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River water quality has been significantly impacted by climate change and extreme weather events worldwide. Despite increasing studies on deep learning techniques for river water quality management, understanding which riverine water quality parameters can be well predicted by meteorologically-driven deep learning still requires further investigation. Here we explored the prediction performance of a traditional Recurrent Neural Network, a Long Short-Term Memory network (LSTM), and a Gated Recurrent Unit (GRU) using meteorological conditions as inputs in the Dahei River basin. We found that deep learning models (i.e., LSTM and GRU) demonstrated remarkable effectiveness in predicting multiple water quality parameters at daily scale, including water temperature, dissolved oxygen, electrical conductivity, chemical oxygen demand, ammonia nitrogen, total phosphorous, and total nitrogen, but not turbidity. The GRU model performed best with an average determination coefficient of 0.94. Compared to the daily-average prediction, the GRU model exhibited limited error increment of 10-40 % for most water quality parameters when predicting daily extreme values (i.e., the maximum and minimum). Moreover, deep learning showed superior performance in collective prediction for multiple water quality parameters than individual ones, enabling a more comprehensive understanding of the river water quality dynamics from meteorological data. This study holds the promise of applying meteorologically-driven deep learning techniques for water quality prediction to a broader range of watersheds, particularly in chemically ungauged areas.

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Carotenoids are essential nutrients for humans and animals, and carotenoid coloration represents an important meat quality parameter for many farmed animals. Increasingly, studies have demonstrated that vertebrate carotenoid cleavage oxygenases (CCOs) are essential enzymes in carotenoid metabolism and are therefore potential candidate genes for improving carotenoid deposition. However, our understanding of carotenoid bioavailability and CCOs functions in invertebrates, particularly marine species, is currently quite limited. We previously identified that a CCO homolog, PyBCO-like 1, was the causal gene for carotenoid coloration in the 'Haida golden scallop', a variety of Yesso scallop (Patinopecten yessoensis) characterized by carotenoid enrichment. Here, we found that another CCO-encoding gene named PyBCO2 (ß-carotene oxygenase 2) was widely expressed in P. yessoensis organs/tissues, with the highest expression in striated muscle. Inhibiting BCO2 expression in P. yessoensis through RNA interference led to increased carotenoid (pectenolone and pectenoxanthin) deposition in the striated muscle, and the color of the striated muscle changed from white to light orange. Our results indicate that PyBCO2 might be a candidate gene used for improving carotenoid content in normal Yesso scallops, and also in 'Haida golden scallops'.

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World's highest arsenic (As) contamination is well-documented for the groundwater system of southwestern region (mainly Jashore district) of Bangladesh, where the majority of inhabitants are underprivileged. To mitigate As poisoning in southwestern Bangladesh, numerous steps have been taken so far by the government and non-governmental organizations (NGOs). Among them, digging deep tube wells and As removal by naturally deposited Fe(OH)3 species are being widely practiced in the contaminated areas. However, these actions have been left unmonitored for decades, making people unaware of this naturally occurring deadly poison in their drinking water. Hence, water samples (n = 63, both treated and untreated) and soil samples (n = 4) were collected from different spots in Jashore district to assess the safety level of drinking water and to understand the probable reasons for high As(III) contamination. About 93.7% of samples were found to contain As(III) above 10 µg/L; among them, 38% contained above 50 µg/L. The study shows that current As(III) removal strategies in the study area are ineffective. In this connection, a simple low-cost As(III) removal adsorbent is proposed that can be prepared with very cheap and locally available materials like iron sludge and charcoal. The adsorbent was characterized in terms of SEM, EDX, and XPS. The optimal dosage of the adsorbent was investigated for real-life application concerning several vital water quality parameters. The Fe-C adsorbent exhibited a maximum As(III) removal efficiency of 92% in real groundwater samples. The study will allow policymakers for informed decision-making regarding water body management as well as enable the local people to avail As-safe water in a way that aligns with their economic factors.

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The current study evaluates additive and non-additive genetic variances for egg quality traits in six genotypes generated through pure mating and reciprocal crossing of Fayoumi (FM) with Koekoek (KK) and White Leghorn (WL). For each genotype, measurements were taken on 30 eggs randomly sampled at 32, 36, and 40 weeks of age to evaluate both external and internal egg quality parameters. The results revealed significant differences (P < 0.001) among the genotypes in all external quality traits and most internal quality traits, including yolk weight (YW), albumen weight (AW), and yolk height (YH). The results also showed that variations due to purebred effect (PE), general combining ability (GCA), maternal effect (ME), and specific combining ability (SCA) were significant in most traits, which reflects that both additive and non-additive variances are important for the inheritances of the parameters investigated. In most of the traits, the ME and PE were higher in KK and WL, while GCA was higher in KK and FM. The FM x WL had higher SCA than FM x KK. The results suggest the likelihood of genetic improvement in these genotypes through selection and crossbreeding strategies and/or a combination of the two.

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Major causes of water pollution in the ecosystem are pollutants such as dyes which are noxious. The present study was based on the synthesis of the green nano-biochar composites from cornstalk and green metal oxide resulting in Copper oxide/biochar, Zinc oxide /biochar, Magnesium oxide/biochar, Manganese oxide/biochar, biochar for removal of dyes combined with the constructed wetland (CW). Biochar Augmentation in constructed wetland systems has improved dye removal efficiency to 95% in order of copper oxide/biochar > Magnesium oxide/biochar > Zinc oxide/biochar > Manganese oxide/biochar > biochar > control (without biochar) respectively in wetlands. It has increased the efficiency of pH by maintaining pH 6.9-7.4, while Total Suspended Solids (TSS) removal efficiency and Dissolved oxygen (DO) increased with the hydraulic retention time of about 7 days for 10 weeks. Chemical oxygen demand (COD) and colour removal efficiency increased with the hydraulic retention time of 12 days for 2 months and there was a low removal efficiency for total dissolved solids (TDS) from control (10.11%) to Copper oxide /biochar (64.44%) and Electrical conductivity (EC) from control (8%) to Copper oxide /biochar (68%) with the hydraulic retention time of about 7 days for 10 weeks. Colour and chemical oxygen demand removal kinetics followed second and first-order kinetic. A significant growth in the plants were also observed. These results proposed the use of agricultural waste-based biochar as part of a constructed wetland substratum can provide enhanced removal of textile dyes. That can be reused.

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This study aimed to evaluate the jujube juice treated by four different sterilization treatments as substrates for producing a probiotic beverage fermented by Lactobacillus plantarum (L. plantarum): sterilization by autoclaving (SA at 0.1 MPa,121 °C, and 20 min), pasteurization (PS at 85 °C/30 min), cold plasma sterilization (CPS at 700 W/120 s) and pulsed strong light sterilization (PLS at 1.0 Hz, 600 J, and 10 times), while jujube juice without sterilization treatment used as control (CK). The results showed that the growth ability of L. plantarum in jujube juice was not affected by different sterilization treatments. After SA and PS treatment, the particle size of jujube juice increased by 440.51% and 222.29%, respectively, and the reducing sugar content decreased by 33.83% and 24.51%, respectively. Compared with SA and PS, PLS and CPS were beneficial to improve the stability of jujube juice, and tartaric acid content in jujube juice was significantly increased after CPS treatment. There was no significant difference in sensory and nutritional quality between PLS treated jujube juice and control, and the color of PLS treated jujube juice was significantly better than that of the other three sterilization treatments. The research indicated that PLS treatment could be a prospective sterilization method applied in the processing of fermented jujube juice. Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-022-05358-8.

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Since, chemically complex environments, the aroma has been a difficult task so far. Therefore, in the present communication, an optofluidic Bragg fiber artificial nose for perceiving the temperature-functional molar fraction of an adulterated binary composition of hydrated mono-alcohols is optimized and reported. The task is theoretically predicted over an optofluidic Bragg fiber sensor having geometrical defects by creating an asymmetry in mid of periodic cylindrical Bragg reflectors. In a cylindrical coordinate system, Henkel function (HF) and transfer matrix technique (TMT) are used to simulate a multilayer concentric hollow-core Bragg fiber (HCBF). The variation in refractive index (RI) of the adulterated binary mono-alcohol fuel is connected to the temperature-functional molar concentration, which is again anticipated by making use of several models, including the most suitable Dale-Gladstone, Lorentz-Lorenz, etc. A prominent sensing signal of which has the full width at half maximum (FWHM) equal to 0.1 nm is observed in the examined photonic bandgap (PBG). The signal is responsive to fluctuations in optofluidic core RI in the vicinity of a structural defect layer. The suggested sensor's temperature-dependent maximum sensitivity (due to varied weather circumstances) for ethanol fuel rather than methanol fuel is 1057.32 nm/RIU. Furthermore, the surface plasmon-based static temperature sensor is compared. Due to the smallest FWHM of output signal around 0.1 nm, other sensing performance metrics such as detection accuracy and quality parameters are also enhanced in the proposed sensor device.

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In this study, we empirically developed a robust model (the Root Mean Square Error (RMSE), bias, NSE and RE were 26.63 mg/L, -4.86 mg/L, 0.47 and 16.47%, respectively) for estimating the total suspended solids (TSS) concentrations in lakes and reservoirs (Hereinafter referred to as lakes) across the Eastern Plain Lake (EPL) Zone. The model was based on 700 in-situ TSS samples collected during 2007-2020 and logarithmic transformed red band reflectance of Landsat data. Based on the Google Earth Engine (GEE), the TSS concentrations in 16,804 lakes were mapped from 1984 to 2019. The results demonstrated a decreasing tendency of TSS in 82.2% of the examined lakes (72.5% of the basins) indicating that the pollutants carried by TSS flowing into the lakes were decreasing. Statistically significant variation (p < 0.05) was found in half of these lakes (28.6% of the basins). High TSS level (>100 mg/L) was observed in 0.31% of lakes (1.1% of the basins). The changing rates of TSS in 47.8% of the lakes (52.7% of the basins) ranged between -50 mg/L/yr and 0. We found high and significantly increased relative spatial heterogeneity of TSS in 4.6% and 6.5% of lakes, respectively. Likewise, the environmental factors, i.e., fertilizer usage, domestic wastewater, industrial wastewater, precipitation, wind speed and Normalized Difference Vegetation Index (NDVI) exhibited a significant correlation with interannual TSS in 38, 21, 20, 11, 17 and 15 of the 91 basins, respectively. This analysis indicated that only precipitation and fertilizer usage were significantly (p < 0.05) related to the spatial distribution of TSS. The relative contributions of the six factors to the interannual TSS changes were varied in different basins. Overall, the NDVI (the representation of vegetation cover) had a high mean contribution to the interannual TSS changes with an average contribution of 7.2%, and contributions of fertilizer were varied greatly among the basins (0.01%-68%). Human activities (fertilizer usage, domestic wastewater, industrial wastewater) and natural factors (precipitation, wind speed and NDVI) played relatively important roles to TSS changes in 14 and 15 of the 91 basins, respectively. Beyond the six factors in this study, other unanalyzed factors (such as lake depth and soil texture) also had some impacts on the distribution of TSS in the study area.

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In small-field radiotherapy (RT), a significant challenge is to define the amount of radiation dose absorbed in the patient where the quality of the beam has to be measured with high accuracy. The properties of a proposed new beam quality specifier, namely the dose-area-product ratio at 20 and 10 cm depths in water or DAPR20,10, were studied to yield more information on its feasibility over the conventional quality specifier tissue-phantom ratio or TPR20,10. The DAPR20,10may be measured with a large-area ionization chamber (LAC) instead of small volume chambers or semi-conductors where detector, beam and water phantom positioning and beam perturbations introduce uncertainties. The effects of beam shape, size and energy on the DAPR20,10were studied and it was shown that the DAPR20,10increases with increasing beam energy similarly to TPR20,10but in contrast exhibits a small beam size and shape dependence. The beam profile outside the beam limiting devices has been shown to have a large contribution to the DAPR20,10. There is potential in large area chambers to be used in DAPR measurement and its use in dosimetry of small-beam RT for beam quality measurements.

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Linking environmental and biological data using ecological models can provide crucial knowledge about the effects of water quality parameters on freshwater ecosystems. However, a model can only be as reliable as its input data. Here, the influence of sampling frequency of temporal variable environmental input data on the reliability of model results when linked to biological data was investigated using Threshold Indicator Taxa Analysis (TITAN) and species sensitivity distributions (SSDs). Large-scale biological data from benthic macroinvertebrates and matching water quality data including four metals and four nutrients of up to 559 site-year combinations formed the initial data sets. To compare different sampling frequencies, the initial water quality data sets (n = 12 samples per year, set as reference) were subsampled (n = 10, 8, 6, 4, 2 and 1), annual mean values calculated and used as input data in the models. As expected, subsampling significantly reduced the reliability of the environmental input data across all eight substances. For TITAN, the use of environmental input data with a reduced reliability led to a considerable (1) loss of information because valid taxa were no longer identified, (2) gain of unreliable taxon-specific change points due to false positive taxa, and (3) bias in the change point estimation. In contrast, the reliability of the SSD results appeared to be much less reduced. However, closer examination of the SSD input data indicated that existing effects were masked by poor model performance. The results confirm that the sampling frequency of water quality data significantly influences the reliability of model results when linked with biological data. For studies limited to low sampling frequencies, the discussion provides recommendations on how to deal with low sampling frequencies of temporally variable water quality data when using them in TITAN, in SSDs, and in other ecological models.

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In 2020, a sudden COVID-19 pandemic unprecedentedly weakened anthropogenic activities and as results minified the pollution discharge to aquatic environment. In this study, the impacts of the COVID-19 pandemic on aquatic environment of the southern Jiangsu (SJ) segment of Beijing-Hangzhou Grand Canal (SJ-BHGC) were explored. Fluorescent component similarity and high-performance size exclusion chromatography analyses indicated that the textile printing and dyeing wastewater might be one of the main pollution sources in SJ-BHGC. The water quality parameters and intensities of fluorescent components (WT-C1(20) and WT-C2(20)) decreased to low level due to the collective shutdown of all industries in SJ region during the Spring Festival holiday and the outbreak of the domestic COVID-19 pandemic in China (January 24th to late February, 2020). Then, they presented a gradual upward trend after the domestic epidemic was under control. In mid-March, the outbreak of the international COVID-19 pandemic hit the garment export trade of China and consequently inhibited the production activities of textile printing and dyeing industry (TPDI) in SJ region. After peaking on March 26th, the intensities of WT-C1(20) and WT-C2(20) decreased again with changed intensity ratio until April 12th. During the study period (135 days), correlation analysis revealed that WT-C1 and WT-C2 possessed homology and their fluorescence intensities were highly positively correlated with conductivity and CODMn. With fluorescence fingerprint (FF) technique, this study not only excavated the characteristics and pollution causes of water body in SJ-BHGC, but also provided novel insights into impacts of the COVID-19 pandemic on production activities of TPDI and aquatic environment of SJ-BHGC. The results of this study indicated that FF technique was an effective tool for precise supervision of water environment.

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Unmanned aerial vehicle (UAV) multispectral remote sensing can be used to monitor multiple water quality parameters, such as suspended solids, turbidity, total phosphorus, and chlorophyll. Establishing a stable and accurate water quality parameter inversion model is a prerequisite for this work. The matching pixel-by-pixel (MPP) algorithm is an inversion algorithm for high resolution features of UAV images; however, it is associated with problems of excessive computation and over-fitting. To overcome these problems, the optimize-MPP (OPT-MPP) algorithm is proposed. In this study, Qingshan Lake in Hangzhou City, Zhejiang Province, was used as the research area. Forty-five samples were collected to construct the OPT-MPP algorithm inversion model for two water quality parameters:the suspended sediments concentration (SS) and turbidity (TU). The results showed that the optimal suspended sediment concentration inversion model had a determination coefficient (R2) of 0.7870 and a comprehensive error of 0.1308. The optimal turbidity inversion model had a R2 of 0.8043 and a comprehensive error of 0.1503. Hence, the inversion of the spatial distribution information for water quality parameters in each experimental area of QingShan Lake was realized by using the optimal models of the two established parameters.

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This work was attempted to evaluate the feasibility of a constructed on-line NIR platform coupled with efficient algorithms for rapid and robust quantification of quality parameter in cherry tomato. Specifically, a system was developed based on shortwave NIR spectroscopy for on-line quality inspection of cherry tomatoes. The spectra were recorded in diffuse reflectance mode from 900 to 1700 nm, and the conveyor belt speed was fixed to five samples per second. Three novel methods, namely variable combination population analysis (VCPA), uninformative variable elimination (UVE) and competitive adaptive reweighed sampling algorithm (CARS) were coupled with partial least square (PLS) for selecting optimal dataset, and modeling. The obtained results showed that under the optimal tuning parameters (N = 100, k = 500, ω = 14, σ = 10%), a total of 512 original variables, only 9 variables (1.75%) were extracted by VCPA. Subsequently, VCPA-PLS yielded outstanding performance in predicting soluble solid content in cherry tomatoes, with a higher correlation coefficient (RP = 0.9053), and lower root mean square errors (RMSEP = 0.382) in prediction set. This methodology demonstrated the versatile potential of the proposed installation coupled with VCPA methods for on-line detection of total soluble solids in cherry tomatoes.

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Understanding the complex relationships between land use and stream water quality is critical for water pollution control and watershed management. This study aimed to investigate the relationship between land use types and water quality indicators at multiple spatial scales, namely, the watershed and riparian scales, using the ordinary least squares (OLS) and geographically weighted regression (GWR) models. GWR extended traditional regression models, such as OLS to address the spatial variations among variables. Our results indicated that the water quality indicators were significantly affected by agricultural and forested areas at both scales. We found that extensive agricultural land use had negative effects on water quality indicators, whereas, forested areas had positive effects on these indicators. The results also indicated that the watershed scale is effective for management and regulation of watershed land use, as the predictive power of the models is much greater at the watershed scale. The maps of estimated local parameters and local R2 in GWR models showcased the spatially varying relationships and indicated that the effects of land use on water quality varied over space. The results of this study reinforced the importance of watershed management in the planning, restoration, and management of stream water quality. It is also suggested that planners and managers may need to adopt different strategies, considering watershed characteristics-such as topographic features and meteorological conditions-and the source of pollutants, in managing stream water quality.

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Oxidative stress is believed to be an important cause of sperm damage during freezing. l-Carnitine (LC) may have the potential to improve sperm quality after frozen-thawed process. The present study aimed to investigate the effect of LC supplementation in cryoprotectant media of mouse epididymal sperm on post-thaw sperm quality and expression of apoptosis-related genes. Male BALB/cJ mice spermatozoa were cryopreserved in a cryoprotectant medium containing 2.5 or 5 mM LC. The untreated group was cryopreserved with the cryoprotectant medium only. Six months following cryopreservation, the samples were thawed and sperm quality parameters, chromatin and acrosome integrity, reactive oxygen species (ROS) and glutathione (GSH) levels, mitochondrial activity, and mRNA expression of Bax and Bcl-2 were assessed. The results demonstrated that the concentration of 5 mM LC in cryoprotectant media exhibited higher values for the sperm quality parameters and integrity of chromatin and acrosome in post-thaw spermatozoa than those of the untreated group. Furthermore, sperm ROS levels decreased while GSH and mitochondrial activity levels increased in 5 mM LC group compared to those in the untreated group (P < 0.01). In 5 mM LC-treated group, Bax was down-regulated (P < 0.05) while Bcl-2 was up-regulated (P < 0.001) compared to the untreated group. Collectively, LC supplementation of cryoprotectant medium improved the quality of frozen-thawed mouse epididymal spermatozoa, as showed reduced ROS level and Bax expression as well as increased GSH, mitochondrial activity, and Bcl-2 expression.

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Milk protein concentrates are common ingredients in the dairy industry, with varying processing histories and composition. The objective of this research was to determine the feasibility of using the whey protein nitrogen (WPN) index, a well-established index for skim milk powder and nonfat dry milk, as a quality parameter for milk protein concentrates. The WPN index is a value based on the moisture-adjusted weight of skim milk powder. We hypothesized that WPN, even when standardized based on protein, may change depending on solubilization conditions of milk protein concentrates because of differences in solubilization conditions or processing history. The WPN was measured for model concentrates with different thermal history or reconstitution conditions. The WPN was not affected by an increased concentration of soluble casein in the dispersions nor after solubilization of the powder at 22 or 60°C. All reconstituted samples were standardized for protein. The WPN was also in full accordance with residual native protein measured by chromatography.

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Complete transurethral resection of bladder tumor (TURBT) is the initial procedure of choice for non-muscle-invasive bladder cancer, but its quality is far from optimal in clinical practice. We evaluated the existing body of evidence substantiating current quality control indicators (QCIs) for TURBT. A literature search was performed using PubMed and Embase, and selected articles were reviewed according to their level of evidence. Disease recurrence and progression were used as the primary end points. No hard evidence supports complete resection as a QCI, but rationally, it is the most important indicator for TURBT. A repeat resection is an important QCI in high-risk disease patients, but evidence suggests that it may not be necessary when detrusor muscle is present in the initial resection specimen. The presence of detrusor muscle in the resection specimen is a validated QCI for TURBT. Adjuvant intravesical instillation is a scientifically proven QCI. Bladder perforation is a controversial QCI in the existing literature. No evidence indicates the ideal time frame for the initial TURBT; thus, initial therapy in the first 6 weeks after diagnosis is not a good QCI. Three of the 6 proposed QCIs for TURBT are supported by evidence. Our literature analysis indicated the use of complete resection, repeat resection, the presence of detrusor muscle, and intravesical instillation are QCIs to minimize recurrence and progression, and increase beneficial outcomes.

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Risk of cross-connection is becoming higher due to greater construction of potable-reclaimed water dual distribution systems. Cross-connection events can result in serious health concerns and reduce public confidence in reclaimed water. Thus, reliable, cost-effective and real-time online detection methods for early warning are required. The current study carried out pilot-scale experiments to simulate potable-reclaimed water pipe cross-connection events for different mixing ratios (from 30% to 1%) using machine learning methods based on multiple conventional water quality parameters. The parameters included residual chlorine, pH, turbidity, temperature, conductivity, oxidation-reduction potential and chemical oxygen demand. The results showed that correlated variation occurred among water quality parameters at the time of the cross-connection event. A single parameter-based method can be effective at high mixing ratios, but not at low mixing ratios. The direct supporting vector machine (SVM)-based method managed to overcome this drawback, but coped poorly with abnormal readings of water parameter sensors. In that respect, a Pearson correlation coefficient (PCC)-SVM-based method was developed. It provided not only high detection performance under normal conditions, but also remained reliable when abnormal readings occurred. The detection accuracy and true positive rate of this method was still over 88%, and the false positive rate was below 12%, given a sudden variation of an individual water quality parameter. The receiver operating characteristic curves further confirmed the promising practical applicability of this PCC-SVM-based method for early detection of cross-connection events.

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PURPOSE: The aim of this study was to clarify whether physical activity may be associated with semen quality, considering the different types of sports, their intensity, and the semen parameters studied in the literature. METHODS: Eligible studies included those that evaluated the impact of physical activity in semen parameters in human population. Outcomes evaluated included the following seminal quality parameters: volume, concentration, total sperm count, progressive motility, total motility, total motile sperm count, morphology, and motile sperm concentration. RESULTS: We identified 32 manuscripts that analyzed this effect. Among them, 20 articles examined the role of general physical activity and 17 analyzed this relationship among specific sports. Although most results point to a lack of major effects of physical activity on semen quality, recreational physical activity could have a positive effect on semen concentration or progressive motility. On the contrary, elite physical activity could be detrimental for some semen parameters, such as progressive motility. Regarding specific sports, a negative effect of cycling on semen concentration is suggested. CONCLUSIONS: In conclusion, recreational physical activity seems to be of benefit for men with infertility issues. However, elite physical activity could have a detrimental effect on semen quality, which should be taken into consideration.

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In recent years, the haze incidents have occurred frequently in China. Therefore, more attention should be taken in comprehensively determination and analysis of the extended-ranges of volatile organic compounds (VOCs). Here, up to 99 non-methane VOCs (NMVOCs), including not frequently reported partial halocarbons and oxygenated VOC (OVOC) species, were monitored in atmosphere of Beijing. The mean concentration of total NMVOC (TNMVOC) decreased in the order of winter polluted days (216.05 µg m-3) > summer polluted days (127.01 µg m-3) > summer normal days (95.63 µg m-3) > winter normal days (50.25 µg m-3). The ethane to n-butane, ethylene to 1-butene, BTEX, acetaldehyde, acetone, n-hexanal, dichloromethane, chloroform and 1,2-dichloroethane, were determined to be the main composition in their respective alkane, alkene, aromatic, OVOC and halocarbon classes. The minor propylbenzene, diethylbenzene, ethyltoluene, and trimethylbenzene isomer ratios were within the narrow range of 1.3-3.21. Generally, the most abundant NMVOCs were alkanes in winter but OVOCs in summer. TNMVOC significantly positively correlated with PM10, PM2.5, CO, RH, SO2 (winter), NO2 (winter), but negatively with windspeed, SSD and PRS (winter). The opposite correlation was observed between TNMVOC and O3 in winter and summer. There was no meaningful correlation between TNMVOC and T, PRS (summer), SO2 (summer) and NO2 (summer). 3D surface graphs, built by MATLAB, were drawn to investigate the relationship between PM2.5 and NMVOC taking air quality parameters into account. The PM2.5 concentration increased non-linearly as TNMVOC concentration increased, with various surface graphs. Unlike other air quality parameters, O3 affected the relationship differently between winter and summer. The findings presented herein may provide a new train of thought for occurrence of haze.

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