Search

Background: The European Union (EU) faces many health-related challenges. Burden of diseases information and the resulting trends over time are essential for health planning. This paper reports estimates of disease burden in the EU and individual 27 EU countries in 2019, and compares them with those in 2010. Methods: We used the Global Burden of Disease 2019 study estimates and 95% uncertainty intervals for the whole EU and each country to evaluate age-standardised death, years of life lost (YLLs), years lived with disability (YLDs) and disability-adjusted life years (DALYs) rates for Level 2 causes, as well as life expectancy and healthy life expectancy (HALE). Results: In 2019, the age-standardised death and DALY rates in the EU were 465.8 deaths and 20,251.0 DALYs per 100,000 inhabitants, respectively. Between 2010 and 2019, there were significant decreases in age-standardised death and YLL rates across EU countries. However, YLD rates remained mainly unchanged. The largest decreases in age-standardised DALY rates were observed for "HIV/AIDS and sexually transmitted diseases" and "transport injuries" (each -19%). "Diabetes and kidney diseases" showed a significant increase for age-standardised DALY rates across the EU (3.5%). In addition, "mental disorders" showed an increasing age-standardised YLL rate (14.5%). Conclusions: There was a clear trend towards improvement in the overall health status of the EU but with differences between countries. EU health policymakers need to address the burden of diseases, paying specific attention to causes such as mental disorders. There are many opportunities for mutual learning among otherwise similar countries with different patterns of disease.

Polyesters from furandicarboxylic acid derivatives, i.e., dimethyl 2,5-furandicarboxylate (2,5-DMFDCA) and 2,4-DMFDCA, show interesting properties among bio-based polymers. Another potential heteroaromatic monomer, 3,4-bis(hydroxymethyl)furan (3,4-BHMF), is often overlooked but holds promise for biopolymer synthesis. Cleaning and greening synthetic procedures, i.e., enzymatic polymerization, offer sustainable pathways. This study explores the Candida antarctica lipase B (CALB)-catalyzed copolymerization of 3,4-BHMF with furan dicarboxylate isomers and aliphatic diols. The furanic copolyesters (co-FPEs) with higher polymerization degrees are obtained using 2,4-isomer, indicating CALB’s preference. Material analysis revealed semicrystalline properties in all synthesized 2,5-FDCA-based co-FPEs, with multiple melting temperatures (Tm) from 53 to 124 °C and a glass-transition temperature (Tg) of 9-10 °C. 2,4-FDCA-based co-FPEs showed multiple Tm from 43 to 61 °C and Tg of −14 to 12 °C; one of them was amorphous. In addition, all co-FPEs showed a two-step decomposition profile, indicating aliphatic and semiaromatic segments in the polymer chains.

2,5-furandicarboxylic acid is an extremely appealing renewable chemical building block because of its potential to replace the petrochemical and industrially widespread terephthalic acid via the synthesis of poly(alkylene 2,5-furanoate)s (2,5-PAF). The recent interest in its structural isomer, 2,4-furandicarboxylic acid (2,4-FDCA), opened the study of poly(alkylene 2,4-furanoate)s (2,4-PAF). In this work, 2,4-FDCA was polymerized with linear glycols of increasing chain length, via a solvent-free polycondensation reaction, obtaining high molecular weight 2,4-PAF. Namely, poly(trimethylene 2,4-furanoate) (2,4-PTF), poly(pentamethylene 2,4-furanoate) (2,4-PPeF) and poly(hexamethylene 2,4-furanoate) (2,4-PHF). These polyesters were compression molded into films and subjected to NMR, GPC, WAXS, PLOM, TGA and DSC analyses. The functional properties for food packaging applications were evaluated by mechanical and gas permeability tests. 2,4-PAF had tunable mechanical properties, depending on the glycol used, and in some cases, the mechanical behavior of a thermoplastic elastomer and shape recovery after break. In particular, 2,4-PPeF had outstanding gas barrier properties, while DSC analyses on 2,4-PHF showed an endothermic phenomenon attributed to the isotropization of a partially-ordered phase: it was possible to demonstrate that this phase was disrupted during tensile tests and slowly recovered over time, at room temperature. Overall, the results offer new insights into the structure-property relationships of poly(alkylene 2,4-furanoate)s and display their great potential for the production of biobased, monomaterial, easily recyclable and sustainable food packaging.

Since 5-(hydroxymethyl)furfural (HMF) has been labelled as the “sleeping giant” of the bio-based platform-chemical realm, numerous investigations have been devoted to the exploitation of this versatile molecule and its endless chemical transformations into novel monomers for producing bio-based polymers. However, beyond 2,5-furandicarboxylic acid (2,5-FDCA), little attention has been devoted to key aspects that deserve being addressed before bringing forward other HMF-derivatives into the bio-based plastic market, i.e., procedures, scaling-up of the syntheses, products’ purification, physical-thermal properties, and above all green metrics (sustainability/greenness of procedures). This critical review focuses on the most investigated derivatives of HMF beyond 2,5-FDCA, assessing their exploitation as monomers for bio-based polymers. HMF-derived compounds have been classified according to their functionalities, i.e., aldehyde-, diol-, polyol-, amine-, acid-, ester-, carbonate-, acrylate-, and epoxy-based monomers. The related synthetic approaches are discussed, evaluating the sustainability of the procedures reported so far, based on green metrics such as the environmental factor (E-factor) and the process mass intensity (PMI). For each family of HMF derivatives, their use as monomers for the synthesis of bio-based polymers has been addressed, taking into consideration the efficiency of the polymerisation reactions, the physical-chemical and thermal properties of the resulting bio-based polymers, as well as their biodegradability if applicable. The overall picture that emerges is that much has been achieved for the synthesis of furan monomers; however, many obstacles still need to be overcome prior to massively introducing these compounds into the bio-based plastic market. Hopefully, the data reported in this review will shed light on the goals achieved so far, and on some critical issues that must still be tackled in the short- or medium-term for a more sustainable

Due to environmental concerns, there is a growing demand for more sustainable materials. As a result, the renewability of the raw materials and catalysts involved in production is important for rendering sustainable and circular polymers. Due to its environmentally friendly nature and high selectivity, enzymatic polymerization is a viable approach for producing such polymers. Recent developments in the field of biobased furan building blocks have led to renewed interest in 2,4-furandicarboxylic acid (2,4-FDCA) and 3,4-FDCA. Furthermore, far too little attention has been given to 2,5-bis(hydroxymethyl)furan (2,5-BHMF), another class of hetero-aromatic diol that can be derived from carbohydrates. These furan monomers are attractive due to their potential for producing novel biobased polyesters with interesting properties. To date, however, there has been little discussion about the use of these materials for polymerization via enzymatic approaches. Hence, a comparative study of CALB-catalyzed copolymerization involving two FDCA dimethyl ester isomers, either 2,4- or 3,4-DMFDCA, with 2,5-BHMF and various aliphatic diols has been carried out. This provides further insight into the regioselectivity promoted by CALB for asymmetrical 2,4-DMFDCA over symmetrical 3,4-DMFDCA. This is evidenced by the high degree of polymerization achieved with a weight-average molecular weight of up to 14 kg mol−1. In agreement with previous findings, a preference for the formation of cyclic species from symmetrical monomers catalyzed by CALB was observed. Structural characterization and thermal and crystallinity analyses were used to assess the correlation between structure and material properties.

Centrifugal compressors are widely used in turbocharged powertrains for Heavy-Duty applications. The volute of the centrifugal compressors is generally of the overhung type. The design of volutes is often neglected, and the shape of the volute is dictated by the packaging requirements of the engine. However, with the advent of Hydrogen-based propulsion systems, the efficiency of all the components of the centrifugal compressor stage is important in order to achieve a higher efficiency at the stage level and also to understand the contribution of the volute towards stage performance. Measuring static pressure and total pressure inside and at the exit of the volute is a challenging task due to the complex nature of the flow inside an overhung volute. This study involves an experimental campaign to quantify the volute performance using static and total pressure measurements at different locations on the volute. The total pressure measurements were carried out using calibrated rotating Kiel probes to quantify the flow angles and the corresponding total pressure values. This enabled the measurement of the maximum total pressure value at a location for a given operating condition. These total pressures and static pressures were measured for a variety of operating conditions across the entire compressor map at the inlet and exit of the volute. In addition, two new parameters were introduced, a fictive area ratio and uniformity index that could be used to quantify volute performance and also help match the volute to a given diffuser and impeller configuration., Part of ISBN 9780791888018QC 20240926

This paper deals with the component level breakdown of performance characteristics of a centrifugal compressor using detailed measurements. The compressor stage used for Heavy-Duty applications consisting of the impeller, vaneless diffuser, and volute has been experimentally tested in a gas stand. Several static pressure measurements combined with total pressure and temperature measurements on the compressor stage have been carried out. Based on the detailed measurements, the component level aerothermal performance parameters are calculated on the entire compressor map that includes tip speeds from subsonic to supersonic speeds. The effect of individual component performance characteristics and their impact on the design of the entire stage is discussed both at design and off-design conditions. A better understanding of the component level performance aids to design of a compressor stage for increased efficiency, range, and better surge margin. However, this component-level detailed breakdown of the compressor stage for HD truck application is unavailable in open literature. In addition to the detailed measurements, a 1D model of the impeller is created to correlate measurements with predictions iteratively to identify the relevant 1D modeling parameters for varied tip speeds on the compressor map., QC 20240820

PURPOSE: Recently, handgrip, knee extensor and respiratory muscle strength were proposed as candidate biomarkers to assess the neuromuscular function of vitality capacity in older persons. This umbrella review aims to provide an overview of the available instruments and their measurement properties to assess these biomarkers. METHODS: The databases PubMed, Web of Science and Embase were systematically screened for systematic reviews and meta-analyses reporting on handgrip, knee extensor or respiratory muscle strength assessments, resulting in 7,555 articles. The COSMIN checklist was used to appraise psychometric properties and the AMSTAR for assessing methodological quality. RESULTS: Twenty-seven systematic reviews were included in this study. Some of the identified reviews described the psychometric properties of the assessment tools. We found five assessment tools that can be used to measure neuromuscular function in the context of healthy ageing. Those are the handheld dynamometer for handgrip strength, the dynamometer for knee extensor strength and regarding respiratory muscle strength, the sniff nasal inspiratory pressure, maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP). CONCLUSION: The handheld dynamometer for hand grip strength, the dynamometer for knee extensor strength, sniff nasal inspiratory pressure, MIP and MEP were identified. Therefore, these assessments could be used to identify community-dwelling older adults at risk for a declined neuromuscular function in the context of vitality capacity.

In this letter, we propose a PIPE-CovNet+ model that is ba-sed on convolutional neural networks (CNNs) with multiple kernel sizes, gradient boosting techniques, and hyper-densely connected layers for abnormality detection in wastewater pipe infrastructure. The PIPE-CovNet+ model achieved 85% accuracy and 84% F1-score following assessment utilizing an open-source dataset, overcoming the constraints of imbalanced data and over-fitting issues. Furthermore, it showed greater efficacy when compared against other relevant models, displaying 3% higher accuracy and F1-score than our prior work under ideal test settings. Installing PIPE-CovNet+ into a robot system can alleviate the limitations of being tedious, laborious, and prone to human error in closed-circuit television (CCTV) inspections.

Corrosion of concrete wastewater pipes is a major problem for water utilities around the world. Internal pipe coatings for protecting wastewater pipes from corrosion-related structural damage are viewed as a low-cost alternative to the expensive process of replacing pipes. The coatings are, however, susceptible to defects owing to acids produced by microbes that dwell on pipe walls. Therefore, water utilities are keen on assessing the state of acid permeation of internal pipe coatings on a regular basis to ensure the coating's long-term performance. Current standard practice for evaluating acid permeation is to collect core samples from the pipe and analyze them in a lab, which is costly, and labor intensive. In this paper, we propose an improved method for accessing acid permeation conditions of cement-based pipe coatings within hostile wastewater pipes using real-time pH measurements. Field experiments were carried out within a real wastewater pipe owned by Sydney Water in Australia. Sensor measurements of three different coatings were obtained, and the results were compared to the benchmark values. Overall, the proposed sensing method improves the current practice (core sampling) of acid permeation assessments of wastewater pipe coatings.

Many indoor robots operate in environments designed to support human activities. Understanding probable human actions in such surroundings is crucial for facilitating better human-robot interactions. This article presents an innovative approach to map unseen human actions in indoor environments by leveraging spatial affordances learned from geometric features extracted from point clouds captured by 3D cameras. Instead of directly observing real people to understand human context, the method utilizes virtual human models and their interactions with the environment to uncover hidden human affordances. This approach proves to be efficient for learning the affordance map, even when dealing with highly imbalanced datasets. To achieve this, we employ a supervised learning model optimized for the F1 score, using the Structured-SVM (S-SVM) architecture. We conducted experiments with actual 3D scenes, evaluating various affordance types both qualitatively and quantitatively. The results show that the proposed S-SVM-based method outperforms other models, demonstrating its effectiveness in efficiently mapping human context in indoor environments. The S-SVM-based method outperformed other models, demonstrating efficient human context mapping in indoor environments.

The text also presents many case studies of robotic systems developed for real-world applications in maintaining various civil infrastructures, including steel bridges, tunnels, underground water mains, underwater structures, and sewer ...

As awareness of the environmental impact of fossil-based polymers grows, the demand for biobased alternatives rises. In this context, combining eco-friendly synthesis techniques with renewable resources is important to produce polymers efficiently and sustainably. Furandicarboxylic acid (FDCA) is one of the key building blocks for producing biobased polymers. However, most studies predominantly focus on 2,5-FDCA, while FDCA encompasses other noteworthy isomers, namely, 2,4- and 3,4-FDCA. The polymers derived from these two isomers have recently gained attention due to their promising properties. In this study, an environmentally friendly approach for producing biobased polyesters from 2,5-, 2,4-, and 3,4-FDCA dimethyl ester isomers is proposed. The synthesis is conducted under greener conditions, utilizing Candida antarctica lipase B (CALB) enzyme as a biocatalyst. The performance of the enzyme is assessed, revealing CALB preference for polymerizing 2,5-FDCA over 2,4- and 3,4-FDCA dimethyl ester, which is elucidated by docking analysis. Moreover, CALB shows varying rates of cyclic oligomer formation for each isomer, favoring 2,5-FDCA cyclization. The structure-property relationship, encompassing the variation in isomeric structure, is evaluated through structural characterization, thermal analysis, and surface properties. This study primarily emphasized enzymatic polymerization and highlighted its versatility in accommodating different monomer isomeric substitutions.

Application developers advertise their Apps by creating product pages with App images, and bidding on search terms. It is then crucial for App images to be highly relevant with the search terms. Solutions to this problem require an image-text matching model to predict the quality of the match between the chosen image and the search terms. In this work, we present a novel approach to matching an App image to search terms based on fine-tuning a pre-trained LXMERT model. We show that compared to the CLIP model and a baseline using a Transformer model for search terms, and a ResNet model for images, we significantly improve the matching accuracy. We evaluate our approach using two sets of labels: advertiser associated (image, search term) pairs for a given application, and human ratings for the relevance between (image, search term) pairs. Our approach achieves 0.96 AUC score for advertiser associated ground truth, outperforming the transformer+ResNet baseline and the fine-tuned CLIP model by 8% and 14%. For human labeled ground truth, our approach achieves 0.95 AUC score, outperforming the transformer+ResNet baseline and the fine-tuned CLIP model by 16% and 17%.

Researchers must stay current in their fields by regularly reviewing academic literature, a task complicated by the daily publication of thousands of papers. Traditional multi-label text classification methods often ignore semantic relationships and fail to address the inherent class imbalances. This paper introduces a novel approach using the SciBERT model and CNNs to systematically categorize academic abstracts from the Elsevier OA CC-BY corpus. We use a multi-segment input strategy that processes abstracts, body text, titles, and keywords obtained via BERT topic modeling through SciBERT. Here, the [CLS] token embeddings capture the contextual representation of each segment, concatenated and processed through a CNN. The CNN uses convolution and pooling to enhance feature extraction and reduce dimensionality, optimizing the data for classification. Additionally, we incorporate class weights based on label frequency to address the class imbalance, significantly improving the classification F1 score and enhancing text classification systems and literature review efficiency.

Background: In 2016, the World Health Assembly adopted the resolution to eliminate viral hepatitis by 2030. This study aims to provide an overview of the burdens of hepatitis B virus (HBV) and hepatitis C virus (HCV) in Europe and their changes from 2010 to 2019 using estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods: We used GBD 2019 estimates of the burden associated with HBV-related and HCV-related diseases: acute hepatitis, cirrhosis and other chronic liver diseases, and liver cancer. We report total numbers and age-standardised rates per 100 000 for mortality, prevalence, incidence, and disability-adjusted life-years (DALYs) from 2010 to 2019. For each HBV-related and HCV-related disease and each measure, we analysed temporal changes and percentage changes for the 2010–19 period. Findings: In 2019, across all age groups, there were an estimated 2·08 million (95% uncertainty interval [UI] 1·66 to 2·54) incident cases of acute hepatitis B and 0·49 million (0·42 to 0·57) of hepatitis C in Europe. There were an estimated 8·24 million (7·56 to 8·88) prevalent cases of HBV-related cirrhosis and 11·87 million (9·77 to 14·41) of HCV-related cirrhosis, with 24·92 thousand (19·86 to 31·03) deaths due to HBV-related cirrhosis and 36·89 thousand (29·94 to 45·56) deaths due to HCV-related cirrhosis. Deaths were estimated at 9·00 thousand (6·88 to 11·62) due to HBV-related liver cancer and 23·07 thousand (18·95 to 27·31) due to HCV-related liver cancer. Between 2010 and 2019, the age-standardised incidence rate of acute hepatitis B decreased (–22·14% [95% UI –35·44 to –5·98]) as did its age-standardised mortality rate (–33·27% [–43·03 to –25·49]); the age-standardised prevalence rate (–20·60% [–22·09 to –19·10]) and mortality rate (–33·19% [–37·82 to –28·13]) of HBV-related cirrhosis also decreased in this time period. The age-standardised incidence rate of acute hepatitis C decreased by 3·24% (1·17 to 5·02) and its age-standa

The rapid, global spread of COVID-19, and the measures intended to limit or slow its propagation, are having major impacts on diverse sectors of society. Notably, these impacts are occurring in the context of other anthropogenic-driven threats including global climate change. Both anthropogenic stressors and the COVID-19 pandemic represent significant economic challenges to aquaculture systems across the globe, threatening the supply chain of one of the most important sources of animal protein, with potential disproportionate impacts on vulnerable communities. A web survey was conducted in 47 countries in the midst of the COVID-19 pandemic to assess how aquaculture activities have been affected by the pandemic, and to explore how these impacts compare to those from climate change. A positive correlation between the effects of the two categories of drivers was detected, but analysis suggests that the pandemic and the anthropogenic stressors affect different parts of the supply chain. The immediate measurable reported losses varied with aquaculture typology (land vs. marine, and intensive vs. extensive). A comparably lower impact on farmers reporting the use of integrated multitrophic aquaculture (IMTA) methods suggests that IMTA might enhance resilience to multiple stressors by providing different market options under the COVID-19 pandemic. Results emphasize the importance of assessing detrimental effects of COVID-19 under a multiple stressor lens, focusing on areas that have already locally experienced economic loss due to anthropogenic stressors in the last decade. Holistic policies that simultaneously address other ongoing anthropogenic stressors, rather than focusing solely on the acute impacts of COVID-19, are needed to maximize the long-term resilience of the aquaculture sector.

A compressor map with variations in component level characteristics is introduced. This novel approach to plot component level characteristics identify and give context to the critical design parameters such as flow angles, pressure coefficients, and loss coefficients across the entire compressor map along with the conventional performance parameters. Compressor design involves a significant amount of CFD at a stage level, but the decisive importance of component performance, design and analysis are many times overshadowed by 3D CFD, both steady RANS and unsteady RANS/LES/DES. Although the authors support the development of high-fidelity computational tools, validating these computational results with experimental measurements is essential. A detailed analysis of the Scania's in-house designed compressor stage tested in the Scania Gas stand shows that in order to create an optimal design, component level performance assessment is necessary for the impeller, diffuser and volute. The variation of performance parameters along a speed line and across varied tip speeds are shown along with indications for the onset of instabilities at a component level. This is a crucial input for the design of a compressor stage. In addition to detailed analysis of experimental results, this work includes predictions from two different CFD solvers and discussion of deviations between them. Both the CFD solvers can be used to predict performance parameters at a stage level for most parts of the map. For operating conditions close to surge and higher tip speeds (565 m/s), there are major deviations in the CFD solvers' predictions. The impeller pressure rise and efficiency could be predicted well with the CFD solvers for most of the tip speeds. However, deviations between measurements and predictions increase with increasing tip speeds. The diffuser performance is predicted well by one of the solvers. The other solver underpredicts the diffuser and overpredicts the volute performance. Thes, Part of ISBN 9780791887035QC 20231204

Regular inspection of multibillion dollar wastewater pipe infrastructure is crucial to any city around the globe. Traditional processes of inspection are laborious, time-consuming, and prone to human errors, such as the manual assessment of video and image sources obtained by closed-circuit television (CCTV). These limitations can be circumvented through the utilization of novel deep learning techniques. In this letter, we propose the PIPE-CovNet model, leveraging a convolutional neural network for automatic pipe surface abnormality detection. The proposed deep learning framework was trained and evaluated on a publicly accessible dataset. Evaluation results indicate the PIPE-CovNet achieves 82% accuracy and F1-score 0.82. In addition, the PIPE-CovNet outperformed other comparable deep learning models in terms of accuracy by at least 5% and F1-score by at minimum 8%.

In this paper, we propose a reconfigurable intelligent surface (RIS) that can dynamically switch the transmission and reflection phase of incident electromagnetic waves in real time to realize the dual-beam or quad-beam and convert the polarization of the transmitted beam. Such surfaces can redirect a wireless signal at will to establish robust connectivity when the designated line-of-sight channel is disturbed, thereby enhancing the performance of wireless communication systems by creating an intelligent radio environment. When integrated with a sensing element, they are integral to performing joint detection and communication functions in future wireless sensor networks. In this work, we first analyze the scattering performance of a reconfigurable unit element and then design a RIS. The dynamic field scattering manipulation capability of the RIS is validated by full-wave electromagnetic simulations to realize six different functions. The scattering characteristics of the proposed unit element, which incorporates two p-i-n diodes have been substantiated through practical implementation. This involved the construction of a simple prototype and the subsequent examination of its scattering properties via the free-space measurement method. The obtained transmission and reflection coefficients from the measurements are in agreement with the anticipated outcomes from simulations.

The gut microbiota impacts systemic levels of multiple metabolites including NAD+ precursors through diverse pathways. Nicotinamide riboside (NR) is an NAD+ precursor capable of regulating mammalian cellular metabolism. Some bacterial families express the NR-specific transporter, PnuC. We hypothesized that dietary NR supplementation would modify the gut microbiota across intestinal sections. We determined the effects of 12 weeks of NR supplementation on the microbiota composition of intestinal segments of high-fat diet-fed (HFD) rats. We also explored the effects of 12 weeks of NR supplementation on the gut microbiota in humans and mice. In rats, NR reduced fat mass and tended to decrease body weight. Interestingly, NR increased fat and energy absorption but only in HFD-fed rats. Moreover, 16S rRNA gene sequencing analysis of intestinal and fecal samples revealed an increased abundance of species within Erysipelotrichaceae and Ruminococcaceae families in response to NR. PnuC-positive bacterial strains within these families showed an increased growth rate when supplemented with NR. The abundance of species within the Lachnospiraceae family decreased in response to HFD irrespective of NR. Alpha and beta diversity and bacterial composition of the human fecal microbiota were unaltered by NR, but in mice, the fecal abundance of species within Lachnospiraceae increased while abundances of Parasutterella and Bacteroides dorei species decreased in response to NR. In conclusion, oral NR altered the gut microbiota in rats and mice, but not in humans. In addition, NR attenuated body fat mass gain in rats, and increased fat and energy absorption in the HFD context.

Clostridioides difficile infection (CDI) is a major health concern and one of the leading causes of hospital-acquired diarrhea in many countries. C. difficile infection is challenging to treat as C. difficile is resistant to multiple antibiotics. Alternative solutions are needed as conventional treatment with broad-spectrum antibiotics often leads to recurrent CDI. Recent studies have shown that specific microbiota-based therapeutics such as bile acids (BAs) are promising approaches to treat CDI. Clostridium scindens encodes the bile acid-induced (bai) operon that carries out 7-alpha-dehydroxylation of liver-derived primary BAs to secondary BAs. This biotransformation is thought to increase the antibacterial effects of BAs on C. difficile. Here, we used an automated multistage fermentor to study the antibacterial actions of C. scindens and BAs on C. difficile in the presence/absence of a gut microbial community derived from healthy human donor fecal microbiota. We observed that C. scindens inhibited C. difficile growth when the medium was supplemented with primary BAs. Transcriptomic analysis indicated upregulation of C. scindens bai operon and suppressed expression of C. difficile exotoxins that mediate CDI. We also observed BA-independent antibacterial activity of the secretome from C. scindens cultured overnight in a medium without supplementary primary BAs, which suppressed growth and exotoxin expression in C. difficile mono-culture. Further investigation of the molecular basis of our observation could lead to a more specific treatment for CDI than current approaches.

There is an urgent requisite for an improvement of the white leg shrimp Litopenaeus vannamei health related indices and immunity due to the emerging diseases. Recently, probiotics have been playing an important role in L. vannamei health management. Therefore, the current pond trail was to evaluate the probiotic proficiency of commercial probiotic product of THIONIL (THIO) on enhancement of the water, soil, growth, digestibility, survival, immune related indices and susceptibility of L. vannamei pond level trials. The study was carried out in the major shrimp culturing regions of Kavali, Nellore and Ponneri, Tamil Nadu, India. The experimental L. vannamei was divided into seven groups (1Lacks/ha), such as, negative control (THIO 0% - untreated), positive control (challenge with vibriosis) 2%, 4%, 6%, 8%, and 10% of THIO was encapsulated with commercial feed (CP Aqua). Bioassays were carried out in different day intervals includes, 0, 5, 25, 50, 100 and 123 for evaluating the productivity, anti-vibrio activity, digestive enzyme for digestibility, histological, immunological indices, and cytotoxicity in Artemia nauplii. The significant differences were observed in the increased growth (35.71 g/ shrimp) and digestive parameters in 10% THIO-fed shrimp, however, the other THIO-fed shrimp groups were also showed notable growth compared with control group. The results revealed that, the gill, hepatopancreas and gastro intestine have ha lesser tissue damage in 10% THIO when compared with control. The 10% THIO fed exhibited resistant potential against Vibrio parahaemolyticus (0.008 × 104 cfu/g) (AHPND-Acute Hepatopancreatic Necrosis Disease) and Vibrio harveyi (0.051×105 cfu/g) (Vibriosis). Additionally, 10% THIO fed shrimp revealed significant enhancement of immune related parameters when compared with control. In conclusion the results documented the THIO treatment shrimp had significant enhancement in the water and soil quality growth, strengthens the innate immunity and

Young women with Neurofibromatosis type 1 (NF1) have a high risk of developing breast cancer and poorer survival following breast cancer diagnosis. International guidelines recommend commencing breast screening between 30 and 35 years; however, the optimal screening modality is unestablished, and previous reports suggest that breast imaging may be complicated by the presence of intramammary and cutaneous neurofibromas (cNFs). The aim of this study was to explore potential barriers to implementation of breast screening for young women with NF1.Twenty-seven women (30-47 years) with NF1 completed breast screening with breast MRI, mammogram and breast ultrasound. Nineteen probably benign/suspicious lesions were detected across 14 women. Despite the presence of breast cNFs, initial biopsy rate for participants with NF1 (37%), were comparable to a BRCA pathogenic variant (PV) cohort (25%) (P = 0.311). No cancers or intramammary neurofibromas were identified. Most participants (89%) returned for second round screening.The presence of cNF did not affect clinician confidence in 3D mammogram interpretation, although increasing breast density, frequently seen in young women, impeded confidence for 2D and 3D mammogram. Moderate or marked background parenchymal enhancement on MRI was higher in the NF1 cohort (70.4%) than BRCA PV carriers (47.3%), which is an independent risk factor for breast cancer.Breast MRI was the preferred mode of screening over mammogram, as the majority (85%) with NF1 demonstrated breast density (BI-RADS 3C/4D), which hinders mammogram interpretation. For those with high breast density and high cNF breast coverage, 3D rather than 2D mammogram is preferred, if MRI is unavailable.

If marine organisms are to persist through the Anthropocene, they will need to be resilient, but what is resilience, and can resilience of marine organisms build within a single lifetime or over generations? The aim of this review is to evaluate the resilience capacity of marine animals in a time of unprecedented global climate change. Resilience is the capacity of an ecosystem, society, or organism to recover from stress. Marine organisms can build resilience to climate change through phenotypic plasticity or adaptation. Phenotypic plasticity involves phenotypic changes in physiology, morphology, or behaviour which improve the response of an organism in a new environment without altering their genotype. Adaptation is an evolutionary longer process, occurring over many generations and involves the selection of tolerant genotypes which shift the average phenotype within a population towards the fitness peak. Research on resilience of marine organisms has concentrated on responses to specific species and single climate change stressors. It is unknown whether phenotypic plasticity and adaptation of marine organisms including molluscs, echinoderms, polychaetes, crustaceans, corals, and fish will be rapid enough for the pace of climate change.

In vitro studies of synthetic gut microbial communities (SGMCs) can provide valuable insights into the ecological structure and function of gut microbiota. However, the importance of the quantitative composition of an SGMC inoculum and its effect on the eventual stable in vitro microbial community has not been studied. To address this, we constructed two 114-member SGMCs differing only in their quantitative composition-one reflecting the average human fecal microbiome and another mixed in equal proportions based on cell counts. We inoculated each in an automated anaerobic multi-stage in vitro gut fermentor simulating two different colonic conditions, mimicking proximal and distal colons. We replicated this setup with two different nutrient media, periodically sampled the cultures for 27 days, and profiled their microbiome compositions using 16S rRNA gene amplicon sequencing. While nutrient medium explained 36% of the variance in microbiome composition, initial inoculum composition failed to show a statistically significant effect. Under all four conditions, paired fecal and equal SGMC inoculums converged to reach stable community compositions resembling each other. Our results have broad implications for simplifying in vitro SGMC investigations. IMPORTANCE In vitro cultivation of synthetic gut microbial communities (SGMCs) can provide valuable insights into the ecological structure and function of gut microbiota. However, it is currently not known whether the quantitative composition of the initial inoculum can influence the eventual stable in vitro community structure. Hence, using two SGMC inoculums consisting of 114 unique species mixed in either equal proportions (Eq inoculum) or resembling proportions in an average human fecal microbiome (Fec inoculum), we show that initial inoculum compositions did not influence the final stable community structure in a multi-stage in vitro gut fermentor. Under two different nutrient media and two different colon conditions

Soil moisture is a significant hydrological component that is dynamic in nature. The variation in soil moisture in the basin scale would affect the vegetation, ecology and environment. Soil moisture trend analysis aids in providing the variation of soil moisture over the basin. The present study aimed to analyse the soil moisture trend in Lower Bhavani basin, Tamil Nadu from 2003-2022. Satellite-based soil moisture Global Land Data Assimilation System (GLDAS) data was extracted from the Google Earth Engine (GEE) platform to analyse the variation and trend over the period of time. The highest and lowest soil moisture was observed during monsoon and summer months and its percentage variation was studied. Using Man-Kendall test and Sen’s slope, trend analysis was calculated for two decades (2003-2012 and 2013-2022). In 2003-2012, an increasing trend of soil moisture was observed during winter (October to February); from 2013-2022, an increasing trend was observed during both winter (October to February) and monsoon seasons (June to September). The remaining season did not follow any trend, and there was no decreasing trend in soil moisture. The trend analysis of the study will help to monitor and manage the environmental system across the Lower Bhavani basin.

The gut microbiota impacts systemic levels of multiple metabolites including NAD + precursors through diverse pathways. Nicotinamide riboside (NR) is an NAD + precursor capable of regulating mammalian cellular metabolism. Some bacterial families express the NR-specific transporter, PnuC. We hypothesized that dietary NR supplementation would modify the gut microbiota across intestinal sections. We determined the effects of 12 weeks of NR supplementation on the microbiota composition of intestinal segments of high-fat diet-fed (HFD) rats. We also explored the effects of 12 weeks of NR supplementation on the gut microbiota in humans and mice. In rats, NR reduced fat mass and tended to decrease body weight. Interestingly, NR increased fat and energy absorption but only in HFD-fed rats. Moreover, 16S rRNA gene sequencing analysis of intestinal and fecal samples revealed an increased abundance of species within Erysipelotrichaceae and Ruminococcaceae families in response to NR. PnuC-positive bacterial strains within these families showed an increased growth rate when supplemented with NR. The abundance of species within the Lachnospiraceae family decreased in response to HFD irrespective of NR. Alpha and beta diversity and bacterial composition of the human fecal microbiota were unaltered by NR, but in mice, the fecal abundance of species within Lachnospiraceae increased while abundances of Parasutterella and Bacteroides dorei species decreased in response to NR. In conclusion, oral NR altered the gut microbiota in rats and mice, but not in humans. In addition, NR attenuated body fat mass gain in rats, and increased fat and energy absorption in the HFD context.

Humans can perceive surface properties of an unfamiliar object without relying solely on vision. One way to achieve it is by physically touching the object. This human-inspired tactile perception is a complementary skill for robotic tactile perception. Robot perception depends on the informational quality of the tactile sensor; thus, packaging sensors and integrating them with robots plays a crucial role. In this work, we investigate the influence of conformable packaging designs on soft polydimethylsiloxane-based flexible pressure sensors that work in a variety of surface conditions and load levels. Four different 3D printed packaging designs capable of maintaining sensor trends have been developed. The low detection limits of 0.7 kPa and 0.1 kPa in the piezoresistive and piezocapacitive sensors, respectively, remain unaffected, and a performance variation as low as 30% is observed. Coefficient of variation and sensitivity studies have also been performed. Limit tests show that the designs can handle large forces ranging from 500 N to more than a 1000 N. Lastly, a qualitative study was performed, which covered prospective use-case scenarios as well as the advantages and downsides of each sensor casing design. Overall, the findings indicate that each sensor casing is distinct and best suited for tactile perception when interacting with objects, depending on surface properties.

BACKGROUND: In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults. METHODS: Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults. FINDINGS: There were 1·19 million (95% UI 1·11-1·28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59·6 [54·5-65·7] per 100 000 person-years) and high-middle SDI countries (53·2 [48·8-57·9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14

Assessing the business value for logistics from transport information derived from traffic data prevails decisively for a multi-stakeholder supply chain’s transparent and efficient functioning. It helps in understanding the roles and responsibilities of the stakeholders and highlights the crucial information flow between them that results in the net benefits. The absence of an empirical framework to depict the value creation in a supply chain through transport operations information forms a ground for further research. The dissertation primarily contributes a conceptual framework as a preliminary model to depict value creation through affiliating multiple actors in the context of practical use cases. It facilitates the process of logistical value via useful information from traffic data by incorporating various stakeholders through business model canvases and the underlying idea of business ecosystems, resulting in a consistently structured framework., Freight Traffic Management as a Service - FTMaaS

The WHO concept of Healthy Ageing (ie, the process of developing and maintaining the functional ability that enables well-being in older age) has initiated a global discussion about the need for shifting paradigms to reorient health and social services towards person-centred and coordinated models of care. In particular, the integration of health and social care services is critical to provide the basis for comprehensive information sharing and service delivery to support the evolution of the older person over time. The capability to monitor and respond to an older person's changing health and social care needs will enable prompt and personalised health and social care plans to be implemented.The implementation of an integrated care approach involves all the settings where persons age, but also requires a concerted action among micro (clinical), meso (service delivery) and macro (system) level. The community is of particular relevance given the primary objective of "ageing in place". However, from the perspective of the continuum of care and services acting synergistically, all health and social care settings (including long-term care facilities and hospitals) need to evolve and embrace an integrated way of operating to support functional ability in older people, while maximising resource and information sharing efficiencies.In this paper, we explain that government actions to promote well-being in older age should be built on a seamless continuum of care starting from the assessment of the older person's intrinsic capacity and functional ability with the final aim of providing care aligned with the individual's needs and priorities.

The COVID-19 global pandemic has had severe, unpredictable and synchronous impacts on all levels of perishable food supply chains (PFSC), across multiple sectors and spatial scales. Aquaculture plays a vital and rapidly expanding role in food security, in some cases overtaking wild caught fisheries in the production of high quality animal protein in this PFSC. We performed a rapid global assessment to evaluate the effects of the COVID19 pandemic and related emerging control measures on the aquaculture supply chain. Socio-economic effects of the pandemic were analysed by surveying the perceptions of stakeholders, who were asked to describe potential supply-side disruption, vulnerabilities and resilience patterns along the production pipeline with four main supply chain components: a) hatchery, b) production/processing, c) distribution/logistics and d) market. We also assessed different farming strategies, comparing land-vs. sea-based systems; extensive vs. intensive methods; and with and without integrated multi-trophic aquaculture, IMTA. In addition to evaluating levels and sources of economic distress, interviewees were asked to identify mitigation solutions adopted at local / internal (i.e., farm site) scales, and to express their preference on national / external scale mitigation measures among a set of a priori options. Survey responses identified the potential causes of disruption, ripple effects, sources of food insecurity, and socio-economic conflicts. They also pointed to various levels of mitigation strategies. The collated evidence represents a first baseline useful to address future disaster-driven responses, to reinforce the resilience of the sector and to facilitate the design reconstruction plans and mitigation measures, such as financial aid strategies.

The rapid, global spread of COVID-19, and the measures intended to limit or slow its propagation, are having major impacts on diverse sectors of society. Notably, these impacts are occurring in the context of other anthropogenic-driven threats including global climate change. Both anthropogenic stressors and the COVID-19 pandemic represent significant economic challenges to aquaculture systems across the globe, threatening the supply chain of one of the most important sources of animal protein, with potential disproportionate impacts on vulnerable communities. A web survey was conducted in 47 countries in the midst of the COVID-19 pandemic to assess how aquaculture activities have been affected by the pandemic, and to explore how these impacts compare to those from climate change. A positive correlation between the effects of the two categories of drivers was detected, but analysis suggests that the pandemic and the anthropogenic stressors affect different parts of the supply chain. The immediate measurable reported losses varied with aquaculture typology (land vs. marine, and intensive vs. extensive). A comparably lower impact on farmers reporting the use of integrated multitrophic aquaculture (IMTA) methods suggests that IMTA might enhance resilience to multiple stressors by providing different market options under the COVID-19 pandemic. Results emphasize the importance of assessing detrimental effects of COVID-19 under a multiple stressor lens, focusing on areas that have already locally experienced economic loss due to anthropogenic stressors in the last decade. Holistic policies that simultaneously address other ongoing anthropogenic stressors, rather than focusing solely on the acute impacts of COVID-19, are needed to maximize the long-term resilience of the aquaculture sector.

The COVID-19 global pandemic has had severe, unpredictable and synchronous impacts on all levels of perishable food supply chains (PFSC), across multiple sectors and spatial scales. Aquaculture plays a vital and rapidly expanding role in food security, in some cases overtaking wild caught fisheries in the production of high-quality animal protein in this PFSC. We performed a rapid global assessment to evaluate the effects of the COVID-19 pandemic and related emerging control measures on the aquaculture supply chain. Socio-economic effects of the pandemic were analysed by surveying the perceptions of stakeholders, who were asked to describe potential supply-side disruption, vulnerabilities and resilience patterns along the production pipeline with four main supply chain components: a) hatchery, b) production/processing, c) distribution/logistics and d) market. We also assessed different farming strategies, comparing land- vs. sea-based systems; extensive vs. intensive methods; and with and without integrated multi-trophic aquaculture, IMTA. In addition to evaluating levels and sources of economic distress, interviewees were asked to identify mitigation solutions adopted at local / internal (i.e., farm-site) scales, and to express their preference on national / external scale mitigation measures among a set of a priori options. Survey responses identified the potential causes of disruption, ripple effects, sources of food insecurity, and socio-economic conflicts. They also pointed to various levels of mitigation strategies. The collated evidence represents a first baseline useful to address future disaster-driven responses, to reinforce the resilience of the sector and to facilitate the design reconstruction plans and mitigation measures, such as financial aid strategies.

Chemical vapor deposited (CVD) amorphous tantalum-oxy nitride film on porous three-dimensional (3D) nickel foam (TaNx(O-y)/NF) utilizing tantalum precursor, tris(diethylamino)(ethylimino)tantalum(V), ([Ta(NEt)(NEt2)(3)]) with preformed Ta-N bonds is reported as a potential self-supported electrocatalyst for hydrogen evolution reaction (HER). The morphological analyses revealed the formation of thin film of core-shell structured TaNx(O-y) coating (ca. 236 nm) on NF. In 0.5 M H2SO4, TaNx(O-y)/NF exhibited enhanced HER activity with a low onset potential as compared to the bare NF (-50 mV vs. -166 mV). The TaNx(O-y)/NF samples also displayed higher current density (-11.08 mA cm(-2)vs. -3.36 mA cm(-2) at 400 mV), lower Tafel slope (151 mV dec(-1)vs. 179 mV dec(-1)) and lower charge transfer resistance exemplifying the advantage of TaNx(O-y) coating towards enhanced HER performance. The enhanced HER catalytic activity is attributed to the synergistic effect between the amorphous TaNx(O-y) film and the nickel foam.

Sensors help robots perceive their environment and localize themselves. Determining a robot's location requires a range of sensing systems. Depending on accuracy criteria and navigation conditions, robot localization sensors can differ. Common sensors for robot localization include encoders, GPS, cameras, LIDARs, and IMUs. Traditional sensors are not capable enough in changing environments and uneven terrain. In this paper, we propose a method based on deep learning to use the subsurface features obtained through a Ground Penetrating Radar (GPR) to estimate the odometry of a robot. This proposed method does not rely on visual features or the distance gathered from wheel encoders. The proposed approach was evaluated on a publicly available dataset, and the evaluation results show that the proposed method can be used for robot localization without the need for odometry from wheel encoders.

Condition assessment of underground infrastructures such as pipe networks is crucial for aging cities around the globe. The development of robotic technologies over the years led to the application of them in the condition assessment of pipe networks. However, there is a gap for accurate localization technology due to the complexity of the environment. In this letter, we propose a novel ultra-high frequency radio frequency identification (UHF-RFID) technology dual antenna system combined with Gaussian process and Particle filter algorithms to achieve millimetre level localization accuracy. The system is capable of achieving millimetre level accuracy over 50m of length without an apparent estimation drift. The results were validated through experiments conducted using an extracted water pipe section.

Water utilities across the globe are concerned with the inspection and replacement of buried metallic water pipes due to corrosion-related structural damages. Internal pipe linings are commonly used as a renewal method to improve structural strength as they are regarded to be a less expensive alternative to costly and time-consuming pipe replacements. However, linings are also prone to failure as well. Therefore, water authorities regularly monitor lining performance, where defect evolution over a long period of time is an important parameter to note. It requires an accurate in-pipe robot localization technology. In this article, we propose a novel method for in-pipe robot localization and tag mapping that uses battery-free ultra high frequency (UHF)-radio-frequency identification (RFID) sensor wireless signals. It utilizes a signal mapping approach in combination with a tailored pose-graph simultaneous localization and mapping (SLAM) algorithm. Evaluation results of a field-extracted pipe sample from Sydney Water's distribution network show that the proposed approach is capable of localizing the robot within 2.5 cm accuracy in a 50-m equivalent pipe with an unknown UHF-RFID distribution. The proposed approach outperformed other reported similar work in the literature.

This letter proposes a deep learning approach for nondestructively detecting concrete subsurface boundaries between corroded and noncorroded layers using ground penetrating radar (GPR). We utilize a finite difference time domain technique to simulate GPR electromagnetic wave propagation on various concrete models mimicking corrosion situations. Following that, a deep learning method based on convolutional neural networks is utilized to estimate the bulk relative permittivity of the compound concrete structure, as well as a multilayer perceptron-based method for clutter removal through surface wave prediction. By estimating relative permittivity and removing clutter in GPR signals, the proposed approach can reliably detect the subsurface boundaries, which is demonstrated by the evaluation results.

The use of nondestructive sensing technologies is critical in the evaluation of concrete conditions and structural integrity. In our previous experimental studies, we showed the use of the ground-penetrating radar (GPR)-based nondestructive evaluation method to examine low-range concrete subsurface boundary conditions. As the characterization of GPR signals based on multiple factors is crucial for furthering the accurate conditions of concrete subsurfaces, we investigate the GPR signals in this letter by simulating electromagnetic wave propagation on concrete models through the use of the finite-difference time-domain method. The effects of concrete relative permittivity, the standoff distance of GPR from the top surface of concrete, the operating frequency of GPR, and the depth height of multilayered concrete on the GPR measurements were all investigated, and conclusions were established. Through the outcomes of this investigation, we will be able to choose the most appropriate operating frequency for the GPR for collecting measurements on concrete infrastructures at the most effective standoff distance to the surface and subsurface depths under a variety of relative permittivity conditions in various locations.