Determining OpenEnded HumanComputer Cooperation Techniques Applying a Key points Method

Machine learning techniques have proven to be very useful in environmental and engineering assessments, including water quality studies. This is because they have flexible linear and nonlinear forecasting functions that can efficiently and reliably estimate measurable and continuous variables. The aim of this paper was to classify the water quality and also predict potentially toxic anions (PTAs; e.g., Cl, SO4, HCO3, and NO3) and potentially toxic heavy metals (PTHMs; e.g., Fe, Zn, Ni, Cr, and Pb) in water resources in Ojoto and its surroundings, Nigeria. Q-mode hierarchical clusters (HCs) and artificial neural networks (ANNs) were integrated to achieve the research objectives. Prior to the HCs and ANNs modeling, correlation-, unrotated principal component-, and varimax-rotated factor analyses were performed to flag the level of associations between the input water quality variables. With respect to pH, two water quality cluster groups were identified. However, three and four cluster groups were identified based on the PTAs and PTHMs concentrations, respectively. Four ANN models (two for each group) were used for predicting the PTAs and PTHMs in the waters resources. Using coefficient of determination (R2) and AUC (area under curve) values and direct comparison of parity plots, the performance and accuracy of the ANN models were substantiated. learn more Overall, the results obtained reveal that the proposed ANN models suitably predicted the concentrations of the PTAs and PTHMs. Thus, this paper provides useful information for better monitoring, management, and protection of the water resources. However, more modeling studies are encouraged to validate and/or improve the findings of the current work.Dermaseptins are peptides found in the skin secretions of Phyllomedusinae frogs. These peptides exert a lytic action on various microorganisms and have no considerable hemolytic effect except dermaseptin S4 (DS4) which exhibits a powerful cytotoxic effect. Therefore, we synthesized several analogs of DS4 in an attempt to find molecules with a weak hemolytic effect and significant bioactivities. In this study, we performed the synthesis of truncated peptides by introducing C-terminal and N-terminal amino acid deletions of the native sequence. All peptide analogs, in comparison with parental peptide, were tested firstly on human red blood cells to work out their cytotoxicity, secondly on the multidrug-resistant bacteria by trying to find MICs, and finally on colon cancer tumor cell line SW620 using the MTT test so as to investigate the anti-proliferative effect. Our results showed that, on the one hand, the N terminus of the native peptide was necessary for the antibacterial activity and the anti-proliferative effect of the peptide. On the other hand, the hemolytic activity was more notable in the sequences broken down on the C-terminal side.The scarcity of arsenic and iron-free safe drinking water is an alarming issue in the southern part of the Bengal Basin. The objectives of the present study were to investigate the spatial distribution of manganese (Mn) concentration in the shallow and deep groundwater and its associated health risks for the children and adults of entire southern Bengal Basin. The Mn concentration in the groundwater varied from 0 to 5.4 mg/L with an average value of 0.47 mg/L that exceeded the WHO's and Bangladesh drinking water guideline values of 0.4 and 0.1 mg/L, respectively. Mn concentration in the shallow wells overrode the deep ones. About 23% of the shallow wells and 11% of deep wells exceeded the WHO's safety limit of Mn concentration for human health. The human health risk related to Mn contamination was estimated by computing the average daily dosage (ADD) and hazard quotient (HQ) values for children and adults. The average computed HQ values found 0.108 and 0.099 for children and adults, respectively. The HQ values delimitated that children are posing a higher risk compared to the adults for the shallow wells. Deep wells were found risk-free for both children and adults. The areal coverage of shallow wells with HQ values > 1 was minimal compared to the total study area and covered only a small portion of Patuakhali and Barguna districts. The rest of the site does not pose any health risk due to Mn contamination for children and adults.Spatiotemporal variations of industrial carbon emissions (IE) must be scientifically understood, which will be helpful to formulate reasonable emission reduction strategies. Given that spatial distribution of IE is irrelevant to space agents commonly used (such as population and nighttime light), estimation and spatialization methods for total carbon dioxide (CO2) emissions are not entirely suitable for IE. Therefore, this paper used greenhouse gases observing satellite level 4A product to estimate IE at the city level and used industrial land density to obtain the distribution of IE within the administrative districts. Sectoral emission inventories of 182 cities and a mosaic Asian anthropogenic emission inventory named MIX were used to verify the results. Then, spatiotemporal variation characteristics of China's IE were analyzed from multiple levels. Results showed that (1) the mean relative error of estimation results was 56.11%, among which 62 cities had relative error of less than 30%. Gridded IE in this paper had high consistency with MIX. (2) Cities with high IE experienced rapid growth from 2009 to 2012, followed by slower growth from 2012 to 2017. (3) Centroid of significant cold and hot spots moved to the southeast and northwest, respectively. Most cities with high annual IE growth had relatively low emission efficiency, mainly located in Inner Mongolia and Xinjiang. Aggregation of medium and high IE grids may represent high emission efficiency. Significant differences still exist between cities in IE, and sustainable development strategies should be formulated according to local conditions. Regions with high annual growth or low emission efficiency are the key to achieving IE reduction targets in future.The real-time location of pollution sources is the process of inverting pollution sources based on the dynamic optimization model constructed by the time-varying pollution concentration detected by the water quality sensor. Due to the vast quantities of the water supply networks, the water quality sensors will only be placed on critical nodes, resulting in multiple solutions. However, the increased monitoring data enhances the uniqueness of the solution. Combined with the real-time location of pollution sources, this work proposed a multi-strategy dynamic multi-mode optimization algorithm based on domain knowledge, which could guide the population search and avoid trapped into local optimal. The merging mechanism was used to keep the diversity of the population and prevent sub-population clustering on the same optimal solution. The simulation results showed that the algorithm could effectively solve the real-time location problem of pollution sources in different pipe networks and pollution scenarios.