Variasi Temperatur Pencampuran Terhadap Parameter Marshall Pada Campuran Lapis Aspal Beton

This study was conducted to determine the effect of temperature variations on the mixing processof the asphalt concrete AC-WC (Asphalt Concrete-Wearing Course) subtle gradations in themiddle limit and lower limit of the Marshall parameters with reference to specifications of BinaMarga, 2010.From the results of experiments conducted that the optimum asphalt content is used to middle limitusing a asphalt content of 5,7% and 6,8% for the lower limit after that mixing was done usingtemperature variation of 120 o C, 130 o C, 140 o C, 150 o C, and 160 o C.To a mixture of Laston AC-WC subtle gradations middle limit grading 5,7% asphalt contentmixing temperature using a temperature of 120 o C, 130 o C, 140 o C, 150 o C, 160 o C and still meet allstandards of marshall parameters. Ideal mixing temperature variations in the middle limit ofmixing temperature 150 o C-160 o C. While the lower limit to the level of 6,8% asphalt contentmixing temperatures between 120 o C-160 o C did not meet the specifications, because the MQ valuebelow the minimum value of 250 kg / mm

Blood-Based Gene Expression Profiles Models for Classification of Subsyndromal Symptomatic Depression and Major Depressive Disorder

Subsyndromal symptomatic depression (SSD) is a subtype of subthreshold depressive and also lead to significant psychosocial functional impairment as same as major depressive disorder (MDD). Several studies have suggested that SSD is a transitory phenomena in the depression spectrum and is thus considered a subtype of depression. However, the pathophysioloy of depression remain largely obscure and studies on SSD are limited. The present study compared the expression profile and made the classification with the leukocytes by using whole-genome cRNA microarrays among drug-free first-episode subjects with SSD, MDD, and matched controls (8 subjects in each group). Support vector machines (SVMs) were utilized for training and testing on candidate signature expression profiles from signature selection step. Firstly, we identified 63 differentially expressed SSD signatures in contrast to control (P< = 5.0E-4) and 30 differentially expressed MDD signatures in contrast to control, respectively. Then, 123 gene signatures were identified with significantly differential expression level between SSD and MDD. Secondly, in order to conduct priority selection for biomarkers for SSD and MDD together, we selected top gene signatures from each group of pair-wise comparison results, and merged the signatures together to generate better profiles used for clearly classify SSD and MDD sets in the same time. In details, we tried different combination of signatures from the three pair-wise compartmental results and finally determined 48 gene expression signatures with 100% accuracy. Our finding suggested that SSD and MDD did not exhibit the same expressed genome signature with peripheral blood leukocyte, and blood cell–derived RNA of these 48 gene models may have significant value for performing diagnostic functions and classifying SSD, MDD, and healthy controls

Nine New Gingerols from the Rhizoma of Zingiber officinale and Their Cytotoxic Activities

Nine new gingerols, including three 6-oxo-shogaol derivatives [(Z)-6-oxo-[6]-shogaol (1), (Z)-6-oxo-[8]-shogaol (2), (Z)-6-oxo-[10]-shogaol (3)], one 6-oxoparadol derivative [6-oxo-[6]-paradol (4)], one isoshogaol derivative [(E)-[4]-isoshogaol (5)], and four paradoldiene derivatives [(4E,6Z)-[4]-paradoldiene (8), (4E,6E)-[6]-paradoldiene (9), (4E,6E)-[8]-paradoldiene (10), (4E,6Z)-[8]-paradoldiene (11)], together with eight known analogues, were isolated from the rhizoma of Zingiber officinale. Their structures were elucidated on the basis of spectroscopic data. It was noted that the isolation of 6-oxo-shogaol derivatives represents the first report of gingerols containing one 1,4-enedione motif. Their structures were elucidated on the basis of spectroscopic and HRESIMS data. All the new compounds were evaluated for their cytotoxic activities against human cancer cells (MCF-7, HepG-2, KYSE-150)

A convergence theorem for sums of dependent Hilbert space valued triangular arrays

A generalization of Chung's (1974) theorem concerning a.s. convergence for sums of triangular arrays is proved under conditions weaker than zero correlation. A theorem of Ahn (1988) and a theorem of Jobson and Fuller (1980) can then be proved. Originally these two theorems were proved by a lemma of Jobson and Fuller (1980), but there exists a counter example for this lemma.Dependent triangular arrays a.s. convergence

The neutrophil-to-Lymphocyte ratio is associated with clinical symptoms in first-episode medication-naïve patients with schizophrenia

Abstract Innate immunity has been shown to be associated with schizophrenia (Sch). This study explored the relationship between symptoms and neutrophil-to-lymphocyte ratio (NLR) (a marker of innate immunity) in patients with Sch. Ninety-seven first-episode medication-naïve (FEMN) patients with Sch and 65 healthy controls were recruited in this study. We measured the complete blood count and assessed the clinical symptoms using the PANSS scales. We found higher NEU counts and NLR in patients with Sch compared with control subjects. Male patients showed a higher NEU count than female patients. In addition, FEMN patients with higher NLR and NEU values showed higher PANSS-p, PANSS-g, and PANSS-total scores (all p < 0.05). Regression analysis revealed that NLR was a predictor for PANSS total scores in patients with Sch. Higher NLR value was observed in patients with Sch and the significant associations between NLR and psychotic symptoms indicate that an imbalance in inflammation and innate immune system may be involved in the pathophysiology of Sch

A Novel Seventeen-Gene Metabolic Signature for Predicting Prognosis in Colon Cancer

A metabolic disorder is considered one of the hallmarks of cancer. Multiple differentially expressed metabolic genes have been identified in colon cancer (CC), and their biological functions and prognostic values have been well explored. The purpose of the present study was to establish a metabolic signature to optimize the prognostic prediction in CC. The related data were downloaded from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) database, and Gene Expression Omnibus (GEO) combined with GSE39582 set, GSE17538 set, GSE33113 set, and GSE37892 set. The differentially expressed metabolic genes were selected for univariate Cox regression and lasso Cox regression analysis using TCGA and GTEx datasets. Finally, a seventeen-gene metabolic signature was developed to divide patients into a high-risk group and a low-risk group. Patients in the high-risk group presented poorer prognosis compared to the low-risk group in both TCGA and GEO datasets. Moreover, gene set enrichment analyses demonstrated multiple significantly enriched metabolism-related pathways. To sum up, our study described a novel seventeen-gene metabolic signature for prognostic prediction of colon cancer

Reduction of cogging torque and electromagnetic vibration based on different combination of pole arc coefficient for interior permanent magnet synchronous machine

Cogging torque and electromagnetic vibration are two important factors for evaluating permanent magnet synchronous machine (PMSM) and are key issues that must be considered and resolved in the design and manufacture of high-performance PMSM for electric vehicles. A fast and accurate magnetic field calculation model for interior permanent magnet synchronous machine (IPMSM) is proposed in this article. Based on the traditional magnetic potential permeance method, the stator cogging effect and complex boundary conditions of the IPMSM can be fully considered in this model, so as to realize the rapid calculation of equivalent magnetomotive force (MMF), air gap permeance, and other key electromagnetic properties. In this article, a 6-pole 36-slot IPMSM is taken as an example to establish its equivalent solution model, thereby the cogging torque is accurately calculated. And the validity of this model is verified by a variety of different magnetic pole structures, pole slot combinations machines, and prototype experiments. In addition, the improvement measure of the machine with different combination of pole arc coefficient is also studied based on this model. Cogging torque and electromagnetic vibration can be effectively weakened. Combined with the finite element model and multi-physics coupling model, the electromagnetic characteristics and vibration performance of this machine are comprehensively compared and analyzed. The analysis results have well verified its effectiveness. It can be extended to other structures or types of PMSM and has very important practical value and research significance

Multi-featured spatial-temporal and dynamic multi-graph convolutional network for metro passenger flow prediction

Metro passenger flow prediction is an essential part of crowd flow forecasting and intelligent transportation management systems. However, two challenges still need to be addressed to achieve a more accurate prediction: (1) accounting for featural dependence instead of considering only the temporal connection and spatial relations; (2) utilising graph structures to address non-European relationships of spatial and featural dependence. To address these challenges, we developed a novel model called the multi-featured spatial-temporal (MFST) and dynamic multi-graph convolutional network (DMGCN) model. Temporal connections are learned from both the local and global information in a time-series sequence using the combination of a time-trend feature mapping block and a gated recurrent unit block. Spatial relation and featural dependence are separately captured by two DMGCN blocks. Each DMGCN block encodes various relationships by constructing multiple graphs consisting of predefined and non-defined topologies. The results of evaluations conducted of the MFST tensor and the DMGCN on the real-world Beijing subway dataset indicate that the prediction performance of the proposed model is superior to that of the existing baselines. The proposed model thus contributes significantly to the improvement of public safety by providing early warnings of large passenger flow and enabling the smart scheduling of resources