Stray Example Sheltering by Loss Regularized SVM and k NN Preprocessor

[[abstract]]This paper presents a new model developed by merging a non-parametric k-nearest-neighbor (kNN) preprocessor into an underlying support vector machine (SVM) to provide shelters for meaningful training examples, especially for stray examples scattered around their counterpart examples with different class labels. Motivated by the method of adding heavier penalty to the stray example to attain a stricter loss function for optimization, the model acts to shelter stray examples. The model consists of a filtering kNN emphasizer stage and a classical classification stage. First, the filtering kNN emphasizer stage was employed to collect information from the training examples and to produce arbitrary weights for stray examples. Then, an underlying SVM with parameterized real-valued class labels was employed to carry those weights, representing various emphasized levels of the examples, in the classification. The emphasized weights given as heavier penalties changed the regularization in the quadratic programming of the SVM, and brought the resultant decision function into a higher training accuracy. The novel idea of real-valued class labels for conveying the emphasized weights provides an effective way to pursue the solution of the classification inspired by the additional information. The adoption of the kNN preprocessor as a filtering stage is effective since it is independent of SVM in the classification stage. Due to its property of estimating density locally, the kNN method has the advantage of distinguishing stray examples from regular examples by merely considering their circumstances in the input space. In this paper, detailed experimental results and a simulated application are given to address the corresponding properties. The results show that the model is promising in terms of its original expectations.[[booktype]]紙本[[booktype]]電子

Deep learning based real-time facial mask detection and crowd monitoring

During the Covid pandemic, the importance of wearing mask has been noted globally. Additionally, crowded human clusters facilitated the transmission of the virus, which brings up the need for new systems for monitoring such situations. To address such issues, this research proposes an object recognition visual system based on deep learning to monitor the wearing of masks in a certain space and the control of the number of people indoors as an important tool during an epidemic. This research mainly investigates two types of identification. The first is to monitor whether people entering the site wear a mask at the entrance and exit of the field, and the second is to count the number of people entering a specific area. Experimental results show that by utilising the visual sensor, it is possible to detect and identify the people who frequently enter and exit in real-time. An advanced transfer learning approach has been employed to achieve the best discrimination performance. The actual training results prove that the migration learning Mask R-CNN algorithm produced by this method and the original Mask R-CNN algorithm have increased the mAP by 3%, reaching a mAP of 96%. In addition, the accuracy of the random sampling and identification in actual scenes has reached 92.1%. The developed deep learning vision system has an enhanced identification ability for the verification and analysis of actual scenes and has great application potential

Approximation Order for Multivariate Durrmeyer Operators with Jacobi Weights

Using the equivalence relation between K-functional and modulus of smoothness, we establish a strong direct theorem and an inverse theorem of weak type for multivariate Bernstein-Durrmeyer operators with Jacobi weights on a simplex in this paper. We also obtain a characterization for multivariate Bernstein-Durrmeyer operators with Jacobi weights on a simplex. The obtained results not only generalize the corresponding ones for Bernstein-Durrmeyer operators, but also give approximation order of Bernstein-Durrmeyer operators

Neurological soft signs in persons with amnestic mild cognitive impairment and the relationships to neuropsychological functions

BACKGROUND: Neurological abnormalities have been reported in people with amnestic mild cognitive impairment (aMCI). The current study aimed to examine the prevalence of neurological soft signs (NSS) in this clinical group and to examine the relationship of NSS to other neuropsychological performances. METHODS: Twenty-nine people with aMCI and 28 cognitively healthy elderly people were recruited for the present study. The NSS subscales (motor coordination, sensory integration, and disinhibition) of the Cambridge Neurological Inventory and a set of neuropsychological tests were administered to all the participants. RESULTS: People with aMCI exhibited significantly more motor coordination signs, disinhibition signs, and total NSS than normal controls. Correlation analysis showed that the motor coordination subscale score and total score of NSS were significantly inversely correlated with the combined Z-score of neuropsychological tests in aMCI group. CONCLUSIONS: These preliminary findings suggested that people with aMCI demonstrated a higher prevalence of NSS compared to healthy elderly people. Moreover, NSS was found to be inversely correlated with the neuropsychological performances in persons with aMCI. When taken together, these findings suggested that NSS may play a potential important role and serve as a tool to assist in the early detection of aMCI

Growth mechanism and magnon excitation in NiO nanowalls

The nanosized effects of short-range multimagnon excitation behavior and short-circuit diffusion in NiO nanowalls synthesized using the Ni grid thermal treatment method were observed. The energy dispersive spectroscopy mapping technique was used to characterize the growth mechanism, and confocal Raman scattering was used to probe the antiferromagnetic exchange energy J2 between next-nearest-neighboring Ni ions in NiO nanowalls at various growth temperatures below the Neel temperature. This study shows that short spin correlation leads to an exponential dependence of the growth temperatures and the existence of nickel vacancies during the magnon excitation. Four-magnon configurations were determined from the scattering factor, revealing a lowest state and monotonic change with the growth temperature

Clueless/CLUH regulates mitochondrial fission by promoting recruitment of Drp1 to mitochondria

Mitochondrial fission is critically important for controlling mitochondrial morphology, function, quality and transport. Drp1 is the master regulator driving mitochondrial fission, but exactly how Drp1 is regulated remains unclear. Here, we identified Drosophila Clueless and its mammalian orthologue CLUH as key regulators of Drp1. As with loss of drp1, depletion of clueless or CLUH results in mitochondrial elongation, while as with drp1 overexpression, clueless or CLUH overexpression leads to mitochondrial fragmentation. Importantly, drp1 overexpression rescues adult lethality, tissue disintegration and mitochondrial defects of clueless null mutants in Drosophila. Mechanistically, Clueless and CLUH promote recruitment of Drp1 to mitochondria from the cytosol. This involves CLUH binding to mRNAs encoding Drp1 receptors MiD49 and Mff, and regulation of their translation. Our findings identify a crucial role of Clueless and CLUH in controlling mitochondrial fission through regulation of Drp1

Inaccuracy of Intraocular Lens Power Prediction for Cataract Surgery in Angle-Closure Glaucoma

PURPOSE: To assess the accuracy of intraocular lens (IOL) power predictions for cataract surgery in eyes with primary angle-closure glaucoma (ACG). Because of shifting of the capsular bag apparatus and shortening of the axial length, preoperative calculation of IOL power may be inaccurate for eyes with ACG. MATERIALS AND METHODS: This retrospective comparative case series comprised of 42 eyes from 42 patients with primary ACG and 45 eyes from 45 subjects with normal open-angles undergoing uneventful cataract surgery. Anterior segment biometry including anterior chamber depth, lens thickness, and axial length were compared. Using the SRK-II formula, the powers of the implanted IOL and the actual postoperative spherical equivalent (SE) refractive errors were compared between the two groups. Also, the absolute values of differences between predicted and residual SE refractive errors were also analyzed for each group. RESULTS: In ACG patients, anterior chamber depth and axial length were shorter and the lens was thicker than normal controls (all p < 0.001). Even though residual SE refractive error was not significantly different (p = 0.290), the absolute value of the difference between predicted and residual SE refractive error was 0.64 +/- 0.50 diopters in AGC patients and 0.39 +/- 0.36 diopters in control subjects (p = 0.012). The number of eyes that resulted in inaccurate IOL power predictions of more than 0.5 diopters were 21 (50.00%) in the ACG group, but only 12 (26.67%) in the control group (p = 0.043). CONCLUSION: IOL power predictions for cataract surgery in ACG patients can be inaccurate, and it may be associated with their unique anterior segment anatomy.ope

Depression in Chinese patients with type 2 diabetes: associations with hyperglycemia, hypoglycemia, and poor treatment adherence.

BackgroundWe hypothesize that depression in type 2 diabetes might be associated with poor glycemic control, in part due to suboptimal self-care. We tested this hypothesis by examining the associations of depression with clinical and laboratory findings in a multicenter survey of Chinese type 2 diabetic patients.Method2538 patients aged 18-75 years attending hospital-based clinics in four cities in China underwent detailed clinical-psychological-behavioral assessment during a 12-month period between 2011 and 2012. Depression was diagnosed if Patient Health Questionnaire-9 (PHQ-9) score ≥10. Diabetes self-care and medication adherence were assessed using the Summary of Diabetes Self-care Activities and the 4-item Morisky medication adherence scale respectively.ResultsIn this cross-sectional study (mean age: 56.4 ± 10.5[SD] years, 53% men), 6.1% (n = 155) had depression. After controlling for study sites, patients with depression had higher HbA(1c) (7.9 ± 2.0 vs. 7.7 ± 2.0%, P = 0.008) and were less likely to achieve HbA(1c) goal of &lt;7.0% (36.2% vs 45.6%, P = 0.004) than those without depression. They were more likely to report hypoglycemia and to have fewer days of being adherent to their recommended diet, exercise, foot care and medication. In logistic regression, apart from young age, poor education, long disease duration, tobacco use, high body mass index, use of insulin, depression was independently associated with failure to attain HbA(1c) target (Odds Ratio [OR] = 1.56, 95%CI:1.05-2.32, P = 0.028). The association between depression and glycemic control became non-significant after inclusion of adherence to diet, exercise and medication (OR = 1.48, 95% CI 0.99-2.21, P = 0.058).ConclusionDepression in type 2 diabetes was closely associated with hyperglycemia and hypoglycemia, which might be partly mediated through poor treatment adherence

Anti-Obesity and Anti-Adipogenic Effects of Chitosan Oligosaccharide (GO2KA1) in SD Rats and in 3T3-L1 Preadipocytes Models

Excess body weight is a major risk factor for type 2 diabetes (T2D) and associated metabolic complications, and weight loss has been shown to improve glycemic control and decrease morbidity and mortality in T2D patients. Weight-loss strategies using dietary interventions produce a significant decrease in diabetes-related metabolic disturbance. We have previously reported that the supplementation of low molecular chitosan oligosaccharide (GO2KA1) significantly inhibited blood glucose levels in both animals and humans. However, the effect of GO2KA1 on obesity still remains unclear. The aim of the study was to evaluate the anti-obesity effect of GO2KA1 on lipid accumulation and adipogenic gene expression using 3T3-L1 adipocytes in vitro and plasma lipid profiles using a Sprague-Dawley (SD) rat model. Murine 3T3-L1 preadipocytes were stimulated to differentiate under the adipogenic stimulation in the presence and absence of varying concentrations of GO2KA1. Adipocyte differentiation was confirmed by Oil Red O staining of lipids and the expression of adipogenic gene expression. Compared to control group, the cells treated with GO2KA1 significantly decreased in intracellular lipid accumulation with concomitant decreases in the expression of key transcription factors, peroxisome proliferator-activated receptor gamma (PPARγ) and CCAAT/enhancer-binding protein alpha (CEBP/α). Consistently, the mRNA expression of downstream adipogenic target genes such as fatty acid binding protein 4 (FABP4), fatty acid synthase (FAS), were significantly lower in the GO2KA1-treated group than in the control group. In vivo, male SD rats were fed a high fat diet (HFD) for 6 weeks to induced obesity, followed by oral administration of GO2KA1 at 0.1 g/kg/body weight or vehicle control in HFD. We assessed body weight, food intake, plasma lipids, levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) for liver function, and serum level of adiponectin, a marker for obesity-mediated metabolic syndrome. Compared to control group GO2KA1 significantly suppressed body weight gain (185.8 ± 8.8 g vs. 211.6 ± 20.1 g, p \u3c 0.05) with no significant difference in food intake. The serum total cholesterol, triglyceride, and low-density lipoprotein (LDL) levels were significantly lower in the GO2KA1-treated group than in the control group, whereas the high-density lipoprotein (HDL) level was higher in the GO2KA1 group. The GO2KA1-treated group also showed a significant reduction in ALT and AST levels compared to the control. Moreover, serum adiponectin levels were significantly 1.5-folder higher than the control group. These in vivo and in vitro findings suggest that dietary supplementation of GO2KA1 may prevent diet-induced weight gain and the anti-obesity effect is mediated in part by inhibiting adipogenesis and increasing adiponectin level