High dynamic range image compression based on the multi-peak S-shaped tone curve.

Tone mapping methods aim to compress the high dynamic range (HDR) images so that they can be displayed on common devices. The tone curve plays a key role in many tone mapping methods, which can directly adjust the range of the HDR image. The S-shaped tone curves can produce impressive performances due to their flexibility. However, the conventional S-shaped tone curve in tone mapping methods is single and had the problem of excessive compressing of the dense grayscale areas, resulting in the loss of details in this area, and insufficient compressing of the sparse grayscale areas, resulting in low contrast of tone mapped image. This paper proposes a multi-peak S-shaped (MPS) tone curve to address these problems. Specifically, the grayscale interval of the HDR image is divided according to the significant peak and valley distribution of the grayscale histogram, and each interval is tone mapped by an S-shaped tone curve. We further propose an adaptive S-shaped tone curve based on the luminance adaptation mechanism of the human visual system, which can effectively reduce the compression in the dense grayscale areas and increase the compression in the sparse grayscale areas, preserving details while improving the contrast of tone mapped images. Experiments show that our MPS tone curve replaces the single S-shaped tone curve in relevant methods for better performance and outperforms the state-of-the-art tone mapping methods.

Enhancement of the neural response during 40 Hz auditory entrainment in closed-eye state in human prefrontal region.

Gamma-band activity was thought to be related to several high-level cognitive functions, and Gamma ENtrainment Using Sensory stimulation (GENUS, 40 Hz sensory combined visual and auditory stimulation) was found to have positive effects on patients with Alzheimer's dementia. Other studies found, however, that neural responses induced by single 40 Hz auditory stimulation were relatively weak. To address this, we included several new experimental conditions (sounds with sinusoidal or square wave; open-eye and closed-eye state) combined with auditory stimulation with the aim of investigating which of these induces a stronger 40 Hz neural response. We found that when participant´s eyes were closed, sounds with 40 Hz sinusoidal wave induced the strongest 40 Hz neural response in the prefrontal region compared to responses in other conditions. More interestingly, we also found there is a suppression of alpha rhythms with 40 Hz square wave sounds. Our results provide potential new methods when using auditory entrainment, which may result in a better effect in preventing cerebral atrophy and improving cognitive performance. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-022-09834-x.

Oscillatory properties of class C notifiable infectious diseases in China from 2009 to 2021.

Background: Epidemics of infectious diseases have a great negative impact on people's daily life. How it changes over time and what kind of laws it obeys are important questions that researchers are always interested in. Among the characteristics of infectious diseases, the phenomenon of recrudescence is undoubtedly of great concern. Understanding the mechanisms of the outbreak cycle of infectious diseases could be conducive for public health policies to the government. Method: In this study, we collected time-series data for nine class C notifiable infectious diseases from 2009 to 2021 using public datasets from the National Health Commission of China. Oscillatory power of each infectious disease was captured using the method of the power spectrum analysis. Results: We found that all the nine class C diseases have strong oscillations, which could be divided into three categories according to their oscillatory frequencies each year. Then, we calculated the oscillation power and the average number of infected cases of all nine diseases in the first 6 years (2009-2015) and the next 6 years (2015-2021) since the update of the surveillance system. The change of oscillation power is positively correlated to the change in the number of infected cases. Moreover, the diseases that break out in summer are more selective than those in winter. Conclusion: Our results enable us to better understand the oscillation characteristics of class C infectious diseases and provide guidance and suggestions for the government's prevention and control policies.

Changes in Temporal Properties of Notifiable Infectious Disease Epidemics in China During the COVID-19 Pandemic: Population-Based Surveillance Study.

BACKGROUND: COVID-19 was first reported in 2019, and the Chinese government immediately carried out stringent and effective control measures in response to the epidemic. OBJECTIVE: Nonpharmaceutical interventions (NPIs) may have impacted incidences of other infectious diseases as well. Potential explanations underlying this reduction, however, are not clear. Hence, in this study, we aim to study the influence of the COVID-19 prevention policies on other infectious diseases (mainly class B infectious diseases) in China. METHODS: Time series data sets between 2017 and 2021 for 23 notifiable infectious diseases were extracted from public data sets from the National Health Commission of the People's Republic of China. Several indices (peak and trough amplitudes, infection selectivity, preferred time to outbreak, oscillatory strength) of each infectious disease were calculated before and after the COVID-19 outbreak. RESULTS: We found that the prevention and control policies for COVID-19 had a strong, significant reduction effect on outbreaks of other infectious diseases. A clear event-related trough (ERT) was observed after the outbreak of COVID-19 under the strict control policies, and its decreasing amplitude is related to the infection selectivity and preferred outbreak time of the disease before COVID-19. We also calculated the oscillatory strength before and after the COVID-19 outbreak and found that it was significantly stronger before the COVID-19 outbreak and does not correlate with the trough amplitude. CONCLUSIONS: Our results directly demonstrate that prevention policies for COVID-19 have immediate additional benefits for controlling most class B infectious diseases, and several factors (infection selectivity, preferred outbreak time) may have contributed to the reduction in outbreaks. This study may guide the implementation of nonpharmaceutical interventions to control a wider range of infectious diseases.

Investigating the Relationship between Cough Detection and Sampling Frequency for Wearable Devices.

Cough detection can provide an important marker to monitor chronic respiratory conditions. However, manual techniques which require human expertise to count coughs are both expensive and time-consuming. Recent Automatic Cough Detection Algorithms (ACDAs) have shown promise to meet clinical monitoring requirements, but only in recent years they have made their way to non-clinical settings due to the required portability of sensing technologies and the extended duration of data recording. More precisely, these ACDAs operate at high sampling frequencies, which leads to high power consumption and computing requirements, making these difficult to implement on a wearable device. Additionally, reproducibility of their performance is essential. Unfortunately, as the majority of ACDAs were developed using private clinical data, it is difficult to reproduce their results. We, hereby, present an ACDA that meets clinical monitoring requirements and reliably operates at a low sampling frequency. This ACDA is implemented using a convolutional neural network (CNN), and publicly available data. It achieves a sensitivity of 92.7%, a specificity of 92.3%, and an accuracy of 92.5% using a sampling frequency of just 750 Hz. We also show that a low sampling frequency allows us to preserve patients' privacy by obfuscating their speech, and we analyze the trade-off between speech obfuscation for privacy and cough detection accuracy.Clinical relevance-This paper presents a new cough detection technique and preliminary analysis on the trade-off between detection accuracy and obfuscation of speech for privacy. These findings indicate that, using a publicly available dataset, we can sample signals at 750 Hz while still maintaining a sensitivity above 90%, suggested to be sufficient for clinical monitoring [1].

[Virtual screening and molecular simulations of antisense peptides targeting MT1-MMP].

Membrane type-1 matrix metalloproteinase (MT1-MMP or MMP14) plays the pivotal role in tumor development and metastasis, so it is a promising drug target in malignancy. To acquire MT1-MMP specific binding peptides, we first analyzed MMPs sequences to find the divergent and specific sequence of MT1-MMP by bioinformatics approach, then set the specific sequence as the sense peptide target and designed antisense peptide library. Finally, by means of molecular docking, molecular dynamics simulation and in vitro cell assays, we screened the antisense peptide library against MT1-MMP and further studied the obtained specific peptides. Here, we identified the divergent and specific sequence of AYIREGHE (Named MT1-loop) located in MT1-MMP loop by multiple sequence alignment and established the antisense peptides library with capacity of 1 536 sequences. After two rounds of virtual screening, we obtained five antisense peptides with Rerankscores in the top for further screening. They all interacted with MT1-MMP, and docked well at the active site composed of MT1-loop sequence. Analysis of the affinities of these five antisense peptides to other MMPs (MMP1-3, MMP7-13, MMP14 HPX, MMP16) revealed that the peptide FVTFPYIR was more specific to MT1-MMP. Molecular dynamics simulation showed that the peptide FVTFPYIR might affect the stability of MT1-MMP and thus have effects on its activities. Meanwhile, the peptide FVTFPYIR could specifically inhibit the growth of MG63 and MDA-MB-231 tumor cells both of which expressed MT1-MMP. The work provides a new insight and way for the development of antitumor lead peptides targeting MT1-MMP.