Achieving Biodiesel Standards Through Saturation Level Optimisation

Biodiesels made from waste feedstock are viable sustainable fuels for compression ignition engine use. However, biodiesel produced from single waste source do not always comply with the European biodiesel standard. This study investigated the fuel quality and engine performance when two biodiesels with different characteristics were blended at various proportions. Waste cooking oil biodiesel was blended with sheep fat biodiesel which has a lower unsaturated fatty acid content. The engine performance, combustion and exhaust emission characteristics of the neat biodiesels and their blends (at 60/40, 50/50, and 30/70 ratios) were analysed. The results showed that 60/40 and 50/50 blends met the core parameters of BS EN 14214 biodiesel standard and improved the combustion and emission characteristics as compared to their neat biodiesels and diesel. The 50/50 blends gave up to 5% and 14% improvements in the in-cylinder pressure and maximum heat release rate respectively, when compared to the same results for neat biodiesel operation. Reduction of up to 73% in CO, 96% in smoke and 3% in CO2 emissions were observed. However, NOx emission was 2.5% higher than diesel. The results revealed that carefully selected biodiesel-biodiesel blending could meet fuel standards, improve engine performance and reduce exhaust emissions

Impact of loyal and new customer segments on product upgrades: The role of quality differentiation through online reviews

Firms often strive to expand their market share beyond their established customer base by launching quality upgrades in their products. They recognize that customers often gauge product quality through online reviews. We develop an analytical model to examine the quality upgrade strategies of two competing firms, revealing two potential market equilibria. In the unilateral upgrading equilibrium where only one firm upgrades, the upgrading firm sees an initial increase in loyal demand, leading to higher prices. This price adjustment, however, may deter potential new customers who turn to the more affordable non-upgrading competitor, referred to as the substitution effect. Despite attracting more loyal customers, the upgrading firm may experience a net loss in broader market share due to the substitution effect. In the bilateral upgrading equilibrium where both firms upgrade and engage in quality competition, the situation becomes akin to a prisoner’s dilemma if loyal customers show indifference to quality improvements. The gains from loyal customers are outweighed by fierce competition for new customers, ultimately disadvantaging both firms. Furthermore, our findings indicate that review-revealed quality difference between the two products leads to a higher degree of quality improvement effort by the high-quality firm, while reducing that of the low-quality firm. Intriguingly, in the unilateral equilibrium, the high-quality firm may not benefit from its review-revealed superior quality, while the low-quality firm may not be disadvantaged, depending on the substitution effect relatively

Impact of terminal group on temperature-dependent excited state relaxation in cationic dyes

Cationic organic dyes carry a positive charge distributed along the molecule, and the localization of this charge significantly affects their symmetry and optical properties. Depending on the different factors (topology of the terminal groups, the polarity of the solvent, and the temperature) the polyene, polymethine, or donor-acceptor structure form in such dyes, and excited state relaxation for such systems is not fully explored, particularly at low temperatures. At room temperature, the studied cationic dyes, regardless of symmetry in the ground state, are mostly symmetrical in the excited state. At low temperatures, charge localization effects become evident, leading to symmetry breaking in both ground and excited states. In this paper, we distinguish how terminal groups at the end of the cationic dyes impact the relaxation of excited states by analyzing experimental low-temperature time-resolved spectra combined with quantum-chemical calculations. Distinctive emission (690 nm) in the anti-Stokes range of polymethine band (700–730 nm) features polyene structures forming depending on the temperature, solvent polarity, and charge-donating properties of the dye's terminal groups. Furthermore, in low-temperature time-resolved photoluminescence, a 760 nm band is distinguished and associated with intramolecular charge transfer. Our calculations revealed unequal distribution of total positive charge in different molecular fragments (polymethine chain and terminal groups) and formation of negative charge on polymethine chain. We propose a model of excited state relaxation transitions for linear cationic molecular systems that enable donor-acceptor features. This model offers valuable insights for designing new functional materials with tunable properties or efficient energy transfer systems for artificial photosynthesis

Inferring structure of cortical neuronal networks from activity data: A statistical physics approach

Understanding the relation between cortical neuronal network structure and neuronal activity is a fundamental unresolved question in neuroscience, with implications to our understanding of the mechanism by which neuronal networks evolve over time, spontaneously or under stimulation. It requires a method for inferring the structure and composition of a network from neuronal activities. Tracking the evolution of networks and their changing functionality will provide invaluable insight into the occurrence of plasticity and the underlying learning process. We devise a probabilistic method for inferring the effective network structure by integrating techniques from Bayesian statistics, statistical physics, and principled machine learning. The method and resulting algorithm allow one to infer the effective network structure, identify the excitatory and inhibitory type of its constituents, and predict neuronal spiking activity by employing the inferred structure. We validate the method and algorithm's performance using synthetic data, spontaneous activity of an in silico emulator, and realistic in vitro neuronal networks of modular and homogeneous connectivity, demonstrating excellent structure inference and activity prediction. We also show that our method outperforms commonly used existing methods for inferring neuronal network structure. Inferring the evolving effective structure of neuronal networks will provide new insight into the learning process due to stimulation in general and will facilitate the development of neuron-based circuits with computing capabilities

Elite status-seeking and class reproduction in civil society: an analysis of corporate elite appointments to charity boards

This article examines the relationship between economic elites and civil society by analysing the appointments of corporate elites to the boards of charitable companies in the UK. Whilst previous research has usually focused on who among the corporate elite hold positions in key civil society organisations, and the extent to which these organisations are integrated into corporate networks, we use data on the nature and operations of civil society organisations to identify which are more likely to attract corporate elites as board members. Using a dataset of over thirty-one thousand UK incorporated companies registered with the Charity Commission of England and Wales, we examine the appointments of corporate elite to these organisations over a ten-year period. Based on these appointments, we are able to offer insights into the social networks, values and interests of the corporate elite as a whole. We find that the UK corporate elite are more likely to join the boards of larger, high-status charities, and those that support traditional upper-class culture and class reproduction. We also find they are relatively more likely to join organisations that seek to shape politics and society – such as foundations distributing grants, or think tanks undertaking public policy research and advocacy – than those involved in the provision of welfare and social services. Taken together, the findings are suggestive of a status-seeking, culturally highbrow and secular economic elite, that is more traditional than meritocratic, and more concerned with shaping policy and supporting the institutions of their class, than directly supporting disadvantaged groups

Cell-free expression and SMA copolymer encapsulation of a functional receptor tyrosine kinase disease variant, FGFR3-TACC3

Despite their high clinical relevance, obtaining structural and biophysical data on transmembrane proteins has been hindered by challenges involved in their expression and extraction in a homogeneous, functionally-active form. The inherent enzymatic activity of receptor tyrosine kinases (RTKs) presents additional challenges. Oncogenic fusions of RTKs with heterologous partners represent a particularly difficult-to-express protein subtype due to their high flexibility, aggregation propensity and the lack of a known method for extraction within the native lipid environment. One such protein is the fibroblast growth factor receptor 3 fused with transforming acidic coiled-coil-containing protein 3 (FGFR3-TACC3), which has failed to express to sufficient quality or functionality in traditional expression systems. Cell-free protein expression (CFPE) is a burgeoning arm of synthetic biology, enabling the rapid and efficient generation of recombinant proteins. This platform is characterised by utilising an optimised solution of cellular machinery to facilitate protein synthesis in vitro. In doing so, CFPE can act as a surrogate system for a range of proteins that are otherwise difficult to express through traditional host cell-based approaches. Here, functional FGFR3-TACC3 was expressed through a novel cell-free expression system in under 48 h. The resultant protein was reconstituted using SMA copolymers with a specific yield of 300 µg/mL of lysate. Functionally, the protein demonstrated significant kinase domain phosphorylation (t < 0.0001). Currently, there is no published, high-resolution structure of any full-length RTK. These findings form a promising foundation for future research on oncogenic RTKs and the application of cell-free systems for synthesising functional membrane proteins

New Frontiers and The Impact of Artificial Intelligence and the Digital Revolution on the Future of Intellectual Property Laws

Before the Covid pandemic hit, artificial intelligence (AI) had already embedded itself into our everyday lives. AI as an assistive tool adequately responds to humans’ needs, such as virtual digital assistance, almost everyone will have Apple Siri, Alexa and or Google Home, as voice recognition systems. Relying on artificial intelligence systems such as Spotify to provide a recommended list of music based on your existing music choices and preferences is commonplace, and likewise, for producing works of art. Most notably, a project team behind The Next Rembrandt designed algorithms that allowed a computer to create a painting in the style of the 17th century Dutch artist and is known as the Rembrandt 2.0 . Artificial intelligence can produce works which could be considered as copyright works however international law has yet to acknowledge AI as a copyright owner . Humans working in creative, innovative and legal sectors are discussing the consequence of AI systems when it comes to who will own the intellectual property, more importantly, who will the economic rights belong to. Artificial intelligence systems are developing at a significant pace and as a result, reshaping the whole creative and innovative sectors that are protected in the existing intellectual property systems. Therefore, it is necessary to identify the AI systems at present, defining and distinguishing between the concepts of “AI-assisted” and “AI-generated”, to outline the direction of AI development in the context of intellectual property law

Automated Vehicles: Are Cities Ready to Adopt AVs as the Sustainable Transport Solution?

Cities are looking for an approach to affordable, integrated and sustainable transport systems across all transport modes and services. Automated vehicle (AV) technologies use emerging technologies to integrate multimodal transport systems and ensure sustainable mobility in a city. Vehicle automation has entered the public conscious with several auto companies leading recent developments in legislation and affordable cars. Governments support AVs through policies and legal frameworks, and it is the responsibility of AV dealers to comply with legal and policy provisions so that the benefits of this new and promising industry can be felt. Despite the growing interest in AVs as a potential solution for sustainable transportation, several research gaps remain in relation to technology and infrastructure readiness, policy and regulation, equity and accessibility concerns, public acceptance and behaviour, and integration with public transport. This paper discusses the challenges and dilemmas of adopting AVs within the existing urban transportation system and within existing design standards in the United Kingdom and explores the progress and opportunities related to policies of transportation that may stem from the emergence of AV technologies in the UK. The potential of AVs is still limited by cyber insecurity, incompetent infrastructure, social acceptance, and public awareness. However, AVs are crucial to a city’s efficiency and prosperity and will become essential components for the provision of more flexible, convenient, integrated and sustainable travel options

Altered Patterns of Dynamic Functional Connectivity Underpin Reduced Expressions of Social–Emotional Reciprocity in Autistic Adults

To identify the neurocognitive mechanisms underpinning the social difficulties that characterize autism, we performed functional magnetic resonance imaging on pairs of autistic and non‐autistic adults simultaneously whilst they interacted with one another on the iterated Ultimatum Game (iUG)—an interactive task that emulates the reciprocal characteristic of naturalistic interpersonal exchanges. Two age‐matched sets of male–male dyads were investigated: 16 comprised an autistic Responder and a non‐autistic Proposer, and 19 comprised non‐autistic pairs of Responder and Proposer. Players' round‐by‐round behavior on the iUG was modeled as reciprocal choices, and dynamic functional connectivity (dFC) was measured to identify the neural mechanisms underpinning reciprocal behaviors. Behavioral expressions of reciprocity were significantly reduced in autistic compared with non‐autistic Responders, yet no such differences were observed between the non‐autistic Proposers in either set of dyads. Furthermore, we identified latent dFC states with temporal properties associated with reciprocity. Autistic interactants spent less time in brain states characterized by dynamic inter‐network integration and segregation among the Default Mode Network and cognitive control networks, suggesting that their reduced expressions of social–emotional reciprocity reflect less efficient reconfigurations among brain networks supporting flexible cognition and behavior. These findings advance our mechanistic understanding of the social difficulties characterizing autism

Development of a YouthFit Index to assess health-related quality of life in Hong Kong children

Objective: To develop a YouthFit Index, a comprehensive and easily interpretable measure of youth health-related quality of life (HRQoL). Method: A repeated cross-sectional design was employed to develop and validate the YouthFIt index using the Pediatric Quality of Life Inventory (PedsQL). Activity level and sleep data were collected by a wearable device, Actigraph. Questionnaires were used to gather demographic information and PedsQL data. Multiple-factor analysis of mixed data was employed to identify principal components (PCs) of the modifiable lifestyle variables. The YouthFit Index was calculated by summing the weighted PCs. Logistic regression models were used to assess the odds ratios for risks associated with the YouthFIt Index. Results: A total of 1,867 students were recruited for the study. The findings showed that having YouthFit Index scores greater than 5 was significantly associated with a lower risk of identifying with special health care needs. Compared to the group with YouthFit Index scores below or equal to 5, the group with scores above the cut-off demonstrated a significant 43 % reduction in the risk of PedsQL total score. The results also revealed that increased sleep duration and physical activity are associated with better HRQoL, while longer sedentary periods and later bedtimes are linked to worse HRQoL. Conclusions: The YouthFit Index is a user-friendly tool for assessing the HRQoL of Hong Kong Chinese children between the ages of 6 and 17. It can help raise awareness about healthy quality of life and promote health and well-being among children in Hong Kong