Industrial SO2 emission monitoring through a portable multichannel gas analyzer with an optimized retrieval algorithm

SO2 variability over a large concentration range and interferences from other gases have been major limitations in industrial SO2 emission monitoring. This study demonstrates accurate industrial SO2 emission monitoring through a portable multichannel gas analyzer with an optimized retrieval algorithm. The proposed analyzer features a large dynamic measurement range and correction of interferences from other coexisting infrared absorbers such as NO, CO, CO2, NO2, CH4, HC, N2O, and H2O. The multichannel gas analyzer measures 11 different wavelength channels simultaneously to correct several major problems of an infrared gas analyzer including system drift, conflict of sensitivity, interferences among different infrared absorbers, and limitation of measurement range. The optimized algorithm uses a third polynomial instead of a constant factor to quantify gas-to-gas interference. Measurement results show good performance in the linear and nonlinear ranges, thereby solving the problem that the conventional interference correction is restricted by the linearity of the intended and interfering channels. The results imply that the measurement range of the developed multichannel analyzer can be extended to the nonlinear absorption region. The measurement range and accuracy are evaluated through experimental laboratory calibration. Excellent agreement was achieved, with a Pearson correlation coefficient (r(2)) of 0.99977 with a measurement range from approximately 5 to 10 000 ppmv and a measurement error of less than 2 %. The instrument was also deployed for field measurement. Emissions from three different factories were measured. The emissions of these factories have been characterized by different coexisting infrared absorbers, covering a wide range of concentration levels. We compared our measurements with commercial SO2 analyzers. Overall, good agreement was achieved

DTNBP1, a schizophrenia susceptibility gene, affects kinetics of transmitter release

Schizophrenia is one of the most debilitating neuropsychiatric disorders, affecting 0.5–1.0% of the population worldwide. Its pathology, attributed to defects in synaptic transmission, remains elusive. The dystrobrevin-binding protein 1 (DTNBP1) gene, which encodes a coiled-coil protein, dysbindin, is a major susceptibility gene for schizophrenia. Our previous results have demonstrated that the sandy (sdy) mouse harbors a spontaneously occurring deletion in the DTNBP1 gene and expresses no dysbindin protein (Li, W., Q. Zhang, N. Oiso, E.K. Novak, R. Gautam, E.P. O'Brien, C.L. Tinsley, D.J. Blake, R.A. Spritz, N.G. Copeland, et al. 2003. Nat. Genet. 35:84–89). Here, using amperometry, whole-cell patch clamping, and electron microscopy techniques, we discovered specific defects in neurosecretion and vesicular morphology in neuroendocrine cells and hippocampal synapses at the single vesicle level in sdy mice. These defects include larger vesicle size, slower quantal vesicle release, lower release probability, and smaller total population of the readily releasable vesicle pool. These findings suggest that dysbindin functions to regulate exocytosis and vesicle biogenesis in endocrine cells and neurons. Our work also suggests a possible mechanism in the pathogenesis of schizophrenia at the synaptic level

BNT162b2 or CoronaVac Vaccinations Are Associated With a Lower Risk of Myocardial Infarction and Stroke After SARS‐CoV‐2 Infection Among Patients With Cardiovascular Disease

Background: COVID‐19 vaccines have demonstrated effectiveness against SARS‐CoV‐2 infection, hospitalization, and mortality. The association between vaccination and risk of cardiovascular complications shortly after SARS‐CoV‐2 infection among patients with cardiovascular disease remains unknown. Methods and Results: A case–control study was conducted with cases defined as patients who had myocardial infarction or stroke within 28 days after SARS‐CoV‐2 infection between January 1, 2022 and August 15, 2022. Controls were defined as all other patients who attended any health services and were not cases. Individuals without history of cardiovascular disease were excluded. Each case was randomly matched with 10 controls according to sex, age, Charlson comorbidity index, and date of hospital admission. Adjusted odds ratio with 95% CI was estimated using conditional logistic regression. We identified 808 cases matched with 7771 controls among all patients with cardiovascular disease. Results showed that vaccination with BNT162b2 or CoronaVac was associated with a lower risk of myocardial infarction or stroke after SARS‐CoV‐2 infection with a dose–response relationship. For BNT162b2, risk decreased from 0.49 (95% CI, 0.29–0.84) to 0.30 (95% CI, 0.20–0.44) and 0.17 (95% CI, 0.08–0.34) from 1 to 3 doses, respectively. Similar trends were observed for CoronaVac, with risk decreased from 0.69 (95% CI, 0.57–0.85) to 0.42 (95% CI, 0.34–0.52) and 0.32 (95% CI, 0.21–0.49) from 1 to 3 doses, respectively. Conclusions: Vaccination with BNT162b2 or CoronaVac is associated with a lower risk of myocardial infarction or stroke after SARS‐CoV‐2 infection among patients with cardiovascular disease

Experimental study of freak wave impacts on a tension-leg platform

This study investigates the freak wave impinging on a tension-leg platform through wave flume experiments. The freak waves are generated using the focused wave theory. By adjusting the wave focusing location, different incident wave scenarios at the structure location are produced. Simultaneous measurements of wave shape evolutions upon impingement, wave impact pressures on the platform deck, platform motions and tether forces are carried out for synchronized analyses of the wave kinematics/dynamics and structural responses. The variation of these parameters with the incident wave profile is studied. It is found that although applying less intensive local impact pressures as compared to the highly-breaking freak wave, the slightly-breaking or non-breaking freak wave imposes the same level of adverse effect on the platform's global stability in terms of motions and tether forces. In addition, the high-crest freak wave causes violent motions of the floating platform, which are likely to induce snap loads of large amplitude and high occurrence frequency in tethers. The published results would provide useful benchmarks for validating numerical and analytical models

Safety of BNT162b2 or CoronaVac COVID-19 vaccines in patients with heart failure: A self-controlled case series study

BACKGROUND: COVID-19 vaccines are important for patients with heart failure (HF) to prevent severe outcomes but the safety concerns could lead to vaccine hesitancy. This study aimed to investigate the safety of two COVID-19 vaccines, BNT162b2 and CoronaVac, in patients with HF. METHODS: We conducted a self-controlled case series analysis using the data from the Hong Kong Hospital Authority and the Department of Health. The primary outcome was hospitalization for HF and the secondary outcomes were major adverse cardiovascular events (MACE) and all hospitalization. We identified patients with a history of HF before February 23, 2021 and developed the outcome event between February 23, 2021 and March 31, 2022 in Hong Kong. Incidence rate ratios (IRR) were estimated using conditional Poisson regression to evaluate the risks following the first three doses of BNT162b2 or CoronaVac. FINDINGS: We identified 32,490 patients with HF, of which 3035 were vaccinated and had a hospitalization for HF during the observation period (BNT162b2 = 755; CoronaVac = 2280). There were no increased risks during the 0–13 days (IRR 0.64 [95% confidence interval 0.33–1.26]; 0.94 [0.50–1.78]; 0.82 [0.17–3.98]) and 14–27 days (0.73 [0.35–1.52]; 0.95 [0.49–1.84]; 0.60 [0.06–5.76]) after the first, second and third doses of BNT162b2. No increased risks were observed for CoronaVac during the 0–13 days (IRR 0.60 [0.41–0.88]; 0.71 [0.45–1.12]; 1.64 [0.40–6.77]) and 14–27 days (0.91 [0.63–1.32]; 0.79 [0.46–1.35]; 1.71 [0.44–6.62]) after the first, second and third doses. We also found no increased risk of MACE or all hospitalization after vaccination. INTERPRETATION: Our results showed no increased risk of hospitalization for HF, MACE or all hospitalization after receiving BNT162b2 or CoronaVac vaccines in patients with HF. FUNDING: The project was funded by a Research Grant from the Food and Health Bureau, The Government of the Hong Kong Special Administrative Region (Ref. No. COVID19F01). F.T.T.L. (Francisco T.T. Lai) and I.C.K.W. (Ian C.K. Wong)'s posts were partly funded by the D24H; hence this work was partly supported by AIR@InnoHK administered by Innovation and Technology Commission

BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition

We summarize the results of a host of efforts using giant automatic speech recognition (ASR) models pre-trained using large, diverse unlabeled datasets containing approximately a million hours of audio. We find that the combination of pre-training, self-training and scaling up model size greatly increases data efficiency, even for extremely large tasks with tens of thousands of hours of labeled data. In particular, on an ASR task with 34k hours of labeled data, by fine-tuning an 8 billion parameter pre-trained Conformer model we can match state-of-the-art (SoTA) performance with only 3% of the training data and significantly improve SoTA with the full training set. We also report on the universal benefits gained from using big pre-trained and self-trained models for a large set of downstream tasks that cover a wide range of speech domains and span multiple orders of magnitudes of dataset sizes, including obtaining SoTA performance on many public benchmarks. In addition, we utilize the learned representation of pre-trained networks to achieve SoTA results on non-ASR tasks.Comment: 14 pages, 7 figures, 13 tables; v2: minor corrections, reference baselines and bibliography updated; v3: corrections based on reviewer feedback, bibliography update