Two concept models showing the style of entrainment, transportation, and deposition of aeolian dust in the Junggar basin (A) and the Ili basin (B).

<p>TLD: Talede drilling; SW: Shawa drilling.</p

The distribution of loess and the locations of the investigated loess sections in Xinjiang.

<p>The pictures of loess drillings and sections (4A-4F, 5A-5G, and 6A-6G) are shown in Figs <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125492#pone.0125492.g004" target="_blank">4</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125492#pone.0125492.g005" target="_blank">5</a>, and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125492#pone.0125492.g006" target="_blank">6</a>, and the strata of the numbered sections (1–9) are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125492#pone.0125492.g007" target="_blank">Fig 7</a>. ML: Mulei, QT: Qitai, JMSE: Jimsar, FK: Fukang, HTB: Hutubi, SW: Shawa, KT: Kuitun, NLK: Nilke, XY: Xinyuan, ZS: Zhaosu, GL: Gongliu, YN: Yining, QSH: Qingshuihe, HEGS: Huoerguosi.</p

Map showing the contours of the >63 μm particle component of topsoil in Xinjiang: (A) the Junggar Basin; (B) the Tarim Basin; and (C) the Ili Basin.

<p>Cross symbols represent our sampling sites, dots represent the city/county, and arrows represent the possible wind direction.</p

Photographs of loess sections and drillings from the northern slope of the Tianshan Mountains.

<p>FK: Fukang loess section in Fukang City; QT: Qitai loess section in Qitai County; JMSR: Jimsar loess drilling in Jimsar County; TXH: Taxihe loess on the north slope of the Tianshan Mountains; MNS: Manas loess on the terrace of the Manas River; SW: Shawan loess drilling in Shawan County; TC: Tacheng loess section in Tacheng City in the west of the Junggar Basin.</p

The atmospheric pressure field at sea level (the blue shaded region, hPa) and the UV 10 m wind circulation (m/s) in Xinjiang: (a) January and (b) July.

<p>Red circle denotes the Urumqi, and the black outline shows the outline of the Xinjiang province.</p

Stratigraphic correlations of outcropping loess sections and loess drillings in Xinjiang.

<p>Data sources: Tajik from Ref.73; LC from Ref.72; KL drilling from Ref. 28; DBBX from Ref.15; DW from Ref.16; HKZ and LJW from Ref.76; TLD drilling from Ref.34; ZKT from Ref.31; TLD from Ref.34; ZS from Ref.23.</p

Photographs of loess at the northern slope of the Kunlun Mountains.

<p>Photographs of loess at the northern slope of the Kunlun Mountains.</p

The UV stream field at 500 hPa (approximately 5500 m a.s.l.) in Xinjiang: (a) January and (b) July.

<p>Red circle denotes the Urumqi, and the black outline shows the outline of the Xinjiang province. Red circle denotes the Urumqi, and the black outline shows the outline of the Xinjiang province.</p

Associations between nighttime eating and total caloric intake in college-aged students

Background: Obesity is a nationwide concern across all age groups including the college-aged population. Approximately 35% of college students are reported to be overweight or obese in America, as defined by a body mass index (BMI) over 25 kg/m2. Increased caloric intake has shown to be associated with an elevated BMI. Nighttime eating may be a contributing factor to increased total caloric intake, and it has been associated with higher total caloric intake and weight gain in shift workers and older adults. However, research has not examined whether an association exists between nighttime eating and total daily caloric intake in college-aged students. Nighttime eating has been identified by college students as a potential concern for weight gain, thus making this an important and novel investigation. Objective: The primary objective was to examine possible relationships between nighttime eating and total caloric intake amongst college-aged undergraduate students at the University of Rhode Island (URI) during three consecutive semesters. The secondary objectives were to investigate associations between nighttime eating and dietary quality and sleep patterns. The exploratory objectives were to consider associations between nighttime eating and metabolic syndrome (MetS) risk and body composition. The primary hypothesis was that nighttime eaters would have a higher caloric intake. Design and Methods: This cross-sectional data analysis was an add-on study to an ongoing secondary data analysis project that examines the relationship between diet and chronic disease risk in college-aged students, referred to as the Nutrition Assessment Secondary Data Analysis Project. Undergraduate students (n=173, 72.25% females; BMI=23.7kg/m2) completed the Nutrition Assessment Survey (NAS) to categorize nighttime eaters and assess quantitative sleep patterns. Statistically controlled for confounding variables included, gender and smoking status. The International Physical Activity Questionnaire (IPAQ) assessed activity levels. The Diet History Questionnaire (DHQ II), a web-based food frequency questionnaire, estimated total caloric intake. The DHQ II was also used to calculate the total and component scores of the Healthy Eating Index-2010 (HEI-2010), an indicator of dietary quality. Anthropometric and biochemical measures were taken to determine the students’ number of risk factors for MetS and body weight status. Results: In this population, caloric intake within 2 hours of sleep or after 10:00PM provided more accurate definitions of nighttime eating than in other populations. Caloric intake after 10:00PM and within 2 hours (p=.015, r2=.034) of sleep onset was related to higher caloric consumption (+235.56 - 543.07kcals), lower HEI-2010 total scores (-4.78 – 5.91), and more MetS risk factors. Conclusion: This analysis aimed to determine if nighttime eating was associated with differential total daily caloric intake, along with dietary quality, sleep patterns, MetS risk, and BMI status. This study identified previously uninvestigated information regarding the prevalence of nighttime eating, along with differences in several health-related variables between students who engage in nighttime eating and those who do not. Nighttime eating was associated with increased caloric intake and a poorer diet quality in college students

8 data: Timing and spatial distribution of loess in Xinjiang, NW China

<p>The data of Figure 8.</p> <p>Figure 8 Map showing the contours of the >63 μm particle component of topsoil in Xinjiang: (A) the Junggar Basin; (B) the Tarim Basin; and (C) the Ili Basin. Cross symbols represent our sampling sites, dots represent the city/county, and arrows represent the possible wind direction.</p