Conversion of Cellulose to Value Added-Chemicals

Biomass-derived feedstock is of growing importance in the development of new synthetic pathways for commodity and specialty chemicals. Utilizing basic catalytic concepts such as hydrolysis, dehydration, isomerisation, and other common transformations of sugar in biomass conversion has already produced significant advances in the fundamental understanding of biomass conversion. Despite the progress that has already been made, very few studies are dedicated to understanding the fundamentals of cellulose conversion under heterogeneous catalytic conditions. This is due to the complexity of both the catalytic steps at the metal/support interface and the structure of cellulose itself, being a highly functionalized homopolymer, characterized by hydrophilicity, chirality, and biodegrability. Difficulties in cellulose conversion stem from it’s robust structure filled with intramolecular hydrogen bonding. See comments section below for image. Our focus is on Cellobiose, a two-glucose unit dimer. It is ideal as a simplified model for cellulose because of the presence of a single ether-linkage per molecule and its solubility in water. This study aims to refine the fundamentals of Cellobiose conversion under conditions near the critical point of water. Results have shown that, in the presence of a Ru/C catalyst, cellobiose offers high conversion with the primary products being Sorbitol or Mannitol polyols with shorter chain polyols such as xylitol, erythreitol, threitol, and glycerol also present in the reaction mixture

Replication and exploratory analysis of 24 candidate risk polymorphisms for neural tube defects.

BackgroundNeural tube defects (NTDs), which are among the most common congenital malformations, are influenced by environmental and genetic factors. Low maternal folate is the strongest known contributing factor, making variants in genes in the folate metabolic pathway attractive candidates for NTD risk. Multiple studies have identified nominally significant allelic associations with NTDs. We tested whether associations detected in a large Irish cohort could be replicated in an independent population.MethodsReplication tests of 24 nominally significant NTD associations were performed in racially/ethnically matched populations. Family-based tests of fifteen nominally significant single nucleotide polymorphisms (SNPs) were repeated in a cohort of NTD trios (530 cases and their parents) from the United Kingdom, and case-control tests of nine nominally significant SNPs were repeated in a cohort (190 cases, 941 controls) from New York State (NYS). Secondary hypotheses involved evaluating the latter set of nine SNPs for NTD association using alternate case-control models and NTD groupings in white, African American and Hispanic cohorts from NYS.ResultsOf the 24 SNPs tested for replication, ADA rs452159 and MTR rs10925260 were significantly associated with isolated NTDs. Of the secondary tests performed, ARID1A rs11247593 was associated with NTDs in whites, and ALDH1A2 rs7169289 was associated with isolated NTDs in African Americans.ConclusionsWe report a number of associations between SNP genotypes and neural tube defects. These associations were nominally significant before correction for multiple hypothesis testing. These corrections are highly conservative for association studies of untested hypotheses, and may be too conservative for replication studies. We therefore believe the true effect of these four nominally significant SNPs on NTD risk will be more definitively determined by further study in other populations, and eventual meta-analysis

Technology Challenges of SURROUND: A Constellation of Small Satellites Around the Sun for Tracking Solar Radio Bursts

The SURROUND mission proposes the operational monitoring and forecasting of space weather events using a constellation of five small satellites in orbit around the Sun. This unique mission concept would enable the localisation and tracking of solar events with unprecedented accuracy. The small payload combined with high launch requirements makes this an ideal candidate mission for a distributed constellation of small spacecraft and provides an opportunity for technical development in the areas of deep space communication, propulsion, and survivability. The baseline configuration for SURROUND proposes the deployment of spacecraft to Earth-Sun Lagrange points L1, L4, and L5, and two additional spacecraft in Earth leading (\u3c 1AU) and trailing (\u3e 1AU) orbits. However, the development and realisation of such a constellation in deep space presents a number of challenges, particularly when the use of small spacecraft is considered. This paper presents the conceptual design for the proposed SURROUND constellation, principally focusing on the key technical challenges of deploying the spacecraft into their desired locations around the Sun and subsequently communicating the collected data back to Earth. In addition to the key propulsion system and communications architecture trades, additional technological challenges of the mission are also considered, including attitude control, radiation hardening, and electromagnetic compatibility

The role of competencies in shaping the leadership style of female entrepreneurs: the case of North West of England, Yorkshire, and North Wales

This study investigates linkages between personal competencies and leadership style among female small and micro business owners. Although prior research suggests that leadership style is shaped according to a leader's traits and abilities, few empirical studies corroborate this, particularly among female owners. Using survey data from the North West of England, Yorkshire, and North Wales, we reveal that transformational leadership style is the most dominant style adopted, and it is linked to perceived human and personal competencies as well as entrepreneurial competencies

Moderating influences on the firm's strategic orientation-performance relationship

This paper is focused on the factors that moderate the relationship between firm's strategic orientation and performance in small and medium-sized firms. Much prior research has focused simply on identifying environmental conditions conducive to the effectiveness of the strategic orientation approach. However, recent research has called for studies focused on investigating internal moderators of the strategic orientation-performance relationship. As a result, we propose a contingency framework, considering how corporate and competitive strategies, top management characteristics, and environmental conditions may moderate this relationship. Based on a survey of 295 small and medium sized enterprises pertaining to seven manufacturing sectors, our study shows that the positive influence of firm's strategic orientation may be moderated by the environment conditions, the previous experience of top management team, and the corporate and competitive strategies developed by the firm

Exploring entrepreneurial learning: A comparative study of technology development projects

In this paper, we report findings from a comparative study of factors that influence the learning process that underlies entrepreneurial innovation, as entrepreneurs move from an initial intuition to a well-developed new product or service. Evidence from our comparative study highlights the self-reinforcing effect of prior related knowledge, perceived incentives and the degree of control on the allocation of entrepreneurs' limited time, attention and resources. Combining theory and evidence from our study, we propose an interpretative model that suggests that innovation in entrepreneurial ventures rests on self-reinforcing learning cycles that lead entrepreneurs to dedicate increasing resources to the exploration of some opportunities at the expense of others, following a sensemaking process affected by their previous knowledge and their degree of involvement in the projects

Meta-learning of Sequential Strategies

In this report we review memory-based meta-learning as a tool for building sample-efficient strategies that learn from past experience to adapt to any task within a target class. Our goal is to equip the reader with the conceptual foundations of this tool for building new, scalable agents that operate on broad domains. To do so, we present basic algorithmic templates for building near-optimal predictors and reinforcement learners which behave as if they had a probabilistic model that allowed them to efficiently exploit task structure. Furthermore, we recast memory-based meta-learning within a Bayesian framework, showing that the meta-learned strategies are near-optimal because they amortize Bayes-filtered data, where the adaptation is implemented in the memory dynamics as a state-machine of sufficient statistics. Essentially, memory-based meta-learning translates the hard problem of probabilistic sequential inference into a regression problem.Comment: DeepMind Technical Report (15 pages, 6 figures

The impact of human capital on the early success of necessity versus opportunity-based entrepreneurs

This paper examines whether founders' backgrounds influence new firm survival in the early years after startup, focusing, in particular, on the impact of unemployment-driven entrepreneurship. For entrepreneurs who left their previous employment to found a new firm, both general and specific human capital play a key role in enhancing early survival chances. However, various forms of human capital have little effect on early survival of unemployment-driven entrepreneurs, who rely mostly on previous entrepreneurial experience to persevere. Results suggest that pre-entry capabilities play an important role in the early success of opportunity-based entrepreneurs, but have little influence on the early success of necessity-based ones