Study on a New Technique of On-line Monitoring of Oil Contamination Level Using Computer Vision Technology

In this paper, a new technique of capturing the images of debris inlubrication or hydraulic oil using micro-imaging and computer vision techniques is introduced. Byway of image processing, the size and distribution of debris are obtained, and then the oilcontamination level is also obtained. Because the information of oil contamination is obtaineddirectly from the images of debris by this method, the monitoring result is more intuitive andreliable.

Q-Learning-Based Pesticide Contamination Prediction in Vegetables and Fruits

Pesticides have become more necessary in modern agricultural production.However,these pesticides have an unforeseeable long-term impact on people's wellbeing as well as the ecosystem.Due to a shortage of basic pesticide exposure awareness,farmers typically utilize pesticides extremely close to harvesting.Pesticide residues within foods,particularly fruits as well as veggies,are a significant issue among farmers,merchants,and particularly consumers.The residual concentrations were far lower than these maximal allowable limits,with only a few surpassing the restrictions for such pesticides in food.There is an obligation to provide a warning about this amount of pesticide use in farming.Previous technologies failed to forecast the large number of pesticides that were dangerous to people,necessitating the development of improved detection and early warning systems.A novel methodology for verifying the status and evaluating the level of pesticides in regularly consumed veggies as well as fruits has been identified,named as the Hybrid Chronic Multi-Residual Framework(HCMF),in which the harmful level of used pesticide residues has been predicted for contamination in agro products using Q-Learning based Recurrent Neural Network and the predicted contamination levels have been analyzed using Complex Event Processing(CEP)by processing given spatial and sequential data.The analysis results are used to minimize and effectively use pesticides in the agricultural field and also ensure the safety of farmers and consumers.Overall,the technique is carried out in a Python environment,with the results showing that the proposed model has a 98.57%accuracy and a training loss of 0.30.

Spectrochemical Analysis of Bottled and Tap Water from Selected Counties of Middle Tennessee, USA

A total of 37 elements were determined in tap and bottled water samples from six counties of Middle Tennessee (USA) by Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). The overarching goal of the study is to dispel the myth that bottled water is better than tap water or vice versa. Other parameters analyzed were pH, conductivity, and Total Dissolved Solids (TDS). The results were compared with the Maximum Contaminant Limit (MCL) reported by the US Environmental Protection Agency (US-EPA). The concentrations of phosphorus, silicon, fluoride, and chloride conformed to the established values by US-EPA maximum contaminant level corresponding value. The level of Aluminum (Al), Boron (B), Chromium (Cr), Cobalt (Co), Copper (Cu), Iron (Fe), Lithium (Li), Manganese (Mn), Nickel (Ni), Titanium (Ti), Vanadium (V), and Zinc (Zn) conformed to the established values by governmental agencies (USEPA). Heavy metals such as Arsenic (As), Cadmium (Cd), Cobalt (Co), Lead (Pb), Mercury (Hg), and Silver (Ag) were detected in the tap water of the urban (Davidson) and urbanizing (Rutherford and Williamson) counties;suggesting that rural counties had a less heavy metal concentration in their drinking water sources than urban counties (P < 0.05). However, the values were below the Maximum Contaminant Levels (MCLs).

Trace heavy metals and harmful elements in roots and rhizomes of herbs:Screening level analysis and health risk assessment

Objective:Heavy metal and harmful element contamination are frequently reported in Chinese herbal medicines(CHMs),and roots and rhizomes parts showed a higher content than other parts.To investigate the residue level and assess the potential human health risk of heavy metals and harmful elements in roots and rhizomes,720 batches of the sample representing 20 species of herbs from different sources were collected.Methods:The content of Pb,Cd,As,Hg,and Cu in the digests was determined using ICP-MS.The chronic hazard index estimate based on non-cancer hazard quotient(HQ)was applied for potential health risk assessment of Pb,Cd,As,Hg,and Cu via consumption of CHMs.Results:Compared with the Chinese limit standard(Chinese Pharmacopoeia Commission,2020 edition)of Pb,Cd,As,Hg,and Cu in Ginseng Radix et Rhizoma,the exceedance percentage of Pb in total samples was 14.1%,which were generally far higher than Cd,As,Hg,and Cu.Health risk assessment results based on hazard quotient calculating showed that total HQ of Cu,Pb,As,Cd,and Hg in Pulsatillae Radix and Clematidis Radix et Rhizoma exceeded 1,with the value of 1.543 and 1.235.Besides,Arsenic had the highest HQ value(0.957)in Pulsatillae Radix.Conclusion:Consuming raw materials of Pulsatillae Radix and Clematidis Radix et Rhizoma may pose a potential risk and Arsenic residues in Pulsatillae Radix deserved special attention.

Impacts of n-alkane concentration on soil bacterial community structure and alkane monooxygenase genes abundance during bioremediation processes

Petroleum hydrocarbons,mainly consisting of n-alkanes and polycyclic aromatic hydrocarbons(PAHs),are considered as priority pollutants and biohazards in the environment,eventually affecting the ecosystem and human health.Though many previous studies have investigated the change of bacterial community and alkane degraders during the degradation of petroleum hydrocarbons,there is still lack of understanding on the impacts of soil alkane contamination level.In the present study,microcosms with different n-alkane contamination(1%,3%and 5%)were set up and our results indicated a complete alkane degradation after 30 and 50 days in 1%-and 3%-alkane treatments,respectively.In all the treatments,alkanes with medium-chain length(C_(11)-C_(14))were preferentially degraded by soil microbes,followed by C27-alkane in 3%and 5%treatments.Alkane contamination level slightly altered soil bacterial community,and the main change was the presence and abundance of dominant alkane degraders.Thermogemmatisporaceae,Gemmataceae and Thermodesulfovibrionaceae were highly related to the degradation of C_(14)-and C_(27)-alkanes in 5%treatment,but linked to alkanes with medium-chain(C11-C18)in 1%treatment and C21-alkane in 3%treatment,respectively.Additionally,we compared the abundance of three alkane-monooxygenase genes,e.g.,alk_A,alk_P and alk_R.The abundance of alk_R gene was highest in soils,and alk_P gene was more correlated with alkane degradation efficiency,especially in 5%treatment.Our results suggested that alkane contamination level showed non-negligible effects on soil bacterial communities to some extents,and particularly shaped alkane degraders and degrading genes significantly.This study provides a better understanding on the response of alkane degraders and bacterial communities to soil alkane concentrations,which affects their biodegradation process.