Coverage Planning for UVC Irradiation: Robot Surface Disinfection Based on Swarm Intelligence Algorithm.

Ultraviolet (UV) radiation has been widely utilized as a disinfection strategy to effectively eliminate various pathogens. The disinfection task achieves complete coverage of object surfaces by planning the motion trajectory of autonomous mobile robots and the UVC irradiation strategy. This introduces an additional layer of complexity to path planning, as every point on the surface of the object must receive a certain dose of irradiation. Nevertheless, the considerable dosage required for virus inactivation often leads to substantial energy consumption and dose redundancy in disinfection tasks, presenting challenges for the implementation of robots in large-scale environments. Optimizing energy consumption of light sources has become a primary concern in disinfection planning, particularly in large-scale settings. Addressing the inefficiencies associated with dosage redundancy, this study proposes a dose coverage planning framework, utilizing MOPSO to solve the multi-objective optimization model for planning UVC dose coverage. Diverging from conventional path planning methodologies, our approach prioritizes the intrinsic characteristics of dose accumulation, integrating a UVC light efficiency factor to mitigate dose redundancy with the aim of reducing energy expenditure and enhancing the efficiency of robotic disinfection. Empirical trials conducted with autonomous disinfecting robots in real-world settings have corroborated the efficacy of this model in deactivating viruses.

Feasibility analysis of inactivating influenza A(H1N1) virus using UVC robot in classroom environment.

Background: Starting from 2009, H1N1 has been one of the respiratory diseases that afflict the global population. Concurrently, due to the influence of COVID-19, it has become widely accepted that preventing the virus's spread necessitates personal protection measures and disinfection in public spaces. Experiments: This study conducted two experiments. In the classroom experiment, six UVC dose test points were calibrated to test whether the UVC dose at each testing point met the standards for inactivating IAVs and the time required to meet the standards. In the simulated classroom experiment, seven square slides made of IAVs were placed. After 10 min of robot movement, irradiated sterile square slides were made into suspension and injected into chicken embryos. Cultivate chicken embryos and conduct IAVs testing. Results: Classroom experiment has shown that 5 testing points can meet the standards for inactivating IAVs(3 mJ/cm2), with a required time of 80 min, 40 min, 15 min, 5 min and 10 min. The UVC dose for testing points that do not meet the standards in 80 min is only 0.5 mJ/cm2. The simulation classroom experiment outcomes revealed that 99.99 % of IAVs were deactivated. Furthermore, this study established both a desktop control group and a chair arm control group, both of which yielded identical results, indicating an inactivation logarithm of IAVs≥4log. Conclusion: The study presented that IAVs on the surface of an object can be effectively and rapidly deactivated at an irradiation density of 1.8 mW/cm2. Meanwhile, the study provides evidence of the feasibility of using the GXU robot to inactivate IAVs in a classroom environment.

The Role of Cancer in the Risk of Cardiovascular and All-Cause Mortality: A Nationwide Prospective Cohort Study.

Objectives: Evidence on cardiovascular-related and all-cause mortality risks in a wide range of cancer survivors is scarce but needed to inform prevention and management. Methods: We performed a nationwide prospective cohort study using information from the Continuous National Health and Nutrition Examination Survey (NHANES) in the United States and the linked mortality follow-up files, available for public access. A propensity score-matched analysis with a 1:1 ratio was conducted to reduce the baseline differences between participants with and without cancer. The relationship between cancer status and the cardiovascular-related and all-cause mortality risk was examined using weighted Cox proportional hazards regression. Independent stratification analysis and cancer-specific analyses were also performed. Results: The study sample included 44,342 participants, aged 20-85, interviewed between 1999 and 2018. Of these, 4,149 participants had cancer. All-cause death occurred in 6,655 participants, of whom 2,053 died from cardiovascular causes. Propensity-score matching identified 4,149 matched pairs of patients. A fully adjusted Cox proportional hazards regression showed that cancer was linked to an elevated risk of cardiovascular-related and all-cause mortality both before and after propensity score matching. Stratification analysis and cancer-specific analyses confirmed robustness of results. Conclusion: Our study confirmed that cancer was strongly linked to cardiovascular-related and all-cause mortality, even after adjusting for other factors that could impact a risk, including the American Heart Association (AHA)'s Life's Simple 7 cardiovascular health score, age, sex, ethnicity, marital status, income, and education level.

Atomic Structure of the Fe3O4/Fe2O3 Interface During Phase Transition from Hematite to Magnetite.

Phase transition between iron oxides practically defines their functionalities in both physical and chemical applications. Direct observation of the atomic rearrangement and a quantitative description of the dynamic behavior of the phase transition, however, are rare. Here, we monitored the structure evolution from a rod-shaped hematite nanoparticle to magnetite during H2 reduction at elevated temperatures. Environmental transmission electron microscopy observations, along with selected area electron diffraction experiments, identified that the reduction preferentially commenced with Fe3O4 nucleation on the surface defective sites, followed by laterally growing into a Fe3O4 film until fully covering the particle surface. The Fe3O4 phase then propagated toward the bulk particle via a Fe3O4/α-Fe2O3 interface with the relationship α-Fe2O3(0001)//Fe3O4(111) in an aligned orientation of [112]Fe3O4||[112̅0]α-Fe2O3. Upon this Fe3O4/α-Fe2O3 interface, the Fe-O octahedra in Fe3O4(111) (as layer A) matches that of α-Fe2O3(0001) at a rotation angle of 30°, and the reduction proceeds in such a pattern that two-thirds of the FeOh in the adjacent layer (layer B) is transformed into FeTe.

UFO-Net: A Linear Attention-Based Network for Point Cloud Classification.

Three-dimensional point cloud classification tasks have been a hot topic in recent years. Most existing point cloud processing frameworks lack context-aware features due to the deficiency of sufficient local feature extraction information. Therefore, we designed an augmented sampling and grouping module to efficiently obtain fine-grained features from the original point cloud. In particular, this method strengthens the domain near each centroid and makes reasonable use of the local mean and global standard deviation to extract point cloud's local and global features. In addition to this, inspired by the transformer structure UFO-ViT in 2D vision tasks, we first tried to use a linearly normalized attention mechanism in point cloud processing tasks, investigating a novel transformer-based point cloud classification architecture UFO-Net. An effective local feature learning module was adopted as a bridging technique to connect different feature extraction modules. Importantly, UFO-Net employs multiple stacked blocks to better capture feature representation of the point cloud. Extensive ablation experiments on public datasets show that this method outperforms other state-of-the-art methods. For instance, our network performed with 93.7% overall accuracy on the ModelNet40 dataset, which is 0.5% higher than PCT. Our network also achieved 83.8% overall accuracy on the ScanObjectNN dataset, which is 3.8% better than PCT.

Association between hysterectomy status and stroke risk and cause-specific and all-cause mortality: evidence from the 2005-2018 National Health and Nutrition Examination Survey.

Background: Prior research on women who had hysterectomies has shown mixed results on whether or not hysterectomies increased the incidence of stroke and cause-specific or all-cause mortality. Methods: Using information from the Continuous National Health and Nutrition Examination Survey (NHANES) in the United States, including linked mortality follow-up files available for public access, a multicycle cross-sectional design mortality linkage study was performed. Results: Conducted during the years 2005-2018, the study sample included 14,214 female participants ranging in age from 20 to 85 years. The relationship between the hysterectomy status and the risk of stroke and cause-specific and all-cause mortality was examined using a series of weighted logistic regressions and Cox proportional hazards regressions, respectively. The presence of a hysterectomy was consistently linked to an elevated risk of stroke using weighted logistic regression models. The hysterectomy status, however, consistently showed no effect on survival by adjusted weighted Cox regression analysis. Conclusion: Our study found a significant association between hysterectomy and stroke, even after adjusting for other factors that could impact risk, such as the American Heart Association (AHA)'s Life's Simple 7 cardiovascular health score and variables of age, ethnicity, marital status, income, education, and depression severity.

Immune infiltration and immunophenotyping in atrial fibrillation.

Atrial fibrillation (AF) is a relatively common arrhythmia in clinical practice. Although significant progress has been achieved in the treatment of AF and its associated complications, research on AF prevention lags behind, mainly due to the lack of a deep understanding of AF pathogenesis. In recent years, as our knowledge has grown, the role of the inflammatory/immune response in the occurrence and progression of AF has gradually gained attention. In this paper, based on existing gene expression data in the Gene Expression Omnibus database, a detailed description of immune infiltration status in AF is presented using a series of analytical methods, including differential analysis, Gene Ontology categorization, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and weighted gene coexpression network analysis, and analysis tools such as CIBERSORTx and Cytoscape. Several new AF/immune infiltrations-related signature genes were identified, and the AF/immune infiltration pathology was classified based on these immune signature genes, thus providing novel insights into the pathogenesis of AF based on the inflammatory response.

Association between socioeconomic status and arteriosclerotic cardiovascular disease risk and cause-specific and all-cause mortality: Data from the 2005-2018 National Health and Nutrition Examination Survey.

Background: Morbidity and mortality of arteriosclerotic cardiovascular disease (ASCVD) varied according to socioeconomic status (SES), and evidence on the association between SES and ASCVD risk, and cause-specific and all-cause mortality was nevertheless lacking in large-scale or population-based studies. Methods: A multicycle cross-sectional design and mortality linkage study was conducted using data from Continuous National Health and Nutrition Examination Survey (NHANES) in the United States, including public use linked mortality follow-up files through December 31, 2019. Poverty income ratio (PIR) served as a SES index. A series of weighted Logistic regressions and Cox proportional hazards regressions were used to investigate the association between the SES and the risk of ASCVD and mortality, respectively. Results: The study sample was comprised of 30,040 participants aged 20-85 years old during the 2005-2018 period. Weighted Logistic regression models consistently indicated significant relationship between people experiencing poverty and increased risk of ASCVD, and linear trend tests were all statistically significant (all P for trend < 0.001). Additionally, weighted Cox regression analysis consistently demonstrated that the hazards of cause-specific and all-cause mortality increased, with the decrease of each additional income level, and trend analyses indicated similar results (all P for trend < 0.001). Conclusions: Our study confirmed that the SES was strongly linked to living with ASCVD, and cause-specific and all-cause mortality, even after adjusting for other factors that could impact risk, such as the American Heart Association (AHA)'s Life's Simple 7 cardiovascular health score and variables of age, sex, marital status, education, and depression severity.

Association between level of depression and coronary heart disease, stroke risk and all-cause and cardiovascular mortality: Data from the 2005-2018 National Health and Nutrition Examination Survey.

Research on the association between level of depression and coronary heart disease (CHD), stroke risk, and all-cause and cardiovascular mortality is lacking in large-scale or population-based studies incorporating cardiovascular disease (CVD) endpoints. We aim to assess the relationship between the level of a person's depression and their risk of CHD, stroke, and all-cause and cardiovascular mortality. Utilizing data from the United States National Health and Nutrition Examination Survey (NHANES), multicycle cross-sectional design and mortality linkage studies were conducted. The study sample included 30918 participants aged 20-85 years old during the 2005-2018 period. Depression was assessed using the nine-item Patient Health Questionnaire (PHQ-9), with scores of 5, 10, 15, and 20 being the cut-off points for mild, moderate, moderately severe, and severe depression, respectively. A series of weighted logistic regression analyses and Cox proportional hazards models were utilized to examine the relationship between the level of depression with the risk of CHD, stroke, all-cause, and cardiovascular mortality. Trend analyses were conducted by entering the level of depression as a continuous variable and rerunning the corresponding regression models. Weighted logistic regression models consistently indicated a statistically significant association between the level of depression and increased risk of CHD and stroke, and those linear trend tests were statistically significant (P for trend < 0.001). Furthermore, weighted Cox regression analyses consistently indicated that participants who had a more severe degree of depression were at a higher risk of all-cause death, and trend analyses suggested similar results (P for trend < 0.001). Another weighted Cox regression analysis also consistently indicated that except for severe depression, the hazard of cardiovascular death was increased with each additional level increase of depression. Our study confirmed that the level of depression was strongly associated with CHD, stroke, and all-cause and cardiovascular mortality, even after accounting for other factors that could impact risk, including variables of age, gender, ethnicity, income, education, body mass index (BMI), marital, and smoking status.

Restructuring of the gold-carbide interface for low-temperature water-gas shift.

A passivated Au/α-MoC catalyst, containing 2-4 layered Au clusters of 1.6 nm, was re-activated by CH4/H2 at 590 °C, during which the structure of the gold-carbide interface changed considerably. The partially-oxidized surface Mo species were carburized to MoC, while the Au clusters dispersed into smaller ones, accompanied by the coating of carbide thin layers on Au. This restructuring promoted charge transfer from Au to MoC and extended the Au-MoC interfacial perimeter, which was largely responsible for the activity in the low-temperature water-gas shift reaction.

CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database.

The Comprehensive Antibiotic Resistance Database (CARD; http://arpcard.mcmaster.ca) is a manually curated resource containing high quality reference data on the molecular basis of antimicrobial resistance (AMR), with an emphasis on the genes, proteins and mutations involved in AMR. CARD is ontologically structured, model centric, and spans the breadth of AMR drug classes and resistance mechanisms, including intrinsic, mutation-driven and acquired resistance. It is built upon the Antibiotic Resistance Ontology (ARO), a custom built, interconnected and hierarchical controlled vocabulary allowing advanced data sharing and organization. Its design allows the development of novel genome analysis tools, such as the Resistance Gene Identifier (RGI) for resistome prediction from raw genome sequence. Recent improvements include extensive curation of additional reference sequences and mutations, development of a unique Model Ontology and accompanying AMR detection models to power sequence analysis, new visualization tools, and expansion of the RGI for detection of emergent AMR threats. CARD curation is updated monthly based on an interplay of manual literature curation, computational text mining, and genome analysis.