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Background Haplotypes combine the effects of several single nucleotide polymorphisms (SNPs) with high linkage disequilibrium, which benefit the genome-wide association analysis (GWAS). In the haplotype association analysis, both haplotype alleles and blocks are tested. Haplotype alleles can be inferred with the same statistics as SNPs in the linear mixed model, while blocks require the formulation of unified statistics to fit different genetic units, such as SNPs, haplotypes, and copy number variations. Results Based on the FaST-LMM, the fastLmPure function in the R/RcppArmadillo package has been introduced to speed up genome-wide regression scans by a re-weighted least square estimation. When large or highly significant blocks are tested based on EMMAX, the genome-wide haplotype association analysis takes only one to two rounds of genome-wide regression scans. With a genomic dataset of 541,595 SNPs from 513 maize inbred lines, 90,770 haplotype blocks were constructed across the whole genome, and three types of markers (SNPs, haplotype alleles, and haplotype blocks) were genome-widely associated with 17 agronomic traits in maize using the software developed here. Conclusions Two SNPs were identified for LNAE, four haplotype alleles for TMAL, LNAE, CD, and DTH, and only three blocks reached the significant level for TMAL, CD, and KNPR. Compared to the R/lm function, the computational time was reduced by ~ 10–15 times.

Crude oil is the most important energy source in the world, and fluctuations in oil prices can significantly influence investors, companies, and governments. However, crude oil prices have numerous characteristics, including randomness, sudden structural changes, intrinsic nonlinearity, volatility, and chaotic nature. This makes the accurate forecasting of crude oil prices a difficult and challenging task. In this paper, a hybrid prediction model for crude oil futures prices is proposed, the accuracy and robustness of which are demonstrated via controlled experiments and sensitivity analysis. This study uses a new data denoising method for data processing to improve the accuracy and stability of the predictions of crude oil prices. Furthermore, the chaotic time-series prediction method, shallow neural networks, linear model prediction methods, and deep learning methods are adopted as submodels. The results of interval forecasts with narrow widths and high prediction accuracies are derived by introducing a confidence interval adjustment coefficient. The results of the simulation experiments indicate that the proposed hybrid prediction model exhibits higher accuracy and efficiency, as well as better robustness of the forecasting than the control models. In summary, the proposed forecasting framework can derive accurate point and interval forecasts and provide a valuable reference for the price forecasting of crude oil futures.

The high distribution of water resources among provinces in China considerably impacts the development of society and economy in each region. Thus, it is of great practical significance to examine the water resources carrying capacity (WRCC) of each Chinese province. This paper constructs a comprehensive evaluation index system for the WRCC from two aspects: pressure and support. First, it analyzes dynamic changes in the WRCC of 31 Chinese provinces in China by using the decoupling model (DM). Second, it analyzes the key factors that hinder the improvement of WRCC by using the obstacle degree model (ODM). The study found that there are significant inter-provincial differences in China’s WRCC. Provinces with greater natural water resources have a higher WRCC. Under the condition of similar natural water resources, WRCC in economically developed provinces is higher. From 2008 to 2015, China’s overall WRCC has been increasing. Moreover, three-fifth of China’s provinces can be classified as Upward-type (Upward I, Upward II, and Upward III) provinces and their WRCC is in a good state by considering the decoupling type and trend of WRCC in two periods together. The main obstacle factors hindering the improvement of the WRCC are total water resources ( X 1 ), water supply per capita ( X 2 ), total water supply ( X 3 ), forest cover rate ( X 9 ), soil erosion control area ( X 10 ), water consumption saving ( X 12 ), and water usage penetration rate ( X 22 ). This study can provide a scientific basis for understanding change trend of WRCC in Chinese provinces and improve their WRCC.

TSC-mTORC1 inhibition-mediated translational reprogramming is a major adaptation mechanism upon many stresses, such as low-oxygen, -ATP, and -amino acids. But how cancer cells hijack the adaptive pathway to survive under low-lactate stress when targeting glycolysis-related signaling remains uncertain. ETV4 is an oncogenic transcription factor frequently dysregulated in human cancer. We previously found that ETV4 is associated with tumor progression and poor prognosis in non-small cell lung cancer (NSCLC). In this study, we report that ETV4 controls HK1 expression and glycolysis-lactate production to activate mTORC1 by relieving TSC2 repression of Rheb in NSCLC cells. Targeting ETV4-induced low-lactate stress is an important input for TSC2 to inhibit mTORC1 and global protein synthesis, while the core stress granule components G3BP2 and HDAC6 are selectively translated. Mechanistically, G3BP2 recruits lysosomal-TSC2 to suppress mTORC1. HDAC6 deacetylates TSC2 to sustain protein stability and associates with G3BP2 to facilitate more recruiting of TSC2 to inactivate mTORC1. In addition, the microtubule retrograde transport activity of HDAC6 drives the aggregate-like perinuclear-mTOR distribution paralleled by lower mTORC1 activity under stress. Thus, HDAC6-G3BP2 is the key complex that promotes lysosomal-TSC2 and suppresses mTORC1 when targeting ETV4, which might represent a critical adaptive mechanism for cell survival under low-lactate challenges.

On the basis of measuring the pressure distribution and analyzing its origin in the Carboniferous and Permian of Shenmu-Yulin area, the evolution history of ancient pressure is restored mainly by means of the basin numerical simulation technique, in which the paleo-pressure has been constrained by the compaction restoration and the examination of fluid inclusion temperature and pressure. Then the development and evolution history of abnormal pressure and its effect on gas migration and accumulation are investigated. Studies show that the pressure in southeastern and northwestern parts of studied area is near to hydrostatic pressure, whereas in the remainder vast area the pressure is lower than the hydrostatic pressure, which is caused by difficulty to measure pressure accurately in tight reservoir bed, the calculating error caused by in-coordinate between topography relief and surface of water potential, pressure lessening due to formation arising and erosion. There are geological factors beneficial to forming abnormal high pressure in the Upper Palaeozoic. On the distraction of measured pressure, paleo-pressure data from compaction restoration and fluid inclusion temperature and pressure exa- mining, the evolution history of ancient pressure is restored by the basin numerical simulation technique. It is pointed out that there are at least two high peaks of overpressure in which the highest value of excess pressure could be 5 to 25 MPa. Major gas accumulated in main producing bed of Shanxi Fm (P1s) and lower Shihezi Fm (P2x), because of two-fold control from capillary barrier and overpressure seal in upper Shihezi Fm (P2s). In the middle and southern districts, the two periods of Later Jurassic to the middle of Early Cretaceous, and middle of Later Cretaceous to Palaeocene are main periods of gas migration and accumulation, while they belong to readjustment period of gas reservoirs after middle of Neocene.

China's 2009 national essential medicine system (NEMS) was designed to reduce prices through a zero-markup policy and a centralized bidding system. To analyze NEMS's short-term impact on drug prices, we estimated the retail and wholesale prices before and after the reform at health institutions in rural Jiangxi Province. We undertook two cross-sectional surveys of prices of 39 medicines in November 2008 and May 2010, calculated inflation adjusted prices, and used the Wilcoxon signed-rank and rank-sum tests to examine price changes at different health institutions. Retail prices at pilot (P < 0.01) and nonpilot (P < 0.01) township health centers decreased significantly, whereas the declines at retail pharmacies (P = 0.57) and village clinics (P = 0.29) were insignificant. The decline at pilot township health centers was the largest, compared with other kinds of health institutions (P < 0.01). Retail prices of essential and non-essential medicines declined significantly at pilot facilities (P < 0.05); price drops for non-essential medicines occurred only at pilot facilities (P < 0.05). No significant decline of wholesale prices were found at pilot (P = 0.86) and nonpilot units (P = 0.18), retail pharmacies (P = 0.18), and village clinics (P = 0.20). The wholesale prices changes at pilot units before and after the reform were higher than at nonpilot public units (P < 0.05), retail pharmacies (P < 0.05), and village clinics (P < 0.05). While the NEMS zero-markup policy significantly reduced retail prices at pilot health institutions, the centralized bidding system was insufficient to lower wholesale prices. A drug price management system should be constructed to control medicine prices and a long-term price information system is needed to monitor price changes.

Aiming at a series of problems existing in current smart grid monitoring Control Terminal, such as high costs, poor portability, simple monitoring system, poor software extensions, low system reliability when transmitting information, single man-machine interface, poor security, etc., smart grid remote monitoring system based on the iOS system has been designed. The system interacts with smart grid server so that it can acquire grid data through WiFi/3G/4G networks, and monitor each grid line running status, as well as power plant equipment operating conditions. When it occurs an exception in the power plant, incident information can be sent to the user iOS terminal equipment timely, which will provide troubleshooting information to help the grid staff to make the right decisions in a timely manner, to avoid further accidents. Field tests have shown the system realizes the integrated grid monitoring functions, low maintenance cost, friendly interface, high security and reliability, and it possesses certain applicable value.

In this paper, through the analysis of shortcomings of the current domestic and foreign household power consumption strategy: Passive way of power consumption, ignoring the different priority of electric equipment, neglecting the actual load pressure of the grid, ignoring the interaction with the user, to decrease the peak-valley difference and improve load curve in residential area by demand response (DR technology), an intelligent power consumption scheme based on time-of-use(TOU) pricing for household appliances is proposed. The main contribution of this paper is: (1) Three types of household appliance loads are abstracted from different operating laws of various household appliances, and the control models and DR strategies corresponding to these types are established. (2) The fuzzified processing for the information of TOU price, which is based on the time intervals, is performed to get the price priority, in accordance with such DR events as the maximum restricted load of DR, the time of DR and the duration of interruptible load and so on, the DR control rule and pre-scheduling mechanism are led in. (3) The dispatching sequence of household appliances in the control and scheduling queue are switched and controlled to implement the equilibrium of peak and valley loads. The equilibrium effects and economic benefits of power system by pre-scheduling and DR dispatching are compared and analyzed by simulation example, and the results show that using the proposed household appliance control (HAC) scheme the overall cost of consumers can be reduced and the power system load can be alleviated, so the proposed household appliance control (HAC) scheme is feasible and reasonable.

Comfort is an important aspect in shoe design and shoe manufacture. However, certain criteria have to be determined for shoe comfort. Comfort cannot be measured directly, but some measurable variables may be used to interpret comfort. In this thesis, plantar pressure distribution was used to study comfort. In comparison with less comfortable shoe, the comfortable shoe produced lower pressure and provided an even distribution of the pressure at the plantar surface of the foot. The nervous system plays an important role in comfort. To test the sensory aspect of comfort, plantar pressure distribution was compared between presummed increased sensory input and normal conditions. The increased sensory input caused discomfort and produced high pressure at the plantar surface of the foot. In general, pressure measurement can indicate the changes of comfort and sensory conditions and may be used in definition of comfort.

The summer day-by-day precipitation data of 97 meteorological stations on the Qinghai-Tibet Plateau from 1961 to 2004 were selected to analyze the temporal-spatial distribution through accumulated variance,correlation analysis,regression analysis,empirical orthogonal function,power spectrum function and spatial analysis tools of GIS.The result showed that summer precipitation occupied a relatively high proportion in the area with less annual precipitation on the Plateau and the correlation between summer precipitation and annual precipitation was strong.The altitude of these stations and summer precipitation tendency presented stronger positive correlation below 2000 m,with correlation value up to 0.604（α=0.01）.The subtracting tendency values between 1961-1983 and 1984-2004 at five altitude ranges（2000-2500 m,2500-3000 m,3500-4000 m,4000-4500 m and above 4500 m）were above zero and accounted for 71.4%of the total.Using empirical orthogonal function, summer precipitation could be roughly divided into three precipitation pattern fields：the Southeast Plateau Pattern Field,the Northeast Plateau Pattern field and the Three Rivers＇ Headstream Regions Pattern Field.The former two ones had a reverse value from the north to the south and opposite line was along 35°N.The potential cycles of the three pattern fields were 5.33a,21.33a and 2.17a respectively,tested by the confidence probability of 90%.The station altitudes and summer precipitation potential cycles presented strong negative correlation in the stations above 4500 m,with correlation value of-0.626（α=0.01）.In Three Rivers Headstream Regions summer precipitation cycle decreased as the altitude rose in the stations above 3500 m and increased as the altitude rose in those below 3500 m.The empirical orthogonal function analysis in June precipitation,July precipitation and August precipitation showed that the June precipitation pattern field was similar to the July＇s,in which southern Plateau was positive and northern Plateau negative.But positive value area in July precipitation pattern field was obviously less than June＇s.The August pattern field was totally opposite to June＇s and July＇s.The positive area in August pattern field jumped from the southern Plateau to the northern Plateau.