Design and Coverage Path Planning of a Disinfection Robot

Eliminating pathogen exposure is an important approach to control outbreaks of epidemics such as COVID-19 (coronavirus disease 2019). To deal with pathogenic environments, using disinfection robots is a practicable choice. This research formulates a 3D (three-dimensional) spatial disinfection strategy for a disinfection robot. First, a disinfection robot is designed with an extensible control framework for the integration of additional functions. The robot has eight degrees of freedom that can handle disinfection tasks in complex 3D environments where normal disinfection robots lack the capability to ensure complete disinfection. An ingenious clamping mechanism is designed to increase flexibility and adaptability. Secondly, a new coverage path planning algorithm targeted at the spraying area is used. This algorithm aims to achieve an optimal path via the rotating calipers algorithm after transformation between a 2D (two-dimensional) array and 3D space. Finally, the performance of the designed robot is tested through a series of simulations and experiments in various spaces that humans usually live in. The results demonstrate that the robot can effectively perform disinfection tasks both in computer simulation and in reality.

Comparative study on epidemiological characteristics and public health interventions of COVID-19 among China, South Korea, the United States and France based on the poisson regression model

Objective To analyze the trend of COVID-19 epidemic and to comparatively evaluate effects of economic policies, containment and closure policies and health system policies in China , South Korea, the United States (US) and France. Methods Daily confirmed COVID-19 cases and daily comprehensive policy index, specific indicators in mainland China, South Korea, US and France were collected. Considering the lag effect of policy effects, poisson regression model was established to estimate the daily real-time regeneration (Rt) , and the log-log model with variable coefficient was used to compare the prevention and control effects of policies and measures in different countries. Results Containment and closure policies and health system policies were negatively correlated with Rt, and the cumulative lag effect weakens with the increase of lag time. Economic policies were negatively correlated with Rt only in US and France. The effect of American and French policies on Rt was weaker than that of China and South Korea. Conclusion Containment and closure policies and health system policies have a great effect on reducing Rt and controlling the epidemic, the timely and powerful comprehensive blockade measures at the early stage of the epidemic have better effects than mitigation measures. © 2023, Publication Centre of Anhui Medical University. All rights reserved.

Comparative study on epidemiological characteristics and public health interventions of COVID-19 among China, South Korea, the United States and France based on the poisson regression model.

Objective To analyze the trend of COVID-19 epidemic and to comparatively evaluate effects of economic policies, containment and closure policies and health system policies in China , South Korea, the United States (US) and France. Methods Daily confirmed COVID-19 cases and daily comprehensive policy index, specific indicators in mainland China, South Korea, US and France were collected. Considering the lag effect of policy effects, poisson regression model was established to estimate the daily real-time regeneration (Rt) , and the log-log model with variable coefficient was used to compare the prevention and control effects of policies and measures in different countries. Results Containment and closure policies and health system policies were negatively correlated with Rt, and the cumulative lag effect weakens with the increase of lag time. Economic policies were negatively correlated with Rt only in US and France. The effect of American and French policies on Rt was weaker than that of China and South Korea. Conclusion Containment and closure policies and health system policies have a great effect on reducing Rt and controlling the epidemic, the timely and powerful comprehensive blockade measures at the early stage of the epidemic have better effects than mitigation measures.Copyright © 2023, Publication Centre of Anhui Medical University. All rights reserved.

Supervised and Self-Supervised Pretraining Based Covid-19 Detection Using Acoustic Breathing/Cough/Speech Signals

A rapid-accurate detection method for COVID-19 is rather important for avoiding its pandemic. In this work, we propose a bi-directional long short-term memory (BiLSTM) network based COVID-19 detection method using breath/speech/cough signals. Three kinds of acoustic signals are taken to train the network and individual models for three tasks are built, respectively, whose parameters are averaged to obtain an average model, which is then used as the initialization for the BiLSTM model training of each task. It is shown that such an initialization method can significantly improve the detection performance on three tasks. This is called supervised pre-training based detection. Besides, we utilize an existing pre-trained wav2vec2.0 model and pre-train it using the DiCOVA dataset, which is utilized to extract a high-level representation as the model input to replace conventional mel-frequency cepstral coefficients (MFCC) features. This is called self-supervised pre-training based detection. To reduce the information redundancy contained in the recorded sounds, silent segment removal, amplitude normalization and time-frequency masking are also considered. The proposed detection model is evaluated on the DiCOVA dataset and results show that our method achieves an area under curve (AUC) score of 88.44% on blind test in the fusion track. It is shown that using high-level features together with MFCC features is helpful for diagnosing accuracy.

Mechanism of "Child prevention prescription" of Hunan province in prevention and treatment of COVID-19 based on network pharmacology and molecular docking

To analyze the mechanism of novel coronavirus prevention prescription in Hunan province by using network pharmacology method. Methods TCMSP, Batman-TCM and ETCM were used to retrieve drug composition and target information, and GeneCards, OMIM, DrugBank, TTD and PharmGkb were used to screen disease targets. The visualization network diagram of "drug-active component-target" was constructed by Cytoscape, the protein interaction network was drawn by STRING, the core targets of PPI network were analyzed by CytoNCA, GO function and KEGG pathway were analyzed, and the mechanism of action was predicted. Results A total of 418 active ingredients, 1 715 drug targets, 1 289 disease targets and 266 intersection targets were screened out. Quercetin, luteolin, kaempferol, baicalein, ursolic acid and naringin were identified as the key components, and 6 core targets were obtained: RELA, AKT1, STAT3, JUN, MAPK1 and MAPK3. The results of molecular docking showed that the binding potential and activity of the key active ingredients to the core target were good. Conclusions "Child prevention formula" has the characteristics of multi-target, multi-approach and multi-faceted prevention and treatment, which plays a role in prevention and treatment of COVID-19 among children. Copyright © 2022 Publication Centre of Anhui Medical University. All rights reserved.

RumorDecay: Rumor Dissemination Interruption for Target Recipients in Social Networks

Rumors (i.e., untrue emergence saying of COVID-19 in an area) that rapidly disseminate on the ubiquitous social media easily cause public panics and irrational behaviors (e.g., taking unnecessary medicine) of many very sensitive individuals referred to as target recipients. Thus, rumor controlling or blocking for these target recipients is very critical, which differs from the traditional way of protecting all individuals and remains an open and challenging problem so far. In this work, on the basis that rumors are disseminated from the given sources to target recipients via multiple paths which may be significantly interrupted by deleting a few key links referred to as protectors, we first mathematically define a general target information disseminating (TID) model and do theoretical proofs. Second, based on the TID model, we introduce a random walk algorithm to sample the paths of rumor dissemination for recipients. Third, aiming at deleting a budget-limited set of protectors efficiently in a large number of selected paths to reduce or weaken the negative rumor influences on the target recipients, we propose a heuristical strategy-based rumor influence decay mechanism referred to as RumorDecay (i.e., RumorDecay k hop nearest neighbor method and RumorDecay k hop random walk method in this work) which can locate the optimal protectors quickly and efficiently. Finally, we conduct extensive experiments on many real social networks and the results show that the RumorDecay strategy can significantly weaken the rumor dissemination ability with less time cost.

[A comparison of clinical characteristics between patients with and without"recurrence"RNA positive with COVID-19].

Objective: To analysis the clinical characteristics of"recurrence"RNA positive patients with Coronavirus disease 2019 （COVID-19） and compared with those without"recurrence". Methods: 98 patients with COVID-19 in Wuhan Jinyintan Hospital and designated treatment hospitals in Quanzhou were included in this study from February 2020 to April 2020. There were 55 males and 43 females， aged from15 to 83 years， with a median age of 57.5 years， in which 20 cases were complicated with basic diseases. 15 of these patients had been diagnosed and hospitalized had been found as"recurrence"2019-nCoV RNA positive after discharge while the other 83 cases were all negative. The clinical classification of all patients was common type. Clinical data of the COVID-19 RNA"recurrence"patients were collected， and general situations， symptoms， laboratory examinations and CT images were also observed and analyzed. The patients were divided into 2019-nCoV"recurrent"group and 2019-nCoV"non-recurrent"group. There are 10 males and 5 females in 2019-nCoV"recurrent"group while 45 males and 38 females in"non-recurrent"group （χ²=0.800，P=0.371）. The age of 2019-nCoV"recurrent"group （57±21） was higher than that of"non-recurrent"group（53±17）. 8 of 15 the COVID-19"recurrent"group patients and 12 of 83"non-recurrent"patients have basic diseases. IgG and IgM of 2019-nCoV， IL-6， procalcitonin， ESR， CRP， BNP and other serum biochemical index levels were measured and compared between groups. Results: （1） The proportion of patients with common type of COVID-19 was 15.3% during 2-week medical observation after discharge. （2） All of the 2019-nCoV"recurrent"patients were hospitalized due to COVID-19 RNA positive， when they were quarantined after discharged from hospital. All the patients with mild symptoms which were clarified as common type， including 5 cases of fever， 6 cases of cough， 5 cases of expectoration， and 2 cases of slight shortness of breath. The time of symptoms appeared on （5.73±2.82） days after discharge. （3） The serum procalcitonin of all 2019-nCoV"recurrent"group patients were normal（all<0.05 ng/ml）. The BNP of"recurrent"group （151±171） ng/L， was higher than that of"non-recurrent"group （63±78） ng/L （t = 3.207， P = 0.000）. There was no significant difference in laboratory tests like leukocyte ［（6.17±2.4） and （6.04±2.41）×109/L］， lymphocyte［（1.59±0.52） and （1.32±0.64）×109/L］， CRP ［（12.54±28.20） and （21.74±25.63）mg/L］， ESR ［（31.07±28.72） and （34.10±22.16）mm/1 h］， AST ［（24.73±9.15） and （30.24±23.20）U/L］， ALT ［（22.60±12.82） and （36.47±34.12）U/L）， LDH ［（268±208） and （270±164）U/L］， D-dimer ［（0.60±0.50） and （0.84±0.98）µg/L］， ferritin ［（294±195） and （395±319）µg/L］， IL-6 ［（9.17±6.42） and （14.28±17.74）ng/Lï¼½ and BUN （5.77±2.66） and （4.74±2.81）U/Lï¼½ between"recurrent"and"non-recurrent"groups （all P>0.05）. （4） In"recurrent"group， ground glass， exudative or solid lesions could be found in most of the chest CT performed on re-admission. Meanwhile， fibrosis lesion was relatively rare. （5） There were no secondary transmissions were found to be caused by the 2019-nCoV"recurrent"group patients. Conclusions: Most of the 2019-nCoV patients had underlying diseases and active lesions were still found in CT images， so the possibility of virus replication may still exist. All"recurrent"patients had mild illness which may suggest that they were in recovery stage, and no evidence of transmission is found.