Fibrosis is a ubiquitous pathology, and prior studies have indicated that various artemisinin (ART) derivatives (including artesunate (AS), artemether (AM), and dihydroartemisinin (DHA)) can reduce fibrosis in vitro and in vivo. The medicinal plant, Artemisia annua L., is the natural source of ART and is widely used, especially in underdeveloped countries, to treat a variety of diseases including malaria, while A. afra contains no ART but is also antimalarial. Using human dermal fibroblasts (CRL-2097), we compared the effects of A. annua and A. afra tea infusions, ART, AS, AM, DHA, and a liver metabolite of ART, deoxyART (dART), on fibroblast viability and expression of key fibrotic marker genes after 1 and 4 days of treatment. AS, DHA, and Artemisia tea significantly reduced fibroblast viability at 1 and 4 d post-treatment. After 4 d post treatment, AS, DHA, and A. afra tea downregulated ACTA2, and upregulated MMP3, with other genes either being unaffected or differentially affected. ART and AM had no significant effect on either fibroblast viability or fibrotic gene expression. Although A. annua contains ART, it had a significantly greater anti-fibrotic effect than ART alone. Immunofluorescent staining for smooth muscle α-actin (α-SMA) correlated well with transcriptional responses of drug-treated fibroblasts. Together, proliferation, qPCR, and immunofluorescence results show that treatment with ART, AS, DHA, and the two Artemisia teas yield differing responses, including those related to fibrosis, in human dermal fibroblasts.

The ability to self-direct a research program determines graduate degree completion. Yet, research on incompletion of graduate physics programs assume students’ present level of self-direction adequate and neglects to recognize a lack of self-directed learning as key. One theoretical mathematical physicist focused on changing this challenge of physics graduate education by promoting self-directed learning through the type research flow that has been found to bring the greatest satisfaction to researchers with respect to their insights. This he provided through his space, time, open mindedness and theoretical contributions with his students and in collaboration with his colleagues. A self-directed learner himself, David J. Rowe developed methods of mentoring for encouraging physics graduate students to recognize symmetry as valuable in identifying solutions to problems quickly—helping these students take the lead in finding insightful resolutions to complex, multidimensional, mathematical physics uncertainties. How Rowe set about supporting self-directed learning in his graduate physics education interactions will be examined with the use of narrative research to interpret the texts and conversations with the author he made available. His techniques will be presented and recommendations made regarding how Rowe’s work in this regard can be modeled to improve self-direction in STEM graduate education.

Aim: Streptococcus pneumoniae and influenza H1N1 virus are common organisms associated with human infections. These infections could play a significant role in immune regulation. The study was performed to analyse the genome sequences of these organisms with human genome and study its functional significance. Methods: The study was performed to analyse the overlapping of genome sequences in Streptococcus pneumoniae and Influenza (H1N1) virus against human genome sequences by BLASTn sequence analysis. The alignments are studied against the corresponding genes for their functional significance with DAVID and NDEx software.Results: Several hits or overlapping nucleotide segments were identified. Between streptococcus and homo sapiens 287 overlaps were identified, and among influenza and homo sapiens 124 hits were identified. A wide range of functional significance of these genes were identified, and the results are presented in this study. The results show insights into functional pathways and biological activities associated with the respective vaccinations or infections by these microorganisms. Conclusion: The common organisms like Streptococcus pneumoniae and Influenza H1N1 virus actively interact with the immune system and result in a wide range of immune regulations.

Quantum gravity theories rely on a minimal measurable length for their formulations, which clashes with the classical formulation of the uncertainty principle and with Lorentz invariance from general relativity. These incompatibilities led to the development of the generalized uncertainty principle (GUP) from string theories and its various modifications. GUP and covariant formulations of the uncertainty principle are discussed, together with implications for space-time quantization.

Technological advances in the last decades have led to the realization of the concept of a smart environment. A significant part of this development is decentralized ledger technology and its variant, a blockchain. The blockchain database is immutable, open to all stakeholders, secure by architecture and robust. Applying a blockchain in water supply sanitary control creates opportunities for optimization, higher quality of service, cost reduction, better sanitary standards and public control. Physical, chemical, and biological water supply contamination is a great source of public health hazards. Implementation of a blockchain for water supply IoT, from the source point to the consumption point, enables effective response to changing environments, possible cross-contamination, stormwater management or disaster and emergency action. The chapter encompasses all fundamental elements and principles of water collection, distribution and consumption, with a focus on the health hazards and sanitary requirements for potable water. The chapter listed the main contaminants, methods of their registration and elimination, and requirements for drinking water in accordance with WHO, EU Drinking Water Directive and EPA standards. Blockchain technology solutions are described for smart water supply, including smart supply management, smart contracts, tokenization, smart compliance systems, and, most importantly, effective utilization of distributed ledger technologies for sanitary monitoring of water sources, water treatment, and water distribution systems.

Proposed fundamental laws of biology and a model of health and disease underscore the importance of the lymphatic system. The lymphatics are responsible for two of the laws of biology and the fulcrum of health and disease balancing proliferation with regeneration through the immune system. It is responsible for protection from the environment and repair of senile and damaged tissue. Life is constantly bombarded by forces that increase entropy. Lymphatics provide negative entropy to maintain health. Lymphatics help maintain cellular homeostasis removing products of metabolism. Using these principles, the role of lymphatics is investigated in salt sensitivity hypertension, cardiorenal system, the new pillar of heart failure and kidney disease - Sodium-Glucose Transport Protein 2 (SGLT2) Inhibitors, and brain diseases. The realization of organ lymphatics in maintenance of health and disease opens the avenue to new therapeutics. This is the unrealized potential of lymphatic study.

Quasi-solid composited electrolytes were produced by LiFSI initiated polymerized poly-(Dioxolane) (PDOL) with garnet-LLZO (Li7La2Zr3O12) nanofibers and used in lithium-metal batteries. Linear sweep voltammetry shows that the initial oxidation voltage of 4.6 V for Gel-10% (G10, 10% wt. LLZO in PDOL) vs Li/Li+. EIS test of stainless steel// stainless steel symmetric cells for Gel-1% (G1), Gel-5% (G5) and Gel-10% (G10) show ion conductivity (5*10-5 S/cm). Li/G10/Li symmetric cells have stable stripping-plating cycling performance over 1300 hours continuously with the current density of 0.1 mA/cm2 at 25 oC, indicating a good interface contact and stable lithium-ion transport pathway through the composite electrolytes. LFP/G10/Li batteries have stable charge-discharge plateau, low polarization voltage of 0.07-volt, energy efficiency of 95% and coulombic efficiency of ~99% at current density of 26.3 mA/g at 25 oC for over 100 cycles.

Natural host defensins, also sometimes termed antimicrobial peptides, are evolutionarily conserved. They have been studied as antimicrobials, but some pharmaceutical properties, undesirable for clinical use, led to the development of synthetic molecules with constructed peptide arrangements and/or peptides not found in nature. The leading development currently is synthetic small molecule nonpeptide mimetics, whose physical properties capture the characteristics of the natural molecules, and share their biological attributes. We studied brilacidin, an arylamide of this type, for its activity in vitro against fungi (40 clinical isolates, 20 species) that the World Health Organization has highlighted as problem human pathogens. We find antifungal activity at low concentrations for many pathogens, which indicates further screening for activity, particularly in vivo, is justified to evaluate this compound, and other mimetics, as attractive leads for development of effective antifungal agents.

For 80 years high-intensity focused ultrasound (HIFU) has been a significant area for medical research. It is a non-invasive procedure which causes cell death in a highly localised area at a defined distance from the transducer. Since 2000, the clinical indications have broadened considerable as the technology has improved. This review looks back at the history of HIFU and the current clinical indications.

Reducing GHG emissions is a crucial challenge in urban areas, characterized by high energy consumption and reduced exposure to nature. In this context, the urban green system could play a pivotal role. In the literature, scholars analyzed both the ability of species-specific and layout-specific green infrastructures to increase carbon sequestration and the best location sites of new green infrastructures, to increase the provision of overall ecosystem services. There is a lack of studies helping green urban planners and designers choose where and which green infrastructure to implement, based on vegetation species-specific performance and local carbon emissions of city components. This paper uses tree inventory data from a medium-sized city in central Italy (Perugia) to develop a spatial analysis of the urban parks' performance in carbon sequestration. Then, the method evaluates the carbon emission of a public city building to generate a spatialized balance between buildings’ demand and trees’ supply, to support local decisions about the best locations for new green infrastructures and the choice between species. The paper contributes to GIS-based tools that vary the recommended location sites and species for new green infrastructures based on the demanded ecosystem service.

Companies are increasingly focusing on sustainable business practices. Internal and external stakeholders’ expectations manifest in legal requirements, national and international standards, and market and customer expectations, among other things, must be considered. In addition to profit maximization as the usual target for corporate management, management must consider environmental sustainability aspects such as resource efficiency, greenhouse gas intensity, and a company's emissions behavior. In addition, social aspects relating to the company's employees, the immediate urban environment, the situation in the supply chain, and effects on the market environment must increasingly be considered. Specifically, companies are faced with the chal-lenge of dealing with conflicting objectives regarding the various aspects of sustainability and, if necessary, weighing them up against each other. These trade-offs must be made against the company's socio-economic and ecological environment, corporate strategy, and sustainability goals. This paper provides an overview of current approaches and research gaps on this topic through a literature review. It shows a lack of methods and frameworks to specifically deal with trade-offs and conflicts of goals.

Mallios and Zafiris emphasize that adjoint functors or adjunctions are not only "ubiquitous" in category theory but characterize the naturality of their approach to physical geometry. Hence in this paper, the history and theory of adjoint functors is investigated. Where do adjoint functors come from mathematically and how did the concepts develop historically?

Logical information theory is the quantitative version of the logic of partitions just as logical probability theory is the quantitative version of the dual Boolean logic of subsets. The resulting notion of information is about distinctions, differences, and distinguishability, and is formalized using the distinctions (`dits') of a partition (a pair of points distinguished by the partition). All the definitions of simple, joint, conditional, and mutual entropy of Shannon information theory are derived by a uniform transformation from the corresponding definitions at the logical level. The purpose of this paper is to give the direct generalization to quantum logical information theory that similarly focuses on the pairs of eigenstates distinguished by an observable, i.e., qudits of an observable. The fundamental theorem for quantum logical entropy and measurement establishes a direct quantitative connection between the increase in quantum logical entropy due to a projective measurement and the eigenstates (cohered together in the pure superposition state being measured) that are distinguished by the measurement (decohered in the post-measurement mixed state). Both the classical and quantum versions of logical entropy have simple interpretations as "two-draw" probabilities for distinctions. The conclusion is that quantum logical entropy is the simple and natural notion of information for quantum information theory focusing on the distinguishing of quantum states.

Background. The Stanford Health Assessment Questionnaire-Disability Index (HAQ) is widely used to measure functional ability in persons with Rheumatoid Arthritis (RA). The instrument was developed with limited involvement from persons with RA, and their perception of the instrument has not been studied in depth. The aim of this study was to explore how persons with RA experience the use of the HAQ in care. Methods. Forty persons with RA were purposefully recruited to participate in semi-structured interviews. The interviews were then analyzed qualitatively using thematic analysis. Results. The participants questioned the relevance of the HAQ but nevertheless experienced that the instrument had a profound effect on their understanding of health and how care is delivered. The analysis resulted in three themes: Problems with individual items, meaning of the summative score, and effects on care and health perceptions. Conclusions. To make the HAQ relevant to persons with RA, it needs to be revised or to include an option to select items most meaningful to the respondent. To ensure relevance, the HAQ update should preferably be co-created by researchers, clinicians and persons with RA.

The new logic of partitions is dual to the usual Boolean logic of subsets (usually presented only in the special case to the logic of propositions) in the sense that partitions and subsets are category-theoretic duals. The new information measure of logical entropy is just the normalized quantitative version of partitions. The new approach to interpreting quantum mechanics (QM) is showing that the mathematics (not the physics) of QM is the Hilbert space version of the mathematics of partitions. Or putting it the other way around, the math of partitions is a skeletal version of the math of QM. The key concepts throughout this progression from logic to information theory to quantum theory are distinctions versus indistinctions, definiteness versus indefiniteness, or distinguishability versus indistinguishability. The distinctions of a partitions are the ordered pairs of elements from the underlying set that are in different blocks of the partition. Logical entropy is defined (initially) as the normalized number of distinctions. The cognate notions of definiteness and distinguishability run through the math of QM, e.g., in the key non-classical notion of superposition (= ontic indefiniteness) and in the Feynman rules for adding amplitudes (indistinguishable alternatives) versus adding probabilities (distinguishable alternatives).

There are potentially promising mitigation activities for epidemic and pandemic scenarios that are not currently the subject of significant research effort. Large epidemics and pandemics pose risks that are important to mitigate, even if the likelihood of the events is low and uncertain. While some efforts are the subject of extensive funding and consideration, other approaches are neglected. Here, we consider such neglected interventions which could significantly reduce the impact of such an epidemic or large-scale pandemic. These are identified via a narrative literature review of extant literature reviews and overviews of mitigations in epidemic and pandemic situations, followed by consideration of the economic value of information of further study of heretofore neglected interventions and approaches.Based on that analysis, we considered several classes of mitigations, and conducted more exploratory reviews of each. Those discussed include mitigations for (1) reducing transmission, such as personal protective equipment and encouraging improved hygiene, (2) reducing exposure by changing norms and targeted changes for high-risk or critical professions and activities, (3) reducing impact for those infected, and (4) increasing large scale resilience using disaster and infrastructure continuity planning.Some proposed mitigations are found to be of low marginal value. Other mitigations are likely to be valuable, but the concepts or applications are underdeveloped. In those cases, further research, resources, or preparation are valuable for mitigating both routine and extreme disease outbreak events. Still more areas of research are identified as having uncertain value based on specific but resolvable uncertainties. In both of the latter cases, there is no guarantee that mitigations identified as worthy of further consideration will be valuable, but the argument for further research is clear.

The number of engineers who are transitioning into environmental sustainability careers is growing, though a gap still exists between supply and demand. This presents an opportunity for undergraduate engineering students to fulfill the demand as environmental sustainability professionals. This qualitative exploratory study investigated environmental sustainability learning experiences and future career interests in environmental sustainability. The social cognitive theory (SCCT) was utilized as a theoretical lens, exploring undergraduate students’ environmental sustainability interests, related learning experiences and their interest in pursuing a future career in environmental sustainability. Twenty-five undergraduate engineering students in various engineering disciplines were interviewed for this study. Data were analyzed to (1) identify students’ interest in pursuing a career in environmental sustainability, (2) determine if students’ interests have changed since they began their undergraduate studies, and (3) explore how learning experiences have impacted students’ future career choice. The findings posit that exposure to environmental sustainability learning experiences is impactful and plays an important role, impacting students' interests in pursuing careers in sustainability. Results reveal that elements such as personal beliefs and salary considerations inspire career choices. This research contributes to addressing the demand for additional working professionals who are prepared to tackle environmental sustainability issues, highlighting the role of learning experiences in shaping students' career interests.

Deep learning techniques, such as convolutional neural networks (CNN), generative adversarial networks (GAN), and graph neural networks (GNN), have over the past decade changed the ac-curacy of prediction in many diverse fields. In recent years, the application of deep learning tech-niques in computer vision tasks in pathology demonstrated extraordinary potential in assisting clinicians, automating diagnosis, and reducing costs for patients. Formerly unknown pathologi-cal evidence, such as morphological features related to specific biomarkers, copy number varia-tions, and other molecular features, were also able to be captured by deep learning models. In this paper, we review popular deep learning methods and some recent publications about their appli-cations in pathology.

The grooved carpet-shell clam is one of the most economically relevant shellfish species living in the Mediterranean and nearby Atlantic coasts. Previous studies using different types of genetic markers showed a remarkable genetic divergence of the Eastern Mediterranean, Western Mediterranean and Atlantic populations, but important details remained unclear. Here, data from six nuclear introns scored for restriction fragment size polymorphisms in eight populations that have not been studied before have been pooled for the analysis with data scattered through three previous studies, totaling 32 samples from 29 locations. The results show lower levels of heterozygosity, higher mean number of alleles, and alleles with restricted distribution in the Mediterranean populations, suggesting the existence of a large isolated population in the eastern Mediterranean at the middle Pleistocene. The data also confirm the similarity of populations from Tunisia to western Mediterranean populations. Finally, a genetic mosaic is apparent in the Atlantic coasts of the Iberian Peninsula, with a divergence of Rias Baixas populations from more northern populations and Central Portugal populations. The effects of oceanic fronts, seasonal upwellings, river plumes and/or fishery management operations could explain this and other features of the Atlantic populations.

The allosteric SERCA (Sarcoplasmic/Endoplasmic Reticulum Ca2+-ATPase) activator CDN1163 has been recently added to the group of pharmacological tools for probing SERCA function. We chose to investigate the effects of the compound on T lymphocyte Ca2+ stores, using the well-described Jurkat T lymphocyte as a reliable cell system for Ca2+ signaling pathways. Our study identified the lowest concentrations of the SERCA inhibitors thapsigargin (TG) and 2,5-di-(tert butyl)-1,4-benzohydroquinone (tBHQ) capable of releasing Ca2+, permitting the differentiation of the TG-sensitive SERCA 2b Ca2+ store from the tBHQ-sensitive SERCA 3 Ca2+ store. We proceeded to test the effects of CDN1163 on Ca2+ stores, examining specific actions on the SERCA 2b and SERCA 3 Ca2+ pools using our low dose SERCA blocker regimen. In contrast to previous work, we find CDN1163 exerts complex time-sensitive and SERCA isoform-specific actions on Ca2+ stores. Surprisingly, short-term exposure (0-30 minutes) to CDN1163 perturbs T cell Ca2+ stores by suppressing Ca2+ uptake with diminished Ca2+ release from the SERCA 2b-controlled store. Concomitantly, we find evidence for a SERCA-activating effect of CDN1163 on the SERCA 3 regulated store, given the observation of increased Ca2+ release inducible by low dose tBHQ. Intriguingly, longer-term (>12 hours) CDN1163 exposure reversed this pattern, with increased Ca2+ release from SERCA 2b-regulated pools, yet decreased Ca2+ release responses from tBHQ-sensitive SERCA 3 pool. Our results reveal differential effects of CDN1163 on Ca2+ stores regulated by distinct SERCA isoforms, prompting the need for careful interpretation of the compound’s effects, particularly in cells expressing multiple SERCA isoforms.

Button batteries pose a significant threat to young children and are found in many household items and children’s toys. Along with product manufacturers and retailers, parents and caregivers have a role in button battery ingestion prevention through vigilance regarding items containing button batteries in the home, and knowledge of button battery ingestion symptoms. There is limited information available about parent and caregiver perspectives towards button battery safety. Identifying the areas where increased education is required is important for informing safety campaigns and delivering targeted education. This study aimed to examine parent and caregiver elemental perspectives on button battery safety. One hundred and seventy-four parents and caregivers of children aged 0 to 5 completed a cross-sectional online survey. Distribution occurred via social media. The survey contained multiple-choice questions pertaining to button battery perspectives, and one open-ended question. Respondents recognized the dangers of button battery ingestion, yet only 37% reported being familiar with button battery ingestion symptoms. While 68% knew of household items containing button batteries, only 21% were aware of product recall information sources. Approximately 64% understood immediate post-ingestion steps and 17% found current safety labels unsatisfactory. In an open-ended question, parents and caregivers provided comments about button battery safety that revealed five broad themes; supervision and education; safe storage of button batteries in the home; ensuring children cannot access button batteries; disposing of button batteries safely; and avoiding purchasing items containing button batteries. This study provides a foundation for ongoing investigation of parent and caregiver perspectives on button battery home safety.

Tropical forest and savanna biomes are pivotal in the functioning of the Earth system. Tropical forests are one of the largest terrestrial biosphere carbon pools, whereas savannas exchange carbon between the biosphere and atmosphere via frequent and extensive landscape fires. Both are biodiverse and under increasing threat due to land clearing and anthropogenic climate change. Reliable mapping of tropical forest and savanna is essential to provide understanding of how anthropogenic impacts are affecting the extent of these biomes. Using Google Maps satellite imagery, we manually classified 24,239 random points as forest, savanna, or anthropogenic landscapes within the tropics. Because fire and climate are correlated, we developed separate geospatial models to rank the importance of climate, topography, and human influence on vegetation present. This modelling confirmed that those areas with more fires had lower probabilities of tropical forest, that forest was most likely in areas with high mean annual rainfall with little seasonal variation in precipitation, and that anthropogenic factors disrupt this environmental predictability. We found there were environments where tropical forest and savanna were equally probable are geographically restricted. These relationships suggest that future drier climates projected under anthropogenic climate change, combined with clearing and burning that have reduced tropical forest extent to a subset of its theoretical distribution, will lead to irreversible loss of tropical forests. Our modelling provides global mapping that can be used track further changes to distribution of rainforests.

Studies have shown that STK11 mutation plays a critical role in affecting the lung adenocarcinoma (LUAD) tumor immune environment. By training an Inception-Resnet-v2 deep convolutional neural network model, we were able to classify STK11-mutated and wild type LUAD tumor histopathology images with a promising accuracy (per slide AUROC=0.795). Dimensional reduction of the activation maps before the output layer of the test set images revealed that fewer immune cells were accumulated around cancer cells in STK11-mutation cases. Our study demonstrated that deep convolutional network model can automatically identify STK11 mutations based on histopathology slides and confirmed that the immune cell density was the main feature used by the model to distinguish STK11-mutated cases.

Tomato (Solanum lycopersicum L.) has almost 190 million tonnes produced in 2023. Tomato fruit suffer losses of up to 50% during harvest and transport, which causes financial hardship, reduces the amount of food available and causes environmental harm. Calcium plays an important role in cell wall strength. This work assessed the use of a calcium transport stimulants (MCAS) to increase the firmness of tomato fruit in the laboratory and the foliar application to tomato plants. Then handling damage was simulated. In the laboratory, the calcium with MCAS significantly increased the fruit firmness compared to the untreated and calcium without MCAS, which were not significantly different. When calcium with MCAS was applied to tomato plants foliarly before harvest, the calcium with MCAS treated fruit were significantly firmer than the untreated or calcium without MCAS treated fruit for up to 10 weeks after harvest, and this was achieved by applying only 0.91 kg ha-1 calcium. Finally, when fruit were exposed to a simulated drop, the calcium with MCAS treated fruit remained firmer than the undamaged fruit or dropped fruit with calcium without MCAS. Calcium with MCAS could significantly increase the fruit firmness and increase the shelf-life of tomatoes while applying less calcium.

Historical analysis of Australian bushfire data spanning 170 years addresses whether the strength of recent fire events has been exacerbated by human-induced climate change. The question of “cause” looks at the characteristics of a wider range of natural hazards. Fire characteristics are compared with earthquake hazard characteristics: (1) energy – termed “magnitude”; (2) severity – termed “intensity”; and (3) resultant damage to people and structures – termed “impact”.Published global, Northern and Southern hemisphere temperature data are shown to vary consistently in phase over 170 years, but vary in amplitude with statistical significance. CO₂ levels north and south of the Equator have tracked quite consistently. Thus, Southern Hemisphere bushfire magnitude and intensity is compared with the Southern Hemisphere climate record, rather than a global data set.28 major bushfires and associated droughts since 1850 show neither apparent drought extent, nor area burned, nor bushfire intensity, correlates with changes in Southern Hemisphere climate. Average rainfall from 1900 shows a wetter, rather than drier trend. Cyclone energy shows no significant trend with climate. Planet-wide “greening”, through CO₂ fertilisation, is an insignificant contributor to bushfire magnitude. Combustion theory shows recorded “global warming” could have had no significant influence on bushfire magnitude or intensity. Any increase in Australian bushfire impact, as judged by lives lost, similarly, shows no correlation with bushfire magnitude, nor indeed, any observed Southern Hemisphere global warming.Thus, bushfire magnitude seems much more likely driven by fuel load and any anomalous bushfire intensity is likely driven by anomalous ground level fuel load. The evidence suggests that any CO₂ emissions reduction will have no impact on future bushfire “severity.

Estimates by the World Health Authority suggest that 1 billion people do not have access to the assistive technologies they require. Over the past decade, the design of products that empower people with a disability has shifted from specialised and dedicated products designed only for those with a disability to features and functions integrated into cost-effective consumer technologies for the benefit of all. The opportunity for expansion of the availability of such technologies is at risk of being ignored as a result of models of delivery that are founded in medical devices and which have failed to reflect trends in our understanding of technology and the choices and preferences expressed by persons with a disability. This research undertaken suggests that the opportunities of such expansion offer significant benefits to people with a disability and better both economic and social return on investment for authorities.

The Carnot cycle and the attendant notions of reversibility and entropy are examined. It is shown how the modern view of these concepts still correspond to the ideas Clausius laid down in the nineteenth century. As such, they reflect the outmoded idea current at the time that heat is motion. It is shown how this view of heat led Clausius to develop the entropy of a body based on the work that could be done in a reversible process rather than the work that was actually done. In consequence, Clausius built into entropy a conflict with energy conservation, which is concerned with actual changes in energy. In this paper, a macroscopic formulation of internal mechanisms of damping based on rate equations for the distribution of energy within a gas. It is shown that work processes involving a step-change in external pressure, however small, are intrinsically irreversible. However, under idealised conditions of zero damping the gas inside a piston expands and traces out a trajectory through the space of equilibrium states. Therefore, the entropy change due to heat flow from the reservoir matches the entropy change of the equilibrium states. This trajectory can traced out in reverse as the piston reverses direction, but if the external conditions are adjusted appro-priately, the gas can be made to trace out a Carnot cycle in P-V space. The cycle is dynamic as opposed to quasi-static as the piston has kinetic energy equal in difference to the work done in-ternally and externally.

We review a theory that predicts the onset of thermalization in a quantum mechanical coupled non-linear oscillator system, which models the vibrational degrees of freedom of a molecule. A system of N non-linear oscillators perturbed by cubic anharmonic interactions exhibits a many-body localization (MBL) transition in the vibrational state space (VSS) of the molecule. This transition can occur at rather high energy in a sizable molecule because the density of states coupled by cubic anharmonic terms scales as ~ N3, in marked contrast to the total density of states, which scales as exp(aN), where a is a constant. The emergence of a MBL transition in the VSS is seen by analysis of a random matrix ensemble that captures the locality of coupling in the VSS, referred to as local random matrix theory (LRMT). Upon introducing higher order anharmonicity, the location of the MBL transition of even a sizable molecule, such as an organic molecule with tens of atoms, still lies at an energy that may exceed the energy to surmount a barrier to reaction, such as a barrier to conformational change. Illustrative calculations are provided, and some recent work on the influence of thermalization on thermal conduction in molecular junctions is also discussed.

This study aimed to evaluate the impact of Candida albicans on subgingival biofilm formation on dental implant surfaces. Scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM) were used to compare biofilm structure and microbial biomass in the presence and absence of the fungus after periods of 24, 48, and 72 h. Quantitative polymerase chain reaction (qPCR) was used to quantify the number of viable and total micro-organisms for each of the biofilm-forming strains. A general linear model was applied to compare CLSM and qPCR results between control and test conditions. The biofilm developed with C. albicans at 72 h had a higher bacterial biomass, with a significantly higher cell viability (p < 0.05). After both 48 and 72 h of incubation, in the presence of C. albicans, there was a significant increase in counts of Fusobacterium nucleatum and Porphyromonas gingivalis and in the cell viability of Streptococcus oralis, Aggregatibacter actinomycetemcomitans, F. nucleatum, and P. gingivalis. Using a dynamic in vitro multispecies biofilm model, C. albicans exacerbated the development of the biofilm grown on dental implant surfaces, significantly increasing the number and cell viability of periodontal bacteria.

1. Background: The global COVID-19 lockdowns are unique psychological factors, requiring adjustment and coping. This illustrative, South African case study investigated the influence the COVID-19 lockdown context would have on meditation and physical activity. As these were lifestyle patterns the null hypothesis was of no change. 2. Method: The methodology consisted of quantitative and qualitative phases. The quantitative phase was an empirical, case study review of data from the author’s HeartMath and Fitbit electronic devices, as from 9 November 2019 to 31 July 2021. This consisted of coherence and achievement data from the HeartMath Inner Balance application (app), as well as distance and activity data from the Fitbit app. The qualitative phase consisted of the selection and illustration of meditation sessions documented over lockdown. 3. Results: The highly significant increases in physical activity and meditation coherence and achievement collectively indicated significant health promotion over the COVID-19 Lockdown period. Subtle energetic, experiential descriptions of meditation apprehensions resonated and supported these quantitative findings. 4. Conclusions: COVID-19 lockdown has meant transformation, humility, and reordering of priorities. The meditation descriptions amplified information from the HeartMath and Fitbit electronic devices, together co-creating conscious, embodied, relationship science for discussion, instruction, and further research.

Models of quantum measurements are presented, including observers subject to the laws of quantum mechanics. Observers perform multiple measurements in an attempt to disprove the collapse hypothesis. It is shown that under reasonable assumptions the effort cannot succeed. Under a unitary evolution the end state is a correlation between the result of the first measurement and the result(s) of the others, consistent with the observer's collapse hypothesis. The observer may conclude that the laws of nature include a non-unitary collapse mechanism, even if one does not actually exist. Discard of information is the crucial factor which distinguishes entanglement from measurement.

Planck's constant plays an important role in quantum mechanics but has little physical meaning apart from its contribution to the formulas. Evaluating each of the constant's unit dimensions gives a more granular account of the physical phenomena described by the equations. These formulas show how classical and quantum mechanical equations are related, and they give consistent descriptions of phenomena like momentum and energy in classical and quantum systems.

As a derivative of graphene, graphene oxide (GO) was initially developed by chemists to emulate some of the key properties of graphene, but it was soon recognized as a unique material in its own right, addressing an application space that is not accessible to chemical vapor deposition based materials. Over the past decade, GO has emerged as a new frontier material with tremendous advances in its material fabrication and quality control over its properties. These in turn have led to rapid progress in GO based photonics, electronics, and optoelectronics concepts and devices, evoking new science and paving the way for many technological breakthroughs with exceptional performance. Here, we review the unique fundamental characteristics of GO, its thin film fabrication methods, patterning techniques, and mechanisms for tuning its material properties. This latter capability in particular has enabled novel advanced functional photonic, electronic, and optoelectronic devices. Understanding these insights is essential for designing and tailoring GO properties for state-of-the-art applications including solar energy harvesting, energy storage, medical diagnosis, image displays, and optical communications. We conclude by discussing the open challenges and exciting opportunities of this field, together with future prospects for major technological advancements and breakthroughs.

226Ra and 228Ra are typically monitored for groundwater and surface water compliance at legacy U mining and milling sites. Groundwater monitoring results for combined Ra (226Ra+228Ra) reported by the existing contract laboratory at a former U mine and mill Site (Wyoming, USA) have been highly variable and with increasing trends at the Site compliance and background wells since the method was changed in 2005. Sample reanalysis has indicated poor reproducibility and significant analytical error in 228Ra measurements. An interlaboratory comparison was conducted to evaluate the potential causes of the high variability and analytical error. Two different methods were used for 226Ra (M903.0 and M903.1) and 228Ra (M904.0 and Ra-05). 226Ra results were less variable compared to 228Ra, and 228Ra data from the existing laboratory were qualified as estimated with high bias due to detection of 228Ra in the field blank. Compliance with the 226Ra+228Ra groundwater standard was either met or not met, depending on which laboratory conducted the analyses. Specific laboratory techniques, rather than the analytical method, are contributing to elevated 228Ra values being reported. It was recommended that samples whose 226Ra+228Ra results exceed the Site standard in the future be reanalyzed by the existing laboratory with a sample split also being sent to an outside laboratory for confirmatory analysis.

How much is religion quantitatively involved in global climate politics? After assessing the role of the Conference of Parties to the United Nations Framework Convention on Climate Change from a normative perspective, this descriptive, transdisciplinary and unconventional study offers the first comprehensive quantitative examination of religious nongovernmental organizations that formally participate in its annual meetings, the largest attempts to solve the climate crisis through global governance. This study finds that although their numbers are growing, only about 3 percent of registered nongovernmental organizations accredited to participate in the conference are overtly religious in nature — and that more than 80 percent of those faith-based groups are Christian. Additionally, this study finds that religious nongovernmental organizations that participate in the conference are mostly from the Global North. The results call for greater participation of religious institutions in the international climate negotiations in order for society to address the planetary emergency of climate change.

Dispersal represents a key life-history trait with several implications for the fitness of organisms, population dynamics and resilience, local adaptation, meta-population dynamics, range shifting and biological invasions. Plastic and evolutionary changes of dispersal traits have been intensively studied over the past decades in entomology, in particular in wing-dimorphic insects for which literature reviews are available. Importantly, dispersal polymorphism also exists in wing-monomorphic and wingless insects, and except for butterflies, fewer syntheses are available. In this perspective, by integrating the very last research in the fast moving field of insect dispersal ecology, this review article provides an overview of our current knowledge of dispersal polymorphism in insects. After having provided a definition of the main terms characterising insects’ movements, some of the most often used experimental methodologies for the separation of dispersers and residents in wing-monomorphic and wingless insects are presented. The existing knowledge on the morphological and life-history trait differences between resident and disperser phenotypes is then synthetized. The fourth part examines the effects of range expansion on dispersal traits and performance, in particular for insects from range edges and invasion fronts. Finally, some research perspectives are proposed in the last part of the review.

The utilization and engineering of thermo-optic effects have found broad applications in integrated photonic devices, facilitating efficient light manipulation to achieve various functionalities. Here, we perform both an experimental characterization and theoretical analysis of these effects in integrated micro-ring resonators in high index doped silica (HIDS), which has had many applications in integrated photonics and nonlinear optics. By fitting the experimental results with theory, we obtain fundamental parameters that characterize their thermo-optic performance, including the thermo-optic coefficient, the efficiency for the optically induced thermo-optic process, and the thermal conductivity. The characteristics of these parameters are compared to those of other materials commonly used for integrated photonic platforms, such as silicon, silicon nitride, and silica. These results offer a comprehensive insight into the thermo-optic properties of HIDS based devices. Understanding these properties is essential for efficiently controlling and engineering them in many practical applications.

Though the share of the world population living in extreme poverty declined to 10 percent in 2015, from 16 percent in 2010 and 36 percent in 1990, data shows that the world is not on track in achieving the target of less than 3 percent of people living in extreme poverty by 2030. Hence the study sought to investigate the influence of AI on poverty reduction. Using content analysis one of the unobtrusive research techniques, the study found out that, the availability of relevant data is making AI be able to deliver value to humanity and AI has a strong influence on poverty in areas of relevant data collection through poverty maps, its ability to revolutionize agriculture, education, and the financial sector through digital financial inclusion. The study also discovered that many countries especially developing nations are not collecting as much data to identify the number of poor people and the regions where these people are located. However, the existence of AI is assisting to change this, or instance the study discovered that the research team at Stanford University is using satellite images to provide an alternative to map poverty, to identify the regions where poverty is more concentrated. Also, various robotics and AI programs such as Google and Stanford University’s Sustainability and Artificial Intelligence Lab, are coming forth with AI programs in agriculture which are doing a lot to improve farming, through the identification of diseases, prediction of crop yields, and location of areas prone to a scarcity among several other notable signs of progress in education. Therefore, the study recommends that governments, development institutions and other organizations that are striving to fight poverty to invest more in AI as well as adopting and scaling up its use as it presents benefits in the quest to ensure that poverty is reduced.

A non-negligible fraction of quasars are red at optical wavelengths, indicating (in the vast majority of cases) that the accretion disc is obscured by a column of dust which extinguishes the shorter-wavelength blue emission. In this paper we summarise recent work by our group, where we find fundamental differences in the radio properties of SDSS optically selected red quasars. We also present new analyses, using a consistent colour-selected quasar parent sample matched to four radio surveys (FIRST, VLA Stripe 82, VLA COSMOS 3 GHz and LoTSS DR1) across a frequency range 150 MHz-3 GHz and four orders of magnitude in radio flux. We show this enhancement is driven by systems with small-scale radio emission (∼kpc) and peaks around the radio-quiet threshold (defined as the ratio of 1.4 GHz luminosity to 6μm luminosity) across the four radio samples. Exploring the potential mechanisms behind this enhancement, we rule out star-formation and propose either small-scale jets or dusty winds interacting with the interstellar medium; this will be tested in detail using new multi-band uGMRT data. Overall our results cannot be explained with a simple viewing angle hypothesis, and so may point towards red quasars representing a key phase in the evolution of galaxies.

The Action Control Theory (ACT) is an enactive theory of perception and mental imagery with six components: Schemata, Objects, Actions, Affect, Goals and Others’ Behavior. The evidence support-ing these six connected processes is reviewed in light of research on mental imagery vividness. The six processes and their interconnections receive empirical support from a wide range of studies. All six domains of perception and mental imagery are influenced by individual differences in vividness. Real-world applications of ACT show interesting potential to improve human well-being in both healthy people and patients. Mental imagery can be applied in creative ways to make new collective goals and actions for change that are necessary to maximize the future prospects of the planet.

The IPAT equation provides a simple but powerful model for understanding sustainability, particularly from the challenge posed by the Anthropocene—how to reduce personal or societal impact. Impact is calculated by multiplying population, affluence and technology, and a ‘reduction coefficient’ e is used to explore targeted reductions in impact of different entities to cap total (summed) impact. The model offers two solutions. First, that all three factors are essential in determining total impact; a focus on just one or two is not justifiable without credibly addressing the other(s). Second, by presenting reduction of impact as a proportion of current activity, the solution becomes accessible to an individual actor (e.g., an individual, family, organization, or country). Application of the model is illustrated based on household weekly food consumption from cultures around the world. The model helps unify a) disparate perspectives on population, affluence and technology, which currently oppose one another from a basis of belief or dogma, and b) different sectors (e.g., food production, energy, climate impacts and others), as well as actors, so they can jointly identify strategies to resolve their contributions to approaching larger scale sustainability.

Microwave transversal filters, which are implemented based on the transversal filter structure in digital signal processing, offer a high reconfigurability for achieving a variety of signal processing functions without changing hardware. When implemented using microwave photonic (MWP) technologies, also known as MWP transversal filters, they provide competitive advantages over their electrical counterparts, such as low loss, large operation bandwidth, and strong immunity to electromagnetic interference. Recent advances in high-performance optical microcombs provide compact and powerful multi-wavelength sources for MWP transversal filters that require a larger number of wavelength channels to achieve high performance, allowing for the demonstration of a diverse range of filter functions with improved performance and new features. Here, we present a comprehensive performance analysis for microcomb-based MWP spectral filters based on the transversal filter approach. First, we investigate the theoretical limitations in the filter spectral response induced by finite tap numbers. Next, we analyze the distortions in the filter spectral response resulting from experimental error sources. Finally, we assess the influence of input signal’s bandwidth on the filtering errors. These results provide a valuable guide for the design and optimization of microcomb-based MWP transversal filters for a variety of applications.

We theoretically investigate and optimize the performance of four-wave mixing (FWM) in microring resonators (MRRs) integrated with two-dimensional (2D) layered graphene oxide (GO) films. Owing to the interaction between the MRRs and the highly nonlinear GO films as well as to the resonant enhancement effect, the FWM efficiency in GO-coated MRRs can be significantly improved. Based on previous experiments, we perform detailed analysis for the influence of the GO film parameters and MRR coupling strength on the FWM conversion efficiency (CE) of the hybrid MRRs. By optimizing the device parameters to balance the trade-off between the Kerr nonlinearity and loss, we achieve a high CE enhancement of ~18.6 dB relative to the uncoated MRR, which is ~8.3 dB higher than previous experimental results. The influence of photo-thermal changes in the GO films as well as variations in the MRR parameters such as the ring radius and waveguide dispersion on the FWM performance is also discussed. These results highlight the significantly improved FWM performance that can be achieved in MRRs incorporating GO films

Psychomotor developmental delay in infants includes failure to acquire abilities such as sitting, walking, grasping objects and communication at the ages when most infants have acquired these abilities. Known risk factors include a large number of aspects of family environment, socioeconomic position, problems in pregnancy and birth, and maternal health. It is clinically useful to be able to screen for developmental delay so that healthcare interventions can be considered. The present research used machine learning (random forest) to create an algorithm predicting psychomotor delay in 9-month-old infants using information ascertainable at birth and in early infancy. The dataset was the UK longitudinal Millennium Cohort study. Fifty-two predictors measuring socioeconomic indicators, paternal, family and social support for the mother, beliefs about good parenting, maternal health, pregnancy and birth were included in the initial algorithm. Feature reduction showed that of the 52 variables, birthweight, family income and parents’ ages had the highest feature importance scores and could alone correctly predict developmental delay with over 99% sensitivity and 100% specificity. The relationships between delay and some of the predictors, particularly income, were nonlinear and complex. The results suggest that the risk of psychomotor developmental delay can be identified in early infancy using machine learning, and that the best predictors are factors present prior to birth. Surprisingly, the most important factors included in the present study did not include illnesses during pregnancy such as eclampsia and infections.

Many models with structures of matter associated with a structure of extra spatial dimensions have been proposed in recent decades. On employing a further generalisation from the local 4-dimensional spacetime form to a general form for proper time, we describe how matter fields resembling the Standard Model of particle physics can be accommodated far more directly than with a higher-dimensional spacetime theory. The successful identification of key features of visible matter in this non-spatial sector of extra dimensions in turn motivates seeking a candidate for dark matter residing in the original extra spatial dimension sector, and provides a close guide for the explicit form this invisible matter might take. We describe how such Standard Model and dark matter sectors in different extra-dimensional branches of generalised proper time are gravitationally connected through their common root in the local 4-dimensional spacetime and consider further possible mutual interactions and implications in comparison with existing dark matter models. A yet further possible branch of generalised proper time can be connected with dark energy models, hence in principle accounting for all three major components of cosmological structure within this framework.

Modern life implies a constant exposure of living organisms to electromagnetic fields generated by human made technology. The question of whether or not electromagnetic fields in the non-ionizing frequency range can affect cellular functions, increasing the risk of cancer or another pathologies is currently a subject of interest for scientific community of several disciplines of physics, biology, chemistry and medicine. The first part of this short review presents briefly the possible mechanism of interaction of electromagnetic fields in cellular level based in theoretical models and experimental results. The second part refers to experimental observations published by several authors about the potential cytotoxic and genotoxic effects of electromagnetic fields. Results of researches are no yet conclusive enough to accept or reject the genotoxic, carcinogenic or cytotoxic potential of these fields. Up to date the International Agency for Research on Cancer (IARC) has classified the X, gamma and ultraviolet radiation as carcinogenic and the fields generated by radio frequencies as possibly carcinogenic.

As a fundamental optical approach to interferometry, Sagnac interference has been widely used for reflection manipulation, precision measurements, and spectral engineering in optical systems. Compared to other interferometry configurations, it offers attractive advantages by yielding a reduced system complexity without the need for phase control between different pathways, thus offering a high degree of stability against external disturbance and a low wavelength dependence. The advance of integration fabrication techniques has enabled chip-scale Sagnac interferometers with greatly reduced footprint and improved scalability compared to more conventional approaches implemented by spatial light or optical fiber devices. This facilitates a variety of integrated photonic devices with bidirectional light propagation, showing new features and capabilities compared to unidirectional-light-propagation devices such as Mach-Zehnder interferometers (MZIs) and ring resonators (RRs). Here, we present our latest results for functional integrated photonic devices based on Sagnac interference. We outline the theory of integrated Sagnac interference devices with comparisons to other integrated photonic building blocks such as MZIs, RRs, photonic crystal cavities, and Bragg gratings. We present our latest results for Sagnac interference devices realized in integrated photonic chips, including reflection mirrors, optical gyroscopes, basic filters, wavelength (de)interleavers, and optical analogues of quantum physics.

The phenomena of electrical conductivity and electromigration in metallic systems are related, since in both cases the basic physical process is the scattering of conduction electrons by metal ions. Numerous searches have been made for equations connecting the conductivity with electromigration. In the case of a liquid metal, when using the Drude-Sommerfeld (DS) conduc-tivity equation, it was not possible to obtain a quantitative relationship between these phenomena, which would be correct. Attempts to find such a relationship when taking into ac-count the N. Mott correction (g - factor) in the DS equation were unsuccessful. This article proposes a different correction (b - factor) to the DS equation, which takes into account the pos-sibility of varying the momentum transferred by the conduction electron to a metal ion during the scattering. This correction allows to establish a quantitative relationship between conductivity and electromigration, as well as between electromigration in various binary systems with common components, in agreement with experiment. The proposed theory describes well, in particular, two- and multi-component metal systems of any concentration (the consistency rule for triangles A-B, B-C, C-A). The value of b - factor smoothly changes depending on the heat of vaporization of the metal, per unit volume.

This article analyzes local level normative regulations aimed at directly or indirectly conserving the urban landscape in rural areas. Using a discursive analysis methodology on regulatory documents being enforced in a series of localities assigned to a tourism promotion program, evidence suggests that promotional activity retroactively influences the phraseology of these municipal regulations. The results obtained point to the existence of perpetuating historicist approaches within the current regulations, which appear to largely derive from the search for success in the tourism market and the resulting benefits to the local economy.

When there is uncertainty in the value of parameters of the input random components of a stochastic simulation model, two-level nested simulation algorithms are used to estimate the expectation of performance variables of interest. In the outer level of the algorithm (n) observations are generated for the parameters, and in the inner level (m) observations of the simulation model are generated with the value of parameters fixed at the value generated in the outer level. In this article, we consider the case in which the observations at both levels of the algorithm are independent, showing how the variance of the observations can be decomposed into the sum of a parametric variance and a stochastic variance. Next, we derive central limit theorems that allow us to compute asymptotic confidence intervals to assess the accuracy of the simulation-based estimators for the point forecast and the variance components. Under this framework, we derive analytical expressions for the point forecast and the variance components of a Bayesian model to forecast sporadic demand; and we use these expressions to illustrate the validity of our theoretical results by performing simulation experiments using this forecast model.

Viruses frequently contain overlapping genes, which encode functionally unrelated proteins from the same DNA or RNA region but in different reading frames. Yet overlapping genes are often overlooked during genome annotation, in particular in DNA viruses. Here we looked for the presence of overlapping genes likely to encode a functional protein in human parvovirus B19 (genus erythroparvovirus), using an experimentally validated software, Synplot2. Synplot2 detected an open reading frame, X, conserved in all erythroparvoviruses, which overlaps the VP1 capsid gene, and is under highly significant selection pressure. In a related virus, human parvovirus (genus tetraparvovirus), Synplot2 also detected an open reading frame under highly significant selection pressure, ARF1, which overlaps the VP1 gene. X and ARF1 have exactly the same location (both overlap the region of VP1 encoding the phospholipase A2 domain), and encode proteins with similar predicted properties, such as a transmembrane region, strongly suggesting that they are homologous. These findings provide compelling evidence that the X protein must be expressed and functional. It is probably translated either from a polycistronic mRNA by a non-canonical mechanism, or from an unmapped monocistronic mRNA. Finally, we also discovered proteins predicted to be expressed from a frame overlapping VP1 in other species related to parvovirus B19: porcine parvovirus 2 (Z protein) and bovine parvovirus 3 (X-like protein).

RF photonic transversal signal processors, which combine reconfigurable electrical digital signal processing and high-bandwidth photonic processing, provide a powerful solution for achieving adaptive high-speed information processing. Recent progress in optical microcomb technology provides compelling multi-wavelength sources with compact footprint, yielding a variety of microcomb-based RF photonic transversal signal processors implemented by either discrete or integrated components. Although operating based on the same principle, processors in these two forms exhibit distinct performance. This letter presents a comparative investigation into their performance. First, we compare the performance of state-of-the-art processors, focusing on the processing accuracy. Next, we analyze various factors that contribute to the performance differences, including tap number and imperfect response of experimental components. Finally, we discuss the potential for future improvement. These results provide a comprehensive comparison of microcomb-based RF photonic transversal signal processors implemented using discrete and integrated components and provide insights for their future development.

Today, the most powerful approach to detect distant homologs of a protein is based on structure prediction and comparison. Yet this approach is still inapplicable to many viral proteins. Therefore, we developed a powerful sequence-based procedure to identify distant homologs of viral proteins. It relies on 3 main principles: 1) Traces of sequence similarity with a protein can persist beyond the significance cutoff of homology detection programs; 2) Candidate homologs can be identified among proteins with weak sequence similarity to the query, by using "contextual" information, e.g. taxonomy or type of host infected; 3) These candidate homologs can be validated using highly sensitive profile-profile comparison.As a test case, we applied our approach to a protein without known homologs, ORF4 of Lake Sinai virus (which infects bees). We discovered that ORF4 is composed of a domain that has homologs in proteins from >20 taxa of viruses infecting arthropods. We called it “Widespread, Intriguing, Versatile” (WIV) domain because it is found in proteins with a wide variety of domain organizations and functions. For example, WIV is encoded by the NSs protein of tospoviruses, a global threat to food security, which infect plants through arthropod vectors; by the protein encoded by RNA2 ORF1 of chronic bee paralysis virus, a widespread virus of bees; and by various proteins of cypoviruses, which infect the silkworm bombyx mori. WIV has a previously unknown structural fold, according to Alphafold predictions. In some viral species, WIV facilitates infection of arthropods, according to bibliographical evidence

This paper builds upon my earlier studies, in interpreting interculturally how the Kashmiri nondual Śaiva thinkers, Upaladeva (c. 900-950 CE) and Abhinavagupta (c. 950-1020 CE), in their Pratyabhijñā philosophical theology respond to and reinterpret the Buddhist semantic theory of reference as the exclusion of the inapplicable (anyāpoha). It engages the issues in the Pratyabhijñā debate with the Buddhists, with the interrelations of Claude Shannon and Warren Weaver’s theory of Information, de Saussurean structuralist semiotics and Peircean pragmatic semiotics.

A systematic study has been conducted on barbiturate complexes of all five alkali metals Li–Cs prepared from the metal carbonates or hydroxide in aqueous solution without other potential ligands present, varying the stoichiometric ratio of metal ion to barbituric acid (BAH). Eight polymeric compounds (two each for Na, K, and Rb and one each for Li and Cs) have been characterised by single-crystal X-ray diffraction. All contain some combination of barbiturate anion BA− (necessarily in a 1:1 ratio with the metal cation M+), barbituric acid, and water. All organic species and water molecules are coordinated to the metal centres via oxygen atoms as either terminal or bridging ligands. Coordination numbers range from 4 (for the Li complex) to 8 (for the Cs complex). Extensive hydrogen bonding plays a significant role in all the crystal structures, almost all of which include pairs of N–H…O hydrogen bonds linking BA− and/or BAH components into ribbons extending in one dimension. Factors influencing the structure adopted by each compound include cation size and reaction stoichiometry as well as hydrogen bonding.

Subjective paranormal experience (SPE) has been a notable part of the human historical narrative. Alleged miracles, telepathy, clairvoyance, precognition, witchcraft, spiritualism, monsters and ghosts have received a supernatural interpretation. The incidence and prevalence of reported SPE remains at high levels in all populations investigated to date. Previous research on SPE has focused on the cognitive and social factors that facilitate paranormal beliefs and experiences. I consider here developmental factors in the brain’s responses to trauma that appear to predispose certain individuals towards SPE. The theory draws upon the established mechanisms of dissociation and fantasy generation to describe and explain the origins of paranormal experience. The theory hypothesizes that childhood abuse and victimization trigger autonomic responses of dissociation, depersonalization and compartmentalization. Freezing and associated releases of fantasy serve as a survival strategy in the homeostatic regaining of safety and control. The predictions from the homeostasis theory are consistent with the findings of multiple studies and falsifying evidence has yet to be identified.

Organisms are adapted to each other and the environment, not as tradition would have it, because natural selection made them that way, but because there is inbuilt striving towards stability and equilibrium. A General Theory of Behaviour connects imagery, affect and action with the central executive system we call Consciousness. The General Theory is founded on the assumption that the primary motivation of all of Consciousness and intentional behaviour is Psychological Homeostasis. Psychological homeostasis is as important to the organisation of mind and behaviour as Physiological Homeostasis is to the organisation of bodily systems. Consciousness processes quasi-perceptual images independently of the input to the retina and sensorium. Consciousness is the “I-Am” control centre for integration and regulation of (my) thoughts, (my) feelings and (my) actions with (my) conscious mental imagery as foundation stones. Imagery vividness, a combination of clarity and liveliness, is essential to imagining, remembering, thinking, predicting, planning and acting. Assessment of vividness using introspective report is validated by objective means such as fMRI. A significant body of work shows that vividness of visual imagery is determined by the similarity of neural responses in imagery to those occurring in perception of actual objects and performance of activities. I am Conscious, therefore I am.

The City of Pasadena is located in southern California; a region which has a Mediterranean climate and where the vast majority of rainfall occurs between October and April with the period between January and March being the most intense. A significant amount of the local water supply comes from regional rainfall, therefore any changes in precipitation patterns in the area has considerable significance. HYPOTHESIS: Local climate change has been occurring in the Pasadena area over the last 100 years resulting in changes in air temperature and rainfall. AIR TEMPERATURES: Between 1886 and 2016 the air temperature in Pasadena, California has increased significantly, from a minimum of 23.8°C in the daytime and 8.1°C at night between 1911 and 1920 to 27.2°C and 13.3°C between 2011 and 2016. The increase in nighttime temperature was uniform throughout the year, however daytime temperatures showed more seasonal variation. There was little change in the daytime temperatures May through July but more change the rest of the year. For example, the median daytime temperature for June between 1911 and 1920 was 27.9°C but was 28.7°C between 2011 and 2016, a difference of 0.8°C. In contrast, for October for the same periods the median daytime temperatures were 25.6°C and 28.9°C, a difference of 3.3°C. RAINFALL: There has been a change in local rainfall pattern over the same period. In comparing rainfall between 1883 – 1949 and 1950 – 2016, there appeared to be less rainfall in the months of October, December, and April while other months seemed to show no change in rainfall. For example, between the two periods mentioned above, the median rainfall in October was 12.4 mm and 8.9 mm respectively while for December they were 68.6 mm and 40.4 mm. There was comparatively a smaller change in the median volume of rainfall in April (18.8 mm vs. 17.5 mm). However, between 1883 and 2016 there were 13 with less than 1 mm of rain, 12 of which occurred after 1961. In the same line of logic, no measureable amount of rain occurred for 23 Octobers, 15 of those occurred after 1961. CONCLUSION: As air temperatures increased over the last 100 years in the Pasadena area, rainfall may have decreased in October, December, and April.

Adeno-associated viruses (AAVs, genus dependoparvovirus) are promising gene therapy vectors. In strains AAV1-12, the capsid gene VP1 encodes a recently discovered protein, MAAP, in an overlapping frame. MAAP binds the cell membrane by an unknown mechanism. We discovered that MAAP is also encoded in bovine AAV and in porcine AAVs (which have shown promise for gene transfer into muscle tissues), in which it is probably translated from a non-canonical start codon. MAAP is predicted to be mostly disordered except for a predicted C-terminal, membrane-binding amphipathic α-helix. MAAP has a highly unusual composition. In particular, it lacks internal methionines, and is devoid of tyrosines in most strains. Unexpectedly, we discovered that the N-terminus of VP1 also lacks several amino acids. In all AAVs that encode MAAP, the first 200 aas of VP1 are devoid of internal methionines, probably owing to a selection against ATG codons that could prevent translation of MAAP and of capsid isoforms (VP2, VP3). The N-terminus of VP1 also lacks cysteines, likely to avoid the formation of disulfide bridges when it becomes exposed outside of the capsid during post-endocytic trafficking. Finally, the region common to VP1 and VP2 lacks tyrosine in the vast majority of AAVs that encode MAAP. Avoiding these "forbidden" aas in MAAP and VP1 when creating recombinant AAV capsids might increase the efficiency of capsid design. Conversely, the presence of "forbidden" aas in some rare strains probably indicates that they have unusual properties that could help us understand the viral cycle.

The objective of this study was to compare the pathogens and susceptibilities of the current automated rule-based technology (RBT) antibiogram with one manually collected through chart review with additional rules applied. This study was a 2-year, retrospective cohort study and included all bacterial cultures within the first 30 days from patients admitted to a single Burn Center. The current RBT antibiogram served as the control and new antibiogram versions were created using additional rules and compared to the control. Six-hundred fifty-seven patients were admitted (61% excluded for lack of cultures). Fifty-nine percent had at least one hospital acquired risk factor with over one-third having recent illicit drug use and one-third having a recent hospitalization. Of the 410 cultures included, 57% were Gram-negative and half were from wound infections. Sensitivities were significantly different when comparing manual and the RBT version after including factors, such as days since admission, presence of hospital acquired risk factors, or previous antibiotic courses. Recommended empiric Gram-negative antibiotics changed from double coverage to a single β-lactam with > 90% susceptibility. The susceptibilities between first and subsequent courses were dramatically different. Before developing an antibiogram or interpreting the output, it is important to consider which automated criteria are utilized, especially for units with extended lengths of stay.

3,4-dihydroxyphenylacetaldehyde (DOPAL) is the focus of the catecholaldehyde hypothesis for the pathogenesis of Parkinson disease and other Lewy body diseases. The catecholaldehyde is produced via oxidative deamination catalyzed by monoamine oxidase (MAO) acting on cytoplasmic dopamine. DOPAL is autotoxic, in that it can harm the same cells in which it is produced. Normally DOPAL is detoxified by aldehyde dehydrogenase (ALDH)-mediated conversion to 3,4-dihydroxyphenylacetic acid (DOPAC), which rapidly exits the neurons. Genetic, environmental, or drug-induced manipulations of ALDH that build up DOPAL promote catecholaminergic neurodegeneration. A concept derived from the catecholaldehyde hypothesis imputes deleterious interactions between DOPAL and the protein alpha-synuclein (S), a major component of Lewy bodies. DOPAL potently oligomerizes S, and S oligomers impede vesicular and mitochondrial functions, shifting the fate of cytoplasmic dopamine toward MAO-catalyzed formation of DOPAL—destabilizing vicious cycles. Direct and indirect effects of DOPAL and of DOPAL-induced misfolded proteins could “freeze” intra-neuronal reactions, plasticity of which is required for neuronal homeostasis. The extent to which DOPAL toxicity is mediated by interactions with S, and vice versa, are poorly understood. Because of numerous secondary effects such as augmented spontaneous oxidation of dopamine by MAO inhibition, there has been insufficient testing of the catecholaldehyde hypothesis in animal models. The clinical pathophysiological significance of genetics, emotional stress, environmental agents, and interactions with numerous proteins relevant to the catecholaldehyde hypothesis are matters for future research. The imposing complexity of intra-neuronal catecholamine metabolism seems to require a computational modeling approach to elucidate clinical pathogenetic mechanisms and devise pathophysiology-based, individualized treatments.

We present a modification of the logistic model of epidemics that takes into account the possibility that an epidemic can develop from multiple physically-distinct hot spots with a range of starting times. This produces an improved understanding of the time evolution of the COVID-19 epidemic taking place in the United States in the spring of 2020.

The rapid growth of the global wearable technologies market is projected to reach $61.30 billion by 2030 which reflects a shift towards personalised health monitoring embedded in everyday activities. This paper explores the potential of embroidered interdigitated transducer (IDT)-based sensors for non-invasive, continuous monitoring of human biomarkers, particularly glucose levels, in human sweat. The study employs innovative embroidery techniques to create flexible fabric-based sensors with gold-coated IDTs. Experimental results demonstrate the sensor’s capability to detect water droplets and glucose concentrations, showcasing promising applications for health monitoring. The embroidered IDT-based sensors offer a unique approach for seamless integration into clothing, paving the way for personalised, continuous health data capture.

Life on Earth evolved to accommodate the biochemical and biophysical boundary conditions of the planet millions of years ago. The former includes nutrients, water, and ability to synthesize other needed chemicals. The latter include the 1 g gravity of the planet, radiation, and the geomagnetic field (GMF)of the planet. How complex life forms have accommodated the GMF is not known in detail considering that Homo sapiens evolved a neuro system and a cardiovascular system that develops electromagnetic fields as part of their functioning. In addition, many proteins and physiologic processes utilize Fe ions, an ion that exhibits magnetic properties. Thus, complex organisms such as current humans generate magnetic fields, contain significant quantities of the Fe ion, and also respond to exogenous-supplied static and electromagnetic fields. Whether humans can store information in self-generated magnetic fields remains to be determined. Given the current body of literature, it remains somewhat unclear how Homo sapiens use exogenous magnetic fields to regulate function, and what can happen if the boundary condition of the GMF of Earth is no longer exerting an effect. Proposed deep space flights to destinations such as Mars will provide some insights as space flight could not have been anticipated by evolution. The results of such space flight “experiments” will provide new insights in the role of magnetic fields on human functioning. The outcomes may also have implications for those on Earth as magnetic field influences may play a role in developmental conditions such as autism and senescence-associated conditions such as dementia when integration of the biological and biophysical aspects of humans of humans are required for effective functioning. This review will discuss the involvement of magnetic fields on various normal and disturbed processes in humans while on Earth and then further discuss potential outcomes when the GMF is no longer available to impact host systems. Thus, the GMF of the Earth has been present throughout evolution but details of its role in human functions still remain to be elucidated.

Abstract: Increasing physical activity (PA) and personal and social values are two of the greatest demands in the current educational system. This study examined the effect of a hybrid pro-gramme based on the Personal and Social Responsibility Model and Gamification. A total of 58 students (13.89 years old, SD = 1.14) in two groups (Experimental and Control) participated dur-ing a complete academic year. Motivation, physical activity and sedentary behaviour were as-sessed though questionnaires. Physical fitness was evaluated using previously validated field tests. The results showed significant differences over time between EG and CG in afterschool physical activity (APA) at the weekend (p = 0.003), sedentary time (p = 0.04) and speed-agility (p = 0.04). There were no significant differences in motivation. Regarding the intervention, speed-agility (p = 0.000), strength (p = 0.000), agility (p = 0.000), cardiorespiratory fitness (p = 0.001), APA-weekend (p = 0.000), APA-week (p= 0.000) and sedentary time (p = 0.000) increased signifi-cantly in the EG. Speed-agility (p = 0.000), APA-weekend (p = 0.03) and sedentary time (p = 0.008) increased in the CG. The use of this hybrid program can be useful to produced improvements in physical fitness, physical activity and sedentary hevaviours. The use of a hybrid program based on teaching personal and social responsibility and gamification strategies, produced improvements in physical fitness, physical activity and sedentary behavior, but not in motivation variables. Further research is demanded in order to contrast this relevant findings due to the potential drawbacks and diversity found in the scientific literature among model-based practice.

Caribbean SIDS are among the most vulnerable to climate change which will have a disproportionate impact on local environments and economies. Whilst there is a growing literature on how Caribbean SIDS can adapt to become more resilient a question that has received little attention is with regard to migration as an unplanned response. It is recognised that events such as hurricanes and flooding can lead to internal relocation in the short term but societal responses to droughts through migration have not generally been investigated. This paper seeks to address this by considering the case of the island of Carriacou, part of the state of Grenada. Carriacou with its small population, limited land area and local economy, historically based on agriculture has had a high degree of migration. This is in part a response to limited economic opportunities. Environmental stress manifest through limited water availability, inappropriate land management and social conditions is likely to be exacerbated by climate change and variability. Resultant increases in the frequency and intensity of droughts, in the absence of proactive interventions, are likely to result in non-linear migration, both to Grenada itself and beyond.

Despite the efforts made to stop the tuberculosis (TB) epidemic, it still remains one of the leading causes of death from an infectious disease. Previous work in the group uncovered a new family of amides which showed promising activities against Mycobacterium tuberculosis. A closer look at the literature showed that these compounds are structurally related to the DNB family of DprE1 inhibitors, so, we decided to study a wide range of substituted amides and determine their activity, focusing on unexplored structures related to the dinitrobenzamides (DNB) found in the literature. To synthesize our library of compounds we started from 3,5-dinitrobenzoic acid to form the nitroaromatic core that is characteristic of the DNB’s, to which we then added linear or cyclic amine moieties. Additionally, the impact of terminal aromatic moieties was also assessed for some derivatives, via an ether, ester, or amide bond. In order to obtain the desired derivatives, multiple synthetic approaches were used, mainly focused on nucleophilic addition/elimination reactions, SN2 reactions and Mitsunobu reactions. The activity was impacted mainly by two structural features, the addition of an aromatic moiety as a terminal group and the type of the linker. The most interesting compounds exhibited activities comparable to isoniazid and DNB1. Computational studies were also performed aimed at understanding their possible interactions with DprE1. The most active compounds are a good starting point for further development, and we plan to study an extended family of compounds based in those structures.

Asthma is characterized by mucus abnormalities. Airway epithelial metaplasia results in changes in stored and secreted mucin and the production of a pathologic mucus gel. Mucus transport is impaired culminating in mucus plugging and airway obstruction, a major cause of morbidity in asthma. The polymeric mucins MUC5AC and MUC5B are integral components of airway mucus. MUC5AC and MUC5B gene expression is altered in asthma and recent work sheds light on their contribution to asthma pathogenesis. Herein we review our current understanding of the role of MUC5AC and MUC5B in mucus dysfunction in asthma.

The Arctic is a remote region that has become increasingly globalised yet remains extremely vulnerable to many risks. The COVID-19 pandemic presented new challenges to the region. Using the Search, Appraisal, Synthesis and Analysis (SALSA) approach to conduct a meta-synthesis of the academic and grey literature on the impacts of the pandemic, an assessment is conducted of the types of risks that have been presented by the COVID-19 pandemic, the scales, and the national response strategies for mitigating the risks. Two case studies are explored, Iceland and Greenland, island nations that exemplify the extremes of the Arctic and reliance on tourism, a sector that was nearly entirely suspended by the pandemic. An evaluative matrix is employed which combines five different scales of risk – nano, micro, meso, macro and cosmic – with a sustainability categorisation of impacts. The risks of the pandemic cut across the respective scale and categories, with the potential for macro-scale events (systemic risk) to unfold linked to economic spillover effects driven by the curtailment of tourism and various supply chain delays. Both Iceland and Greenland have exemplified risk mitigation strategies which prioritise health over wealth, very strictly in the case of the latter. Strict border controls and domestic restrictions have enabled Iceland and Greenland to have much lower case and death numbers than most nations. In addition, Iceland has led the way, globally, in terms of testing and accumulating scientific knowledge concerning the genetic sequencing of the virus. The academic contribution of the paper concerns its broadening of understanding concerning systemic risk, which extends beyond financial implications to includes sustainability dimensions. For policymakers and practitioners, the paper highlights successful risk mitigation and science-based measures that will be useful for any nation tackling a future pandemic, regardless of whether they are island states, Arctic nations or another country.

Owing to the growing concerns due to dwindling fossil fuel reserves, increasing energy demand and climate emergency, it is imperative to develop and deploy sustainable energy technologies to ensure future energy supply as well as transition to the net zero world. In this context, there is great potential in the biorefinery concept for supplying drop in biofuels in the form of biodiesel. Biodiesel as a fuel can certainly bridge the gap where electrification or the use of hydrogen is not feasible, for instance heavy vehicles, farm and marine transportation sector. However, biodiesel industry also leads to formation of large amount of crude glycerol as the byproduct. Crude glycerol due to presence of several impurities may not be a suitable feedstock for all high value products derived from glycerol but fits well with glycerol esterification for producing glycerol acetins, which have numerous applications. This review critically looks at the processes using nanostructured solid/liquid acid catalysts for glycerol esterification including the economic viability of the scale up.

In this paper, the authors seek to discuss some of the complexities involved in cross-cultural working in relation to the communication and management of pain in older people. Specifically, the paper addresses the culture construction of ageing and how pain is often constructed as a natural part of ageing. The authors also suggests that with the rise of the ideology of active-ageing many older people who are disabled or living in chronic pain, may feel a moral imperative to hide pain and ill-health. The discussion extends into looking at the impact of culture and the communication of pain, including specific idioms of distress, somaticize and the lay-management of pain through stoicism.

The fact that individuals are spatially close to each other in the urban environment increases the potential number of encounters between them. Thus, theoretically speaking, the probability of interaction and social intercourse among people increases as they get closer to each other spatially. This reduction in spatial distance and propensity for larger networks can offer advantages in lower communication and transaction costs. However, there is also the possibility of entropy in a single (organizational) urban subsystem, characterized by reduced spatial distances between individuals that can lead to more toxic outcomes and the possibility of generalized deconstruction in an urban system as a whole. The current paper considers, through a theoretical model and secondary data analysis, how reductions in spatial distance between individuals in urban business organizations can lead to withdrawals of energy through toxic forms of entropic citizenship behavior, and lead to the development of toxic organizations. Such toxic organizations can ‘infect’ the urban system and lead to systematic entropic urban deconstruction. Practical, implications for management of the theoretical explanatory heuristic of toxic forms of organizational entropy and toxic organizations are briefly discussed in the paper.

The purpose of the present study was to examine if 14 days of supplementation with a pine bark extract leading up to and following an exercise test would increase performance and reduce biomarkers associated with muscle damage, inflammation and oxidative stress. The study used a double-blind, placebo controlled, cross-over design. Participants ingested either 800mg pine bark extract or placebo for 14 days prior to the first exercise trial and for 2 days post-exercise. On the exercise day, participants submitted a pre-exercise blood sample, then completed a VO₂ peak test until volitional failure. A post-blood sample was collected 1 hour after completion of exercise. Participants returned at 24 & 48 hours after the exercise testing for measures of muscle pain in the lower body using an algometer. Participants then had a 7-day washout period before beginning to crossing over to the alternate treatment. Analysis via ordinal regression demonstrated a significant difference in oxidative stress in the pine bark extract group compared to placebo (ChiSq = 2.63; p = 0.05). The pine bark extract was effective at affording protection from oxidative stress post exercise. Further work should be undertaken to evaluate the findings with other exercise modes or in participants with known metabolic syndrome.

Calculating a minimum-time trajectory requires the solving of a boundary value problem resulting from invocation of necessary conditions of optimality to set up a set of ordinary differential equations to solve the trajectory between the initial position and desired ending position with set constraints on the path between the two. This manuscript expresses the minimum time optimum trajectory between a satellite in a geosynchronous orbit and a target set on earth’s surface utilizing a non-rotating earth centric coordinate system. Expressing motion in coordinates of rotating reference frames necessitates transformation between reference frames, and one such transformation is embodied in the Direction Cosine Matrices (DCM) formed by a sequence of three successive frame rotations. Rotation about the local wing of an aerospace vehicle is almost never the pitch angle, yet modern application of kinematics often assumes such (with accompanying angular error). The same assertion is usually true about the nature of roll and yaw angles. This manuscript evaluates which sequence is the most advantageous for an object starting in space and then travels through the atmosphere to a target on the Earth’s surface. Simulation precision (validated by the quaternion normalization condition) reveals the so-called 132 rotation is the most accurate with an average error of 0.14° and a computational time of 0.013 seconds: resulting in a 97.95% increase in accuracy over the ubiquitous 321 “aerospace” rotation sequence and a 99.84% increase over the so-called 313 “orbital” rotation sequence. Utilizing the proposed optimal trajectory candidate yields a total flight time of 2 hours, 34 minutes and 46 seconds, or an average velocity of 3.85 kilometers per second, while impacting the target with a velocity of 11.54 kilometers per second.

Exercise facilitates weight control, partly through effects on appetite regulation. Single bouts of exercise induce a short-term energy deficit without stimulating compensatory effects on appetite, whilst limited evidence suggests that exercise training may modify subjective and homeostatic mediators of appetite in directions associated with enhanced meal-induced satiety. However, large variability in responses exists between individuals. This article reviews the evidence relating to how adiposity, sex and habitual physical activity modulate exercise-induced appetite, energy intake and appetite-related hormone responses. The balance of evidence suggests that adiposity and sex do not modify appetite or energy intake responses to acute or chronic exercise interventions, but individuals with higher habitual physical activity levels may better adjust energy intake in response to energy balance perturbations. The effect of these individual characteristics and behaviours on appetite-related hormone responses to exercise remains equivocal. These findings support the continued promotion of exercise as a strategy for inducing short-term energy deficits irrespective of adiposity and sex, as well as the ability of exercise to positively influence energy balance over the longer term. Future well-controlled studies are required to further ascertain potential mediators of appetite responses to exercise.

Metals are particularly sensitive to some pollutant gases. Many museum showcases and store rooms present atmospheres that can corrode cultural heritage artefacts containing metals. Whilst numerous strategies have been reported to mitigate such situations, avoiding them is preferable. Several approaches to testing materials used in construction, fitting out or dressing are used. The relative merits and drawbacks will be discussed. Several parameters of the most widely used, the accelerated corrosion ‘Oddy’ test have been investigated. The influence of abrasive on subsequent corrosion of lead and copper coupons have been assessed. Quantification methods for tested coupons are reviewed. The influence of test duration and temperature were assessed through comparison with real life, long term experience of materials behaviour. Direct contact tests with the material tested touching the test material has been investigated. Several materials present in artefacts are known to potentially cause corrosion when enclosed with metals in other artefacts. A number of situations have been investigated with pollution and RH and some corrosion rate measurements. Ways to isolate artefacts or mitigate are explored and a decision support model has been developed.

In the event of an abrupt sunlight reduction scenario there is a time window that occurs between when food stores would likely run out for many countries (~6 months or less) and ~1 year when resilient foods are scaled up. A promising temporary resilient food is leaf protein concentrate (LPC). Although it is possible to extract LPC from tree biomass (e.g. leaves and needles), neither the yields nor the toxicity of the protein concentrates for humans from the most common tree species has been widely investigated. To help fill this knowledge gap, this study uses high-resolution mass spectrometry and an open source toolchain for non-targeted screening of toxins on five common North American coniferous species: Western Cedar, Douglas Fir, Ponderosa Pine, Western Hemlock, and Lodgepole Pine. The yields for LPC extraction from the conifers ranged from 1% to 7.5%. The toxicity screenings confirm that these trees may contain toxins that can be consumed in small amounts and additional studies including measuring the quantity of each toxin are needed. The results indicate that LPC is a promising candidate to be used as resilient food, but future work is needed before LPCs from conifers can be used as a wide-scale human food.

The electrocardiogram (ECG) was the first biomedical signal where digital signal processing techniques were extensively applied. By its own nature, the ECG is typically a sparse signal, composed of regular activations (the QRS complexes and other waveforms, like the P and T waves) and periods of inactivity (corresponding to isoelectric intervals, like the PQ or ST segments), plus noise and interferences. In this work, we describe an efficient method to construct an overcomplete and multi-scale dictionary for sparse ECG representation using waveforms recorded from real-world patients. Unlike most existing methods (which require multiple alternative iterations of the dictionary learning and sparse representation stages), the proposed approach learns the dictionary first, and then applies an efficient sparse inference algorithm to model the signal using the learnt dictionary. As a result, our method is much more efficient from a computational point of view than other existing methods, thus becoming amenable to deal with long recordings from multiple patients. Regarding the dictionary construction, we locate first all the QRS complexes in the training database, then we compute a single average waveform per patient, and finally we select the most representative waveforms (using a correlation-based approach) as the basic atoms that will be resampled to construct the multi-scale dictionary. Simulations on real-world records from Physionet's PTB database show the good performance of the proposed approach.

3D-printed models with high anatomic fidelity are an increasingly viable tool in simulation-based medical education. One advantage of 3D models is they provide enhanced tactile and spatial understanding of complex anatomy to develop technical skills used in minimally invasive procedures. We propose that 3D anatomical models can improve the development of Interventional Radiology vascular access skills – first described in the 1950s as the Seldinger Technique – for pre-clerkship medical students. Early adoption of 3D-printed technology in pre-clinical medical education can lead to improved student engagement and satisfaction when learning procedural techniques. This study involved creating a 3D model of the upper extremity vasculature from an anonymized CT angiogram, using it as a medical education tool for 31 pre-clinical medical students practicing the Seldinger Technique on a prefabricated venipuncture arm, and assessing student satisfaction with this form of learning. Overall, attendees responded positively to the incorporation of the 3D model in medical education to improve their anatomic understanding and application to the Seldinger Technique. These results indicate that the use of 3D models in simulation-based medical education can provide benefits to acquiring technical skills and the potential to decrease training costs without harming a patient.

Crisis environments, which are becoming systemic, pose significant challenges to smart government strategies. The paper aims to contribute to academic debate by proposing an analytical framework for examining the institutional capacities of smart government systems in addressing local crises. The paper focuses on the recent approach of robust governance and highlights a set of variables that promote effective smart government: contingency planning capacity, analytical capacity, organizational management capacity, and collaborative capacity. The study presents an analytical model for evaluating the robustness and effectiveness of local smart government systems in crises. One of the significant findings of this study has been the identification of critical indicators that inform institutional capacities of smart government systems. By analyzing these indicators, the proposed analytical framework provides a comprehensive approach to assess the preparedness of smart government systems in dealing with crises. Moreover, it can be used to benchmark the performance of local smart government systems in similar contexts and identify best practices for improving crisis management.

Foam concrete is a highly cellularized cementitious material that undergoes extensive plastic deformation when loaded to failure. Under compression, the foam structure gets progressively crushed at a steady stress stage such that a substantial amount of energy is dissipated. Understanding foam concrete crushing behavior is of special importance for its engineering applications such as energy absorber, but the current studies are insufficient to define material properties for design of field applications. This study characterizes the crushing strength and foam modulus of samples with penetration test and resonant frequency test, respectively. A four-phase crushing behavior is observed. The yield strength and plateau strength are identified to characterize the foam crushing. Using the experimental inputs, the modulus-strength constitutive equations are then established. These findings are useful for expanding the knowledge of normal concrete to studies on foam concrete, as well as design of applications.Foam concrete is a highly cellularized cementitious material that undergoes extensive plastic deformation when loaded to failure. Under compression, the foam structure gets progressively crushed at a steady stress stage such that a substantial amount of energy is dissipated. Understanding foam concrete crushing behavior is of special importance for its engineering applications such as energy absorber, but the current studies are insufficient to define material properties for design of field applications. This study characterizes the crushing strength and foam modulus of samples with penetration test and resonant frequency test, respectively. A four-phase crushing behavior is observed. The yield strength and plateau strength are identified to characterize the foam crushing. Using the experimental inputs, the modulus-strength constitutive equations are then established. These findings are useful for expanding the knowledge of normal concrete to studies on foam concrete, as well as design of applications.

Prevalence rates of anger and aggression are often higher in military personnel, so it is important to understand more about why this is and factors with which they are associated. Despite this, there is little evidence relating to anger and aggression in UK veterans who are seeking treatment for mental health difficulties such as PTSD. This study investigated the prevalence rates of anger and aggression in this population, as well as the associations between anger and aggression, and various sociodemographic, functioning and mental health variables. A cross-sectional design was used, with participants completing a battery of self-report questionnaires. Prevalence rates for significant anger and aggression were 74% and 28% respectively. Both women and those over 55 were less likely to report difficulties. Those with high levels of PTSD and other mental health difficulties were more likely to report anger and aggression. Other factors related to anger and aggression included childhood adversity; unemployment due to ill health; and a perceived lack of family support. Findings show that veterans who are seeking support for mental health are likely to experiencing significant difficulties with anger and aggression, especially if they have co-morbid mental health difficulties. The associations between anger and aggression and other variables has implications for the assessment and treatment of military veterans.

Landscape changes based on spectral responses allow showing plant cover changes through diversity, composition, and ecological connectivity. The spatial and temporal vegetation dynamics of the Bijagual Massif from 1986 to 2021 were analyzed as a measure of ecological integrity, conservation, and territory. The covers identified were high open forest (Hof), dense grassland of non-wooded mainland (Dgnm), a mosaic of pastures and crops (Mpc), lagoons (Lag), and bare and degraded lands (Bdl). The Bijagual Massif has 8,574.1 ha. In 1986, Dgnm occupied 42.6% of the total area, followed by Mpc (32.8%) and Hof (24.5%); by 2000, Mpc and Hof increased (43.7 and 28.1%, respectively), while Dgnm decreased (28%); by 2021, Dgnm was restricted to the northeastern zone and continued to decrease (25.2%), Mpc occupied 52.9%, Hof 21.7% and Bdl 0.1%. Of the three fractions of the connectivity probability index, only dPCintra and dPCflux contribute to ecological connectivity. Hof and Dgnm show patches with biota habitat quality and availability. Between 1986 and 2021, Dgnm lost 1,489 ha (41%) and Hof 239.5 ha (11%). Mpc replaced various covers (1,722.2 ha; 38%) in 2021. Bijagual has a valuable biodiversity potential limited by Mpc. Territorial planning and sustainable agroecological and ecotourism proposals are required due to the context of the ecosystems.

This paper examines the potential of Artificial Intelligence (AI) to address societal megatrends, with a specific focus on OpenAI’s Generative Pre-Trained Transformer 3 (GPT-3). To do this, we con-ducted an analysis using GPT-3 in order to explore the benefits of AI for digitalization, urbanization, globalization, climate change, automation and mobility, global health issues and aging population. We also looked at emerging markets as well as sustainability in this study. Interaction with GPT-3 was done solely through prompt questions and generated responses were analyzed. Our results indicate that AI can significantly improve our understanding of these trends by providing insights into how they develop over time and what solutions could be implemented. Further research is needed to determine how effective AI will be in addressing them successfully but initial findings are encouraging. Our discussion focuses on the implications of our findings for society going forward and suggests that further investigation should be done into how best to utilize new technologies like GPT-3 when tackling these challenges. Lastly, we conclude that while there is still much work left to do before any tangible effects can be seen from utilizing AI tools such as GPT-3 on societal mega-trends; early indications suggest it may have a positive impact if used correctly.

The Flack Parameter is now almost universally reported for all chiral materials characterized by X-ray crystallography. It’s elegantly simplicity was an inspired development by Flack, and although the original algorithm for its computation has been strengthened by other workers, it remains an essential outcome for any crystallographic structure determination. As with any one-parameter metric, it needs to be interpreted in the context of its standard uncertainty.

Purpose: While resultant maximal voluntary contraction (MVC) is commonly used to assess muscular performance, the simultaneous activation of antagonist muscles could dramatically underestimate the strength of the agonist muscles. While quantification of antagonist torque has been performed in plantar- (PF) and dorsi-flexion (DF) joint in isometric conditions, it has yet to be determined in anisometric (concentric and eccentric) conditions. Methods: The experiment was performed in 9 participants through 2 sessions (reliability). The MVCs in DF and PF were measured in isometric, concentric and eccentric conditions (10°.s^-1). Electromyographic (EMG) activities from the soleus, gastrocnemius medialis and lateralis, and tibialis anterior muscles were simultaneously recorded. The EMG biofeedback method was used to quantify antagonist torque, where participants were asked to maintain a level of EMG activity, corresponding to antagonist EMG activity and related to the muscle contraction type, according to a visual EMG bio-feedback displayed on a screen. Results: Resultant torque significantly underestimated agonist torque in DF MVC (30-65%) and to a lesser extent in PF MVC (3%). Triceps surae antagonist torque was significantly modified with muscle contraction type, showing higher antagonist torque in isometric (29 Nm) than eccentric (23 Nm, p < 0.001) and concentric (14 Nm, p < 0.001) conditions and resulting in modification of the DF MVC torque-velocity shape. The difference between DF eccentric and concentric MVC was attenuated when considered agonist torque (12%) rather than resultant torque (45%). Conclusion: Estimation of the antagonist torque in isometric or anisometric condition brings new insights to assessment of muscular performance and could result in costly misinterpretation in strength training and/or rehabilitation programs.

Accurate lithium battery diagnosis and prognosis is critical to increase penetration of electric vehicles and grid-tied storage systems. They are both complex due to the intricate, nonlinear, and path-dependent nature of battery degradation. Data-driven models are anticipated to play a significant role in the behavioral prediction of dynamical systems such as batteries. However, they are often limited by the amount of training data available. In this work, we generated the first big data comprehensive synthetic datasets to train diagnosis and prognosis algorithms. The proof-of-concept datasets are over three orders of magnitude larger than what is currently available in the literature. With benchmark datasets, results from different studies could be easily equated, and the performance of different algorithms can be compared, enhanced, and analyzed extensively. This will expend critical capabilities of current AI algorithms, tools, and techniques to predict scientific data.

The evaluation of geometric defects is necessary in order to maintain the integrity of structures over time. These assessments are designed to detect damages of structures and ideally help inspectors to estimate the remaining life of structures. Current methodologies for monitoring structural systems, while providing useful information about the current state of a structure, are limited in the monitoring of defects over time and in linking them to predictive simulation. This paper presents a new approach to the predictive modeling of geometric defects. A combination of segmented from point clouds are parametrized using the convex hull algorithm to extract features from detected defects, and a stochastic dynamic model is then adapted to these features to model the evolution of the hull over time. Describing a defect in terms of its parameterized hull enables consistent temporal tracking for predictive purposes, while implicitly reducing data dimensionality and complexity as well. In this study, 2D point clouds analogous to information derived from point clouds were first generated over simulated life-cycles. The evolutions of point cloud hull parameterizations were modeled as stochastic dynamical processes via autoregressive integrated moving average (ARIMA) and vectorized autoregression (VAR) and compared against ground truth. The results indicate that this convex hull approach provides consistent and accurate representations of defect evolution across a range of defect topologies and is reasonably robust to noisy measurements, however assumptions regarding the underlying dynamical process play a significant the role in predictive accuracy. The results were then validated on experimental data from fatigue testing with high accuracy. Longer term, the results of this work will support finite element model updating for predictive analysis of structural capacity.

Structural system design is the process of giving form to a set of interconnected components subjected to loads and design constraints while navigating a complex design space. While safe designs are relatively easy to develop, optimal designs are not. Modern computational optimization approaches employ population based metaheuristic algorithms to overcome challenges with the system design optimization landscape. However, the choice of the initial population, or ground structure, can have an outsized impact on the resulting optimization. This paper presents a new method of generating such ground structures, using a combination of topology optimization (TO) and a novel system extraction algorithm. Since TO generates monolithic structures, rather than systems, its use for structural system design and optimization has been limited. In this paper, truss systems are extracted from topologies through morphological analysis and artificial intelligence techniques. This algorithm, and its assessment, constitutes the key contributions of this paper. The structural systems obtained are compared with ground truth solutions to evaluate the performance of the algorithms. The generated structures are also compared against benchmark designs from the literature. The results indicate that the presented truss generation algorithm produces structures comparable to those generated through metaheuristic optimization, while mitigating the need for assumptions about initial ground structures.

Exoskeletons designed to assist patients with activities of daily living are becoming increasingly popular, but still are subject to research. In order to gather requirements for the design of such systems, long-term gait observation of the patients over the course of multiple days in an environment of daily living are required. In this paper a wearable all-in-one data acquisition system for collecting and storing biomechanical data in everyday life is proposed. The system is designed to be cost efficient and easy to use, using off-the-shelf components and a cloud server system for centralized data storage. The measurement accuracy of the system was verified, by measuring the angle of the human knee joint at walking speeds between 3 and 12 km/h in reference to an optical motion analysis system. The acquired data was uploaded to a cloud database via a smartphone application. Verification results showed that the proposed toolchain works as desired. The system reached an RMSE from 2.9° to 8°, which is below most of the comparable system. The system provides a powerful, scalable platform for collecting and processing biomechanical data, which can help to automize the generation of an extensive database for human kinematics.

Empirically based modeling is an essential aspect of design for a wave energy converter. These models are used in structural, mechanical and control design processes, as well as for performance prediction. The design of experiments and methods used to produce models from collected data have a strong impact on the quality of the model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followed for wave tank testing. The general system identification processes are shown to have a number of advantages. The experimental data is then used to produce multiple models for the dynamics of the device. These models are validated and their performance is compared against one and other. While most models of wave energy converters use a formulation with wave elevation as an input, this study shows that a model using a hull pressure sensor to incorporate the wave excitation phenomenon has better accuracy.

. This paper features an analysis of the relative effectiveness of a variety of methods of modelling Realised Volatility (RV), namely: the use of Gegenbaur processes in Auto-Regressive Moving Average format, GARMA, as opposed to Heterogenous Auto-Regressive HAR models and simple rules of thumb. The analysis is applied to two data sets that feature the RV of the S&P500 index, as sampled at 5 minute intervals, provided by the Oxford Man RV database. The GARMA model does perform slightly better than the HAR model, but both models are matched by a simple rule of thumb regression model based on the application of lags of squared, cubed and quartic, demeaned daily returns.

Individual susceptibility to pulmonary oxygen toxicity (PO2tox) is highly variable and currently lacks a reliable biomarker for predicting pulmonary hyperoxic stress. As nitric oxide (NO) is involved in many respiratory system processes and functions, we aimed to determine if expired nitric oxide (FENO) levels can provide an indication of PO2tox susceptibility in humans. Eight U.S. Navy trained divers volunteered as subjects. The hyperoxic exposures consisted of six- and eight-hour hyperbaric chamber dives conducted on consecutive days in which subjects breathed 100% oxygen at 202.65 kPa. Subjects’ individual variability in pulmonary function and FENO was measured twice daily over five days and compared with their post-dive values to assess susceptibility to PO2tox. Only subjects who showed no decrements in pulmonary function following the six-hour exposure conducted the eight-hour dive. FENO decreased by 55% immediately following the six-hour oxygen exposure (n=8, p<0.0001) and by 63% following the eight-hour exposure (n=4, p<0.0001). Four subjects showed significant decreases in pulmonary function immediately following the six-hour exposure. These subjects had the lowest baseline FENO and the lowest post-dive FENO and had clinical symptoms of PO2tox. Individuals with low FENO were the first to develop PO2tox symptoms and deficits in pulmonary function from the hyperoxic exposures. These data suggest that endogenous levels of NO in the lung may protect against the development of PO2tox.

Smallsats are becoming the predominant electro-optical Earth observation (EO) imaging platforms. While atmospheric correction of smallsat data enhances its utility, an established pathway to do so may constrain accuracy and utility. The alternative, Closed-form Method for Atmospheric Correction (CMAC), developed for smallsat application provides surface reflectance derived solely from scene statistics. In a prior paper, CMAC closely agreed with Land Surface Reflectance Code (LaSRC) software for correction of the four VNIR bands of Landsat-8/9 images for conditions of low to moderate atmospheric effect over quasi-invariant warehouse-industrial targets. Those results were accepted as surrogate surface reflectance to support analysis of CMAC and LaSRC reliability for surface reflectance retrieval in two contrasting environments: shortgrass prairie and barren desert. Reliability was defined and tested through a null hypothesis: the same top-of-atmosphere reflectance under the same atmospheric condition will provide the same estimate of surface reflectance. Evaluated against the prior surrogate surface reflectance, the results found decreasing error with increasing wavelength for both methods. From 58 comparisons across the four bands, LaSRC average absolute error ranged from 0.59% (NIR) to 50.30% (blue). CMAC error was well constrained from 0.01% (NIR) to 0.98% (blue) sustaining the null hypothesis for reliability.

Candida glabrata has thoroughly adapted to successfully colonize human mucosal membranes and survive in vivo pressures prior to and during antifungal treatment. Out of all the medically relevant Candida species, C. glabrata has emerged as a leading cause of azole, echinocandin, and multidrug (MDR: azole + echinocandin) adaptive resistance. Neither mechanism of resistance is intrinsic to C. glabrata, since stable genetic resistance depends on mutation of drug target genes, FKS1 and FKS2 (echinocandin resistance), and a transcription factor, PDR1, which controls expression of major drug transporters, such as CDR1 (azole resistance). However, another hallmark of C. glabrata is the ability to withstand drug pressure both in vitro and in vivo prior to stable ‘genetic escape’. Additionally, these resistance events can arise within individual patients, which underscores the importance of understanding how this fungus is adapting to its environment and to drug exposure in vivo. Here, we explore the evolution of echinocandin resistance as a multistep model that includes general cell stress, drug adaptation (tolerance), and genetic escape. The extensive genetic diversity reported in C. glabrata will be highlighted.

Artificial Intelligence (AI) experienced significant advancements in recent years, and its impact is already recognized across various industries. Yet, the rise of AI has led to a growing concern about its impact on meeting the Sustainable Development Goals (SDGs). The aim of this paper was to evaluate contributions and the potential impact of AI to sustainable development in the society domain. Furthermore, the study analyzed GPT-3 responses, as one of the largest language models developed by OpenAI, descriptively. We conducted a set of queries on the SDGs to gather infor-mation on GPT-3`s perceptions of AI impact on sustainable development. Analysis of GPT-3’s contribution potential towards the SDGs showcased its broad range of capabilities for contributing to the SDGs in areas such as education, health, and communication. The study findings provide valuable insights into the contributions of AI to sustainable development in the society domain and highlight the importance of proper regulations to promote the responsible use of AI for sustainable development. We plan subsequent research for effects on ecologic and economic domains of SDGs. We highlighted the potential for improvement in neural language processing skills of GPT-3 by avoiding imitating weak human writing styles with more mistakes in longer texts.

Standard evolutionary theory, supported by mathematical modelling of outbred, dispersed populations predicts that ageing is not an adaptation. We recently argued that in clonal, viscous populations, programmed organismal death could promote fitness through social benefits and has, in some organisms (e.g. Caenorhabditis elegans), evolved to shorten lifespan. Here we review previous adaptive death theory, including consumer sacrifice, biomass sacrifice, and defensive sacrifice types of altruistic adaptive death. In addition we discuss possible adaptive death in semelparous fish, coevolution of reproductive and adaptive death, and adaptive reproductive senescence in C. elegans. We also describe findings from recent tests for the existence of adaptive death in C. elegans using computer modelling. Such models have provided new insights into how trade-offs between fitness at the individual and colony levels mean that senescent changes can be selected traits. Exploring further the relationship between adaptive death and social interactions, we consider examples where adaptive death results more from action of kin than from self-destructive mechanisms and, to describe this, introduce the term adaptive killing of kin.

The study sought to gauge the impact of COVID-19 pandemic in unleashing digital transformation in the education sector in South Africa. In order to gauge the impact, the study tracked the rate at which the 4IR tools were used by various institutions during the COVID-19 lockdown. Data were obtained from secondary sources, mainly newspaper articles, magazines and peer-reviewed journals. The findings are that, in South Africa, during the lockdown, a variety of 4IR tools were unleashed from primary education to higher and tertiary education where educational activities switched to remote learning (online learning). These observations point to the fact that South Africa generally has, some pockets of excellence to drive the education sector into the 4IR, which has the potential to increase access. Access to education, particularly at a higher education level, has always been a challenge due to a limited number of spaces available. Much as this pandemic has brought with it massive human suffering across the globe, there is an opportunity to assess successes and failures of deployed technologies, costs associated with them, and scaling these technologies to improve access.

Part of philosophy is to subject assertions to critical scrutiny, clarifying exactly what the assertion is saying, its implications, and thus its direct plausibility. The goal is to ensure clarity, logical consistency, and rational argumentation in order to arrive at reasoned conclusions. A common problem is that arguments have missing implied premises that, unless explicitly stated, are mistakenly assumed to be true. Here we subject conclusions made regarding the SARS-CoV-2 pandemic to critical scrutiny, revealing their implied premises so that these premises can be explicitly examined and refuted. Specifically, we refute the conclusions that “no one is protected until everyone is protected” and “population lockdowns are required to protect those at high risk of adverse outcomes.” In the end, we argue for the conclusion that “an Emergency Management principles based response to the pandemic, compared to population-wide lockdowns, offers a way to prevent more adverse outcomes from COVID-19, better prevent overwhelmed healthcare, and prevent most of the collateral damage to the wellbeing of the population that has resulted from the lockdowns.”

Temporomandibular joint disorders (TMD) are characterized by their multifactorial etiology and pathogenesis. A 3-year prospective study was conducted in a Portuguese TMD department to study the prevalence of different TMD signs and symptoms and their association with risk factors and comorbidities. Five hundred ninety-five patients were included using an online database: EUROTMJ. Most patients were female (80.50 %), with a mean age of 38.20±15.73 years. The main complaints were temporomandibular joint (TMJ) clicking (13.26%), pain (12.49%), and masticatory muscle tension (12.15%). The main clinical findings were myalgia (74%), TMJ clicking (60-62%) and arthralgia (31-36%). Risk factors such as clenching (60%) and bruxism (30%) were positively associated with TMJ pain and myalgia. Orthodontic treatment (20%) and wisdom tooth removal (19%) were positively associated with TMJ clicking, while jaw trauma (6%) tracheal intubation (4%) and orthognathic surgery (1%) were positively associated with TMJ crepitus, limited man-dibular range of motion and TMJ pain, respectively. 42.88% of TMD patients had other associated chronic diseases, most of them were mental behavioral or neurodevelopmental disorders (33.76%), namely, anxiety (20%) and depression (13%). The authors also observed a positively association of mental disorders with the degree of TMJ pain and myalgia. Online database seems to be a relevant scientific instrument for healthcare providers who treat TMD. The authors expect that EUROTMJ database can serve as a milestone for other TMD departments.