Digital and circular technologies for climate-smart and sustainable agriculture: The case of Vietnamese coffee

\ua9 Published under licence by IOP Publishing Ltd.This comprehensive article addresses the pressing challenges confronting the global agriculture, primarily driven by climate change and resource constraints. With a focus on promoting climate-smart and sustainable agricultural practices, the study explores the transformative potential of emerging technologies, e.g., the innovative use of digital technologies like Internet of Things, Artificial Intelligence, and Blockchain, showcasing real-world examples of their benefits, and circular technologies, e.g., waste-to-value practices. The challenges of population growth, climate change, environmental impact, and the plight of smallholder farmers are elucidated. Climate-Smart Agriculture initiatives supported by the World Bank Group demonstrate practical efforts in addressing these challenges, aligning with sustainable development goals. Here, we introduce an innovative and smart agriculture (INNSA) platform for the creation and operation of sustainable coffee value chain in Vietnam as a case of study. Thought-provoking questions for future research conclude the review, encouraging interdisciplinary collaboration. In summary, this article provides a compelling case for adopting sustainable agricultural practices through digital and circular technologies, offering a roadmap for global agriculture\u27s transformation and resilience in the face of climate change

Derivation of marker gene signatures from human skin and their use in the interpretation trancriptional changes associated with dermatological disorders

Numerous studies have explored the altered transcriptional landscape associated with skin diseases to understand the nature of these disorders. However, data interpretation represents a significant challenge due to a lack of good maker sets for many of the specialised cell types that make up this tissue, whose composition may fundamentally alter during disease. Here we have sought to derive expression signatures that define the various cell types and structures that make up human skin, and demonstrate how they can be used to aid the interpretation of transcriptomic data derived from this organ. Two large normal skin transcriptomics datasets were identified, one RNA-seq (n = 578), the other microarray (n = 165), quality controlled and subjected separately to network-based analyses to identify clusters of robustly co-expressed genes. The biological significance of these clusters was then assigned using a combination of bioinformatics analyses, literature and expert review. After cross comparison between analyses, 20 gene signatures were defined. These include expression signatures for hair follicles, glands (sebaceous, sweat, apocrine), keratinocytes, melanocytes, endothelia, muscle, adipocytes, immune cells, and a number of pathway systems. Collectively we have named this resource SkinSig. SkinSig was then used in the analysis of transcriptomic datasets for 18 skin conditions, providing in-context interpretation of these data. For instance, conventional analysis has shown there to be a decrease in keratinisation and fatty metabolism with age; we more accurately define these changes to be due to loss of hair follicles and sebaceous glands. SkinSig also highlighted the over-/under-representation of various cell types in skin diseases, reflecting an influx in immune cells in inflammatory disorders and a relative reduction in other cell types. Overall, our analyses demonstrate the value of this new resource in defining the functional profile of skin cell types and appendages, and in improving the interpretation of disease data

Serotonin tranporter methylation and response to cognitive behaviour therapy in children with anxiety disorders

Anxiety disorders that are the most commonly occurring psychiatric disorders in childhood, are associated with a range of social and educational impairments and often continue into adulthood. Cognitive behaviour therapy (CBT) is an effective treatment option for the majority of cases, although up to 35-45% of children do not achieve remission. Recent research suggests that some genetic variants may be associated with a more beneficial response to psychological therapy. Epigenetic mechanisms such as DNA methylation work at the interface between genetic and environmental influences. Furthermore, epigenetic alterations at the serotonin transporter (SERT) promoter region have been associated with environmental influences such as stressful life experiences. In this study, we measured DNA methylation upstream of SERT in 116 children with an anxiety disorder, before and after receiving CBT. Change during treatment in percentage DNA methylation was significantly different in treatment responders vs nonresponders. This effect was driven by one CpG site in particular, at which responders increased in methylation, whereas nonresponders showed a decrease in DNA methylation. This is the first study to demonstrate differences in SERT methylation change in association with response to a purely psychological therapy. These findings confirm that biological changes occur alongside changes in symptomatology following a psychological therapy such as CBT

Genomic and vaccine preclinical studies reveal a novel mouse-adapted Helicobacter pylori model for the hpEastAsia genotype in Southeast Asia

\ua9 2024 Crown Copyright.Introduction. Helicobacter pylori infection is a major global health concern, linked to the development of various gastrointestinal diseases, including gastric cancer. To study the pathogenesis of H. pylori and develop effective intervention strategies, appropriate animal pathogen models that closely mimic human infection are essential. Gap statement. This study focuses on the understudied hpEastAsia genotype in Southeast Asia, a region marked by a high H. pylori infection rate. No mouse-adapted model strains has been reported previously. Moreover, it recognizes the urgent requirement for vaccines in developing countries, where overuse of antimicrobials is fuelling the emergence of resistance. Aim. This study aims to establish a novel mouse-adapted H. pylori model specific to the hpEastAsia genotype prevalent in Southeast Asia, focusing on comparative genomic and histopathological analysis of pathogens coupled with vaccine preclinical studies. Methodology. We collected and sequenced the whole genome of clinical strains of H. pylori from infected patients in Vietnam and performed comparative genomic analyses of H. pylori strains in Southeast Asia. In parallel, we conducted preclinical studies to assess the pathogenicity of the mouse-adapted H. pylori strain and the protective effect of a new spore-vectored vaccine candidate on male Mlac:ICR mice and the host immune response in a female C57BL/6 mouse model. Results. Genome sequencing and comparison revealed unique and common genetic signatures, antimicrobial resistance genes and virulence factors in strains HP22 and HP34; and supported clarithromycin-resistant HP34 as a representation of the hpEastAsia genotype in Vietnam and Southeast Asia. HP34-infected mice exhibited gastric inflammation, epithelial erosion and dysplastic changes that closely resembled the pathology observed in human H. pylori infection. Furthermore, comprehensive immunological characterization demonstrated a robust host immune response, including both mucosal and systemic immune responses. Oral vaccination with candidate vaccine formulations elicited a significant reduction in bacterial colonization in the model. Conclusion. Our findings demonstrate the successful development of a novel mouse-adapted H. pylori model for the hpEastAsia genotype in Vietnam and Southeast Asia. Our research highlights the distinctive genotype and pathogenicity of clinical H. pylori strains in the region, laying the foundation for targeted interventions to address this global health burden

Building robust prediction models for defective sensor data using Artificial Neural Networks

Predicting the health of components in complex dynamic systems such as an automobile poses numerous challenges. The primary aim of such predictive systems is to use the high-dimensional data acquired from different sensors and predict the state-of-health of a particular component, e.g., brake pad. The classical approach involves selecting a smaller set of relevant sensor signals using feature selection and using them to train a machine learning algorithm. However, this fails to address two prominent problems: (1) sensors are susceptible to failure when exposed to extreme conditions over a long periods of time; (2) sensors are electrical devices that can be affected by noise or electrical interference. Using the failed and noisy sensor signals as inputs largely reduce the prediction accuracy. To tackle this problem, it is advantageous to use the information from all sensor signals, so that the failure of one sensor can be compensated by another. In this work, we propose an Artificial Neural Network (ANN) based framework to exploit the information from a large number of signals. Secondly, our framework introduces a data augmentation approach to perform accurate predictions in spite of noisy signals. The plausibility of our framework is validated on real life industrial application from Robert Bosch GmbH.Comment: 16 pages, 7 figures. Currently under review. This research has obtained funding from the Electronic Components and Systems for European Leadership (ECSEL) Joint Undertaking, the framework programme for research and innovation Horizon 2020 (2014-2020) under grant agreement number 662189-MANTIS-2014-

Nonlinear thermoelectric response of quantum dots: renormalized dual fermions out of equilibrium

The thermoelectric transport properties of nanostructured devices continue to attract attention from theorists and experimentalist alike as the spatial confinement allows for a controlled approach to transport properties of correlated matter. Most of the existing work, however, focuses on thermoelectric transport in the linear regime despite the fact that the nonlinear conductance of correlated quantum dots has been studied in some detail throughout the last decade. Here, we review our recent work on the effect of particle-hole asymmetry on the nonlinear transport properties in the vicinity of the strong coupling limit of Kondo-correlated quantum dots and extend the underlying method, a renormalized superperturbation theory on the Keldysh contour, to the thermal conductance in the nonlinear regime. We determine the charge, energy, and heat current through the nanostructure and study the nonlinear transport coefficients, the entropy production, and the fate of the Wiedemann-Franz law in the non-thermal steady-state. Our approach is based on a renormalized perturbation theory in terms of dual fermions around the particle-hole symmetric strong-coupling limit.Comment: chapter contributed to 'New Materials for Thermoelectric Applications: Theory and Experiment' Springer Series: NATO Science for Peace and Security Series - B: Physics and Biophysics, Veljko Zlatic (Editor), Alex Hewson (Editor). ISBN: 978-9400749863 (2012

Daily antibiotic cost of nosocomial infections in a Turkish university hospital

BACKGROUND: Many studies associated nosocomial infections with increased hospital costs due to extra days in hospital, staff time, extra investigations and drug treatment. The cost of antibiotic treatment for these infections represents a significant part of hospital expenditure. This prospective observational study was designed to determine the daily antibiotic cost of nosocomial infections per infected adult patient in Akdeniz University Hospital. METHODS: All adult patients admitted to the ICUs between January 1, 2000, and June 30, 2003 who had only one nosocomial infection during their stay were included in the study. Infection sites and pathogens, antimicrobial treatment of patient and it's cost were recorded. Daily antibiotic costs were calculated per infected patient. RESULTS: Among the 8460 study patients, 817 (16.6%) developed 1407 episodes of nosocomial infection. Two hundred thirty three (2.7%) presented with only one nosocomial infection. Mean daily antibiotic cost was $89.64. Daily antibiotic cost was$99.02 for pneumonia, $94.32 for bloodstream infection,$94.31 for surgical site infection, $52.37 for urinary tract infection, and$162.35 for the other infections per patient. The treatment of Pseudomonas aeruginosa infections was the most expensive infection treated. Piperacillin-tazobactam and amikacin were the most prescribed antibiotics, and meropenem was the most expensive drug for treatment of the nosocomial infections in the ICU. CONCLUSIONS: Daily antibiotic cost of nosocomial infections is an important part of extra costs that should be reduced providing rational antibiotic usage in hospitals

The dimension of the space of R-places of certain rational function fields

We prove that the space $M(K(x,y))$ of $\mathbb R$-places of the field $K(x,y)$ of rational functions of two variables with coefficients in a totally Archimedean field $K$ has covering and integral dimensions \dim M(K(x,y))=\dim_\IZ M(K(x,y))=2 and the cohomological dimension $\dim_G M(K(x,y))=1$ for any Abelian 2-divisible coefficient group $G$.Comment: 8 page

HIV self-testing intervention experiences and kit usability: results from a qualitative study among men who have sex with men in the SELPHI (Self-Testing Public Health Intervention) randomized controlled trial in England and Wales.

OBJECTIVES: SELPHI (HIV Self-Testing Public Health Intervention) is the largest randomized controlled trial (RCT) of HIV self-testing (HIVST) in a high-income setting to date, and has recruited 10 000 men who have sex with men (cis- and transgender) and transgender women who have sex with men. This qualitative substudy aimed to explore how those utilizing self-tests experience HIVST and the implications for further intervention development and scale-up. This is the first qualitative study in Europe investigating experiences of HIVST among intervention users, and the first globally examining the experience of using blood-based HIVST. METHODS: Thirty-seven cisgender MSM SELPHI participants from across England and Wales were purposively recruited to the substudy, in which semi-structured interviews were used to explore testing history, HIVST experiences and intervention preferences. Interviews were audio-recorded, transcribed and analysed through a framework analysis. RESULTS: Men accessed the intervention because HIVST reduced barriers related to convenience, stigma and privacy concerns. Emotional responses had direct links to acceptability. Supportive intervention components increased engagement with testing and addressed supportive concerns. HIVST facilitated more frequent testing, with the potential to reduce sexually transmitted infection (STI) screening frequency. Substudy participants with an HIV-positive result (n = 2) linked to care promptly and reported very high acceptability. Minor adverse outcomes (n = 2; relationship discord and fainting) did not reduce acceptability. Ease of use difficulties were with the lancet and the test processing stage. CONCLUSIONS: Intervention components shaped acceptability, particularly in relation to overcoming a perceived lack of support. The intervention was broadly acceptable and usable; participants expressed an unexpected degree of enthusiasm for HIVST, including those with HIV-positive results and individuals with minor adverse outcomes