Polymorphism of Transcription Factor 7-Like 2 in Obese Patients with Type 2 Diabetes Mellitus

Objective: The article is to investigate the relationship between the polymorphism of transcription factor 7-like 2 (TCF7L2) gene rs7903146 and type 2 diabetes mellitus with obesity in Chinese Han population. Methods: 216 patients with type 2 diabetes mellitus (T2DM), 92 males, 124 females, 194 normal controls, 89 males and 105 females. The polymorphism of TCF7L2 gene rs7903146 was measured by PCR-RFLP. PCR amplifier was used for amplification reaction, followed by polymorphism analysis of TCF7L2 gene: the reaction system was 20 μl, among which restriction endonuclease was 0.5 μl and PCR product was 7.5 μl. Restriction enzyme SspI (Fermentas) was used for PCR product and was bathed at 37°C for 16 h. The enzyme digestion products were detected and genotypes were identified by 2% agarose gel electrophoresis. The genotyping was repeated in 10% of the samples, and the genotyping rate was 100%. Height and weight were measured and BMI calculated. According to BMI, the experimental group was further divided into the obese group (n = 137, BMI > 25 kg/m2) and the normal body mass group (n = 79, BMI < 25 kgm2). Normal control group: BMI < 25 kgm2: FBG < 6.1 mmol/L and 2 h BG < 7.8 mmol/L after meal. Finally, SPSS18.0 software was used for analysis. Results: FBG, 2 h BG, FIN and Lg homa-ir showed significant differences between the control group and the T2DM groups (P < 0.01), while no statistical difference was found between the other parameters (P > 0.05). There was a significant difference in genotype frequency between the control group and the experimental group (χ2 = 17.382, P < 0.001), but no significant difference in allele frequency between the control group and the T2DM group (P > 0.05). Genotype frequency at BMI level was significantly different between the control group and the T2DM group (χ2 = 20.427, P = 0.001), but there was no significant difference in allele frequency distribution (P > 0.05). The TT type and TC + CC type were significantly different between the T2DM group and the control group (χ2 = 78.154, P = 0.006) and the T2DM obesity group and the control group (χ2 = 7.247, P = 0.009), but there was no significant difference between the T2DM normal body mass group and the control group (P > 0.05). In addition, there was no significant difference between TC type + TT type and CC type between the T2DM group and the control group and the T2DM obesity group and the control group (P > 0.05). Conclusion: There were significant differences in the genotype frequency and recessive inheritance pattern (TT/CC + TC) of rs7903146, suggesting that this SNP may be associated with the incidence of T2DM in obesity and insulin resistance.

Context-Aware Using Carrier Phase for Adaptive MEMS IMU / GNSS Filtering in Deep Urban Navigation

Context-aware is becoming standard on the most mobile navigation devices. The performance of MEMS IMU/GNSS gains significant benefits from context information in terms of improvement of filter＇ s adaptive capability. A context-aware algorithm using differential carrier phase was proposed to recognize a molile MEMS IMU/GNSS equipped vehicle＇ s stationary, slow moving or fast moving status. The corresponding context error in awarding was analyzed and consequently conducted two fading factors based on the analysis The factors were applied in the system＇ s adaptive filter with targeting applications in deep urban where severe multipath presents. The dense urban field test shows that the false alarm of proposed context-aware algorithm is less than 5% and the adaptive filtering can achieve around 15% improvement in terms of lo in two-dimension position accuracy.

Evaluating the Effects of Aquaculture Wastewater Irrigation with Fertilizer Reduction on Greenhouse Tomato Production,Economic Benefits and Soil Nitrogen Characteristics

The utilization of aquaculture wastewater as irrigation is an effective way to recycle and reuse water and nitrogen fertilizer resources because it contains numerous nutrients.However,it is still unclear that the pattern of substituting aquaculture wastewater irrigation for fertilizer supplementing is conducive to improving the soil nitrogen status,fruit yield and water-fertilizer use efficiency for tomato production.In this context,the experiment was intended to establish the appropriate irrigation regime of aquaculture wastewater in tomato production for freshwater replacement and fertilizer reduction to ensure good yields.Pot experiments were conducted with treatments as farmers accustomed to irrigation and fertilization used as control(CK),1.75 L aquaculture wastewater with base fertilizer(W1),2 L aquaculture wastewater with base fertilizer;and 2.25 L aquaculture wastewater with base fertilizer(W3).We examined the effects of aquaculture wastewater irrigation on soil nitrogen distribution,Nrelated hydrolases,tomato yield,and economic benefits.The results showed that the control treatment had the highest N input,about 24.68%higher than the W3 treatment,while the yield was only about 7.81%higher than W3.This indicated that the overuse of chemical fertilizer was present in the current tomato production.Although the reduction of fertilizer in aquaculture wastewater irrigation caused a decrease in tomato production,this economic loss can be compensated by cost savings in the wastewater disposal.Among aquaculture wastewater treatments,the W3 treatment had the highest overall benefit,achieving 62.63%freshwater savings,37.50%fertilizer input reduction,and an economic return of approximately 19,466 Yuan per hectare higher than the control.Additionally,increasing the irrigation volume of aquaculture wastewater could provide more available nutrients to the soil,which were more prevalent in the form of organic nitrogen.The lower soil nitrate reductase activities(NR)under aquaculture wastewater treatments after harvesting also proved that this pattern was beneficial to reduce soil nitrate nitrogen residues.Overall,the results demonstrate that aquaculture wastewater irrigation alleviates the soil nitrate residues,improves nutrient availability,and results in more economic returns with water and fertilizer conservation for the greenhouse production of tomatoes.

Self-Powered Intelligent Human-Machine Interaction for Handwriting Recognition

Handwritten signatures widely exist in our daily lives.The main challenge of signal recognition on handwriting is in the development of approaches to obtain information effectively.External mechanical signals can be easily detected by triboelectric nanogenerators which can provide immediate opportunities for building new types of active sensors capable of recording handwritten signals.In this work,we report an intelligent human-machine interaction interface based on a triboelectric nanogenerator.Using the horizontal-vertical symmetrical electrode array,the handwritten triboelectric signal can be recorded without external energy supply.Combined with supervised machine learning methods,it can successfully recognize handwritten English letters,Chinese characters,and Arabic numerals.The principal component analysis algorithm preprocesses the triboelectric signal data to reduce the complexity of the neural network in the machine learning process.Further,it can realize the anticounterfeiting recognition of writing habits by controlling the samples input to the neural network.The results show that the intelligent human-computer interaction interface has broad application prospects in signature security and humancomputer interaction.

Floor positioning method indoors with smartphone’s barometer

This paper presents an indoor floor positioning method with the smartphone’s barometer for the purpose of solving the problem of low availability and high environmental dependence of the traditional floor positioning technology.First,an initial floor position algorithm with the“entering”detection algorithm has been obtained.Second,the user’s going upstairs or downstairs activities are identified by the characteristics of the air pressure fluctuation.Third,the moving distance in the vertical direction and the floor change during going upstairs or downstairs are estimated to obtain the accurate floor position.In order to solve the problem of the floor misjudgment from different mobile phone’s barometers,this paper calculates the pressure data from the different cell phones,and effectively reduce the errors of the air pressure estimating the elevation which is caused by the heterogeneity of the mobile phones.The experiment results show that the average correct rate of the floor identification is more than 85%for three types of the cell phones while reducing environmental dependence and improving availability.Further,this paper compares and analyzes the three common floor location methods–the WLAN Floor Location(WFL)method based on the fingerprint,the Neural Network Floor Location(NFL)methods,and the Magnetic Floor Location(MFL)method with our method.The experiment results achieve 94.2%correct rate of the floor identification with Huawei mate10 Pro mobile phone.

Embedding laser generated GaAs nanocrystals in perovskite wires for enhanced charge transport and photodetection

Solution-processed perovskite wires are attractive candidates for photodetectors(PDs)due to their simple processibility as well as one-dimensional(1D)geometry with desirable charge carrier transport.However,the performance of the perovskite PDs is generally restricted by the charge carrier transport and extraction efficiency.Herein,we demonstrate that the charge transport and the consequent photodetection performance of MAPbI_(3)perovskite wires can be effectively enhanced by incorporating nanocrystals(NCs)of GaAs-a semiconductor with high charge carrier mobility.Taking advantage of the pulsed laser irradiation technique,we successfully fabricate ligand-free GaAs NCs with a size of~7 nm and homogeneously embed them in MAPbI_(3) perovskite wires through a simple solution-processed synthesis route.Compared with the pristine perovskite wires,the GaAs NCs modulated perovskite wires show improved charge carrier transport with the mobility rising from 1.13 to 3.67 cm^(2)V^(-1)s^(-1),and the resultant PD shows significant improvement in responsivity and detectivity.This study provides a new strategy for improving optoelectronic properties of halide perovskite materials and optimizing the device performance.

A FIR flter assisted with the predictive model and ELM integrated for UWB-based quadrotor aircraft localization

To improve the accuracy of the Ultra-Wide Band(UWB)based quadrotor aircraft localization,a Finite Impulse Response(FIR)flter aided with an integration of the predictive model and Extreme Learning Machine(ELM)is proposed in this work.The FIR flter estimates the quad-rotor aircraft’s position by fusing the positions measured with the UWB and Inertial Navigation System respectively.When the UWB dada are unavailable,both the ELM and the predictive model are used to provide the measurements,replacing those unavailable UWB data,for the FIR flter.The ELM estimates the measurement via the mapping between the one step prediction of state vector and the measurement built when the UWB data are available.For the predictive model,we mathematically describe the missing UWB data.Then,both the measurements estimated with the ELM and predictive model are employed to estimate the observations via Mahalanobis distance.The test results show that the FIR flter aided by the predictive model/ELM integrated can reduce the Cumulative Distribution Function and position Root Mean Square Error efectively when the UWB is unavailable.Compared with the ELM assisted FIR flter,the proposed FIR flter can reduce the localization error by about 48.59%,meanwhile,the integrated method is close to the method with a better solution.