Explore the vast range of titles available.

Mung bean (Vigna radiata L.) is an important edible bean in the human diet worldwide. However, its growth, development, and yield may be restricted or limited by insufficient or unbalanced nitrogen (N), phosphorus (P), and potassium (K) fertilization. Despite this, there are few long-term studies of the effects of varying levels of N, P, and K combined fertilizers and the optimal fertilization for improving mung bean yield and quality. This study was conducted to optimize the fertilization strategies for high yield and to improve yield components (pods per plant, seeds per pod, and 100-seed weight) in the Bailv9 mung bean cultivar, 23 treatments were tested in 2013-2015, using a three-factor (N, P, and K fertilizers), five-level quadratic orthogonal rotation combination design. Our studies showed that, the N, P, and K fertilizers significantly influenced the pods per plant and yield, which increased and then decreased with the increasing N, P, and K fertilizers. The 100-seed weight was significantly affected by the N and P fertilization, and it was increased consistently with the increasing N fertilizer, and decreased significantly with the increasing P fertilizer. Whereas, the seeds per pod significantly decreased with the increasing N and K fertilizers, and the P fertilizer had no significant effect on it. The NP interaction had a significant effect on yield and pods per plant at high N levels, while the NK interaction had a significant but opposite effect on yield at low N levels. The optimal fertilization conditions to obtain yield >2,141.69 kg ha-1 were 34.38-42.62 kg ha-1 N, 17.55-21.70 kg ha-1 P2O5, and 53.23-67.29 kg ha-1 K2O. Moreover, the optimal N, P, and K fertilization interval to achieve pods per plant > 23.41 and the optimal N fertilization to achieve a 100-seed weight > 6.58 g intersected with the interval for yield, but the seeds per pod did not. The fertilizer ratio for the maximum yield was N:P2O5:K2O = 1:0.5:1.59. Following three years experimentation, the optimal fertilization measures were validated in 2016-2017, the results indicated that yield increased by 19.6% than that obtained using conventional fertilization. The results of this study provide a theoretical basis and technical guidance for high-yield mung bean cultivation using the optimal fertilization measures.

Sources and mechanisms of nutrient transport in lawn irrigation driven surface runoff are largely unknown. We investigated the transport of nitrogen (N) and phosphorus (P) in lawn irrigation driven surface runoff from a residential neighborhood (28 ha) of 56% impervious and 44% pervious areas. Pervious areas encompassing turfgrass (lawns) in the neighborhood were irrigated with the reclaimed water in common areas during the evening to late night and with the municipal water in homeowner's lawns during the morning. The stormwater outlet pipe draining the residential neighborhood was instrumented with a flow meter and Hach autosampler. Water samples were collected every 1-h and triple composite samples were obtained at 3-h intervals during an intensive sampling period of 1-week. Mean concentrations, over 56 sampling events, of total N (TN) and total P (TP) in surface runoff at the outlet pipe were 10.9±6.34 and 1.3±1.03 mg L-1, respectively. Of TN, the proportion of nitrate-N was 58% and other-N was 42%, whereas of TP, orthophosphate-P was 75% and other-P was 25%. Flow and nutrient (N and P) concentrations were lowest from 6:00 a.m. to noon, which corresponded with the use of municipal water and highest from 6:00 p.m. to midnight, which corresponded with the use of reclaimed water. This data suggests that N and P originating in lawn irrigation driven surface runoff from residential catchments is an important contributor of nutrients in surface waters.

There is increasing evidence that deregulation of metals contributes to a vast range of neurodegenerative diseases including multiple sclerosis (MS). MS is a chronic inflammatory disease of the central nervous system (CNS) manifesting disability and neurological symptoms. The precise origin of MS is unknown, but the disease is characterized by focal inflammatory lesions in the CNS associated with an autoimmune reaction against myelin. The treatment of this disease has mainly been based on the prescription of immunosuppressive and immune-modulating agents. However, the rate of progressive disability and early mortality is still worrisome. Metals may represent new diagnostic and predictive markers of severity and disability as well as innovative candidate drug targets for future therapies. In this review, we describe the recent advances in our understanding on the role of metals in brain disorders of neurodegenerative diseases and MS patients.

The occurrence of hypoxia in coastal oceans is a long-standing and growing problem worldwide and is clearly linked to anthropogenic nutrient inputs. While the need for reducing anthropogenic nutrient loads is generally accepted, it is costly and thus requires scientifically sound nutrient-reduction strategies. Issues under debate include the relative importance of nitrogen (N) and phosphorus (P) as well as the magnitude of the reduction requirements. The largest anthropogenically induced hypoxic area in North American coastal waters (of 15 000 ± 5000 km2) forms every summer in the northern Gulf of Mexico where the Mississippi and Atchafalaya rivers deliver large amounts of freshwater and nutrients to the shelf. A 2001 plan for reducing this hypoxic area by nutrient management in the watershed called for a reduction of N loads. Since then evidence of P limitation during the time of hypoxia formation has arisen, and a dual nutrient-reduction strategy for this system has been endorsed. Here we report the first systematic analysis of the effects of single and dual nutrient load reductions from a spatially explicit physical–biogeochemical model for the northern Gulf of Mexico. The model has been shown previously to skillfully represent the processes important for hypoxic formation. Our analysis of an ensemble of simulations with stepwise reductions in N, P, and N and P loads provides insight into the effects of both nutrients on primary production and hypoxia, and it allows us to estimate what nutrient reductions would be required for single and dual nutrient-reduction strategies to reach the hypoxia target. Our results show that, despite temporary P limitation, N is the ultimate limiting nutrient for primary production in this system. Nevertheless, a reduction in P load would reduce hypoxia because primary production is P limited in the region where density stratification is conducive to hypoxia development, but reductions in N load have a bigger effect. Our simulations show that, at present loads, the system is almost saturated with N, in the sense that the sensitivity of primary production and hypoxia to N load is much lower than it would be at lower N loads. We estimate that reductions of 63±18 % in total N load or 48±21 % in total N and P load are necessary to reach a hypoxic area of 5000 km2, which is consistent with previous estimates from statistical regression models and highly simplified mechanistic models.

Diese Dissertationsschrift beschäftigt sich einerseits mit der Aktivierung von Elementen der Gruppe 15 mittels niedervalenter metallorganischer Vorstufen. Im Fokus steht hierbei die Aktivierung von nanopartikulärem Arsen mit mono- und divalenten Aluminiumverbindungen sowie nicht-klassischen, divalenten Lanthanoidkomplexen zur Darstellung von 4f-Element Polyarseniden. Darüber hinaus wird über die Aktivierung von weißem Phosphor mit verschiedenen Lanthanoid-Vorstufen berichtet, welche zur Darstellung von 4f-Element-Polyphosphiden dient. Ein zweites Themengebiet dieser Dissertation behandelt die Synthese und Charakterisierung von Lanthanoid-Sandwichverbindungen. Dabei wird zum einen die Synthese von Lanthanoid-Koordinationspolymeren auf Basis eines disilylsubstituierten Cyclooctatetraendiid-Liganden beschrieben, zum anderen wird das Cycloheptatrienyl-Trianion als verbrückender Ligand in der Synthese von heteroleptischen Lanthanoid-Multideckerkomplexen eingesetzt. Neben den strukturellen Eigenschaften dieser neuen metallorganischen Verbindungen, wurden diese auf ihr Verhalten als Einzelmolekülmagnet (SMM) sowie auf ihre lumineszente Eigenschaften untersucht.

Excess nutrient pollution contributes to the formation of harmful algal blooms (HABs) that compromise fisheries and recreation and that can directly endanger human and animal health via cyanotoxins. Efforts to quantify the occurrence, drivers, and severity of HABs across large areas is difficult due to the resource intensive nature of field monitoring of lake nutrient and chlorophyll‐a concentrations. To better characterize how nutrients interact with other environmental factors to produce algal blooms in freshwater systems, we used spatially explicit and temporally matched climate, landscape, in‐lake characteristic, and nutrient inventory data sets to predict nutrients and chlorophyll‐a across the conterminous US (CONUS). Using a nested modeling approach, three random forest (RF) models were trained to explain the spatiotemporal variation in total nitrogen (TN), total phosphorus (TP), and chlorophyll‐a concentrations across US EPA's National Lakes Assessment (n = 2,062). Concentrations of TN and TP were the most important predictors and, with other variables, the RF model accounted for 68% of variation in chlorophyll‐a. We then used these RF models to extrapolate lake TN and TP predictions to lakes without nutrient observations and predict chlorophyll‐a for ∼112,000 lakes across the CONUS. Risk for high chlorophyll‐a concentrations is highest in the agriculturally dominated Midwest, but other areas of risk emerge in nutrient pollution hot spots across the country. These catchment and lake‐specific results can help managers identify potential nutrient pollution and chlorophyll‐a hot spots that may fuel blooms, prioritize at‐risk lakes for additional monitoring, and optimize management to protect human health and other environmental end goals. Plain Language Summary When lakes receive large amounts of nutrients from the surrounding landscape due to fertilizer runoff or other sources of nutrient pollution, they can develop algal blooms. Algal blooms are harmful to the lake ecosystem and sometimes produce toxins which are dangerous to humans and animals. To assess this issue, lake chlorophyll‐a, a measure of algal presence, is monitored. This monitoring is limited in reach due to the expense of in‐lake sampling and the limited resolution of satellite technology. However, there is a wealth of climate, nutrient, landscape, and in‐lake characteristic data for the conterminous US (CONUS) which explains much of what contributes to nutrient pollution and algal growth. Here, we use this data in a machine learning model to predict nutrient (total nitrogen and total phosphorus) and chlorophyll‐a concentrations in about 112,000 lakes in the CONUS. We found that high chlorophyll‐a concentrations are more likely in the Midwest where agriculture is prevalent, but other areas with high lake chlorophyll‐a concentrations are present across the CONUS in nutrient pollution hot spots. These predictions of lake nutrient and chlorophyll‐a concentrations can help managers identify areas of concern, prioritize at‐risk lakes for testing, and target management to protect human health and the environment. Key Points Chlorophyll‐a and nutrient concentrations in ∼112,000 lakes were predicted using widely available national data sets and machine learning Nutrients far outweigh other environmental predictors in driving chlorophyll‐a concentrations in lakes With more information about likely chlorophyll‐a concentrations, managers can prioritize lakes at risk for harmful algal bloom production

To develop a new sealant for the expansion joint on concrete pavement, styrene–butadiene–styrene (SBS), polyurethane (PU) and organ silicon (OS) were selected to modify asphalt, respectively, and effects of the three modifiers on thermal stability, main constituents, microstructures and chemical elements of asphalt, and their modification mechanisms were discussed. Results indicate that PU shows the most satisfactory modification effects on thermal stability of asphalt, followed successively by OS and SBS modifiers. Further, the aggregation state change temperatures of SBS- and OS-modified asphalt samples are not obviously altered, but SBS and OS play the comprehensive balance roles in lowering endothermic amount of asphalt. However, some components of asphalt react with PU to reduce the transition of aggregation state, leading to the decrease in endothermic reactions in PU-modified asphalt. Additionally, SBS, PU and OS are dispersed with asphalt matrix, but PU shows the most satisfactory dispersity in asphalt, followed successively by OS and SBS modifiers. Finally, three modifiers form network microstructures to improve mechanical strength and flexibility of asphalt. PU presents a better dispersity in asphalt matrix than other two modifiers. Physical modification is the main mechanism of three modifiers. PU is proposed to use as a modifier for preparing asphalt-based sealing material of expansion joint on concrete pavement.