Structural effects of 3D printing resolution on the gauge factor of microcrack-based strain gauges for health care monitoring

Channels are commonly used in long-distance water transfer projects, where landslides, collapses, or erosion may occur in its course of operation; thus, safety evaluation is conducted through monitoring and detection in its key and potentially hazardous areas. However, monitoring and detection information cannot comprehensively reflect the prominent problems of the safety state of the channel in terms of time and space. Therefore, studying how to realize the integration of monitoring and detection information is an important task for the safety evaluations of channels. In this paper, a method of integrating monitoring and detection information based on Bayesian theory is presented. The research shows that the fusion method of gathering monitoring and detection information based on Bayesian theory successfully captures the safety state of high-filling channels, and it can quantify and reduce uncertainty compared with fuzzy theory and the GA-BP neural network. By studying the influence of monitoring information on the safety of the channel, it is found that the horizontal displacement has a greater impact on the safety of the channel than the vertical displacement. A comparison of the results of fusing seven different monitoring points shows that the comprehensive utilization of horizontal and vertical displacement can improve the accuracy of the evaluation results. Compared to the safety coefficient calculated by the actual exploration, the error rate of the GA-BP neural network is 42.7%, and the fusion method based on Bayesian theory is 2.9%. The proposed method based on Bayesian theory can better use the detection information to recognize and understand the rock and soil in advance; hence, the evaluation results are more reliable and consistent with the actual engineering state.

Simultaneously increasing the activity and stability of the single-atom active sites of M"“N"“C catalysts is critical but remains a great challenge. Here, we report an Fe"“N"“C catalyst with nitrogen-coordinated iron clusters and closely surrounding Fe"“N4 active sites for oxygen reduction reaction in acidic fuel cells. A strong electronic interaction is built between iron clusters and satellite Fe"“N4 due to unblocked electron transfer pathways and very short interacting distances. The iron clusters optimize the adsorption strength of oxygen reduction intermediates on Fe"“N4 and also shorten the bond amplitude of Fe"“N4 with incoherent vibrations. As a result, both the activity and stability of Fe"“N4 sites are increased by about 60% in terms of turnover frequency and demetalation resistance. This work shows the great potential of strong electronic interactions between multiphase metal species for improvements of single-atom catalysts.

A novel vinyl polymer bearing an extended conjugated disodium dicarboxylate structure, specifically, the terphenyl side chain structure, which has a favorable electrochemical performance, has been synthesized and evaluated as an anode for sodium-ion batteries. The electrochemical performance was significantly improved over that of the vinyl polymer with disodium terephthalate. In particular, the discharge potential shifted by ~0.1"‰V to a lower potential at 0.28"‰V (vs. Na/Na+). Additionally, a specific capacity of 121"‰mAh"‰g"“1 at 10"‰mA"‰g"“1, which corresponds to an 88% theoretical capacity, was observed. Moreover, better rate performance was also achieved through the extended Ï€-conjugated system.

Automated driving systems (ADS) have undergone a significant improvement in the last years. ADS and more precisely self-driving cars technologies will change the way we perceive and know the world of transportation systems in terms of user experience, mode choices and business models. The emerging field of Deep Learning (DL) has been successfully applied for the development of innovative ADS solutions. However, the attempt to single out the best deep neural network architecture and tuning its hyperparameters are all expensive processes, both in terms of time and computational resources. In this work, Bayesian optimization (BO) is used to optimize the hyperparameters of a Spatiotemporal-Long Short Term Memory (ST-LSTM) network with the aim to obtain an accurate model for the prediction of the steering angle in a ADS. BO was able to identify, within a limited number of trials, a model-namely BO_ST-LSTM-which resulted, on a public dataset, the most accurate when compared to classical end-to-end driving models.

Digital medicine tools, including medical AI, have been advocated as potential game-changers to solve long-standing healthcare access and treatment inequality issues in low and middle income countries. For example, automated tools can fill gaps in trained healthcare workforce availability and even augment equipment capabilities. As these applications are increasingly becoming a reality, we connect here with researchers with experience in planning and deployment of these tools in under-resourced settings, to understand what the current bottlenecks are from a practical point of view. The experts involved are Walter H. Curioso (a digital health expert and biomedical informatics consultant, Universidad Continental, University of Washington), Daniel S.W. Ting (an expert in deep learning for medical imaging and digital innovation, Singapore Health Service, Duke-NUS Medical School), Bram van Ginneken (an expert in machine learning for medical image analysis, Radboud University) and Martin C. Were (an expert in digital health and medical informatics, Vanderbilt University Medical Center).

Shielding those vulnerable to COVID-19, while allowing the virus to spread, largely unmitigated, through the rest of the population, would have failed according to a new modeling paper published today in PLOS Global Public Health by University of Bath scientists. Shielding strategies or "focused protection", as advocated for in the...

Rett syndrome (RTT) is a progressive neurodevelopmental disorder caused by variants in MECP2. Emerging evidence of ethnic specificity of genetic variations has allowed precise diagnostic approaches with tailored therapies. In this study, we reviewed the variation spectrum of MECP2 in Korean RTT(-like)Â patients and compared it with previous reports in multiple ethnic groups. We reevaluated variants found in Korean RTTÂ patients according to the new Clinical Genome Resource guideline to reinterpret and reclassify variants of uncertain significance in MECP2. Among 377 cases, 56 (14.9%) showed pathogenic variants, and three novel variants, p.(Ala277Argfs*7), p.(Ala378Glyfs*8), and p.(Arg270_Ser332del), were identified. Comprehensive data from Korea revealed an overall consistent variation spectrum with those from other ethnicities. Through the reevaluation of variants, nine that previously had insufficient evidence for pathogenicity were reclassified into pathogenic variants. Our study provided insight on the genetic contribution of MECP2 in RTT and a useful background for genetic counseling in the Korean population.

Microbial communities and their associated bioactive compounds1,2,3 are often disrupted in conditions such as the inflammatory bowel diseases (IBD)4. However, even in well-characterized environments (for example, the human gastrointestinal tract), more than one-third of microbial proteins are uncharacterized and often expected to be bioactive5,6,7. Here we systematically identified more than 340,000 protein families as potentially bioactive with respect to gut inflammation during IBD, about half of which have not to our knowledge been functionally characterized previously on the basis of homology or experiment. To validate prioritized microbial proteins, we used a combination of metagenomics, metatranscriptomics and metaproteomics to provide evidence of bioactivity for a subset of proteins that are involved in host and microbial cell"“cell communication in the microbiome; for example, proteins associated with adherence or invasion processes, and extracellular von Willebrand-like factors. Predictions from high-throughput data were validated using targeted experiments that revealed the differential immunogenicity of prioritized Enterobacteriaceae pilins and the contribution of homologues of von Willebrand factors to the formation of Bacteroides biofilms in a manner dependent on mucin levels. This methodology, which we term MetaWIBELE (workflow to identify novel bioactive elements in the microbiome), is generalizable to other environmental communities and human phenotypes. The prioritized results provide thousands of candidate microbial proteins that are likely to interact with the host immune system in IBD, thus expanding our understanding of potentially bioactive gene products in chronic disease states and offering a rational compendium of possible therapeutic compounds and targets.

Nitrogen substitutional doping in the Ï€-basal plane of graphene has been used to modulate the material properties and in particular the transition from hole to electron conduction, thus enlarging the field of potential applications. Depending on the doping procedure, nitrogen moieties mainly include graphitic-N, combined with pyrrolic-N and pyridinic-N. However, pyridine and pyrrole configurations of nitrogen are predominantly introduced in monolayer graphene:N lattice as prepared by CVD. In this study, we investigate the possibility of employing pyridinic-nitrogen as a reactive site as well as activate a reactive center at the adjacent carbon atoms in the functionalized C"“N bonds, for additional post reaction like oxidation. Furthermore, the photocatalytic activity of the graphene:N surface in the production of singlet oxygen (1O2) is fully exploited for the oxidation of the graphene basal plane with the formation of pyridine N-oxide and pyridone structures, both having zwitterion forms with a strong p-doping effect. A sheet resistance value as low as 100 Ω/â–¡ is reported for a 3-layer stacked graphene:N film.

Recent years have seen a rapid acceleration of research on framework materials, including, among others, metal–organic frameworks, covalent organic frameworks, supramolecular organic frameworks, porous organic polymers, and inorganic framework materials. These materials demonstrate properties beyond what was considered achievable for inorganic or organic porous materials in the past, and have potential applications in separation and storage, heterogeneous catalysis, sensing, drug delivery, and beyond.

Large-scale clinical studies on the post-infectious impacts of SARS-CoV-2 have suggested that patients who have recovered from acute infection have increased risk for cardiometabolic syndrome-associated morbidities such as diabetes, chronic kidney disease and heart failure. Initial studies have taken the first steps towards unravelling the molecular processes that may be driving these findings, including the role of immune and inflammatory factors, but a comprehensive aetiology remains unclear. Given that cardiometabolic syndrome progression in patients with Long COVID may pose a significant global health and economic burden post pandemic, there is an emergent need to identify therapeutic targets and treatment options.

Refineries generally employ multiple energy-intensive distillation/adsorption columns to separate and purify complicated chemical mixtures. Materials such as multi-functional molecular separators integrating various modules capable of separating molecules according to their shape and chemical properties simultaneously may represent an alternative. Herein, we address this challenge in the context of one-step removal of alkynes and propadiene from cracking gases (up to 10 components) using a multi-functional and responsive material ZU-33 through a guest/temperature dual-response regulation strategy. The responsive and guest-adaptive properties of ZU-33 provide the optimized binding energy for alkynes and propadiene, and avoid the competitive adsorption of olefins and paraffins, which is verified by breakthrough tests, single-crystal X-ray diffraction experiments, and simulation studies. The responsive properties to different stimuli endow materials with multiple regulation methods and broaden the boundaries of the applicability of porous materials to challenging separations.

Children’s Cancer Hospital 57357 and Cairo University, Cairo, Egypt. Kathmandu Institute of Applied Sciences, Kathmandu, Nepal. Institute of Tropical Medicine Pedro Kouri, Havana, Cuba. Huan Jiang. BGI, Shenzhen, China. Firdausi Qadri. International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh. National Institute of Biomedical Genomics, Kalyani, India. On behalf of...

Polypropylene fibres are difficult to dye using commonly used techniques due to the high crystallinity and non-polar aliphatic structure, that lack reactive places for dyes in the molecule. Dyeing PP fabric in scCO2 with antibacterial dyes merged the dyeing and finishing methods, resulting in a more productive technique in terms of water and energy consumption. Unmodified polypropylene fabric was dyed with 4-[2-[4-(ethenylsulphonyl)phenyl]diazenyl]-N,N-diethylbenzenamine antibacterial dye under scCO2 medium. The influences of scCO2 working parameters, such as dye concentration, pressure, dyeing time, and temperature, on fabric dye absorption expressed as color strength were studied. The color strength (K/S) was measured as well as CIELAB color parameters. The results were compared with its water dyeing analogue and it was observed that color strength as well as color depth (L) of the samples dyed in scCO2 were noticeably better than its water counterpart. In both scCO2 and water, the fastness properties (washing, rubbing, and light) of the dyed samples were excellent. Antibacterial activity of the dyed polypropylene sample in scCO2 was estimated and the results indicated good antibacterial efficiency.

Due to the prolonged inflammatory process induced by infection of the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), indices of autonomic nervous system dysfunction may persist long after viral shedding. Previous studies showed significant changes in HRV parameters in severe (including fatal) infection of SARS-CoV-2. However, few studies have comprehensively examined HRV in individuals who previously presented as asymptomatic or mildly symptomatic cases of COVID-19. In this study, we examined HRV in asymptomatic or mildly symptomatic individuals 5"“7 weeks following positive confirmation of SARS-CoV-2 infection. Sixty-five ECG Holter recordings from young (mean age 22.6"‰Â±"‰3.4 years), physically fit male subjects 4"“6 weeks after the second negative test (considered to be the start of recovery) and twenty-six control male subjects (mean age 23.2"‰Â±"‰2.9 years) were considered in the study. Night-time RR time series were extracted from ECG signals. Selected linear as well as nonlinear HRV parameters were calculated. We found significant differences in Porta's symbolic analysis parameters V0 and V2 (p"‰<"‰0.001), α2 (p"‰<"‰0.001), very low-frequency component (VLF; p"‰="‰0.022) and respiratory peak (from the PRSA method; p"‰="‰0.012). These differences may be caused by the changes of activity of the parasympathetic autonomic nervous system as well as by the coupling of respiratory rhythm with heart rate due to an increase in pulmonary arterial vascular resistance. The results suggest that the differences with the control group in the HRV parameters, that reflect the functional state of the autonomic nervous system, are measurable after a few weeks from the beginning of the recovery even in the post-COVID group-a young and physically active population. We indicate HRV sensitive markers which may be used in long-term monitoring of patients after recovery.

European Journal of Clinical Nutrition (2022)Cite this article. This study aimed to investigate the association of breakfast consumption frequency (BCF) with glycemic control indices in a cross-sectional sample of adults from families at high risk for type 2 diabetes mellitus (T2DM), exploring the role of sex and socioeconomic status (SES).

The urban centres are the first to be discovered in the region, challenging archaeological dogma. You have full access to this article via your institution. Mysterious mounds in the southwest corner of the Amazon Basin were once the site of ancient urban settlements, scientists have discovered. Using a remote-sensing technology to map the terrain from the air, a research team has revealed that, starting about 1,500 years ago, ancient Amazonians built and lived in densely populated centres, featuring 22-metre-tall earthen pyramids and encircled by kilometres of elevated roadways.

In the version of this article initially published, the second paragraph of the Discussion had several incorrect reference citations (62"“65 in the original). They have been removed and the remaining references renumbered throughout. The changes have been made to the HTML and PDF versions of the article. Public Health...

Silver-Russel syndrome (SRS) is a representative imprinting disorder (ID) characterized by growth failure and diagnosed by clinical features. Recently, international consensus has recommended using the Netchine-Harbison clinical scoring system (NH-CSS) as clinical diagnostic criteria. Loss of methylation of H19/IGF2:intergenic differentially methylated region (H19LOM) and maternal uniparental disomy chromosome 7 (UPD(7)mat) are common etiologies of SRS; however, other IDs, pathogenic variants (PVs) of genes, and pathogenic copy number variants (PCNVs) have been reported in patients meeting NH-CSS. To clarify the frequency and clinical characteristics of each etiology, we conducted (epi)genetic analysis in 173 patients satisfying NH-CSS. H19LOM and UPD(7)mat were identified in 34.1%. PCNVs, other IDs, and PVs were in 15.0%. Patients with all six NH-CSS items were most frequently observed with H19LOM and UPD(7)mat. This study confirmed the suitability of NH-CSS as clinical diagnostic criteria, the (epi)genetic heterogeneity of SRS, and showed the necessity of further discussion regarding the "SRS spectrum".

The food system is a major source of both environmental and health challenges. Yet, the extent to which policy-induced changes in the patterns of food demand address these challenges remains poorly understood. Using a survey-based, randomized controlled experiment with 5,912 respondents from the United Kingdom, we evaluate the potential effect of carbon and/or health taxes, information and combined tax and information strategies on food purchase patterns and the resulting impact on greenhouse gas emissions and dietary health. Our results show that while information on the carbon and/or health characteristics of food is relevant, the imposition of taxes exerts the most substantial effects on food purchasing decisions. Furthermore, while carbon or health taxes are best at separately targeting emissions or dietary health challenges, respectively, a combined carbon and health tax policy maximizes benefits in terms of both environmental and health outcomes. We show that such a combined policy could contribute to around one third of the reductions in residual emissions required to achieve the United Kingdom's 2050 net-zero commitments, while discouraging the purchase of especially unhealthy snacks, sugary drinks and alcohol and increasing the purchase of fruit and vegetables.