Deep learning based an effective hybrid model for water quality assessment.

Water, which is very important for life and civilizations on Earth, has been a source of life for all living things. However, freshwater resources gradually decrease due to climate change, pollution, and population growth. Water pollution is the quality changes that occur due to various activities of people, change the chemical, biological, and physical properties of water, restrict or prevent its use, and disrupt ecological balances. The water quality criteria determined to keep this pollution under control ensure the safe use of water. Water quality observations have gained more importance today due to intense environmental concerns and water pollution. This situation revealed the necessity of water quality assessment for water source use. In this study, the CNN-LSTM-based hybrid model was proposed to assess water quality. The proposed model was compared with AdaBoost, DT, GNB, kNN, LGBM, RF, and LSTM according to accuracy, precision, recall, F-score, and AUC. The proposed model has 98.81% accuracy, 99.03% precision, 99.65% recall, 99.33% F-score, and 93% AUC. PRACTITIONER POINTS: CNN-LSTM hybrid model was developed to water quality assessment. The proposed model is compared with established techniques like AdaBoost, DT, GNB, kNN, LGBM, RF, and LSTM. The developed model has 98.81% classification accuracy. Experimental results show that the developed model will ensure the use of safe water according to water quality criteria.

Microplastic pollution in two remote rivers of Türkiye.

Microplastic pollution in aquatic ecosystems presents an emerging environmental threat that can have adverse effects on ecology, endanger aquatic species, and result in economic damage. Despite the numerous studies reporting the presence of microplastics in marine environments, research into their presence in freshwater systems or inland waters remains limited. This study aimed to assess the level of microplastic pollution transported by the Munzur and Pülümür Rivers and some small rivers that flow into the Uzunçayir dam lake, which is the confluence of the Munzur and Pülümür Rivers in Türkiye. Samples were collected from 23 stations, with the concentration of microplastics ranging from 0.01 MP/m3 at P-4 station to 28.21 MP/m3 at P-10, a station located near a city. Microplastics comprise four types: fiber, film, fragment, and glitter. The average size of microplastics was 1.46 ± 0.05 mm, with the average size of fibers, films, fragments, and glitter-type microplastics being 1.58 ± 0.07 mm, 1.23 ± 0.10 mm, 1.21 ± 0.11 mm, and 0.78 ± 0.16 mm, respectively. The most frequent polymers were polyethylene (31.8%), polystyrene (21.1%), and polypropylene (10.5%). Despite being considered remote and less populated rivers compared to other river systems in Türkiye, all sampling sites showed varying concentrations of microplastics.

Dopamine release in the nucleus accumbens core signals perceived saliency.

A large body of work has aimed to define the precise information encoded by dopaminergic projections innervating the nucleus accumbens (NAc). Prevailing models are based on reward prediction error (RPE) theory, in which dopamine updates associations between rewards and predictive cues by encoding perceived errors between predictions and outcomes. However, RPE cannot describe multiple phenomena to which dopamine is inextricably linked, such as behavior driven by aversive and neutral stimuli. We combined a series of behavioral tasks with direct, subsecond dopamine monitoring in the NAc of mice, machine learning, computational modeling, and optogenetic manipulations to describe behavior and related dopamine release patterns across multiple contingencies reinforced by differentially valenced outcomes. We show that dopamine release only conforms to RPE predictions in a subset of learning scenarios but fits valence-independent perceived saliency encoding across conditions. Here, we provide an extended, comprehensive framework for accumbal dopamine release in behavioral control.

An Evaluation Research About Effects of Characterized Cadmium Selenide (CdSe) and Lead Selenide (PbSe) Quantum Dots on Brine Shrimp (Artemia salina).

Quantum dots (QDs), such as cadmium selenide (CdSe) and lead selenide (PbSe) exhibit excellent optical, magnetic and chemical properties due to their extremely size (ca. 1-10 nm) and are attractive semiconductor nanomaterials for optical studies and energy storage. In this study, aqueous synthesis of CdSe and PbSe QDs in a size range of 2-10 nm was described. Synthesized QDs were characterized using SEM and TEM, DLS, zeta potential, FTIR, EDX and XRD. Highest accumulation (72.5 ± 5.8 mg L-1) of PbSe QDs occurred at 10 ppm suspensions. In general accumulation increased up to 48 h exposure then fluctuate tended to decline. For CdSe QDs, accumulation tended to decrease for 72 h exposure except that for 5 ppm groups. For the elimination period, in general, the elimination levels of PbSe and CdSe QDs from exposed individuals decreased (p < 0.05) even it has some fluctuate.

Temporal and seasonal variations in phytoplankton community structure in Uzuncayir Dam Lake (Tunceli, Turkey).

Seasonal variations in species composition and growth dynamics of phytoplankton in Uzuncayir Dam Lake (Tunceli, Turkey) were studied in relation to ecological factors by collecting horizontal water and phytoplankton samples for over a year. A total of 46 phytoplankton taxa were recorded, where Bacillariophyta was the most abundant in species number representing 24 taxa. Diatoms were the most conspicuous phytoplankton in terms of abundance as well as occurrence frequency. Charophyta, Chlorophyta, Cyanobacteria, Ochrophyta, Miozoa, and Euglenozoa were the least abundant. However, some Diatoms (Gyrosigma attenuatum, Hippodonta hungarica, Meridion circulare, Nitzschia clausii, Nitzschia frustulum, Pantocsekiella ocellata, Rhoicosphenia abbreviata), Charophytes (Cosmarium granatum, Mougeotiopsis calospora), Cyanobacteria (Leiblenia epiphytica, Planktothrix agardhii); Dinoflagellates (Ceratium hirundinella, Parvodinium africanum, Parvodinium inconspicuum, Peridinium cinctum), and Ochrophyta (Dinobryon pediforme) were also noticeable, with their occurrence in all seasons. Canonical correspondence analysis (CCA) and principal component analysis (PCA) were employed to analyze the relationship between occurrence and abundance of phytoplankton species as well as the ecological factors. The results showed that pH and the concentrations of NH4, NO3, and PO4 influenced seasonal occurrence and abundance of phytoplankton species in the lake. Uzuncayir Dam Lake may be classified as an oligotrophic lake with the mean value of nitrate 2.62 mg L-1 and phosphate 0.23 mg L-1 as supported by the occurrence of various phytoplankton groups. Findings related to pollution indices yielded that Uzuncayir Dam Lake is on the edge of the moderate state of organic pollution.

Assessment of Oxidative Stress on Artemia salina and Daphnia magna After Exposure to Zn and ZnO Nanoparticles.

In this study, the effect of zinc nanoparticles (Zn NPs) and zinc oxide nanoparticles (ZnO NPs) on Artemia salina and Daphnia magna, the primary consumer organisms were investigated. In this sense, investigation of trophic transfer and ecological sustainability potentials among living things, such as fish and crustaceans that are at the top of the food chain were also aimed. Zn NPs in the size of 40-60 nm and 80-100 nm and ZnO NPs (10-30 nm) were administered to A. salina and D. manga (respectively in total 105000 and 14000 individuals) in seven groups (Control, 0.2, 1, 5, 10, 25 ve 50 ppm) with three repetitions for a period of 72 h. Intensive and possible misuse of nanoscale materials is one of the biggest threats to the environment and all living things worldwide. Therefore, the control mechanisms for the use of NPs need to be established.

Assessment of impact of α-Fe2 O3 and γ-Fe2 O3 nanoparticles on phytoplankton species Selenastrum capricornutum and Nannochloropsis oculata.

In this study, the impact of alpha-iron oxide (α-Fe2 O3 , 20-40 nm) and gamma iron oxide (γ-Fe2 O3 , 20-40 nm) nanoparticles (NPs) on phytoplankton species Selenastrum capricornutum and Nannochloropsis oculata was investigated Characterizations of the NPs were systematically carried out by TEM, dynamic light scattering, zeta potential, X-ray diffraction, SEM, and Fourier transformation infrared spectroscopy. Acute toxicity was tested between 0.2 and 50 mg/L for each NP for a period of 72 hours exposure. γ-Fe2 O3 NP inhibited development of N oculata at the rate of 54% in 0.2 mg/L group with a high mortality rate of up to 82%. α-Fe2 O3 NPs were less toxic that induced 97% mortality on N oculata at 10 mg/L suspensions. In contrast, α-Fe2 O3 NP inhibited growth of S capricornutum strongly (73%) in 0.2 mg/L group. γ-Fe2 O3 NPs showed similar growth inhibition (72%) on S capricornutum in 10 mg/L suspensions. Despite the differential effects, the results indicated acute toxicity of α-Fe2 O3 and γ-Fe2 O3 NPs on N oculata and S capricornutum.

Effects of Zn and ZnO Nanoparticles on Artemia salina and Daphnia magna Organisms: Toxicity, Accumulation and Elimination.

In the study, Zn in the size of 40-60 nm and 80-100 nm and ZnO in the size of 10-30 nm were applied to A. salina and D. magna individuals in 7 groups with 3 repetitions. Measurements were made at 24th, 48th and 72nd hours and elimination values were examined at +24 h. LC50 values of NPs were determined and chemical analysis (metal accumulation and elimination), ion quantities which were given to the environment and the survival rates of organisms were determined after the exposure. According to the results of phase contrast microscopy, it was found that both experimental organisms absorbed the NPs in the medium level. In the toxicity results of D. magna, it can be said that Zn NP (40-60 nm) has a highly toxic effect only at 50 ppm concentration for 48 h and lethal dose can be accepted as of 5 ppm at the end of 72 h. In A. salina individuals, it is clearly seen that there is an increase in mortality in organisms parallel to the dose increase. Although all NPs were applied to organisms in low doses corresponding to environmental values, it was observed that toxic effect was in parallel with the increase in time. It is clearly known that there is the inverse proportion between the size of NPs and the toxic effect. The smaller the size of NPs is, the higher the toxic effect becomes When the results of Zn accumulation and elimination of A. salina and D. magna individuals exposed to the Zn and ZnO NPs were examined; it was found that accumulation and elimination occurred in parallel with the increase in concentration at each application hour and elimination. Intensive and possible misuse of nanoscale materials is one of the biggest threats to the environment and all living things worldwide.

Ecological risk assessment of heavy metals in surface sediments of northern littoral zone of Lake Çildir, Ardahan, Turkey.

In this paper, the heavy metal levels (Cu, Pb, Zn, Ni, Mn, Fe, As, Cd, Cr, Hg), organic carbon, and chlorophyll degradation products were studied to prove their ecological effects in Lake Çildir, where fossil fuels are used as an energy source in the studied area for most of the year, and domestic waste from settlements is discharged directly into the lake. Sediment samples were collected from six sites on the northern shore of Çildir Lake, Turkey in November 2012. Enrichment (EF) and contamination factor (CF) values were determined, and Pollution Load (PLI) and Potential Ecological Risk (PER) indices were calculated. Average concentrations of heavy metals in the sediments were, in descending order, Fe > Mn > Zn > Ni > Cr > Cu > Pb > As > Cd > Hg, respectively. According to mean values, the source of these elements may be considered natural due to lack of enrichment in Cu, Pb, Zn, Ni, and Cr in the sediment samples. Regarding enrichment of As, Cd, Mn, and Hg, the highest EF belongs to Hg. PLI and PER values indicate there are moderate ecological risk in the lake.