AI detection of mild COVID-19 pneumonia from chest CT scans.

OBJECTIVES: An artificial intelligence model was adopted to identify mild COVID-19 pneumonia from computed tomography (CT) volumes, and its diagnostic performance was then evaluated. METHODS: In this retrospective multicenter study, an atrous convolution-based deep learning model was established for the computer-assisted diagnosis of mild COVID-19 pneumonia. The dataset included 2087 chest CT exams collected from four hospitals between 1 January 2019 and 31 May 2020. The true positive rate, true negative rate, receiver operating characteristic curve, area under the curve (AUC) and convolutional feature map were used to evaluate the model. RESULTS: The proposed deep learning model was trained on 1538 patients and tested on an independent testing cohort of 549 patients. The overall sensitivity was 91.5% (195/213; p < 0.001, 95% CI: 89.2-93.9%), the overall specificity was 90.5% (304/336; p < 0.001, 95% CI: 88.0-92.9%) and the general AUC value was 0.955 (p < 0.001). CONCLUSIONS: A deep learning model can accurately detect COVID-19 and serve as an important supplement to the COVID-19 reverse transcription-polymerase chain reaction (RT-PCR) test. KEY POINTS: • The implementation of a deep learning model to identify mild COVID-19 pneumonia was confirmed to be effective and feasible. • The strategy of using a binary code instead of the region of interest label to identify mild COVID-19 pneumonia was verified. • This AI model can assist in the early screening of COVID-19 without interfering with normal clinical examinations.

[Current status of initial diagnosis of speech sound disorder in a child healthcare clinic].

OBJECTIVE: To investigate the understanding of speech sound disorder (SSD) among child health practitioners. METHODS: The clinical data of 506 children with an initial diagnosis of SSD from January 2017 to May 2019 were retrospectively analyzed. RESULTS: Of the 506 SSD children, 90.5% had a description of developmental behavior in their medical records; 97.6% received a developmental-behavioral evaluation, mostly intellectual and developmental screening tests, which were given to 95.8% (485/506) of the total children. A total of 116 (22.9%) children also had neurodevelopmental disorders, commonly presenting with language disorder, global developmental delay, and intellectual disability; however, 53 (45.7%) of the 116 children had no history records of such abnormal developmental behavior. The incidence of neurodevelopmental disorders was significantly higher in the children with abnormal hearing reported by their families than in the children with normal hearing reported by their families (P<0.001). The children with abnormal response to sound stimulation on physical examination had significantly more frequent neurodevelopmental disorders than those with normal response to sound stimulation (P<0.05). Among the 506 children with SSD, hearing condition was ignored in 33.2% in history records, and in 31.2% on physical examination. Ninety-two children (18.2%) completed the diagnostic hearing test, 12% (11/92) of whom were diagnosed with hearing loss. Of the 11 children with hearing loss, three had passed a hearing screening, three had family-reported normal hearing, and seven had normal response to sound stimulation on physical examination. CONCLUSIONS: SSD is frequently comorbid with neurodevelopmental disorders in children. Children's communication performance is a key to the diagnosis of neurodevelop-mental disorders. It's necessary to the diagnosis of SSD to perform a medical history collection about neuropsychological development and a developmental-behavior evaluation. There is a high proportion of children with SSD receiving the developmental-behavioral evaluation, suggesting that child health practitioners pay close attention to the neuropsychological development of SSD children, but mostly, the evaluation merely involves intellectual developmental screening tests. The detection rate of hearing loss in children with SSD is high. However, child health practitioners underestimate this problem, and have an insufficient understanding of the importance of the diagnostic hearing test. The diagnostic hearing test should be the preferred recommendation for assessing hearing ability rather than past hearing screening results or children's response to sound stimulation in life scenes.

Sulfur recycle in biogas production: Novel Higee desulfurization process using natural amino acid salts.

In this work, a desulfurization method using natural amino acid salts (AAS), which can be green prepared by biological fermentation, is proposed to remove H2S from raw biogas. Biogas purification and fertilizer production can be simultaneously achieved to close sulfur recycle. The reaction kinetic characteristics of H2S absorption with three kinds of AAS, including potassium ß-alaninate (PA), potassium sarcosinate (PS) and potassium l-prolinate (PP) are first studied. Kinetic parameters including orders of reaction, rate constants, pre-exponential factors and activation energies are given. AAS absorbent exhibits good potential for biogas desulfurization. Higee (high gravity) technology is utilized to intensify H2S removal. The effects of operating conditions on H2S removal efficiency are investigated and PP shows the best desulfurization performance. The phytotoxicity of AAS and amino acid salt sulfide (AASS) is assessed by the germination index of mungbean seeds. PP and its salt sulfide (PPS) show relatively low phytotoxicity and their allowable agricultural feeding concentrations are below 0.08 M and 0.04 M, respectively. The desulfurization method demonstrates a green route for biogas purification to achieve sulfur recycle.

Chromatic-free spatially resolved optical emission spectroscopy diagnostics for microplasma.

A chromatic-free spatially resolved diagnostic system for microplasma measurement is proposed and demonstrated, which consists of an optical chromatic-free microscope mirror system, an electron multiplying charge coupled device (EMCCD), and bandpass filters. The diagnostic system free of chromatic aberrations with a spatial resolution of about 6 microm is achieved. The factors that limit the resolution of this diagnostic system have been analyzed, which are optical diffraction, the pixel size of the EMCCD, and the thickness of the microplasma. In this paper, the optimal condition for achieving a maximum resolution power has been analyzed. With this diagnostic system, we revealed the spatial nonuniformity of a microwave atmospheric-pressure argon microplasma. Furthermore, the spatial distribution of the time-averaged effective electron temperature has been estimated from the intensity distributions of 750.4 and 415.8 nm emissions.