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Flying insects rely mainly upon visual motion to detect and track objects. There has been a lot of research on fly inspired algorithms for object detection, but few have been developed based on visual motion alone. One of the daunting difficulties is that the neural and circuit mechanisms underlying the foreground-background segmentation are still unclear. Our previous modeling study proposed that the lobula held parallel pathways with distinct directional selectivity, each of which could retinotopically discriminate figures moving in its own preferred direction based on relative motion cues. The previous model, however, did not address how the multiple parallel pathways gave the only detection output at their common downstream. Since the preferred directions of the pathways along either horizontal or vertical axis were opposite to each other, the background moving in the opposite direction to an object also activated the corresponding lobula pathway. Indiscriminate or ungated projection from all the pathways to their downstream would mix objects with the moving background, making the previous model fail with non-stationary background. Here, we extend the previous model by proposing that the background motion-dependent gating of individual lobula projections is the key to object detection. Large-field lobula plate tangential cells are hypothesized to perform the gating to realize bioinspired background subtraction. The model is shown to be capable of implementing a robust detection of moving objects in video sequences with either a moving camera that induces translational optic flow or a static camera. The model sheds light on the potential of the concise fly algorithm in real-world applications.

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【Objective】 To analyze the cost and effectiveness of different HIV screening strategies based on multi-center HIV residual risk study, so as to provide reference for blood centers to adopt appropriate HIV testing strategies. 【Methods】 According to the HIV screening and confirmation of blood donors in three blood centers in Anhui Province, the residual risk of different HIV screening strategies was estimated. A decision tree model was established to analyze the cost-effectiveness differences of three different screening strategies under current domestic policies. 【Results】 The residual risk of anti-HIV-1 +2 ELISA, HIV Ag/Ab1+2 ELISA and ELISA+NAT were 1.17×10-6,0.84×10-6 and 0.59×10-6, respectively. According to decision tree model analysis, HIV Ag/Ab1+2 ELISA had a cost-effectiveness advantage over anti-HIV 1+2 ELISA when there was no NAT, but the advantage of HIV Ag/Ab1+2 ELISA disappeared when there was one NAT. The cost of HIV reagents, the cost of HIV treatment and the cost of false positive discarding were sensitive factors of the model. 【Conclusion】 In this area, one anti-HIV 1+2 ELISA combined with one NAT has a cost-effectiveness advantage. Blood centers need to confirm and evaluate the ELISA reagents used before conducting HIV screening. Under the premise of ensuring sensitivity, reagent cost and reagent false positive rate are the key factors.

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Small cell transformation was one mechanism by which EGFR-mutation NSCLC acquired resistance after tyrosine kinase inhibitors (TKIs) treatment. A few reports of small cell transformation occurred in other oncogene-driven lung cancers. We found the first case of transformation of a RET-rearranged lung adenocarcinoma to SCLC after selpercatinib, a novel highly selective RET TKIs. Whole-exome sequencing (WES) was used to explore alteration in gene expression in tumor tissue at initial diagnosis and after transformation into small cell carcinoma. We found that transformed into SCLC tumor tissue had inactivation of RB1 and TP53, with RET fusion was still present. In addition, the APOBEC family of cytidine deaminases appeared amplification. Although RET rearrangement still existed, using another RET TKIs was ineffective, and etoposide plus platinum might be an effective rescue treatment.

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Cuproptosis and associated immune-related genes (IRG) have been implicated in tumorigenesis and tumor progression. However, their effects on lung adenocarcinoma (LUAD) have not been elucidated. Therefore, we investigated the impact of cuproptosis-associated IRGs on the immunotherapy response and prognosis of LUAD using a bioinformatical approach and in vitro experiments analyzing clinical samples. Using the cuproptosis-associated IRG signature, we classified LUAD into two subtypes, cluster 1 and cluster 2, and identified three key cuproptosis-associated IRGs, NRAS, TRAV38-2DV8, and SORT1. These three genes were employed to establish a risk model and nomogram, and to classify the LUAD cohort into low- and high-risk subgroups. Biofunctional annotation revealed that cluster 2, remarkably downregulating epigenetic, stemness, and proliferation pathways activity, had a higher overall survival (OS) and immunoinfiltration abundance compared to cluster 1. Real-time quantitative PCR (RT-qPCR) validated the differential expression of these three genes in both subgroups. scRNA-seq demonstrated elevated expression of NRAS and SORT1 in macrophages. Immunity and oncogenic and stromal activation pathways were dramatically enriched in the low-risk subgroup, and patients in this subgroup responded better to immunotherapy. Our data suggest that the cuproptosis-associated IRG signature can be used to effectively predict the immunotherapy response and prognosis in LUAD. Our work provides enlightenment for immunotherapy response assessment, prognosis prediction, and the development of potential prognostic biomarkers for LUAD patients.

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The adsorption performances of ammonia nitrogen (NH+4-N) in water by unmodified biochar are ineffective. In this study, nano zero-valent iron-modified biochar (nZVI@BC) was prepared to remove NH+4-N from water. The NH+4-N adsorption characteristics of nZVI@BC were investigated through adsorption batch experiments. The composition and structure characteristics of nZVI@BC were analyzed using scanning electron microscopy, energy spectrum analysis, BET-N2 surface area (SSA), X-ray diffraction, and FTIR spectra to explore the main adsorption mechanism of NH+4-N by nZVI@BC. The results showed that the composite synthesized at the iron to biochar mass ratio of 1:30 (nZVI@BC1/30) performed well in NH+4-N adsorption at 298 K. The maximum adsorption amount of nZVI@BC1/30 at 298 K was remarkably increased by 45.96% and reached 16.60 mg·g-1. The pseudo-second-order model and Langmuir model fitted well with the adsorption process of NH+4-N by nZVI@BC1/30. There was competitive adsorption between coexisting cations and NH+4-N, and the sequence of coexisting cations to the adsorption of NH+4-N by nZVI@BC1/30 was Ca2+> Mg2+> K+> Na+. The adsorption mechanism of NH+4-N by nZVI@BC1/30 could be mainly attributed to ion exchange and hydrogen bonding. In conclusion, nano zero-valent iron-modified biochar can improve the adsorption performance of NH+4-N and enhance the application potential of biochar in the field of nitrogen removal from water.

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Quantum teleportation plays a significant role in the field of quantum communication. This paper investigates quantum teleportation through a noisy environment by using GHZ state and non-standard W state as quantum channels. We analyze the efficiency of quantum teleportation by solving analytically a master equation in Lindblad form. Following the quantum teleportation protocol, we obtain the fidelity of quantum teleportation as a function of evolution time. The calculation results show that the teleportation fidelity using non-standard W is higher in comparison to GHZ state at the same evolution time. Moreover, we consider the efficiency of teleportation with weak measurements and reverse quantum measurement under amplitude damping noise. Our analysis suggests that the teleportation fidelity using non-standard W is also more robust to noise than GHZ state in the same conditions. Interestingly, we found that weak measurement and its reverse operation have no positive effect on the efficiency of quantum teleportation by using GHZ and non-standard W state in the amplitude damping noise environment. In addition, we also demonstrate the efficiency of quantum teleportation can be improved by making minor modifications to the protocol.

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Noise exists inherently in realistic quantum systems and affects the evolution of quantum systems. We investigate the dynamics of quantum networks in noisy environments by using the fidelity of the quantum evolved states and the classical percolation theory. We propose an analytical framework that allows us to characterize the stability of quantum networks in terms of quantum noises and network topologies. The calculation results of the framework determine the maximal time that quantum networks with different network topologies can maintain the ability to communicate under noise. We demonstrate the results of the framework through examples of specific graphs under amplitude damping and phase damping noises. We further consider the capacity of the quantum network in a noisy environment according to the proposed framework. The analytical framework helps us better understand the evolution time of a quantum network and provides a reference for designing large quantum networks.

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Objective: To investigate the distribution of blood pressure and analyze the associated factors of blood pressure of the elderly with type 2 diabetes in Jiangsu Province. Methods: The elderly over 60 years old participants with type 2 diabetes in the communities of Huai'an City and Changshu City, Jiangsu Province were selected in this study. They were divided into two groups: taking antihypertensive drugs and not taking antihypertensive drugs. The demographic characteristics, such as age and sex, and relevant factors were collected by questionnaire. The systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured by physical examination. The percentile of SBP and DBP in each age group of men and women were described. The kernel density estimation curve was used to show the blood pressure distribution. The trend of blood pressure with age was fitted by locally weighted regression. The logistic regression model was used to analyze relevant factors of blood pressure. Results: A total of 12 949 participants were included in this study, including 7 775 patients in the antihypertensive drug group and 5 174 patients in the group without antihypertensive drugs. The SBP of participants was concentrated at 140-160 mmHg, and their DBP was concentrated at 75-85 mmHg. There were significant differences in the distribution of blood pressure among the subgroups of body mass index (BMI) and rural areas whether taking antihypertensive drugs and not. For participants aged under 80 years old, the SBP showed an increasing trend with age and the DBP showed a decreasing trend with age. Age, BMI ≥24 kg/m2, fasting blood glucose ≥7.0 mmol/L, living in rural areas and no smoking were influencing factors of the elevated SBP; BMI ≥24 kg/m2, male, living in rural areas, no smoking, drinking alcohol and not receiving drug hypoglycemic treatment were influencing factors of the elevated DBP. Conclusion: The SBP of older diabetic adults in Jiangsu Province is at a high level, and the distribution of blood pressure is significantly different between men and women in taking antihypertensive drugs group. The SBP presents a rising trend and the DBP is decreasing at the age of 60-80 years. The blood pressure level of this population are mainly affected by age, BMI, urban and rural areas, smoking.

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Objective: To investigate the association between long-term fasting blood glucose (FPG) variability and all-cause mortality in patients with type 2 diabetes. Methods: A total of 7 174 type 2 diabetic patients included in National Basic Public Health Service Program in Changshu of Jiangsu Province were recruited as participants. Long-term glucose variability was assessed using standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variability independent of the mean (VIM) across FPG measurements at the more than three visits. Death information were mainly obtained from the death registry system in Jiangsu. Then Cox proportional hazards regression models were used to estimate the associations of four variability indicators and all-cause mortality's hazard ratios (HRs) and their 95%CIs. Results: Among 55 058.50 person-years of the follow-up, the mean follow-up time was 7.67 years, and 898 deaths occurred during the follow-up period. After adjustment, compared with T1 group, the Cox regression model showed that HRs of T3 group in SD, CV, ARV and VIM were 1.24 (95%CI: 1.03-1.49), 1.20 (95%CI: 1.01-1.43), 1.28 (95%CI: 1.07-1.55) and 1.20 (95%CI:1.01-1.41), respectively. HRs of per 1 SD higher SD, CV, ARV and VIM were 1.13 (95%CI: 1.06-1.21), 1.08 (95%CI: 1.01-1.15), 1.05 (95%CI: 1.00-1.12) and 1.09 (95%CI: 1.02-1.16) for all-cause mortality, respectively. In the stratified analysis, age, gender, hypoglycemic agent and insulin uses had no effect on the above associations (all P for interaction >0.05). Conclusion: Long-term FPG glycemic variability was positively associated with the risk of all-cause mortality in type 2 diabetes patients.

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Objective: To analyze the prevalence and the trend of the disease burden of chronic respiratory diseases and relevant risk factors in Jiangsu province from 1990 to 2019 and provide evidence for the prevention and treatment of chronic respiratory diseases. Methods: The data from the 2019 Global Burden of Disease Study (GBD2019) were used to calculate the prevalence rate, mortality rate and disability-adjusted life year (DALY) rate. Software Joinpoint was used to calculate the annual percent change (APC) and average annual percent change (AAPC) of the standardized prevalence rate, standardized mortality rate and standardized DALY rate. The population attributable fractions (PAF) were used to estimate the proportion of chronic respiratory disease caused by different risk factors. Results: In 1990 and 2019, the prevalence rates of chronic respiratory diseases were 4.83% and 5.45%. The mortality rates were 134.91/100 000 and 80.99/100 000 respectively, and the DALY rates were 2 678.52/100 000 and 1 534.31/100 000 respectively. From 1990 to 2019, the age-standardized prevalence rate, mortality rate and DALY rate in Jiangsu showed a significant downward trend (AAPC values were -0.90%, -5.28% and -4.70% respectively, P<0.05). Tobacco use was the leading cause of chronic respiratory diseases, followed by air pollution, occupational exposure, suboptimal temperature and high BMI. Compared with 1990, the proportion of DALYs of chronic respiratory diseases attributable to tobacco use and high BMI increased in 2019. Conclusion: The overall burden of chronic respiratory diseases in Jiangsu shows a downward trend. Prevention and health education should be focused on the population with a smoking history and high BMI. At the same time, environmental management, attention to suboptimal temperature and control of occupational exposure factors should also be adopted as important means to prevent and control chronic respiratory diseases.

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Objective: To analyze the prevalence and the trend of the disease burden of chronic respiratory diseases and relevant risk factors in Jiangsu province from 1990 to 2019 and provide evidence for the prevention and treatment of chronic respiratory diseases. Methods: The data from the 2019 Global Burden of Disease Study (GBD2019) were used to calculate the prevalence rate, mortality rate and disability-adjusted life year (DALY) rate. Software Joinpoint was used to calculate the annual percent change (APC) and average annual percent change (AAPC) of the standardized prevalence rate, standardized mortality rate and standardized DALY rate. The population attributable fractions (PAF) were used to estimate the proportion of chronic respiratory disease caused by different risk factors. Results: In 1990 and 2019, the prevalence rates of chronic respiratory diseases were 4.83% and 5.45%. The mortality rates were 134.91/100 000 and 80.99/100 000 respectively, and the DALY rates were 2 678.52/100 000 and 1 534.31/100 000 respectively. From 1990 to 2019, the age-standardized prevalence rate, mortality rate and DALY rate in Jiangsu showed a significant downward trend (AAPC values were -0.90%, -5.28% and -4.70% respectively, P<0.05). Tobacco use was the leading cause of chronic respiratory diseases, followed by air pollution, occupational exposure, suboptimal temperature and high BMI. Compared with 1990, the proportion of DALYs of chronic respiratory diseases attributable to tobacco use and high BMI increased in 2019. Conclusion: The overall burden of chronic respiratory diseases in Jiangsu shows a downward trend. Prevention and health education should be focused on the population with a smoking history and high BMI. At the same time, environmental management, attention to suboptimal temperature and control of occupational exposure factors should also be adopted as important means to prevent and control chronic respiratory diseases.

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ObjectiveArtificial intelligence （AI） full smear automated diatom detection technology can perform forensic pathology drowning diatom detection more quickly and efficiently than human experts.However， this technique was only used in conjunction with the strong acid digestion method， which has a low extraction rate of diatoms. In this study， we propose to use the more efficient proteinase K tissue digestion method （hereinafter referred to as enzyme digestion method） as a diatom extraction method to investigate the generalization ability and feasibility of this technique in other diatom extraction methods. MethodsLung tissues from 6 drowned cadavers were collected for proteinase K ablation and made into smears， and the smears were digitized using the digital image matrix cutting method and a diatom and background database was established accordingly.The data set was divided into training set， validation set and test set in the ratio of 3：1：1， and the convolutional neural network （CNN） models were trained， internally validated， and externally tested on the basis of ImageNet pre-training. ResultsThe results showed that the accuracy rate of the external test of the best model was 97.65 %， and the area where the model features were extracted was the area where the diatoms were located. The best CNN model in practice had a precision of more than 80 % for diatom detection of drowned corpses. ConclusionIt is shown that the AI automated diatom detection technique based on CNN model and enzymatic digestion method in combination can efficiently identify diatoms and can be used as an auxiliary method for diatom detection in drowning identification.

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Bimetallic catalysts offer unique advantages for improving the hydrogen storage performance of MgH2. Herein, Ni3Fe/BC nanocatalysts were prepared via a simple solid phase reduction method using a low-cost biomass charcoal (BC) material as the carrier. The onset temperature of hydrogen release for the MgH2 + 10 wt% Ni3Fe/BC composite was 184.5 °C, which is 155.5 °C lower than that of pure MgH2. The dehydrogenated composite starts to absorb hydrogen at as low as 30 °C and is able to absorb 5.35 wt% of H2 within 10 min under 3 MPa hydrogen pressure at 150 °C. In comparison to pure MgH2, the apparent activation energies of dehydrogenation and rehydrogenation of MgH2 + 10 wt% Ni3Fe/BC were reduced by 52.89 kJ mol-1 and 23.28 kJ mol-1, respectively. The hydrogen storage capacity of the composite was maintained in 20 de/rehydrogenation cycles, indicating a good cycling stability. X-Ray diffraction (XRD), transmission electron microscopy (TEM), and X-ray energy dispersive spectroscopy (EDS) characterization reveal that the in situ formation of multiphases Mg2Ni and Fe catalysts during the hydrogen uptake and release reaction and the transformation of Mg2Ni/Mg2NiH4 together contribute to the superior hydrogen adsorption and desorption performance of MgH2.

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BACKGROUND: High-quality tea requires leaves of similar size and tenderness. The grade of the fresh leaves determines the quality of the tea. The automated classification of fresh tea leaves improves resource utilization and reduces manual picking costs. The present study proposes a method based on an improved genetic algorithm for identifying fresh tea leaves in high-speed parabolic motion using the phenotypic characteristics of the leaves. During parabolic flight, light is transmitted through the tea leaves, and six types of fresh tea leaves can be quickly identified by a camera. RESULTS: The influence of combinations of morphology, color, and custom corner-point morphological features on the classification results were investigated, and the necessary dimensionality of the model was tested. After feature selection and combination, the classification performance of the Naive Bayes, k-nearest neighbor, and support vector machine algorithms were compared. The recognition time of Naive Bayes was the shortest, whereas the accuracy of support vector machine had the best classification accuracy at approximately 97%. The support vector machine algorithm with only three feature dimensions (equivalent diameter, circularity, and skeleton endpoints) can meet production requirements with an accuracy rate reaching 92.5%. The proposed algorithm was tested by using the Swedish leaf and Flavia data sets, on which it achieved accuracies of 99.57% and 99.44%, respectively, demonstrating the flexibility and efficiency of the recognition scheme detailed in the present study. CONCLUSION: This research provides an efficient tea leaves recognition system that can be applied to production lines to reduce manual picking costs. © 2022 Society of Chemical Industry.

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In this paper, we present a new method for the construction of maximally entangled states in Cd⊗Cd' when d'≥2d. A systematic way of constructing a set of maximally entangled bases (MEBs) in Cd⊗Cd' was established. Both cases when d' is divisible by d and not divisible by d are discussed. We give two examples of maximally entangled bases in C2⊗C4, which are mutually unbiased bases. Finally, we found a new example of an unextendible maximally entangled basis (UMEB) in C2⊗C5.

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In order to promote the rapid development of the meat sheep industry, a three-way crossbred combination experiment was carried out with Australian White, Dorper, and Charollais sheep as terminal male parents and the elite F1 hybrids of Australian White  × â€¯Small-tailed Han (Han), Dorper  × â€¯Han, and Charollais  × â€¯Han as female parents, which was based on the screening of a two-way crossbred combination in meat sheep. The growth performance of six groups of three-way crossbred combinations and Han lambs was measured and analyzed, and the effect of a polymorphism in the CLPG gene on the growth performance of three-way crossbred lambs was also studied. The results showed that under the same rearing conditions, weight at 3 and 6 months of age and average daily gain from birth to 3 months and from 3 to 6 months of age were all the largest for Australian  × â€¯(Charollais  × â€¯Han) crossbred lambs. They were significantly or extremely significant different from the other three-way crossbred combinations and Han lambs ( P < 0.05 , P < 0.01 ). The body height, body length, chest girth, and cannon bone circumference at 3 months of age and body length, chest girth, and cannon bone circumference at 6 months of age were also the largest for Australian  × â€¯(Charollais  × â€¯Han) crossbred lambs. Among them, body length, chest girth, and cannon bone circumference at 3 months of age were significantly different from the other three-way crossbred combinations and Han lambs ( P < 0.05 ), and body length, chest girth, and cannon bone circumference at 6 months of age were significantly or extremely significant different from the other three-way crossbred combinations and Han lambs ( P < 0.05 , P < 0.01 ). The potential genetic effects of the CLPG gene on the growth performance indicators of three-way crossbred lambs showed that a mutation site ( g .232 C   >   T ) of this gene had two genotypes: CC and CT. Among them, the data of body weights and body sizes from CT genotype individuals at birth, 3 months old, and 6 months old were significantly higher than those of CC genotype individuals, and some indicators showed significant or extremely significant differences ( P < 0.05 , P < 0.01 ), suggesting that higher growth performance was observed in individuals with T alleles. To sum up, the crossbred combination of Australian  × â€¯(Charollais  × â€¯Han) could be suggested as the optimal choice. The T allele of the CLPG gene showed potential advantages in the performance of meat production in meat sheep. Based on the current results, we recommend that the offspring of Australian  × â€¯(Charollais  × â€¯Han) with the T allele should be preferentially utilized for meat sheep production.

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Objective:To explore the research trends and hot spots of atrial fibrillation and cognitive impairment.Methods:Research papers and review articles related to atrial fibrillation and cognitive impairment was retrieved from the Web of Science core collection database from inception to November 17, 2021. The bibliometric and visualization analysis on the publishing times,journals and countries,related disciplines and key words was conducted with Excel and VOSviewer software.Results:A total of 1 496 articles were collected,showing a parabolic rise in the number of published articles in recent years. During this period,journal Stroke published more high quality articles in the field than others. The academic areas with the most publications were neurology, cardiovascular research, peripheral vascular disease and geriatrics. "Stroke" and "risk factors" were the keywords with the highest frequency. The research hot spots of atrial fibrillation and cognitive impairment mainly focused on anticoagulant drugs, mechanism research, epidemiology catheter ablation and status quo investigation. Conclusion:Through visualization, the development trend and research hot spots on atrial fibrillation and cognitive dysfunction are displayed intuitively, to provide reference for future studies.

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Diatom test is the main laboratory test method in the diagnosis of drowning in forensic medicine. It plays an important role in differentiating the antemortem drowning from the postmortem drowning and inferring drowning site. Artificial intelligence (AI) automatic diatom test is a technological innovation in forensic drowning diagnosis which is based on morphological characteristics of diatom, the application of AI algorithm to automatic identification and classification of diatom in tissues and organs. This paper discusses the morphological diatom test methods and reviews the research progress of automatic diatom recognition and classification involving AI algorithms. AI deep learning algorithm can assist diatom testing to obtain objective, accurate, and efficient qualitative and quantitative analysis results, which is expected to become a new direction of diatom testing research in the drowning of forensic medicine in the future.

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OBJECTIVES@#To select four algorithms with relatively balanced complexity and accuracy among deep learning image classification algorithms for automatic diatom recognition, and to explore the most suitable classification algorithm for diatom recognition to provide data reference for automatic diatom testing research in forensic medicine.@*METHODS@#The "diatom" and "background" small sample size data set (20 000 images) of digestive fluid smear of corpse lung tissue in water were built to train, validate and test four convolutional neural network (CNN) models, including VGG16, ResNet50, InceptionV3 and Inception-ResNet-V2. The receiver operating characteristic curve (ROC) of subjects and confusion matrixes were drawn, recall rate, precision rate, specificity, accuracy rate and F1 score were calculated, and the performance of each model was systematically evaluated.@*RESULTS@#The InceptionV3 model achieved much better results than the other three models with a balanced recall rate of 89.80%, a precision rate of 92.58%. The VGG16 and Inception-ResNet-V2 had similar diatom recognition performance. Although the performance of diatom recall and precision detection could not be balanced, the recognition ability was acceptable. ResNet50 had the lowest diatom recognition performance, with a recall rate of 55.35%. In terms of feature extraction, the four models all extracted the features of diatom and background and mainly focused on diatom region as the main identification basis.@*CONCLUSIONS@#Including the Inception-dependent model, which has stronger directivity and targeting in feature extraction of diatom. The InceptionV3 achieved the best performance on diatom identification and feature extraction compared to the other three models. The InceptionV3 is more suitable for daily forensic diatom examination.

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