In this paper, we consider the problem that the maximal order consider the groups that consisting of transformations we called NG-Transformation on a nonempty set A has no bijection as its element. We find the order of these groups not greater that (n-1)!. In addition, we will prove our result by showing that any kind of NG-group in the theorem be isomorphic to a permutation group on a quotient set of A with respect to an equivalence relation on A.

RAxML-NG is a new phylogentic inference tool that replaces the widely-used RAxML and ExaMLtree inference codes. Compared to its predecessors, RAxML-NG offers improvements in accur-acy, flexibility, speed, scalability, and user-friendliness. In this chapter, we provide practicalrecommendations for the most common use cases of RAxML-NG: tree inference, branch supportestimation via non-parametric bootstrapping, and parameter optimization on a fixed tree topo-logy. We also describe best practices for achieving optimal performance with RAxML-NG, inparticular, with respect to parallel tree inferences on computer clusters and supercomputers. AsRAxML-NG is continuously updated, the most up-to-date version of the tutorial described inthis chapter is available online at: https://cme.h-its.org/exelixis/raxml-ng/tutorial .

Blockchain technology has become one of the most popular technologies for maintaining digital transactions. From the foundation of Bitcoin to the now predominant smart contract, blockchain technology promises to induce a shift in thought about digital transactions in many fields, such as energy, healthcare, Internet of Things, cybersecurity, financial services and the supply chain. Despite blockchain technology offers many cryptography advantages such as immutability, digital signature and hashing; it has suffered from several critical cybersecurity threats and vulnerabilities. In this paper, we build upon the previous studies on vulnerabilities and investigates over 60 real cybersecurity incidents that have been happening on the blockchain networks between 2009 and 2019. We categorise those incidents against the key cybersecurity vulnerabilities in blockchain technologies; and have developed a taxonomy that captures five types of cybersecurity threats and vulnerabilities based on five main players in blockchain. The outcome of this research prompted concerns and research direction in developing countermeasures to alleviate these risks.

The COVID-19 outbreak has focused attention on the use of social distancing as the primary defence against community infection, yet forcing social animals to maintain that physical distance has presented significant challenges for health authorities and law enforcement. Anecdotal media reports suggest widespread dissatisfaction with social distancing as a policy, yet there is little prior work aimed at measuring community acceptance of social distancing. In this paper, we propose a new approach to measuring attitudes towards social distancing by using social media and sentiment analysis. Over a 4 month period, we found 82.5% of tweets were in favour of social distancing. The results indicate a widespread acceptance of social distancing in the community. We conclude by examining options for estimating the optimal (minimal) social distance required at scale, and the implications for securing widespread community support and acceptance of public health messaging.

This paper introduces an innovative energy circuit that challenges conventional understandings of energy conservation, marking a significant departure from traditional frameworks. Seeking to enhance energy generation within existing paradigms, this innovation holds promise for addressing pressing global issues such as the energy crisis and environmental sustainability, while also stimulating scientific inquiry. In contrast to prevalent misconceptions rooted in philosophical and scientific constraints, this study refutes the notion of generating energy from nothing and questions the viability of perpetual motion machines as conceptual models. Instead, it proposes a novel circuit design derived from an unconventional electrical short circuit, which is shown to disrupt the established principles of energy conservation. This circuit offers a transformative approach with diverse applications, including self-recharging capabilities for electric vehicles, bolstering microgrid infrastructure, and facilitating the integration of renewable energy sources. Transcending conventional scientific boundaries, this paper prompts philosophical reflections on the evolving nature of scientific exploration. Ultimately, the energy circuit represents a pivotal step towards mitigating the global energy crisis by reducing reliance on finite resources and fostering sustainability. The paper concludes by illustrating the circuit's potential to revolutionize energy systems and contribute to a more resilient and sustainable future.

The worldwide interconnected objects, called Internet of Things (IoTs), have been increasingly growing in the last several years. Different social media platforms and devices are continuously generating data about individuals and facilitate the technological and the social convergence of their Internet-based data and services with globalized users. These social and device-related IoTs create rooms for data breaches as such platforms provide ability to collect private and sensitive data. We assert that data breaches are fundamentally failures of access control - most users are too busy or technically ill-equipped to understand access control policy expressions and decisions. We argue that this is symptomatic of globalised societies structured by the conditions of algorithmic modernity; an era in which our data is increasingly interdependent on, and enmeshed with, ever more complex systems and processes that are vulnerable to attack. Ethically managing data breaches is now too complex for current access control systems, such as Role-Based Access Control (RBAC) and Context-Aware Access Control (CAAC). These systems do not provide an explicit mechanism to engage in decision making processes, about who should have access to what data and when, that are involved in data breaches. We argue that a policy ontology will contribute towards the development of Ethical CAAC better suited to attributing accountability for data breaches in the context of algorithmic modernity. We interrogate our proposed Ethical CAAC as a theoretical construct with implications for future policy ontology models and data breach countermeasures. An experimental study on the performance of the proposed framework is carried out with respect to a more generic CAAC framework.

Together with display and input, storage and processing are requisite to computing. While storage technologies have improved tremendously in capacity and speed over the years, the basic principles enabling information storage into digital 1 and 0 remains the same: induction of phase change in the storage substrate. But recently, there has been much research into structural phase change material (SPCM) and exploration of its possible use in various types of memory storage applications. Despite unconventional use of structural change between amorphous and crystalline state as well as that between crystal structures for encoding information, key barriers for its widespread use remains access speed, capacity to cost ratio, and fidelity of storage. Hence, given the performance requirement of SPCM for memory applications, what are the material and design considerations that feed into translating a promising application into a practical reality? Given the important role of kinetic and thermal energy in structural organization of a phase change material, precise characterization of structural change in the material with external physical factors such as heat, voltage and current, is critical for storage material design. Next comes the precision at which individual memory cells for storing single bits of information could be defined reproducibly and at high fidelity using SPCM. In congruent with memory cell definition lies the equally important aspect of constraining the field characteristics used in modulating the phase state of the memory medium. Specifically, while heat is useful for mediating the “melting” of a crystalline material into its amorphous state, heat conduction is less useful for transferring the “switch command” from the effector to the memory material. More importantly, choice of structural phase change material for memory applications likely revolves around those where individual memory cells could be defined in a cross array format, which is amenable to high density information storage. Durability and fidelity of information storage are additional factors of design that favours selection of SPCM with phase change occurring at narrow operating windows without hysteresis over extended cycling. But, the most important requirement is speed of access. To this end, energetic cost of phase transitions might affect operation of the phase change memory at the system level: for example, usage of large current for high energy transition step may impact on device durability. Ultimately, there is a fundamental limit on the number of reproducible phase transitions in a SPCM before fidelity of information storage is no longer guaranteed. Hence, what are the drivers for uptake of phase change memories in consumer devices? Performance gains must be realized in access speed, storage capacity, form factor, and fidelity of information storage for practical application of structural phase change memories.

Growing cells is the typical mode of operation in many aspects of biotechnology and metabolic engineering. This comes about due to cell growth processes creating a driving force that pull metabolic flux along different metabolic pathways, that indirectly help move substrate to product. But, there is an alternative mode of operation that uses resting (non-growing) cells to achieve similar or even higher productivities. In general, resting cells are provided with carbon substrates for biocatalytic reactions but starved of nitrogen or phosphorus. Such resting cells have been usefully employed in many forms of biocatalysis and biotransformation, with or without cofactor regeneration. However, much remains unknown about the transcriptome and metabolome of resting cells in biotransformation settings. This short writeup provides the backdrop of resting cells in biocatalysis, documents their use in biotransformation with application examples, and identifies research gaps that could be filled with contemporary RNA-seq and mass spectrometry proteomics technology. Overall, utility of resting cells in biocatalysis and the extant knowledge gap in their fundamental physiology are highlighted in this resource.

Ribosomes are macromolecular complexes important to protein translation, and thus, essential to life. Comprising an ensemble of ribosomal proteins and RNA molecules, ribosomes are conserved in structure and function across all domains of life, but recent structural studies have revealed differentiated structures of ribosomes from bacterial, archaea and eukaryotes. Additionally, unique ribosomal protein mass fingerprints have been found for individual species; thereby, indicating that ribosomes are differentiated in structure amongst different species. Given that structure defines function, differentiated function likely exists amongst ribosomes of different species, which could manifest as differences in translation efficiency that could impact on cell growth rate. But ribosomal proteins also hold phylogenetic significance in informing the evolutionary trajectory of each species. Such ribosomal proteins are thus not highly conserved and offers sufficient sequence space for the evolution of differentiated structure and function in different species. Using ribosomal proteins that hold phylogenetic significance as templates, this study sought to understand the mutational and conformational limits that define functional ribosomes. Specifically, ribosomal proteins in Bacillus subtilis that hold phylogenetic cues would be mutated through error-prone polymerase chain reaction to generate variants that are subsequently transformed into Escherichia coli. To help assess the functional properties of the heterologous ribosomal proteins, endogenous ribosomal protein genes would be inactivated by multiplex CRISPR interference. Since variants in ribosomal proteins would likely impact on ribosome function and translation efficiency, live/dead screening on LB agar would be effective as a preliminary screen for functional mutants. These mutants would subsequently be inoculated into liquid LB medium in 96 well plates to quantify relative growth rates between different strains harbouring different heterologous variants of ribosomal proteins. Plasmids containing different ribosomal protein mutants would be extracted from each functional strain and subjected to Sanger sequencing for determining the specific mutations involved. Collection of such mutations would provide a comprehensive mutational map that define the limits of ribosomal protein sequence space important to ribosome function. Furthermore, biochemical isolation of ribosomal proteins and their structural characterization by X-ray crystallography or cryo-electron microscopy would further illuminate the structural significance of each mutation on ribosome structure and function; thereby, elucidating the structural tolerance space for functional ribosomes. Overall, generating a diverse pool of mutant ribosomal proteins in viability assays followed by sequencing and structural characterization would help define the mutational and conformational limits of a functional and efficient ribosome.

Bacterial phylogenetics has largely been determined via 16S rRNA gene sequencing and phylogenetic tree reconstruction. Observed utility of this approach has driven the popularity of the 16S rRNA gene amplicon metagenomics method for profiling and identifying diverse microbes from specific habitats. This work sought to develop universal primers for amplifying the 16S rRNA gene from a consortium of disparate microbial species. Using multiple sequence alignment of the 16S rRNA gene of a variety of microbes, the resulting highly conserved region of the consensus sequence was used for design of universal polymerase chain reaction (PCR) primers for 16S rRNA gene. Application of the universal primers in simulated PCR reveals poor amplification efficiency where only 12 species out of 31 generated an amplicon. BLAST analysis of the resulting amplicons reveals a classification error of 50%. More significantly, analysis of the amplicon length indicates variable read length ranging from 81 to 122 base pair compared to the predicted read length of 100 base pairs. This suggests that the 16S rRNA gene harbours significant hitherto underappreciated sequence diversity, and may have unknown alternative splicing and recombination mechanisms. Overall, results from this study suggests that primer design for 16S rRNA amplicon metagenomics may be application and habitat specific, where it is difficult to design universal primers for all bacterial species. Conceptually, this meant that there may be sequence co-evolution in 16S rRNA gene for microbial species in the habitat where environmental and nutritional conditions impact on 16S rRNA gene structure and sequence. In essence, 16S rRNA gene may habour epigenetics signals at the gene level.

The world of science is drowned in a wealth of information. How to make sense of this wealth of published articles, blog posts and abstracts has become an important challenge given the importance of science to different aspects of societal function. At the crux of the issue lies the increasing trend where scientific discovery informs decision making at the societal level. One example, is the elucidation of the ozone hole to the promulgation of the Montreal Protocol in 1987, and documenting increasing atmospheric carbon dioxide concentration led to climate action and signing of the Paris Agreement in 2015. Hence, understanding a research field becomes an important need for many decision makers across different sectors of society. But, the scientific literature is cryptic and esoteric, and presents a significant barrier to comprehension. One approach to ameliorate the problem is statistical machine reading, which provides the critical capability of identifying key concepts that underpins a research field. Such important concepts help provide an incision point to gain further understanding of the field and initiating further conversation about the field. This work sought to validate the concept of whether applying statistical machine reading to a body of literature comprising short blog posts and abstracts of published articles help in understanding the field of metabolic engineering. One important angle pursued in this research is whether the tabulated list of terms and phrases identified by statistical machine reading could be creatively analyzed to gain a deeper understanding of the research field. For example, the most frequently occurring terms and phrases could describe key concepts of the research field. Moving down in frequency occurrence would be terms and phrases that describe methodologies and approaches of the field. Finally, less frequently occurring terms and phrases may be tools and resources used in the research field. Results validated the utility of statistical machine reading in identifying important terms and phrases associated with the research field. But the small dataset of blog posts and abstracts used in this study severely hampered the identification of most of the key concepts of metabolic engineering, which is a fairly broad field of research. Overall, statistical machine reading shows utility in identifying terms and phrases that could describe a field. However, the level of understanding is closely tied in to the breadth and depth of reading material available, which meant that the methodology is data intensive in nature. Future use of supercomputing or quantum computing could help alleviate constraints of computational capacity, and help tackle the exponential rise in computational complexity as the size of the reading material for machine reading expands.

Promoting organic foods production and consumption contributes to accomplishing United Nations sustainable development goals. Social commerce provides a promising opportunity to develop the organic food industry. However, there is limited knowledge regarding customer behaviors in relation to purchasing organic foods via social commerce platforms. Therefore, this study expanded upon the unified theory of acceptance and use of technology (UTAUT-2) to develop a comprehensive model that explains how customers' social commerce trust and behavioral intentions to purchase organic foods using Instagram social commerce affect their purchasing behaviors. The research model was analyzed by employing partial least squares structural equation modeling (PLS-SEM) for the data collected from a quantitative survey of 410 customers who used Instagram to purchase organic foods in Iran. The results revealed that facilitated purchasing conditions, hedonic motivations, social influence, rating and reviews, and influencers’ endorsements increase customers' purchase intentions. Moreover, Instagram’s recommendations and referrals, influencers’ endorsements, as well as social influence boost customers' trust in the social commerce platform. Eventually, it was determined that influencers’ endorsements, social commerce trust, and purchase intention determine a customer’s organic foods purchasing behaviors. This research provides valuable insights for organic food marketers to optimize their social commerce strategies.

Phylogenetic tree analysis is commonly used to understand the evolutionary distance between different species or strains of the same species. This work originally aimed to gain an understanding and visual depiction of the evolutionary distance in 23S rRNA gene of different Helicobacter pylori strains. Using an in-house MATLAB multiple sequence alignment and phylogenetic tree analysis software, the phylogenetic tree constructed for 23S rRNA gene reveals two major lineages with further subdivisions in each cluster. This suggests two major evolutionary forces driving the evolution of the 23S rRNA gene. In comparison, there is relatively short evolutionary distance in the 16S rRNA gene phylogenetic tree of H. pylori, suggesting lack of major evolutionary forces driving mutational changes of the gene. Overall, the data suggests that the large ribosome subunit which houses the 23S rRNA of H. pylori is undergoing significant conformational changes that may be a response to the frequent use of various antibiotics that target the ribosome of H. pylori.

Quantitative polymerase chain reaction (qPCR) is the gold standard approach for detecting a variety of pathogens either via probe-based or SYBR green detection chemistry. Generally, probe-based detection is more specific than SYBR green chemistry. This report describes work done in using a FAM probe targeting a specific segment of the human KRAS gene for detecting presence and relative abundance of the gene in human gastric CloTest samples. Results indicate ineffective detection of the human KRAS gene in samples that are shown to harbor the gene through a similar qPCR assay using SYBR green detection chemistry. Such observations point to inability of the designed FAM probe to bind to target segment of the human KRAS gene that suggests a region of rapid genomic evolution that require close surveillance in the public health community. Given its rapid genomic evolution, this probe region may be an important region in the human KRAS gene playing critical functional roles in either molecular recognition or other structural functions. Overall, human KRAS gene may be undergoing rapid genomic evolution, and qPCR probes targeting specific segment of the gene may be rendered ineffective in short time clinically, thereby, making SYBR green qPCR assay a more reliable choice.

Dawn of the omics revolution in biological sciences meant that we seek to understand more and in greater detail the molecular constituents of cells and biological systems. While we have gained significant insights from conventional omics tools, we now seek to understand the spatial dimensions of the data where subcellular localisation may impact on cellular physiology and phenotype. This review paper seeks to address current questions in the new field of image-based spatial proteomics as well as outline future challenges of the field. At first glance, spatial proteomics offers enormous potential to expand our understanding of different cell types in different disease and cell states. But limitations in types of fluorophores and issues with spectral overlap significantly hampers the practical implementation of the technique. On the other hand, while we have super-resolution microscopy techniques such as STED, PALM and STORM able to achieve 10 to 20 nm spatial resolution in single molecule localisation, problems with slow image acquisition limits high temporal resolution tracking of multiple protein targets in live cell imaging. Hence, the field of spatial proteomics is a mix of promises and challenges where we could image, in multi-colour, upwards of 10 well-chosen proteins that could inform on the molecular mechanisms of selected biological processes, but, at present, the method could not tackle larger scale questions. In essence, current implementation of image-based spatial proteomics is useful, but it is unable to fulfil the mission of large-scale projects such as the Human Protein Atlas or Human Cell Atlas. Future challenges in the field includes the development of more fluorophores (especially photoswitchable and photoactivable ones) for single molecule localisation microscopy, as well as seeking to improve temporal resolutions to the sub-millisecond range.

Bacterial transformation is the essential tool for introducing foreign DNA into bacterial cells in a host of recombinant technology applications useful for biomanufacturing and drug production. Thus far, chemically competent cells remain an important enabling technology for bacterial transformation given its facile transformation approach. However, many parameters affect transformation efficiency, and there is relatively little documentation of their cross-interacting effect in the literature. This work explores the roles played by incubation time on ice, competent cell concentration, and plasmid-to-cell ratio on transformation efficiency in Escherichia coli DH5α. Results revealed that increases in incubation time improve transformation efficiency, but 2 minutes incubation still yield appreciable efficiency. On the other hand, low concentration competent cells (10⁶ CFU/mL) yielded significant improvement in transformation efficiency compared to high concentration competent cells (10⁸ CFU/mL). In terms of plasmid-to-cell ratio, higher ratio increases transformation efficiency. Overall, bacterial transformation is incompletely understood particularly in the area of cross-interacting parameters. Experiments reported here revealed the possibility of short duration transformation where lower competent cell concentration and higher plasmid-to-cell ratio could improve transformation.

Metagenomics have opened our eyes to the otherwise enigmatic microbial consortia that relies on different human body niches that impact on disease pathogenesis. This work originally aims to re-analyse a public shotgun metagenomics dataset to glean insights on the microbial species that may partake in stomach cancer pathogenesis. However, a random selection of sequenced reads reveals poor percent identities (79 to 94%) of the microbial identification obtained in a BLAST search. This surprising result suggests possible stomach acid induced degradation or modification of the sequenced read that reduced the effectiveness of the metagenomics approach in microbial identification. Further analysis of the dataset highlights that poor percent identities did not arise due to highly fragmented nature of the genetic material where there is a good abundance of sequenced reads in the 100 to 1300 base pair category. More intriguingly, attempts to obtain a correlation between percent identity and read length did not reveal a correlation which meant that stomach acid did not modify all types of nucleotides. More likely, stomach acid only modified low abundance nucleotide in this case, which point to the probability of identifying a microbe in the modified gene fragment in totally unpredictable ways. Overall, data reported in this work suggests caution in the interpretation of results of shotgun metagenomics studies of stomach cancer microbiota where stomach acid likely degraded the genetic material of microbes that may result in mis-identification.

Due to species barriers and poor adaptability to new host environments, few pathogens cause global pandemics. But, SARS-CoV-2 is one exception with its high transmissivity and delayed onset of symptoms. Fortunately, the world was able to tap on the technologies especially the maturing RT-qPCR designed to combat SARS to launch an initial offensive on SARS-CoV-2. These initial efforts may have bought time for scientists to develop more refined diagnostic tests that specifically target SARS-CoV-2. This article describes the effort put forth by the biotech industry and academia in Singapore to develop diagnostic tests that aid the early detection of positive cases, and thereby help contain the virus. Direct tests such as RT-qPCR and antigen rapid test profile the virus nucleic acid and surface proteins, respectively. But, of equal importance in case detection and treatment is serological tests that measure the relative abundance of IgM and IgG which is indicative of infection phase and quality of immune response in positive cases. Other tests such as isothermal amplification, CRISPR-based diagnostics and breath tests are also in development or at initial field deployment, and would undoubtedly provide valuable use experience useful for the development of molecular assays to detect and combat the next pathogen of global concern.

Although cofactor regeneration is an established system in biocatalysis, work remains in developing new and alternative cofactor regeneration systems with greater efficiency, ease of use, and higher atom economy. In addition, cofactor regeneration system only works if the cofactor regeneration reaction operates at similar kinetics compared to the biotransformation reaction. This meant that only specific cofactor regeneration system is capable of coupling with particular biotransformation reaction. This then leaves open the field for the development of a plethora of alternative cofactor regeneration systems each capable of coupling with different biotransformation reaction of different kinetics. This short write-up examines the possibility of tapping on the NADH regenerated from a two-step ethylene glycol utilization pathway. Current knowledge suggests that this angle has not been explored; thereby, opening up possibilities for future experimental investigations into the feasibility of coupling ethylene glycol utilization pathway with biotransformation reaction as a coupled cofactor regeneration system.

Successful engineering of a microbial host for efficient production of a target product from a given substrate can be viewed as an extensive optimization task. Such a task involves the selection of high activity enzymes as well as their gene expression regulatory control elements (i.e., promoters and ribosome binding sites). Finally, there is also the need to tune expression of multiple genes along a heterologous pathway to relieve constraints from rate-limiting step and help reduce metabolic burden on cells from unnecessary over-expression of high activity enzymes. While the aforementioned tasks could be performed through combinatorial experiments, such an approach incurs significant cost, time and effort, which is a handicap that can be relieved by application of modern machine learning tools. Such tools could attempt to predict high activity enzymes from sequence, but they are currently most usefully applied in classifying strong promoters from weaker ones as well as combinatorial tuning of expression of multiple genes. This perspective reviews the application of machine learning tools to aid metabolic pathway optimization through identifying challenges in metabolic engineering that could be overcome with the help of machine learning tools.

Hydrogen is useful as a fuel and could be produced by a variety of means. One approach uses artificial photosynthesis where energy from sunlight powers the splitting of water into hydrogen and oxygen. But, biological methods for producing hydrogen has emerged strongly over the past decades. In particular, specific microorganisms could use different substrates to produce hydrogen at differing yields. Such fundamental discoveries with industrial applications thus motivated the use of metabolic engineering approaches and methodologies in enhancing biological hydrogen production through a series of enzyme over-expression, pathway debottlenecking, and gene deletion. However, such approaches heavily rely on the selection of an appropriate microbial chassis for biohydrogen production. With the proper strain in hand, use of alternative substrates may engender greater hydrogen productivities. But learning from the bioprocessing field, co-culture of two compatible microorganisms have been sought after for improving biohydrogen production. In addition, thermophilic microbes may also be useful candidates for exploiting hydrogen production from composting. Future outlook in the field looks into filling our gaps in understanding of the metabolic network that feeds into hydrogen production in different organisms. But, more importantly, problems such as reduced growth rate in engineered microbes point to fundamental issues with using genetically engineered microorganisms for improved biohydrogen production, to which clever bioprocess engineering may yield solutions.

History is often thought to be dull and boring – where large numbers of facts are memorized for passing exams. But the past informs the present and future, especially in delineating the context surrounding specific events that, in turn, help provide a deeper understanding of their causes and implications. Scientific progress (whether incremental or breakthroughs) is built upon prior work. Chronological examination of computational chemistry’s evolution reveals the existence of major “epochs” (e.g., transition from semi-empirical methods to first principles calculations), and the centrality of key ideas (e.g., Schrodinger equation and Born Oppenheimer approximation) in potentiating progress in the field. The longstanding question of whether computing power (both capacity and speed) or theoretical insights play a more important role in advancing computational chemistry was examined by taking into account the field’s development holistically. Specifically, availability of large amount of computing power at declining cost, and advent of graphics processing unit (GPU) powered parallel computing are enabling tools for solving hitherto intractable problems. On the other hand, this essay argues (using Born Oppenheimer approximation as an example) that theoretical insights’ role in unlocking problems through simple (but insightful) assumptions is often overlooked. Collectively, the essay should be useful as a primer for appreciating major development periods in computational chemistry, from which counterfactual questions illuminate the relative importance of theoretical insights and advances in computer science in moving the field forward.

Antennas are crucial elements for wireless technologies, communications and power transfer across the entire spectrum of electromagnetic waves, including radio, microwaves, THz and optics. In this paper, we review our recent achievements in two promising areas: coherently enhanced wireless power transfer (WPT) and superdirective dielectric antennas. We show that the concept of coherently enhanced WPT allows improvement of the antenna receiving efficiency by coherent excitation of the outcoupling waveguide with a backward propagating guided mode with a specific amplitude and phase. Antennas with the superdirectivity effect can increase the WPT systems performance in another way, through tailoring of radiation diagram via engineering antenna multipoles excitation and interference of their radiation. We demonstrate a way to achieving the superdirectivity effect via higher-order multipoles excitation in a subwavelength high-index spherical dielectric resonator supporting electric and magnetic Mie multipoles. Thus, both types of antenna discussed here possess a coherent nature and can be used in modern intelligent antenna systems.

The emergence of Artificial Intelligence (AI) driven Keyword Spotting (KWS) technologies has revolutionized human to machine interaction. Yet, the challenge of end-to-end energy efficiency, memory footprint and system complexity of current Neural Network (NN) powered AI-KWS pipelines has remained ever present. This paper evaluates KWS utilizing a learning automata powered machine learning algorithm called the Tsetlin Machine (TM). Through significant reduction in parameter requirements and choosing logic over arithmetic based processing, the TM offers new opportunities for low-power KWS while maintaining high learning efficacy. In this paper we explore a TM based keyword spotting (KWS) pipeline to demonstrate low complexity with faster rate of convergence compared to NNs. Further, we investigate the scalability with increasing keywords and explore the potential for enabling low-power on-chip KWS.

This paper investigates the constructability of angles multiples of 3 within the framework of Euclidean geometry. It makes a significant contribution by presenting the first geometric construction for all such angles, offering a rigorous solution to a longstanding geometric problem. The paper reaffirms the efficacy of Euclidean geometry in providing precise constructions and robust proofs for these angles, demonstrating the enduring strength of Euclidean principles from classical to modern times. The presented workflow goes beyond Euclidean geometry to examine non-Euclidean methods, particularly analytical approaches, revealing misconceptions that compromise the genetic and geometric rigor of Euclidean principles. The paper exposes incongruities when algebraic proofs related to angle constructability are applied to the Euclidean system, emphasizing the misalignment of fundamental geometric concepts. A notable result in the paper is the construction of a angle, introducing the “ angle chord” as a novel geometric property. This property challenges assumptions made by non-Euclidean methods and highlights the nuanced geometric properties crucial for rigorous constructions. The paper refutes the fallacy of relying solely on algebra for solutions to angles multiples of , emphasizing the necessity of embracing Euclidean geometry for geometric discoveries. The paper underscores the merits and resilience of Euclidean geometry, showcasing its independence and depth across historical and modern perspectives. The newly presented geometric construction not only resolves a longstanding question but also emphasizes the intrinsic strength and uniqueness of Euclidean principles in contrast to alternative methodologies.

Background: Probiotics can provide health benefits to an individual by regulation of the immune system. Many clinical trials have found that probiotics can prevent upper respiratory tracts infections. Aim: To perform a systematic review and meta-analysis of available trials to investigate the effectiveness of probiotics in the prevention of upper respiratory tract infections in individuals of all ages. Conclusion: Probiotics were found to be better in reducing the number of participants who experienced acute URTI, the average duration per episode of acute URTI, use of antibiotics in URTI related cases and absence due to URTI. Side effects were found to be minor, making probiotics a good candidate for clinical use. This shows that probiotics are effective in preventing acute URTIs. However, due to limited studies and small sample size, the results are subjected to bias and should be interpreted with care.

Solid tumors universally possess the ability to evade contact inhibition of proliferation (CIP), a mechanism halting cell proliferation when cell-cell contacts occur. Merlin, an ERM-like protein, crucially regulates CIP and is frequently deactivated in various cancers, indicating its signifi-cance as a tumor suppressor in cancer biology. Despite extensive investigations into Merlin's role in cancer, its lack of intrinsic catalytic activity and frequent conformation changes has made it notoriously challenging to study. To address this challenge, we harnessed innovative luciferase technologies to create and validate a split-luciferase biosensor system. This system enables precise quantification of Merlin's conformation and activity both in vitro and within living cells. This biosensor significantly enhances the study of Merlin's molecular functions, serving as a potent tool to explore its contributions to CIP and tumorigenesis.

Background: This study delves into the examination of racial and ethnic disparities in the distribution of the Monkeypox (MPOX) virus vaccine within the United States, offering a critical healthcare perspective on an emerging public health concern. It particularly focuses on the demographic patterns associated with MPOX transmission and the allocation of vaccines. Methods: A comprehensive analysis was conducted, drawing on a wide array of data sources to understand the vaccine distribution and demographic trends in the United States. The study scrutinized three main aspects: MPOX cases by race and ethnicity, vaccine administration across different racial and gender categories, and the potential disparities therein. Results: The findings reveal significant disparities in the distribution of vaccine doses, with males, particularly gay, bisexual, and other Men who have sex with men (MSM), receiving the majority of doses. Moreover, substantial variations in MPOX cases are observed among different racial and ethnic groups, emphasizing the need for culturally sensitive public health strategies. Conclusions: The study underscores the urgent need for targeted public health interventions to address disparities and safeguard the well-being of those at higher risk, particularly MSM. It highlights the importance of equity in vaccine distribution and culturally sensitive approaches, and serves as a foundation for shaping effective public health policies and strategies to mitigate the spread of MPOX. This research advances our understanding of healthcare disparities in the context of an emerging viral infection, providing valuable insights for future public health initiatives.

The changes in consumer preferences and the increasingly competitive global market have demanded that food entrepreneurs engage in innovative value-added activities. The date is a delicatessen fruit known by its content of active compounds (e.g., dietary fiber and antioxidants) and its biological activity which has a vast potential in the design of new products such as bioactive ingredients, sugar substitutes, dietary supplements, functional foods, among others. In the current paper, innovative approaches to the value addition to date fruits and their processing by-products have been reviewed from recent high-quality scientific works. New processes such as ultrafiltration and hydrothermal treatments are shown as a useful alternative to obtain differentiated date-based ingredients (e.g., fiber concentrates, sap syrups, and date powders). Moreover, the use of date fruits and their byproducts as natural sources of value-added active compounds in the preparation of dairy, meat, and bakery and cereal products is also presented.

The fluorine-less noble-gas containing anions OBONgO- and OCNNgO-have been studied by correlated electronic structure calculation and density functional theory. The obtained energetics indicates that for Ng = Kr and Xe, these anions should be kinetically stable at low temperature. The molecular structures and electron density distribution suggests that these anions are stabilized by ion-induced dipole interactions with charges concentrated on the electronegative OBO and OCN groups. The current study shows that in additional to the fluoride ion, polyatomic groups with strong electronic affinities can also form stable noble-gas containing anions of the type X-...NgO.

The links between mindfulness, savoring positive experiences, and depressive symptoms have been well-established in the literature. Nevertheless, little has been done to disentangle the prospective relations among these constructs. Clarifying the longitudinal relations is crucial, as it enables researchers and practitioners to discern potential trajectories of mental health interventions. In this study, 180 emerging adults between 18 and 27 years old were recruited twice at 3 months apart to complete self-reported measures including mindfulness, savoring positive experiences, and depressive symptoms. Cross-lagged path analysis indicated that savoring the moment was predictive of mindfulness three months later, whereas depressive symptoms were predictive of both mindfulness and savoring the moment three months later, above and beyond the effects of age, gender, and family income. Additionally, mindfulness, savoring positive experiences, and depressive symptoms were significantly correlated at baseline. The present study evidenced short-term inversed effects of depressive symptoms on mindfulness and savoring the moment, as well as a positive effect of savoring the moment on mindfulness. Hence, interventions gearing towards symptom reduction of depression are likely to carry concurrent and prospective benefits of psychological functioning, namely the ability to be present in the moment and to savor. Taken together, reducing depressive symptoms may be crucial in fostering psychological well-being.

We have investigated the influence of the relative proportions of glass formers in a series of lithium alumino-borosilicate glasses with respect to electrical conductivity () and glass transition temperature (Tg) as functions of glass structure, as determined by Raman spectroscopy. The ternary lithium alumino-borate glass exhibits the highest  and lowest Tg among all the compositions of the glass series, 30Li2O•3Al2O3• (67-x) B2O3•xSiO2. However, as B2O3 is replaced by SiO2, a shallow minimum in  as well as a shallow maximum in Tg are observed near x = 27, where the Raman spectra indicate isolated diborate/tetraborate/orthoborate groups are being progressively replaced by danburite/reedmergnerite-like borosilicate network units. Overall, as the glasses become silica-rich,  is minimized, while Tg is maximized. In general, these findings show correlations among Tg, (sensitive to network polymerization),  (proportional to ionic mobility), and the different borate and silicate glass structural units as determined by Raman spectroscopy. X-ray diffraction analyses demonstrate the absence of appreciable crystallinity in the glasses investigated. However, scanning electron microscopy (SEM) images of HF-etched samples showed that glasses, and especially the borate-rich compositions comprise two distinct glassy phases. The isolated phase is 25-100 nm in diameter, dispersed evenly in a glassy matrix.

This study considers an application of the first-order Grey Markov Model to foresee the values of Italian power generation in relation to the available energy sources. The model is used to fit data from the Italian energy system from 2000 to 2022. The integration of Markovian error introduces a random element to the model, which is able now to capture inherent uncertainties and misalignments between the Grey model predictions and the real data. This application provides valuable insights for strategic planning in the energy sector and future developments. The results show good accuracy of the predictions, which provides powerful information for the effective implementation of energy policies concerning the evolution of energy demand in the country. Despite advancements, Italy’s 2032 energy mix will still significantly rely on fossil fuels, emphasizing the need for sustained efforts beyond 2032 to enhance sustainability.

Nanoscale structuring/printing is of interest for range of applications in 3D subtractive and additive manufacturing (3D^+/-). Basic principles of light field enhancement and control at the nanoscale are overviewed in this section/chapter for bulk, surface, and localised plasmons (1D, 2D, and 3D localisation, respectively). All these plasmons are resonant phenomena which have common Lorentzian spectral lineshape which relates refractive and absorption properties as well as defining the phase of transmitted and scattered light. Localisation of light at the nanoscale creates the possibility of modification with matching resolution. Harnessing this light enhancement can be demonstrated as a "nano-pen" for direct write nanolithography.

Drag-dominant tidal turbine energy holds tremendous clean energy potential but faces significant hurdles as unsuitability of Disk Actuator theory due to the varying swept blockage area, unaccounted bypass flow downstream interaction and rotor parasitic drag whereas Blade Element Momentum theory is computably effective for majorly 3-blade lift-dominated aerofoil. This study proposes a novel method to find the optimal TSR of any turbine with a cost-effective and user-friendly Moment Balancing algorithm to support robust tidal energy development. Performance analysis CFD study of Pinwheel and Savonius tidal turbines was carried out. Dynamic TSR matrix was developed with varying rotational speeds and fluid velocities for reliability, unlike previous works simulated at a fixed fluid velocity. Novel parameters such as thrust and idle moment are introduced as functions of only inlet fluid velocity and rotational speed respectively. These relationships are verified through regression analysis, and the turbines' net moment equations are established based on these parameters. Rotational speed was a reliable predictor for Pinwheel's idle moment, while inlet velocity was a reliable predictor for thrust moment in both models. The optimal (Cp, TSR) values for Pinwheel and Savonius turbines were (2.37, 0.223) and (0.63, 0.16) respectively, within an acceptable error range for experimental validation.

The Internet of Things (IoT) technology and devices constitute an exciting field in computer science that is rapidly emerging worldwide. IoT devices function by connecting real-world objects to the internet, resulting in a higher number of interconnected devices than ever witnessed in history. Through internet connectivity, these devices can be utilized in various ways, such as monitoring and tracking. Their prevalence is increasing exponentially, coinciding with advancements in wireless networking technologies. The internet’s enhanced connectivity has played a vital role in fostering the proliferation of IoT devices. Presently, almost any everyday object can be network-connected. The demand for automation and efficiency has also been a contributing factor to the advancements in this technology. This paper aims to review the emergence of IoT devices, analyze their common applications, and explore the future prospects in this promising field of computer science. The examined applications encompass healthcare, agriculture, and smart cities. Although IoT technology exhibits similar deployment trends, this paper will explore different fields to discern the subtle nuances that exist among them. IoT technology can be applied to nearly any domain, and each use case has unique requirements. To comprehend the future of IoT, it is essential to comprehend the driving forces behind its advancements in various industries. By gaining a better understanding of the emergence of IoT devices, readers will develop insights into the factors that have propelled their growth and the conditions that led to technological advancements. Moreover, a comprehensive understanding of the prevalent methodologies will enable readers to distinguish between current practices and future methods. Given the rapid rate at which IoT technology is advancing, this paper aims to provide researchers with an understanding of the factors that have brought us to this point and the ongoing efforts to shape the future of IoT.

In this review, we explore a broad-based view of technologies for supporting human activities on the Moon. Primarily, we assess the state of life support systems technology beginning with physicochemical processes, waste processing, bioregenerative methods, food production systems and the robotics and advanced biological technologies that support the latter. We observe that the Moon possesses in-situ resources but that these resources are of limited value in CELSS – indeed, CELSS technology is most mature in recycling water and oxygen, the two resources that are abundant on the Moon. This places a premium on developing CELSS that recycles other elements that are rarified on the Moon including C and N in particular but also other elements such as P, S and K which might be challenging to extract from local resources. Although we focus on closed loop ecological life support systems, we also consider related technologies that involve the application of biological organisms to bioregenerative medical technologies and bioregenerative approaches to industrial activity on the Moon as potential future developments.

The paper briefly reviews the Clifford algebras of space Cl(3,0) and anti-space Cl(0,3) with a particular focus on the paravector representation, emphasizing the fact that both algebras have an isomorphic center represented just by two coordinates. Since the paravector representation allows assigning the scalar element of grade 0 to the time coordinate, we consider the relativity in such two-dimensional spacetime for a uniformly accelerated frame with the constant acceleration 3Hc. Using the Rindler coordinate transformations in two-dimensional spacetime and then applying it to Minkowski coordinates, we obtain the FLRW metric, which in the case of the Clifford algebra of space Cl(3,0) corresponds to the anti-de Sitter (AdS) flat (k=0) case, the negative cosmological term and an oscillating model of the universe. The approach with anti-Euclidean Clifford algebra Cl(0,3) leads to the de Sitter model with the positive cosmological term and the exact form of the scale factor used in modern cosmology.

A novel effective vibrational mode was discovered in the conventional transducer with an array of orthogonal (square) regular piezoelectric rods in 1-3 piezocomposite, containing the damping backing and front matching layers. The operational resonance in the structure was determined as the Surface Acoustic Wave (SAW) on the backing boundary excited by the adjacent piezo-rods, with its frequency typically near 3 times lower the fundamental half-lambda conventional piezocomposite resonance. Pulse-echo sensitivity and transmitting sound-pressure-level (SPL) in air showed that the signal strength is roughly comparable to the industrial similar air transducers at the frequency range 100…700 kHz, where at these frequencies the lateral and longitudinal piezoelement dimensions in the conventional transducer design are typically close to each other causing interference with unwanted coupling modes. As was determined theoretically and proved in experiments, the backing SAW resonance effect in the transducer performance is inherent just to the regular periodic 1-3 piezocomposite structure, and does occur neither with randomly located/oriented piezo-rods, nor in the homogeneous piezo-plate at least with the same lateral cross-section as the connected to it backing. The purpose of the article is to investigate a newly discovered operational vibrational mode of a SAW type in 1-3 regular piezocomposite, other than piezoelectric resonance. The investigated phenomena can improve the transceiver sensitivity, bandwidth, providing lower drive voltage, and smaller and lighter weight ultrasonic transducers. Based on the piezocomposites with thickness’ 1…1.5 mm (rod resonance near 2…3 MHz), pillar width 0.2…0.8 mm, kerf width 0.1…0.4 mm, the transceivers with an operating frequency from 140 kHz to 650 kHz were designed and fabricated with a conventional backing of a mixture of high-density tungsten powder and epoxy, and a matching layer of a mixture of low-density glass bubbles and epoxy. Experimental evaluation of their acoustical performance showed expected characteristics suitable for practical applications.

The exact etiology of myopia remains elusive. The author proposes the particle property of photon in living tissue and the photon-electron theory in living tissue, if the frequency of the photon exceeds the threshold, the photon has enough energy to strike the electron away and forms a hole of a diameter in photon diameter scale in living tissue include the eye. Longer time of high-frequency electromagnetic radiation will cause more holes and a larger radius of holes. The visual light which passes through the radiated hole in the eye cannot be refracted on the macula, this is myopia symptom of blurred vision, shortening the distance of the eye and the object will include more visual light into cornea and lens, this is myopia another symptom of nearsightedness. The particle property of photon causes elongation of the eye and the macular holes.Blue light and X-ray are two kinds of high-frequency electromagnetic radiation which can shot holes in eye and cause myopia.

The electric field is enormously more powerful than the gravitational field. However, in our normal experience there is no electric field, the electric force is missing. How is it that when you get to larger and larger scales the gravitational field is extremely important whereas the electric field becomes less and less important [1]? This paper proposes a model to explain why gravitation dominates at a larger scale.

Background: Cell proliferation and the cell cycle are fundamental to tumor development, with mitosis playing a crucial role in cell division. Understanding the complexities of the cell cycle and mitosis is critical for cancer research, especially in the context of developing therapeutic strategies. Objective: This review highlights mitotic poisons as potential anti-cancer pharmacotherapeutics, particularly their structural and functional group diversity presenting opportunity for semi-synthesis of new derivatives with multi-target mechanisms relevant for cancer pharmacotherapeutics. Also, the review explores naturally occurring mitotic poisons and inhibitors of microtubule-dependent molecular motors as promising cancer pharmacotherapeutics. Methods: A comprehensive review of literature from 2004 to 2023 was conducted, covering studies on cell proliferation, mechanism of cell cycle regulation, mitosis, cytokinesis, and anti-cancer drug development. The published literature was collected primarily from PubMed, Scopus, Medline, Web of Science Core Collections, Google Scholar and other relevant scientific databases using keywords including but not limited to mitotic poisons and cancer, sources of mitotic poisons, mechanism of mitotic poisons, targets of mitotic poisons and structural diversity of mitotic poisons. The efficacy and limitations of various mitotic poisons and their impact on different cancer types were examined. Recent advancements in targeted therapeutic interventions for various cancers were also explored. Results: The effectiveness and limitations of mitotic poisons, including Taxanes, Epothilones, Colchicine, Vinca alkaloids, Berberine, Laulimalide, and Pseudolaric acid B, were highlighted. Drugs targeting mitotic kinases such as CDKs, Aurora kinases, PLK1, and WEE1 inhibitors were reported. Inhibiting kinesin motor proteins such as Eg5 and KIF15 to interfere with spindle formation and cell division were discussed, along with specific genomic alterations in KIF genes and the discovery of KIFC1 as potential for future research and drug development. Conclusion: Targeting microtubules and mitotic kinases, along with inhibiting kinesin motor proteins, show promise for cancer pharmacotherapeutics. The combination of targeted therapies, patient stratification based on biomarkers (such as low alpha-1 acid glycoprotein and high p63 expression), and exploration of alternative natural sources of mitotic poisons and analogues can significantly advance cancer pharmacotherapy to improve patient outcomes.

Natural cycles underpin the very stuff of life. In this commentary we consider unnatural cycles: that is, anthropogenic activities which have a circularity, but whose nature is to have a detrimental effect on human health, exacerbating existing problems. Natural cycles have feedback loops, some of which have recently come to light, with an understanding that everything is connected in some way. In health, feedback loops are imperative in homeostatic mechanisms. However, in the unnatural cycle the feedback loops serve to reinforce (and in some cases amplify) negative problems. We offer a commentary on an unnatural cycle moving from air quality to lung function and back to air quality; we call this the lung disease unnatural cycle. We suggest where links occur, and where wider consideration of interactions between various disciplines can lead to breaking this unnatural (or vicious) cycle, changing it to a healthy cycle where individual health can be improved, along with better global scale outcomes. We suggest that many activities within this unnatural cycle occur within silos. However, the improved cycle incorporates joint activities at geological, health, and financial levels, to the mutual benefit of all, breaking the unnatural cycle, and improving health, life and financial costs.

Nowadays, diamonds are widely used in science and technology. However, the properties of diamonds due to their defects are not fully understood. In addition to optical methods, positron annihilation spectroscopy (PAS) can be successfully used to study defects in diamonds. Positrons are capable of detecting vacancies, small and large clusters of vacancies induced by irradiation, by providing information about their size, concentration, and chemical environment. By mapping in the infrared (IR) range, it is possible to consider the admixture composition of the main inclusions of the whole plate. The article presents the results of the study of defects in synthetic diamond plates, one of which was irradiated by electrons. Presents data about the distribution of the defect concentration obtained by Infrared spectroscopy. PAS with a monochromatic positron beam can be used as a non-destructive technique of detecting defects (vacancy) distribution over the depth of diamond plates.

Reducing sedentary behaviours can help prevent non-communicable diseases, particularly among young adolescents with long term illnesses or disabilities (LTID). Much of young people’s voluntary sedentary time is related to screen-time behaviours (STBs) such as TV viewing, playing computer games, and using the computer for other activities. Although public health data on adolescents’ STB is growing, information about adolescents with LTID is currently lacking in a European context. The purpose of this study is to compare time on STBs between adolescents with and without LTID in European Countries through the HBSC 2013/14 study. Young adolescents (n = 61,329; boys 47.8%) from 15 European countries reported the time spent on TV viewing, playing computer games, and using the computer for other purposes on weekdays and the weekend. STBs were dichotomised based on international recommendations of less than 2 h per day, and Chi-square tests of independence were performed to investigate differences. STB time was combined to produce a sum score as dependent variable in multiple analysis of covariance with age and family affluence as covariates. There were statistically significant differences in computer gaming among boys and other computer use among girls for both weekdays and weekends, whereby adolescents with LTID reported higher use. In addition, both boys and girls with LTID spent more time on STBs than their same sex peers without LTID (Boys, F = 28.17, p < 0.001; Girls, F = 9.60, p = 0.002). The results of this study indicate a need for preventive strategies to address high levels of STB among young adolescents with LTID and reduce the risk of poor health outcomes associated with higher levels of sedentary behaviour.

Synchrotron radiation computed tomography (SRCT) allows more accurate calcified plaque and coronary stenosis assessment as a result of its superior spatial resolution, however, typical micro-computed tomography (micro-CT) systems have even higher resolution. The purpose of this study was to compare performance of high-resolution micro-CT with SRCT in the assessment of calcified plaques and a previously published dataset of coronary stenosis assessment. This experimental study involved micro-CT scanning of three-dimensional printed coronary artery models with calcification in situ used in our previously published SRCT study on coronary stenosis assessment. Measurements of coronary stenosis utilizing both modalities were compared using a paired sample t-test. The degrees of stenosis measured on all but one micro-CT dataset were statistically significantly lower than the corresponding SRCT measurements reported in our previous paper (p&lt;0.0005-0.05). This indicates that the superior spatial resolution of micro-CT was able to further reduce over-estimation of stenosis caused by extensive calcification of coronary arteries and hence false positive results. This study shows that high-resolution micro-CT outperforms SRCT in both calcified plaque and coronary stenosis assessment. This finding will become clinically important for cardiovascular event prediction and enable reclassification of individuals with low and intermediate risk into appropriate risk categories when the technical challenges of micro-CT in clinical practice such as the small field of view and demanding on image processing power are addressed.

Next-generation sequencing is now a mature technology, allowing partial animal genomes to be produced for many clades. Though many software exist for genome assembly and annotation, a simple pipeline that allows researchers to input raw sequencing reads in fastq format and allow the retrieval of a completely assembled and annotated mitochondrial genome is still missing. mitoMaker 1.0 is a pipeline developed in python that implements (i) recursive de novo assembly of mitochondrial genomes using a set of increasing k-mers; (ii) search for the best matching result to a target mitogenome and; (iii) performs iterative reference-based strategies to optimize the assembly. After (iv) checking for circularization and (v) positioning tRNA-Phe at the beginning, (vi) geneChecker.py module performs a complete annotation of the mitochondrial genome and provides a GenBank formatted file as output.

Retinoic acid receptor-related orphan receptor γ (RORγ) is a transcription factor regulating the expression of the pro-inflammatory cytokine IL-17 in human T helper 17 (Th17) cells. Activating RORγ can induce multiple IL-17-mediated autoimmune diseases but may also be useful for anticancer therapy. Its deep immunological functions make RORɣ an attractive drug target. Over 100 crystal structures have been published describing atomic interactions between RORɣ and agonists and inverse agonists. In this review, we focus on the role of dynamic properties and plasticity of the RORɣ orthosteric and allosteric binding sites by examining structural information from crystal structures and simulated models. We discuss the possible influences of allosteric ligands on the orthosteric binding site. We find that high structural plasticity favors the druggability of RORɣ, especially for allosteric ligands.

Simulating the non-perturbative and non-Markovian dynamics of open quantum systems is a very challenging many body problem, due to the need to evolve both the system and its environments on an equal footing. Tensor network and matrix product states (MPS) have emerged as powerful tools for open system models, but the numerical resources required to treat finite temperature environments grow extremely rapidly and limit their applications. In this study we use time-dependent variational evolution of MPS to expore the striking theory of Tamescelli et al. that shows how finite temperture open dyanmics can be obtained from zero temperature, i.e. pure wave function, simulations. Using this approach, we produce a benchmark data set for the dynamics of the Ohmic spin-boson model across a wide range of coupling and temperatures, and also present detailed analysis of the numerical costs of simulating non-equilibrium steady states, such as those emerging from the non-perturbative coupling of a qubit to baths at different temperatures. Despite ever growing resource requirements, we find that converged non-perturbative results can be obtained, and we discuss a number of recent ideas and numerical techniques that should allow wide application of MPS to complex open quantum systems.

With rapid advances in gene editing and gene therapy technologies, the development of genetic, cell, or protein-based cures to disease are no longer the realm of science fiction but that of today’s practice. The impact of these technologies are rapidly bringing them to the veterinary market as both enhanced therapeutics and towards modeling their outcomes for translational application. Simply put, gene editing enables scientists to modify an organism’s DNA a priori through the use of site-specific DNA targeting tools like clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). Gene therapy is a broader definition that encompasses the addition of exogenous genetic materials into specific cells to correct a genetic defect. More precisely, the U.S Food and Drug Administration (FDA) defines gene therapy as “a technique that modifies a person’s genes to treat or cure disease” by either (i) replacing a disease-causing gene with a healthy copy of the gene; (ii) inactivating a disease-causing gene that was not functioning properly; or (iii) introducing a new or modified gene into the body to help treat a disease. In some instances, this can be accomplished through direct transfer of DNA or RNA into target cells of interest or more broadly through gene editing. While gene therapy is possible through the simple addition of genetic information into cells of interest, gene editing allows the genome to be reprogrammed intentionally through the deletion of diseased alleles, reconstitution of wild type sequence, or targeted integration of exogenous DNA to impart new function. Cells can be removed from the body, altered, and reinfused, or edited in vivo. Indeed, manufacturing and production efficiencies in gene editing and gene therapy in the 21^st century has brought the therapeutic potential of in vitro and in vivo reprogrammed cells, to the front lines of therapeutic intervention (Brooks et al., 2016). For example, CAR-T cell therapy is revolutionizing hematologic cancer care in humans and is being translated to canines by us and others, and gene therapy trials are ongoing for mitral valve disease in dogs.

Head and neck squamous cell carcinoma (HNSCC) is a type of cancer that arises from the epithelium lining of the oral cavity, hypopharynx, oropharynx, and larynx. Despite advancement of the current treatment to HNSCC, such as surgery, chemotherapy, and radiotherapy, the overall survival rate of HNSCC remains poor due to late diagnosis and acquired resistance to treatment. Natural products have been extensively explored as a safer and more acceptable alternative to current treatments, with numerous studies displaying their potential against HNSCC. This review highlights preclinical studies in the past 5 years involving natural products against HNSCC and explores the signalling pathways altered by these products. This review also addresses challenges and future directions of the use of natural products as chemotherapeutic and chemoprevention agents against HNSCC.

Fresnel incoherent correlation holography (FINCH) is a well-established incoherent imaging technique. In FINCH, three self-interference holograms are recorded with calculated phase differences between the two interfering, differently modulated object waves and projected into a complex hologram. The object is reconstructed without the twin image and bias terms by a numerical Fresnel back propagation of the complex hologram. A modified approach to implement FINCH by a single camera shot by pre-calibrating the system involving recording of the point spread function library and reconstruction by a non-linear cross-correlation has been introduced recently. The expression of the imaging characteristics from the modulation functions in original FINCH and the modified approach by pre-calibration in spatial and polarization multiplexing schemes are reviewed. The study reveals that a reconstructing function completely independent of the function of the phase mask is required for the faithful expression of the characteristics of the modulating function in the image reconstruction. In polarization multiplexing method by cross-correlation, a partial expression was observed, while in spatial multiplexing method by cross-correlation, the imaging characteristics converged towards a uniform behavior.

In this work, we present some results related with the issue of the Loop Quantum Black Holes (LQBH) thermodynamics by the use of the tunneling radiation formalism. The information loss paradox is also discussed in this context, where we have considered the influence of back reaction effects.

Despite the increase in popularity of Zero Waste (ZW) concept, the successful implementation of this concept in waste management is still facing many challenges. The plastic recycling rate in Australia is currently only about 9.4%, which could leave up to 90.6% of plastic consumption being sent to landfills. The state of Victoria (in Australia) has proposed an ambitious plan to upgrade its waste and recycling system and to divert about 80% of waste from landfills by 2030. The aim of this research is to study Victoria’s current waste management plan and to develop a simulation model to assess the feasibility of it achieving zero plastic waste by 2035. In this direction, a fundamental knowledge of global ZW implementation needs to be acquired in order to understand the challenges, obstacles, and uncertainties in achieving ZW target. A simulation model is established using a method called double baselines. This method was developed as an improvisation to address the limitation of data availability for the model development. The model will run on 4 scenarios including one from Victoria’s current plan. Outcomes from the model are produced in comparative charts covering 6 key considerations including the rates of plastic consumption, waste to landfill, diversion, recycling, relative accumulative cost and effort. The findings of this study pointed out that Victoria’s current plan are feasible for its goal and presented with opportunities for improvement especially towards zero plastic waste. Besides, study results also reveal that the Victoria’s current plan to achieve 80% diversion rate by 2030 is possible but the zero plastic waste target by 2035 is less likely to happen.

As mental health problems tend to increase during adolescence and is a serious public health issue in the Republic of Kazakhstan. Early detection is necessary and monitoring at the population level can be used to evaluate the progress of national programmes promoting positive well-being. Physical activity (PA) can be protective whereas increased screen time behaviours (STB) can be a risk for low levels of well-being. A national representative sample (n=4,731) of young adolescents aged 11y, 13y, and 15y from the Republic of Kazakhstan took part in the WHO collaborative Health Behaviour in School-aged Children (HBSC) study. Respondents completed the WHO-5 Well-being scale, and items in on PA and STB. Internationally recognised, recommended cut-offs were used for analyses. Two models of binary logistic regressions were performed to examine the associations with PA (Model 1) and PA with STB (Model 2) after stratification by gender and controlling for age, locality and family affluence. Three quarters of young adolescents in the Republic of Kazakhstan have good overall well-being, despite the proportion reduces as adolescents age from 11y to 15y (boys, OR=0.66 CI=0.49-0.80; girls, OR=0.55, CI=0.43-0.71). The odds ratio for positive well-being were more than twice for boys and more than 3.5 for girls who reported daily PA than not being active daily. Spending less time on STB for girls was associated with positive well-being than spending more STB time (OR=1.28, CI=1.04-1.59). Well-being among young adolescents drops dramatically between the ages of 11y and 15y and is higher among rural schools attendees than in urban schools. The recommended amounts of PA can be protective of low well-being for both boys and girls. However, meeting reporting STB recommendations was only protective for girls and not boys. Designing and implementing positive well-being programmes require consideration of locality and amounts of PA and STB

G protein-coupled receptors (GPCRs) are critical drug targets. GPCRs convey signals from the extracellular to the intracellular environment through G proteins. There is evidence that some ligands that bind to the GPCRs activate different downstream signaling pathways. G protein activation or -arrestin biased signaling involves ligands binding to receptors and stabilizing conformations that trigger a specific pathway. Molecular dynamics (MD) simulations are especially valuable for obtaining detailed mechanistic information, including identification of allosteric sites and understanding modulators' interactions between receptors and ligands. Here, we highlight recent simulation studies and methods used to study biased G protein-coupled receptor signaling and their conformational dynamics. We also highlight applications of MD simulations to drug discovery.

Views of fire in the contemporary physical sciences arguably accord with Heraclitus’ proposal that ‘all things are an exchange for fire, and fire for all things, as goods for gold and gold for goods.’ Fire is a media, as John Durham Peters has stated, a species of transformative biochemical reactions between the flammable gases found in air, such as oxygen, and those found in fuels, such as plants. Inspired by an ignition source, these materials react and transform themselves and their surrounds into light and heat energy, carbon dioxide, water vapour, char and much else besides. Fire is conjunctural, durational and transformative. Fire is a dialectician, at once consuming living and dead organic matter and providing both the space and ingredients for new and renewed organic life. In this article, we consider the diverse ways in which fire is today framed as a social problem, an ecological process, an ancient tool, a natural disaster, a source of economic wealth and much more. In this way, we seek to explore the value and limits of ‘elemental thinking’ in relation to the planetary predicaments described by ‘the Anthropocene’.

Candida albicans as an opportunistic pathogen exploits the host immune system and causes a variety of life-threatening infections. The polymorphic nature of this fungus gives it tremendous advantage to breach mucosal barriers and cause a variety of oral and disseminated infections. Enterococcus faecalis, another opportunistic pathogen co-exists with C. albicans in several niches in the human body, including the oral cavity and gastrointestinal tract. However, interactions between E. faecalis and C. albicans on oral mucosal surfaces remain unknown. Here, for the first time, we comprehensively characterized the interactive profiles between laboratory and clinical isolates of C. albicans (SC5314 and BF1) and E. faecalis (OG1RF and 846) on an organotypic oral mucosal model. Our results demonstrated that the two species formed robust biofilms on the mucosal tissue surface with profound surface erosion and fungal invasion. Specifically, this effect was more pronounced in the laboratory isolates than in the clinical isolates. Notably, several genes of C. albicans involved in tissue adhesion, hyphal formation, fungal invasion, and biofilm formation were significantly upregulated in the presence of E. faecalis. This study highlights the strain-dependent cross-kingdom interactions between E. faecalis and C. albicans on oral mucosa, demonstrating the requisite to study more substrate-dependent polymicrobial interactions.

Community peer review is a method that extends the ethics of consent into scientific practices. It gives communities affected by scientific research the ability to determine whether research may cause them harm and be part of determining how knowledge should best circulate to reduce or eliminate that harm. This paper introduces the method of community peer review by first looking at the concepts of consent and refusal, then outlining the steps to community peer review, using a case study of community meetings on a study of plastic ingestion by fish to elucidate the details of each step. Steps include: hiring a community member to the team; researching the social, cultural, and economic contexts of the community; identify the community; ensure skills for community conversation are in place; call the community meeting; conduct the community meeting; and analyze feedback for consent and refusal. Community peer review is premised on the idea that research is not inherently good and can cause harm, and that the best people to know whether and what kinds of harms are likely to occur are community members rather than researchers. The second premise is that the researcher’s “right” to research never supersedes a community’s right to not be harmed.

In this paper, possibilities for the bandwidth and wavelength utilization in future next-generation passive optical networks are presented and reasons for realizing and utilizing of extended dynamic wavelength and bandwidth algorithms for NG-PON2 networks are analyzed. Next, principles of the effective dynamic bandwidth allocation are introduced in details, focused on the importance of the decision criterion optimization. For achieving better bandwidth utilization of dedicated wavelengths, this paper is focused on the novel effective dynamic bandwidth allocation algorithm with adaptive allocation of wavelengths to ONU units and on the optimization of the decision criterion. For analyzing the novel extended DWBA algorithm utilizing for various wavelength allocation cases possible in NG-PON2 networks, a simulation program with the enhancement of the EDBA algorithm is realized. Finally, an optimization of the decision criterion defining a minimum bandwidth utilization of the actual wavelength is executed for NG-PON2 networks based on the hybrid TWDM technique.

Because of an often complicated and difficult-to-access care system, help-seeking for people with suspected dementia can be stressful. Difficulty in help-seeking may contribute to carer burden, in addition to other known stressors in dementia care. This study examined the relationship between perceived help-seeking difficulty and carer burden, and the barriers contributing to perceived difficulty. We interviewed 110 carers accessing a community-based dementia assessment service for suspected dementia of a family member for their perceived difficulty, delays, and barriers in help-seeking, and carers burden in terms of role strain, self-criticism, and negative emotions. Linear regression models showed that perceived help-seeking difficulty is associated with carer self-criticism, while carer role strain and negative emotions are associated with symptom severity of the person with dementia but not help-seeking difficulty. Inadequate knowledge about symptoms, service accessibility, and affordability together explained more than half of the variance in perceived help-seeking difficulty (Nagelkerke R2 = .56). Public awareness about symptoms, support in navigating service, and financial support may reduce perceived difficulty in help-seeking, which in turn may reduce carer self-criticism during the early course of illness.

Background: Advances in additive manufacturing and the development of antimicrobial biopolymers facilitate the production of critical medical devices with strong and safe biocidal properties. The purpose of this study was to assess the antimicrobial efficacy, safety, and longevity of a polylactic acid-based biopolymer supplemented with a copper-based composite additive. Methods: An antimicrobial polylactic acid-based biopolymer was tested against several inoculants including Staphylococcus Aureus, MRSA, E. coli, Listeria, HCoV-229E (a SARS-CoV-2 surrogate), and HIV-1. Material safety was evaluated according to international testing standards for in vitro cytotoxicity. Results: The main findings of the present investigation showed a strong and long-lasting biocidal effect of a polylactic acid-based biopolymer embedded with a copper-based composite additive against Staphylococcus Aureus, MRSA, E. coli, Listeria, HCoV-229E (a SARS-CoV-2 surrogate), and HIV-1. Furthermore, the cytotoxicity and safety assessment of the antimicrobial biopolymer was found to be “non-toxic” and safe for human skin contact. Conclusions: The present investigation showed that the antimicrobial biopolymer exhibits strong and long-lasting biocidal properties against an array of viral and bacterial inoculants.

Beta-carotene is a fat-soluble antioxidant commonly found in foods such as fruits, vegetables, and palm oil. Despite various liquid chromatography methods are proposed to detect and measure the sera carotenoid level, a long retention time to elute this marker is needed. This study attempted to develop a rapid reverse phase method in eluding beta-carotene in human sera. The researchers managed to elute the antioxidant in 2.2 minutes by applying a combination of a C8 column, mobile phase comprising of acetonitrile mixed with methanol in 70:30 proportion, and an ultra-high performance liquid chromatography system. The outputs had a good calibration curve (R²=0.959) and low coefficient of variation (0.2%), suggesting this protocol is reliable. A column with a lower carbon chain such as C8 allows the beta-carotene molecule to flow through the column faster. Besides, selecting solvents with high elution strength coupled with an ultra-high performance liquid chromatography system which equipped with high pressure can force the beta-carotene through the column in a shorter duration compared to previous reported methods. Therefore, it is recommended to adopt this protocol in epidemiological studies where beta-carotene is screened as a dietary biomarker associated with disease of interest by using human sera in the population level.

Ventilation in cities is crucial for the well being of their inhabitants. Therefore, local governments require air ventilation assessments (AVAs) prior to the construction of new buildings. In a standard AVA, however, only neutral stratification is considered, although diabatic and particularly unstable conditions may be observed more frequently in nature. The results presented here indicate significant changes in ventilation within most of the area of Kowloon City, Hong Kong, included in the study. A new definition for calculating ventilation was introduced, and used to compare the influence of buildings on ventilation under conditions of neutral and unstable stratification. The overall ventilation increased due to enhanced vertical mixing. In the vicinity of exposed buildings, however, ventilation was weaker for unstable stratification than for neutral stratification. The influence on ventilation by building parameters, such as the plan area index, was altered when unstable stratification was considered. Consequently, differences in stratification were shown to have marked effects on ventilation estimates, which should be taken into consideration in future AVAs.

This research investigates the implementation of complex exponential-based neurons in FPGA, which can pave the way for implementing bio-inspired spiking neural networks to compensate for the existing computational constraints in conventional artificial neural networks. The increasing use of extensive neural networks and the complexity of models in handling big data lead to higher power consumption and delays. Hence, finding solutions to reduce computational complexity is crucial for addressing power consumption challenges. The complex exponential form effectively encodes oscillating features like frequency, amplitude, and phase shift, streamlining the demanding calculations typical of conventional artificial neurons through levering simple phase addition of complex exponential functions. The article implements such a two-neuron and a multi-neuron neural model using Xilinx system generator and Vivado design suite, employing 8-bit, 16-bit, and 32-bit fixed-point data format representations. The study evaluates the accuracy of the proposed neuron model across different FPGA implementations while also providing a detailed analysis of operating frequency, power consumption, and resource usage for the hardware implementations. BRAM-based Vivado designs outperformed Simulink regarding speed, power, and resource efficiency. Specifically, the Vivado BRAM-based approach supported up to 128 neurons, showcasing optimal LUT and FF resource utilization. Such outcomes accommodate choosing the optimal design procedure for implementing spiking neural networks on FPGAs.

The power system has rapidly grown and expanded over the past decades and has been experiencing major changes and challenges. The increase in energy demand and the modern advancements in the smart grid, such as solar and wind energies and electric vehicles, have led to complexity and complications for utilities. A further layer of complexity and difficulty was added by the rapid expansion of behind-the-meter (BTM) photovoltaic (PV) systems with various designs and characteristic features. The rapid increase and the invisible solar power (BTM) have led to fluctuations in power grid stability and reliability and to inefficiency. Accurate forecasting of load generation will help to assure optimal planning, minimize the negative effects of the PV systems, and minimize the operational and maintenance costs. The authors propose a solution that uses combinations of K-means clustering with neural network machine learning models, AMI real-world PV load generation, and weather data to forecast the generation load at customer locations to achieve a 2.49% error between actual and predicted generation load.

Grill-specific footprints for common fuels/grill types in the USA are estimated from public information and data from a major grill manufacturer. These are a function of both 1) a fuel’s footprint and 2) a grill’s efficiency of cooking. In 2022, grill-specific footprints vary by 9:1. A typical gas grill is highest at 3.6 lb CO2e/grill session, nine times that of a wood-pellet grill, lowest at 0.4 lb. Charcoal briquettes, electricity and super-efficient gas grills come in-between. Pellets are lowest, because they are made from waste wood and their production burden is modest. Electricity has the highest fuel footprint, yet the second-lowest grill-specific footprint, thanks to its high efficiency. Briquettes come in fourth, because their production involves fossil gas, and they contain some fossil coal. Grill efficiency is key for gas (natural gas or propane): a typical gas grill has twice the footprint of a super-efficient one. In 2027, with bio substitution, the super-efficient gas grill would move ahead of pellets. Electricity and charcoal could improve but would still place fifth and sixth. The range of grill-specific footprints could fall to 4.5:1, within a much-lower range, the highest footprint in 2027 almost 60% lower than 2022’s highest.

The late universe contains a wealth of information about fundamental physics and gravity, wrapped up in non-Gaussian fields. To make use of as much information as possible it is necessary to go beyond two-point statistics. Rather than going to higher order N-point correlation functions, we demonstrate that the probability distribution function (PDF) of spheres in the matter field (a one-point function) already contains a significant amount of this non-Gaussian information. The matter PDF dissects different density environments which are lumped together in two-point statistics, making it particularly useful for probing modifications of gravity or expansion history. Our approach in Cataneo et. al. 2021 extends the success of Large Deviation Theory for predicting the matter PDF in ΛCDM in these “extended” cosmologies. A Fisher forecast demonstrates the information content in the matter PDF via constraints for a Euclid-like survey volume combining the 3D matter PDF with the 3D matter power spectrum. Adding the matter PDF halves the uncertainties on parameters in an evolving dark energy model, relative to the power spectrum alone. Additionally, the matter PDF contains enough non-linear information to substantially increase the detection significance of departures from General Relativity, with improvements up to six times the power spectrum alone. This analysis demonstrates that the matter PDF is a promising non-Gaussian statistic for extracting cosmological information, particularly for beyond ΛCDM models.

Here we introduce Literature Mapper, a Python QGIS plugin that provides a method for creating a spatial bibliography manager as well as a specification for storing spatial data in a bibliography manager. Literature Mapper uses QGIS’ spatial capabilities to allow users to add location information to a Zotero library, a free and open source bibliography manager. Literature Mapper enhances the citations in a user’s online Zotero database with geo-locations by storing spatial coordinates as part of traditional citation entries. Literature Mapper receives data from and sends data to the user’s online database via Zotero’s web API. By using Zotero as the backend data storage, Literature Mapper benefits from all of its features including shared citation Collections, public sharing, and an open web API usable by additional applications, such as web mapping libraries. We evaluate Literature Mapper’s ability to provide insights into the spatial distribution of published literature by mapping the study sites described in academic publications related to California’s coastal strand vegetation. The results of this exercise are presented in static and web map form.

Lanthanide ion doped upconversion nanoparticles (UCNPs) that can convert low-energy infrared photons into high-energy visible and ultraviolet photons, are becoming highly sought-after for advanced biomedical and biophotonics applications. Their unique luminescent properties enable UCNPs to be applied for diagnosis, including biolabeling, biosensing, bioimaging and multiple imaging modality, as well as therapeutic treatments including photothermal and photodynamic therapy, bio-reductive chemotherapy and drug delivery. For the employment of the inorganic nanomaterials into biological environment, it is critical to bridge the gap in between nanoparticles and biomolecules via surface modifications and subsequent functionalisation. This work reviews the various ways to surface modify and functionalise UCNPs so as to impart different functional molecular groups to the UCNPs surfaces for a board range of applications in biomedical areas. We discussed commonly used base functionalities, including –COOH, -NH2 and –SH, that are typically imparted to UCNP surfaces so as to provide further functional capacity.

A novel physiologically based algorithm (PBA) for the computation of fractional flow reserve (FFR) in coronary artery trees (CATs) using computational fluid dynamics (CFD) is proposed and developed. The PBA is based on the extension of Murray's law and additional inlet conditions prescribed iteratively, and is implemented in OpenFOAM for testing and validation. 3D models of CATs are created using CT scans and computational meshes, and the results are compared to in-vasive coronary angiographic (ICA) data to validate the accuracy and effectiveness of the PBA. The discrepancy between calculated and experimental FFR is within 2.33-5.26% in steady-state and transient simulations, respectively, when convergence is reached. The PBA is a reliable and physiologically sound technique compared to the current lumped parameter model (LPM), which is based on empirical scaling correlations and requires nonlinear iterative computing for conver-gence. The accuracy of the PBA method is further confirmed using the FDA nozzle, which demonstrates good alignment with CFD-validated values.

Background: Neurological disorders are the leading cause disability in Australia and the world. Combating the perceived difficulty of neurology or “neurophobia” and improving physician education is a key component in addressing this problem. We aim to conduct the first study to identify whether neurophobia exists in medical students and junior doctors in an Australian population and try to identify factors that may contribute to this in this population. Methods: A 24 question online validated survey was distributed via email broadcast to all medical students and junior doctors at a metropolitan tertiary care centre in Australia. Responses were collected over 6 weeks with weekly reminder emails for 4 weeks after the initial invitation email. Results: 114 medical students and junior doctors participated in the study. Participants perceived neurology as the most difficult medical speciality compared to 10 other medical specialties (p=0.001). The top three factors contributing to this perceived difficulty were: a lack of understanding of neuroanatomy, lack of diagnostic certainty and lack of clinical exposure. 65% of the participants stated that they had too little planned teaching in neurology with only 36% of the participants having performed a neurology rotation during medical school. Conclusion: The prevalence of neurophobia in this Australian cohort of medical students and junior doctors is consistent with previous findings from around the world. This concerning finding requires further examination into the contributing factors in order to created trials of targeted interventions in order to resolve this.

3D-mapping-aided (3DMA) global navigation satellite system (GNSS) positioning that improves positioning performance in dense urban areas has been under development in the recent years, but it still faces many challenges. This paper details a new algorithm that explores the potential of using building boundary for positioning. Rather than applying complex simulations to analyze and correct signal reflections by buildings, the approach utilizes a convolutional neural network to differentiate between the sky and building in a sky-pointing fisheye image. A new skymask matching algorithm is then proposed to match the segmented fisheye images with skymasks generated from a 3D building model. Each matched skymask holds a latitude and longitude coordinate to determine the precise location of the fisheye image. The results are then compared with the conventional GNSS and advanced 3DMA GNSS positioning methods. The aims of the proposed algorithm are to increase positioning and heading accuracy in a rich urban environment.

Increased soluble endoglin (sENG) were observed in human brain arteriovenous malformations (bAVMs), and overexpression of sENG with vascular endothelial growth factor (VEGF)-A induced dysplastic vessel formation in mouse brain. However, the underlying mechanism of sENG-induced vascular malformations is not clear. While evidence suggests the role of sENG as a pro-inflammatory modulator, increased microglial accumulation and inflammations were observed in bAVMs. Therefore, we hypothesized that microglia mediate sENG-induced inflammation and endothelial cell (EC) dysfunction in bAVMs. In this study, we confirmed that sENG with VEGF-A overexpression induced dysplastic vessel formation. Remarkably, there were increased microglial activation around dysplastic vessels with expression of NLRP3, inflammasome marker. We found that sENG increased the gene expression of VEGF-A, pro-inflammatory cytokines/inflammasome mediators (TNF-α, IL-6, NLRP3, ASC, Caspase-1, and IL-1β), and proteolytic enzyme (MMP-9) in BV2 microglia. The conditioned media from sENG-treated BV2 (BV2-sENG-CM) significantly increased angiogenic factors (Notch-1 and TGFβ) and pERK1/2 in ECs while it decreased IL-17RD, an anti-angiogenic mediator. Finally, the BV2-sENG-CM significantly increased EC migration and tube formation. Together, our study demonstrates that sENG provokes microglia to release angiogenic/inflammatory responses which may be involved in EC dysfunction. Our study suggests the contribution of microglia in the pathology of sENG-associated vascular malformations.

Food insecurity is a pervasive issue for Allegheny County as one in five residents experience food insecurity. Food insecurity is linked to chronic health conditions like heart disease and hypertension and disproportionately affects women in the United States, particularly women who are head of household. There are multiple dimensions used to measure regional food insecurity, one of which is food accessibility. Prior research has examined the linkages between food access and food insecurity, and this study aims to further explore the relationship between equitable access to sustainable food and levels of regional food insecurity. This study examines food outlets in Allegheny County to determine if there is a significant relationship between food outlet availability and food insecurity. Both the presence and accessibility of these food outlets were examined. To measure accessibility, the walking distance to the nearest public transportation stop was calculated for each public transportation stop. The minimum distance to each food outlet was compared to food insecurity rates on a Census Tract level. Results showed that communities without grocery stores did, on average, have higher rates of food insecurity. Also, communities with a higher proportion of female-headed households experienced greater food insecurity, regardless of access to food outlets. However, there was no statistically significant relationship between the distance from public transportation stops to grocery stores and rates of food insecurity. Based on these findings, we suggest that sole reliance on distance as an indicator of food insecurity can be misleading, and there should be a greater focus on walkability within the community as using opposed to physical distance alone.

Human ether-a-go-go-related gene (hERG) potassium channel is well-known contributor to drug-induced cardiotoxicity and therefore an extremely important target when performing safety assessments of drug candidates. Ligand-based approaches in connection with quantitative structure active relationships (QSAR) analyses have been developed to predict hERG toxicity. Availability of the recent published cryogenic electron microscopy (cryo-EM) structure for the hERG channel opened the prospect for using structure-based simulation and docking approaches for hERG drug liability predictions. In recent time, the idea of combining structure- and ligand-based approaches for modeling hERG drug liability has gained momentum offering improvements in predictability when compared to ligand-based QSAR practices alone. The present article demonstrates uniting the structure-based SILCS (site-identification by ligand competitive saturation) approach in conjunction with physicochemical properties to develop predictive models for hERG blockade. This combination leads to improved model predictability based on Pearson’s R and percent correct (represents rank-ordering of ligands) metric for different validation sets of hERG blockers involving diverse chemical scaffold and wide range of pIC50 values. The inclusion of the SILCS structure-based approach allows determination of the hERG region to which compounds bind and the contribution of different chemical moieties in the compounds to blockade, thereby facilitating the rational ligand design to minimize hERG liability.

Cognitive scientists have paid very little attention to magic as a distinctly human activity capable of creating situations or events that are considered impossible because they violate expectations and conclude with the apparent transgression of well-established cognitive and natural laws. And even though magic techniques appeal to all known cognitive processes from sensing, attention and perception to memory and decision making, the relation between science and magic has so far been mostly unidirectional, with the primary goal of unraveling how magic works. Building up from the deconstruction of a classic magic trick, we provide here a cognitive foundation for the use of magic as a unique and largely untapped research tool to dissect cognitive processes in tasks arguably more natural than those usually exploited in artificial laboratory settings. Magicians can submerge every spectator into the precise experimental protocol they have previously designed, accounting with ease for both circumstantial and social contexts. Magicians do not base the success of their experiments in statistical measures that smear out the individual in favor of an average spectator that we know never exists in the real world. They target each and everyone in the audience and, often, with a complete accomplishment. Magicians deliver their cognitive manipulations in real-time, in tight closed-loop with the audience, and in a single trial (they cannot afford to repeat the trick if it fails). Magic has also an inherent and strong social component, merging the private cognitive processes of each spectator with the group dynamics. Finally, when combined with the wide range of precise measuring and wearable technologies available today, magic paves the way for a road not taken towards real-world cognitive science. We dare to speculate that some of the mysteries of how the brain works may be trapped in the split realities present in each magic effect.

We examine the nonequilibrium production of topological defects -- braids -- in semiflexible filament bundles under cycles of compression and tension. During these cycles, the period of compression facilitates the thermally activated pair production of braid/anti-braid pairs, which then may separate when the bundle is under tension. As result, appropriately tuned alternating periods of compression and extension should lead to the proliferation of braid defects in a bundle so that linear density of these pairs far exceeds that expected in thermal equilibrium. Secondly, we examine the slow extension of braided bundles under tension, showing that their end-to-end length creeps nonmonotonically under a fixed force due to braid deformation and the motion of the braid pair along the bundle. We conclude with a few speculations regarding experiments on semiflexible filament bundles and their networks.

The universal Debye – Mayer – Kelly hybrid model was proposed for the description of the heat capacity from 0 K to the melting points of substance within the experimental uncertainty for the first time. To describe the heat capacity, the in-house software on the base of commercial one DELPHI-7 was used with a 95% confidence level. To demonstrate the perfect suitability of this model, a thermodynamic analysis of the heat capacities of the fourth group elements, and some compounds of the A^IIIB^V and A^IIB^VI phases was carried out. It produced good agreement within the experimental uncertainty. There is no a similar model description in literature.The Similarity Method is a convenient and effective tool for critical analysis of the heat capacities of isostructural phases, which was used as an example for diamond-like compounds. Phases with the same sum of the atomic numbers of elements (Z), such as diamond and B_0.5 N_{0.5 (cub)} (Z = 6); pure silicon (Si) and Al_0.5 P_0.5 (Z=14); pure germanium (Ge) and Ga_0.5 As_0.5 (Z = 32)); pure grey tin (alpha-Sn) and In_0.5 Sb_0.5, and Cd_0.5 Te_0.5 (Z = 50) have the same heat capacity experimental values in the solid state. The proposed models can be used to both different binary and multicomponent phases. It helps to standardize the physicochemical constants.

Immune complexes (ICs) made of antibody-bound antigens exhibit immunomodulatory activities exploitable in a vaccination strategy to optimize vaccine efficacy. The modulatory effects of ICs are typically attributed to the Fc fragments of the antibody components, which engage Fc receptors, complement and complement receptors on various immune cells. These Fc-mediated functions facilitate the critical interplay between innate and adaptive immune systems to impact the quality and quantity of the elicited adaptive responses. In addition to the Fc contribution, the Fab fragment also plays an immunoregulation role. The antigen-binding domains of the Fab fragment can bind their specific epitopes at high affinity to sterically occlude these antigenic sites from recognition by other antibodies. Moreover, the Fab-mediated binding have been demonstrated to induce allosteric alterations at nearby or distant antigenic sites. In this review article, we survey published studies to illuminate how the immunomodulatory functions of ICs have been investigated or utilized in a vaccination strategy to fight against an array of infectious pathogens, culminating with IC vaccine designs aimed at preventing HIV-1 infection. In particular, we highlight IC vaccine candidates that exploit Fab-mediated steric and allosteric effects to direct antibody responses away or toward the V1V2 domain, the V3 loop, and other antigenic sites on the HIV-1 envelope gp120 glycoprotein. Like other HIV-1 vaccine approaches, the path for IC-based vaccines to reach the clinic faces major hurdles yet to be overcome; however, investigations into this vaccine strategy have provided insights into the multifaceted activities of antibodies beyond their conventional roles in the host defense against HIV-1 and other microbial pathogens.

Determining disability prevalence is an important area for population statistics, especially among young adolescents. The Washington Group on Disability Statistics is one source of reporting disabilities through functional difficulties. However, young adolescents self-reporting this measure is in its infancy. The purpose of this study was to carry out an intra-rater test-retest reliability study on a modified set of items for self-reporting functional difficulties. Young adolescents (n=74; boys=64%; age m=13.7, SD=1.8) completed a self-reported version of the child functioning module in a supervised classroom. The second administration took place two weeks later. Intraclass correlation coefficient (ICC) and Kappa (k) statistics were used to test reliability of the items, and interpretation through Landis &amp; Koch, and Cohen, respectively. The majority of items had substantial or moderate agreement, although there was only fair agreement for self-care (ICC=0.59), concentration (ICC=0.50), and routine (ICC=0.54). Kappa statistics of behaviour were interpreted to be large (k=0.65), and seeing (k=0.49), walking (k=0.49), and speaking (k=0.49) difficulties were moderate. The majority of the items in the self-reported version of the child functioning module can be used in a scale format, although some caution may be required on items of self-care and concentration when used as a dichotomous variable.

The development and qualification of CrAlN coatings deposited by DC magnetron sputtering offer new industrial solutions to increase the lifecycle of material forming tools (machining and shaping). This study focuses on the selection and optimization of deposition modes for CrAlN layers to be deposited on a 90CrMoV8 tool steel substrate. The adopted methodology aims to optimize the deposition conditions to meet the customer's requirement of a CrAlN coating thickness of approximately 2-3 µm for use in a hot forming process. Different polarizations using two Al and Cr targets, with both stationary and rotating substrate modes during deposition, were tested and evaluated. Characterizations of the CrAlN coating layers (microhardness, residual stress, structures) and performance in service (wear, friction, adhesion, corrosion) were chosen as selection criteria for a particular coating mode. The aluminum content plays a crucial role in the tribological and mechanical behavior of CrAlN layers. Corrosion resistance is more sensitive to the aluminum content for the stationary deposition mode. As a result, the rotating mode provides higher adhesion (+100%) and less wear (-60%) compared to the stationary mode. Therefore, depending on the likely performance in service, either a stationary or rotating mode could be applied for coating the functional surfaces of hot forming tools.

Background: Disorders of immunity are poorly recognised in some rare multisystem genetic con-ditions. We aim to describe syndromic features and immunological defects in children with syn-dromic primary immunodeficiencies (sPIDs). Methods: This is a retrospective descriptive study of children aged 0-18 years with sPIDs under the care of the paediatric immunology service at the Bristol Royal Hospital for Children, United Kingdom from January 2006 to September 2021. Results: sPIDs were identified in 36 patients. Genetic diagnoses which are not commonly associ-ated with PIDs and not included in the International Union of Immunological Societies classifica-tion were present in 7/36 (19%): Trisomy 22, Arboleda-Tham syndrome, 2p16.3 deletion syn-drome, supernumerary ring chromosome 20 syndrome, Myhre syndrome, Noonan syndrome, trichothiodystrophy/Cockayne syndrome complex. Recurrent and/or severe infections were the commonest clinical features (n=33, 92%). Approximately half had combined immunodeficiency or antibody deficiency. Commonest extra-immunological manifestations include dysmorphism (72%), disorders of nervous (78%), musculoskeletal (69%), haematology/lymphatic (58%), and gastrointestinal, hepatic/pancreatic (58%) systems. Conclusions: Patients with sPIDs often have multiorgan involvement and some are non-immunologically mediated. There should be low threshold to clinically assess and investi-gate for disorders of immunity in any patients with syndromic features especially when they pre-sent with recurrent/severe/opportunistic infections, features of immune dysregulation, autoin-flammation or lymphoproliferation.

This study assesses Human Thermal Comfort in two selected areas: a Green Infrastructure (GI) area represented by a garden and a high-rise building area, in the Central Business District (CBD) of Melbourne, Australia. Three-dimensional microclimatic modelling software, ENVI-met version 4 was used to simulate the microclimate. The indices of Predicted Mean Vote (PMV), Physiological Equivalent Temperature (PET) and Universal Temperature Climate Index (UTCI) were used to quantify the level of thermal comfort in the research areas. The simulation results showed that at midday, the difference in temperature between the garden area and the high-rise building area was approximately 1°C. Increasing temperatures at midday led to a change in the level of thermal comfort for both the areas, even though it was not significant. In general, the thermal perception in the GI area was slightly ‘cooler’ than in the high-rise building area. The results of the study indicated the important role of GI in improving the thermal comfort in urban areas.

Isotopic stable analysis (SIA) is a powerful tool in the assessment of different types of ecological and physiological studies. For that, different preservative methods for the samples are commonly used prior to isotopic analysis. The effects of various preservative methods (drying, freezing, ethanol and formaldehyde) have been analyzed for C:N ratio, δ13C and δ15N on a variety of tissues including dorsal fins (three seahorse and two pipefish species), seahorse newborns (three seahorses species), and prey (copepods and different stages of Artemia) commonly used to feed the fishes in rearing conditions. The aims of the study were to: (i) evaluate isotopic effects of preservation methods across tissues; and (ii) construct the first conversion models available in syngnathid fishes. The preservation in ethanol and to a lesser extend in formaldehyde significantly affected δ13C values, whereas δ15N signatures were not affected significantly. Due to their low lipid content, the isotopic signals in fish fins were almost unaffected, supporting the suitability of dorsal fins as a convenient tool in isotopic studies on vulnerable species such as syngnathids. The regression equations provided permit the successful conversion of δ13C and δ15N values between preservative treatments. The conversion models can be applied to isotopic studies in the field and in the laboratory.

Angiogenesis is a critical physiological response to ischemia but becomes pathological when dysregulated and driven excessively by inflammation. We recently identified a novel angiogenic role for tripartite-motif-containing protein 2 (TRIM2) whereby lentiviral shRNA-mediated TRIM2 knockdown impaired endothelial angiogenic functions in vitro. This study sought to determine whether these effects could be translated in vivo and to determine the molecular mechanisms involved. CRISPR/Cas9-generated Trim2–/– mice that underwent a periarterial collar model of inflammation-induced angiogenesis exhibited significantly less adventitial macrophage infiltration relative to wildtype (WT) littermates, concomitant with decreased mRNA expression of macrophage marker Cd68 and reduced adventitial proliferating neovessels. Mechanistically, TRIM2 knockdown in endothelial cells in vitro attenuated inflammation-driven induction of critical angiogenic mediators, including nuclear HIF-1α, and curbed the phosphorylation of downstream effector eNOS. Conversely, in a hindlimb ischemia model of hypoxia-mediated angiogenesis, there were no differences in blood flow reperfusion to the ischemic hindlimbs of Trim2–/– and WT mice despite a decrease in proliferating neovessels and arterioles. TRIM2 knockdown in vitro attenuated hypoxia-driven induction of nuclear HIF-1α but had no further downstream effects on other angiogenic proteins. Our study has implications for understanding the role of TRIM2 in the regulation of angiogenesis in both pathophysiological contexts.

A university canteen is a queueing system characterised by non-stationary time of arrival with limited resources where the arrival rate is time dependent and has different pattern of arrival for different time interval. This means at certain time of the day, the arrival rate is much higher than other time and for a university canteen, the arrival rate of customer during the lunchtime is much higher and the food (resources) is limited. Non-stationary time dependent queueing system is not easily modelled mathematically hence such queueing systems are modelled using simulation tools such as ARENA. In order to model a non-stationary time dependent queueing system with limited resources and solve queueing problems using ARENA, researchers have to depend on their knowledge and experience in identifying the appropriate and relevant parameters for the system and make modifications to these parameters of the system to solve queueing problems by means of trial and error. Hence, this research work explores the potentials of applying a systematic problem solving tool, TRIZ to help users to make better decisions in deriving solutions to improve a non-stationary time dependent queueing system with limited resources. A case study was carried out to minimize the waiting time of the customers at the cafeteria of the Faculty of Engineering, Universiti Putra Malaysia (UPM), which has queueing problems for years during lunchtime. TRIZ was applied in this case study and the results showed that TRIZ can assist researchers to derive a solution model that lead to shorter waiting time without incurring additional cost and resources.

The Agile Building Adaptation (AgiBuild) framework is the adoption and adaptation of the large-scale agile framework for building adaptation projects. The agile methodology is proven to drive innovation by focusing on adaptation to change and user centricity. Similarly, the authors envision that the AgiBuild framework can fundamentally change the way that buildings are re-designed, refurbished, and operated. The AgiBuild framework is developed from the need of the building adaptation industry to manage uncertainties, overcome communication barriers, and improve innovation. In this study, a literature review of Agile and its impact on building adaptation projects is undertaken. Based on this systematic literature review, this paper defines the AgiBuilt framework and provides its benefits and barriers to implementation. A key finding of the literature review is that leadership influence, and adequate training form the key foundation for the implementation of the AgiBuild Framework. In defining the AgiBuild framework, the paper describes its components and how its implementation is likely to proceed. The authors propose that by adopting the AgiBuild framework, the industry can transform itself into a highly innovative and user-centred industry to improve productivity and performance of the construction industry..

The provenance of the aminoacyl-tRNA synthetases (aaRS) poses challenging questions because of their role in the emergence and evolution of genetic coding. We investigate evidence about their ancestry from curated structure-based multiple sequence alignments of a structurally invariant “scaffold” shared by all 10 canonical Class I aaRS. Three uncorrelated phylogenetic metrics—residue-by-residue conservation, its variance, and row-by-row cladistic congruence—imply that the Class I scaffold is a mosaic assembled from distinct, successive genetic sources. These data are especially significant in light of: (i) experimental fragmentations of the Class I scaffold into three partitions that retain catalytic activities in proportion to their length; and (ii) evidence that two of these partitions arose from an ancestral Class I aaRS gene encoding a Class II ancestor in frame on the opposite strand. Phylogenetic metrics of different modules vary in accordance with their presumed functionality. A 46-residue Class I “protozyme” roots the Class I molecular tree prior to the adaptive radiation of the Rossmann dinucleotide binding fold that refined substrate discrimination. Such rooting is consistent with near simultaneous emergence of genetic coding and the origin of the proteome, resolving a conundrum posed by previous inferences that Class I aaRS evolved long after the genetic code had been implemented in an RNA world. Further, pinpointing discontinuous enhancements of aaRS fidelity establishes a timeline for the growth of coding from a binary amino acid alphabet.

Vision impairment may delay responses to hazards when driving. In a proof-of-concept driving simulator study, we evaluated a hazard warning device designed for vision impaired drivers. Three groups participated: 11 persons with central vision loss (CVL; median age 60 years), 12 with homonymous field loss (HFL; 52 years) and 11 with normal vision (NV; 60 years). CVL is characterised by impaired visual acuity and contrast sensitivity while HFL is a loss of vision in the same half of the visual field (blind side) in both eyes. Participants completed drives with and without the device which gave a directional vibro-tactile warning for an approaching pedestrian hazard when collision risk exceeded a pre-defined threshold. Warnings significantly (p< 0.001) reduced brake response times for CVL (∆= 0.54s) and HFL (∆= 0.30s), but not NV participants. For HFL participants, the reduction was greater (p = 0.02) for hazards on the blind (∆= 0.57s) than seeing side (∆= 0.10s). The warnings significantly reduced collision rates for CVL participants from 11 to 0% (all hazards) and for HFL participants from 30 to 1.7% (blind side hazards). Thus, hazard warnings may be beneficial in improving safety of vision impaired drivers; further research is warranted.

More than 179,000 individuals have fallen ill of the Coronavirus disease (COVID-19) caused by the SARS-CoV-2 virus, which first emerged in China less than four months ago in December 2019. As of today, there exist no approved treatments against COVID-19. Vaccines are being developed, but they will take time, at least one year, to reach the population. Drug repositioning represents a fast track because already approved medicines have been broadly tested through multiple trials. We developed a repositioning strategy that mostly leads to candidates that are commonly used. The advantages are that they will facilitate proof of concept in humans through a “real-world evidence” approach and should be rapidly available to the population. We focus on the established research results that the unfolded protein response (UPR) and autophagy pathways of the host cells are essential to the life cycle of previously known coronaviruses. We performed the relevant bioinformatics analysis to understand and confirm if SARS-CoV-2 may interact with these druggable pathways. Based on these considerations, we prioritized two additional druggable pathways, which are important to the viral life cycle and tightly connected to UPR/autophagy signaling: the mitochondrial permeability transition pores (MPTP) and NLRP-3 inflammasome pathways. These four important pathways are perturbed in most major common diseases and have therefore been targeted by numerous broadly prescribed drugs. We have identified 97 approved drugs that are known to modulate these four identified pathways, and which represent, therefore, interesting repositioning candidates. Although it is indisputable that these drugs should never be used for immediate self-medication against COVID-19, we notice that some of them could also be prescribed to individuals who have COVID-19 comorbidities (e.g., hypertension). It is debated if these comorbidities are linked to the pathology itself (e.g., hypertension) or the drugs used to treat the pathology (e.g., sartans). Therefore, relevant preclinical tests and massive electronic health records (i.e., real-world evidence) must be used to pre-screen them and check the COVID-19 prognosis of individuals taking these drugs.

Hong Kong is the biggest consumer of eggs in the world and ranks on the top with an average consumption of 24.52kg/capita/year. The egg consumption trend in Hong Kong has been increasing specifically; a drastic increase of about 100% has been observed from 2008 to 2020. One of the reasons behind this significant increase is the increase in the gross national income of Hong Kong in addition to the population growth rate. However, there was a slight decline in egg consumption trend in the year 2020 amid the COVID-19 pandemic. It has been estimated that there was a bulk of 17,100 tons of recoverable waste eggshells in 2019 (pre-COVID-19 situation), having a daily yield of 47 tons per day. Based on the linear regression, it may be expected that if the pre-COVID-19 trend of egg consumption remains sustained, there will be a big bulk of more than 45,000 tons per year and up to 125 tons per day of waste eggshells till 2050. In addition, a public survey was conducted across the city targeting individuals, families, and restaurants majorly on egg consumption and reuse. The survey outcomes revealed that Chinese eggs have an extensive market in Hong Kong, and people have a positive attitude towards eggshell recycling. Also, a massive population disposes of the waste eggshells while only a trace population reuses them. Therefore, Hong Kong has a very high potential to improve the circular economy by reusing waste eggshells on a commercial level in cementitious products.

Accurate localization of road agents is the basis of intelligent transportation systems, which is still difficult to achieve for GNSS positioning in urban areas due to the signal interferences from buildings. Various collaborative positioning techniques are recently developed to improve the positioning performance by the aid from neighboring agents. However, it is still challenging to study their performances comprehensively. The GNSS measurement error behavior is complicated in urban areas and unable to be represented by naive models. On the other hand, real experiment requiring numbers of devices is hard to be conducted, especially for a large-scale test. Therefore, a GNSS realistic urban measurement simulator is developed to provide measurements for collaborative positioning studies. The proposed simulator employs a ray-tracing technique searching for all possible interferences in the urban area. Then, it categorizes them into direct, reflected, diffracted, and multipath signal to simulate the pseudorange, carrier-phase, 〖C/N〗_0, and Doppler shift measurements correspondingly. The performance of the proposed simulator is validated through real experimental comparisons with different scenarios. The proposed simulator is also applied with different positioning algorithms, which verifies it is sophisticated enough for the collaborative positioning studies in the urban area.

Nutritional management of depression has long been discussed due to the perceived benefit of a nutritional product having less side effects than pharmaceutical agents. Candidate nutrients for managing depression include Vitamin D, B-vitamins, tryptophan, branch chain amino acids, probiotics, omega-3 fatty acids, folate/methylfolate (aka Vitamin B9), and s-adenosylmethionine. This paper reviews three nutrients which have significant scientific support for the management of depression and have evidence of low levels in subjects with depression, and that correction of the nutritional deficiency provides clinical benefit. We present epidemiological evidence, mechanistic explanation and a review of interventional studies for these nutrients. Finally, relevant nutritional guidelines are presented with their conclusion for the role of each nutrient in the management of depression.

A Physical Unclonable Framework (PUF) is a detached hardware component or, the structural arrangement of hardware that provides natural variations in the physical parts of semiconductor devices to generate unique and unpredictable identifiers based on challenging-to-replicate. In this case, PUFs are giving us a tool to utilise these variations to create an unclonable identifier for your device. PUFs generate a response or a unique pattern based on the physical characteristics of the device, and this response is difficult to predict or duplicate. This study aims to introduce a PUK device to provide security research on the Internet of Things technology. The elliptic curve cryptography algorithm was modified with an advanced equation to calculate a private key and K value. In this study, a PUF device will be employed with a modified elliptic curve cryptography algorithm on a novel security system to be used in current and future communication technology.

In air-breathing proton exchange membrane fuel cells (Air PEM FCs), high rate of water evaporation from the cathode might influence the resistance of the membrane electrode assembly (MEA), which is highly dependent on the water content of the Nafion membrane. We propose a dead-end hydrogen anode as a means of intermediate storage of water/humidity for self-humidification of the membrane. Such inflatable bag integrated with the PEM FC has a potential in blimp applications for anode self-humidification. A dynamic numerical water balance model, validated by experimental measurements, is derived to predict the effect of MEA configuration, membrane’s hydration state, and water transfer rate at the anode on MEA resistance and performance. The experimental setup included humidity measurements, polarization and electrochemical impedance spectroscopy tests to quantify the effect of membrane hydration on its resistance in a lightweight MEA integrated with an inflatable dead-end hydrogen storage bag. Varying current density (20 mA, 40 mA and 60 mA) and cathode humidity (20, 50 and 80%) were examined and compared with the numerical results. The validated model predicts that the hydration state of the membrane and water transfer rate at the anode can be increased by using a thin membrane and thicker gas diffusion layer.

We presents results obtained from the numerical simulation of the gas-phase chemical kinetics in atmospheric pressure air non-equilibrium plasmas. In particular we have addressed the effect of pulsed operation mode of a planar dielectric barrier discharge. As it was conjectured, the large difference in the time scales involved in the fast dissociation of molecules in plasmas and their subsequent reactions to produce stable chemical species, makes the presence of a continuously repeated plasma production stage unnecessary and a waste of electrical power and efficiency. Results on NOx remediation, ozone production, water vapor and ammonia dissociation are discussed. A few comparisons with experimental findings in a dielectric barrier discharge reactor already used for applications is briefly addressed too. Our results clearly indicate a pattern for the optimization of the discharge using a carefully designed repetition rate and duty-cycle.

The degradation and detachment of the polyamide (PA) layer in thin-film composite (TFC) membranes due to chlorine based chemical cleaning and material difference of PA layer and substrate are two major bottlenecks of forward osmosis (FO) technology. In this study, a new type of FO membranes were prepared by controlling self-polymerization of dopamine (DA) in the aqueous phase and the reaction with trimesoyl chloride (TMC) during interfacial polymerization (IP) process. These membranes were characterized by attenuated total reflection Fourier transform infrared (ATR-FTIR), X-ray photoelectron spectroscopy (XPS), field-emission scanning electron microscopy (FESEM) and water contact angle measurements. The influence of synthesis parameters such as pH of the aqueous phase, reaction time, temperature, and monomer concentrations were systematically investigated. The optimized membrane showed enhanced structure stability in ethanol (7.1 times higher) and chlorine resistance (72.3 times higher) than the conventional Piperazine(PIP)/TMC membrane due to（poly-dopamine）PDA bio-adhesion and polyester groups in the membrane structure. In general, DA/TMC membranes could be an effective strategy to fabricate high-performance FO membranes with excellent structural stability and chlorine resistance.

Revolutionizing Lng Plant Construction and its Comprehensive Comparative Analysis And Evaluation Of Modular Design Development Versus Stick-Built Approach For Enhanced Efficiency And Cost-Effectiveness,.Although the utilization of modularization concepts in the LNG industry remains limited, this study focuses on exploring their potential. It is worth noting that modular units typically incur higher costs compared to field erected units due to the additional requirements of structural steel and robustness for transportation purposes.Nevertheless, the increased cost of modularization can often be balanced by conducting the work at the fabrication site instead of on-field construction. This approach reduces the overall project cost by minimizing field construction expenses and shortening the construction schedule. The objective of this paper is to assess and compare LNG modularization options for a newly established LNG facility in comparison to a conventional stick-built plant used as the base case.:The paper delves into various topics related to LNG plant construction, such as the development of modular units, a comprehensive comparison of different options, evaluation of construction schedules and manpower requirements, logistics considerations, and a recommended approach for design and construction. The cost estimates and engineering, procurement, and construction (EPC) schedules are meticulously compared for each option. Additionally, an inshore/near shore gravity base structure (GBS) option is included for further comparison. It is crucial to emphasize that establishing general costs is not possible as each project is distinct and requires individual study and analysis.:Each project has unique characteristics, resulting in varying shapes of cost curves and break-even points. The outcomes of the feasibility evaluation play a crucial role in determining the extent to which the modular approach to construction is advantageous for the specific project at hand. The evaluation takes into consideration multiple factors to determine the potential benefits of adopting a modular construction approach, allowing decision-makers to make informed choices regarding the project's construction methodology

Background: Young adults, particularly university students might be at greater risk of developing psychological distress, and exhibiting symptoms of anxiety and depression during the COVID-19 pandemic. Objective: The primary objective of this study was to explore and compare the determinants and predictors of mental health (anxiety and depression) during and after COVID-19 lockdown among university students. Methods: This was an observational, cross-sectional study with a sample size of 417 students. An online survey utilizing International Physical Activity Questionnaire–Short Form (IPAQ-SF), General Anxiety Disorder–7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) was distributed to Universiti Tunku Abdul Rahman students via Google forms. Results: During lockdown, family income [χ² (1, n=124) = 5.155, p=0.023], and physical activity [χ² (1, n=134) = 6.366, p=0.012] were associated with anxiety, while depression was associated with gender [χ² (1, n=75) = 4.655, p=0.031]. After lockdown, family income was found to be associated with both anxiety [χ2 (1, n=111) = 8.089, p=0.004], and depression [χ2 (1, n=115) =9.305, p=0.002]. During lockdown, family income (OR=1.60, p=0.018), and physical activity (OR=0.59, p=0.011) were predictors for anxiety, and gender (OR=0.65, p=0.046) being the only predictor for depression. After lockdown, family income was a predictor for both anxiety (OR=1.67, p=0.011), and depression (OR=1.70, p=0.009). Conclusion: Significant negative effects attributed to the COVID-19 lockdown, and certain factors predisposed to the worsening of mental health status in university students. Family income, physical activity level, and gender were some of the major determinants that influenced the anxiety and depression.