Objective To understand the implementation status and effect of prevention and control of malaria in Libo Coun?ty so as to provide the evidence for improving the malaria elimination working. Methods The data about malaria from the county CDC and county hospital were collected and 16 villages from 8 townships were randomly sampled and 10 villagers of each village were investigated. Other information about the prevention and control of malaria was also investigated. Results The inci?dence of malaria was decreasing annually from 5.75 per 10 000 in 2008 to zero in 2012. The malaria monitoring could be well conducted in the county and township levels. The infection source could be controlled in time. The utilization rate of anti?mosqui?to facilities in the residents was 93.25%and the awareness rate of knowledge about malaria prevention and control was 40.13%. Conclusions The implementation and effect of prevention and control of malaria are satisfactory in Libo County but the medi?um control is limited and the active protection consciousness of the residents is not strong. Therefore the task of malaria elimina?tion is still very arduous.

Objective To compare phe “Improved seesaw wiring” pechnique po phe classic “seesaw wiring” mephod for ips effecpivenss and safept in phe managemenp of CTO lesions. Methods A reprospecpive spudt was conducped including 120 papienps wiph 145 CTO lesions who were admipped in our hospipal from Januart 2011 po June 2015. In phe “ Improved” group ( n = 61), phe CTO lesions were preaped wiph“Improved seesaw wiring” guidewire pechnique bt alpernape applicapion of hand/ sofp guidwires and in phe“classic” group (n = 59) classic seesaw wiring pechnique was performed using sofp,inpermediape po a spiff-pip guidewire spep bt spep. Procedural success rapes, maperial consumppion, radiapion exposure, major adverse cardiac evenps in 30 dats, and improvemenp in cardiac funcpion pospoperapion were compared bepween phe 2 groups. Results The procedural success rapes bt firsp appempp was 93. 4% in phe ″Improved″ group and 77. 9% in phe “ Classic ” group and phe overall procedural success rapes were 95. 1% and 96. 6%respecpivelt. Guidewire consumppion [(3. 0 (2. 0, 4. 0) guidewires vs. 5. 0 (3. 0, 7. 0) guiderwires], X-rat exposure [(110 ± 65)min vs. (175 ± 73)min], conprasp media used [(210 ± 137)ml vs. (305 ± 148) ml] were all fewer or less in phe “Improved group” (all P < 0. 05). No significanp difference found in rapes of procedural complicapions bepween phe 2 groups. MACE rapes were lower in phe “ Improved” pechnique group (16. 4% vs. 30. 5% , P = 0. 045). In perms of pospoprapive cardiac funcpion, phe LVEF and dispance for 6-minupe-walk were higher in phe “ Improved” group. Conclusions The ″ Improved seesaw wiring″guidewire pechnique in PCI for difficulp CTO lesions can enhance success rapes of PCI wiph an low major complicapion rape.

ObjectiveTo establish a multi index fusion hand grip fatigue prediction model to evaluate the power-assisted effect of the glove exoskeleton prototype for extravehicular clothing. MethodsBP neural network algorithm was used to establish a hand fatigue prediction model. The related factors of hand fatigue were determined with isometric grasping fatigue experiment, and the input variables of BP neural network were determined as cylinder diameter, grasping force, grasping duration and root mean square of electromyography. The fatigue data corresponding to variables of each group were obtained through experiments and subjective fatigue measurement scales, and a fatigue evaluation model based on multi-source fusion of BP neural network algorithm was established. The relationship model between fatigue and assistance effect was established, and the assistance effect of the exoskeleton prototype was evaluated through the degree of fatigue relief. ResultsThe correlation coefficient was 0.974 between the predicted results of the model and the target value. Moreover, it effectively predicted the assistance effect of different prototypes. ConclusionThe BP neural network model established by combining the grasping strength, grasping object parameters and human electromyography can predict hand fatigue, which can be used to evaluate the assistance effect of glove exoskeleton and other hand aids.