Reducing the vibration responses caused by the unbalance of the rotor is a crucial technology to ensure the safe and efficient operation of high-speed rotating machinery. For the flexible rotor system, the unbalance responses of rotors vary in different radial directions due to the anisotropic stiffness. The holospectrum technique using multi-sensor fusion provides ideas to solve this issue. The standard balancing method based on the holospectrum technique takes the Initial Phase Vector (IPV) as the balancing object, which could not represent the unbalance of flexible rotors correctly. In addition, the operating speed of the flexible rotor is generally higher than the first critical speed (FCS), making it necessary to fulfill the balancing of the first two modal shapes respectively in two steps. The above-mentioned procedure is not only very dangerous but also requires a large number of test runs resulting in corresponding wastages. In order to solve the issues mentioned above, a synchronous holo-balancing method for flexible rotors based on the modified initial phase vector (MIPV) is developed in this paper. Firstly, to tackle the limitation of IPV, the concept of equivalent rotating frequency circle is presented and then the MIPV is proposed as a new balancing object. MIPV could linearly represent the unbalance of the flexible rotor and increase the accuracy of holo-balancing. Secondly, the synchronous holo-balancing method is carried out to achieve the balancing at the speed below the FCS, reducing the complexity and danger of test runs at high operating speeds. And the synchronous balancing procedures based on the MIPV are further summarized in detail. Finally, two experimental results with different operating speeds and probe installations validate the feasibility and effectiveness of the proposed method. Compared with other traditional balancing methods, the proposed method can minimize the residual vibration and achieve state-of-the-art performances.
Over the past two decades, our appreciation of the gut mucus has moved from a static lubricant to a dynamic and essential component of the gut ecosystem that not only mediates the interface between host tissues and vast microbiota, but regulates how this ecosystem functions to promote mutualistic symbioses and protect from microbe-driven diseases. By delving into the complex chemistry and biology of the mucus, combined with innovative in vivo and ex vivo approaches, recent studies have revealed novel insights into the formation and function of the mucus system, the O-glycans that make up this system, and how they mediate two major host-defense strategies - resistance and tolerance - to reduce damage caused by indigenous microbes and opportunistic pathogens. This current review summarizes these findings by highlighting the emerging roles of mucus and mucin-type O-glycans in influencing host and microbial physiology with an emphasis on host defense strategies against bacteria in the gastrointestinal tract.
Spare-parts surgery in traumatic amputation sources tissue from the amputated part to cover the residual amputation defect. This case describes a trauma patient requiring below-elbow amputation. Stump closure was accomplished with a pedicled fillet flap derived from the still-attached hand, avoiding donor site morbidity and maximizing stump length.
There is a growing appreciation that the interaction between diet, the gut microbiota and the immune system contribute to the development and progression of inflammatory bowel disease (IBD). A mounting body of scientific evidence suggests that high-fat diets exacerbate IBD; however, there is a lack of information on how specific types of fat impact colitis. The Mediterranean diet (MD) is considered a health-promoting diet containing approximately 40% total fat. It is not known if the blend of fats found in the MD contributes to its beneficial protective effects. Mice deficient in the mucin 2 gene (Muc 2-/-) were weaned to 40% fat, isocaloric, isonitrogenous diets. We compared the MD fat blend (high monounsaturated, 2:1 n-6:n-3 polyunsaturated and moderate saturated fat) to diets composed of corn oil (CO, n-6 polyunsaturated-rich), olive oil (monounsaturated-rich) or milk fat (MF, saturated-rich) on spontaneous colitis development in Muc2-/- mice. The MD resulted in lower clinical and histopathological scores and induced tolerogenic CD103+ CD11b+ dendritic, Th22 and IL-17+ IL-22+ cells necessary for intestinal barrier repair. The MD was associated with beneficial microbes and associated with higher cecal acetic acid levels negatively correlated with colitogenic microbes like Akkermansia muciniphila. In contrast, CO showed a higher prevalence of mucin-degraders including A. muciniphila and Enterobacteriaceae, which have been associated with colitis. A dietary blend of fats mimicking the MD, reduces disease activity, inflammation-related biomarkers and improves metabolic parameters in the Muc2-/- mouse model. Our findings suggest that the MD fat blend could be incorporated into a maintenance diet for colitis.
Severe toxicity of heavy metal ions and their adverse effects on the ecosystem and health of living species raised a requirement to develop practical detection configurations capable of simultaneous and differentiable detection of toxic metal ions in aquatic samples. In this regard, we have fabricated a high-performance sensor configuration based on the integrated reduced graphene oxide (rGO) flakes with brominated white polyaniline (PANi) flakes toward the prompt and accurate detection of Pb (II) and Cd (II) in biological and non-biological specimens. The as-developed configuration simultaneously identified both Pb (II) and Cd (II) through a differentiable manner with a limit of detection (LOD)/quantification limit (QL) of 7.3 nM/85 nM and 6.5 nM/92 nM, respectively. The sensor also showed superior sensitivity of about 4547.77 and 3914.01 µA.µM⁻¹.cm⁻² toward Pb (II) and Cd (II), respectively, along with a favorable recovery rate in actual human blood plasma and wastewater samples. The as-developed complex proved to be an ideal platform for simultaneous detection/recovery of heavy metal ions in various aquatic samples.
Combining hybrid polymeric platforms with laser-assisted reduced graphene oxide (LArGO) could bridge the gap between a battery and supercapacitor device, overshadow the drawbacks of polymeric configurations, and boost the cyclic stability, specific capacitance (SC), and energy density of the resulting configurations. Herein, drawbacks of polymeric configurations such as polypyrrole (PPy) and polyindole (PIN) are modified via reinforcement with silver nanowires (Ag-PPy and Ag-PIN), and their performances are compared via in-depth fundamental analyses to select the superior one. Accordingly, the SC of PPy and PIN increased from 282 and 324 F.g-1 to 452 and 587 F.g-1 at the current density of 1 A.g-1 upon reinforcement with silver nanowires, respectively. The Ag-PIN configuration as the superior modified polymeric platform is assembled in an asymmetric supercapacitor along with LArGO. The as-developed electrodes show an ideal synergic effect and reveal favorable SC retention (94.2%) after 5000 cycles, high specific capacitance of 368.8 F.g-1, and energy density of 41.5 W.h.Kg-1 at the power density of 450 W.Kg-1. The obtained data illuminate the great capability of the hybrid package that bridges the gap between a high-performance battery and supercapacitor.
Background Rural and remote communities faced unique access challenges to essential services such as healthcare and highspeed infrastructure pre-COVID, which have been amplified by the pandemic. This study examined patterns of COVID-related challenges and the use of technology among rural-living individuals during the first wave of the COVID-19 pandemic. Methods A sample of 279 rural residents completed an online survey about the impact of COVID-related challenges and the role of technology use. Latent class analysis was used to generate subgroups reflecting the patterns of COVID-related challenges. Differences in group membership were examined based on age, gender, education, race/ethnicity, and living situation. Finally, thematic analysis of open-ended qualitative responses was conducted to further contextualize the challenges experienced by rural-living residents. Results Four distinct COVID challenge impact subgroups were identified: 1) Social challenges (35%), 2) Social and Health challenges (31%), 3) Social and Financial challenges (14%), and 4) Social, Health, Financial, and Daily Living challenges (19%). Older adults were more likely to be in the Social challenges or Social and Health challenges groups as compared to young adults who were more likely to be in the Social, Health, Financial, and Daily Living challenges group. Additionally, although participants were using technology more frequently during the COVID-19 pandemic to address challenges, they were also reporting issues with quality and connectivity as a significant barrier. Conclusions These analyses found four different patterns of impact related to social, health, financial, and daily living challenges in the context of COVID. Social needs were evident across the four groups; however, we also found nearly 1 in 5 rural-living individuals were impacted by an array of challenges. Access to reliable internet and devices has the potential to support individuals to manage these challenges.
Introduction Despite an increasing number of women pursuing careers in science, engineering, and medicine, gender disparities in patents persist. This study sought to analyze trends in inventor's gender for surgical device patents filed and granted in Canada and the United States from 2015 to 2019. Methods This study analyzed patents filed and granted by the Canadian Intellectual Property Office (CIPO) in the category of “Diagnosis; Surgery; Identification” and the United States Patent and Trademark Office (USPTO) in the category of “Surgery” from 2015 to 2019. The gender of the patent applicants was determined using a gender algorithm that predicts gender based on first names. Gender matches with names having a probability of less than 95% were excluded. Results We identified 14,312 inventors on patents filed and 12,737 inventors on patents granted by the CIPO for “Diagnosis; Surgery; Identification”. In the USPTO category of “Surgery,” we identified 75,890 inventors on patents filed and 44,842 inventors on patents granted. Female inventors accounted for 7%-10% of inventors from 2015 to 2019 for both patents filed and granted. The proportion of female inventors on patents granted was significantly lower than for patents filed for four of the 5 y analyzed for both the USPTO and CIPO. Conclusions Female representation in surgical device patenting has stagnated, between 7 and 10%, from 2015 to 2019 in Canada and the United States. This underrepresentation of female inventors in surgical device patenting represents sizable gender disparity.
Rapid distribution of viral-induced diseases and weaknesses of common diagnostic platforms for accurate and sensitive identification of infected people raises an urgent demand for the design and fabrication of biosensors capable of early detection of viral biomarkers with high specificity. Accordingly, molecularly imprinted polymers (MIPs) as artificial antibodies prove to be an ideal preliminary detection platform for specific identification of target templates, with superior sensitivity and detection limit (DL). MIPs detect the target template with the “lock and key” mechanism, the same as natural monoclonal antibodies, and present ideal stability at ambient temperature, which improves their practicality for real applications. Herein, a 2D MIP platform consisting of decorated graphene oxide with the interconnected complex of polypyrrole-boronic acid is developed that can detect the trace of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen in aquatic biological samples with ultrahigh sensitivity/specificity with DL of 0.326 and 11.32 fg mL–1 using voltammetric and amperometric assays, respectively. Additionally, the developed MIP shows remarkable stability, selectivity, and accuracy toward detecting the target template, which paves the way for developing ultraspecific and prompt screening diagnostic configurations capable of detecting the antigen in 1 min or 20 s using voltammetric or amperometric techniques.
Carbonaceous immunosensors are ideal nanoplatforms for developing rapid, precise, and ultra-specific diagnostic kits capable of early detection of viral infectious illnesses such as COVID-19. However, developing a proper carbonic immunosensor requires stepwise protocols to find optimum operating conditions to minimize drawbacks. Herein, for the first time and through a stepwise protocol, activation, and monoclonal IgG antibody mounting capability of multi-walled carbon nanotubes (MWCNTs) at two diverse outer diameters (ODs), viz., 20–30 nm and 50–80 nm, and graphene deriv atives (graphene oxide (GO) and reduced graphene oxide (rGO)) were examined and compared with each other toward finding the prime carbonaceous nanomaterial(s) for maximized antibody loading efficiency along with an ideal detection limit (DL) and sensitivity. Next, the effect of common amplifying agents, i.e., Au nanostars (Au NSs) and Ag nanowires (Ag NWs), on the total performance of the best carbonaceous structure was carefully assessed, and the responsible detection mechanism is investigated in detail. Next, the developed carbonaceous immunosensors were assessed via voltammetric and impedance assays, and their performances toward specific detection of SARS-CoV-2 antigen through immunoreaction were examined in detail. The study's outcome showed the superior performance of conjugated rGO-based immunosensor with Au NSs toward specific and quick (1 min) detection of SARS-CoV-2 antigen in biological fluids compared with other 1D/2D carbonaceous nanomaterials.
In order to model the spatial correlations of seismic performances within a portfolio of buildings, an approach based on multiple-output Gaussian random field is proposed in this paper. Seismic performances, including engineering demand parameters, economic loss, repair time, and collapse state, are modeled as functions of latent Gaussian random fields. The correlations of seismic performances are specified by the kernel functions of Gaussian random fields, whose hyperparameters are determined by using Gaussian process regression. After applying the proposed method to a spatially distributed building portfolio, it is demonstrated that overlooking spatial correlations may lead to an underestimate of the probability of occurrence of extreme seismic losses.
Proper seismic analysis and design of bridges are critical, especially in locations prone to high seismic activities where critical infrastructure is at a high risk of seismic damage leading to direct and indirect losses. The seismic performance of bridges has been widely investigated in the literature, but the effect of asynchronous ground motions for short-to-medium overall length girder bridges is a phenomenon that has not been adequately addressed by bridge codes and thus it warrants further research. For such bridges, the often-employed envelope response spectrum is not generally applicable for asynchronous ground motions as this is a multiple-support excitation problem where potential local demand concentrations are critical. This study investigates the effects of asynchronous ground motion on the seismic response of short-to-medium overall length girder bridges with reinforced concrete columns considering crustal, subcrustal and subduction earthquakes. The main source of spatial variability of ground motions considered was the variation in the local soil conditions at the foundation of 3-span (short) and 7-span (medium) overall length prototype girder bridges. Soil classes A (rocky soil) and E (softer soil) were considered to establish different combinations of soil distribution in the foundation and then compared to baseline models where site class C was applied to all the supports of the structure to study the effects of asynchronous ground motions. It was found that the variation of site class in the foundations for such structures could produce detrimental effects on the dynamic response of the structure. The presence of softer soil in most of the structure's foundations elongated the vibration period of the structure and resulted in higher displacement demands. Results also showed that critical demands are concentrated at locations where the soil conditions change, indicating increased sensitivity to seismic effects at certain locations, which would not be captured by the typical code-prescribed procedure in the presence of asynchronous ground motion effects.
Conventional steel moment-resisting frames (SMRFs) absorb seismic energy through steel yielding behavior, leading to significant residual displacement. Although steel yielding behavior can ensure the seismic safety of SMRFs under strong earthquakes, excessive residual displacement may lead to post-earthquake demolition decisions, causing a large amount of economic loss. This paper aims to develop a peak and residual displacement-based design (PRDBD) method for controlling the peak and residual inter-story drift responses of SMRFs by installing self-centering braces. The peak and residual displacements are both set as the design targets in the proposed PRDBD method. To this end, the machine learning prediction models of inelastic and residual displacement ratios were first developed based on the median responses of single-degree-of-freedom systems under earthquakes. The detailed design steps of the proposed PRDBD method were subsequently introduced. The three- and nine-story demonstration buildings were retrofitted by using the PRDBD method with two different design targets. Static and dynamic analyses were conducted to validate the effectiveness of the proposed PRDBD method. The static analysis results indicated that the self-centering braces could efficiently enhance the SMRF’s stiffness and strength. The retrofitted SMRFs showed no strength deterioration, whereas the original SMRFs showed obvious strength deterioration at the roof drifts of 3.2% and 2.5% in the three- and nine-story buildings, respectively. The dynamic analysis results confirm that the self-centering braces can efficiently reduce the peak and residual inter-story drift responses of the existing SMRFs and the retrofitted SMRFs can achieve the peak and residual inter-story performance objectives under the considered seismic intensity. Moreover, the retrofitted SMRFs can be fully recoverable after maximum considered earthquakes by controlling the maximum residual inter-story drift lower than 0.2%.
Self-centering energy-absorbing rocking core (SCENARIO) systems are emerging aseismic structural systems developed for obtaining excellent self-centering and collapse-resistant performance with negligible residual inter-story drifts in steel buildings under strong earthquakes. Despite its demonstrated superior structural performance, the nonstructural performance of SCENARIO systems, which is another essential consideration in seismic resilience evaluation of building structures, has not been well studied. For filling this research gap, this paper aims to make the original contributions by systematically assessing the structural and nonstructural damage of steel building structures equipped with SCENARIO systems under earthquakes and finding the efficient solution for enhancing the structural and nonstructural damage-control performance of SCENARIO systems. Two types of SCENARIO systems, including the SCENARIO system with friction spring dampers (denoted as SCENARIO-F system) and the SCENARIO system with hybrid dampers (denoted as SCENARIO-H system), were considered in this research. Three prototype steel buildings with SCENARIO systems were designed to achieve the same target displacement under design basis earthquakes (DBE). Incremental dynamic analyses (IDAs) were performed to study the seismic responses of the designed buildings subjected to far-field and near-fault ground motions with different intensities. The collapse-resistant performance, structural damage, post-earthquake repairability, and nonstructural damage of the designed buildings were investigated via seismic fragility analyses based on IDA results. Seismic fragility analysis results indicate that the SCENARIO-H systems show better performance than the SCENARIO-F systems in controlling structural and nonstructural damage under both far-field and near-fault earthquakes with high intensities. Benefiting from excellent self-centering capacity, the buildings equipped with SCENARIO-F and SCENARIO-H systems can show excellent post-earthquake repairability under strong earthquakes.
The purpose of this manuscript is to review LCA studies of organic field crops to identify best practices in collecting life cycle inventory data. Previous LCA studies of organic field crops from 2010 to 2021 were identified and data were collected in the following categories: 1) crops studied, 2) geographical locations and spatial resolution, 3) life cycle inventory data collected, 4) models used for estimating changes in soil carbon and for estimating field-level emissions and their associated data inputs. Based on these data, recommendations were made with respect to the best data to collect, and emissions and soil carbon models to use for LCAs of organic field crops. Based on the assessment of LCI inventory data collected for activities, inputs and emissions modelling, a list of recommendations for future LCI data collection for organic field crops was tabulated. This included the data that should come directly from farmers, as well as data from secondary sources, and the specific models that can be used for soil carbon and emissions modelling. The recommendations made based on the LCI data identified can be used to inform data collection for high quality, regionally resolved LCAs of organic field crop production.
In mathematical modelling, several different functional forms can often be used to fit a data set equally well, especially if the data is sparse. In such cases, these mathematically different but similar looking functional forms are typically considered interchangeable. Recent work, however, shows that similar functional responses may nonetheless result in significantly different bifurcation points for the Rosenzweig–MacArthur predator–prey system. Since the bifurcation behaviours include destabilizing oscillations, predicting the occurrence of such behaviours is clearly important. Ecologically, different bifurcation behaviours mean that different predictions may be obtained from the models. These predictions can range from stable coexistence to the extinction of both species, so obtaining more accurate predictions is also clearly important for conservationists. Mathematically, this difference in bifurcation structure given similar functional responses is called structural sensitivity. We extend the existing work to find that the Leslie–Gower–May predator–prey system is also structurally sensitive to the functional response. Using the Rosenzweig–MacArthur and Leslie–Gower–May models, we then aim to determine if there is some way to obtain a functional description of data so that different functional responses yield the same bifurcation structure, i.e., we aim to describe data such that our model is not structurally sensitive. We first add stochasticity to the functional responses and find that better similarity of the resulting bifurcation structures is achieved. Then, we analyse the functional responses using two different methods to determine which part of each function contributes most to the observed bifurcation behaviour. We find that prey densities around the coexistence steady state are most important in defining the functional response. Lastly, we propose a procedure for ecologists and mathematical modellers to increase the accuracy of model predictions in predator–prey systems.
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