MDPI Contact

MDPI
St. Alban-Anlage 66,
4052 Basel, Switzerland
Support contact
Tel. +41 61 683 77 34
Fax: +41 61 302 89 18

For more contact information, see here.

秒速飞艇:Advanced Search

You can use * to search for partial matches.

Search Results

13 articles matched your search query. Search Parameters:
Authors = Wenjun Zhou ORCID = 0000-0003-2346-8151

秒速赛车是哪里的开奖 www.0dv0k.cn Matches by word:

WENJUN (182) , ZHOU (4972)

View options
order results:
result details:
results per page:
Articles per page View Sort by
Displaying article 1-50 on page 1 of 1.
Export citation of selected articles as:
Open AccessArticle Development and Validation of the Policies, Opportunities, Initiatives and Notable Topics (POINTS) Audit for Campuses and Worksites
Int. J. Environ. Res. Public Health 2019, 16(5), 778; https://doi.org/10.3390/ijerph16050778
Received: 28 January 2019 / Revised: 19 February 2019 / Accepted: 26 February 2019 / Published: 4 March 2019
Viewed by 289 | PDF Full-text (762 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Background: Workplace or campus wellness/obesity-prevention policies and initiatives can improve health. Research tools to assess worksite or campus policies/initiatives are scarce. Thus, the aim of this research is to develop and validate the policies, opportunities, initiatives, and notable topics (POINTS) audit. Methods: POINTS [...] Read more.
Background: Workplace or campus wellness/obesity-prevention policies and initiatives can improve health. Research tools to assess worksite or campus policies/initiatives are scarce. Thus, the aim of this research is to develop and validate the policies, opportunities, initiatives, and notable topics (POINTS) audit. Methods: POINTS was developed and refined via expert review, pilot-testing, and field testing. Trained researchers completed a web-based review from a student-focus or employee-focus regarding 34 health-promoting topics for colleges. Each topic was evaluated on a 0–2 scale: 0 = no policy/initiative, 1 = initiatives, 2 = written policy. When a written policy was detected, additional policy support questions (administered, monitored, reviewed) were completed. Results: Cronbach’s Alpha for the student-focused POINTS audit was α = 0.787 (34 items, possible points = 65), and for the employee-focused POINTS audit was α = 0.807 (26 items, possible points = 50). A total of 115 student-focused and 33 employee-focused audits were completed. Although there was little evidence of policy presence beyond stimulant standards (smoking and alcohol), there were extensive examples of health initiatives. The student-focused POINTS audit was validated using the Healthier Campus Initiative’s survey. Conclusions: POINTS is a web-based audit tool that is valid and useful for pre-assessment, advocacy, benchmarking, and tracking policies for health and well-being for students (campus) and employees (worksite). Full article
(This article belongs to the Section Health Behavior, Chronic Disease and Health Promotion)
Figures

Figure 1

Figure 1
<p>An example of the phases of identifying a policy with POINTS, regarding nutrient standards.</p>
Full article ">
Open AccessArticle Sex Differences in Lifestyle Behaviors among U.S. College Freshmen
Int. J. Environ. Res. Public Health 2019, 16(3), 482; https://doi.org/10.3390/ijerph16030482
Received: 4 January 2019 / Revised: 29 January 2019 / Accepted: 3 February 2019 / Published: 7 February 2019
Viewed by 348 | PDF Full-text (317 KB) | HTML Full-text | XML Full-text
Abstract
Within lifestyle behavior research, the sex of populations causes differences in behaviors and outcomes of studies. This cross-sectional study investigated lifestyle behavior patterns in college students, examining sex differences in four areas: Nutrition, physical activity, sleep, and stress. Data from over 1100 college [...] Read more.
Within lifestyle behavior research, the sex of populations causes differences in behaviors and outcomes of studies. This cross-sectional study investigated lifestyle behavior patterns in college students, examining sex differences in four areas: Nutrition, physical activity, sleep, and stress. Data from over 1100 college freshmen across 8 United States universities were used for this cross-sectional analysis. Self-reported data assessed fruit and vegetable intake, fat percent intake, physical activity, perceived stress, and sleep quality. Statistical analysis included Pearson chi-squared and Mann–Whitney’s U tests for scores by sex. Likewise, healthy cut-offs were used to determine frequency of participants within range of the five tools. Males reported higher intake of both fruits and vegetables, and percent energy from fat than females. Males also reported higher physical activity levels, lower stress levels, and poorer sleep quality than females. Of the five self-reported tools, males were found to have a larger frequency of participants with healthy ranges than females. In a large college freshmen sample, sex was found to be related to general lifestyle behaviors which strengthen results reported in the previous literature. These findings shed light on the need for lifestyle behavior interventions among at-risk college students to enhance their behaviors to healthy levels. Full article
Open AccessArticle More than Fast Food: Development of a Story Map to Compare Adolescent Perceptions and Observations of Their Food Environments and Related Food Behaviors
Int. J. Environ. Res. Public Health 2019, 16(1), 76; https://doi.org/10.3390/ijerph16010076
Received: 27 November 2018 / Revised: 18 December 2018 / Accepted: 21 December 2018 / Published: 28 December 2018
Viewed by 716 | PDF Full-text (5891 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The purpose of this convergent, multiphase, mixed methods study was to better understand the perceptions of adolescents’ food environments and related food behaviors using grounded visualization and story mapping. Adolescents from one high school (13–16 years) in the southeastern United States were evaluated [...] Read more.
The purpose of this convergent, multiphase, mixed methods study was to better understand the perceptions of adolescents’ food environments and related food behaviors using grounded visualization and story mapping. Adolescents from one high school (13–16 years) in the southeastern United States were evaluated via data from health behavior surveys (n = 75), school environment maps, focus groups (n = 5 groups), and Photovoice (n = 6) from October 2016 to April 2017. Data from each phase were integrated using grounded visualization and new themes were identified (n = 7). A story map using ArcGIS Online was developed from data integration, depicting the newly identified themes. Participants failed to meet national recommendations for fruit and vegetable intake (2.71 cups). Focus group and Photovoice findings indicated the need for convenience food items in all environments. The story map is an online, interactive dissemination of information, with five maps, embedded quotes from focus groups, narrative passages with data interpretation, pictures to highlight themes, and a comparison of the participants’ food environments. Story mapping and qualitative geographic information systems (GIS) approaches may be useful when depicting adolescent food environments and related food behaviors. Further research is needed when evaluating story maps and how individuals can be trained to create their own maps. Full article
(This article belongs to the Special Issue Environmental Influences on Food Behaviour)
Figures

Figure 1

Figure 1
<p>In-depth analysis of school food environment with buffer zone surrounding school highlighted (green).</p>
Full article ">Figure 2
<p>Pictorial depiction of online, interactive story map as follows: (<bold>a</bold>) Start of convenience section where fast food is depicted for family meals and embedded quote from focus groups; (<bold>b</bold>) next convenience section where school food environment with buffer zone and identified food outlets are shown; (<bold>c</bold>) transportation shown with narrative regarding dependent travel activity and embedded quotes from focus groups; (<bold>d</bold>) the next section depicting support of healthy behaviors starts with cooking skills; (<bold>e</bold>) mapping of county region from Prong 1; (<bold>f</bold>) use of technology with meal planning and preparation shown.</p>
Full article ">
Open AccessArticle Self-Reported vs. Measured Height, Weight, and BMI in Young Adults
Int. J. Environ. Res. Public Health 2018, 15(10), 2216; https://doi.org/10.3390/ijerph15102216
Received: 6 September 2018 / Revised: 5 October 2018 / Accepted: 8 October 2018 / Published: 11 October 2018
Viewed by 543 | PDF Full-text (732 KB) | HTML Full-text | XML Full-text
Abstract
Self-reported height and weight, if accurate, provide a simple and economical method to track changes in body weight over time. Literature suggests adults tend to under-report their own weight and that the gap between self-reported weight and actual weight increases with obesity. This [...] Read more.
Self-reported height and weight, if accurate, provide a simple and economical method to track changes in body weight over time. Literature suggests adults tend to under-report their own weight and that the gap between self-reported weight and actual weight increases with obesity. This study investigates the extent of discrepancy in self-reported height, weight, and subsequent Body Mass Index (BMI) versus actual measurements in young adults. Physically measured and self-reported height and weight were taken from 1562 students. Male students marginally overestimated height, while females were closer to target. Males, on average, closely self-reported weight. Self-reported anthropometrics remained statistically correlated to actual measures in both sexes. Categorical variables of calculated BMI from both self-reported and actual height and weight resulted in significant agreement for both sexes. Researcher measured BMI (via anthropometric height and weight) and sex were both found to have association with self-reported weight while only sex was related to height difference. Regression examining weight difference and BMI was significant, specifically with a negative slope indicating increased BMI led to increased underestimation of weight in both sexes. This study suggests self-reported anthropometric measurements in young adults can be used to calculate BMI for weight classification purposes. Further investigation is needed to better assess self-reported vs measured height and weight discrepancies across populations. Full article
(This article belongs to the Special Issue Recent Advances of Adolescents and Children Health Research)
Figures

Figure 1

Figure 1
<p>Simple linear regression of weight and height differences on BMI. (<bold>a</bold>) Plot of regression examining weight difference and BMI relationship. (<bold>b</bold>) Plot of regression examining height difference and BMI relationship.</p>
Full article ">Figure 2
<p>ANCOVA of weight and height differences on BMI for males and females. (<bold>a</bold>) ANCOVA model examining weight difference and BMI relationship among genders. (<bold>b</bold>) ANCOVA model examining height difference and BMI relationship among genders.</p>
Full article ">
Open AccessArticle A Novel Fault Location Method for a Cross-Bonded HV Cable System Based on Sheath Current Monitoring
Sensors 2018, 18(10), 3356; https://doi.org/10.3390/s18103356
Received: 7 September 2018 / Revised: 3 October 2018 / Accepted: 6 October 2018 / Published: 8 October 2018
Viewed by 463 | PDF Full-text (11924 KB) | HTML Full-text | XML Full-text
Abstract
In order to improve the practice in the operation and maintenance of high voltage (HV) cables, this paper proposes a fault location method based on the monitoring of cable sheath currents for use in cross-bonded HV cable systems. This method first analyzes the [...] Read more.
In order to improve the practice in the operation and maintenance of high voltage (HV) cables, this paper proposes a fault location method based on the monitoring of cable sheath currents for use in cross-bonded HV cable systems. This method first analyzes the power–frequency component of the sheath current, which can be acquired at cable terminals and cable link boxes, using a Fast Fourier Transform (FFT). The cable segment where a fault occurs can be localized by the phase difference between the sheath currents at the two ends of the cable segment, because current would flow in the opposite direction towards the two ends of the cable segment with fault. Conversely, in other healthy cable segments of the same circuit, sheath currents would flow in the same direction. The exact fault position can then be located via electromagnetic time reversal (EMTR) analysis of the fault transients of the sheath current. The sheath currents have been simulated and analyzed by assuming a single-phase short-circuit fault to occur in every cable segment of a selected cross-bonded high voltage cable circuit. The sheath current monitoring system has been implemented in a 110 kV cable circuit in China. Results indicate that the proposed method is feasible and effective in location of HV cable short circuit faults. Full article
Figures

Figure 1

Figure 1
<p>The configuration of a cross-bonded HV cable and its online sheath currents monitoring system.</p>
Full article ">Figure 2
<p>A typical structure of a single core HV cable.</p>
Full article ">Figure 3
<p>Equivalent two-port network of the cable.</p>
Full article ">Figure 4
<p>Schematic diagram of the cable system.</p>
Full article ">Figure 5
<p>The simulation results of sheath currents during a short circuit fault. (<bold>a</bold>) The detected sheath current at G1 (<bold>b</bold>) The detected sheath current at J1 (<bold>c</bold>) The detected sheath current at J2 (<bold>d</bold>) The detected sheath current at G2.</p>
Full article ">Figure 6
<p>An equivalent circuit diagram of the sheath current.</p>
Full article ">Figure 7
<p>The short-circuit fault between the core conductor and the metal sheath.</p>
Full article ">Figure 8
<p>The core conductor current with its magnetic flux.</p>
Full article ">Figure 9
<p>The relationship between <italic>P</italic>(segment) and the fault location.</p>
Full article ">Figure 10
<p>The relationship between <italic>P</italic>(segment) and <italic>R<sub>g.</sub></italic></p>
Full article ">Figure 11
<p>The schematic diagram of the power system with three major cable sections.</p>
Full article ">Figure 12
<p>The electric and magnetic field directions for a typical HV cable.</p>
Full article ">Figure 13
<p>Normalized energy of the sheath current signal as a function of <italic>x<sub>f</sub></italic>. The real fault location is <italic>x<sub>f</sub></italic> = 300 m, the largest energy concentration is <italic>x<sub>f</sub></italic> = 278 m.</p>
Full article ">Figure 14
<p>Normalized energy of the sheath current signal as a function of <italic>x<sub>f</sub></italic>. The real fault location is <italic>x<sub>f</sub></italic> = 500 m, the largest energy concentration is <italic>x<sub>f</sub></italic> = 497 m.</p>
Full article ">Figure 15
<p>The electromagnetic transients transfer function <italic>f</italic>(<italic>xf</italic>,ω) under the sampling rate of 1 MHz.</p>
Full article ">Figure 16
<p>The electromagnetic transients transfer function <italic>f</italic>(<italic>xf</italic>,ω) under the sampling rate of 10 MHz.</p>
Full article ">Figure 17
<p>The electromagnetic transients transfer function <italic>f</italic>(<italic>x<sub>f</sub></italic>,ω) under the sampling rate of 100 MHz.</p>
Full article ">Figure 18
<p>The cable passage of the case study.</p>
Full article ">Figure 19
<p>The on-site installation pictures of the case study (the first two pictures were taken in an indoor substation, the last picture was taken outdoors).</p>
Full article ">Figure 20
<p>The sheath currents at each of the sensor locations.</p>
Full article ">Figure 21
<p>The equivalent circuit of fault current.</p>
Full article ">
Open AccessArticle Food Choice Priorities Change Over Time and Predict Dietary Intake at the End of the First Year of College Among Students in the U.S.
Nutrients 2018, 10(9), 1296; https://doi.org/10.3390/nu10091296
Received: 9 August 2018 / Revised: 4 September 2018 / Accepted: 7 September 2018 / Published: 13 September 2018
Viewed by 1246 | PDF Full-text (614 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This study assessed food choice priorities (FCP) and associations with consumption of fruits and vegetables (FV), fiber, added sugars from non-beverage sources, and sugar-sweetened beverages (SSB) among college students. Freshmen from eight U.S. universities (N = 1149) completed the Food Choice Priorities [...] Read more.
This study assessed food choice priorities (FCP) and associations with consumption of fruits and vegetables (FV), fiber, added sugars from non-beverage sources, and sugar-sweetened beverages (SSB) among college students. Freshmen from eight U.S. universities (N = 1149) completed the Food Choice Priorities Survey, designed for college students to provide a way to determine the factors of greatest importance regarding food choices, and the NCI Dietary Screener Questionnaire. Changes in FCP and dietary intake from fall 2015 to spring 2016 were assessed. Multiple regression models examined associations between FCP and log-transformed dietary intake, controlling for sex, age, race, and BMI. Participant characteristics and FCP associations were also assessed. FCP importance changed across the freshmen year and significantly predicted dietary intake. The most important FCP were price, busy daily life and preferences, and healthy aesthetic. Students who endorsed healthy aesthetic factors (health, effect on physical appearance, freshness/quality/in season) as important for food choice, consumed more FV and fiber and less added sugar and SSB. Busy daily life and preferences (taste, convenience, routine, ability to feel full) predicted lower FV, higher added sugar, and higher SSB consumption. Price predicted lower FV, higher SSB, and more added sugar while the advertising environment was positively associated with SSB intake. FCP and demographic factors explained between 2%–17% of the variance in dietary intake across models. The strongest relationship was between healthy aesthetic factors and SSB (B = −0.37, p < 0.01). Self-rated importance of factors influencing food choice are related to dietary intake among students. Interventions that shift identified FCP may positively impact students’ diet quality especially considering that some FCP increase in importance across the first year of college. Full article
Figures

Figure 1

Figure 1
<p>Cross-sectional, significant relationships between dietary intake and food choice priorities at the end of the freshmen year controlling for BMI, race, age, and sex (model 2). Numbers represent percentage change. Blue arrows indicate dietary intake in the direction one would prefer to promote healthy diets. Red arrows indicate dietary intake in a less desirable direction. Food Choice Priorities Survey (FCPS) scales and items are listed in order from most to least important based on mean ratings on a Likert scale. FV = Fruit and Vegetables minus French fries, SSB = Sugar sweetened beverages.</p>
Full article ">
Open AccessArticle Neck Circumference Positively Relates to Cardiovascular Risk Factors in College Students
Int. J. Environ. Res. Public Health 2018, 15(7), 1480; https://doi.org/10.3390/ijerph15071480
Received: 18 June 2018 / Revised: 9 July 2018 / Accepted: 11 July 2018 / Published: 13 July 2018
Cited by 1 | Viewed by 808 | PDF Full-text (522 KB) | HTML Full-text | XML Full-text
Abstract
The objective of this study was to determine the relationship between neck circumference (NC) and other anthropometric measures and examine cut-off points for males and females according to existing waist circumference cut-off levels in this age group. Across 8 universities, 1562 students underwent [...] Read more.
The objective of this study was to determine the relationship between neck circumference (NC) and other anthropometric measures and examine cut-off points for males and females according to existing waist circumference cut-off levels in this age group. Across 8 universities, 1562 students underwent a physical assessment. Spearman rho correlations (ρ) were calculated to determine associations between NC and other continuous variables of health. Receiving operating characteristic curves were constructed to assess the optimal cut-off levels of NC of males and females with central obesity. Participants were predominantly Caucasian (67%), female (70%), and outside of Appalachia (82%). Forty-one percent of males and 34% of females had a BMI ≥ 25 kg/m2. In both sexes, significant positive correlations were seen between NC and body weight, BMI, waist circumference, hip circumference, and systolic blood pressure (all p-values < 0.0001). NC ≥ 38 cm for males and ≥33.5 cm for females were the optimal cut-off values to determine subjects with central obesity. NC has been identified to closely correlate with other anthropometric measurements related to disease and could be used as a convenient, low-cost, and noninvasive measurement in large-scale studies. Full article
Figures

Figure 1

Figure 1
<p>Receiving operating characteristics (ROC) curves determined from the neck circumference and central obesity (waist circumference &gt;102 cm in males (<bold>left</bold>) and &gt;88 cm females (<bold>right</bold>)).</p>
Full article ">
Open AccessArticle The Deoxygenation Pathways of Palmitic Acid into Hydrocarbons on Silica-Supported Ni12P5 and Ni2P Catalysts
Catalysts 2018, 8(4), 153; https://doi.org/10.3390/catal8040153
Received: 3 March 2018 / Revised: 31 March 2018 / Accepted: 7 April 2018 / Published: 11 April 2018
Cited by 1 | Viewed by 1010 | PDF Full-text (22551 KB) | HTML Full-text | XML Full-text
Abstract
Pure Ni12P5/SiO2 and pure Ni2P/SiO2 catalysts were obtained by adjusting the Ni and P molar ratios, while Ni/SiO2 catalyst was prepared as a reference against which the deoxygenation pathways of palmitic acid were investigated. [...] Read more.
Pure Ni12P5/SiO2 and pure Ni2P/SiO2 catalysts were obtained by adjusting the Ni and P molar ratios, while Ni/SiO2 catalyst was prepared as a reference against which the deoxygenation pathways of palmitic acid were investigated. The catalysts were characterized by N2 adsorption, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), transmission election microscopy (TEM), infrared spectroscopy of pyridine adsorption (Py-IR), H2-adsorption and temperature-programmed desorption of hydrogen (H2-TPD). The crystallographic planes of Ni(111), Ni12P5(400), Ni2P(111) were found mainly exposed on the above three catalysts, respectively. It was found that the deoxygenation pathway of palmitic acid mainly proceeded via direct decarboxylation (DCO2) to form C15 on Ni/SiO2. In contrast, on the Ni12P5/SiO2 catalyst, there were two main competitive pathways producing C15 and C16, one of which mainly proceeded via the decarbonylation (DCO) to form C15 accompanying water formation, and the other pathway produced C16 via the dehydration of hexadecanol intermediate, and the yield of C15 was approximately twofold that of C16. Over the Ni2P/SiO2 catalyst, two main deoxygenation pathways formed C15, one of which was mainly the DCO pathway and the other was dehydration accompanying the hexadecanal intermediate and then direct decarbonylation without water formation. The turn over frequency (TOF) followed the order: Ni12P5/SiO2 > Ni/SiO2 > Ni2P/SiO2. Full article
Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>X-ray diffraction (XRD) patterns for the Ni/SiO<sub>2</sub>, Ni<sub>12</sub>P<sub>5</sub>/SiO<sub>2</sub> and Ni<sub>2</sub>P/SiO<sub>2</sub> catalysts. Intensity is given in arbitrary units (a.u.).</p>
Full article ">Figure 2
<p>X-ray photoelectron spectroscopy (XPS) spectra in the Ni (2p) regions (<bold>a</bold>) and P (2p) regions (<bold>b</bold>) for Ni/SiO<sub>2</sub>, Ni<sub>12</sub>P<sub>5</sub>/SiO<sub>2</sub> and Ni<sub>2</sub>P/SiO<sub>2</sub>.</p>
Full article ">Figure 3
<p>Nitrogen adsorbtion–desorption isotherm (<bold>a</bold>) and the Barrett–Joyner–Halenda (BJH) pore-size distribution curve (<bold>b</bold>) of all samples.</p>
Full article ">Figure 4
<p>Transmission electron microscopy (TEM) and high-resolution TEM (HRTEM) images of the Ni/SiO<sub>2</sub> (<bold>a</bold>,<bold>d</bold>), Ni<sub>12</sub>P<sub>5</sub>/SiO<sub>2</sub> (<bold>b</bold>,<bold>e</bold>) and Ni<sub>2</sub>P/SiO<sub>2</sub> (<bold>c</bold>,<bold>f</bold>) catalysts.</p>
Full article ">Figure 5
<p>Infrared spectroscopy of pyridine adsorption (Py-IR) profiles of Ni/SiO<sub>2</sub>, Ni<sub>12</sub>P<sub>5</sub>/SiO<sub>2</sub> and Ni<sub>2</sub>P/SiO<sub>2</sub> catalysts.</p>
Full article ">Figure 6
<p>Gas chromatographs (GC) of the products over different samples.</p>
Full article ">Figure 7
<p>The conversion of palmitic acid in terms of the yields and selectivity of several typical products on the Ni/SiO<sub>2</sub> (<bold>a</bold>,<bold>b</bold>); Ni<sub>12</sub>P<sub>5</sub>/SiO<sub>2</sub> (<bold>c</bold>,<bold>d</bold>); and Ni<sub>2</sub>P/SiO<sub>2</sub> (<bold>e</bold>,<bold>f</bold>) catalysts. Reaction conditions: batch reactor, 543 K, H<sub>2</sub> initial pressure: 1.2 MPa; stirring at 600 rpm, heptane (100 mL), catalyst (5 g L<sup>?1</sup>); palmitic acid (10 g L<sup>?1</sup>); NOL: hexadecanol, NAL: hexadecanal.</p>
Full article ">Figure 8
<p>The conversion of reactant ((<bold>a</bold>): hexadecanol, (<bold>b</bold>): hexadecanal, (<bold>c</bold>): the ratio hexadecanal/hexadecanol = 1) and the yields of the main products as a function of reaction time on the Ni/SiO<sub>2</sub> catalyst. Reaction conditions: batch reactor, 543 K, H<sub>2</sub> initial pressure: 1.2 MPa; stirring at 600 rpm, heptane (100 mL), catalyst (5 g·L<sup>?1</sup>); hexadecanal (10 g·L<sup>?1</sup>), hexadecanol (10 g·L<sup>?1</sup>), hexadecanal/hexadecanol = 1 (5 g·L<sup>?1</sup>); NOL: hexadecanol, NAL: hexadecanal.</p>
Full article ">Figure 9
<p>The ratio of C15/C16 hydrocarbons over the Ni/SiO<sub>2</sub> (<bold>a</bold>); Ni<sub>12</sub>P<sub>5</sub>/SiO<sub>2</sub> (<bold>b</bold>) and Ni<sub>2</sub>P/SiO<sub>2</sub> (<bold>c</bold>) catalysts.</p>
Full article ">Figure 10
<p>The conversion of reactant ((<bold>a</bold>): hexadecanol, (<bold>b</bold>): hexadecanal, (<bold>c</bold>): the ratio hexadecanal/hexadecanol = 1) and the yields of the main products as a function of reaction time on the Ni<sub>12</sub>P<sub>5</sub>/SiO<sub>2</sub> catalyst. Reaction conditions: batch reactor, 543 K, H<sub>2</sub> initial pressure: 1.2 MPa; stirring at 600 rpm, heptane (100 mL), catalyst (5 g·L<sup>?1</sup>); hexadecanal (10 g·L<sup>?1</sup>), hexadecanol (10 g·L<sup>?1</sup>), hexadecanal/hexadecanol = 1 (5 g·L<sup>?1</sup>); NOL: hexadecanol, NAL: hexadecanal.</p>
Full article ">Figure 11
<p>The conversion of reactant ((<bold>a</bold>): hexadecanol, (<bold>b</bold>): hexadecanal, (<bold>c</bold>): the ratio hexadecanal/hexadecanol = 1) and the yields of the main products as a function of reaction time on the Ni<sub>2</sub>P/SiO<sub>2</sub> catalyst. Reaction conditions: batch reactor, 543 K, H<sub>2</sub> initial pressure: 1.2 MPa; stirring at 600 rpm, heptane (100 mL), catalyst (5 g·L<sup>?1</sup>); hexadecanal (10 g·L<sup>?1</sup>), hexadecanol (10 g·L<sup>?1</sup>), hexadecanal/hexadecanol = 1 (5 g·L<sup>?1</sup>); NOL: hexadecanol, NAL: hexadecanal.</p>
Full article ">Scheme 1
<p>Possible deoxygenation reactions for fatty acid conversion.</p>
Full article ">Scheme 2
<p>(<bold>a</bold>) The suggested main reaction pathways of palmitic acid over the Ni/SiO<sub>2</sub> catalyst; (<bold>b</bold>) the suggested main reaction pathways of palmitic acid over the Ni<sub>12</sub>P<sub>5</sub>/SiO<sub>2</sub> catalyst; (<bold>c</bold>) the suggested main reaction pathways of palmitic acid over the Ni<sub>2</sub>P/SiO<sub>2</sub> catalyst.</p>
Full article ">
Open AccessArticle Relationship between Soil Characteristics and Stand Structure of Robinia pseudoacacia L. and Pinus tabulaeformis Carr. Mixed Plantations in the Caijiachuan Watershed: An Application of Structural Equation Modeling
Forests 2018, 9(3), 124; https://doi.org/10.3390/f9030124
Received: 20 December 2017 / Revised: 3 March 2018 / Accepted: 3 March 2018 / Published: 6 March 2018
Viewed by 840 | PDF Full-text (1252 KB) | HTML Full-text | XML Full-text
Abstract
In order to study the multi-factor coupling relationships between typical Robinia pseudoacacia L. and Pinus tabulaeformis Carr. mixed plantations in the Caijiachuan basin of the Loess Plateau of Shanxi Province, West China, 136 sample plots were selected for building a structural equation model [...] Read more.
In order to study the multi-factor coupling relationships between typical Robinia pseudoacacia L. and Pinus tabulaeformis Carr. mixed plantations in the Caijiachuan basin of the Loess Plateau of Shanxi Province, West China, 136 sample plots were selected for building a structural equation model (SEM) of three potential variables: terrain, stand structure, and soil characteristics. Additionally, the indicators (also known as observed variables) were studied in this paper, including slope, altitude, diameter at breast height (DBH), tree height (TH), tree crown area, canopy density, stand density, leaf area index (LAI), soil moisture content, soil maximum water holding capacity (WHC), soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), ammonia-nitrogen (NH3-N), nitrate-nitrogen (NO3-N), and available phosphorus (AP). The results showed that terrain was the most important factor influencing soil moisture and nutrients, with a total impact coefficient of 1.303 and a direct path coefficient of 0.03, which represented mainly positive impacts; while correspondingly stand structure had a smaller negative impact on soil characteristics, with a total impact coefficient of ?0.585 and a direct path coefficient of ?0.01. The terrain also had a positive impact on the stand structure, with a total impact coefficient of 0.487 and a direct path coefficient of 0.63, indicating that the topography factors were more suitable for site conditions and both the stand structure and the soil moisture and nutrient conditions were relatively superior. By affecting the stand structure, terrain could restrict some soil, water, and nutrient functions of soil and water conservation. The influence coefficients of the four observed variables of DBH, stand density, soil water content, and organic matter, and potential variable topography reached 0.686, ?0.119, 1.117, and 0.732, respectively; and the influence coefficients of soil moisture, organic matter and stand structure were ?0.502 and ?0.329, respectively. Therefore, besides observing the corresponding latent variables, the observed variables had a considerable indirect influence on other related latent variables. These relationships showed that the measures, such as changing micro-topography and adjusting stand density, should effectively maintain or enhance soil moisture and nutrient content so as to achieve improved soil and water conservation benefits in the ecologically important Loess Area. Full article
(This article belongs to the Special Issue Afforestation and Reforestation: Drivers, Dynamics, and Impacts)
Figures

Figure 1

Figure 1
<p>The initial structural equation model (SEM) used in the study. Note: The hypothesized initial model used for predicting topography, stand structure, and soil properties is based on soil and water conservation science. A rectangular box is used for each observed variable, with a measurement error, and the numbers correspond to the standardized path coefficients of the initial model on the single arrows in operation. A value outside of a rectangular box is the mean of the indicator, and a value outside of a round box is the residual error before modification. In the figure, DBH is the abbreviation for diameter at breast height; TH is the acronym for height of tree; LAI is the acronym for leaf area index; WHC is the abbreviation for soil maximum water holding capacity; SOM is the acronym for soil organic matter; TN is the is the acronym for total nitrogen; TP is the acronym for total phosphorus; NH<sub>3</sub>-N is the acronym for ammonia-nitrogen, NO<sub>3</sub>-N is the acronym for nitrate-nitrogen; and AP is the acronym for available phosphorus.</p>
Full article ">Figure 2
<p>The modified model. Note: The numbers correspond to the standardized path coefficients on the single arrows, and to correlation coefficients on the double arrows. A value outside of a rectangular box is the mean of the indicator, and a value outside of a round box is the residual error after modification. In the figure, DBH is the abbreviation for diameter at breast height; TH is the acronym for height of tree; LAI is the acronym for leaf area index; WHC is the abbreviation for soil maximum water holding capacity; SOM is the acronym for soil organic matter; TN is the is the acronym for total nitrogen; TP is the acronym for total phosphorus; NH<sub>3</sub>-N is the acronym for ammonia-nitrogen, NO<sub>3</sub>-N is the acronym for nitrate-nitrogen; and AP is the acronym for available phosphorus.</p>
Full article ">
Open AccessArticle A Novel Method for Separating and Locating Multiple Partial Discharge Sources in a Substation
Sensors 2017, 17(2), 247; https://doi.org/10.3390/s17020247
Received: 15 December 2016 / Accepted: 23 January 2017 / Published: 27 January 2017
Cited by 6 | Viewed by 1555 | PDF Full-text (4808 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
To separate and locate multi-partial discharge (PD) sources in a substation, the use of spectrum differences of ultra-high frequency signals radiated from various sources as characteristic parameters has been previously reported. However, the separation success rate was poor when signal-to-noise ratio was low, [...] Read more.
To separate and locate multi-partial discharge (PD) sources in a substation, the use of spectrum differences of ultra-high frequency signals radiated from various sources as characteristic parameters has been previously reported. However, the separation success rate was poor when signal-to-noise ratio was low, and the localization result was a coordinate on two-dimensional plane. In this paper, a novel method is proposed to improve the separation rate and the localization accuracy. A directional measuring platform is built using two directional antennas. The time delay (TD) of the signals captured by the antennas is calculated, and TD sequences are obtained by rotating the platform at different angles. The sequences are separated with the TD distribution feature, and the directions of the multi-PD sources are calculated. The PD sources are located by directions using the error probability method. To verify the method, a simulated model with three PD sources was established by XFdtd. Simulation results show that the separation rate is increased from 71% to 95% compared with the previous method, and an accurate three-dimensional localization result was obtained. A field test with two PD sources was carried out, and the sources were separated and located accurately by the proposed method. Full article
(This article belongs to the Section Physical Sensors)
Figures

Figure 1

Figure 1
<p>The direction measurement method for one partial discharge (PD) source based on two directional antennas.</p>
Full article ">Figure 2
<p>The separation method of the time delay (TD) sequences.</p>
Full article ">Figure 3
<p>The localization principle for one PD source with multi-PD source.</p>
Full article ">Figure 4
<p>The simulation model arrangement and the Vivaldi antenna; (<bold>a</bold>) The space distribution of the simulated PD sources and the measurement points; (<bold>b</bold>) The Vivaldi antenna; (<bold>c</bold>) The radiation pattern of the Vivaldi antenna.</p>
Full article ">Figure 5
<p>The original and noisy ultra-high frequency (UHF) signals radiated by P<sub>2</sub> at O<sub>2</sub> and the calculated TDs. (<bold>a</bold>) The received UHF signals radiated by P<sub>2</sub> at O<sub>2</sub>; (<bold>b</bold>) The noisy UHF signals when the signal-to-noise ratio (SNR) = 5 dB; (<bold>c</bold>) The calculated TDs.</p>
Full article ">Figure 5 Cont.
<p>The original and noisy ultra-high frequency (UHF) signals radiated by P<sub>2</sub> at O<sub>2</sub> and the calculated TDs. (<bold>a</bold>) The received UHF signals radiated by P<sub>2</sub> at O<sub>2</sub>; (<bold>b</bold>) The noisy UHF signals when the signal-to-noise ratio (SNR) = 5 dB; (<bold>c</bold>) The calculated TDs.</p>
Full article ">Figure 6
<p>The TDs and decision diagram at O<sub>2</sub> when SNR = 5 dB. (<bold>a</bold>) The TDs at the measurement point O<sub>2</sub>; (<bold>b</bold>) The decision diagram when <italic>α<sub>j</sub> </italic>= 0°; (<bold>c</bold>) The separated TD center sequences at O<sub>2</sub>.</p>
Full article ">Figure 6 Cont.
<p>The TDs and decision diagram at O<sub>2</sub> when SNR = 5 dB. (<bold>a</bold>) The TDs at the measurement point O<sub>2</sub>; (<bold>b</bold>) The decision diagram when <italic>α<sub>j</sub> </italic>= 0°; (<bold>c</bold>) The separated TD center sequences at O<sub>2</sub>.</p>
Full article ">Figure 7
<p>The field test site arrangement and the on-line monitoring result of the disc insulator PD. (<bold>a</bold>) The field test site and the test arrangement; (<bold>b</bold>) The on-line monitoring result; (<bold>c</bold>) The coordinate system of the field test site arrangement.</p>
Full article ">Figure 8
<p>The TDs and decision diagram at O<sub>2</sub>. (<bold>a</bold>) The TDs at the measurement point O<sub>2</sub>; (<bold>b</bold>) The decision diagram when <italic>α<sub>j</sub> </italic>= ?30°; (<bold>c</bold>) The separated TD sequences at O<sub>2</sub>.</p>
Full article ">Figure 9
<p>The UHF signals received at O<sub>2</sub>; (<bold>a</bold>) The waveform of the UHF signal radiated from the first PD source; (<bold>b</bold>) The waveform of the UHF signal radiated from the second PD source; (<bold>c</bold>) The spectrum of the UHF signal radiated from the first PD source; (<bold>d</bold>) The spectrum of the UHF signal radiated from the second PD source.</p>
Full article ">Figure 10
<p>The TD distributions at each measurement point.</p>
Full article ">
Open AccessArticle An Ultrahigh Frequency Partial Discharge Signal De-Noising Method Based on a Generalized S-Transform and Module Time-Frequency Matrix
Sensors 2016, 16(6), 941; https://doi.org/10.3390/s16060941
Received: 18 May 2016 / Revised: 17 June 2016 / Accepted: 20 June 2016 / Published: 22 June 2016
Cited by 8 | Viewed by 2085 | PDF Full-text (4830 KB) | HTML Full-text | XML Full-text
Abstract
Due to electromagnetic interference in power substations, the partial discharge (PD) signals detected by ultrahigh frequency (UHF) antenna sensors often contain various background noises, which may hamper high voltage apparatus fault diagnosis and localization. This paper proposes a novel de-noising method based on [...] Read more.
Due to electromagnetic interference in power substations, the partial discharge (PD) signals detected by ultrahigh frequency (UHF) antenna sensors often contain various background noises, which may hamper high voltage apparatus fault diagnosis and localization. This paper proposes a novel de-noising method based on the generalized S-transform and module time-frequency matrix to suppress noise in UHF PD signals. The sub-matrix maximum module value method is employed to calculate the frequencies and amplitudes of periodic narrowband noise, and suppress noise through the reverse phase cancellation technique. In addition, a singular value decomposition de-noising method is employed to suppress Gaussian white noise in UHF PD signals. Effective singular values are selected by employing the fuzzy c-means clustering method to recover the PD signals. De-noising results of simulated and field detected UHF PD signals prove the feasibility of the proposed method. Compared with four conventional de-noising methods, the results show that the proposed method can suppress background noise in the UHF PD signal effectively, with higher signal-to-noise ratio and less waveform distortion. Full article
(This article belongs to the Special Issue Non-Contact Sensing)
Figures

Figure 1

Figure 1
<p>Simulated UHF PD signals: (<bold>a</bold>) Simulated PD signals; (<bold>b</bold>) Simulated noisy PD signals.</p>
Full article ">Figure 2
<p>The time-frequency distribution of the noisy PD signals calculated by (<bold>a</bold>) the S-transform; and (<bold>b</bold>) the generalized S-transform.</p>
Full article ">Figure 3
<p>Relative errors by using different value of λ: (<bold>a</bold>) frequency; (<bold>b</bold>) amplitude.</p>
Full article ">Figure 4
<p>UHF PD signals with suppressed periodic narrowband noise: (<bold>a</bold>) in time domain; (<bold>b</bold>) in time-frequency domain.</p>
Full article ">Figure 5
<p>Procedure of the conventional SVD de-noising method.</p>
Full article ">Figure 6
<p>Calculated singular values by decomposing the MTFM.</p>
Full article ">Figure 7
<p>Selection results of effective singular values based on the FCM clustering algorithm.</p>
Full article ">Figure 8
<p>De-noised PD signals: (<bold>a</bold>) time-domain signals; (<bold>b</bold>) time-frequency distribution.</p>
Full article ">Figure 9
<p>De-noised PD signals employing SVD when (<bold>a</bold>) <italic>k</italic> = 3; and (<bold>b</bold>) <italic>k</italic> = 5.</p>
Full article ">Figure 10
<p>Procedure of the proposed de-noising method.</p>
Full article ">Figure 11
<p>De-noising results by employing each method: (<bold>a</bold>) Method B; (<bold>b</bold>) Method C; (<bold>c</bold>) Method D; and (<bold>d</bold>) Method E.</p>
Full article ">Figure 12
<p>Comparisons of the original and the de-noised PD pulse shapes. (<bold>a</bold>) Pulse 1; (<bold>b</bold>) Pulse 2; (<bold>c</bold>) Pulse 3; (<bold>d</bold>) Pulse 4.</p>
Full article ">Figure 13
<p>Field detection setup in substation.</p>
Full article ">Figure 14
<p>PRPD patterns corresponding to the detected UHF signals: (<bold>a</bold>) signal #1; (<bold>b</bold>) signal #2.</p>
Full article ">Figure 15
<p>Waveforms and time-frequency distributions detected UHF PD signals: (<bold>a</bold>) signal #1; (<bold>b</bold>) signal #2.</p>
Full article ">Figure 16
<p>De-noised PD signals in field detection using each method: (<bold>a</bold>) signal #1; (<bold>b</bold>) signal #2.</p>
Full article ">
Open AccessArticle Serum Metabolomic Characterization of Liver Fibrosis in Rats and Anti-Fibrotic Effects of Yin-Chen-Hao-Tang
Molecules 2016, 21(1), 126; https://doi.org/10.3390/molecules21010126
Received: 25 November 2015 / Revised: 31 December 2015 / Accepted: 14 January 2016 / Published: 21 January 2016
Cited by 8 | Viewed by 2493 | PDF Full-text (1610 KB) | HTML Full-text | XML Full-text
Abstract
Yin-Chen-Hao-Tang (YCHT) is a famous Chinese medicine formula which has long been used in clinical practice for treating various liver diseases, such as liver fibrosis. However, to date, the mechanism for its anti-fibrotic effects remains unclear. In this paper, an ultra-performance liquid chromatography-time-of-flight [...] Read more.
Yin-Chen-Hao-Tang (YCHT) is a famous Chinese medicine formula which has long been used in clinical practice for treating various liver diseases, such as liver fibrosis. However, to date, the mechanism for its anti-fibrotic effects remains unclear. In this paper, an ultra-performance liquid chromatography-time-of-flight mass spectrometry (UPLC-TOF-MS)-based metabolomic study was performed to characterize dimethylnitrosamine (DMN)-induced liver fibrosis in rats and evaluate the therapeutic effects of YCHT. Partial least squares-discriminant analysis (PLS-DA) showed that the model group was well separated from the control group, whereas the YCHT-treated group exhibited a tendency to restore to the controls. Seven significantly changed fibrosis-related metabolites, including unsaturated fatty acids and lysophosphatidylcholines (Lyso-PCs), were identified. Moreover, statistical analysis demonstrated that YCHT treatment could reverse the levels of most metabolites close to the normal levels. These results, along with histological and biochemical examinations, indicate that YCHT has anti-fibrotic effects, which may be due to the suppression of oxidative stress and resulting lipid peroxidation involved in hepatic fibrogenesis. This study offers new opportunities to improve our understanding of liver fibrosis and the anti-fibrotic mechanisms of YCHT. Full article
(This article belongs to the Section Metabolites)
Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Representative histological photomicrographs of rat liver sections in the control (<bold>A</bold>); model (<bold>B</bold>) and YCHT group (<bold>C</bold>). Paraffin-embedded sections were stained with Sirius red (original magnification × 200).</p>
Full article ">Figure 2
<p>Representative UPLC-TOF-MS total ion chromatograms (TICs) of serum samples from control (<bold>A</bold>); model (<bold>B</bold>); and YCHT treated rats (<bold>C</bold>). Peak numbers of the identified metabolites are consistent with those in <xref ref-type="table" rid="molecules-21-00126-t002">Table 2</xref> and <xref ref-type="table" rid="molecules-21-00126-t003">Table 3</xref>.</p>
Full article ">Figure 3
<p>PLS-DA scores plot (<bold>A</bold>) and loadings plot (<bold>B</bold>) of rat serum data control group (blue dot, <italic>n</italic> = 15), model group (<bold>red triangle</bold>, <italic>n</italic> = 15), YCHT group (<bold>dark diamond</bold>, <italic>n</italic> = 15) and QC samples (<bold>green star</bold>, <italic>n</italic> = 10). The numbers of changed metabolites in loadings plot are consistent with those in <xref ref-type="table" rid="molecules-21-00126-t003">Table 3</xref>.</p>
Full article ">Figure 4
<p>High-resolution TOF-MS mass spectra of the representative markers: (<bold>A</bold>) Lyso-PC C18:1 (No. 4) and (<bold>B</bold>) arachidonic acid (No. 7). The numbers of metabolites are consistent with those in <xref ref-type="table" rid="molecules-21-00126-t003">Table 3</xref>.</p>
Full article ">Figure 5
<p>Altered levels of candidate markers in the control, model and YCHT treated rats. Data are represented as mean ± SEM (<italic>n</italic> = 15 in each group), with <bold>*</bold> <italic>p</italic> &lt; 0.05 and <bold>**</bold> <italic>p</italic> &lt; 0.01 from one-way ANOVA analysis. Lyso-PC C16:0 and Lyso-PC C18:0 could not be considered as fibrosis-related markers since their levels in the control and model groups showed no statistical differences.</p>
Full article ">Figure 6
<p>Proposed mechanistic pathways for the DMN-induced liver fibrosis and anti-fibrotic effects of YCHT. Upward arrowhead indicates up-regulation and downward arrowhead indicates down-regulation. HSC, hepatic stellate cell; ROS, reactive oxygen species; YCHT, Yin-Chen-Hao-Tang.</p>
Full article ">
Open AccessArticle Astataricusones A–D and Astataricusol A, Five New Anti-HBV Shionane-Type Triterpenes from Aster tataricus L. f.
Molecules 2013, 18(12), 14585-14596; https://doi.org/10.3390/molecules181214585
Received: 9 October 2013 / Revised: 13 November 2013 / Accepted: 15 November 2013 / Published: 25 November 2013
Cited by 8 | Viewed by 2454 | PDF Full-text (388 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Five new shionane-type triterpenes, astataricusones A–D (compounds 14) and astataricusol A (5), together with one known shionane-type triterpene 6 were obtained from the roots and rhizomes of Aster tataricus L. f. Their structures were elucidated on the basis [...] Read more.
Five new shionane-type triterpenes, astataricusones A–D (compounds 14) and astataricusol A (5), together with one known shionane-type triterpene 6 were obtained from the roots and rhizomes of Aster tataricus L. f. Their structures were elucidated on the basis of spectroscopic data, mainly NMR and MS data. The absolute configurations of 1 and 4 was determined by single crystal X-ray diffraction and CD analysis. Compound 2 showed inhibitory activity on HBsAg secretion with an IC50 value of 23.5 μM, while 2 and 6 showed inhibitory activities on HBeAg secretion with IC50 values of 18.6 and 40.5 μM, and cytotoxicity on HepG 2.2.15 cells with CC50 values of 172.4 and 137.7 μM, respectively. Compounds 2 and 6 also exhibited inhibitory activities on HBV DNA replication with IC50 values of 2.7 and 30.7 μM, respectively. Full article
(This article belongs to the Section Natural Products Chemistry)
Figures

Figure 1

Figure 1
<p>Structures of compounds <bold>1</bold>–<bold>6</bold>.</p>
Full article ">Figure 2
<p>Key <sup>1</sup>H?<sup>1</sup>H COSY (<inline-graphic xmlns:xlink="//www.w3.org/1999/xlink" xlink:href="molecules-18-14585-i001.tif"/>) and HMBC (H<inline-graphic xmlns:xlink="//www.w3.org/1999/xlink" xlink:href="molecules-18-14585-i002.tif"/>C) correlations of <bold>1</bold>–<bold>5</bold>.</p>
Full article ">Figure 3
<p>X-ray crystallographic structure of <bold>1</bold>.</p>
Full article ">Figure 4
<p>ICD spectrum of the <italic>in situ</italic>-formed Mo-complex of <bold>4</bold> and Mo<sub>2</sub>(OAc)<sub>4</sub> in a ratio of 1:1.2.</p>
Full article ">

Years

Subjects

Refine Subjects

Journals

All Journals Refine Journals

Article Types

Refine Types

Countries / Territories

Refine Countries / Territories
秒速赛车是哪里的开奖
Back to Top
  • 河北馆陶:端午节火了“艾旅游” 2019-04-18
  • 安倍访美又遭“握手杀” 手都被捏皱了 2019-04-18
  • 五月份经济运行稳中向好——新动能茁壮成长 企业效益持续改善 2019-04-18
  • 【周展安】重新认识《在延安文艺座谈会上的讲话》的现实意义 2019-04-17
  • 新时代我国社会的主要矛盾及其现实意义 2019-04-17
  • 国产新型雷达芯片华睿2号与组网中心同时亮相 2019-04-16
  • 山西省重要党务政务信息新闻发布会——黄河新闻网 2019-04-16
  • 中华人民共和国安全生产法 2019-04-16
  • 数百人吃发芽糙米 三个月收获健康 2019-04-15
  • 历次五年规划(计划)资料库 2019-04-15
  • 阶级是过去私有制社会的产物,在现代公有制和私有制并存的社会主义社会,阶级已不复存,存在的是阶层。 2019-04-14
  • 浮世边缘的净土——山神家园文章中国国家地理网 2019-04-14
  • [福]什么是“幸福”?这两个字所表示的直接含义就是:“幸”是指机会,“福”就是指拜求神赐田地生长粮棉等生物而足食丰衣。 2019-04-14
  • 你所说的时候正是四两酒半仙处于姑娘的时候。四两酒半仙说,她俩当年一人一餐饭就要吃一斤半米,你说这亩产够四两酒半仙一年吃吗??[微笑] 2019-04-13
  • 新西塘孔雀城 回家 ——凤凰网房产北京 2019-04-13
  • 370| 905| 440| 144| 893| 542| 841| 186| 672| 711|