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The spatial and temporal distribution of aquaporin-4 (AQP4) expression in rat brain following brain trauma and AQP4-siRNA treatment, as well as corresponding pathological changes, were studied to explore the mechanism underlying the effect of AQP4-siRNA treatment on traumatic brain injury (TBI). The rats in the sham operation group had normal structure, with AQP4 located in the perivascular end-foot membranes and astrocytic membranes in a polarized pattern. The accelerated polarity reversal was observed in the TBI group in 1–12 h after TBI. During this period, AQP4 abundance on the astrocytic membrane is gradually increased, while AQP4 abundance on the perivascular end-foot membrane declined rapidly. Twelve hours after TBI, AQP4 expression was depolarized, showing a shift from the perivascular end-foot membrane to the astrocytic membrane. Pathological observation showed that vasogenic edema occurred immediately after TBI, at which time the extracellular space was expanded, leading to severe intracellular edema. AQP4-siRNA reduced the polarity reversal index at the early stage of TBI recovery and reduced edema, demonstrating the potential benefit of reduced AQP4 expression during recovery from TBI.

Hypertension is a confirmed risk factor for cerebral hemorrhage in humans. Which endogenous factor directly induces hypertension-related stroke is unclear. In this study, 42 hemorrhagic stroke patients with hypertension and hyperlipidemia and 42 age-matched healthy controls were recruited. The contents of serum semicarbazide-sensitive amine oxidase (SSAO) and formic acid (FC, a final product of SSAO metabolism) were examined in the patients after stroke. Hemorrhagic areas were quantified by computer tomography. In the animal study, hemorrhagic degree was assessed by hemotoxylin & eosin or tissue hemoglobin kits. The relationship between FC and blood pressure/hemorrhagic degree was explored in wild-type mice and hSSAOTG mice fed with high-fat diets or high-fat and -salt diets. The results showed that the levels of serum FC were positively correlated with blood pressure and hemorrhagic areas in stroke patients. Transfection of microRNA-134 could enhance SSAO expression in human vascular smooth muscle cells. Consistently, after treatment with high-fat and -salt diets, hSSAOTG mice exhibited higher levels of miR134 and FC, higher blood pressure, and more severe hemorrhage than wild-type mice. Interestingly, folic acid reduced hypertension and hemorrhage in hSSAOTG mice fed with high-fat diets. These findings suggest that FC is a crucial endogenous factor for hypertension and hemorrhage.

Background: Obstructive sleep apnea-hypopnea syndrome (OSAHS) is closely associated with pulmonary diseases. N6-methyladenosine (m6A) is involved in the process of intermittent hypoxia-reoxygenation (IR) promoting lung injury. However, it is unclear whether m6A regulates the progression of lung injury under IR.Methods: Pathological examination by using Hematoxylin and eosin and Masson staining. Protein and mRNA were determined by Western blot and RT-qPCR, respectively. The m6A levels and concentrations of inflammatory cytokines were measured using ELISA. Cell apoptosis was measured by Annexin V-FITC/PI staining. m6A methylation modification of pre-miR-21 detected by gene-specific m6A assay.Results: Toll-like receptors 4 (TLR4) was elevated in IR-induced rat lung tissues and pulmonary microvascular endothelial cells (PMVEC). Knockdown of TLR4 alleviated IR-induced PMVEC cell inflammation and apoptosis via inhibiting MyD88/NF-kB signaling pathway. Next, we found the miR-21-5p expression downregulated and targeted TLR4 expression. Overexpression miR-21-5p alleviated IR-induced PMVEC cells inflammation and apoptosis, and inhibited MyD88/NF-kB signaling pathway by targeting TLR4. Interestingly, we found the m6A demethylase AlkB homolog 5 (ALKHB5) was increased in IR-induced rat lung tissues and PMVEC cells, which was associated with decreased m6A levels. ALKBH5 overexpression decreased m6A methylations of pre-miR-21 and reduced the levels of both pre-miR-21 and miR-21-5p. In addition, suppression of ALKBH5 alleviates IR-induced lung injury by reducing the activity of TLR4/MyD88/NF-kB signaling pathway in a miR-21-5p-dependent manner.Conclusion: Our findings demonstrated that ALKBH5 promotes OSA-induced lung injury through activation of TLR4/MyD88/NF-kB signaling pathway by reducing m6A methylations of pre-miR-21 to decrease the expression levels of both pre-miR-21 and miR-21-5p.

This work was financially supported by the National Natural Science Foundation of China (NSFC Nos. 21875112 and 21576139), the National and Local Joint Engineering Research Center of Biomedical Functional Materials, and the Priority Academic Program Development of Jiangsu Higher Education Institutions.

BackgroundMorning urine formaldehyde concentrations could predict the severe degree of dementia in patients with post-stroke dementia and Alzheimer’s disease. However, the routinely available technique of high-performance liquid chromatography (HPLC) for detecting urine formaldehyde requires expensive and sophisticated equipment.MethodsWe established a fluorescence spectrophotometric method by using a formaldehyde-specific fluorescent probe-NaFA (λex/em = 430/543 nm). As a standard reference method, the same batch of urine samples was analysed by HPLC with a fluorescence detector (λex/em = 346/422 nm). Then we compared the limits of detection and the limits of quantization detected by these two methods and addressed the relationship between urine formaldehyde and human cognitive ability. The Mini-Mental State Examination (MMSE), Clinical Dementia Rating and Activities of Daily Living scale were used to evaluate cognition function in 30 Alzheimer’s disease patients and 52 healthy age-matched controls.ResultsLimits of detection and limits of quantization (1.27 and 2.48 μM) of the NaFA probe method were more accurate than Fluo-HPLC (1.52 and 2.91 μM). There was no difference in the detected formaldehyde values within day and day-to-day. Notably, only 3/82 urine formaldehyde concentrations detected by NaFA probe were below zero, while 12/82 of the values analysed by Fluo-HPLC were abnormal. More importantly, there were negatively correlated between urine formaldehyde concentrations detected by NaFA probe and MMSE scores, but positively correlated with Clinical Dementia Rating scores in Alzheimer’s disease patients.ConclusionsThis detecting urine formaldehyde method by NaFA probe was more rapid, sensitive and accurate than Fluo-HPLC.

A broadband dual-band microstrip antenna which is applied to the specified standards of WLAN application band and data transmission rate is proposed in this paper. The antenna based on the conventional planar monopole antenna is obtained by adding two L-shaped resonant branches which make this antenna be able to transmit and receive the dual frequencies electromagnetic wave signals. Parameters of the antenna are optimized by HFSS. The simulation results show that the low frequency band of antenna is 2.34 GHz ~2.61 GHz, the relative bandwidth is 14.9% and the maximum gain is 2.04dB; the high frequency band is 4.89 GHz-7.81 GHz, the relative bandwidth is 45.6% and the maximum gain is 4.04dB. This antenna is enough to satisfy the requirement of WLAN application frequencies. The antenna has the advantages of good radiation performance, wide band, small size, simple structure and easy integration.

This paper focuses on the problem of target imaging detection in low light environment at night, designed the driving circuit of sensor Based on Gsense400 chip and Virtex-5 of Xilinx FPGA chip, which can replace the traditional image intensifier when the illumination is under 10-3 lux, including power interface, clock configuration, SPI interface, timing relationship, LVDS to CameraLink interface. The data processing speed of the sensor is 2.4gb/s, readout noise is 1.6e-, image resolution is 2048x2048, frame rate is 24fps. The optical system is designed based on double Gauss by using ZEMAX, which is composed of nine lenses. The field range is 12°x 12°, F-Number is 1, the system distortion is less than 0.2%, the MTF in the central 50% field is more than 0.4 , the TOTR length is 112mm, which realized the system requirements in miniaturization, starlight level image, high dynamicperformance ,day and night availability.

Most of the current health management products are used in medical institutions and generally do not pay enough attention to the student population. Based on this, this paper designs a student-oriented and functional autonomous health management system. This paper proposes a personal health management system based on a multidimensional data model based on the main social characteristics of the population with chronic diseases and the actual needs of personal health management for chronic diseases. The value of various health data for health management is deeply analyzed and mined, and a multidimensional model data warehouse is constructed according to relevant national health data standards to create a standard data platform for intelligent health warning and disease risk assessment. This paper researches and designs a closed-loop personal health management method based on the Plan-Do-Check-Action (PDCA) cycle management model, with detailed functional design in four aspects: health data collection and recording, health assessment, health planning, and tracking and execution. This paper researches health data collection, processing, and storage technologies and adopts HDFS data storage technology, html, css, Java Script, java, and other software development technologies, combined with j Query, UEditor, Date Range Picker, and other plug-ins, as well as SMS email generation interface, wireless Bluetooth transmission interface, etc. This system web and mobile application platforms are designed and developed. Relational database is used as the system database, and a snowflake-type multidimensional data model is designed. Finally, the functions and performance of this system were tested, and the development and trial run of the basic version have been completed.

Coronavirus disease 2019 (COVID-19) is a newly emerged disease with various clinical manifestations and imaging features. The diagnosis of COVID-19 depends on a positive nucleic acid amplification test by real-time reverse transcription-polymerase chain reaction (RT-PCR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the clinical manifestations and imaging features of COVID-19 are non-specific, and nucleic acid test for SARS-CoV-2 can have false-negative results. It is presently believed that detection of specific antibodies to SARS-CoV-2 is an effective screening and diagnostic indicator for SARS-CoV-2 infection. Thus, a combination of nucleic acid and specific antibody tests for SARS-CoV-2 will be more effective to diagnose COVID-19, especially to exclude suspected cases.

Aircrafts are potentially subjected to damaging events during their service life. How to cope with impact events and impact related damage is a priority in the development of aircraft composite structures. The impact monitoring method presented in this paper utilizes acoustic emission (AE) based data to classify and thereby localize impact events. The method is implemented and tested on a full-scale aircraft elevator. This work builds on earlier research for the classification of AE signals acquired by a single sensor during impact events using a backpropagation neural network with two hidden layers [1]. The innovative aspect of the new method lies in the use of a deep learning algorithm to achieve the zonal localization of impact events. Compared to the backpropagation neural network method, the deep learning method can output localization results with improved accuracy without the need to extract signal features, such as time of arrival, signal strength and amplitude. For this paper, stacked autoencoder algorithms were applied. To train and test the performance of the new model, the same aircraft elevator impact test setup from prior work was used. A single sensor was attached to the spar of the elevator to collect the acoustic emission events. Impacting with steel spheres was conducted on the elevator skin at various distances from the impact source to the sensor. Results demonstrate the efficacy and potential of the deep learning-based approach for localization of impact events for aircraft elevators.

For the old intelligent malfunction diagnosis method has the problem of low diagnostic precision in the malfunction diagnosis of scrolling bearings, a heuristic search algorithm, cuckoo searching algorithm (CS) is proposed to optimize the BP network, so as to improve the diagnostic precision. First, utilize the BP network to construct scrolling bearings’ malfunction diagnosis classification model, secondly, utilize the cuckoo searching algorithm to optimize the BP’s weight and finally, utilize the optimized BP network for malfunction diagnosis. Simulating effects indicate that this means has better sort effect and is suitable for malfunction diagnosis of scrolling bearing. It has certain practicability.

Along with increasing mobility of populations, TB in migrating population is one of the main reasons for aggravating epidemics of TB. TB in migrating population is more serious than that in common people, with more factors influencing its epidemics and more challenging detection and management. The migrating population with TB is characterized by high mobility, low socioeconomic status, poor living conditions in areas with heavy TB burden, insufficient knowledge about health, poor accessibility of health-care service, and prolonged delay for diagnosis and treatment of TB. The morbidity and mortality of TB in migrating populations are higher than those in urban residents and the migrating population is the high-risk population of TB. TB in migrating population constitutes a great challenge to prevention and control of TB.

Alkali-silica reaction (ASR) is one of main damages causes in concrete structures such as nuclear power plants which may endanger structural serviceability and integrity. Acoustic emission (AE) is a passive nondestructive method for structural health monitoring. It is very sensitive and has the capability of monitoring structures continuously. This method may be an alternative for early damage detection in concrete nuclear structures affected by ASR. The innovation of this paper lies in the implementation of deep learning algorithms to evaluate the ASR progress. ASR was monitored by AE in a concrete specimen, which was cast with reactive coarse aggregates and reinforced by steel rebars. The AE signals recorded during the experiment were filtered and divided into two classes. Two deep learning algorithms of convolutional neural network (CNN) and stacked autoencoder were employed to classify the AE signals into the corresponding classes. The model based on CNN resulted in a classifier with higher accuracy than the model based on the autoencoder network.

Yeying Wang,1,2 Li Ai,1 Jiahong Luo,2 Ran Li,1 Yanlin Chai,1 Xiaojie He,1 Yu Cao,1 Yongxia Li1 1Department of Respiratory Medicine, The Second Affiliated Hospital of Kunming Medical University, 2Department of Epidemiology and Biostatistics, School of Public Health, Kunming Medical University, Chenggong New City, Kunming, Yunnan Province, People’s Republic of China Objectives: The aims of this study were to describe changes in day- and nighttime symptoms and the adherence to nasal continuous positive airway pressure (nCPAP) during the first 3-month nCPAP therapy among newly diagnosed patients with obstructive sleep apnea/hypopnea syndrome (OSAS) and to identify the effect of adherence on the changes in day- and nighttime symptoms during the first 3months.Methods: Newly diagnosed OSAS patients were consecutively recruited from March to August 2013. Baseline clinical information and measures of the Epworth Sleepiness Scale (ESS), Fatigue Severity Scale (FSS), Zung’s Self-Rating Depression Scale (SDS) and the Pittsburgh Sleep Quality Index (PSQI) at baseline and the end of 3rd, 6th, 9th and 12th week of therapy were collected. Twelve weeks’ adherence was calculated as the average of each 3-week period. Mixed model was used to explore the effect of adherence to nCPAP therapy on ESS, FSS, SDS and PSQI in each 3-week phase.Results: Seventy-six patients completed the 12-week follow-up. The mixed-effects models showed that under the control of therapy phase adherence in the range of

How to adjust the training and construction plan for the college faculty and improve their capacity or education and instruction in Chinese universities is an urgent problem to be explored and solved under the background of education big data. In the era of big data, relevant analysis has received extensive attention because of its ability to discover the intrinsic associations between things quickly and efficiently, and has been effectively applied to various fields. In this paper, we are based on the data of 2018 senior professional title defense in several Chinese universities to analyze the correlation between the respondent’s grades and ages, education and majors by using big data correlation mining technology. The purpose is to explore the status quo and problems of teachers’ talent team construction, and then find a suitable way for the construction and training of college teachers in the era of big data.

Obstructive sleep apnea (OSA) has been demonstrated to be implicated in disorder of insulin secretion and diabetes mellitus. In this study, we aimed to evaluate the protective role of tempol, a powerful antioxidant, in chronic intermittent hypoxia (IH)-induced pancreatic injury. The rat model of OSA was established by IH exposure. The pathological changes, increased blood-glucose level, and raised proinsulin/insulin ratio in pancreatic tissues of rats received IH were effectively relieved by tempol delivery. In addition, the enhanced levels of pro-inflammatory cytokines, TNF-α, IL-1β, IL-6, and inflammatory mediators, PGE2, cyclooxygenase-2 (COX-2), NO, and inducible nitric oxide synthase (iNOS) in pancreatic tissue were suppressed by tempol. Moreover, tempol inhibited IH-induced apoptosis in pancreatic tissue as evidenced by upregulated Bcl-2 level, and downregulated Bax and cleaved caspase-3 levels. Finally, the abnormal activation of mitogen-activated protein kinase (MAPK) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathways induced by IH was restrained by tempol administration. In summary, our study demonstrates that tempol relieves IH-induced pancreatic injury by inhibiting inflammatory response and apoptosis, which provides theoretical basis for tempol as an effective treatment for OSA-induced pancreatic injury.

The bearings used in the mechanical equipment that bear and transfer the load are vulnerable parts. In this paper, a rolling bearing fault diagnosis method based on eigenvalue selection and dimensionality reduction is presented. This is suitable for analyzing fault signals with nonstationary characteristics, and it has a good recognition rate. The characteristic quantity of vibration signals in the time domain and the frequency domain is calculated, and the characteristic quantity is selected by calculating the degree of difference. A dimension reduction algorithm is proposed, which is based on a neural network and ISOMAP. Its performance is compared using PCA, LTSA, and ISOMAP algorithms. Fault diagnosis is carried out by using KNN and SVM classification algorithms, and good recognition results are obtained.

The dry cask storage system (DCSS) canisters have been used for the storage of high-level nuclear for decades. The inspections are needed to ensure that structural integrity is maintained. One mechanism of degradation on DCSS canisters that is of interest is stress corrosion cracking (SCC). Acoustic emission (AE) is a nondestructive technique that can be employed as an inspection approach since it can offer real-time degradation detection. This paper presents the approaches that can localize SCC sources by minimal acoustic emission (AE) sensor. To achieve this goal, three machine learning techniques (artificial neural network, random forest, stacked autoencoders) were adopted to improve the conventional source localization approach. In this paper, source localization is treated as a classification problem. The testing specimen was divided into multiple zones and located the AE signals to their corresponding zones. The AE signals were processed to create two datasets: a dataset consisting of AE parametric features and a dataset consisting of AE waveforms. Source localization approaches using artificial neural networks, random forest, and stacked autoencoders were trained and tested based on the datasets. The results show all three machine learning techniques can learn to map AE signals to their sources. Among them, stacked autoencoders have the best performance (97.8% accuracy of stacked autoencoders versus 91.5% of random forest, and 80.0% of ANN), demonstrating that it could be a potential approach to localize SCC events on DCSS canister.

Multilocular cystic renal neoplasm of low malignant potential (MCRNLMP) might be benefited from nephron-sparing surgery. Contrast-enhanced computed tomography is used for the diagnosis of MCRNLMP but contrast-enhanced ultrasound has lack of nephrotoxicity and several advantages over contrast-enhanced computed tomography and contrast-enhanced magnetic resonance. The purpose of the study was to compare diagnostic parameters of preoperative contrast-enhanced ultrasound against contrast-enhanced computed tomography for the detection of MCRNLMP in patients who faced curative surgery for complex cystic renal mass.Data regarding contrast-enhanced ultrasound, contrast-enhanced computed tomography, and clinicopathological results of 219 patients who underwent curative surgery for complex cystic renal mass (Bosniak classification III or IV) were retrospectively collected and analyzed. Bosniak classification for imaging modality and the 2016 WHO criteria for clinic pathology were used for detection of MCRNLMP.Contrast-enhanced ultrasound, contrast-enhanced computed tomography, and clinicopathology were detected 68, 66, and 67 as a MCRNLMP respectively. Contrast-enhanced ultrasound and contrast-enhanced computed tomography had 30.37% and 29.27% sensitivities for the detection of MCRNLMP. While 60% and 50% specificities respectively. Bosniak classification III (P = .045) and lower mean Hounsfield unit (P = .049) were associated with the prevalence of MCRNLMP. Contrast-enhanced computed tomography was detected 6 and 7, while contrast-enhanced ultrasound detected 3 and 2 complex cystic renal mass as false positive and false negative MCRNLMP respectively. A contrast-enhanced ultrasound had 0.011 to 1.0 diagnostic confidence and contrast-enhanced computed tomography had 0.045 to 0.983 diagnostic confidence for decision making of nephron-sparing surgeries.Contrast-enhanced ultrasound may have better visualization of MCRNLMP than contrast-enhanced computed tomography.Level of Evidence: III.

A new thermal barrier coating system based on La1.7Dy0.3Zr2O7 (LDZ), which had a lower thermal conductivity for applications above 1773 K, was prepared by the air plasma spraying (APS). The phase composition, thermal expansion coefficient, thermal conductivity, the actual heat insulation and antioxidant ablation of the as-sprayed coatings were investigated. XRD results reveal that single pyrochlore phase LDZ coating is prepared and no new phase appears after ablation at 1573 K and 1773 K. Compared to 8 wt% yttria partially stabilized zirconia (YSZ) coatings, LDZ has better phase stability, lower thermal conductivity, better actual heat insulation, antioxidant ablation and heat resistance performance. These results imply that the LDZ ceramics can be explored as candidate material for the ceramic layer in TBC system. (C) 2015 Elsevier Ltd and Techna Group S.r.l. All rights reserved.

We report on two strategies to design and implement the galvanometer-based laser-scanning mechanisms for the realization of reflectance confocal microscopy (RCM) and stimulated Raman scattering (SRS) microscopy systems. The RCM system uses a resonant galvanometer scanner driven by a home-built field-programmable gate array circuit with a novel dual-trigger mode and a home-built high-speed data acquisition card. The SRS system uses linear galvanometers with commercially available modules. We demonstrate video-rate high-resolution imaging at 11 frames per second of in vivo human skin with the RCM system and label-free biomolecular imaging of cancer cells with the SRS system. A comparison of the two strategies for controlling galvanometer scanners provides scientific and technical reference for future design and commercialization of various laser-scanning microscopes using galvanometers.

Metamaterials are materials engineered to have properties that are naturally unavailable. They hold potentials for developing novel products to be used in wave filtering, acoustic cloaking, vibration control, and energy harvesting. A novel robotized laser powder-feed metal additive manufacturing system has recently been developed for fabricating metallic metamaterials in the Research Center for Advanced Manufacturing in Southern Methodist University. Five types of metallic metamaterials with an enlarged positive Poisson’s ratio, a negative Poisson’s ratio, a bi-stable property, a non-positive coefficient of thermal expansion, and frequency band gaps were designed and additively manufactured by using the developed system.

Virtual Reality (VR) is on the rise nowadays. To save bandwidth and ensure high quality at the same time, only the tiles within field of view (FOV) of the user should be transmitted in high quality while other tiles in low quality or even not transmitted. However, if a user's viewpoint moves fast while watching a panoramic video, low-quality content will always appear in the FOV because of the round-trip time (RTT) delay. Therefore, prediction of viewpoints is used to reduce low-quality area in the FOV. In this paper, we propose methods based on Laplace compensation and Sphere-Markov probability to increase high-quality area in the FOV. Quality value could be increased at most 60.6% and 137% respectively by the two methods.

For hydroelectric generator unit conventional vibration fault diagnosis technology prone to inconsistent results, a information fusion method is proposed based on improved evidence theory. Through the introduction of the credibility factor correct the original evidence, and then by the combination rule of evidence theory carry out information fusion. Case examples show that the method can be the high conflict in the original evidence still gets a better match to determine conclusions, and avoid the existence of divergent phenomenon in several representative improved methods in synthetic consistent evidence, with higher fault tolerance and robustness. Aims to explore the mechanism of evolution of hydropower unit failure, fitting complex nonlinear relationship between fault key parameters and fault types, in order for predict the impending failure of the unit in advance.

The common problem of continuous rigid frame bridge is excessive mid-span deflection. The three factors of excessive deflection including vehicle loads, structural rigidity and prestressed loss are discussed on the case of a three spans continuous rigid frame bridge. Midas Civil is applied to analyze the sensitivity of mid-span deflection for these factors. The results indicate that the deflection is increasing with the increase of vehicle loads or the decrease of structural rigidity or the increase of prestressed loss. Furthermore, mid-span deflection is the most sensitive to the change of prestressed loss.

In order to improve the sealing quality and reduce the labor intensity of people, the stepping motors have been adopted in the salver mechanical transmission part and sealing part of the original sealing machine. In the paper, salver feeding and control system of sealing machine have been designed. The results have been obtained such as control principle diagram of the control system, equivalent circuit diagram and outer wiring diagram of PLC and PLC control program. It can realize the automatic control of the sealing machine. Improved sealing machine has the characteristic of simple mechanical transmission parts, advanced control system, small human error, low fault rate and easy operation.

Based on the survey of existing brush cutter and the analysis of the known conditions, this paper mainly studied design mechanism and principle of brush cutter, and carried on calculation and calibration of spiral bevel gear cutting machine parts, so as to ensure that the design of brush cutter is safe, efficient, simple, comfortable and environmentally friendly. Product after research is of reliable performance, convenient operation, low noise and zero smoke and higher safety factor, making it get more extensive application in the industry.

With the increase of people’s living quality, entertainment has become an essential way of life in modern life, and thus it has become an important and significant research goal to design safe, functional, practical and aesthetic entertainment facilities. In the paper, a novel self-propelled air railcar has been designed on the basis of the characteristics of existing ones. According to the working principle of railcar, the paper adopted ergonomics, to design the seat’s position and height reasonably to ensure passengers’ comfort; adopted innovation design method of bionics, where the appearance modeling design combined the moon, clouds and stars to comply with the times; used 3D software to model and render the model, and thus to express the artistic conception and reality sense of product, then the product will get recognition by consumers in both function and aesthetics.

Sled motorcycle model design is a comprehensive design gathering mechanical engineering, ergonomics, aerodynamics and color design. This paper analyzed the design in detail from the perspectives of ergonomics, aerodynamics and color design, and researched the significance of products using functions and spiritual aesthetics.

The Multi-functional medical bed has been designed to the patient whose life cant been provided for oneself, critically ill patients, and the special needs of paralyzed patients. In the paper, through market research and according to the structure of existing medical bed, a manual medical bed has been designed; And the bed board, lift back and leg mechanism, defecation device and eat device of the medical bed have been discussed; the feasibility analysis of the motion mechanism has been carried and the basic design parameters of the product have been determined; on the basis, the main structure for medical bed has been carried on the design and calculation. The results showed that function of the medical bed is reliable, the structure is reasonable, and it is in line with the requirements of ergonomics. Especially, some of these institutions have been optimized and replace to use more convenient and quickly.

The whispering gallery mode (WGM) microcavity has been widely used for sensing and detection because of its high quality factor, small mode size, simple and diverse manufacturing process, and high sensitivity to the surrounding environment. Microsphere cavityand microdisk cavity are typical whispering gallery mode microcavities. However, the real controllable size of the on-chip three-dimensional microsphere cavity has rarely been reported because it is difficult to prepare by photolithography. At the same time, most of the current microsphere cavity are prepared by hot melting, which have the poor ability to control the size. In this article, we have mainly demonstrated the fabrication of a dye-doped polymer whispering gallery mode microsphere by femtosecond laser two-photon polymerization, which shows good surface smoothness with a fabrication spatial resolution beyond the diffraction limit. The microsphere cavity consists with commercial photoresist SU-8 as the cavity material and Rhodamine B as the gain medium. With the 532 nm pump, the RhB-doped SU-8 can emit fluorescence in the spectral range of 600–700 nm, and thus resonant whispering gallery laser modes in this spectral region can be eventually formed in the microsphere cavities. The microcavity shows excellent lasing performance with a quality factor of ~2000. Due to the special luminescence mechanism of organic dyes, the fluorescence spectrum of the dye drifts with the change of ambient temperature, and it will form a new resonance excitation with the eigenmode of the cavity. Within a certain temperature range (20 ℃－35 ℃), the wavelength of the main lasing peak is linearly related to temperature. The results shows that the organic dye doped micro-resonator has a unique laser mechanism which can be used to construct a new type of microlaser. Moreover, the tunable microsphere laser can be used as a temperature sensor after further optimized. We believe our work will provide a positive inspiration for the rational design of miniaturized lasers with ideal performance.

Since the 21st century, with the rapidly development of the Internet, it promotes the rapidly development of electronic commerce. In present e-commerce activities,it mainly includes government agencies and online shopping which draw people's special attention to it . This study analyzes the statistical data in a certain time the user access to online shopping site and puts forward that this law according with certain probability density distribution conclusion. This paper plans a table which pushed a compound probability distribution model through the basic probability density function in order to adapt to the search engine's rule.It finally applied the composite model to probability distribution of people use search engine successful and found that the use of composite model prediction value are at risk than other models. probability distribution of the users in a certain time shopping can be pointed out which has a certain guiding significance on the search engine marketing model in electronic commerce environment.

RMB contains a large number of coins in circulation in the financial and other fields, this coin inventory and classification, is through manual means, this mode of operation and low work efficiency and give the operator a great trouble, the labor intensity greatly, and not accurate. In the paper, an automatic sorting and measuring machine has been designed and mainly used for sorting, counting, packaging to a variety of coin. The main function of automatic sorting and measuring machine are automatic sorting, counting and packaging. The machine mainly consists of mechanical systems and control systems. It is applied to the modern innovative design and it is the device meeting the need in places for many small denominations of currency. The machine has achieved automation, improved labor productivity, and also brought many conveniences to life. The machine is the inevitable trend of future development.

Glycated haemoglobin (HbA1c) might reflect glycaemic control in persons with diabetes. Study aims were to identify changes in glycated haemoglobin values and predictors (baseline coping behaviour, fasting plasma glucose, disease-related and demographic factors) in patients during 1 year after hospital discharge. A longitudinal prospective design with convenience sampling was used. Subjects were recruited from a community hospital in Taiwan. Measures included Jalowiec Coping Scale, fasting plasma glucose, HbA1c values, and demographics. Generalized estimating equation was used to determine factors of change in glycated haemoglobin. A total of 57 patients completed 1 year of follow-up. Half did not receive diabetes mellitus education and regular exercise. Patients' glycated haemoglobin levels follow controls at 6 months after discharge. Patients with higher levels of blood glucose, less problem-focused coping and greater emotion-focused coping were associated with poor glycaemic control. Education programmes should involve individual-centred care and health behaviours for prevention of diabetes complications.

In this paper, bionic design of the sled motor body has been introduced on the basis of the main structural features of sled motor. The bionic design included the body design and color design. The theories of the law of formal beauty for the shape and color collocation have been rationally analyzed. And the conclusion has been achieved that there is one process from sensibility to rationality in the bionic model design and color design. It is also the design process, rule and pattern of the abstract form in bionic design.

With the development of social, economic, health is increasingly being emphasized by people and has become a topic that can not be ignored. However, having a healthy body also need been the right health care. So, efficient and safe products are more popular with consumers. In paper, a self-service-based and purely mechanical traction treatment bed has been designed. The various parts of the self-traction treatment bed is introduced in detail. The structural designs of its unique folding feature, adjustable bed, a fixed bracket, rotation driving handle, the bottom track sliding, etc., make up for the design of the traditional traction therapy instrument. This traction treatment bed breaks the traditional design style and does reflect the modernist design style in the man-machine combination.

The equivalent salt deposit density (ESDD) of insulator in power system is the main basis of defining pollution classes and mapping pollution areas. However, The meteorological factors on it is complex, using traditional methods is difficult to establish accurate mathematical model to express the relationship, In this paper, the gray theory and neural network model to reflect the changing trend of data series on the apparent effect, Gray neural network model used to predict the insulators ESDD under certain meteorological factors, and to design a neural network compensator correction on the predicted results. The simulation results show that the model has higher prediction accuracy, better than a simple gray neural network model, and have certain theoretical value and practical application value.

Aiming at the characteristics of the gun code image that characters are easy to wear and contrast gradient is too large or too small,a binarization method based on wavelet packet filter floating threshold and Niblack method is proposed.Firstly,the image is filtered using wavelet packet filter and binarized with the low pass image after filtering.Then,the image is binarized with the Niblack method to obtain the second fusing image.Finally,two fusing images are merged based on the minimum principle of image gray values to get the final binarization image.Experimental results show that the method has a good performance in binarization effect and adaptation range and can imply in many situation.

To resolve t he problem of nonlinear and hysteretic temperature controlling of geothermal air conditioning system, this paper, puts forward a fuzzy Smith- PID control policy which is compared with the conventional Smith algorithm over the stability under different temperature and Robust characteristics.The simulation show that the practicability and validity of the fuzzy Smith- PID controlling algorithm in geothermal air conditioning system.

With technology changing rapidly, design of sealing machine for bagged food is also already at the leading edge of the times. This single-layer film and sealing a variety of composite membrane is widely used in food, pharmaceutical, seed, chemical, light industry and other departments. In modern life, it can say that we have all the time with the "seal" has a direct or indirect contact. Therefore, the design of a simple food vacuum bag-sealing machine, it went into the family, Is the common expectations of consumers.In paper, principle of sealing machine for bagged food has been discussed and the vacuum sealing machine including use function and art function has been designed. The sealing machine is fit for home and can prevent food in refrigerator dehydrating, mixing smell, deteriorating etc.

In order to improve the accuracy of fault diagnosis of asynchronous motor, neural network model combined with ant colony algorithm is presented. Taken the mean square error as objective function, then the weights and threshold values are optimized through multiple generation computation of ant colony, and the fault diagnosis is accomplished via the optimized neural network. The simulation results show that the algorithm is to overcome the slow convergence, easy to fall into local minimum problem of BP network, and achieve good diagnosis.

In this paper, according to the requirements of the topic, through the large market research and a series of calculation, I design the requirements of the grinding wheel frame and the spindle. In combination with relevant patent reform on the basis of grinding machine, The guide part of the drive system, micro feeding and automatic feeding mechanism is analyzed and design calculation, so that the machine can greatly reduce the labor intensity of workers and improve the processing accuracy. On this base of the design, I design and select the suitable rail to guarantee the processing precision and the wheel frame seat movement accuracy by using the calculated data and shape dimensions. At last, I design structural and shaping of the centerless cylindrical grinding machine.

Hawthorn (CFS) has commonly been applied as an important traditional Chinese medicine and food for thousands of years. The raw material of CFS is commonly processed by stir-frying to obtain yellow (CFY), dark brown (CFD), and carbon dark (CFC) colored products, which are used for different clinical uses. In this study, an intelligent sensory system (ISS) was used to obtain the color, gas, and flavor samples data, which were further employed to develop a novel and accurate method for the identification of CFS and its processed products using principal component analysis. Moreover, this research developed a model of an artificial neural network, which could be used to predict the total organic acid, total flavonoids, citric acid, hyperin, and 5-hydroxymethyl furfural via determination of the color, odor, and taste of a sample. In conclusion, the ISS and the artificial neural network are useful tools for rapid, accurate, and effective discrimination of CFS and its processed products.

For traditional methods for coal mine gas emission prediction accuracy is not high, an adaptive mutation particle swarm optimization neural network approach is introduced. The algorithm increases the mutation operation in iterative process, and adaptive adjusts mutation probability of the size, in order to enhance the ability to jump out of the local optima. The simulation results show that the method can be better predicted coal mine gas, has a certain practicality.