for carbon reduction, demand novel solutions to regulate on- and off-grid operations, as well as both energy and monetary transfers between the microgrid and the central grid and among different microgrid participants. This research aims to develop and validate an intelligent microgrid management system to secure the competitiveness of Singapore’s energy market, by leveraging the inherent synergy between two emerging technologies, i.e., blockchain for Peer-to-Peer (P2P) solar power trading and fog computing for grid infrastructure management. For this vision, we have developed FogChain, an integrative, cost-effective, and scalable microgrid operating system (MGOS), consisting of three technical service layers: 1) a novel microgrid information infrastructure based on the fog-computing paradigm (i.e., intelligence on edge); 2) a blockchain-based microgrid service layer, providing smart contract and decentralized control capabilities for grid application development; and 3) a microgrid application layer (i.e., P2P energy trading) over the blockchain-based grid service. This MGOS would fundamentally transform how solar power is traded among participating electricity prosumers, leading to potentially new operational and business models. We have implemented the FogChain system and conducted extensive experiments to verify its performance advantages. Our results demonstrate that FogChain can efficiently process energy auction among 1000 participants with 1.1 s delay on average, reduce transmission cost up to 20% under the loss-aware trading mechanism, and reduce the solar yield prediction error to 0.11. Our system prototype suggests that FogChain provides a promising solution for efficient decentralized energy trading and intelligent distributed control for microgrids.

Machine learning-informed ensemble framework for evaluating shale gas production potential: Case study in the Marcellus Shale

Artificial intelligence and machine learning (ML) are being applied to many oil and gas (O&G) applications and seen as novel techniques that may facilitate efficiency gains in exploration and production operations. Significant improvements in that regard are likely to occur when ML can be applied to evaluate O&G challenges with inherent synergies that may have otherwise not been evaluated concurrently. This study introduces an ensembled framework that couples a data-driven ML predictive model capable estimating a productivity indicator for unconventional O&G horizontal wells that correlates to estimated ultimate recovery (EUR) with a well design optimization approach that maximizes productivity. The framework is then applied to spatially rank productivity potential from low to high across the Marcellus Shale. The ML model developed used a gradient boosted regression tree (GBRT) algorithm and is capable of 82 percent prediction accuracy on holdout data. The distribution of geological properties as well as the resulting optimized well design and completion attributes specific to regions commonly ranked in productivity potential are evaluated statistically to comprehend controlling factors on shale well production, and to identify if commonality or disparity exists in the prominent features. The highest productivity ranked region is isolated in the Marcellus Shale's northeastern core region and its periphery. Statistical analyses indicate that regions higher in productivity ranking show a significant difference for certain (but not all) geologic features favorable to gas production potential relative to lower productivity regions; most notably net thickness and porosity. Optimized well design parameter settings vary relative to their placement across the study area and subsequent productivity ranking region. Overall, the ML-based framework discussed in this paper attempts to analyze shale controlling factors concurrently, to deliver a systematic evaluation result for production potential that accounts for and quantifies controlling features associated with geologic properties and well design attributes.

Adipocyte Model of Mycobacterium tuberculosis Infection Reveals Differential Availability of Iron to Bacilli in the Lipid-Rich Caseous Environment.

ABSTRACTMycobacterium tuberculosis, a successful human pathogen, utilizes multiple carbon sources from the host but adapts to a fatty-acid-rich environment in vivo. We sought to delineate the physiologic response of M. tuberculosis to a lipid-rich environment by using differentiated adipocytes as a model system. Global transcriptome profiling based on RNA sequencing was performed for bacilli from infected adipocytes and preadipocytes. Genes involved in de novo fatty acid synthesis were downregulated, while those predicted to be involved in triglyceride biosynthesis were upregulated, in bacilli isolated from adipocytes, indicating reliance on host-derived fatty acids. Transcription factor network analysis indicated suppression of IdeR-regulated genes, suggesting decreased iron uptake by M. tuberculosis in the adipocyte model. This suppression of iron uptake coincided with higher ferritin and iron levels in adipocytes than in preadipocytes. In accord with the role of iron in mediating oxidative stress, we observed upregulation of genes involved in mitigating oxidative stress in M. tuberculosis isolated from adipocytes. We provide evidence that oleic acid, a major host-derived fatty acid, helps reduce the bacterial cytoplasm, thereby providing a safe haven for an M. tuberculosis mutant that is sensitive to iron-mediated oxidative stress. Via an independent mechanism, host ferritin is also able to rescue the growth of this mutant. Our work highlights the inherent synergy between macronutrients and micronutrients of the host environment that converge to provide resilience to the pathogen. This complex synergy afforded by the adipocyte model of infection will aid in the identification of genes required by M. tuberculosis in a caseous host environment.

Human locomotion analysis: Identifying a dynamic mapping between upper and lower limb joints using the Koopman operator.

Human locomotion is a complex process that shows some inherent synergies and coordination, also called inter-joint coordination, between the upper and lower limbs. In this paper, we investigate the use of Koopman operator to identify a dynamic mapping between an upper limb and its contra-lateral lower limb in the human locomotion. We perform a human locomotion analysis in the sagittal plane and restrict the study to the forward motion; more specifically, a straight walking task at a constant speed. We use canes as walking aids to provide additional information about the terrain and enforce a frequency locking between the upper and lower body. This mapping will provide a model of the human locomotion.

Honeycomb-Like Interconnected Network of Nickel Phosphide Heteronanoparticles with Superior Electrochemical Performance for Supercapacitors.

Transition-metal-based heteronanoparticles are attracting extensive attention in electrode material design for supercapacitors owing to their large surface-to-volume ratios and inherent synergies of individual components; however, they still suffer from limited interior capacity and cycling stability due to simple geometric configurations, low electrochemical activity of the surface, and poor structural integrity. Developing an elaborate architecture that endows a larger surface area, high conductivity, and mechanically robust structure is a pressing need to tackle the existing challenges of electrode materials. This work presents a supercapacitor electrode consisting of honeycomb-like biphasic Ni5P4-Ni2P (NixPy) nanosheets, which are interleaved by large quantities of nanoparticles. The optimized NixPy delivers an ultrahigh specific capacity of 1272 C g-1 at a current density of 2 A g-1, high rate capability, and stability. An asymmetric supercapacitor employing as-synthesized NixPy as the positive electrode and activated carbon as the negative electrode exhibits significantly high power and energy densities (67.2 W h kg-1 at 0.75 kW kg-1; 20.4 W h kg-1 at 15 kW kg-1). These results demonstrate that the novel nanostructured NixPy can be potentially applied in high-performance supercapacitors.

Sankey-Diagram-based insights into the hydrogen economy of today

Many posit a distinct role for hydrogen within the purview of a future low-carbon, renewables-based transportation system. However, hydrogen is already established as an important energy resource and industrial product displaying versatility of uses and roles in the energy system. In this work, we develop and present an original Sankey-Diagram-based analytical framework aiming at identifying and characterizing key structural aspects of the real hydrogen economy as it exists today (2004–2015). We include global hydrogen demand and supply, assorted energy flows, as well as the costs of production and we consider value flows. We suggest that potentially evolutionary trends can be insightfully elucidated via a systems perspective on the existing global hydrogen economy. Perhaps counterintuitively, we build upon suggestions that the best prospects for the evolutionary emergence of a robust hydrogen economy could arise in a world of cheap and abundant oil rather than in a world of oil scarcity and rising fossil fuel prices. Furthermore, in the long term (2050), if global oil supply continues to be ample and environmental pressures intensify, then there will be a need for new and more aggressive energy policies and enhanced pressure for rapid technological innovation including in the domain of hydrogen. The information presented in this paper, however, reminds us of the situation as it applies today. Approximately 96% of global hydrogen is a product of fossil fuel, while 35% is required by the fossil fuel industry for its own purposes. This indirect connection between hydrogen economy and global fossil fuel industry will continue to shape the future of hydrogen economy for decades to come. Currently, over $107 billion/annum is spent globally by the petrochemical industry in producing hydrogen, suggesting the scale as well as the irreducible aspects and inherent synergies associated with the aforementioned connection.

Values as a bridge between sustainability and institutional assessment

Purpose– The purpose of this paper is to illustrate that values-focused assessment can provide a useful lens for integrating sustainability and institutional performance assessment in universities.Design/methodology/approach– This study applies a values elicitation methodology for indicator development, through thematic analysis of semi-structured interviews and a stakeholder workshop, in a pilot project at BOKU University, Vienna.Findings– This case highlights that many of the values held by university staff and students are pro-sustainability values. Starting from these values may be a useful way of engaging university stakeholders in sustainability dialogues. The paper illustrates how values-based indicators can be integrated into university performance assessments, providing a novel way of thinking about sustainability assessment in universities.Research limitations/implications– The exploratory pilot was carried out in a university with a focus on natural sciences. Further research could replicate and compare the results of this paper in other institutions.Originality/value– Creating a shared understanding of pro-sustainability values can help individuals to reconceptualise sustainability in relation to their own work and motivations. In doing so, it can highlight the inherent synergies between sustainability assessment and institutional performance assessment in the higher education sector, which are usually seen as separate domains.

Impact of Factors of Family Business on the Performance: A PLS-SEM Study

Family Business is seen as significant source for economic growth and development in today’s world. Family businesses have the potential to outperform any other form of business organization through their inherent synergies between capital and management. Performance is an essential indicator of the organisational success and competitive advantage of firms. If firms are able to identify the factors that determine improved performance, they could take advantage of their specific features. The purpose of this research is to give insight in the determinants of family business that contribute in meeting/exceeding performance objectives of the firm. Structural Equation Modelling is used for the analysis.

Pharmacokinetic synergy from the taxane extract of Taxus chinensis improves the bioavailability of paclitaxel

BackgroundTaxus chinensis (Pilger) Rehd is widely distributed in China and the northern hemisphere, and the most popular medicinal component isolated from Taxus chinensis is paclitaxel (PTX), which has now become the first-line chemotherapeutic drug for breast cancer and ovarian cancer. Oral administration of pure PTX as a potential anti-cancer agent is compromised by low bioavailability. Hypothesis/purposeIn the clinical practice of traditional Chinese medicine, drug co-administration in the form of mixtures or formula could achieve pharmacokinetic/pharmacodynamic synergies. In this study, we aimed to investigate whether there exist any ‘inherent’ phytochemical synergy from Taxus chinensis extract that could improve PTX bioavailability. Study designPharmacokinetic study of PTX after oral administration of Taxus chinensis extracts or single PTX was performed. In addition, comparative cytotoxic studies were carried out on the MCF-7 breast cancer cell lines. MethodsThe plasma concentrations of PTX were determined using a validated high performance chromatography tandem mass spectrometry method. The cytotoxicity was compared using the MTT assay. ResultsOral administration of taxane fractions isolated from Taxus chinensis (containing 17.2% PTX) could achieve remarkably higher blood concentration and systemic exposure of PTX in rats, while the retention of PTX was significantly improved. Further tissue distribution analysis revealed that the penetration of PTX into major tissues was drastically increased compared with that of single PTX. In addition, in MCF-7 cells, the co-existing components in taxane mixtures could strengthen the inhibitory effects of PTX on tumor cell proliferation. ConclusionTogether, these results support that administration of PTX in the form of taxane mixtures may become a novel approach to improve the poor bioavailability of PTX. Moreover, the inherent synergy from Taxus chinensis taxane extracts promises a novel strategy to strengthen PTX efficacy.

A Computational Model of the Dendron of the GnRH Neuron.

Gonadotropin-releasing hormone (GnRH) neurons have two major processes that have properties of both dendrites (they receive synaptic input from other neurons) and axons (they actively propagate action potentials to the synaptic terminal). These processes have thus been termed dendrons. We construct a stochastic spatiotemporal model of the dendron of the GnRH neuron, with the goal of studying how stochastic synaptic input along the length of the dendron affects the initiation and propagation of action potentials. We show (1) that synaptic inputs closer to the soma are effective controllers of action potential initiation and electrical bursting and (2) that although the effects on the amplitude and width of propagating action potentials are critically dependent on the timing and location of synaptic input addition, the effects remain small. We conclude that although stochastic synaptic input along the length of the dendron is likely to be a major determinant of action potential initiation, it is an unlikely mechanism for controlling whether or not action potentials reach the synaptic terminal. Thus, the role of synaptic inputs situated along the dendron a long way from the site of action potential initiation remains unclear. We also show that the actions of kisspeptin can result in significant modulation of the amount of calcium released by an action potential at the synaptic terminal. Furthermore, we show that the actions of kisspeptin are greatest when multiple effects operate together and that a kisspeptin-induced increase in firing rate is, by itself, less effective at increasing Ca2+ release than is a combination of an increased firing rate, an increase in Ca2+ influx, and an increase in inositol trisphosphate (IP3) production. We conclude that the inherent synergies in the various actions of kisspeptin make it a likely candidate for the precise control of Ca2+ transients at the synaptic terminal.

Water scarcity and climatic change in India: the need for water demand and supply management

Against the discussion on the rationale and scope for water demand and supply management in India, this paper provides a brief overview of the status and effectiveness, as well as the technical, institutional and financial requirements of six demand management options (i.e. water pricing, water markets, water rights, energy regulations, water saving technologies, and user and community organizations) and one supply management option (involving the implementation of the National River Linking Project, NRLP). The paper then develops a framework that captures the analytics of water demand management in terms of both the impact pathways of and operational linkages among the options and their underlying institutions. Using this framework, the paper outlines a strategy for water demand management that can exploit well the inherent synergies among the options, and also align them well with the underlying institutional structure and its environment. Similarly, based on an analysis of the NRLP, the paper also indicates the strategy for implementing the NRLP and thereby promoting water supply management within the financial, institutional and political constraints. The paper concludes with the policy implications for water demand and supply management in India. Citation Saleth, R. M. (2011) Water scarcity and climatic change in India: the need for water demand and supply management. Hydrol. Sci. J. 56(4), 671–686.

A Phenomenological Study on the Synergistic Role of Precious Metals in the Steam Reforming of Logistic Fuels on Bimetal-Supported Catalysts

Fuel processors are required to convert sulfur-laden logistic fuels into hydrogen-rich reformate and deliver to the fuel cell stack with little or no sulfur. Since sulfur poisons and deactivates the reforming catalyst, robust sulfur-tolerant catalysts ought to be developed. In this paper, the development, characterization and evaluation of a series of reforming catalysts containing two noble metals (with total metal loading not exceeding 1 weight percent) supported on nanoscale ceria for the steam-reforming of kerosene is reported. Due to inherent synergy, a bimetallic catalyst is superior to its monometallic analog, for the same level of loading. The choice of noble metal combination in the bimetallic formulations plays a vital and meaningful role in their performance. Presence of ruthenium and/or rhodium in formulations containing palladium showed improved sulfur tolerance and significant enhancement in their catalytic activity and stability. Rhodium was responsible for higher hydrogen yields in the logistic fuel reformate. Duration of steady hydrogen production was higher in the case of RhPd (75 h) than for RuPd (68 h); hydrogen generation was stable over the longest period (88 h) with RuRh containing no Pd. A mechanistic correlation between the characteristic role of precious metals in the presence of each other is discussed.

Avoiding transcription factor competition at promoter level increases the chances of obtaining oscillation

BackgroundThe ultimate goal of synthetic biology is the conception and construction of genetic circuits that are reliable with respect to their designed function (e.g. oscillators, switches). This task remains still to be attained due to the inherent synergy of the biological building blocks and to an insufficient feedback between experiments and mathematical models. Nevertheless, the progress in these directions has been substantial.ResultsIt has been emphasized in the literature that the architecture of a genetic oscillator must include positive (activating) and negative (inhibiting) genetic interactions in order to yield robust oscillations. Our results point out that the oscillatory capacity is not only affected by the interaction polarity but by how it is implemented at promoter level. For a chosen oscillator architecture, we show by means of numerical simulations that the existence or lack of competition between activator and inhibitor at promoter level affects the probability of producing oscillations and also leaves characteristic fingerprints on the associated period/amplitude features.ConclusionsIn comparison with non-competitive binding at promoters, competition drastically reduces the region of the parameters space characterized by oscillatory solutions. Moreover, while competition leads to pulse-like oscillations with long-tail distribution in period and amplitude for various parameters or noisy conditions, the non-competitive scenario shows a characteristic frequency and confined amplitude values. Our study also situates the competition mechanism in the context of existing genetic oscillators, with emphasis on the Atkinson oscillator.