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Nick K. Jones1,2*, Lucy Rivett1,2*, Chris Workman3, Mark Ferris3, Ashley Shaw1, Cambridge COVID-19 Collaboration1,4, Paul J. Lehner1,4, Rob Howes5, Giles Wright3, Nicholas J. Matheson1,4,6¶, Michael P. Weekes1,7¶1 Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK2 Clinical Microbiology & Public Health Laboratory, Public Health England, Cambridge, UK3 Occupational Health and Wellbeing, Cambridge Biomedical Campus, Cambridge, UK4 Cambridge Institute of Therapeutic Immunology & Infectious Disease, University of Cambridge, Cambridge, UK5 Cambridge COVID-19 Testing Centre and AstraZeneca, Anne Mclaren Building, Cambridge, UK6 NHS Blood and Transplant, Cambridge, UK7 Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK*Joint first authorship¶Joint last authorshipCorrespondence: [email protected] UK has initiated mass COVID-19 immunisation, with healthcare workers (HCWs) given early priority because of the potential for workplace exposure and risk of onward transmission to patients. The UK’s Joint Committee on Vaccination and Immunisation has recommended maximising the number of people vaccinated with first doses at the expense of early booster vaccinations, based on single dose efficacy against symptomatic COVID-19 disease.1-3At the time of writing, three COVID-19 vaccines have been granted emergency use authorisation in the UK, including the BNT162b2 mRNA COVID-19 vaccine (Pfizer-BioNTech). A vital outstanding question is whether this vaccine prevents or promotes asymptomatic SARS-CoV-2 infection, rather than symptomatic COVID-19 disease, because sub-clinical infection following vaccination could continue to drive transmission. This is especially important because many UK HCWs have received this vaccine, and nosocomial COVID-19 infection has been a persistent problem.Through the implementation of a 24 h-turnaround PCR-based comprehensive HCW screening programme at Cambridge University Hospitals NHS Foundation Trust (CUHNFT), we previously demonstrated the frequent presence of pauci- and asymptomatic infection amongst HCWs during the UK’s first wave of the COVID-19 pandemic.4 Here, we evaluate the effect of first-dose BNT162b2 vaccination on test positivity rates and cycle threshold (Ct) values in the asymptomatic arm of our programme, which now offers weekly screening to all staff.Vaccination of HCWs at CUHNFT began on 8th December 2020, with mass vaccination from 8th January 2021. Here, we analyse data from the two weeks spanning 18thto 31st January 2021, during which: (a) the prevalence of COVID-19 amongst HCWs remained approximately constant; and (b) we screened comparable numbers of vaccinated and unvaccinated HCWs. Over this period, 4,408 (week 1) and 4,411 (week 2) PCR tests were performed from individuals reporting well to work. We stratified HCWs <12 days or > 12 days post-vaccination because this was the point at which protection against symptomatic infection began to appear in phase III clinical trial.226/3,252 (0·80%) tests from unvaccinated HCWs were positive (Ct<36), compared to 13/3,535 (0·37%) from HCWs <12 days post-vaccination and 4/1,989 (0·20%) tests from HCWs ≥12 days post-vaccination (p=0·023 and p=0·004, respectively; Fisher’s exact test, Figure). This suggests a four-fold decrease in the risk of asymptomatic SARS-CoV-2 infection amongst HCWs ≥12 days post-vaccination, compared to unvaccinated HCWs, with an intermediate effect amongst HCWs <12 days post-vaccination.A marked reduction in infections was also seen when analyses were repeated with: (a) inclusion of HCWs testing positive through both the symptomatic and asymptomatic arms of the programme (56/3,282 (1·71%) unvaccinated vs 8/1,997 (0·40%) ≥12 days post-vaccination, 4·3-fold reduction, p=0·00001); (b) inclusion of PCR tests which were positive at the limit of detection (Ct>36, 42/3,268 (1·29%) vs 15/2,000 (0·75%), 1·7-fold reduction, p=0·075); and (c) extension of the period of analysis to include six weeks from December 28th to February 7th 2021 (113/14,083 (0·80%) vs 5/4,872 (0·10%), 7·8-fold reduction, p=1x10-9). In addition, the median Ct value of positive tests showed a non-significant trend towards increase between unvaccinated HCWs and HCWs > 12 days post-vaccination (23·3 to 30·3, Figure), suggesting that samples from vaccinated individuals had lower viral loads.We therefore provide real-world evidence for a high level of protection against asymptomatic SARS-CoV-2 infection after a single dose of BNT162b2 vaccine, at a time of predominant transmission of the UK COVID-19 variant of concern 202012/01 (lineage B.1.1.7), and amongst a population with a relatively low frequency of prior infection (7.2% antibody positive).5This work was funded by a Wellcome Senior Clinical Research Fellowship to MPW (108070/Z/15/Z), a Wellcome Principal Research Fellowship to PJL (210688/Z/18/Z), and an MRC Clinician Scientist Fellowship (MR/P008801/1) and NHSBT workpackage (WPA15-02) to NJM. Funding was also received from Addenbrooke’s Charitable Trust and the Cambridge Biomedical Research Centre. We also acknowledge contributions from all staff at CUHNFT Occupational Health and Wellbeing and the Cambridge COVID-19 Testing Centre.

Scene flow tracks the three-dimensional (3D) motion of each point in adjacent point clouds. It provides fundamental 3D motion perception for autonomous driving and server robot. Although the Red Green Blue Depth (RGBD) camera or Light Detection and Ranging (LiDAR) capture discrete 3D points in space, the objects and motions usually are continuous in the macro world. That is, the objects keep themselves consistent as they flow from the current frame to the next frame. Based on this insight, the Generative Adversarial Networks (GAN) is utilized to self-learn 3D scene flow with no need for ground truth. The fake point cloud of the second frame is synthesized from the predicted scene flow and the point cloud of the first frame. The adversarial training of the generator and discriminator is realized through synthesizing indistinguishable fake point cloud and discriminating the real point cloud and the synthesized fake point cloud. The experiments on Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) scene flow dataset show that our method realizes promising results without ground truth. Just as human, the proposed method can identify the similar local structures of two adjacent frames even without knowing the ground truth scene flow. Then, the local correspondence can be correctly estimated, and further the scene flow is correctly estimated.   Corresponding author(s) Email: [email protected]

Leukocyte differential test is a widely performed clinical procedure for screening infectious diseases. Existing hematology analyzers require labor-intensive work and a panel of expensive reagents. Here we report an artificial-intelligence enabled reagent-free imaging hematology analyzer (AIRFIHA) modality that can accurately classify subpopulations of leukocytes with minimal sample preparation. AIRFIHA is realized through training a two-step residual neural network using label-free images of isolated leukocytes acquired from a custom-built quantitative phase microscope. By leveraging the rich information contained in quantitative phase images, we not only achieved high accuracy in differentiating B and T lymphocytes, but also classified CD4 and CD8 cells, therefore outperforming the classification accuracy of most current hematology analyzers. We validated the performance of AIRFIHA in a randomly selected test set and cross-validated it across all blood donors. Owing to its easy operation, low cost, and accurate discerning capability of complex leukocyte subpopulations, we envision AIRFIHA is clinically translatable and can also be deployed in resource-limited settings, e.g., during pandemic situations for the rapid screening of infectious diseases.  Corresponding author(s) Email:    [email protected],  [email protected]

Tam Hunt [1], Jonathan SchoolerUniversity of California Santa Barbara Synchronization, harmonization, vibrations, or simply resonance in its most general sense seems to have an integral relationship with consciousness itself. One of the possible “neural correlates of consciousness” in mammalian brains is a combination of gamma, beta and theta synchrony. More broadly, we see similar kinds of resonance patterns in living and non-living structures of many types. What clues can resonance provide about the nature of consciousness more generally? This paper provides an overview of resonating structures in the fields of neuroscience, biology and physics and attempts to coalesce these data into a solution to what we see as the “easy part” of the Hard Problem, which is generally known as the “combination problem” or the “binding problem.” The combination problem asks: how do micro-conscious entities combine into a higher-level macro-consciousness? The proposed solution in the context of mammalian consciousness suggests that a shared resonance is what allows different parts of the brain to achieve a phase transition in the speed and bandwidth of information flows between the constituent parts. This phase transition allows for richer varieties of consciousness to arise, with the character and content of that consciousness in each moment determined by the particular set of constituent neurons. We also offer more general insights into the ontology of consciousness and suggest that consciousness manifests as a relatively smooth continuum of increasing richness in all physical processes, distinguishing our view from emergentist materialism. We refer to this approach as a (general) resonance theory of consciousness and offer some responses to Chalmers’ questions about the different kinds of “combination problem.”  At the heart of the universe is a steady, insistent beat: the sound of cycles in sync…. [T]hese feats of synchrony occur spontaneously, almost as if nature has an eerie yearning for order. Steven Strogatz, Sync: How Order Emerges From Chaos in the Universe, Nature and Daily Life (2003) If you want to find the secrets of the universe, think in terms of energy, frequency and vibration.Nikola Tesla (1942) I.               Introduction Is there an “easy part” and a “hard part” to the Hard Problem of consciousness? In this paper, we suggest that there is. The harder part is arriving at a philosophical position with respect to the relationship of matter and mind. This paper is about the “easy part” of the Hard Problem but we address the “hard part” briefly in this introduction.  We have both arrived, after much deliberation, at the position of panpsychism or panexperientialism (all matter has at least some associated mind/experience and vice versa). This is the view that all things and processes have both mental and physical aspects. Matter and mind are two sides of the same coin.  Panpsychism is one of many possible approaches that addresses the “hard part” of the Hard Problem. We adopt this position for all the reasons various authors have listed (Chalmers 1996, Griffin 1997, Hunt 2011, Goff 2017). This first step is particularly powerful if we adopt the Whiteheadian version of panpsychism (Whitehead 1929).  Reaching a position on this fundamental question of how mind relates to matter must be based on a “weight of plausibility” approach, rather than on definitive evidence, because establishing definitive evidence with respect to the presence of mind/experience is difficult. We must generally rely on examining various “behavioral correlates of consciousness” in judging whether entities other than ourselves are conscious – even with respect to other humans—since the only consciousness we can know with certainty is our own. Positing that matter and mind are two sides of the same coin explains the problem of consciousness insofar as it avoids the problems of emergence because under this approach consciousness doesn’t emerge. Consciousness is, rather, always present, at some level, even in the simplest of processes, but it “complexifies” as matter complexifies, and vice versa. Consciousness starts very simple and becomes more complex and rich under the right conditions, which in our proposed framework rely on resonance mechanisms. Matter and mind are two sides of the coin. Neither is primary; they are coequal.  We acknowledge the challenges of adopting this perspective, but encourage readers to consider the many compelling reasons to consider it that are reviewed elsewhere (Chalmers 1996, Griffin 1998, Hunt 2011, Goff 2017, Schooler, Schooler, & Hunt, 2011; Schooler, 2015).  Taking a position on the overarching ontology is the first step in addressing the Hard Problem. But this leads to the related questions: at what level of organization does consciousness reside in any particular process? Is a rock conscious? A chair? An ant? A bacterium? Or are only the smaller constituents, such as atoms or molecules, of these entities conscious? And if there is some degree of consciousness even in atoms and molecules, as panpsychism suggests (albeit of a very rudimentary nature, an important point to remember), how do these micro-conscious entities combine into the higher-level and obvious consciousness we witness in entities like humans and other mammals?  This set of questions is known as the “combination problem,” another now-classic problem in the philosophy of mind, and is what we describe here as the “easy part” of the Hard Problem. Our characterization of this part of the problem as “easy”[2] is, of course, more than a little tongue in cheek. The authors have discussed frequently with each other what part of the Hard Problem should be labeled the easier part and which the harder part. Regardless of the labels we choose, however, this paper focuses on our suggested solution to the combination problem.  Various solutions to the combination problem have been proposed but none have gained widespread acceptance. This paper further elaborates a proposed solution to the combination problem that we first described in Hunt 2011 and Schooler, Hunt, and Schooler 2011. The proposed solution rests on the idea of resonance, a shared vibratory frequency, which can also be called synchrony or field coherence. We will generally use resonance and “sync,” short for synchrony, interchangeably in this paper. We describe the approach as a general resonance theory of consciousness or just “general resonance theory” (GRT). GRT is a field theory of consciousness wherein the various specific fields associated with matter and energy are the seat of conscious awareness.  A summary of our approach appears in Appendix 1.  All things in our universe are constantly in motion, in process. Even objects that appear to be stationary are in fact vibrating, oscillating, resonating, at specific frequencies. So all things are actually processes. Resonance is a specific type of motion, characterized by synchronized oscillation between two states.  An interesting phenomenon occurs when different vibrating processes come into proximity: they will often start vibrating together at the same frequency. They “sync up,” sometimes in ways that can seem mysterious, and allow for richer and faster information and energy flows (Figure 1 offers a schematic). Examining this phenomenon leads to potentially deep insights about the nature of consciousness in both the human/mammalian context but also at a deeper ontological level.

Cannabis sativa is an extraordinarily versatile species. Hemp and its cousin marijuana, both C. sativa, have been used for millennia as a source of fibre, oil and for medicinal, spiritual and recreational purposes. Because the consumption of Cannabis can have psychoactive effects, the plant has been widely banned throughout the last century. In the past decade, evidence of its medicinal properties did lead to the relaxation of legislation in many countries around the world. Consequently, the genetics and development of Cannabis as well as Cannabis-derived products are the subject of renewed attention.Here, we review the biology of C. sativa, including recent insights from taxonomy, morphology and genomics, with an emphasis on the genetics of cannabinoid synthesis. Because the female Cannabis flower is of special interest as the site of cannabinoid synthesis, we explore flower development, flowering time well as the species’ unique sex determination system in detail. Furthermore, we outline the tremendous medicinal, engineering, and environmental opportunities that Cannabis bears. Together, the picture emerges that our understanding of Cannabis biology currently progresses at an unusual speed. A future challenge will be to preserve the multi-purpose nature of Cannabis, and to harness its medicinal properties and sustainability advantages simultaneously.

Quantum chemistry must evolve if it wants to fully leverage the benefits of the internet age, where the world wide web offers a vast tapestry of tools that enable users to communicate and interact with complex data at the speed and convenience of a button press. The Open Chemistry project has developed an open source framework that offers an end-to-end solution for producing, sharing, and visualizing quantum chemical data interactively on the web using an array of modern tools and approaches. These tools build on some of the best open source community projects such as Jupyter for interactive online notebooks, coupled with 3D accelerated visualization, state-of-the-art computational chemistry codes including NWChem and Psi4 and emerging machine learning and data mining tools such as ChemML and ANI. They offer flexible formats to import and export data, along with approaches to compare computational and experimental data.

This paper responds to one by Graham Martin and colleagues, who offered a critique of my previous publications on masks for the lay public in the Covid-19 pandemic. I address their charges that my co-authors and I had misapplied the precautionary principle; drawn conclusions that were not supported by empirical research; and failed to take account of potential harms. But before that, I remind Martin et al that the evidence on mask wearing goes beyond the contested trials and observational studies they place centre stage. I set out some key findings from basic science, epidemiology, mathematical modelling, case studies and natural experiments, and use this rich and diverse body of evidence as the backdrop for my rebuttal of their narrowly-framed objections. I challenge my critics’ apparent assumption that a particular kind of systematic review should be valorised over narrative and real-world evidence, since stories are crucial to both our scientific understanding and our moral imagination. I conclude by thanking my academic adversaries for the intellectual sparring match, but exhort them to remember our professional accountability to a society in crisis. It is time to lay straw men to rest and engage, scientifically and morally, with the dreadful tragedy that is unfolding across the world.

This Supporting information includes interactive plots, videos, and data captured while performing evaluation and validation experiments for our paper. 

The construct of wellbeing has been criticised as a neoliberal construction of western individualism that ignores wider systemic issues including increasing burden of chronic disease, widening inequality, concerns over environmental degradation and anthropogenic climate change. While these criticisms overlook recent developments, there remains a need for biopsychosocial models that extend theoretical grounding beyond individual wellbeing, incorporating overlapping contextual issues relating to community and environment. Our first GENIAL model \cite{Kemp_2017} provided a more expansive view of pathways to longevity in the context of individual health and wellbeing, emphasising bidirectional links to positive social ties and the impact of sociocultural factors. In this paper, we build on these ideas and propose GENIAL 2.0, focusing on intersecting individual-community-environmental contributions to health and wellbeing, and laying an evidence-based, theoretical framework on which future research and innovative therapeutic innovations could be based. We suggest that our transdisciplinary model of wellbeing - focusing on individual, community and environmental contributions to personal wellbeing - will help to move the research field forward. In reconceptualising wellbeing, GENIAL 2.0 bridges the gap between psychological science and population health health systems, and presents opportunities for enhancing the health and wellbeing of people living with chronic conditions. Implications for future generations including the very survival of our species are discussed.  

Floral plantings are promoted to foster ecological intensification of agriculture through provisioning of ecosystem services. However, a comprehensive assessment of the effectiveness of different floral plantings, their characteristics and consequences for crop yield across global regions is lacking. Here we quantified the impacts of flower strips and hedgerows on pest control and pollination services in adjacent crops using a global dataset of 529 sites. Flower strips, but not hedgerows, enhanced pest control services in adjacent fields by 16% on average. However, effects on crop pollination and yield were more variable. Our synthesis identifies several important drivers of variability in effectiveness of plantings: pollination services declined exponentially with distance from plantings, and perennial and older flower strips with higher flowering plant diversity enhanced pollination more effectively. These findings provide promising pathways to optimize floral plantings to more effectively contribute to ecosystem service delivery and ecological intensification of agriculture in the future.

Researchers' ability to accurately screen fossil and subfossil specimens for preservation of DNA and protein sequences remains limited. Thermal exposure and geologic age are usable proxies for sequence preservation on a broad scale but are of nominal use for specimens of similar depositional environments. Cell and tissue biomolecular histology is thus proposed as a novel proxy for determining sequence preservation potential of ancient specimens with improved accuracy. Biomolecular histology as a proxy is hypothesized to elucidate why fossils/subfossils of some depositional environments preserve sequences while others do not and to facilitate selection of ancient specimens for use in molecular studies.

IntroductionConsistent with World Health Organization (WHO) advice [1], UK Infection Protection Control guidance recommends that healthcare workers (HCWs) caring for patients with coronavirus disease 2019 (COVID-19) should use fluid resistant surgical masks type IIR (FRSMs) as respiratory protective equipment (RPE), unless aerosol generating procedures (AGPs) are being undertaken or are likely, when a filtering face piece 3 (FFP3) respirator should be used [2]. In a recent update, an FFP3 respirator is recommended if “an unacceptable risk of transmission remains following rigorous application of the hierarchy of control” [3]. Conversely, guidance from the Centers for Disease Control and Prevention (CDC) recommends that HCWs caring for patients with COVID-19 should use an N95 or higher level respirator [4]. WHO guidance suggests that a respirator, such as FFP3, may be used for HCWs in the absence of AGPs if availability or cost is not an issue [1].A recent systematic review undertaken for PHE concluded that: “patients with SARS-CoV-2 infection who are breathing, talking or coughing generate both respiratory droplets and aerosols, but FRSM (and where required, eye protection) are considered to provide adequate staff protection” [5]. Nevertheless, FFP3 respirators are more effective in preventing aerosol transmission than FRSMs, and observational data suggests that they may improve protection for HCWs [6]. It has therefore been suggested that respirators should be considered as a means of affording the best available protection [7], and some organisations have decided to provide FFP3 (or equivalent) respirators to HCWs caring for COVID-19 patients, despite a lack of mandate from local or national guidelines [8].Data from the HCW testing programme at Cambridge University Hospitals NHS Foundation Trust (CUHNFT) during the first wave of the UK severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic indicated a higher incidence of infection amongst HCWs caring for patients with COVID-19, compared with those who did not [9]. Subsequent studies have confirmed this observation [10, 11]. This disparity persisted at CUHNFT in December 2020, despite control measures consistent with PHE guidance and audits indicating good compliance. The CUHNFT infection control committee therefore implemented a change of RPE for staff on “red” (COVID-19) wards from FRSMs to FFP3 respirators. In this study, we analyse the incidence of SARS-CoV-2 infection in HCWs before and after this transition.

Context: Scientific research, increasingly reliant on data and computational analysis, confronts the challenge of integrating collaboration and data sharing across disciplines. Collaborative frameworks that support decentralized decision-making and knowledge-sharing are essential, yet integrating them into computational environments presents technical challenges, such as decentralized identity, user-centered policy-making, flexible asset management, automated provenance, and distributed collaborative workflow management. Solution: This study introduces a conceptual framework and its prototype implementation called Decentralized Virtual Research Environment (D-VRE). This approach enhances seamless, trusted data sharing and collaboration within research lifecycles. It incorporates custom sharing policies, secure asset management, collaborative workflows, and research activity tracking, all without centralized oversight. Evaluation: Demonstrated through a real-world case study in the CLARIFY project, the prototype of the decentralized virtual research environment proved effective in enabling advanced data sharing and collaborative scenarios, showcasing its adaptability in scientific research. Results: Integrated into JupyterLab, D-VRE supports custom collaboration agreements and smart contract-based automated execution on the Ethereum blockchain. This ensures secure, verifiable transactions and promotes trust and reliability in shared research findings. Contribution: D-VRE addresses barriers to scientific research collaboration and data sharing, offering a scalable and adaptable decentralized model. This model promotes a more inclusive, efficient, and trustworthy research ecosystem, paving the way for future advancements in virtual research environments.

Genetic analyses of host-specific parasites can elucidate the evolutionary histories and biological features of their hosts. Here, we used population-genomic analyses of ectoparasitic seal lice (Echinophthirius horridus) to shed light on the postglacial history of seals in the Arctic Ocean and the Baltic Sea region. One key question was the enigmatic origin of relict landlocked ringed seal populations in lakes Saimaa and Ladoga in northern Europe. We found that that lice of four postglacially diverged subspecies of the ringed seal (Pusa hispida) and Baltic gray seal (Halichoerus grypus), like their hosts, form genetically differentiated entities. Using coalescent-based demographic inference, we show that the sequence of divergences of the louse populations is consistent with the geological history of lake formation. In addition, local effective population sizes of the lice are generally proportional to the census sizes of their respective seal host populations. Genome-based reconstructions of long-term effective population sizes revealed clear differences among louse populations associated with gray vs. ringed seals, with apparent links to Pleistocene and Holocene climatic variation as well as to the isolation histories of ringed seal subspecies. Interestingly, our analyses also revealed ancient gene flow between the lice of Baltic gray and ringed seals, suggesting that the distributions of Baltic seals overlapped to a greater extent in the past than is the case today. Taken together, our results demonstrate how genomic information from specialized parasites with higher mutation and substitution rates than their hosts can potentially illuminate finer scale population genetic patterns than similar data from their hosts.

A document by Juan Añon-Hidalgo. Click on the document to view its contents.

Protein cis-regulatory elements (CREs) are regions that modulate the activity of a protein through intramolecular interactions. Kinases, pivotal enzymes in numerous biological processes, often undergo regulatory control via inhibitory interactions in cis. This study delves into the mechanisms of cis regulation in kinases mediated by CREs, employing a combined structural and sequence analysis. To accomplish this, we curated an extensive dataset of kinases featuring annotated CREs, organized into homolog families through multiple sequence alignments. Key molecular attributes, including disorder and secondary structure content, active and ATP-binding sites, post-translational modifications, and disease-associated mutations, were systematically mapped onto all sequences. Additionally, we explored the potential for conformational changes between active and inactive states. Finally, we explored the presence of these kinases within membraneless organelles and elucidated their functional roles therein. CREs display a continuum of structures, ranging from short disordered stretches to fully folded domains. The adaptability demonstrated by CREs in achieving the common goal of kinase inhibition spans from direct autoinhibitory interaction with the active site within the kinase domain, to CREs binding to an alternative site, inducing allosteric regulation revealing distinct types of inhibitory mechanisms, which we exemplify by archetypical representative systems. While this study provides a systematic approach to comprehend kinase CREs, further experimental investigations are imperative to unravel the complexity within distinct kinase families. The insights gleaned from this research lay the foundation for future studies aiming to decipher the molecular basis of kinase dysregulation, and explore potential therapeutic interventions.

The RETERO project develops new methods to Reduce, Replace and Refine (3R-principle) animal experiments for assessing the risk of harm to fish when passing through turbines or pumps. Since behavior of fish influences the mortality risk during turbine and pump passages, knowledge about species-specific behavior and its triggers are necessary. A primary objective of the RETERO project is the study of fish behavior in hydraulic conditions similar to turbine and pump intakes. Therefore, an experimental conduit was constructed at the Hubert-Engels Laboratory of Technische Universität Dresden (Germany) specifically for the RETERO project’s study on fish behavior, equipped with a 3D camera infrared tracking system. The conduit was designed to model hydraulic conditions typical for turbine and pump intakes. In the experimental setup the effects of flow velocities exceeding the maximum swim speed of fish, as well as spatial velocity gradients and illumination conditions, on the fish behavior are studied. The data from studies involving brown trout ( Salmo trutta) allow for an analysis of how these fish react to flow accelerations and velocities surpassing their sprint speed, using quantitative metrics for movement and activity. An initial evaluation of these experiments highlights the potential of this approach for further research.

In this paper, we present a new cutting plane method, a variant of Kelley’s cutting plane method. Since the new algorithm, termed a globally cutting hyperplanes algorithm, can solve a nonlinear optimization program we are motivated in this work to present the theory and illustrations. Earlier, authors have reported another variant of Kelley’s cutting plane method termed a sharp-cut algorithm. The new algorithm too is based on successive linear programming principle and has a convergence rate at par with the sharp-cut algorithm. The new algorithm was also able to find multiple optimum solutions by varying a parameter in the algorithm. Two test examples are solved using the algorithm. We then solve a two-point boundary value problem using the new algorithm for the first time. A challenging nonlinear optimization problem from Hock and Schittkowsky (1981) is solved next. Lastly, an application example of profit maximization of an alkylation plant is presented.

Amyloidosis are a group of diseases in which soluble proteins aggregate and deposit in fibrillar conformation extracellularly in tissues. The effectiveness of therapeutic strategies depends on the specific protein involved, being crucial to accurately determine its nature. Moreover, following the diagnosis, the search for the mutation within relatives allows the clinical advice. Here we report the precise diagnosis and explored the possible reasons of the structural pathogenicity. Whole exome sequencing and GATK calling pipeline were leveraged to characterize the protein variant present in a patient with kidney failure. Bioinformatics strategies were applied to suggest potential explanations of the variants aggregation. Our pipeline allowed the identification of a single point variant of fibrinogen Aα chain, which opened the possibility of curative transplantation. I n silico structural analysis, suggested that the pathogenicity of the variant may be attributed to a heightened susceptibility to yield a peptide prone to deposit as an oligomer with a β-sheet structure. Exploiting the comprehensive coverage of whole genome sequencing we managed to fill a vacant stage in the diagnosis of hereditary amyloidosis and to stimulate the advancement in biomedicine.

Background: It is necessary to evaluate the parental ability to achieve nutritional adequacy while avoiding allergens for children with food allergies (FA), yet this area is currently understudies. Our study aimed to develop and validate the Parental Self-Efficacy Scale for Dietary Management of Children with Food Allergies (PSED-FA). Methods: PSED-FA was developed through a literature review and semi-structured interviews, refined by a panel of five allergists and five dietitians, and validated using responses from caregivers of children with FA. The construction of the tool involved exploratory factor analysis (EFA), confirmatory factor analysis for model fit, and evaluation of internal consistency using Cronbach’s alpha. Convergent and divergent validity were assessed using the average variance extracted (AVE), maximum shared variance (MSV), and average shared variance (ASV). Results: Participants included nine focus interview groups, with 114 individuals in the validation group. Egg whites (55.2 %), tree nuts (35.2%), and peanuts (22.8%) were the most common allergens. The EFA identified three factors: preparing allergen-free meals, knowledge of nutrition management, and management of food restrictions. The goodness of fit of our model met all the criteria. The tool showed high internal consistency (overall Cronbach’s alpha: 0.902) and met the criteria for both convergent (AVE >0.5) and divergent validity (AVE >MSV and ASV). Conclusion: This study validated a reliable and effective tool for assessing parental self-efficacy in managing the dietary needs of children with FA. This tool can aid health professionals in evaluating parental confidence and identifying areas for improving dietary management in children with FA.

Background and Purpose Alzheimer’s disease (AD), a progressive neurological disorder that causes memory decline and cognitive dysfunction, increasingly threatens human health. Rehmanniae Radix Praeparata (RRP) is derived from the steamed or wine-steamed Scrophulariaceae plant, Rehmannia glutinosa Libosch. (RR). They show promise in the treatment of AD, yet the variations in medical components and their mechanisms of action against AD remain unclear. Experimental Approach This study initially used APP/PS1 mice as AD animal models and used UPLC-QE-MS/MS, network pharmacology, proteomics, 16S rRNA sequencing to investigate differences in the medical components and mechanisms of action of RR and RRP in treating AD. Results UPLC-QE-MS/MS screening revealed that ajugol was the effective medicinal component of RR for AD treatment, and isoacteoside was that of RRP. Integrated multi-omics analyses predicted the involvement of the neuroinflammatory pathway, apoptosis pathway, and autophagy pathway in the mechanisms of the two ingredients for AD treatment. Subsequent in vivo and in vitro experiments confirmed that RR and its active component, ajugol, primarily modulated TLR/NF-κB/NLRP3 neuroinflammatory pathway and Bcl-2/Bax/Cytochrome C/Caspase-3 apoptosis pathway, whereas RRP and its active component isoacteoside predominantly affected LC3-Ⅱ/P62/p-mTOR/mTOR autophagy pathway. These components collectively improved cognitive deficits in AD mice, reduced Aβ plaque deposition in brain tissue, and diminished BV2 microglial cell cytotoxicity in the inflammation model, thereby ameliorating the progression of AD. Conclusion This study systematically elucidated the distinctions in the medical components and biological mechanisms of RR and RRP in treating AD, revealing that the unique processing of TCM is key to its efficacy.

In this paper, we use a stochastic partial differential equation (SPDE) as a model for the density of a population under the influence of random external forces/stimuli given by the environment. We study statistical properties for two crucial parameters of the SPDE that describe the dynamic of the system. To do that we use the Galerkin projection to transform the problem, passing from the SPDE to a system of independent SDEs; in this manner, we are able to find the Maximum likelihood estimator of the parameters. We validate the method by using simulations of the SDEs. We prove consistency and asymptotic normality of the estimators; the latter is showed using the Malliavin-Stein method. We illustrate our results with numerical experiments.

Background: Mast cells are the major effector cells that mediate IgE-dependent allergic reactions via high-affinity IgE receptors. We sought to use integrated network analysis to identify genomic biomarkers associated with high response in IgE-mediated activation of primary human mast cells. Methods: Primary human mast cell cultures derived from a cohort of 262 normal donors were categorized into High, Average and Low responder groups according to their activation response profiles. Microarray analysis followed by qPCR was used to identify genes that were differentially expressed in different responder cultures in their baseline conditions. The data were analyzed by constructing personalized perturbed profile (PEEP). Results: Data derived from qPCR validation of 8 selected genes that exhibited differential expression in the High responder group showed extensive heterogeneity. For upregulated genes, construction of PEEP for each individual sample of all 3 responder groups revealed that High responders exhibited higher percentage of “perturbed” samples whose PEEP values lied outside the normal range of expression. Moreover, the integration of PEEP of 4 selected upregulated genes into distinct sets of combinatorial profiles demonstrated that the specific pattern of upregulated expression of these 4 genes, in a tandem combination, was observed exclusively among the High responders. Conclusion: PEEP analysis was used to integrate the PEEP of a set of signature genes to construct a distinct combinatorial gene expression pattern for each individual sample. Such combinatorial approach was useful in identifying a set of genomic biomarkers that are associated with high degranulation response in human mast cell cultures derived from the blood of a cohort of normal donors.

To solve the problem of high impedance line-to-ground fault (HILGF), a solution using isolation transformers for subnetwork divisions was previously implemented in the power distribution network. As a result of that, the network has been experiencing ferroresonance more often. We have furthered our understanding of the situation by modelling and simulations under the Power System Computer-Aided Design for Electromagnetic Transients and Direct Current (PSCAD/EMTDC) based on its real parameters. The ferroresonance originates from the network response to the HILGF clearing. Subnetwork division has certainly improved the network fault damping factor, but the line capacitance reduction it caused has exposed the system to ferroresonance. To mitigate the ferroresonance, high-frequency components are removed from the zero-sequence current using the morphological filter; then through edge detection, it is used as the input signal to the control module. The control module then takes the ferroresonance mitigation action intelligently. Testing this proposed solution has given promising results that testify to its effectiveness in real-time application.