[Impact of different angles of pulmonary surfactant administration on bronchopulmonaryplasia and intracranial hemorrhage in preterm infants: a prospective randomized controlled study]. / ä¸åŒè§’åº¦æ³¨å ¥è‚ºè¡¨é¢æ´»æ€§ç‰©è´¨å¯¹æ—©äº§å„¿æ”¯æ°”ç®¡è‚ºå‘è‚²ä¸è‰¯å’Œé¢ å† å‡ºè¡€çš„å½±å“ï¼šä¸€é¡¹å‰çž»æ€§éšæœºå¯¹ç §ç ”ç©¶.

OBJECTIVES: To investigate the effects of different angles of pulmonary surfactant (PS) administration on the incidence of bronchopulmonary dysplasia and intracranial hemorrhage in preterm infants. METHODS: A prospective study was conducted on 146 preterm infants (gestational age <32 weeks) admitted to the Department of Neonatology, Provincial Hospital Affiliated to Anhui Medical University from January 2019 to May 2023. The infants were randomly assigned to different angles for injection of pulmonary surfactant groups: 0° group (34 cases), 30° group (36 cases), 45° group (38 cases), and 60° group (38 cases). Clinical indicators and outcomes were compared among the groups. RESULTS: The oxygenation index was lower in the 60° group compared with the other three groups, with shorter invasive ventilation time and oxygen use time, and a lower incidence of bronchopulmonary dysplasia than the other three groups (P<0.05). The incidence of intracranial hemorrhage was lower in the 60° group compared to the 0° group (P<0.05). The cure rate in the 60° group was higher than that in the 0° group and the 30° group (P<0.05). CONCLUSIONS: The clinical efficacy of injection of pulmonary surfactant at a 60° angle is higher than other angles, reducing the incidence of intracranial hemorrhage and bronchopulmonary dysplasia in preterm infants.

Occupational exposure to blood and body fluids among dental personnel in a Chinese dental hospital.

OBJECTIVE: To determine the prevalence of occupational exposure (OE) occurring to dentists, dental nurses and senior dental students in a Chinese dental hospital and to assess associated factors with these exposures. METHODS: Data were collected through anonymous questionnaires, which were distributed to dentists, nurses, and senior dental students. RESULTS: All 205 dental personnel who voluntarily participated in the survey completed the questionnaire. Up to 71.2% of respondents experienced at least one OE to blood and body fluids (BBF) one year prior to this study. Dentists had a significantly higher incidence of OE than nurses (82.6% verse 60.8%), and a higher incidence of percutaneous injury than students (63.8% versus 41.7%). Sixty-seven percent of exposed dental personnel did not report the incidents and only 4.1% underwent postexposure blood tests. Although 97.6% of respondents wore gloves, more than half the subjects did not use protective goggles or masks during daily dental practice. CONCLUSION: There was a high level of OE and a significant incidence of underreporting among Chinese dental personnel, particularly in dentists. Inadequate use of personal protective equipment and ignorance about postexposure management were of great concern.

[Design and analysis of spectral recognition system based on neural network].

The technology of spectral recognition is the foundation of qualitative analysis by spectrum. With the technology of pattern recognition developed, the technology of spectral recognition has been a important tool for quick detection in medicine, environment and petrochemical industry etc. Artificial neural network has many good qualities, such as nonlinear mapping, self-adaptive learning, robustness and fault tolerant ability. It is widely applied in signal procesing, knowledge engineering and pattern recognition etc. The present paper takes spectral signal according with Lambert-Beer' law as object, introduces basic pattern recognition theory of artificial neural network in brief, puts forward spectral recognition method based on multiple features and neural network according to spectral recognition need, makes system design and the basic frame of model, and gives an example for explanation.

[Model transfer method based on support vector machine].

The model transfer is a basic method to build up universal and comparable performance of spectrometer data by seeking a mathematical transformation relation among different spectrometers. Because of nonlinear effect and small calibration sample set in fact, it is important to solve the problem of model transfer under the condition of nonlinear effect in evidence and small sample set. This paper summarizes support vector machines theory, puts forward the method of model transfer based on support vector machine and piecewise direct standardization, and makes use of computer simulation method, giving a example to explain the method and compare it with artificial neural network in the end.

[Application of fractal theory to spectral signal recognition].

The fractal theory is a discipline that studies a kind of irregular and chaotic object with similarity of its part and whole. The fractal dimension is a basic index mark of irregularity and self-similarity in the fractal theory. The present paper takes the spectral signal according with Lambert-beer' law as the object, introduces the basic theory of fractal geometry in brief, puts forward the method of fractal dimension as the feature of spectral signal recognition, makes use of reconstructing phase space to gain the fractal dimension of spectral signal, compares different values of the fractal dimension to recognize different spectral signal, and gives an example for explanation.

[Spectral signal recognition based on wavelet packet analysis].

Automated recognition of spectral signal is an importance part of spectral analysis, which jnvolves comparing spectral signals under the same conditions and obtaining relation of chemistry constitution according to similarity by pattern recognition method and computer technique, and is useful to determine the nature of spectral signal and validate spectral signal. This paper takes spectral signal according with Lambert-beer' law as object, introduces basic theory and method of recognition of spectral signal in brief, normalizes spectral signal to decrease difficulty, introduces wavelet analysis theory, puts forward the method of wavelet packet analysis to gain features of spectral signal, obtains formula to compute feature vector and error vector by statistics method, then makes use of binary tree' mode distinguishing step by step for quick recognition, and finally gives an example to explain.

[Reducing the influence non-linearity of detecting array on absorption spectrum with curve fitting].

In a micro spectral analytical system, the non-linearity response of the photoelectronic detecting array pixel will cause the deformation of the spectrum, especially in the measurement of absorption spectrum. In this paper, the factors that cause the deformation were studied and a corresponding solution was proposed to reduce such deformation. By using curve fitting, the non-linearity of the pixel can be corrected. This method was adopted to correct the absorption spectrum obtained by a micro spectral analytical system and the result showed that it is a efficient way to correct the non-linearity in the pixel of photoelectronic detecting array.