This paper proposes a motor imagery recognition algorithm based on feature fusion and transfer adaptive boosting (TrAdaboost) to address the issue of low accuracy in motor imagery (MI) recognition across subjects, thereby increasing the reliability of MI-based brain-computer interfaces (BCI) for cross-individual use. Using the autoregressive model, power spectral density and discrete wavelet transform, time-frequency domain features of MI can be obtained, while the filter bank common spatial pattern is used to extract spatial domain features, and multi-scale dispersion entropy is employed to extract nonlinear features. The IV-2a dataset from the 4 ^th International BCI Competition was used for the binary classification task, with the pattern recognition model constructed by combining the improved TrAdaboost integrated learning algorithm with support vector machine (SVM), k nearest neighbor (KNN), and mind evolutionary algorithm-based back propagation (MEA-BP) neural network. The results show that the SVM-based TrAdaboost integrated learning algorithm has the best performance when 30% of the target domain instance data is migrated, with an average classification accuracy of 86.17%, a Kappa value of 0.723 3, and an AUC value of 0.849 8. These results suggest that the algorithm can be used to recognize MI signals across individuals, providing a new way to improve the generalization capability of BCI recognition models.
Brain-Computer Interfaces ; Humans ; Support Vector Machine ; Algorithms ; Neural Networks, Computer ; Imagination/physiology* ; Pattern Recognition, Automated/methods* ; Electroencephalography ; Wavelet Analysis

Objective To explore the differences in neck and lumbar spine injuries among different types of aircraft pilots and the correlation between body surface temperature and the severity of injury.Methods Data were collected by questionnaire surveys and medical examinations.Forty male pilots were selected as research objects,including 14 fighter pilots and 26 helicopter pilots,aged between 28 and 39 years,with a height range of 168 to 178 cm,and a total flight time of 600 to 2 000 h.Infrared thermal imaging was employed for skin temperature.A questionnaire survey was conducted for the assessment of the common site and degree of pain.The relationship between body surface temperature and pain was investigated.Results Fighter pilots mainly complained of discomfort in the neck and scapular region,while helicopter pilots were more likely to experience lower back pain.The skin temperature in the affected regions was significantly higher than that in the surrounding normal regions in both fighter pilots and helicopter pilots(P<0.05).The pain score was positively related with elevated temperature in the affected areas(P<0.05).Conclusion It is found that fighter pilots are more prone to neck and scapular pain,while helicopter pilots are more likely to experience lower back pain.The severity of pain is positively related with increased temperature in the affected areas.Infrared thermal imaging can be used to assess temperature variation at injured sites and the location of training injuries among pilots.

Objective:To compare the degranulation levels of basophils in peripheral blood mononuclear cell (PBMC) and granulocyte populations between healthy subjects and patients with sepsis, and to explore the underlying mechanisms. Additionally, plasma cytokine levels were measured in these volunteers.Methods:Peripheral blood samples were collected from both healthy individuals and sepsis patients. The degranulation level of basophils in sepsis patients and its potential mechanisms were examined. Plasma levels of IL-1β, IL-9, and IL-10 were detected, and Pearson correlation analysis was performed to assess the relationship between degranulated basophils in the granulocyte population and IL-9 levels.Results:Compared with healthy subjects, sepsis patients showed a reduction in basophil percentages within PBMC and granulocyte populations by 94.8% and 37.9%, respectively ( Z = -6.441, P < 0.05; Z = -2.681, P < 0.05). In contrast, both the proportion and number of degranulated basophils in the granulocyte population were increased (both P < 0.05). Plasma levels of IL-1β, IL-9, and IL-10 were significantly elevated in sepsis patients--by 80.6%, 36.7%, and 11.9-fold, respectively ( Z = -4.258, P < 0.05; Z = -3.606, P < 0.05; Z = -4.814, P < 0.05). Moreover, plasma IL-9 levels were highly correlated with both the percentage and count of degranulated basophils in the granulocyte population (both P < 0.05). GO and KEGG enrichment analyses revealed cytological changes and potential mechanisms involving basophils in the PBMC of sepsis patients. Conclusions:The decreased total count of basophils in sepsis patients may elevate the risk of secondary infection. Degranulated basophils in the granulocyte population may contribute to excessive inflammatory responses through IL-9 secretion.

To investigate the effectiveness of a self-developed intelligent medical record writing assistant in enhancing the efficiency of discharge record writing and improving the quality of discharge records, and to assess physicians' satisfaction with the assistant.

Objective:To improve the perception of computed tomography(CT)images in detecting fine fracture through multi-task network of global attention,and to realize the detection of the target of fine fracture at case level through multi-task,and to quickly and accurately identify and locate fracture from a large number of CT images,so as to assist doctors to timely conduct treatment.Methods:A grouped Non-local network method was introduced to calculate the remote dependency relationship between each position of CT image continuous sections and channel.A single-stage detector of multi-objective detection model three dimension(3D)RetinaNet was integrated with the medical image semantic segmentation architecture(3D U-Net).A end-to-end multi-task 3D convolutional network was realized,which realized the detection of case level for fine fracture through multi-task collaboration.Select 600 CT scan images from the Rib Frac Dataset of rib fractures provided by the MICCAI 2020 Challenge,and they were divided into training set(500 cases)and test set(100 cases)as the ratio of 5:1 to test the precise performance of multi-task 3D convolutional network.Results:The precise performance of multi-task 3D convolutional network method was better than that of single-task FracNet,3D RetinaNet and 3D Retina U-Net in detection,which average precision was respectively higher 7.8%and 11.4%than 3D RetinaNet and 3D Retina U-Net.It was better than two kinds of single-task network detection method included 3D Faster R-CNN and 3D Mask R-CNN,and the average precision of that was respectively higher 6.7%and 3.1%than them.Conclusion:The integrated different modules of global attention multi-task network can improve the detection performance of fine fracture.The introduction of grouped Non-local network method can further improve the precise performance for the targets of fine fractures in detection.

Objective To establish and evaluate a gas chromatography-tandem mass spectrometry(GC-MS/MS)method for the detection of six common drugs(methamphetamine,meperidine,caffeine,codeine,cocaine and ketamine)in blood,and to improve the determination basis of results.Methods The above six drugs were added into the blank blood,and GC-MS/MS was used for detection after ether extraction.The collection,quantification and confirmation were carried out under the mode of multi-reaction monitoring(MRM).The qualitative results of the above six drugs were evaluated based on the maximum allowable deviation of the retention time and relative ion abundance ratio in the qualitative results of GC-MS/MS.Results There was a good linear relationship between the six common drugs,among which ketamine and caffeine had the lowest detection limit(0.01 μg/mL),methamphetamine had the highest detection limit(0.5 μg/mL).The retention time(RT)and relative retention time(RRT)of the target substance were stable under the six supplemental levels,and the absolute deviation(ΔRTabsolute)of RT was within±0.025 min.The absolute deviation of RRT(ΔRRTabsolute)was within±0.004.The relative ion abundance ratio absolute deviation(ΔIabsolute)is±20%,and the relative ion abundance ratio relative deviation(ΔIrelative)is±50%.Conclusion This study clarified the reference range for qualitative determination of six common drugs in blood matrix detected by GC-MS/MS,and effectively supplemented the qualitative determination indicators of existing instrumental analysis methods.

Objective:To retrospectively analyze the screening results for genetic metabolic diseases among newborns from Changsha in order to determine the prevalence of single diseases and their mutational spectrum.Methods:352 449 neonates born from January 2016 to December 2021 in Changsha were subjected to tandem mass spectrometry. Suspected cases were further analyzed by biochemical and genetic testing.Results:Among the 352 449 newborns, 6 170 were positive for the screening, which yielded a positive rate of 1.75%. 5 437 cases were recalled, and 92 were confirmed, with the overall prevalence being 1∶3 831 and positive predictive value of 1.69%. Eighteen genetic metabolic diseases were detected among the 92 children, including 33 amino acid metabolic disorder, among which 20 were phenylalanine hydroxylase deficiency (60.60%). 17 cases had organic acid metabolic disorders, among which 4 were 2-methyl-dehydrogenase deficiency (23.50%). 42 had fatty acid metabolic disorders, among which 27 (64.30%) were primary carnitine deficiency and 12 were short-chain acyl-CoA dehydrogenase deficiency (28.60%). In total 90 genetic variants were identified, with the most common ones including c. 51C>G, c. 1400C>G, c. 760C>T, c. 1031A>G and c. 1165A>G.Conclusion:The common neonatal genetic metabolic diseases in Changsha include primary carnitine deficiency, phenylalanine hydroxylase deficiency and short-chain acyl-CoA dehydrogenase deficiency. The preliminary delineation of mutational spectrum for genetic metabolic diseases in Changsha can facilitate early diagnosis and intervention, so as to improve the quality of newborn population.

Objective: To explore the applicability of semi-quantitative risk assessment methods in wood furniture manufacturing companies. Methods: Two medium-sized wooden furniture manufactures were randomly selected as research objects, namely A company and B company. Used the Semi-Quantitative risk assessment method (the ratio method, the index method and the comprehensive method) in the "Guidelines for occupational health risk assessment of chemicals in the workplace" (GBZ/T 298-2017) to conduct occupational hygiene survey, occupational hazard factor testing and occupational health risk assessments for two wood furniture manufacturers from January to October 2018, and compared and analyzed the applicability of these three semi-quantitative risk assessment methods in wooden furniture manufacturing enterprises. Results: The occupational health status of A enterprises was worse than that of B enterprises, and the occupational health risk level was higher than that of B enterprises, and the risk level of A enterprise is 3~4, and the risk level of B enterprise is 2~3. The occupational health risk level obtained by the index method was consistent with the comprehensive method, while the risk level of some occupational disease hazards used the ratio method was inconsistent with the results of the index method and the comprehensive method. Compared with the index method and the comprehensive method, when E/OEL<0.5 or E/OEL≥2, there might be a certain fluctuation in the occupational health risk level obtained by the ratio method. Conclusion The semi-quantitative risk assessment is more objective, comprehensive and flexible in the application of occupational health risk assessment, and can assess the occupational health risk level of chemical poisons in wood furniture manufacturing enterprises.

An accident of mixed acute gas poisoning accident happened in a place in GuangDong in March 2018. To investigates three poisoning workers and related clinical data were summarized., we tested the field air and analyzed the accident reasons. This event due to the staff lack of occupational protection awareness and illegal operation. The working environment must be ventilated before limited space operation, and must be sure that the limited space is safe by toxic gas monitoring. In case of occupational acute gas poisoning, rescuers should help the persons who are poisoned reasonably and meanwhile their own safety.

OBJECTIVE: To explore the applicability of Singapore Ministry of Manpower( MOM) risk model and MES model in risk assessment of occupational health hazard caused by chemical poisons in shoemaking enterprises. METHODS: A medium-sized shoemaking enterprise in Guangzhou City was selected as the research object to carry out on-the-spot investigation of occupational health,measure the level of chemical hazards in the air of the workplace. Occupational health risk assessment of chemical toxins in the workplace was conducted using the MOM model and the MES model,and the results of the two evaluations were compared. RESULTS: The occupational chemical hazards in workplace of the shoemaking enterprise mainly included the toluene,xylene,ethyl acetate,butyl acetate,n-hexane,and 1,2-dichloroethan( 1,2-DCE). The concentration-time weighted average( CTWA) of 1,2-DCE at the stitching post,methylbenzene at the brush coating post and ethyl acetate at the cleaning post exceeded occupational exposure limits. The MOM model assessment results showed that methylbenzene was of high risk and 1,2-DCE was of medium risk in brush coating post. n-Hexane and1,2-DCE were of medium risk in stitching post. Ethyl acetate and 1,2-DCE was of medium risk in cleaning post. The results of the MES model evaluation showed that the risk level of n-hexane and 1,2-DCE used in sticking,brush coating and cleaning posts was extremely high and the remaining chemicals were highly dangerous. CONCLUSION: Both MOM model and MES model can easily predict and assess the occupational health risk of various posts in shoemaking enterprises to some extent. The assessment result of MES model is more practical than that of MOM model.