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A detection and classification machine-learning model to inspect Thin Film Transistor Liquid Crystal Display (TFT-LCD) Mura is proposed in this study. To improve the capability of the machine-learning model to inspect panels’ low-contrast grayscale images, piecewise gamma correction and a Selective Search algorithm are applied to detect and optimize the feature regions based on the Semiconductor Equipment and Materials International Mura (SEMU) specifications. In this process, matching the segment proportions to gamma values of piecewise gamma is a task that involves derivative-free optimization which is trained by adaptive particle swarm optimization. The detection accuracy rate (DAR) is approximately 93.75%. An enhanced convolutional neural network model is then applied to classify the Mura type through using the Taguchi experimental design method that identifies the optimal combination of the convolution kernel and the maximum pooling kernel sizes. A remarkable defect classification accuracy rate (CAR) of approximately 96.67% is ultimately achieved. The entire defect detection and classification process can be completed in about 3 milliseconds.

ABSTRACT Vascular adhesion protein‐1 (VAP‐1) plays a dual role with its adhesive and enzymatic properties, facilitating leukocyte migration to sites of inflammation and catalyzing the breakdown of primary amines into harmful by‐products, which are linked to diabetic complications. Present in various tissues, VAP‐1 also circulates in a soluble form in the bloodstream. Diabetes is associated with several complications such as cardiovascular disease, retinopathy, nephropathy, and neuropathy, significantly contributing to disability and mortality. These complications arise from hyperglycemia‐induced oxidative stress, inflammation, and the formation of advanced glycation end‐products (AGEs). Earlier research, including our own from the 1990s and early 2000s, has underscored the critical role of VAP‐1 in these pathological processes, prompting extensive investigation into its contribution to diabetic complications. In this review, we examine the involvement of VAP‐1 in diabetes and its complications, alongside its link to other conditions related to diabetes, such as cancer and metabolic dysfunction‐associated fatty liver disease. We also explore the utility of soluble VAP‐1 as a biomarker for diabetes, its complications, and other related conditions. Since the inhibition of VAP‐1 to treat diabetic complications is a novel and promising treatment option, further studies are needed to translate the beneficial effect of VAP‐1 inhibitors observed in animal studies to clinical trials recruiting human subjects. Besides, future studies should focus on using serum sVAP‐1 levels for risk assessment in diabetic patients, identifying those who need intensive glycemic control, and determining the patient population that would benefit most from VAP‐1 inhibitor therapies. Vascular adhesion protein‐1 (VAP‐1) has adhesive and enzymatic functions, aiding leukocyte migration to inflammation sites and producing by‐products linked to diabetic complications. This review focuses on the impact of VAP‐1 on diabetes and its complications, its association with related diseases, and the potential of soluble VAP‐1 as a biomarker.

Overweight and obesity are important risk factors of gestational diabetes mellitus (GDM). Clustering of metabolic risk factors in early pregnancy may be a potential pathogenesis between the link of overweight/obesity and GDM. Since it remains unexplored, we investigated if overweight and obesity are associated with clustering of metabolic risk factors in early pregnancy and the risk of GDM in this cohort study. Total 527 women who visited National Taiwan University Hospital for prenatal care in between November 2013 to April 2018 were enrolled. Risk factors of GDM in the first prenatal visit (FPV) were recorded. Overweight/obesity was defined if body mass index ≥24 kg/m2. GDM was diagnosed from the result of a 75g oral glucose tolerance test in 24-28 gestational weeks. Overweight/obesity was associated with clustering of metabolic risk factors of GDM, including high fasting plasma glucose, high HbA1c, insulin resistance, high plasma triglyceride and elevated blood pressure in FPV (p<0.05). There was a positive relationship between the number of metabolic risk factors and the incidence of GDM (p <0.05). The odds ratios of HbA1c and diastolic blood pressure were higher in overweight/obese women, compared with those in normal-weight women. Overweight/obesity is associated with clustering of metabolic risk factors in early pregnancy, which is correlated with higher risk of GDM. Our findings suggest that metabolic risk factors during early pregnancy should be evaluated in overweight/obese women.

DAPA‐HF EMPEROR‐Reduced Dapagliflozin Placebo Empagliflozin Placebo n 2,373 2,371 1,863 1,867 Age (years) 66.2 ± 11.0 66.5 ± 10.8 67.2 ± 10.8 66.5 ± 11.2 Female sex, n (%) 564 (23.8) 545 (23.0) 437 (23.5) 456 (24.4) NYHA functional classification, n (%) II 1,606 (67.7) 1,597 (67.4) 1,399 (75.1) 1,401 (75.0) III 747 (31.5) 751 (31.7) 455 (24.4) 455 (24.4) IV 20 (0.8) 23 (1.0) 9 (0.5) 11 (0.6) LVEF (%) 31.2 ± 6.7 30.9 ± 6.9 27.7 ± 6.0 27.2 ± 6.1 Median NT‐pro BNP, pg/mL (IQR) 1,428 (857–2,655) 1,446 (857–2,641) 1,887 (1,077–3,429) 1,926 (1,153–3,525) Ischemic cause of heart failure, n (%) 1,316 (55.5) 13,158 (57.3) 983 (52.8) 946 (50.7) History of HHF, n (%) 1,124 (47.4) 1,127 (47.5) 577 (31.0) 574 (30.7) Device therapy, n (%) ICD 622 (26.2) 620 (26.1) 578 (31.0) 593 (31.85) CRT 190 (8.0) 164 (6.9) 220 (11.8) 222 (11.9) Diabetes, n (%) 993 (41.8) 990 (41.8) 927 (49.8) 929 (49.8) CKD, n (%) 962 (40.6) 964 (40.7) 893 (48.0) 906 (48.6) eGFR (mL/min/1.73 m2) 66.0 ± 19.6 65.5 ± 19.3 61.8 ± 21.7 62.2 ± 21.5 Heart failure medications ACE inhibitor 1,332 (56.1) 1,329 (56.1) 1,314 (70.5)† 1,286 (68.9)† ARB 675 (28.4) 632 (26.7) ARNI 250 (10.5) 258 (10.9) 340 (18.3) 387 (20.7) MRA 1,696 (71.5) 1,674 (70.6) 1,306 (70.1) 1,355 (72.6) Chronic kidney disease (CKD) was defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2. †Total number (%) for the use of angiotensin‐converting enzyme (ACE) inhibitor or angiotensin‐receptor blocker (ARB) were shown. ARNI, angiotensin receptor‐neprilysin inhibitor; CRT, cardiac resynchronization therapy; eGFR, estimated glomerular filtration rate; DAPA‐HF, the dapagliflozin and prevention of adverse outcomes in heart failure trial; EMPEROR‐Reduced, the empagliflozin outcome trial in patients with chronic heart failure and a reduced ejection fraction; HHF, hospitalization for heart failure; ICD, implantable cardioverter‐defibrillator; IQR, interquartile range; LVEF, left ventricular ejection fraction; MRA, mineralocorticoid receptor antagonist; NT‐pro BNP, N‐terminal pro B‐type natriuretic peptide; NYHA, New York Heart Association. 2 TableComparison of outcomes in the dapagliflozin and prevention of adverse outcomes in heart failure trial (DAPA‐HF) and empagliflozin outcome trial in patients with chronic heart failure and a reduced ejection fraction (EMPEROR‐Reduced). DAPA‐HF EMPEROR‐Reduced Dapagliflozin Placebo HR (95% CI) Empagliflozin Placebo HR (95% CI) Primary composite outcome, n (%) 386 (16.3) 502 (21.2) 0.74 (0.65–0.85) 361 (19.4) 462 (24.7) 0.75 (0.65–0.86) Type 2 diabetes at baseline, n (%) Yes 215 (20.0) 271 (25.5) 0.75 (0.63–0.90)† 200 (21.6) 265 (28.5) 0.72 (0.60–0.87) No 171 (13.2) 231 (17.7) 0.73 (0.60–0.88)† 161 (17.2) 197 (21.0) 0.78 (0.64–0.97) Patients without type 2 diabetes at baseline, n (%) Hemoglobin A1c <5.7% 53 (12.1) 71 (16.9) 0.67 (0.47–0.96)† NA NA NA Hemoglobin A1c 5.7–6.4% 118 (13.7) 160 (18.0) 0.74 (0.59–0.94)† NA NA NA Change of laboratory and other measures from baseline‡ A1c (%) −0.21 ± 1.14* 0.04 ± 1.29 −0.28 ± 0.03* −0.12 ± 0.03 Weight (kg) −0.88 ± 3.86* 0.10 ± 4.09 −0.73 ± 0.13* 0.08 ± 0.13 Systolic blood pressure (mmHg) −1.92 ± 14.92* −0.38 ± 15.27 −2.4 ± 0.4 −1.7 ± 0.4 The primary composite outcome in dapagliflozin and prevention of adverse outcomes in heart failure trial (DAPA‐HF) trial included hospitalization for heart failure, an urgent visit for heart failure and cardiovascular death. The renal protection effects of SGLT2 inhibitors in patients with and without diabetes are tested in two large randomized controlled trials (a Study to Evaluate the Effect of Dapagliflozin on Renal Outcomes and Cardiovascular Mortality in Patients with Chronic Kidney Disease [DAPA‐CKD], NCT 03036150, and the Study of Heart and Kidney Protection with Empagliflozin [EMPA‐KIDNEY], NCT 03594110).

With the development of several new classes of anti‐diabetic drugs in the past decade, the concept for the pharmacological management of type 2 diabetes is evolving from ‘glycemic control’ to ‘organ protection’. Besides, the increase in the prevalence of an aging population urges a strategy focusing on safety and de‐intensification. In the coming years, with the development of several novel and potent anti‐obesity drugs, the ‘weight‐centric’ strategy is expected to gain more and more attention in the treatment of diabetes, since it can both prevent diabetic complications and optimize the quality of life. With all these strategies, clinicians should consider the patient’s clinical characteristics and make an individualized goal through shared decision making with the patient.

Sandwich panel structures (SPSs) with lattice cores can considerably lower material consumption while simultaneously maintaining adequate mechanical properties. Compared with extruded lattice types, triply periodic minimal surface (TPMS) lattices have light weight but better controllable mechanical properties. In this study, the different types of TPMS lattices inside an SPS were analysed comprehensively. Each SPS comprised two face sheets and a core filled with 20×5×1 TPMS lattices. The types of TPMS lattices considered included the Schwarz primitive (SP), Scherk’s surface type 2 (S2), Schoen I-graph-wrapped package (I-WP), and Schoen face-centred cubic rhombic dodecahedron (F-RD). The finite element method was applied to determine the mechanical performance of different TPMS lattices at different relative densities inside the SPS under a three-point bending test, and the results were compared with the values calculated from analytical equations. The results showed a difference of less than 21% between the analytical and numerical results for the deformation. SP had the smallest deformation among the TPMS lattices, and F-RD can withstand the highest allowable load. Different failure modes were proposed to predict potential failure mechanisms. The results indicated that the mechanical performances of the TPMS lattices were mainly influenced by the lattice geometry and relative density.

Background The aim was to determine the prevalence and impact of an occluded “culprit” artery (OCA) in patients with non-ST segment elevation myocardial infarction (NSTEMI). Methods We searched PubMed, EMBASE, and Web of Science, with no language restrictions, up to 1 Jul. 2016. Observational cohorts or clinical trials of adult NSTEMI were eligible for inclusion to determine the prevalence if the proportion of OCA on coronary angiography was reported. Studies were further eligible for inclusion to determine the outcome if the association between OCA and clinical endpoints was reported. Results Among the 60,898 patients with NSTEMI enrolled in 25 studies, 17,212 were found to have OCA. The average proportion of OCA in NSTEMI was 34% (95% CI 30–37%). Patients with OCA were more likely to have left circumflex artery as their culprit artery (odds ratio (OR) 1.65, 95% CI 1.15–2.37, p  = 0.007), and this was associated with lower left ventricular ejection fraction (standard mean difference -0.29, 95% CI -0.34 to -0.34, p  < 0.001), higher peak enzyme level (standard mean difference 0.43, 95% CI 0.27–0.58, p  < 0.001), and higher risk for cardiogenic shock (OR 1.66, 95% CI 1.35–2.04, p  < 0.001), compared with patients with a non-occlusive culprit artery. Death rate (OR 1.72, 95% CI 1.49–1.98, p  < 0.001) and recurrent myocardial infarction (OR 1.7, 95% CI 1.06–2.75, p  = 0.029) were also higher in patients with OCA, compared with patients with a non-occlusive culprit artery. Conclusions Patients with OCA comprised a substantial portion of the NSTEMI population. These patients present with more severe symptoms and worse clinical outcome. Whether these patients should be treated with more aggressive strategy warrants further study.