In Japan, the main island of Honshu also has several sites that contain obsidian obtained from Kozu Island (Izu Islands) by 32,000 years ago ( Habu, 2010). Overall, the evidence from Sunda and Sahul demonstrates

significant maritime voyaging, ocean navigation, and island colonization by the Late Pleistocene. Somewhat later in time, colonization of California’s Channel Islands at least 11,000 B.C. (all B.C./A.D./B.P. dates are calibrated calendar ages unless otherwise Bortezomib noted) required boats and was achieved by some of the earliest people to live in the Americas (Erlandson et al., 2011a and Erlandson et al., 2011b). Early coastal sites in California, elsewhere on the Pacific Rim, and in Chile have helped support the coastal migration theory for the initial peopling of the Americas (Erlandson et al., 2007). Colonization of several Mediterranean islands

occurs about this same time, with hunter-gatherers or early agriculturalists expanding to several islands and traveling to Melos to obtain obsidian during the Terminal Pleistocene and Early Holocene (Cherry, 1990, Patton, 1996 and Broodbank, 2006). During the Middle and Late Sirolimus Holocene, there is an explosion of maritime exploration and island colonization, facilitated by major advances in sailing and boat technology (Anderson, 2010). The Austronesian expansion of horticulturalists out of island Southeast Asia, through Near Oceania and into Remote Oceania (ca. 1350 B.C.) begins several millennia of island colonization in the vast Pacific, culminating in the Polynesian colonization of Hawaii, Easter Island, and New Zealand during the last millennium

(Kirch, 2000 and Anderson, 2010). Human settlement of Caribbean islands began at least 7000 years ago, initially by 4��8C hunter-gatherers and later by horticulturalists expanding primarily, if not exclusively, out of South America (Keegan, 2000, Fitzpatrick and Keegan, 2007 and Wilson, 2007). In the North Atlantic, Mesolithic peoples began an expansion into the Faroes and elsewhere that increased during the Viking Age, with voyages to Iceland, Greenland, and northeast North America (see Dugmore et al., 2010 and Erlandson, 2010a). Other islands in southern Chile and Argentina, northeast Asia, the Indian Ocean, and beyond were all colonized by humans during the Holocene, each starting a new anthropogenic era where humans often became the top predator and driver of ecological change. A final wave of island colonization occurred during the era of European exploration, when even the smallest and most remote island groups were visited by commercial sealers, whalers, and others (Lightfoot et al., 2013). Early records of human colonization of islands are often complicated by a small number of archeological sites and fragmentary archeological record, which is hindered by interglacial sea level rise that left sites submerged offshore. Consequently, the early environmental history of colonization can be difficult to interpret.

The new version of the STEAM model (St2, STEAM2, Jalkanen et al. 2012) used in this study also calculates emissions of CO, CO2 and particulate matter (elementary and organic carbon, ash, hydrated SO4). The main advantage of the

new AIS-based inventory is its excellent temporal and spatial resolution. The modelled 2008–2011 average oxidised nitrogen (NOx), reduced nitrogen (NHx) and sulphur (S) depositions are presented in Figure 1. The dry deposition share of the total NOx deposition increases Ku-0059436 ic50 from 10–20% over the northern Gulf of Bothnia to 20–30% in the Sea of Bothnia, the Gulf of Finland and the Gulf of Riga, being 30–40% in the central Baltic Proper and in the southern Baltic Sea. The share of reduced nitrogen in the total N deposition was less than 30% north of Åland, increasing gradually southwards to over 50% in the Kattegat and Belt Sea areas.

There was a rather sharp dry deposition gradient over the shorelines for both INCB024360 nitrogen compounds. The 2008–2011 average depositions of NOx and S caused by the international ship traffic in the BS are presented in Figure 2 and the ship deposition shares of the respective total deposition in Figure 3. The annual sums of the total and ship-emission-originated depositions of sulphur and nitrogen to the BS with a map of BS sub-basins – the Gulf of Bothnia (B1), the Gulf of Finland (B2), the northern Baltic Proper (B3), the southern Baltic Proper (B4) and the Kattegat and the Belt Sea (B5) – are presented aminophylline in Figure 4. The ship emission originated deposition of oxidised nitrogen increased between 2008 to 2011 from 12 to 14% of the BS total NOx deposition, while the respective sulphur deposition declined from 28 to 20% of the total due to the sulphur directive restrictions. Sulphur is effectively dry-deposited

into the sea, only 19–25% of the ship emission originated sulphur deposition is wet deposition. The total modelled NOx deposition to the BS was respectively 6% and 15% lower in 2008 and 2011 but 1% and 5% higher in 2009 and 2010 than the most recent EMEP estimates from HELCOM 2013. The modelled deposition of NHx was respectively 18, 22, 5 and 15% lower than the EMEP estimate for the years 2008–2011. One reason for the difference is the high deposition gradient at the coastline: in Hilatar, the deposition was integrated only over grid points with 100% open water (372 954 km2), while the complete 0.068° Hirlam BS mask of 420 325 km2, also covered non-marine water areas in the BS coastal zone. Total depositions have a rather high seasonal variation (Figure 5). During spring and early summer when the MABL is usually stably stratified, accumulated precipitation is low and storms are rare, depositions have their minimum values.

After cooling, the cooled extract was centrifuged (5000 × g for 10 min) and then filtered through a Whatman no.5 filter paper. The extract was stored at −20 °C until analysed. The residual tissue was further digested with papain, and uronic acid contents in both the extract and the residual tissue were determined by the carbazole PI3 kinase pathway reaction (see Section 2.7). These estimates enabled the proportion of uronic acid liberated to be expressed as a percentage of the total uronic acid recovered. The total extractability of uronic acid was then compared between the different extraction conditions. The preparation of each extract, which was referred to as antler papain extract, was performed in triplicate and the entire

experiment was independently replicated three times to address precision. Antler CS fractions were isolated and examined for molecular size using Sephacryl S-300 chromatography (Pharmacia Biotech Inc., Quebec, Canada). A portion of the antler papain extract was fractionated using a 1 × 110 cm column equilibrated and eluted with 0.05 M NaCl buffer, pH 5.8, at a flow rate of 3 mL/h. Blue dextran GDC-0980 order and tritiated water were used to determine void volume (Vo) and total volume (Vt) of the column, respectively. The partition coefficient was calculated from the formula: Kav = (Ve−Vo)/(Vt−Vo), in which Ve represents the volume of the peak fraction. The eluates (1 mL) were analysed for protein at 280 nm absorbance, hydroxyproline,

sulfated GAG and uronic acid content as explained in Section 2.7. Antler CS fractions were pooled almost and freeze-dried for further study. All chromatography data presented in this paper are means of 3 experiments. Electrophoresis was performed in 0.6% acrylamide in agarose in Tris buffer, pH 6.8. Samples were dissolved in deionised water. Two slabs were

generally run at the same time, one for staining with toluidine blue and the other for western blot with monoclonal antibodies to chondroitin sulfate (CS-56) (Sigma–Aldrich, USA). Electrophoretic transfer to nitrocellulose was accomplished in Tris–borate (gel electrophoresis buffer) without sodium dodecyl sulfate at 40 V for 2 h. Nitrocellulose sheets were then soaked in 2% bovine serum albumin (BSA) in phosphate-buffered saline (PBS), pH 7.2 for 1 h at room temperature. After washing in PBS (three times for 5 min each), nitrocellulose sheets were incubated with anti-CS monoclonal antibodies (in PBS containing 1% BSA) for 1 h at room temperature. The incubation was followed by washing in PBS and 1 h incubation with rabbit anti-mouse IgM conjugated with horseradish peroxidase. Colour was developed by incubating in 0.05% diaminobenzidine tetra-hydrochloride in PBS containing hydrogen peroxide (0.01% w/v) and cobalt chloride (0.033% w/v) for 5 min. Stained blots were then washed several times in water and dried. Hyaluronic acid from human umbilical cord (Sigma–Aldrich, USA) was dissolved in 0.5 M sodium acetate buffer, pH 6.

brasiliensis cathepsin L. Various band signals with a molecular weight ranging from about 30–38 kDa, similar to zymography, were detected ( Fig. 6). Since the samples were separated

under reducing conditions, the molecular weights differed slightly from those observed in in-gel zymograms. The establishment of a T. cruzi infection in the intestinal tract of the vector depends on many factors which modulate the parasite-vector interaction PD0332991 molecular weight ( Azambuja et al., 2005 and Garcia et al., 2007). The midgut of triatomines is the interface for development and multiplication of parasites and exerts in its physiological and biochemical conditions a great influence on the T. cruzi development ( Kollien and Schaub, 2000, Garcia et al., 2007 and Garcia et al., 2011). In some hematophagous insects (e.g. Pediculidae, Culicidae) the midgut is responsible for both storage and digestion of the blood, whereas in Hemiptera these two functions occur in different midgut regions

( Lehane, 2005 and Waniek, 2009). Dipteran insects use serine proteinases (trypsins and chymotrypsins) as their major luminal Selleckchem BGB324 proteolytic enzymes in their digestion process, which are active at alkaline pH ( Johnston et al., 1991 and Chougule et al., 2005), the phylogenetically distant hemipterans possess an rather different digestion, using cysteine and/or aspartic proteinases, which are highly active in acidic conditions ( Houseman, 1978, Houseman and Downe, 1980, Houseman and Downe, 1981, Houseman and Downe, 1982, Houseman et al., 1984, Lehane, 1994 and Borges et al., 2006). These peculiarities of the triatomine midgut physiology and digestion must be specifically taken into account in the studies of triatomine–trypanosomatid Thalidomide interactions. So far, triatomine cathepsin L encoding cDNA sequences have been identified and characterized in R. prolixus and T. infestans ( Lopez-Ordoñez et al., 2001 and Kollien et al., 2004). In their deduced amino acid sequences triatomine cathepsin L precursors are structurally similar, possess all characteristic

motifs and are highly conserved but less as for example triatomine defensins or lysozymes ( Kollien et al., 2004, Araújo et al., 2006, Waniek et al., 2009a and Waniek et al., 2009b). Triatomine cathepsins are synthesized as pre-proenzymes. In general signal peptides are approximately 20 amino acids long, hydrophobic and cleaved during their passage to the endoplasmatic reticulum ( von Heijne, 1983 and Turk et al., 2000). Signal peptides of insect cathepsins L are within the usual boundaries and all Triatoma cathepsin B and L signal peptides, so far identified, are composed of 16 amino acid residues. Activation peptides are important for the proper folding of the protein and for protection of the cell from potentially negative effects of unregulated proteolytic activity.

Other FTIR studies on corn and corn flour have also reported two bands at 2927–2925 and 2855 cm−1, being respectively attributed to asymmetric and symmetric C–H stretching in lipids (Cremer and Kaletunç, 2003 and Gordon et al., 1997). Thus, the sharp bands at 2920 and 2850 cm−1 observed in the spectra presented for coffee in Fig. 1 can be attributed to combination PLX3397 bands to which both caffeine and lipids contribute. The sharp band at 1740 cm−1 was also reported on previous FTIR studies on roasted coffee,

in association to carbonyl (C O) vibration of the ester group in triglycerides (Kemsley et al., 1995) or to aliphatic esters (Lyman et al., 2003), indicating that this band could be associated to lipids. The combination of absorptions at 1740 cm−1 (C O stretch) and at 2830-2695 cm−1 (H–C O stretch) with a weak shoulder-type peak at 2725–2740 cm−1 could be interpreted as a presence of aldehydes (Miller, Mayo, & Hannah, 2003), which are volatile compounds found aplenty in roasted coffee, as a result of the thermal degradation of unsaturated fatty acids, such as linoleic acid, which is quite abundant in the coffee lipid fraction (Oliveira et al., 2006). The wavenumber 1659 cm−1 has been identified by Garrigues, Bouhsain, Garrigues, and De La Guardia (2000) as due to the presence of carbonyl groups in caffeine in their FTIR analysis of trichloromethane extracts of roasted

coffee, and was further used as the determinant band in their quantitative analytical procedure for caffeine in roasted coffee samples. However, in our study, this band appears rather modestly GBA3 in the spectra for roasted and ground coffee. TSA HDAC chemical structure Thus, it can be assumed that several

other compounds in roasted coffee also absorb in that range of wavenumbers and that, apparently, trichloromethane does not extract them, since in the work by Garrigues et al. (2000) the 1659 cm−1 was quite sharp in the trichloromethane extract. A comparison of average DR spectra obtained for green and roasted coffees is shown in Fig. 2a. The spectra are qualitatively similar, even though roasted coffees presented higher absorbance in comparison to green coffees. It is interesting to observe that, once the spectra were normalized (see Fig. 2b), all the previously cited bands (2920, 2850 and 1740 cm−1) presented similar levels of absorbance in green and roasted coffees. This could be associated to the fact that both caffeine and lipids levels are not expected to vary significantly during roasting (Franca et al., 2005b, Franca et al., 2005 and Vasconcelos et al., 2007). Evaluation of Fig. 2b also shows no significant differences between green and roasted coffees regarding absorbance values of the small band at 3008 cm−1. This band can be attributed to the symmetric stretching vibration of C–H cis-olefinic groups (=C–H in cis RHC = CHR) and can be also associated to the presence of lipids ( Yang & Irudayaraj, 2001).

( Fig. 1) Description (based on eight specimens)

Third larval stage, 19.9 (17.4–23.1) total length; 0.53 (0.45–0.62) maximum width. Cuticle transversally striated. No lateral alae. Larval teeth at the anterior extremity. Oesophagus 1.85 (1.45–2.78) long. Ventriculus with appendix, 2.09 (1.6–2.4) long; and 1.5 (0.91–2.0) large. Excretory pore anterior to the level of the nerve ring. Host: Diplodon suavidicus (Lea, 1856) (Mollusca, Unioniformes, Hyriidae). Host examined: (based on 68 specimens). check details Hosts showed a mean length of 32.4 mm (varying between 22.45 and 44.7), ( Fig. 2) Prevalence and intensity: from the 68 molluscs collected, 56 were parasitized. The prevalence was 82%, with a mean intensity of 4.71 and mean abundance of 3.88. The amplitude of variation was between 1–16 individuals per host. Site of infection: pericardic cavity Diplodon suavidicus. INPA 1291; 1260; 1265; 1273; 129; 1300; 1306. Hysterothylacium sp. INPA 1291; 1260; 1265; 1273; 129; 1300; 1306. The Anisakidae family shows a worldwide distribution and parasitizes

all classes of vertebrates, including fish, mammals, birds and reptiles (Moravec, 1998). Their life cycle is still not clear for most species and many intermediate and definitive hosts are not known yet. Trametinib mouse Some larvae can have a zoonotic character and reach men through the ingestion of raw or improperly cooked fish meat. Clinical signs depend on the site where the larva is deposited, but it generally causes abdominal pain and vomiting, as well as some allergic reactions (Fumarola et al., 2009 and Valls et al., 2005). Nematodes of the Hysterothylacium genus reach sexual maturity inside the intestine of fish or marine mammals. Larvae of Hysterothylacium

are found using a great variety of organisms as intermediate hosts ( Jackson et al., 1997, Marcogliese, 1996, Bicudo et al., 2005 and Navone DNA ligase et al., 1998). This is the first report of Hysterothylacium larvae in Mollusca for the Amazon and Brazil. It is also the first record of a South American Hyriidae freshwater mussel as an Anisakidae intermediate host. Thiengo et al. (2000) also recorded the presence of Anisakidae larva species in South American molluscs. However, these authors investigated the gastropod mollusc Gundlachia radiata (Guilding, 1828) and identified the larvae as belonging to the Contracaecum genus. Luque et al. (2007) recorded the presence of Hysterothylacium larvae in amphipods in New Zealand. However, the prevalence found by Thiengo et al. (2000) and Luque et al. (2007) were low compared to this study. From the 65 Gundlachia radiata specimens collected, only three were parasitized by Contracaecum larvae and with a maximum intensity of two larvae per host. From the amphipods collected by Luque et al. (2007), around one to 10% of the hosts were parasitized, depending on the sampling site, with one or two nematodes being found per host.

The distribution of smoke yields for the elements after normalization with corresponding nicotine yields was addressed, since data normalization has been recommended when dealing with data sets derived from brands with diverse design features, particularly

with reference to regulation [39]. Only normalized data for cadmium are reported in Table 5. The large number of values below LOQ for lead and arsenic makes any estimate for the distribution Selleck Atezolizumab of their normalized yields meaningless. For comparison, mean values for nicotine-normalized cadmium yields of samples available in the published literature are also reported in Table 5. In general, the transfer rates of elements may be influenced by a broad range of cigarette design Ion Channel Ligand Library parameters, as recently reported [40]. In the present case, we performed an analysis of variance (ANOVA) on the transfer rates of cadmium and lead (insufficient amount of data for arsenic) under ISO and HCI smoking regimes as response variables, taking the presence of activated carbon in the filter, measured filter ventilation, filter length, and cigarette diameter as independent design features. The results for lead transfer rates show a strong residual contribution of more than 85% to the total variance under the HCI smoking regime, and significant apparent contributions to the total variance from filter

ventilation (ISO smoking regime) or cigarette diameter (HCI smoking regime). In the case of cadmium transfer, under both ISO and HCI smoking regimes more than 30% of the total variance can be attributed to the presence of activated carbon in the filter, and 30–40% is a residual contribution. If one assumes that lead and cadmium reside in the particulate phase, the contribution of the cigarette design features to the variance of yields should cancel out if we instead take the ratio of their transfer rates to nicotine transfer rates as response variables, since nicotine is entirely

present in the smoke particle-phase Interleukin-3 receptor throughout its transfer across the unburnt tobacco and the filter [41], [42] and [43]. Indeed, the same ANOVA performed on metals transfer rates normalized to nicotine transfer rates showed that for lead 84% and 96% of the total variance is contained in the residuals under ISO and HCI smoking regimes respectively. For cadmium, however, there remains a large contribution from the presence of activated carbon in the filter, which accounts for about 50% of the total variance under both ISO and HCI smoking regimes. The residual contribution is at a level of 40–50%. This last result suggests that a specific filtration of cadmium by activated carbon may be taking place, which would imply that cadmium is partly present in the gas-phase.

However, these types of data are currently unavailable for seagrass bed, offshore pelagic, and deep-sea ecosystems; thus, it is difficult to use this criterion for EBSA selection for these ecosystems. Even in references regarding this criterion [35], the application of this criterion in the deep sea was considered difficult in many cases. BMN 673 mw As a result, criterion 2 is difficult to be employed in most ecosystems because

of a lack of data. This occurred in the case study on EBSA selection on a wider Asian regional scale (Uchifune et al. under review). This criterion does not need to include quantitative data from across the entire ocean, considering the underlying concept that includes qualitative information regarding breeding areas that are already known.

However, basic data collection on habitat use by major mobile species in Asian waters during their life histories, such as use of spawning grounds, is insufficient. Fisheries statistics can be used as substitutes for stock data regarding the kelp community. Although the availability of fine-scale reliable data is limited, rough spatial resolution, such as regional analysis, is better to avoid conflict between conservation and fisheries in this case. Research on animal tracking by bio-logging to investigate the movement of marine organisms has recently been increasing [37]. Data sharing and gathering after initial publication are useful to when utilizing these types of data for selecting important sites with respect to the life history of certain species. This is criterion is defined as an “area containing habitat for the survival U0126 supplier and recovery of endangered, threatened or declining species or area with significant assemblages of such species,” [5]. This criterion targets threatened, endangered, or declining species and their habitats for consideration. As discussed for criterion 1, the selection of endangered species depends on the individual study areas. If the research target is limited to certain areas (e.g., within the Japanese coast as in the present study), locally endangered species should be used even if they are still abundant in other regions worldwide. Phosphatidylinositol diacylglycerol-lyase The present

research program used the area and the species number of endangered species listed in the IUCN red list as well as the endangered species list of the Ministry of the Environment of Japan. In the case of kelp forest ecosystems, the distributions of 5 kelp species listed in the Ministry of the Environment red list were used to rank the sites according to this criterion. For seagrass bed and coral reef ecosystems, both the Ministry of the Environment endangered species list and the IUCN red list can be used. However, these lists do not include any endangered species among offshore deep-sea chemosynthetic benthic organisms or oceanic plankters. Therefore, additional information on engendered species is required to apply this criterion.

We performed immunofluorescence examination using the antibody against the immediately early lytic gene BRLF1, and found that 2% of the AGS–EBV cells were positive for BRLF1, which are entering the lytic phase of EBV replication ( Supplementary Figure 1C). The 10 EBV genes verified in AGS–EBV, SNU719, and YCCEL1 were

verified further in primary EBV(+) gastric cancer tissues with a positive detection rate between 7.7% and 46.2% by RT-PCR ( Figure 1C). Expression of EBV genes may contribute to EBV-associated gastric carcinogenesis. We compared the whole genome sequences of AGS–EBV and AGS to identify EBV-caused host genomic alterations, including single-nucleotide variants (SNVs)/point mutations, small insertions and deletions (indels), and structural variations (SVs) (Supplementary Tables 3–8). SP600125 mw A total of 139 EBV-associated SNVs covering 131 genes were identified to be of interest, including 45 nonsynonymous SNVs (affecting 44 genes), and 94 SNVs located at important regulatory regions

(splice sites, 5- or 3-untranslated regions, and promoter regions; affecting AZD2281 clinical trial 87 genes). We also found 56 indels covering 54 genes in AGS–EBV and 48 AGS–EBV–specific SV events affecting 24 genes and other nongene regions. Seven randomly selected SNVs in 6 genes (AKT2, CCNA1, TGFBR1, ACVR1C, MAP3K4, and NRXN1) were well validated in AGS–EBV, but not in AGS or AGS-hygro by PCR followed by Sanger sequencing ( Supplementary Figure 2A). Among them, AKT2, the putative oncogene documented with important functions in the cancer pathway of mitogen-activated protein kinase (MAPK) signaling, harbors 2 EBV-associated nonsynonymous SNVs. Two randomly selected indels (FAM35A and ADAMTS12) and 4 randomly selected SVs (GGT7-IRS1, KMD3A-KMD3A, SMAD5-STXBP5, and NA-KDM3B) also were well validated in AGS–EBV by PCR followed by Sanger sequencing, but were not detected in AGS or AGS-hygro cells ( Supplementary Figure 2B and C). By comparing the 45

EBV-associated nonsynonymous host SNVs/point mutations (covering 44 genes) (Figure 2A) identified in AGS–EBV with the Adenosine Catalogue of Somatic Mutations in Cancer database, which collects somatic mutations in human cancers, we found that all 44 genes had been recorded, but none of the 45 mutation sites had been documented ( Supplementary Table 4), inferring the novelty and potential importance of these mutations caused by EBV infection. To clarify if the EBV-associated mutations in AGS–EBV also occurred in primary EBV(+) gastric cancers, we performed Sanger sequencing to compare the prevalence of mutations in AKT2, CCNA1, TGFBR1, ACVR1C, and MAP3K4 between EBV(+) and EBV(-) gastric cancer samples.

Bordi et al., 2004 and Bordi et al., 2009 argued that a time scale of 18 month capture the low frequency variability and filters out the effects on drought and wetness of short-term periodicities and seasonal cycles. We used the PCA (Von Storch and Zwiers, 1999 and Wilks, see more 2006) to the SPIn (t) series to analyze the patterns of droughts/wetness co-variability. The SPI at single grid points as variables (X  i) and the time periods as individuals has been used in what is commonly known as S-mode. This method allows to obtain the Principal Component (PCs) as signals or time series and the eigenvectors (u  ij) as spatial patterns, which vary in time according to the PCs. The variable

correlation matrix was used in the PCA because we want to determine the spatial relationships between variables (SPI series at each grid point) more than the internal variability in each SPI series. Then, we assessed the spatial distribution of the correlation

for each variable (SPI time series at a single grid point) with each of the first PCs. These representations are equivalent to the traditional eigenvectors patterns and have a more direct interpretation for the reader. The use of a correlation matrix, defined by: equation(1) A=[aij] where   aij=Corr(Xi,PCj)A=[aij] where   aij=Corr(Xi,PCj)allows the rapid calculation of the proportion of variance of variable X  i accounted for by the k   first PCs through the addition ai12+ai22+⋯+aik2 LDK378 ( Krepper and Sequeira, 1998). The temporal behavior of PCs was analyzed with SSA (Ghil et al., 2001 and Wilks, 2006) in the low frequency band (LFB), with the objective Miconazole of determining the structures of trend and oscillatory modes in SPIn (t) series. SSA is applied in the time domain and aims to describe the variability of a discrete and finite time series Xi*=X*(iΔt), (i = 1, …, N and Δt = sampling interval) in terms of its lagged autocovariance structure. Variables are normalized to Xi = X(iΔt) and lagged autocovariance matrix C (M × M)

is defined: equation(2) Cij=1N−M∑s=iN−M+|i−j|XsXs+|i−j| (i,j=1,…,M)where M is the temporal embedding dimension (windows length) over which the covariance is defined and τ = MΔt maximum delay (lag). The eigenvalue decomposition of the lagged autocovariance matrix C (M × M), up to lag MΔt, produces temporal-empirical orthogonal functions T-EOF = [T-EOF1, …, T-EOFM] with T-EOFk = [Ek (1), …, Ek (M)]T and temporal-principal components T-PC = [T-PC1, …, T-PCN−M] with column vectors defined as T-PCk = [PCk(1), …, PCk(N − M)]T statistically independent, with no presumption as to their functional form. Each T-PCs has a variance λs (eigenvalue) and represents a filtered version of the original series Xi. A key issue in SSA is the proper choice of M. Von Storch and Navarra (1995) recommended not to exceed M = N/3 and explain that SSA is typically successful at analyzing periods in the range (M/5, M).