Grinding wheel condition monitoring with boosted classifiers

In this thesis, two data sets collected in grinding process under different cutting and wheel conditions were studied. One is the cutting forces in three directions, i.e. X, Y and Z, collected under two different cutting conditions. The other one is the acoustic emission (AE) signals collected under different wheel conditions(sharp and dull). For the goal of grinding wheel condition monitoring, the regression model with autocorrelated errors was proved to be effective and was used to extract features from signals in this study. The coefficients of the models served as the features used in the classification step that employed boosting method. Based on the AdaBoost and A-boosting algorithms which can only be used in two classes situation, two improved boosting methods called Adaboost-M and A-boosting-M, which can be used to classify multiple classes, are proposed. With the forces data set, we compared Adaboost-M and A-boosting-M against the traditional AdaBoost.M1 and the corresponding weak learners(KNN and Prototype). The accuracies of Adaboost-M and A-boosting-M are higher than that of AdaBoost.M1 and the weak learners in our application. With the AE data set, our focus is to recognize the signals collected when the wheels were dull from the signals collected when the wheels were sharp. The AdaBoost, A-boosting and the corresponding weak learners(KNN and Proto) were used. The results indicate that (i) boosting does not improve the effectiveness of k-nearest neighbor but greatly improve the effectives of the prototype classifier, (ii) depending upon the data, AdaBoost or A-Boosting might produce higher classification accuracy, (iii) the error of false positive is higher than the error of false negative for the better classifiers. Based on the study, the combined use of AR models for feature extraction and boosted algorithms for classification are proved to be a viable approach for grinding wheel condition monitoring

High altitude polycythemia and its maladaptive mechanisms: an updated review

High altitude polycythemia is a maladaptation of highlanders exposed to hypoxic environment, leading to high blood viscosity and severe cardiorespiratory dysfunction. Prolonged hypoxia causes respiratory depression and severe hypoxemia, and further mediates changes in genetic and molecular mechanisms that regulate erythropoiesis and apoptosis, ultimately resulting in excessive erythrocytosis (EE). This updated review investigated the maladaptive mechanisms of EE, including respiratory chemoreceptor passivation, sleep-related breathing disorders, sex hormones, iron metabolism, and hypoxia-related factors and pathways

Factors influencing patient willingness to participate in genetic research after a myocardial infarction

Abstract Background Achieving 'personalized medicine' requires enrolling representative cohorts into genetic studies, but patient self-selection may introduce bias. We sought to identify characteristics associated with genetic consent in a myocardial infarction (MI) registry. Methods We assessed correlates of participation in the genetic sub-study of TRIUMPH, a prospective MI registry (n = 4,340) from 24 US hospitals between April 2005 and December 2008. Factors examined included extensive socio-demographics factors, clinical variables, and study site. Predictors of consent were identified using hierarchical modified Poisson regression, adjusting for study site. Variation in consent rates across hospitals were quantified by the median rate ratio (MRR). Results Most subjects consented to donation of their genetic material (n = 3,484; 80%). Participation rates varied greatly between sites, from 40% to 100%. After adjustment for confounding factors, the MRR for hospital was 1.22 (95% confidence interval (CI) 1.11 to 1.29). The only patient-level factors associated with consent were race (RR 0.93 for African Americans versus whites, 95% CI 0.88 to 0.99) and body mass index (RR 1.03 for BMI ≥ 25, 95% CI 1.01 to 1.06). Conclusion Among patients with an MI there were notable differences in genetic consent by study site, but little association with patient-level factors. This suggests that variation in the way information is presented during recruitment, or other site factors, strongly influence patients' decision to participate in genetic studies.Peer Reviewe

Long‐Term Outcomes Among Elderly Survivors of Out‐of‐Hospital Cardiac Arrest

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139093/1/jah31396_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139093/2/jah31396.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139093/3/jah31396-sup-0001-SupInfo.pd

Wind-driven sediment exchange between the Indian marginal seas over the last 18,000 years

The Indian Coastal Current is the only channel for material exchange between the two largest marginal seas in the northern Indian Ocean: the Bay of Bengal and the Arabian Sea. However, its past history is poorly known, limiting accurate predictions of its future changes. Here, we present a new clay mineral record from south of India supported by interpretations of model simulations to trace its variability over the last 18,000 years. Decreased smectite/(illite+chlorite) ratios during the cold intervals suggest that a stronger northeasterly wind led to a mean southward flow of the Indian Coastal Current in the Bay of Bengal. In contrast, increased smectite/(illite+chlorite) ratios during the warm intervals suggest the opposite scenario. Combining the proxy record with model simulations, we infer that atmospheric circulation changes were the main driver of the changes. Moreover, a possible link is observed between a positive Indian Ocean Dipole (IOD) and weakened southward flow of the Indian Coastal Current in the Bay of Bengal during the Holocene. These findings imply that future warming scenarios, if associated with more intense positive IOD events as proposed, may lead to a reduction in fresh water transport from the Bay of Bengal to the Arabian Sea

Birt-Hogg-Dubé syndrome with c.1579_1580insA variant in a Chinese family: a case report

Birt-Hogg-Dubé (BHD) syndrome, is a rare genetic disease with heterogeneous manifestations in different populations. In this study, we reported a Chinese female BHD case and her family members with c.1579_1580insA variant in FLCN gene, who were characterized by diffused pulmonary cysts/bulla, and reviewed another five familial BHD cases in China. Based on these cases, recurrent spontaneous pneumothorax is likely to be the first symptom for BHD in Chinese patients, with particularly but not limited to c.1579_1580insA variant. Therefore, attention to the early diagnosis of BHD in China should focus on pulmonary signs, but skin or kidney lesions still can not be neglected

FMT reduces systemic inflammatory response in severe acute pancreatitis by increasing the abundance of intestinal Bifidobacteria and fecal bacteria

Severe acute pancreatitis (SAP) is one of the leading causes of hospital admissions for gastrointestinal diseases, with a rising incidence worldwide. Intestinal microbiota dysbiosis caused by SAP exacerbates systemic inflammatory response syndrome and organ dysfunction. Fecal microbiota transplantation (FMT) has emerged as a promising therapeutic option for gastrointestinal diseases. In this study, fecal samples from healthy, control, and FMT-treated groups were analyzed using 16S rRNA sequencing to assess microbiome abundance and diversity. Composition and functional prediction analyses were conducted to explore the mechanisms underlying FMT in SAP. FMT significantly improved clinical parameters in SAP patients, including leukocyte count, C-reactive protein (CRP), neutrophil granulocyte count, lactate dehydrogenase (LDH), and calcitonin (P < 0.05). Organ failure rates significantly increased in the control group but decreased in the FMT group after treatment (P < 0.05). Fecal microbiota sequencing revealed that FMT significantly upregulated the abundance of Bifidobacterium longum among all SAP patients (P < 0.05). Receiver operating characteristic (ROC) curve analysis indicated that Bifidobacterium longum might play a critical role in the efficacy of FMT, with an area under the curve (AUC) value of 0.84. Additionally, there was a negative correlation between Bifidobacterium longum abundance and procalcitonin (PCT) levels, as well as a negative correlation between Escherichia coli abundance and both CT and Ca values (P < 0.05). The relative abundances of Bifidobacterium longum and Escherichia coli were significantly higher in the FMT group compared to the Bifidobacterium triple viable group (P < 0.05). In conclusion, this research supports FMT as a safe and effective intervention for treating SAP patients