Revealing the dual impact of VOCs on recycled rubber workers: Health risk and odor perception.

Volatile organic compounds (VOCs) pose potential hazards to human health and contribute significantly to odor pollution. This study examined VOC emissions from a representative recycled rubber industry, evaluating the occupational health risks for frontline workers in various workshops. Variables such as gender and workshop-specific concentration variations were considered using Monte Carlo simulation methods. Employees in the five production workshops and office areas face noncarcinogenic health risks with hazard indices (HIs) greater than 1, with the rubber compounding phase presenting the highest risk. Acetaldehyde is identified as the primary noncarcinogenic health risk substance, with hazard quotient (HQ) values exceeding 1 in all workshops. Carcinogenic health risks vary by area, with the highest risks found in compounding and refining workshops. Formaldehyde poses the greatest risk in rubber grinding workshops and offices, with cumulative weights exceeding unacceptable levels of M80.58 % and W77.56 % in grinding and M94.98 % and W92.24 % in the office. Male workers face 4-7 % greater noncarcinogenic VOC health risks than females and 5-14 % greater carcinogenic risks from individual VOCs, increasing their susceptibility to health risks caused by VOCs. Additionally, our analysis of odor identification and intensity classification revealed that 53 VOCs are capable of causing odor pollution, with several substances reaching odor levels of 2 or higher. The predominant perceived odors, as reflected in the odor wheel, include categories such as "solvent/aromatic" and "sweet/fruit," with aldehydes being the primary odor-causing substances. In summary, emissions of VOCs from rubber industrial processes not only pose substantial health risks to workers but also contribute significantly to odor pollution. Consequently, enterprises must prioritize optimizing workplace conditions to ensure the occupational health and well-being of their employees.

An improved method for isotopic and quantitative analysis of dissolved organic carbon in natural water samples.

A wet chemical oxidation (WCO) method has been widely used to obtain the dissolved organic carbon (DOC) content and carbon isotope (δ13CDOC) ratios. However, it is sometimes difficult to get high precision results because not enough CO2 was oxidized from the natural water samples with low DOC concentrations. This improvement primarily aims to increase the water sample volume, improve the removal rate of dissolved inorganic carbon (DIC), and minimize the blank DOC from the standard solution. Following the improved procedure, the δ13C ratios of standardized DOC solutions were consistent with their actual values, and their differences were less than 0.2‰. The improved method demonstrated good accuracy and stability when applied to natural water samples with DOC concentrations ≥0.5 mg L-1, with the precisions of DOC concentrations and δ13C ratios were better than 0.07 mg L-1 and 0.1‰, respectively. More importantly, this method saved much pre-treatment time and realized batch processing of water samples to obtain their DOC contents and isotope ratios.

Assessment of the migration characteristics and source-oriented health risks of heavy metals in the soil and groundwater of a legacy contaminated by the chlor-alkali industry in central China.

The chlor-alkali industry (CAI) is crucial for global chemical production; however, its operation has led to widespread heavy metal (HM) contamination at numerous sites, which has not been thoroughly investigated. This study analysed 122 soil and groundwater samples from a typical CAI site in Kaifeng, China. Our aim was to assess the ecological and health risks, identify the sources, and examine the migration characteristics of HMs at this site using Monte Carlo simulation, absolute principal component score-multiple linear regression (APCS-MLR), and the potential environmental risk index (Ei). Our findings revealed that the exceedance rates for Cd, Pb, Hg, and Ni were 71.96%, 45.79%, 49.59%, and 65.42%, respectively. Mercury (Hg) displayed the greatest coefficient of variation across all the soil layers, indicating a significant anthropogenic influence. Cd and Hg were identified as having high and extremely high potential environmental risk levels, respectively. The spatial distributions of the improved Nemerow index (INI), total ecological risk (Ri), and HM content varied considerably, with the most contaminated areas typically associated with the storage of raw and auxiliary materials. Surface aggregation and significant vertical transport were noted for HMs; As and Ni showed substantial accumulation in subsoil layers, severely contaminating the groundwater. Self-organizing maps categorized the samples into two different groups, showing strong positive correlations between Cd, Pb, and Hg. The APCS-MLR model suggested that industrial emissions were the main contributors, accounting for 60.3% of the total HM input. Elevated hazard quotient values for Hg posed significant noncarcinogenic risks, whereas acceptable levels of carcinogenic risk were observed for both adults (96.60%) and children (97.83%). This study significantly enhances historical CAI pollution data and offers valuable insights into ongoing environmental and health challenges.

Assessment of source-oriented health risk associated with the oral ingestion of heavy metals in dust within an iron/steel smelting-affected area of the North China Plain.

Heavy metals (HMs) from iron/steel smelting activities pose notable risks to human health, especially to those living around industrial facilities of North China Plain, the base of China's steel production. In this study, 78 outdoor windowsill dust samples were collected around a large-scale iron/steel smelter with more than 65 years of production history in the western North China Plain. Nine HMs were analysed to comprehensively assess the health risks by integrating Monte Carlo simulation, oral bioaccessibility, and source apportionment. Results showed serious pollution with Cd, Pb, and Zn based on their geo-accumulation index values and concentrations. Four potential sources including industrial sources (49.85%), traffic sources (21.78%), natural sources (20.58%), and coal combustion (7.79%) were quantitatively identified by multivariate statistical analysis. The oral bioaccessibilities of HMs determined by the physiologically based extraction test ranged from 0.02% to 65.16%. Zn, Mn, Cd, and Pb had higher bioaccessibilities than other HMs. After incorporating oral bioavailability adjustments, noncarcinogenic and carcinogenic risks were significantly reduced, especially for adults. The mean hazard index (HI) for children and adults was below the safety threshold (1.0), whereas the mean of the total carcinogenic risk (TCR) based on HM bioaccessibilities in the gastric phase remained above the acceptable level (1.0E-06) (children: 5.20E-06; adults: 1.16E-06). Traffic sources warranted increased concern as it substantially increased TCR. Cd was identified as the priority pollution in iron/steel smelting areas. Assessing source-oriented health risks associated with oral ingestion exposure can guide the management and control of HM contamination within iron/steel smelting-affected areas.

Health risk assessment of heavy metals in road dust from the fourth-tier industrial city in central China based on Monte Carlo simulation and bioaccessibility.

Health risks caused by heavy metal (HM) exposure in road dust has attracted extensive attention, but few studies have focused on the health risks of residents living in small- and medium-sized cities with rapid industrialization and urbanization. Thus, 140 road dust samples were collected across Anyang, a typical fourth-tier industrial city in central China, which were analysed for 10 different HMs (Mn, Zn, Pb, V, Cr, As, Cd, Ni, Cu and Co). Monte Carlo simulation and bioaccessibility were used to quantify the health risks of heavy metals comprehensively in road dust. Results revealed a remarkable accumulation of Mn, Zn, Pb, Cd and Cu. According to the Geo-accumulation index and potential ecological risk index, Cd was priority control pollutant. Moreover, 55.0% of the road dust samples reached heavily polluted level, and 52.86% of the samples were at high ecological risk levels. These results illustrated that HM contamination was serious and universal in the road dust of Anyang. The occurrences of HMs were allocated to traffic emissions, natural sources, industrial activities and agricultural activities with contribution rates of 35.4%, 6.0%, 41.6% and 17.0%, respectively. Except for Zn in the gastric phase, all other HMs had relatively low bioaccessibilities in the gastrointestinal system, usually less than 20%. The bioaccessibilities of most HMs were higher in the gastric phase, except for Cr, Ni and Cu, which remained higher in the intestinal phase. The non-carcinogenic risk and carcinogenic risk were remarkably reduced when considering the HM bioaccessibilities in the gastrointestinal system, especially for adults. The outcomes of this paper are valuable for understanding HM contamination in road dust and highlight the importance of risk assessment for populations living in the fourth- and fifth-tier cities.

Chemical formation and source apportionment of PM2.5 at an urban site at the southern foot of the Taihang mountains.

The region along the Taihang Mountains in the North China Plain (NCP) is characterized by serious fine particle pollution. To clarify the formation mechanism and controlling factors, an observational study was conducted to investigate the physical and chemical properties of the fine particulate matter in Jiaozuo city, China. Mass concentrations of the water-soluble ions (WSIs) in PM2.5 and gaseous pollutant precursors were measured on an hourly basis from December 1, 2017, to February 27, 2018. The positive matrix factorization (PMF) method and the FLEXible PARTicle (FLEXPART) model were employed to identify the sources of PM2.5. The results showed that the average mass concentration of PM2.5 was 111 µg/m3 during the observation period. Among the major WSIs, sulfate, nitrate, and ammonium (SNA) constituted 62% of the total PM2.5 mass, and NO3- ranked the highest with an average contribution of 24.6%. NH4+ was abundant in most cases in Jiaozuo. According to chemical balance analysis, SO42-, NO3-, and Cl- might be present in the form of (NH4)2SO4, NH4NO3, NH4Cl, and KCl. The liquid-phase oxidation of SO2 and NO2 was severe during the haze period. The relative humidity and pH were the key factors influencing SO42- formation. We found that NO3- mainly stemmed from homogeneous gas-phase reactions in the daytime and originated from the hydrolysis of N2O5 in the nighttime, which was inconsistent with previous studies. The PMF model identified five sources of PM2.5: secondary origin (37.8%), vehicular emissions (34.7%), biomass burning (11.5%), coal combustion (9.4%), and crustal dust (6.6%).

Health risk assessment and bioaccessibilities of heavy metals for children in soil and dust from urban parks and schools of Jiaozuo, China.

Urban parks and schools sever as the mainly activity areas for children, but risk assessment posed by heavy metals (HMs) from soil and dust in these area has rarely been investigated. In this study, six urban parks and seven schools in Jiaozuo, China, were taken as research objects to understand the contamination level and bioaccessibility of HMs from soil and dust in urban parks and schools. The results indicated that Zn, Cu, Pb, Cd, As, Ni and Co from soil and dust were above the background values, especially Zn and Cd in dust, and As and Cd in soil. Serious Cd pollution was discovered, and respective Cd concentrations in soil and dust were 17.83 and 7.52 times the background value. Additionally, the average concentration and bioaccessibility of Zn, Mn, Pb, Cd, Cr, Ni and Co in dust were both higher than in soil. High concentration and high bioaccessibility of HMs in dust suggested that HMs contamination were serious and universal in Jiaozuo. The concentrations of most HMs were higher in the gastric phase, except for Cu and Cd which remained higher in the intestinal phase. Both in the gastric phase and intestinal phase, Mn, As and Cd in soil and dust both have high bioaccessibility which all exceed 10%. The carcinogenic and non-carcinogenic risks base on the total HMs for children (soil: 7.93, 1.96E-05; dust: 6.44, 3.58E-05) were greater than those for adults (soil: 6.35E-01, 1.32E-05; dust: 5.06E-01, 2.42E-05), and urban parks and schools posed high potential risk for children. Therefore, assessment the risk posed by HMs contamination of soil and dust in urban parks and schools is vital and urgent for children.

[Application Progress of Three-dimensional Laser Scanning Technology in Medical Surface Mapping].

The booming three-dimensional laser scanning technology can efficiently and effectively get spatial three-dimensional coordinates of the detected object surface and reconstruct the image at high speed,high precision and large capacity of information.Non-radiation,non-contact and the ability of visualization make it increasingly popular in three-dimensional surface medical mapping.This paper reviews the applications and developments of three-dimensional laser scanning technology in medical field,especially in stomatology,plastic surgery and orthopedics.Furthermore,the paper also discusses the application prospects in the future as well as the biomedical engineering problems it would encounter with.

An Adaptive Sensor Data Segments Selection Method for Wearable Health Care Services.

As cloud computing and wearable devices technologies mature, relevant services have grown more and more popular in recent years. The healthcare field is one of the popular services for this technology that adopts wearable devices to sense signals of negative physiological events, and to notify users. The development and implementation of long-term healthcare monitoring that can prevent or quickly respond to the occurrence of disease and accidents present an interesting challenge for computing power and energy limits. This study proposed an adaptive sensor data segments selection method for wearable health care services, and considered the sensing frequency of the various signals from human body, as well as the data transmission among the devices. The healthcare service regulates the sensing frequency of devices by considering the overall cloud computing environment and the sensing variations of wearable health care services. The experimental results show that the proposed service can effectively transmit the sensing data and prolong the overall lifetime of health care services.

The impacts of water-sediment regulation on organic carbon in the Yellow River.

The Yellow River water-sediment regulation (WSR) is a unique hydraulic engineering project that involves the resuspension and rapid discharge of sediment downstream under the influence of density currents. This process leads to short-term high-intensity sediment scouring, which in turn increases the output of organic carbon. The impact of WSR on the biogeochemical cycling of organic carbon in rivers has not been adequately explored. In this study, we applied stable isotope and 3-D fluorescence analyses to investigate the impact of WSR at the Xiaolangdi (XLD) Reservoir on the sources and fluxes of dissolved organic carbon (DOC) and particulate organic carbon (POC) in the Yellow River. The POC and DOC fluxes during WSR (∼51 days) accounted for 95.5 % and 28.3 % of the annual fluxes. According to the Bayesian model used in the study, the fluxes of POC from sediment, terrestrial plants, and sewage increased by 23.2, 13.36, and 56.55 times, respectively, during the WSR period. On the other hand, the flux from various sources of DOC decreased by ∼0.7 times during the WSR process. The three-dimensional fluorescence index (specific UV absorbance [SUVA254], humification index [HIX], biological index [BIX], and fluorescence index [FI]) further reveals that in the WSR process, more DOC comes from sediment and upstream water. This study provides quantitative insights into the effects of WSR on river organic carbon export dynamics and the driving mechanisms behind them. It also has important implications for understanding the impact of anthropogenic disturbance on the global carbon cycle.

Quantitative Effects of Anthropogenic and Natural Factors on Heavy Metals Pollution and Spatial Distribution in Surface Drinking Water Sources in the Upper Huaihe River Basin in China.

The water quality of sources in the Huaihe River Basin significantly affects the lives and health of approximately 16.7% of China's population. Identifying and quantifying pollution sources and risks is essential for effective water resource management. This study utilized Monte Carlo simulations and Geodetector to assess water quality and eutrophication, as well as to evaluate the sources of heavy metals and the associated health risks for both adults and children. The results showed that eutrophication of water sources in Huaihe River was severe, with an overall EI value of 37.92; 67.8% of the water sources were classified as mesotrophic and 32.2% classified as eutrophic. Water quality and eutrophication levels in the southern mountainous regions were better than those in the densely populated northern areas. Adults were found to have a higher carcinogenic risk than children, whereas children faced a higher noncarcinogenic risk than adults. Cr presented the highest carcinogenic risk, affecting more than 99.8% of both adults and children at levels above 1 × 10-6 but not exceeding 1 × 10-4. The noncarcinogenic risk from metals did not surpass a level of 1, except for Pb. As was primarily influenced by agricultural activities and transportation, whereas Cd, Cr, and Pb were mainly affected by industrial activities, particularly in local textile industries such as knitting and clothing manufacturing. The analysis demonstrated that the influence of anthropogenic factors on heavy metal distribution was significantly enhanced by indirect natural factors. For example, the explanatory power of Precipitation and Road Network Density on As was 0.362 and 0.189, respectively, whereas their interaction had an explanatory power as high as 0.673. This study indicates that the geodetector method is effective in elucidating the factors influencing heavy metal distribution in water, thereby providing valuable insights into pollution sources in global drinking water.

[Research progress of methods for brain vigilance improvement].

Vigilance is defined as the ability to maintain attention or alertness over prolonged periods of time. Since Mid-20th century, following the increasing man-machine communication, high level of vigilance has been demanded in many areas including driving safety, medical care and therapy, aerospace and military affairs, etc. Therefore, finding quick methods to improve the level of vigilance has become a key issue in medical study. Based on physical regulation, chemical regulation and physiological regulation, the research progress has been summarized in this paper. We, furthermore, also try to predict the future trend in this academic area and develop some tentative ideas about seeking more effective and convenient ways to improve the level of brain vigilance.

Community characteristics of macroinvertebrates and ecosystem health assessment in Qin River, a main tributary of the Yellow River in China.

To know well the ecosystem health status of Qin River, a main tributary of the Yellow River and the largest river in Jincheng region, macroinvertebrates from 49 sampling sites in the Qin River and its largest tributary, the Dan River, were investigated, and community characteristics were analyzed in the autumn of 2020; a Benthic index of Biotic Integrity (B-IBI) was established based on four metrics by a series of steps. The results showed that a total of 38 species of macroinvertebrates were collected and identified, belonging to 6 orders and 19 families, consisting of 17 Insecta species, 13 Gastropoda species, and 4 Oligochaeta species. Four species in Insecta belonged to EPT (E, Ephemeroptera; P, Plecoptera; T, Trichoptera); 10 species in Insecta belonged to Chironomidae and Tipulidae families. All species in Gastropoda belonged to Basematophora order, and, especially, Bellamya aeruginosa is highly tolerant to nutrients. All species in Oligochaetes belonged to Tubificidae family, which indicates eutrophication and low-dissolved oxygen. The dominant species in the study were Ephemera orientalis, Chironomus riparius Meigen, and Limnodrilus claparedianus. The final B-IBI scores varied from 0.75 to 3.75, with 5 sites in "excellent," 10 sites in "good," 10 sites in "normal" status, 12 sites in "poor" status, 12 sites in "very poor." "Very poor" and "poor" sites were mainly located in the middle reach of the Qin River and upper-middle reach of the Dan River in Jincheng region. B-IBI strongly differentiated the reference sites and impaired sites, suggesting the suitability of the B-IBI in the Qin River basin. Significantly negative correlations between NH4+-N, TN, and B-IBI indicated the B-IBI characterized well the influence of nitrogen pollution.

Characterization and sources of water-soluble inorganic ions during sulfate-driven and nitrate-driven haze on the largest loess accumulation plateau.

With the rapid reduction of anthropogenic SO2 emissions, the critical driver of haze in China has shifted from being dominated by sulfate to alternating sulfate and nitrate. Haze induced by different driver species may differ in the chemical forms of water-soluble inorganic ions (WSIIs). The unique topography and high-emission industrial agglomeration of the Loess Plateau determine its severe local PM2.5 pollution and influence global weather patterns through the outward export of pollutants. PM2.5 samples were conducted in Pingyao, on the eastern Loess Plateau of China, in autumn and winter. The average mass of PM2.5 was 88.82 ± 57.37 µg/m3; sulfate, nitrate, and ammonium were the dominant component. The chemical form of the ion was dominated by (NH4)2SO4, NH4NO3, NaNO3 and KNO3 during the nitrate-driven (ND) haze, while (NH4)2SO4, NH4HSO4, NH4NO3, NaNO3 and KNO3 were predominant species during the sulfate-driven (SD) haze. Heterogeneous oxidation reactions dominated the mechanism of sulfate formation. Primary sulfate emissions or other generation pathways contributed to sulfate formation during the SD haze. The gas-phase homogeneous reaction of NO2 and NH3 dominates the nitrate generation during the ND haze. The heterogeneous reactions also played an essential role during the SD haze. Nitrate aerosol (42.30%) and coal and biomass combustion (23.23%) were the dominant sources of WSIIs during the ND haze. In comparison, nitrate aerosol (31.80%) and sulfate aerosol (25.08%) were considered the primary control direction during the SD haze. The chemical characteristics and sources of aerosols under various types of haze differ significantly, and knowledge gained from this investigation provides insight into the causes of heavy haze.

The Impact of Land Use Structure Change on Utilization Performance in Henan Province, China.

Because of the trends in population growth and rapid industrialization and urbanization, the intensity and structure of land use are undergoing great changes. Henan Province is an important economic province and a major grain producing and energy consumption area, and its land use plays a key role in the sustainable development of the whole of China. This study takes Henan Province as the research object, selects panel statistical data from 2010 to 2020, and discusses the land use structure (LUS) in Henan Province in terms of three aspects: information entropy, analysis of land use dynamic change, and land type conversion matrix. Based on the indicator system "social economy (SE)-ecological environment (EE)-agricultural production (AP)-energy consumption (EC)", a land use performance (LUP) evaluation model was constructed to judge the performance of various land use types in Henan Province. Finally, the relational degree between LUS and LUP was calculated through the grey correlation. The results show that among the eight land use types in the study area since 2010, land used for water and water conservancy facilities increased by 4%. In addition, transport and garden land changed significantly, and was mainly converted from cultivated land (decreased by 6674 km2) and other land. From the perspective of LUP, the increase in ecological environment performance is the most obvious, while agriculture performance is lagging behind; it is worth paying attention to the energy consumption performance, which is decreasing year by year. There is an obvious correlation between LUS and LUP. LUS in Henan Province presents a gradually stable state, and the transformation of land types promotes LUP. Proposing an effective and convenient evaluation method to explore the relationship between LUS and LUP is very beneficial in helping stakeholders to actively focus more on optimizing land resource management and decision making for the coordinated and sustainable development among agricultural, socio-economic, eco-environmental, and energy systems.

Driving forces and relationship between air pollution and economic growth based on EKC hypothesis and STIRPAT model: evidence from Henan Province, China.

The aim of this research is to analyze the main influencing factors and relationship between atmospheric environment and economic society. Using the panel data of 18 cities in Henan Province from 2006 to 2020, this paper employed some advanced econometric estimation included entropy method, extended environmental Kuznets curve (EKC) and STIRPAT model to conduct empirical estimations. The results show that most regions in Henan Province have verified the existence of the EKC hypothesis; and the peak of air pollution level in all cities of Henan Province generally occurred in around 2014. Multiple linear Ridge regression indicated that the positive driving forces of air pollution in most cities in Henan Province are industrial structure and population size; the negative driving forces are urbanization level, technical level and greening degree. Finally, we used the grey GM (1, 1) model to predict the atmospheric environment of Henan Province in 2025, 2030, 2035 and 2040. What should pay close attention to is that air pollution levels in northeastern and central Henan Province will continue to remain high.

Establishing an emission inventory for ammonia, a key driver of haze formation in the southern North China plain during the COVID-19 pandemic.

Despite the significant reduction in atmospheric pollutant levels during the COVID-19 lockdown, the presence of haze in the North China Plain remained a frequent occurrence owing to the enhanced formation of secondary inorganic aerosols under ammonia-rich conditions. Quantifying the increase or decrease in atmospheric ammonia (NH3) emissions is a key step in exploring the causes of the COVID-19 haze. Historic activity levels of anthropogenic NH3 emissions were collected through various yearbooks and studies, an anthropogenic NH3 emission inventory for Henan Province for 2020 was established, and the variations in NH3 emissions from different sources between COVID-19 and non-COVID-19 years were investigated. The validity of the NH3 emission inventory was further evaluated through comparison with previous studies and uncertainty analysis from Monte Carlo simulations. Results showed that the total NH3 emissions gradually increased from north-west to south-east, totalling 751.80 kt in 2020. Compared to the non-COVID-19 year of 2019, the total NH3 emissions were reduced by approximately 4 %, with traffic sources, waste disposal and biomass burning serving as the sources with the top three largest reductions, approximately 33 %, 9.97 % and 6.19 %, respectively. Emissions from humans and fuel combustion slightly increased. Meanwhile, livestock waste emissions decreased by only 3.72 %, and other agricultural emissions experienced insignificant change. Non-agricultural sources were more severely influenced by the COVID-19 lockdown than agricultural sources; nevertheless, agricultural activities contributed 84.35 % of the total NH3 emissions in 2020. These results show that haze treatment should be focused on reducing NH3, particularly controlling agricultural NH3 emissions.

A vision based top-view transformation model for a vehicle parking assistant.

This paper proposes the Top-View Transformation Model for image coordinate transformation, which involves transforming a perspective projection image into its corresponding bird's eye vision. A fitting parameters searching algorithm estimates the parameters that are used to transform the coordinates from the source image. Using this approach, it is not necessary to provide any interior and exterior orientation parameters of the camera. The designed car parking assistant system can be installed at the rear end of the car, providing the driver with a clearer image of the area behind the car. The processing time can be reduced by storing and using the transformation matrix estimated from the first image frame for a sequence of video images. The transformation matrix can be stored as the Matrix Mapping Table, and loaded into the embedded platform to perform the transformation. Experimental results show that the proposed approaches can provide a clearer and more accurate bird's eye view to the vehicle driver.

Road sign recognition with fuzzy adaptive pre-processing models.

A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance.

[The research progress in brain vigilance detection].

Vigilance is the body level of awareness for objective things. It has been used in security, medical and other fields since people used it as an objective indicator. Therefore automatical vigilance detection has become a major issue needed to be resolved as soon as possible. The methods of vigilance detection at home and abroad in recent years was analyzed in this paper, which will benefit the research and the people dedicated in vigilance detection.