, 2005). This erosive regime straightens the coast and steers a large southward longshore drift to

the Sulina mouth. If the elongation of the Musura barrier will connect it to the northern protective jetty of the Sulina navigation canal, the fluvial sediment load of the main secondary distributary, the Old Stambul, may be redirected from the shallow infilling lagoon behind the barrier toward the offshore. In such conditions, an eventual depositional merging of the Chilia lobe with the Sulina shipping canal can be envisioned with dramatic consequences for maintaining navigation access at the Sulina mouth. This project benefited funding from various sources including a Romanian doctoral grant for F.F. and a WHOI selleck products Coastal Ocean Institute grant to L.G. We thank colleagues from WHOI (Jeff Donnelly and Andrew Ashton) and University of Bucharest, in particular Emil Vespremeanu and Stefan Constatinescu, for their support and are grateful for discussions with Sam White and Bogdan Murgescu on the cultural and agricultural histories of the Ottoman Empire and the Romanian Principalities. “
“Uniformitarianism as an approach to the interpretation

of geologic evidence for past Earth events and processes has been a fundamental guiding principle in many areas of geoscience (Oldroyd Selleckchem Raf inhibitor and Grapes, 2008) (Table 1). The origins of this approach and its relevance to the history of research in geography and geology are described in detail (Chorley et al., 1984) and critiqued elsewhere (e.g., Shea, 1982), but this approach is derived from Hutton’s Theory of the Earth (1795) which argued that observation

and measurement of present-day Earth surface processes and their products can be used to explain the formation of similar products by similar processes that operated in the past, for through the application of ‘natural laws’. This reasoning means that geology (e.g. stratigraphy) is therefore similar to cosmology, in which observations are made on the outcomes of processes, rather than the processes themselves (Balashov, 1994). Lyell (1830–1833) expanded upon Hutton’s thesis, including statements on the rate and steady-state nature of geologic processes (Camardi, 1999). Gould (1965) classified these components into substantive uniformitarianism (whereby theories of uniform conditions or rates of change (i.e., natural laws) can be tested) and methodological uniformitarianism (whereby these natural laws apply over a range of spatial and temporal scales). Conflation of different components within Lyell’s viewpoint of uniformitarianism, into the single Principle of Uniformitarianism (or Actualism), is a motivation to reject the notion of uniformitarianism in geography and geology (Gould, 1965, Shea, 1982 and Baker, 1999).

A simple calculation on dry basis may also overestimate the retention of these compounds (De Sá and Rodriguez-Amaya, 2004 and Rodriguez-Amaya, 1999). Therefore, besides the results being expressed as μg/g of sample, they were also presented based on the mass of raw food, multiplying the concentration obtained for the sample by the ratio of the food mass after processing and of the food mass prior to processing. Therefore, true Alectinib retention (% TR) was calculated by the equation proposed by Murphy, Criner and Gray (1975) cited by De Sá and Rodriguez-Amaya (2004), as follows: % TR = 100 × (nutrient content per g of processed food × g of food after processing)/(nutrient content per g of raw food × g of food before processing).

The results were submitted to analysis of variance (ANOVA) and to Tukey test for any significant differences

(P ⩽ 0.05). In all the statistical analyses, the ANOVA assumptions, such as independence and normal distribution of the residues and homogeneity of variances, were considered. The composition of carotenoids in the raw samples, in the cooked samples, and in the C. moschata ‘Menina Brasileira’ and C. maxima ‘Exposição’ pumpkin purees were determined by reverse phase HPLC ( Fig. 1). The parameters used for the identification of the peaks are shown in Table 1. As expected, epoxy-carotenoids and hydroxy-carotenoids, such as violaxanthin and lutein, were the first to elute in the reverse ABT-263 order phase column, followed by ζ-carotene, α-carotene, all-trans-β-carotene and cis-β-carotene, respectively. Peak 3 was not identified. Peaks 4 and 5 showed chromatographic data and UV–visible absorption spectra similar to those described for the carotenoids zeaxanthin and α-cryptoxanthin, respectively, as had already been noted in another study involving the same species of pumpkins ( Azevedo-Meleiro & Rodriguez-Amaya, 2007). However, because they are present in low concentrations, it was not possible to obtain isolation by OCC, therefore the spectra were not determined in other solvent systems nor were the necessary

reactions of identification carried out, and thus only one indication of the identity of those carotenoids was considered. Other minor peaks were also O-methylated flavonoid ignored. Typically, one to four carotenoids are predominant in the pumpkin species, with several other compounds detected in low concentrations or traces. The separation, identification, and quantification of these carotenoids were not the aim of this work; they can be better studied with the use of a mass spectrophotometer ( Azevedo-Meleiro & Rodriguez-Amaya, 2004). The concentration of the major carotenoids identified by HPLC in raw C. moschata ‘Menina Brasileira’ and C. maxima ‘Exposição’ pumpkins are shown in Table 2. The purity of the standard used was of 92% for lutein and 98% for α-carotene e all-trans-β-carotene, with coefficient of co-relation of (R2) of the standard curves of 0.9928, 0.9941 and 0.9933, respectively. Fig. 2 and Fig.

The largest differences found were between the two different varieties Catuai and Tipica. There were profound differences in their compositions: at 210 nm, Catuai shows a larger area for the HMW fraction, whereas Tipica shows a larger area at 280 nm. The results at 280 nm are particularly interesting; differences between the degrees of ripeness are visible for both coffee varieties, and clearly lower values were measured for the ripe beans than for the KU-57788 research buy unripe and half-ripe ones ( Fig. 3). The volatile profile of green coffee was investigated by analysing both the headspace of finely ground green coffee as well as of whole green beans. It was found that analysing the headspace above whole green beans

is more reproducible than when doing the same with ground green coffee. It is likely that volatile oxidation products of green coffee beans occurred with different intensities for different ground replicates and some compounds were even absent from certain chromatograms. There was no observable systematic trend to these differences in the ground green samples, such as stabilisation of headspace over a time period or degradation with time, therefore sampling above whole beans was used. This not only simplified the analysis of the sample, but also eliminated a processing step (grinding) that may have introduced some variance

between the replicates (e.g. particle size distributions) Everolimus price and potentially masked small but real differences in the compositions of the different samples. In total, 68 compounds were identified and peak areas were integrated. Three different types of behaviour for peak intensity were identified. (i) No clear trends between the degrees of ripeness, but relatively repeatable data between replicates. E.g. 1-hexanol showed the highest intensity in Tipica for half-ripe, whereas in Catuai the half-ripe beans had the lowest intensity of the three degrees of ripeness – Fig. 4a. (ii) Very different intensities between the two varieties, with possible but small differences dependent on the degree of ripeness. For example, higher intensity for 2,6-dimethyl pyridine was observed in Catuai beans ( Fig. 4b),

while the intensity for 2,3-butanediol was higher in Tipica beans ( Fig. 4c). (iii) Furfural ( Fig 4d) was differentiating between the ripeness levels of Catuai, whereas no differentiation was observed for Tipica. The unripe and Ergoloid half-ripe Catuai samples had higher furfural signals than the corresponding Tipica samples. In contrast, furfural signal was much lower in the ripe Catuai beans than in the ripe Tipica beans. In order to extract differences between samples across the two varieties and three degrees of ripeness, the various datasets were analysed by principal component analysis (PCA). A statistical analysis with PCA of the RP-HPLC data showed very good separation in the degree of ripeness especially along PC2 (24% loadings) for both the Catuai ( Fig. 5a) and the Tipica ( Fig. 5b) samples.

No study sponsor was involved in the work.

We used BioScience Writers LLC, Huston, Texas, USA for language editing. We acknowledge Jan Hagberg, Ph.D., for help with statistical analysis. “
“Over two decades, plant and ecosystem responses to future elevated atmospheric CO2 (eCO2) levels have been examined by experimental manipulation. Such research was tasked with understanding how this global environmental change factor will affect plants and communities and how they influence carbon budgets for the future. Predicting vegetation responses to eCO2 is important because it may directly alter future net primary productivity (NPP) in ecosystems across the globe (Korner, Epigenetic Reader Domain inhibitor 2006), thereby modulating carbon dynamics and the balance of terrestrial carbon. Experimental free air CO2 enrichment (FACE) of semi-natural plant communities was implemented to determine the capacity of terrestrial ecosystems to sequester carbon under future conditions of eCO2. This research demonstrated initially higher rates of photosynthesis (Korner, 2006 and Norby and Zak, 2011), stimulation

ON 1910 of above- and below-ground biomass and increased microbial and soil C (Ainsworth and Long, 2005 and Luo et al., 2006). However, plant communities often acclimate to eCO2 in the long-term and above ground growth rates do not continue to positively respond to CO2 addition (Reddy et al., 2010 and Norby and Zak, 2011). Uncertainty as to the duration of the eCO2 response and its variation globally limits our ability to predict how plant communities will continue to take up additional anthropogenic CO2 in the atmosphere. In an assessment of such research presented herein, we suggest that throughout its experimental history, a collective spatial bias has existed in eCO2

research which is weighted towards temperate biomes (Korner, 2009, Luo et al., 2006 and Luo et al., 2011). eCO2 research has therefore missed important regions with large C sink potentials, including globally significant biomes, such as boreal and tropical forest. With many eCO2 experimental programs now in decline, questions are outstanding regarding the effect of eCO2 on global carbon budgets. Given a geographical bias we observe in experimental locations, we reappraise what has been learnt and consider remaining uncertainties. A disparity exists between the Amine dehydrogenase global distribution of eCO2 experiments and hotspots for NPP, total plant biomass-carbon and soil-carbon. We review how such limitations might affect our capacity to predict atmospheric CO2 uptake for the future and, thereby, constrain the effectiveness of policy decisions relating to the world’s major terrestrial biomes for C uptake and storage. By indicating opportunities for future development in this area we suggest how researchers and policymakers can work together to understand the global impact of eCO2 on plant communities and ecosystem services to complete the FACE of elevated CO2 research.

Again, this interaction was not significantly modulated by the task mapping, F(1, 38) = .51. As in the previous experiments, we checked whether the asymmetry pattern persisted across the entire

block and found a numerical reduction of the asymmetry effect from 145 to 108 ms, that however was not significant, F(1, 38) = 1.81, MSE = 7780.39, p < .15. 4 To conclude, with the present results Selleck Ibrutinib we cannot rule out the presence of associative learning effects between consecutive tasks (e.g., Koch, 2001). Small effects of this kind may have been difficult to detect with our design. However, the results provide little reason to suspect that associative links between tasks play a major role in producing the interruption-specific, cost-asymmetry pattern. Therefore, they strengthen our structural hypothesis, namely that interruptions enforce an updating operation in the AZD5363 mouse course of which interference through LTM traces can enter the selection

process. Different from the preceding experiments, we presented the interruption-task stimuli far from the screen’s center to avoid any kind of bias favoring the central cue after an interruption. The qualitative pattern of effects was very similar to the one obtained in precious experiments. Therefore it is unlikely that the positioning of the interruption task on the screen played a major role in the pattern of costs. One limitation of our results thus far is that we used interruption tasks which themselves were fairly Baricitinib complex and required considerable attentional control. Maybe the pattern of post-interruption costs we had observed can be explained in terms of an after-effect of immediately preceding, high control demands. Therefore, in this experiment, we used a variant of a spatial Stroop task requiring manual key responses as interruption events that allowed us to directly manipulate control demands. Specifically, one group of subjects performed

the interruption task with low-demand instructions, where correct key responses were indicated through the dominant dimension (i.e., arrow directions). The second group of subjects performed the task with high-demand instructions. Here, correct key presses were indicated through arbitrary color-key assignment rules and the arrow direction produced potentially conflicting information. Also, different from the preceding experiments, the interruption events were not just single trials, but followed the same probabilistic “switch” rules as the primary tasks. Specifically, no matter what the current task type, there was a p = .2 probability that the next trial switched to the other task possible in that block. This also allowed us to examine to what degree the pattern of post-interruption costs depended in any critical manner on the number of intervening interruption events/trials. A total of 40 students of the University of Oregon participated in exchange for course credits in this experiment.

Estimates at a national scale can be calculated by summing over all strata (31 strata in the whole of Sweden). The variances of the estimators described by (5), (6) and (7) were estimated by Taylor series expansion (Appendix B). Biomass, stem volume and their changes with time were estimated using different estimators combined with the stock www.selleckchem.com/products/PLX-4032.html change approach (Table 3). BEFs derived using estimates of the standing stocks in 1990 and 2005 were found to be of the same order of magnitude (1.40 and 1.36 ton CO2/m3, respectively)

(Table 3 and Table 5). However, the BEF for the change in stock between 1990 and 2005 was lower (420/402 = 1.05 ton CO2/m3). Estimates of change in biomass stocks between 1990 and 2005 based on BEFs combined with estimates of stem volume were about 30% higher than those based on biomass equations. As expected, the paired sample method resulted in lower estimated sample variances than the independent sample method (Table 4). The BEFs were not constant over time (Table 5). Assuming that separate biomass equations for different tree fractions can allow for these fractions developing in different ways, Table 3 indicates that estimates based on combining BEFs and stem volume overestimate the net change

of living biomass in Sweden. This is probably because BEFs derived using estimates of standing stock do not represent the true relation between change in biomass and change in volume. Even though the true population Nutlin-3a mw is unknown due to sampling effects, this study indicates a large potential bias is introduced when BEFs based on the standing stock are used. This bias may be particularly large in the case of Sweden because the net change is the difference between large values for gross growth and gross harvest (equivalent to 170 vs. 129 M ton CO2 per year). This corresponds to a stem volume growth of about 124 M m3 per year (2006; The Swedish NFI) and a stem volume harvest of about 94 M m3 per year (2006; Swedish Forest Agency, 2009). During the period studied, the average BEF based on the standing stock was estimated to be 1.38 (whole tree ton CO2-equivalents/m3 stem wood), whereas the average

BEF for change in stock was estimated to be 1.15 (data for a few selected years are shown in Table 5). Norway spruce and Scots pine are also diglyceride the dominant species in Finland, and according to the Finnish NFI, the BEFs for these species are 1.48 and 1.28 ton CO2/m3, respectively. Although the estimates based on BEFs derived for change in stock are probably unbiased, they varied substantially over time, which is likely due to a combination of sampling errors and real changes in BEFs over time. Therefore, in the absence of BiEqs, we would neither recommend the use of BEFs derived from stock estimates nor BEFs based on changes in stock. Instead, the use of age-dependent BEFs, or similar models described in Section 1, may help eliminate or reduce the risk of bias.

J Oral Rehabil 2001;28(2):120–4. “
“Due to a submission error, an author’s name was misspelled on the article “Comparison

of Two Techniques for Assessing the Shaping Efficacy of Repeatedly Used Nickel-Titanium Rotary Instruments” (J Endod 2011;37:847–50). The fourth author’s name should be Khalid Al-Hezaimi, BDS, MSc, and his affiliation listed as Eng.A.B. Research Chair for Growth Factors and Bone Regeneration, Division of Periodontics, College of Dentistry, King Saud University, Riyadh, Saudi Arabia. “
“The article “Effect of Canal Length and Curvature on Working Length Alteration with WaveOne Reciprocating Files” by Elio Berutti, Giorgio Chiandussi, Davide Salvatore Paolino, Nicola Scotti, Giuseppe Cantatore, Arnaldo Castellucci and Damiano Pasqualini (J Endod 37[12]:1687–90; Protease Inhibitor Library purchase 2011] should have included this statement in the author information section: “Giuseppe Cantatore, Arnaldo Castellucci, and Elio Berutti declare that they have financial

involvement (patent licensing arrangements) with Dentsply Maillefer with direct financial interest in the materials discussed in this article.” In addition, Dentsply provided some of the instruments used in this study.”" The authors regret this omission. Volasertib in vitro “
“In the Discussion section of the article “Antibiotic Resistance in Primary and Persistent Endodontic Infections” (J Endod 2011;37[10]:1337–44), references were made to work previously performed by Rossi-Fedele et al (references 23 and 24 in the article). The authors wish

to correct the language used to refer to that work in the following manner. The statement, “TetM has been identified in tetracycline-resistance Enterococcus faecalis found in endodontic infections (23, 24)” should be “TetM has been identified in tetracycline-resistance bacteria found in endodontic infections (23, 24).” Also, the statement, “These studies found that 8 of 15 tetracycline-resistance bacteria isolated possessed the tetM gene and were resistant to tetracycline irrigation in an in vitro tooth model” should be “These studies found that tetracycline-resistance bacteria were resistant Thymidylate synthase to tetracycline irrigation in an in vitro tooth model.” The authors regret any confusion in describing the work done in these studies. “
“Herpes Simplex Virus types 1 and 2 (HSV-1; HSV-2) are alpha-herpesviruses with double-stranded DNA packed in an icosahedral capsid and a lipidic envelope formed by various glycoproteins. They replicate by three rounds of transcription, resulting in α (immediate early) proteins that mainly regulate viral replication, such as ICP27; β (early) proteins that synthesize and package DNA, such as UL42; and γ (late) proteins, most of which are virion proteins, like gB and gD. Inhibition of any of the former stages blocks HSV replication and therefore are potential targets for antiviral therapy (Roizman et al., 2007).

Notably, the DNA viruses strongly up-regulate glycolysis including kinases such as pyruvate kinase. It can be hypothesized that phosphorylation of CDV and other ANPs might be selectively activated in this productive or transformed environment compared to more quiescent normal cells. Accordingly, to explain the selectivity of CDV for HPV-positive cells,

Johnson and Gangemi (1999) claimed that CDV could be mTOR inhibitor differentially metabolized in HPV-positive cells and normal keratinocytes. Following 8 and 16 h incubation, CDV was found to predominantly accumulate in the form of CDVp-choline (considered the intracellular depot form of CDV) in human primary keratinocytes (PHKs) while in HPV16-transformed keratinocytes, CDVpp was the most abundant anabolic product with little CDVp-choline having formed. Recently, we reported that following 72 h incubation with CDV, CDVp-choline appeared to be the most abundant metabolite while the monophosphate form was the least abundant one in PHKs as well as in HPV-positive and HPV-negative tumor cells (De Schutter et al., 2013c). Importantly, no significant differences in the levels of the active metabolite CDVpp, CDVp-choline or CDV were observed between PHKs and HPV-positive tumor cells. However, lower CDVp levels were measured in PHKs compared to HPV-positive cells

following 72 h incubation. Notably, lower concentrations of CDV and of all metabolites were observed in the spontaneously transformed keratinocyte cell line HaCaT that lack HPV sequences, compared to either HPV-positive cells or PHKs, suggesting that

HaCaT cells have a different uptake and/or Tau-protein kinase efflux of CDV, rather than differences in drug metabolism. To reveal Tyrosine Kinase Inhibitor high throughput screening the molecular mechanisms underlying the selectivity of CDV for tumor cells, in particular for HPV-positive carcinoma cells, our research team evaluated gene expression changes following CDV treatment of different cell types [including two HPV-positive cervical carcinoma cell lines (SiHa, HPV16+ and HeLa HPV18+), an HPV-immortalized keratinocyte cell line (HaCaT), and PHKs (De Schutter et al., 2013c). In addition, drug incorporation into genomic DNA was analysed in the four cell types. An exhaustive and thorough analysis of the microarray data highlighted distinct responses to CDV exposure in PHKs compared to HPV-positive cervical carcinoma cells, on the one hand, and to HPV-immortalized keratinocytes, on the other hand. Our data indicated that the selectivity of CDV for HPV-transformed cells is based on differences in response to DNA damage, replication rate and CDV incorporation into cellular DNA between immortalized cells and normal cells, rather than on a specific effect of CDV on expression of the viral oncoproteins (De Schutter et al., 2013c). Normal cells possess an arsenal of repair pathways and cell cycle checkpoints to detect and repair DNA damage unlike transformed cells that have a significantly reduced set of DNA repair pathways for survival (Fig. 12A).

1B), therefore, the inhibitory activity of PPD-SF in in vitro models could not have been due to its nonspecific cytotoxicity. Meanwhile, HPLC analysis showed that this fraction (PPD-SF) mostly contained G-Rb1 (33.2%), G-Rc (29.4%), G-Rb2 (31.7%), and G-Rb3 (5.4%) ( Fig. 1C), implying that these specific ginsenosides could contribute to the mediation of the anti-inflammatory activity of PPD-SF. To understand the molecular mechanism of PPD-SF-induced anti-inflammatory activity,

we next examined whether this fraction inhibited the secretion of inflammatory mediators at the transcriptional level. We measured the mRNA levels of iNOS, TNF-α, and cyclo-oxygenase-2 by real-time PCR. Like the upregulation of inflammatory mediators, the mRNA levels of their corresponding genes selleck products were also markedly upregulated by LPS, up to 200–1,400-fold (Fig. 2A), similar to findings that have been reported previously [15]. Similarly, PPD-SF strongly decreased the mRNA levels of the genes in a dose-dependent manner (Fig. 2A). Moreover, the promoter-binding activities of AP-1 and IRF3, but not selleck antibody NF-κB, triggered by PMA (Fig. 2B, 2E) and adaptor molecules (TRIF and MyD88) (Fig. 2C, 2D, 2F) were also dose-dependently inhibited by PPD-SF, indicating that this red ginseng fraction could modulate the transcriptional activation of AP-1 and IRF-3. In agreement

with these results, this fraction suppressed the nuclear translocation of c-Jun and the phosphorylation of

ATF-2 and IRF-3 (Fig. 2G), implying that the nuclear translocation and phosphorylation events of these transcription factors could be targeted by PPD-SF. Considering that red ginseng marc oil was able to block the expression of inflammatory Rho genes in LPS-treated RAW264.7 cells by suppression of NF-κB [33], and that Panax notoginseng saponins were also found to block the NF-κB pathway [34], the pharmacological features of PPD-SF from KRG seem to be distinctive from those of marc oil and P. notoginseng saponins. However, because there is still a possibility that PPD-SF can suppress the activation of NF-κB, we will further evaluate its potential inhibitory activity under LPS-stimulated conditions. Therefore, we further investigated PPD-SF-targeted molecular events regulating the activation and translocation of AP-1 and IRF-3 in LPS-treated RAW264.7 cells. Previously, it has been reported that ERK, p38, and JNK are major proteins involved in the regulation of AP-1 family activation [35]. TBK1 is also regarded as an important upstream enzyme regulating IRF-3 phosphorylation [4]. PPD-SF clearly suppressed the phosphorylation of p38 from 5 minutes to 30 minutes after treatment, and the phosphorylation of JNK at 15–30 minutes after treatment (Fig. 3A), suggesting that these two enzymes could be directly or indirectly inhibited by PPD-SF.

1), draining an area of ∼742,400 km2 which covers semi-arid and semi-humid climatic zones. Its upper reaches (from the headwater to Toudaoguai) drain the northern Qinghai-Tibetan mountains and provide approximately 60% of the river’s water discharge. The middle reaches of the Huanghe (from Toudaoguai to Huayuankou) cross the soil-rich Loess Plateau, where the soils are highly

erodible during rain-storm events. The river gains ∼90% of its sediment load during this journey. As the Huanghe enters its flatter lower basin, however, it loses considerable energy for sediment transport and deposits large amounts of sediment (primarily coarser-grained) on the riverbed. Moreover, the lower reaches have few tributaries, further diminishing water flux and transportation capacity. The heavy sedimentation results in an elevated riverbed several meters (locally > 10 m) learn more above the surrounding floodplain. River discharge of the Huanghe is highly dependent on the monsoon flood season (July–October), which brings about 60% of the annual precipitation for the drainage basin. But water discharge is also affected by short-term climatic oscillations. The lower reaches of the Huanghe experienced

no flow PR 171 or low flow conditions during the 1970s–1990s, which was mainly due to low basin precipitation associated with drought. The sediment load is also sensitive to human-controlled very land use in its source region, the Loess plateau. Since the 1960s, more than 20 large reservoirs have been constructed in the Huanghe and its tributaries to meet demands for water. In particular, four large dams (Longyangxia, Liujiaxia, Sanmenxia, Xiaolangdi) on the Huanghe (Fig. 1) each exceeds 100 m in height (Table 1). The four reservoirs have a total impoundment capacity of 55.7 × 109 m3, roughly equaling the river’s annual water discharge. This capacity enables modulation of the river’s runoff by storing flood water within reservoirs

in wet seasons and releasing it in dry seasons (Wang et al., 2007). Given the different source regions for Huanghe’s water and sediment, the Sanmenxia and Xiaolangdi reservoirs in the lower middle reaches have major impacts on sediment entrapment. The upstream reservoirs (Longyangxia and Liujiaxia) play a more significant role in modulating runoff. The Xiaolangdi dam (location shown in Fig. 1) situates at the end of the middle reaches and thus controls the runoff entering the lower Huanghe (Table 1). Long-term (1950–2012) datasets of water and sediment recorded at gauging stations on the Huanghe (see Fig. 1) allow an assessment of how dams affect the delivery of material to the sea.