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Toxicant default guideline values for water quality in aquatic ecosystems
Accounting for local conditions
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Toxicant default guideline values technical briefs
Default guideline values (DGVs) can provide you with an important starting point for managing water quality but they cannot account for the large spatial or temporal variation in natural water quality. This includes variation in environmental variables that influence the bioavailability and toxicity of contaminants.
Toxicant DGVs are based on data from a specific set of solution parameters, such as pH, hardness, dissolved organic carbon, salinity and temperature. These characteristics vary widely throughout Australian and New Zealand waters.
In addition, DGVs may not protect locally important species because published global data are usually only available for a very limited number of (usually standard) toxicity testing species. Very few of them are Australian or New Zealand species.
This is why you should, wherever possible, tailor DGVs and the types of water chemistry data collected to account for local conditions. The ultimate tailoring of a DGV to local conditions is the derivation of a site-specific guideline value. In addition to the guidance provided in the Water Quality Guidelines, another relevant source of guidance for deriving site-specific guideline values can be found in van Dam et al. (2019), while Huynh & Hobbs (2019) provide specific guidance tailored for the coal resource industry, but which will also have broader applicability.
In some cases, DGVs can be appropriately modified to account for some important local factors. For example:
corrections for the effects of hardness for metals
corrections for the effects of pH for ammonia
dealing with naturally elevated background concentrations (natural toxicant concentrations unrelated to human disturbance).
In addition, or alternatively, direct toxicity assessment (DTA) can be a useful tool to account for local conditions (sections 8.3.5.19 and 8.3.6 of ANZECC & ARMCANZ 2000), and has several applications. We provide some updated guidance on the benefits and uses of DTA.
The process of accounting for local conditions is usually completed in the Water Quality Management Framework at:
Step 4 — Determine water/sediment quality guideline values
Step 6 — Assess if draft water/sediment quality objectives are met.
Knowing when to refine default guideline values
Note that your local jurisdiction may have its own guidance for applying and refining guideline values, and you should always consult with it on appropriate methods.
For most indicators and issues, you would only refine DGVs after continuous and extensive monitoring showed that test-site data exceedances posed no risk to the ecosystem. This would require hierarchical measurements of the stressor line of evidence, in this case water chemistry, together with other lines of evidence that also demonstrate no ecosystem detriment.
You could also refine guideline values if longer-term monitoring showed that test-site data were consistently below the DGVs.
Evaluating monitoring data against default guideline values
You need to interpret water quality monitoring data correctly to enable effective comparison with guideline values.
To do this, you should apply a decision scheme that provides step-by-step guidance on how to consider and (if necessary) treat water chemistry data obtained for site-specific environmental conditions. Such a scheme would include consideration of:
bioavailable fraction
background concentrations
analytical detection limits.
It is not mandatory to use hierarchical chemical measurements because, in most instances, the chemistry line of evidence will be assessed in parallel with other lines of evidence.
If you want to make meaningful and appropriate comparisons with DGVs or site-specific guideline values, then hierarchical chemical measurements are important. They can greatly assist with interpretation of the chemistry line of evidence where initial measurements (i.e. steps early in the hierarchy) are near or above the guideline value.
The simple adjustments and corrections that we describe here make this a cost-effective and (in practice) rapid exercise when data on key water quality parameters are available.
You should consider the extent to which local factors will influence your sampling and data collection and manipulation requirements when defining the issue and setting objectives for a monitoring or assessment program.
Expand all
Summary of recommended actions:
Measure the bioavailable fraction (dissolved metals concentration) in the water sample by:
passing it through a filter membrane
using chemical speciation techniques, or
using a biotic ligand model (BLM) to predict the speciation of the metal.
In the case of metals, the first option is to test the total (particulate plus dissolved) metals concentration against the guideline value.
More commonly, since it is generally the dissolved fraction that is bioavailable rather than any particulate forms, the fraction that passes through a 0.45 µm filter membrane is compared to the guideline value.
Another option to determine the bioavailable fraction in a sample is to use metal speciation measurements or modelling. This may be necessary, for example, if a hardness-modified guideline value is still exceeded. Labile metals that relate to a bioavailable fraction can be determined using Chelex® columns (Bowles et al. 2006), anodic stripping voltammetry or diffusive gradients in thin-films (DGT) gel samplers (Batley et al. 2004, Huynh & Vink 2016). Refer to ANZECC & ARMCANZ (2000) Section 8.3.5.16 for information on chemical speciation measurement and modelling techniques.
If a biotic ligand model (BLM) has been developed for a metal, you can use the BLM to predict the speciation of the metal in the environmental medium. The complexity of the BLMs requires the prior existence of an intensive calibration effort and multi-parameter mathematical calculations for implementation. BLMs are currently applicable to a limited range of metals and do not specifically handle metal mixtures, even though mixtures are commonly present at contaminated sites.
Organic toxicants
If considered appropriate, measure the bioavailable fraction (dissolved organic toxicant concentration) in the water sample by:
using passive samplers, or
investigating the use of ultrafiltration separation.
Otherwise, measure the total fraction.
pH will be a potential modifier of bioavailability for those organic toxicants with ionisable functional groups. Other solution parameters may also affect solubility and partitioning of the more hydrophobic organics.
Few studies to date have looked at speciation and bioavailability of organic contaminants in any detail. There is potential for many of these to be associated with colloidal particulates, and separations based on ultrafiltration may be worth investigation.
The use of passive samplers represents best practice in monitoring of dissolved organics in waters (e.g. Vrana et al. 2005, Ghosh et al. 2014). Passive samplers can identify sources of contaminants where extremely low levels have to be detected or when the input and presence of the contamination is not constant.
Default guideline values and background concentrations
If the stressor is an inorganic toxicant or an organic toxicant with widespread (e.g. global) distribution, determine a reliable background level for the study stressor at a reference site, equivalent to the test site.
If the background level exceeds the DGV, and it is deemed that the ecosystem could tolerate further increases in concentration, use the referential approach to derive a new site-specific guideline value. The 80th percentile of the background becomes the site-specific guideline value.
Some surface waters contain concentrations of toxicants that may naturally exceed the DGVs. If this is the case, then you can use the referential approach to derive new guideline values based on natural background or baseline data. This applies mostly to metals and metalloids.
In highly mineralised areas, the background may involve mainly mineralised biologically unavailable metal forms.
The very few organic toxicants where background concentrations might be elevated include some phenols and globally distributed chemicals, such as DDT and other persistent organic pollutants (POPs), with rare exceptions, such as hydrocarbon-rich fluid seeps.
Gathering background data is always recommended — at least in the initial stages of a water quality management program — to establish whether or not concentrations of toxicants are naturally high.
Toxicant concentrations may vary seasonally, which is why you need confidence in the best estimate of background concentrations. To increase confidence in the estimate, you should gather data at least monthly for at least 2 years. In all respects, data requirements and collection are the same as for physical and chemical (PC) stressors.
Until the minimum data requirement has been established, you should compare the test site median with reference to the DGV. For those months, seasons or flow periods that constitute logical time intervals or events to consider and characterise background water quality, the 80th percentile of background data (from a minimum of 10 observations) should be compared with the DGV. Use the 80th percentile value as the new guideline value for this period if it exceeds the DGV.
In naturally mineralised catchments where background concentrations of certain inorganic compounds can be high and well above DGVs, there is often little evidence for enhanced tolerance by the ecosystem. It may be naturally stressed by the elevated toxicant concentrations and unable to tolerate substantial further increases in concentration. If this is the case, then the current understanding of the system should capture the status of the ecosystem under baseline conditions and its ability to tolerate increased contaminant concentrations. This is particularly important if the local biotic assemblage (plants, animals and microbes in the aquatic ecosystem) has naturally reduced biodiversity.
If background toxicant values fall consistently below DGVs, then sampling intensity at these sites could be reduced after a suitable period (e.g. 2 years).
DTA might be usefully applied to the background or reference waters to confirm that there is no toxicity (van Dam & Chapman 2001). If toxicity is observed, you could apply toxicity identification and evaluation (TIE) to try to determine the compound classes causing toxicity (Burkhard & Ankley 1989, USEPA 1992, 1993, Burgess et al. 2013).
Default guideline values and analytical detection limits
Where a toxicant DGV is below the analytical detection limit, and the toxicant is detected with reasonable reliability, the DGV can be assumed to have been exceeded. Your options are to:
accept that the DGV has been exceeded and institute remedial action, or
examine the water chemistry data management decision scheme to see if site-specific factors reduce the environmental risk, and/or
consider DTA to determine if the ambient waters have a potential biological effect and potentially undertake
site-specific toxicity testing of the toxicant in question, using local species under local conditions, to derive a site-specific guideline value, or
DTA of the ambient water to ascertain whether adverse effects are observed at the toxicant concentration present. If effects are observed, then initiate management action.
Particularly where guideline values are derived from extrapolation of a species sensitivity distribution (SSD), it is possible that they may be near or below the analytical practical quantitation limits (PQLs) or even the method detection limits (DLs), which are often around one-fifth of the PQL.
It is not reasonable to automatically raise a guideline value to the analytical PQL if this is likely to result in environmental harm.
If such chemicals are detected with reasonable assurance, it may indicate that the guideline value is exceeded.
Sometimes it may be possible to introduce effluent controls to ensure that calculated ambient levels in the receiving ecosystem do not exceed guideline values. In other cases, low guideline values may encourage development of more sensitive analytical techniques. The measurement of chemical concentrations at levels below those currently available may well be feasible in the near future.
If the guideline value is below an analytical PQL or DL, biological data (e.g. DTA, field biological monitoring) provide the only certainty that the environment is protected. If testing of ambient waters indicates a toxic effect, management action should be initiated. This could include the use of TIE techniques, which can assist in identifying the unmeasured toxicant source.
The issue of guideline values being below the PQLs of commonly used analysis methods raises the possibility that a laboratory using a method with a relatively high level of detection may deliver only nondetectable results even if the true concentrations are at or above the guideline value. Water authorities may reserve the right to question and reject nondetectable results if there is concern that an appropriate methodology has not been used.
Given the possibility of analytical error around the PQL — resulting in false positives — it may be better to invest in analytical methods with lower PQLs if available, or use biological data (e.g. DTA) in preference to the chemistry line of evidence than to rely on a cheaper analysis method with a PQL that is too high.
Refining default guideline values for metals
When evaluating measured chemistry against DGVs for metals, where possible it will be important to account for the influences of important local water quality variables, such as water hardness, pH, salinity and the associated mix of dissolved salts, and dissolved organic carbon (DOC) on metal bioavailability.
DGVs are typically derived for either low hardness, near neutral pH fresh waters with negligible DOC or pristine marine waters of typical oceanic salinity. Currently, there are no DGVs for estuarine waters or inland saline waters.
If the water sample exceeds the standard hardness value of 30 mg CaCO3/L, then it is appropriate to modify the DGV for all hardness-sensitive metals except copper.
Increases in water hardness reduce the toxicity of some metals. The hardness corrections used in the ANZECC & ARMCANZ (2000) guidelines followed those used by the US Environmental Protection Agency. All the toxicity test endpoint values were adjusted to a standard hardness value of 30 mg CaCO3/L, which was considered appropriate for the generally soft waters present in Australia and New Zealand. These corrections were largely based on acute toxicity data for fish but were being applied to modify guideline values based on chronic toxicity data.
Updated guidance on guideline-value derivation by Batley et al. (2018) and Warne et al. (2018) advised that no hardness adjustment should be undertaken for copper for chronic toxicity, but that hardness adjustments should still be incorporated for other hardness-sensitive metals (cadmium, chromium, lead, nickel, zinc) until otherwise advised.
If the water being examined has a hardness greater than 30 mg CaCO3/L, then it is appropriate to modify the DGV for that hardness.
Other toxicity modifying factors
If the knowledge is available, deal with factors that modify the toxicity of metal concentrations in the water sample by modifying the guideline values for the site-specific solution parameters or comparing the bioavailable fraction with the DGV.
Competition with hydrogen ions, or complexation by DOC or alkalinity (bicarbonate), can reduce metal bioavailability.
Methods for dealing with these modifying factors involve:
modifying guideline values for the site-specific solution parameters, or
measuring or modelling the bioavailable fraction of the total dissolved metal fraction and then comparing that with the DGV.
Modelling could include application of the BLM (discussed later) or geochemical models of solution speciation.
One of few examples of a DOC correction for a guideline value in Australia was described for uranium by van Dam et al. (2017). However, that correction was for a site-specific guideline value, for which many site and species-specific data were required to develop the guideline value and associated correction.
Salinity effects
Examine supporting data for freshwater and marine water guideline values if you must compare them to estimate the salinity effects in an estuary.
Include biological lines of evidence in your assessment of which guideline value to use, and consider developing a locally relevant guideline value.
Guideline values have been derived for both freshwater and marine water, for appropriate use in each system. Few toxicity data exist for estuarine organisms, which live in a mix of freshwater and salt water. In most cases, it will be necessary to make best estimates of the appropriate guideline value for estuarine ecosystems.
Exercise care when comparing figures for freshwater and marine water guideline values. We do not recommend making such comparisons to estimate salinity effects in an estuary without closely examining the supporting data, because different types of datasets were used to calculate each guideline value.
For salinity changes in freshwaters, the additional stress of higher toxicant concentrations on top of elevated salinity levels in normally freshwater ecosystems may result in mixture toxicity. The nature of this mixture toxicity cannot be readily predicted at present.
If you are uncertain about the appropriate guideline value to use for an estuary or a freshwater ecosystem with elevated salinity, then we recommend that you include ecosystem receptor lines of evidence in the assessment and consider developing a locally relevant guideline value.
Biotic ligand models
Until existing BLMs have been validated for Australian and New Zealand ecosystems, you should only use them to make site-specific adjustments to DGVs based on site-specific water quality conditions.
In recent years, an alternative methodology for guideline-value derivation internationally has been to use biotic ligand models (BLMs) for metals (including copper, nickel, silver, zinc and manganese) to predict toxicity after incorporating the effects of the water quality modifying factors.
The central notion of a BLM is that organisms possess a key binding site (biotic ligand) that interacts with the toxic metal and other cationic components of the water, and that the degree of accumulation of the toxic metal at the binding site is directly related to the observed toxicity.
By defining and determining equilibrium constants for the reactions of the biotic ligand with key ionic species, including those of the metal of interest, BLMs take a wide range of ionic interactions into account. This allows the models to describe metal interactions with organisms over a range of water chemistry conditions. The interactions that the models take account of include:
solution complexation
competition by protons and base cations (Na+, Mg2+, K+, Ca2+)
binding with DOC over a range of pH conditions.
These derivation procedures are complex and a suite of BLM-binding equations must be developed for acute and chronic toxicity data for key taxa groups (i.e. fish, invertebrates and algae). This can allow bioavailability corrections to be made for the ecosystem, rather than individual species, enabling bioavailability principles to be applied to derive water quality guideline values.
Development of BLMs has so far been based almost entirely on data from laboratory studies, although many of the validation tests have been performed on field collected water samples.
The US Environmental Protection Agency has used a BLM to derive a water quality criterion for copper (USEPA 2007). The US implementation of a BLM for copper requires that water quality information be available for a site prior to being able to calculate a numeric guideline value. More recently, a BLM has been used to derive predicted no-effect concentration (PNEC) values for copper in Europe (De Schamphalaere & Janssen 2008, Bass et al. 2008). This differs from the US approach in that a single environmental quality standard (EQS, expressed as 'bioavailable metal') is derived from the PNEC, and the BLM can be modified based on local exposure water quality conditions to provide a site-specific biological exposure concentration for that metal. The derivation of the EQS uses the BLM to provide normalised toxicity data as part of the derivation process, and the local bioavailability corrections are derived from BLM predictions of local ecosystem sensitivity.
BLM calculations can be used to:
adjust toxicity values to a 'normalised' set of water quality conditions prior to deriving water quality guideline values, so that the sensitivity of all species is expressed under the same water chemistry conditions
make site-specific adjustments to DGVs based on site-specific water quality conditions.
For copper, the US and European BLMs differ in their origin and incorporate different predictive equations, due to differences in the approaches used (i.e. being based principally on acute or chronic toxicity information). As such, they predict different responses to water quality modifiers, thus requiring specific consideration as to the appropriateness of their use.
A recent report by Hickey et al. (2016) investigated these options and compared them to an approach for zinc proposed by Environment Canada (2016), which generated relationships between modifiers and guideline values and provided look-up tables for categorised modifiers (considered a reasonable short-term option).
Regardless, existing US and European BLMs can be used as part of a consideration of metal bioavailability under the local water composition for Australian and New Zealand waters.
It would be considered appropriate to use existing BLM based approaches (if a suitably validated one exists for the metal and exposure period of interest for the ecosystem) for a site-specific assessment to derive a site-specific guideline value based on local water quality composition, and to use this as an additional line of evidence alongside the DGV.
Existing BLMs have not been validated for Australian and New Zealand conditions and, consequently, have not been incorporated into DGV-derivation processes. Research has been undertaken to validate the European nickel BLM for Australian and New Zealand conditions but the results are yet to be published and the method yet to be proposed for implementation.
At this stage, the use of BLMs is recommended only for site-specific assessments. You will need to consider what water quality variables (e.g. pH, hardness, alkalinity, DOC) act as important toxicity modifiers for the metal of interest when adapting the guideline value for local conditions. The process of normalising toxicity data — or correcting guideline values — to a standard water quality condition for the site of interest is complicated by the fact that toxicity modifiers may have:
different response relationships for different taxonomic groups
response relationships that depend on the duration of test exposures (whether acute or chronic).
Alternatives to application of a BLM-modifier approach are to censor the toxicity data in relation to the modifiers — to bound variability which might be associated with that parameter — or in some cases to exclude data where there is a high likelihood that strong effects will be occurring (e.g. DOC).
Refining toxicant guideline values based on other considerations
We describe how guideline values can potentially be refined based on a number of other considerations.
Compare the toxicities of the commercial formulation and the active ingredient (AI) to account for any other chemicals that may modify the toxicity of the AI. If their toxicities differ by greater than a factor of 3, correct the guideline value by the difference.
Make a statement on whether the guideline value is likely to provide sufficient or insufficient protection for the environment if you do not have quantitative data on the relative toxicities of the AI and the commercial formulation.
Many chemicals, such as pesticides, are released into the environment as part of a commercial formulation.
Guideline values for such chemicals should be based on toxicity tests where the test organism was exposed to a reasonably pure form of the active ingredient (AI) — typically more than 70% — such as a technical grade form of the chemical.
In practice, you should compare the toxicities of the commercial formulation and the AI because other chemicals present may modify the toxicity of the AI.
When refining a guideline value based on the AI for local conditions, it will be important to take into account the toxicity of the commercial formulation to protect the environment from it. Any formulation toxicity data must have gone through a screening and quality assurance process before it can be used in this comparison.
If the toxicities of the commercial formulation and the AI differ by greater than a factor of 3, then it would be appropriate to correct the guideline value by the difference. The resulting formulation-corrected guideline value might be larger or smaller than the guideline value of the AI.
If you only have qualitative information on the relative toxicity of the AI and the commercial formulation, then you should make a statement on whether the guideline value is likely to provide sufficient or insufficient protection.
Express guideline values for AIs as a concentration of the AI (e.g. x µg AI/L).
If a toxicant has the potential to be bioaccumulative, the next most protective DGV than the one that would normally be applied based on the agreed ecosystem condition and associated level of protection should be applied (e.g. the 99% species protection DGV for slightly to moderately disturbed ecosystems instead of the 95% species protection DGV), unless:
the DGV is High or Very high reliability AND has been derived based on a significant proportion of (a) long-term mesocosm/field effects data, or (b) multigenerational laboratory toxicity data for a range of taxa (e.g. > 30% of the dataset and for > 3 taxa groups); or
a rigorous weight-of-evidence process has demonstrated that aquatic and terrestrial species are not experiencing harmful direct and indirect effects from the toxicant due to bioaccumulation, and the community values are being protected; or
a lower protection level interim target is agreed upon by stakeholders for a highly disturbed site where the higher protective level could not be attained in a reasonable timeframe.
In these three cases, the DGV relevant to the agreed ecosystem condition and associated level of protection can be used, subject to consultation with stakeholders, particularly regulators and the community.
As with all other toxicants, where the concentration of a potentially bioaccumulative toxicant is below the appropriate guideline value, then the over-riding objective should be to continue to improve, or at least maintain, water quality (i.e. not to allow increases in concentration up to the guideline value).
What is bioaccumulation?
According to Gobas et al. (2009), bioaccumulation is a process in which the concentration of a chemical in an organism achieves a level that exceeds that in the respiratory medium (e.g., water for a fish or air for a mammal), the diet, or both.
Bioaccumulation occurs by two main pathways: bioconcentration and biomagnification. Bioconcentration involves the absorption of a chemical substance exclusively from the ambient environment, i.e. through respiratory and dermal surfaces only (Arnot and Gobas 2006). Biomagnification relates exclusively to dietary intake of chemicals. It is defined as the process whereby pollutants are transferred from food to an organism resulting in higher concentrations in the organism compared with the source (Mann et al. 2011). Biomagnifying toxicants may also exhibit trophic magnification. Trophic magnification occurs when the concentration of the toxicant in organisms increases as it passes up two or more trophic levels in a food chain (Gobas et al. 2009).
Why do bioaccumulative toxicants require additional consideration?
Bioaccumulative–relative to non-bioaccumulative–toxicants may pose an increased risk of toxic effects to populations, due to an additional body burden and/or duration of exposure resulting from internal concentration of the toxicant. Bioaccumulative toxicants also present a risk of intergenerational effects, by maternal transfer of accumulated toxicants to offspring (Niimi 1983, Wanget al. 2015). Trophic magnification of toxicants threatens entire food webs, including higher trophic levels (i.e. top predators), within which tissue toxicant concentrations can be at their highest (Kelly et al. 2009). Some toxicants have the potential to biomagnify to concentrations that risk harmful effects across trophic levels (e.g. DDT, perfluoroalkylacids (PFAAs), dioxins, methyl-mercury). Trophic magnification threatens not only aquatic taxa, but also associated terrestrial taxa, e.g. birds that feed upon fish.
The DGVs are largely derived from single-species toxicity data that only account for direct effects of toxicants observed at the end of relatively short exposure durations. For bioaccumulative toxicants, such data are unlikely to capture toxicity caused as a result of longer-term bioaccumulation. The effects of bioaccumulative toxicants are best assessed using chronic field, mesocosm or microcosm data, or chronic laboratory toxicity data from tests carried out over multiple generations. Long-term chronic tests are best able to capture toxic effects of toxicants that bioaccumulate in tissues and manifest over longer timescales; multigenerational tests are best able to capture effects involving reproductive toxicity or maternal transfer of toxicants; and microcosm/mesocosm tests are best for detecting effects resulting from trophic magnification.
Which toxicants are bioaccumulative?
Bioaccumulation is typically measured in the field (Arnot and Gobas 2006). Toxicants considered 'bioaccumulative' for water respiring organisms (e.g. fish and macroinvertebrates) are those with log BAF (bioaccumulation factors) values ≥ 4. [Biomagnifying toxicants are those with a biomagnification factor (BMF) > 1 and trophically magnifying toxicants are those with a TMF (trophic magnification factor) > 1 (Gobaset al. 2009).]
BAFs are derived from field measurements of the ratio of the steady state chemical concentrations in an aquatic water-respiring organism and the water determined from sampled organisms exposed to a chemical in the water and in their diet (Gobaset al. 2009). They are considered to be reliable indicators of bioaccumulation. However, literature BAF values are often unavailable for toxicants (Arnot and Gobas 2006). Such toxicants may be deemed 'potentially bioaccumulative' based on indirect measures, e.g. (Gobaset al. 2009) where their:
log Kow (octanol–water partition coefficient) ≥ 4, or
log BCF (bioconcentration factor) ≥ 4.
However, the risks of applying these inferential approaches should be noted, especially for emerging contaminants such as per- and poly-fluoroalkyl substances (PFAS). Inferring a toxicant's potential to bioaccumulate from its log Kow, for example, assumes the toxicant concentrates in lipid tissue. This is true of many historic persistent organic pollutants, but does not apply to all toxicants. PFAS have a much higher affinity for proteins, hence their bioaccumulation potential cannot be reliably inferred from their log Kow values (Ng and Hungerbühler 2014). Similarly, log BCF values, by ignoring dietary intake, significantly underestimate the considerable bioaccumulation potential of many biomagnifying chemicals, e.g. perfluorooctane sulfonate (PFOS) (Gobaset al. 2009).
Field measurements of bioaccumulation, e.g. BAFs, BMFs and TMFs, should therefore be considered the most reliable indicators of a toxicant's bioaccumulation potential (above inferences based upon indirect measures such as log Kow and log BCF).
What is the GV approach for bioaccumulative toxicants?
If a toxicant has the potential to bioaccumulate, and the dataset used to derive its DGV did not include a significant proportion of (a) long-term mesocosm/field effects data, or (b) multigenerational tests where both bioaccumulation and ecologically relevant effects were measured (e.g. > 30% of the dataset and for > 3 taxa groups), we recommend using the 99% species protection DGV for slightly to moderately disturbed ecosystems instead of the 95% species protection DGV. Similarly, the 95% species protection DGV could be used for highly disturbed ecosystems instead of the 90% species protection DGV. A lower level of protection than this for highly disturbed sites is not recommended, due to the potential risks associated with bioaccumulative toxicants. However, a lower level of protection (e.g. 90% species protection DGV) could potentially be adopted as an interim target for a specified indicator only if it was evident and agreed by stakeholders, including regulators, that the 95% species protection DGV could not be attained in an acceptable timeframe (also see guidance on Level of protection for how to apply guideline values to highly disturbed ecosystems).
The recommended approach has no mechanistic basis with regards to bioaccumulation, and is recommended solely as a precautionary measure to minimise the risks from bioaccumulative substances. A more mechanistically-based approach may involve, for example, the future development of tissue residue guidelines (ANZECC & ARMCANZ 2000, pp. 8.3–17 to 20).
If, through a rigorous weight of evidence process, it can be shown that aquatic and terrestrial species are not experiencing harmful direct and indirect effects from the toxicant due to bioaccumulation at concentrations of the DGV that would normally have been applied based on the agreed ecosystem condition (e.g. the 95% species protection DGV for slightly to moderately disturbed ecosystems), and the community values are being protected, then this should be sufficient to support a corresponding change back to that DGV. Such decisions should always be made in consultation with regulators and the community and in accordance with the guidance on levels of protection for aquatic ecosystems.
Finally, the over-riding principle of continual improvement dictates that, where the concentration of a contaminant is below the appropriate guideline value, then the over-riding objective should be to continue to improve, or at least maintain, water quality (i.e. not to allow increases in concentration up to the guideline value).
For additional context and guidance on how to deal with bioaccumulation, refer to:
Warne et al. (2018) toxicant guideline value derivation method
ANZECC & ARMCANZ (2000) Section 8.3.3.4 background to incorporating bioaccumulation into guidelines values.
Science has progressed since ANZECC & ARMCANZ (2000), and some of the guidance may be outdated. Further guidance on guideline values that incorporate the impacts of bioaccumulative substances may need to be developed in the future.
Transient exposures
If site-specific transient exposures are known to occur, and the DVGs are considered overly-protective, follow guidance provided in Batley et al. (2018) and Warne et al. (2018) to derive your own short-term guideline values.
Transient or short-term exposures of aquatic biota to toxicants can occur for various reasons, such as:
highly volatile or hydrophobic toxicants that are rapidly lost from the water column
toxicants with very short half-lives
toxicants present in episodic or intermittent discharges (e.g. mine water discharges, stormwater discharges, pesticides in waterways draining agricultural land).
The current DGVs may not be relevant to such exposures but would at least be likely to be over-protective.
Short-term exposure DGVs have not as yet been derived for Australia and New Zealand. Such DGVs are focused at ensuring that short-term acutely toxic events do not occur and, as such, are often derived from acute EC/LC50 data.
Concentrations at which acute toxicity is likely to occur may not necessarily bear resemblance to the concentrations that should protect against transient exposure. This is because some toxicants are known to cause delayed effects after transient exposures have ceased.
Where site-specific transient exposures are known to occur, and the DGVs are considered to be inappropriate, Batley et al. (2018) and Warne et al. (2018) provided guidance on how to derive short-term guideline values.
Importantly, the exposure regime used to derive the toxicity data should be as similar as possible to the exposure regime being considered. This includes how frequently the pulses occur, the likely period needed for recovery and the cumulative effect of repeated pulses. If pulses are frequent with minimal recovery period it may be more appropriate to use the DGVs.
A useful example of the development of transient exposure guideline values is provided in the case study for the assessment of mine water discharges from Ranger uranium mine.
Additional details of research completed to develop these guideline values can be found in Hogan et al. (2013), Sinclair et al. (2014) and Prouse et al. (2015).
Locally important ecosystems or species
Where water quality characteristics or species composition at a site vary markedly from those used to derive the DGV, or there are locally important species at a site, it may be warranted to derive site-specific guideline values using toxicity data for local species.
When developing site-specific guideline values for toxicants based on toxicity data from local species in local waters, take care when making decisions about exclusion or inclusion of data used in the derivation method.
Whilst site-specific guideline values should be developed for specific issues and locations, it is not always going to be practicable or necessary.
Local ecosystems or species are sometimes deemed so ecologically, economically or culturally important that we need assurance the guideline values will protect them enough.
A good example of this is the need to ensure that the highly valued aquatic ecosystems of Kakadu National Park are protected from the impacts of uranium mining. Because of these high ecological and cultural value ecosystems, much effort has been invested in deriving site-specific guideline values for toxicants of concern based on toxicity data from local species in local waters.
An example is provided in the case study for the assessment of mine water discharges from the Ranger uranium mine. Additional details can be found in van Dam et al. (2010), Hogan et al. (2013), Harford et al. (2015) and van Dam et al. (2017).
When incorporating local species toxicity data, take care when excluding or including the original data used in the DGV derivation (if it exists).
This decision often becomes a trade-off between sample size (number of values used to derive the DGV) and relevance of the data to the ecosystem and species of interest. Considerations include whether the species and type of water quality used to assess toxicity of the toxicant in question are sufficiently representative of those for the ecosystem of interest. The requirements for data quality and quantity, including taxonomic representation, always need to be met. Seek expert guidance to help with making decisions about inclusion or exclusion of data.
Refer to relevant background information provided in ANZECC & ARMCANZ (2000) Section 8.3.5.8.
Summary of recommended actions
When mixtures of chemicals are present in a water body, in the first instance you should estimate the combined toxicity of all the chemicals using the concentration addition method. More environmentally realistic methods of estimating the combined can also be used in higher tier analyses.
Even though the DGVs are based on data from toxicity tests for single toxicants, it is well known that toxicants rarely occur in isolation. In most circumstances, a particular toxicant will be present in combination with numerous other toxicants, and their combined presence may alter their toxicity. There are numerous terms for the various joint toxicities of mixtures, but at their simplest, mixtures of toxicants (Rand 1995) can result in:
additive toxicity (sum of the toxicity of the individual components)
greater than additive toxicity (also known as 'synergism'), or
less than additive toxicity (also known as 'antagonism').
The brief guidance provided here is generally reflective of that provided in ANZECC & ARMCANZ (2000) Section 8.3.518.
A thorough review of the science of mixture toxicity and associated methods for its assessment is beyond the scope of the Water Quality Guidelines but is likely to be necessary in the future if updated guidance on dealing with multiple stressors is to be provided.
A number of reviews on mixture toxicity and associated methods of assessment since the ANZECC & ARMCANZ (2000) guidelines (e.g. de Zwart & Posthuma 2005, Cedergreen 2014, Liu et al. 2017) suggest that its guidance is still applicable.
Cedergreen (2014) concluded that true synergistic interactions between chemicals are rare, and that addressing the cumulative rather than synergistic effect of co-occurring toxicants was the most important step in assessing the effects of toxicant mixtures.
Similarly, Liu et al. (2017) found that statistically significant deviations from additivity are not necessarily biologically relevant for metal mixtures and, as such, recommended to first use a relatively simple method for effect prediction of un-investigated metal mixtures.
Two types of models are most often used to predict mixture toxicity:
concentration addition model of joint action — applied to mixtures with toxicants that have the same mode of action
response addition model of independent action — applied to mixtures with toxicants that have different modes of action.
If we assume toxicity conforms to the concentration addition model (it is additive), then significant combined effects could be expected if all toxicants in a mixture are present at close to their DGVs.
You can determine whether or not a mixture exceeds a collective water quality guideline value using the formula (modified from Vighi & Calamari 1996):
TTM = Σ(Ci / WQGi)
where TTM is the total toxicity of the mixture, Ci is the concentration of the 'i'th toxicant in the mixture and WQGi is the guideline for that toxicant.
If TTM exceeds 1, the mixture has exceeded the collective water quality guideline value.
The ANZECC & ARMCANZ (2000) guidelines stated that this method should only be applied to mixtures of up to 4 components. It is now recommended that this method be applied irrespective of the number of components in the mixture.
A number of studies have shown that the concentration addition model consistently predicts higher toxicity (and hence is more environmentally protective) than the response addition model (e.g. Faust et al. 1994, Backhaus et al. 2000, Chevre et al. 2006). This has led to the accepted practice of using the concentration addition model as a first step in estimating the toxicity of mixtures.
A more accurate estimate can be provided using a 2-step method (e.g. Altenburger et al. 2004, De Zwart and Posthuma 2005), which applies the concentration addition model to chemicals with the same mode of action, but then uses the response addition model to estimate the toxicity of groups of chemicals with different modes of action.
The best experimental method to account for the toxicity of mixtures is DTA of the mixture, which may be an effluent or ambient water. Refer to details in The best experimental method to account for the toxicity of mixtures is DTA of the mixture, which may be an effluent or ambient water. Refer to details in our guidance on DTA.
Using multiple lines of evidence
So far our discussion concerns the assessment of the chemistry line of evidence for evaluating compliance with guideline values. But it is important that compliance with guideline values is considered as one of a number of lines of evidence that may be used when assessing water quality (as part of a weight-of-evidence process). These lines of evidence could include monitoring or assessment of other pressures, stressors (e.g. habitat, flow) and ecosystem receptors.
Ultimately, it is biological measurement of relevant ecosystem receptors that will provide confirmation that water quality at a site is not being affected.
If the guideline value is exceeded or there is low confidence in desktop assessments (e.g. difficulty in modelling metal speciation), then you should opt for DTA or biodiversity assessment as an additional line of evidence. Additional evidence can be obtained from measurements of bioaccumulation.
The toxicity line of evidence could specifically deal with cases where chemical mixtures modify toxicity from that based on the additivity of individual toxicant effects. This will also be of use where the protection of locally important species is a concern.
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Information for Spear of Longinus, a usable item in Arena of Valor (AoV). Included are its effects, unique passives and/or actives, price, and item tree. We also measure effect ranges, explain any ambiguous effects, and give our recommendations on how to use the item.
These are Spear of Longinus' attributes on the mobile version of Arena of Valor. Click here for its attributes on the Nintendo Switch version.
Unique Passive(s) Shatter: Decreases target armor by 50 on hit for 5 seconds. Stacks up to 5 times.
1: Any damage taken from any ability will trigger Shatter. For example, a single cast of Zephys' Death's Flurry or Ormarr's Walking Tall can trigger all five stacks. Abilities that enhance attacks, like Arthur's Righteous Fervor, automatically stack twice.
2: Unlike Veera's passive, the armor reduction is applied after damage calculation rather than before.
This item gives your beefy front liners the ability to weaken the opposing tanks while improving their own tankiness at the same time. Spear of Longinus' wielder's normal attacks and abilities remove enemies' armor, effectively giving your entire team a pierce effect (read more about calculating pierce damage or how pierce percentages are calculated). Its high cooldown reduction also allows its wielder to cast their abilities more consistently.
Generally warriors and front liners who deal physical damage like Ormarr, Thane, and Arthur (surprisingly, we found in testing that Ormarr's Unstoppable consistently removed 150 armor in one hit, though we're not sure if that's intended). An enemy can not go above five stacks of armor reduction, even if multiple heroes on the team use the item. As a result, check your teammates' items before blindly purchasing the spear.
Rankbreaker and Spear of longinus stack?
Yes, all armor pierce items stack with one another.
Question, does the burning damage from the Mantle of Ra/Leviathan trigger the armor reduction? Same question for mail of pain and other damaging items.


rd47blog: "Hopi Navajo Dispute, Arab Jew Dispute"
"Hopi Navajo Dispute, Arab Jew Dispute"
The never ending battle in the middle east. Can be compare to, the same battle. Going on in the American southwest. The Hopi and the Arabs, where the first to live on their embattled lands. The Jews, who will never have a permanent home because. They have the same problem the Navajo have. Both where wandering peoples. Both are ruthless and soulless. The Navajo never where meant to be farmers, living in one place. The Jews where never meant to be, farmers living in one place. They both prefer to let others, do the hard work. While they both, watch from the side lines and invade. When the crops are ready for harvest. America's wealth was created by the hard working citizens. Not the Jews (Zionist) hard work. The Zionist of today are also. Destroying the very folks, who labored their hearts out. To make America, what it is today. The same can be said for the Navajo. The Navajo's like the Jews are wanders. The Hopi are a passive type. Just like most of the their, hard working American, counter part. Both are under attack from, uncivilized lower forms of humanity. Both their enemies, have no real "God". And are awaiting their "God's" arrival. Both are ruthless murders, as their pasts have shown. And now both want something that belongs to others. The Navajo would go on murderous raids against the tribes of the southwest. The Jews do the same thing to their neighbours. Neither group will ever have souls. Their DNA is far to inter twined and dead. This is the reason they are both so heartless. The American system has tried to paint both as loving caring tribes. (Navajo, Jewish) The Jews want to believe, that the Hopi are their long lost brothers in the west. When in reality, their long lost white brother, is the Navajo. The Navajo and Jews, are just to similar, for this not to be true. The Navajo have always been hated by, other tribes from the southwest. The Jews have always been hated by everyone, they have ever associated with. What does this say, about their tribes? Everything!!!
Here is another good comparison, between the Hopi and Navajo. And America, as it stands today. America was built on a protestant belief system. Supreme Court today, has only one protestant member. The rest are made up of, six Catholics and two Jews. America was once dominated by the Hopi. Now has only a population of approximately 7,000 Hopi. While the Navajo counter part, has grown to over a million. The Hopi reservation is tiny and surrounded by Navajo reservation. With Old Oribia, (Jerusalem too, both tribes) being smack dab, in the middle. The Zionist surround congress, with their Zionist lobbyists.
Since my last letter home. The Crop Circle continue to get more and more sophisticated. It is easy to tell, that someone is trying to warn someone else. Leading some scientist to believe that 7 July 09. Will bring a giant explosion on the Sun, on that date. A Solar Flare so large, it will effect life on Earth for ever. You can go to NASA site and see the activity. Now they are classified as a type 'B' Solar Flare. Others believe this is just a precursor, for larger things to come. The Mayans understood the significance of the Solar Flare and their cycles. The Mayan believed the DNA up grades, came from the Sun. So rite in line with the coming of 2012. Is this the coming Solar Event, to do just that? Bring the change the Mayans and many other ancient cultures always talked of? I've rarely talked to any one over 30 years old. Who doesn't feel something in the air. All agree, "Time" has been speeded up. One thing for sure, two Cats and a board. Aren't creating the incredible formation, now or ever.
This is illiterate, antisemitic garbage.
One would hope that there are Navajo that rise above this.


That was a dark twist! And I loved how you drew us in to sympathize with the narrator, only to have her take such a dark path.
Thank you, I'm happy to hear you enjoyed it!
Nicely done. A solid twist!
Oh dear! Makes me wonder a bit at what in her own life she's so willing to leave behind in order to take over for her sister. Clearly not a healthy relationship… heh.
Not at all 😈 Thanks for your comment!


text:
Resident Crews of the Mir
Mir: Expedition 19
(EO-19)
hi res version (493 KB)
alternate crew photo
Crew, launch- and landing data
No. Nation Surname Given names Position Spacecraft
(launch) Launch
date Launch
time Spacecraft
(landing) Landing
date Landing
time Mission
duration Orbits
1 Soloviyov Anatoli Yakovlevich Commander STS-71 27.06.1995 19:32:18.988 UTC Soyuz TM-21 11.09.1995 06:52:40 UTC 75d 11h 20m 21s 1194
2 Budarin Nikolai Mikhailovich Flight Engineer STS-71 27.06.1995 19:32:18.988 UTC Soyuz TM-21 11.09.1995 06:52:40 UTC 75d 11h 20m 21s 1194
Backup Crew
No. Nation Surname Given names Position
1 Onufriyenko Yuri Ivanovich Commander
2 Usachyov Yuri Vladimirovich Flight Engineer
Expedition Report
Launch from Cape Canaveral (KSC).
The primary objectives of this flight were to rendezvous and perform the first docking between the Space Shuttle and the Russian space station Mir on June 29, 1995. In the first U.S.-Soviet docking in twenty years, Atlantis delivered a relief crew of two cosmonauts Anatoli Soloviyov and Nikolai Budarin to Mir.
Other prime objectives were on-orbit joint United States of America-Russian life sciences investigations aboard SPACELAB/Mir, logistical resupply of the Mir and returning of US astronaut Norman Thagard.
STS-71 marked a number of historic firsts in human spaceflight history: the 100th U.S. human space launch conducted from the Cape; first U.S. Space Shuttle-Russian space station docking and joint on-orbit operations; largest spacecraft ever in orbit; and the first on-orbit changeout of a Shuttle crew.
STS-71's rendezvous and docking with the Russian space station Mir actually began with the precisely timed launch of Atlantis on a course for the station. Over the next two days, periodic small engine firings gradually brought Atlantis to a point eight nautical miles behind Mir. At that time, on the third day of the flight, a Terminal Phase Initiation (TI) burn was fired, and the final phase of the rendezvous began. Atlantis closed the final eight nautical miles to Mir during the next 90-minute orbit.
As Atlantis moved in, the Shuttle's rendezvous radar system began tracking Mir and provided range and closing rate information to the Shuttle crew. As Atlantis neared Mir, the Trajectory Control Sensor, a laser ranging device mounted in the payload bay, supplemented the Shuttle's onboard navigation information by supplying additional data on the range and closing rate.
Docking occurred at 13:00 UTC, June 29, 1995, using R-Bar or Earth radius vector approach, with Atlantis closing in on Mir from directly below. R-bar approach allows natural forces to brake the orbiter's approach more than would occur along standard approach directly in front of the space station; also, an R-bar approach minimizes the number of orbiter jet firings needed for approach. The manual phase of the docking began with Atlantis about a half-mile (800 m) below Mir, with Robert Gibson at the controls on aft flight deck. Stationkeeping was performed when the orbiter was about 75 meters (246 ft) from Mir, pending approval from Russian and U.S. flight directors to proceed. Robert Gibson then maneuvered the orbiter to a point about 10 meters (33 ft) from Mir before beginning the final approach to station. Closing rate was close to the targeted 0.1 foot per second (30 mm/s), being approximately 0.107 foot per second (33 mm/s) at contact. Interface contact was nearly flawless: less than 25 millimeters (0.98 in) lateral misalignment and an angular misalignment of less than 0.5 degrees per axis. Docking occurred about 216 nautical miles (400 kilometers (250 mi)) above Lake Baikal region of the Russian Federation.
Docking began when the orbiter was maneuvered to bring the interfaces of the active docking mechanism in contact with Mir's passive mechanism. At this point, the maximum allowable axial rate of approach of the two vehicles was 0.2 foot per second (6 centimeters per second). Minor misalignments of the two mechanisms of up to eight inches and five degrees were corrected as the orbiter interface was displaced and rotated so the capture ring could latch onto the opposing androgynous interface ring. This rotation was produced by the relative velocity of the two vehicles.
Soft latching occurred when the capture ring alignment was complete and the interfaces were aligned. Each of the petals on Atlantis' APAS was equipped with two capture latches. The capture latch assemblies, which operated independently, grapple body mounts on the Mir APAS.
Five seconds after capture, dampers designed to reduce relative vehicle motion were activated for 30 seconds. Before the dampers were activated, a load-limiting clutch prevents either vehicle from being overloaded. The dampers were deactivated to allow the dampers to align the vehicles.
After the relative motion of the two vehicles had subsided, the retraction phase of the docking process then began. During this phase, the latched capture ring and passive vehicle were pulled into the orbiter mechanism. The five engaged fixators made the capture ring rigid and prevent relative vehicle misalignments from accumulating during retraction.
Structural latching occurred at the completion of the capture ring retraction process. Twelve active structural latches located at the structural interface are grouped into two separate activated gangs of six latches each. A passive, immobile hook is located next to each active latch. The Mir mechanism also had these latches and hooks. In the process of structurally latching the orbiter and Mir, latch actuator motors deployed the orbiter's active latches, which hooked onto Mir's passive hooks. The actuator drives the first hook directly, and a cable transmitted power to the remaining five slave hooks. The hooks were driven beyond the point where the hook was overcenter. The overcenter hooks carried the sealing load, rather than the cables. Mir's active latches could also be used to hook onto the orbiter's passive hooks as a backup procedure. The entire docking process was completed in less than one hour. The final portion of the process, after capture, took approximately 15 minutes.
Atlantis and Mir were linked by an orbiter docking system (ODS). The $95.2-million orbiter docking system consisted of an external airlock, a supporting truss structure, a docking base, avionics required to operate the system, and a 632-pound (286.7 kg) Russian-built docking mechanism, called the androgynous peripheral assembly system (APAS), which was mounted on top of the airlock and docking base.
Atlantis received extensive wiring changes to accommodate the new system, which measured nearly 15 feet (4.57 meters) wide, 6-½ feet (1.98 meter) long, and 13-½ feet (4.11 meters) high and weighed more than 3,500 pounds (1,587 kg). It was installed near the forward end of the orbiter's payload bay and was connected by short tunnels to the existing airlock inside the orbiter's pressurized crew cabin and the pressurized Spacelab module, which was aft of the airlock in the payload bay. The ODS worked flawlessly during the docking sequence.
The APAS was a hybrid version of the docking system the Russians used in 1975 for the Apollo-Soyuz Test Project. It differed from its predecessor in several key respects. First, it was much more compact, with an overall external diameter of 60 inches (152 centimeters) compared to 80 inches (203 centimeters) on ASTP, although the inner egress tunnel diameter remained approximately the same. Second, the APAS docking mechanism had 12 structural latches, compared to eight on the ASTP. Third, the APAS guide ring and its extend/retract mechanism were packaged inside the egress tunnel rather than being outside of the mechanism as they were on ASTP. Finally, the three guide petals on the APAS pointed inboard rather than outboard.
Both Atlantis and Mir were equipped with an APAS, which consisted of a three-petal androgynous capture ring mounted on six interconnected ball screw shock absorbers, which operated like a sophisticated car suspension system. The absorbers arrested the relative motion of the two vehicles and prevented them from colliding.
When linked, Atlantis and Mir formed the largest spacecraft ever in orbit, with a total mass of about 225 metric tons (almost one-half million pounds), orbiting some 218 nautical miles (404 kilometers (251 mi)) above the Earth. After hatches on each side opened, STS-71 crew passed into Mir for a welcoming ceremony.
With the Russian and U.S. flags as a backdrop, the STS-71 and Mir crews exchanged gifts on flight day four in the Shuttle's Spacelab module. Gifts included a halved pewter medallion bearing a relief image of a docked Shuttle and Mir space station; the two halves were joined during the ceremony. A 1/200th-scale model of the Shuttle and the Mir also was joined. These gifts were presented to the U.S. and Russian Heads of State and the leaders of the two space agencies after the mission.
For five days, about 100 hours in total, joint U.S.-Russian operations were conducted, including biomedical investigations, and transfer of equipment to and from Mir. Fifteen separate biomedical and scientific investigations were conducted, using the Spacelab module installed in the aft portion of Atlantis's payload bay, and covering seven different disciplines: cardiovascular and pulmonary functions; human metabolism; neuroscience; hygiene, sanitation and radiation; behavioral performance and biology; fundamental biology; and microgravity research. The Mir-18 crew served as test subjects for investigations. Three Mir-18 crew members also carried out an intensive program of exercise and other measures to prepare for re-entry into gravity environment after more than three months in space.
Numerous medical samples as well as disks and cassettes were transferred to Atlantis from Mir, including more than 100 urine and saliva samples, about 30 blood samples, 20 surface samples, 12 air samples, several water samples and numerous breath samples taken from Mir-18 crew members. Also moved was a broken Salyut 5 computer. Transferred to Mir were more than 450 kilograms (990 lb) of water generated by the orbiter for waste system flushing and electrolysis; specially designed spacewalking tools for use by the Mir-19 crew during a spacewalk to repair a jammed solar array on the Spektr module; and transfer of oxygen and nitrogen from Shuttle's environmental control system to raise air pressure on the station, to improve Mir's consumables margin.
Joint scientific investigations by the two premier spacefaring nations continued with the flight of STS-71, the Spacelab-Mir mission, providing more knowledge about the human body and the microgravity environment. Research in seven different medical and scientific disciplines begun during Mir-18 was concluded on STS-71. Of the 28 experiments being conducted as part of the joint United States-Russian cooperative effort, 15 was performed as part of the STS-71 mission.
The metabolic research on STS-71 included studies of the cardiovascular and pulmonary systems; neurosensory research; hygiene, sanitation, and radiation research; behavior and performance research; fundamental biology research; and microgravity research.
Deconditioning of the cardiovascular and pulmonary system, with the occurrence of orthostatic intolerance (or lightheadedness upon standing) observed in returning crew members of long duration spaceflight is of primary interest to researchers. Researchers measured changes in blood volume during flight and the pooling of blood in the legs and abdomen upon reentry.
Investigations in neurosensory research begun during Mir-18 focused on the mixed messages the body receives when the brain integrates nerve impulses from the eyes, inner ear, muscles and joints. The brain can no longer rely on gravity as a constant in determining body position and orientation. Two of these studies seek to enhance our understanding of how humans adapt to spaceflight and readapt to Earth's environment.
Two investigations in hygiene, sanitation, and radiation research looked at the radiation environment experienced during an extended stay in space, and two others looked at the presence of microbes or trace chemicals found in the air and water consumed by the astronauts.
Data from tests to study the long-term effects of microgravity on muscle coordination and mental acuity, collected during more than three months on Mir-18, were returned to Earth aboard Atlantis. A Russian spacecraft control simulator used before, during and after flight, allowed researchers to measure crew member's functional state and manual control performance.
STS-71 studied how weightlessness affects embryo development by returning to Earth a set of pre-fertilized quail eggs incubated on board Mir. The incubation process was stopped at various stages of development, and the embryos placed in a fixative solution for later analysis. Improved sensors were carried to orbit by Atlantis to be added to the Mir station greenhouse by the Mir-19 crew. The updated greenhouse then was ready for plant experiments on future NASA-Mir missions.
STS-71 carried several hundred protein samples, frozen in a thermos-bottle-like vacuum jacket or dewar, to the Mir space station. After they thaw, the proteins crystallized until the dewar is retrieved by the STS-74 crew in November 1995.
The months-long growing time aboard Mir should produce large protein crystals of sufficient size and quality to compare with corresponding crystals grown in Earth-based laboratories. The Mir experiment was used to evaluate the effectiveness of flash-frozen bath and liquid-liquid diffusion techniques for growing protein and virus crystals on long-duration space missions. Experience gained will help shape PCG investigations to be conducted aboard the International Space Station.
The Mir resident crew was exchanged. Anatoli Soloviyov and Nikolai Budarin became the 19th resident crew. The former 18th resident crew (Vladimir Dezhurov, Gennadi Strekalov, Norman Thagard) returned to Earth with STS-71.
After over 100 hours of docked operations, the hatches were closed on both Atlantis and the Mir, and the vestibule in the Shuttle's docking system was depressurized. The initial separation was performed by springs that slightly pushed the Shuttle and the Mir away from each other on a command sent to the docking mechanism from an aft flight deck control panel in Atlantis. Both the Mir and Atlantis were in a mode called "free drift" during the undocking, a mode that has the steering jets of each spacecraft shut off to avoid any inadvertent firings.
STS-71 left Mir on July 04, 1995.
The separation of STS-71 was observed from the also separated Soyuz spacecraft.
The first EVA was performed by Anatoli Soloviyov and Nikolai Budarin on July 14, 1995 (5h 34m). The cosmonauts repaired the solar array and they inspected the exterior of the space station. They discovered no pollution or damages on the outside of the docking mechanism of the -Z axis. They deployed the jammed solar array on Spektr with the exception of 1 section. The solar array has now been included in the power supply system of the complex. They also worked at a solar array of Kvant2 and an antenna.
Module Kristall was moved from the forward port (-X axis) to the side port (-Z axis) on July 17, 1995 between 02:30 and 04:00 UTC. The redocking took place by the use of the 'lyappa'. a manipulator arm. So Kristall was now in the right position to receive the Atlantis (STS-74) and the new docking module in October 1995. On July 17, 1995 Anatoli Soloviyov reported that the airseal of the system after the redocking was normal.
Anatoli Soloviyov and Nikolai Budarin went out of Mir to conduct the second spacewalk on July 19, 1995 (3h 08m). The cosmonauts did not accomplish their tasks and the EVA was shorter than planned. The thermoregulation in the spacesuit of Anatoli Soloviyov was not working normally. He got orders to remain in the hatch of the airlock and observe the activities of his crew mate. Nikolai Budarin did some preparations for the installation of the Belgian MirAS experiment and brought back some materials from Mir's outer surface.
The third and final EVA occurred on July 21, 1995 (5h 50m). The main task of the crew consisted of the installation of the Belgian Spectrometer, MirAS, on the outer surface of the Spektr module. The EVA was a success. During the EVA the geostationary satellite Altair (west) has not been used during all possible windows and if so only for voice communications. The recorded images have been transmitted to Earth after the EVA.
The freighter Progress M-28 blasted off from Baikonur on July 20, 1995 at 03:04:40 UTC for a 2-days flight to the Mir space station. The vessel docked with Mir's front port on July 22, 1995 at 04:39:37 UTC, undocked on September 04, 1995 at 05:09:53 UTC and was destroyed in reentry on September 04, 1995 at 08:58:55 UTC.
Soyuz TM-22 with the Mir-20 crew was launched from Baikonur on September 03, 1995 at 09:00 UTC. Soyuz TM-22 carried the relief crew to the Mir station together with the ESA astronaut, the German, Thomas Reiter. The Russian crew consisted of the Mir Commander Yuri Gidzenko, who made his first spaceflight, and Flight Engineer Sergei Avdeyev, who already made one spaceflight. Soyuz TM-22 docked with Mir's front (-X) port at 10:29:54 UTC on September 05, 1995 and the hatch was opened at 11:01:23 UTC.
The Soyuz spacecraft is composed of three elements attached end-to-end - the Orbital Module, the Descent Module and the Instrumentation/Propulsion Module. The crew occupied the central element, the Descent Module. The other two modules are jettisoned prior to re-entry. They burn up in the atmosphere, so only the Descent Module returned to Earth.
Having shed two-thirds of its mass, the Soyuz reached Entry Interface - a point 400,000 feet (121.9 kilometers) above the Earth, where friction due to the thickening atmosphere began to heat its outer surfaces. With only 23 minutes left before it lands on the grassy plains of central Asia, attention in the module turned to slowing its rate of descent.
Eight minutes later, the spacecraft was streaking through the sky at a rate of 755 feet (230 meters) per second. Before it touched down, its speed slowed to only 5 feet (1.5 meter) per second, and it lands at an even lower speed than that. Several onboard features ensure that the vehicle and crew land safely and in relative comfort.
Four parachutes, deployed 15 minutes before landing, dramatically slowed the vehicle's rate of descent. Two pilot parachutes were the first to be released, and a drogue chute attached to the second one followed immediately after. The drogue, measuring 24 square meters (258 square feet) in area, slowed the rate of descent from 755 feet (230 meters) per second to 262 feet (80 meters) per second.
The main parachute was the last to emerge. It is the largest chute, with a surface area of 10,764 square feet (1,000 square meters). Its harnesses shifted the vehicle's attitude to a 30-degree angle relative to the ground, dissipating heat, and then shifted it again to a straight vertical descent prior to landing.
The main chute slowed the Soyuz to a descent rate of only 24 feet (7.3 meters) per second, which is still too fast for a comfortable landing. One second before touchdown, two sets of three small engines on the bottom of the vehicle fired, slowing the vehicle to soften the landing.
Soyuz TM-21 landed on September 11, 1995 at 06:52 UTC with the crew of Nikolai Budarin and Anatoli Soloviyov aboard.
EVA data
Name Start End Duration Mission Airlock Suit
EVA Budarin, Nikolai 14.07.1995, 03:56 UTC 14.07.1995, 09:30 UTC 5h 34m Mir-19 Mir - Kvant2 Orlan-DMA No. 18
EVA Soloviyov, Anatoli 14.07.1995, 03:56 UTC 14.07.1995, 09:30 UTC 5h 34m Mir-19 Mir - Kvant2 Orlan-DMA No. 27
Relocations of Manned Spacecrafts
Spacecraft from Undocking Time UTC to Redocking Time UTC
Soyuz TM-21 Mir - Kvant 04.07.1995 10:55:01 Mir - Kvant 04.07.1995 11:38:12
Photos / Graphics
Last update on May 22, 2021.

redpajama_set_name: RedPajamaCommonCrawl


text:
Erik Lykke Mortensen
Øster Farimagsgade 5, 05 Øster Farimagsgade 5, Building: 05-2-06B
elme@sund.ku.dk
https://www.ifsv.ku.dk/afdelinger/ms/
Web Track 2: Retirement and transitions
On the relation between demographic variables and neuropsychological test performance
Mortensen, Erik Lykke & Gade, Anders, Dec 1993, In: Scandinavian Journal of Psychology. 34, 4, p. 305-317 13 p.
A Wais Longitudinal Study of Cognitive Development During The Life Span From Ages 50 To 70
Mortensen, Erik Lykke & Kleven, M., 1 Apr 1993, In: Developmental Neuropsychology. 9, 2, p. 115-130 16 p.
The interrelationship of weight loss, dietary intake, and quality of life in ambulatory patients with cancer of the lung, breast, and ovary
Ovesen, Lars, Hannibal, J. & Mortensen, Erik Lykke, 1993, In: Nutrition and Cancer. 19, 2, p. 159-67 9 p.
Effect of dietary counseling on food intake, body weight, response rate, survival, and quality of life in cancer patients undergoing chemotherapy: A prospective, randomized study
Ovesen, Lars, Allingstrup, L., Hannibal, Jens, Mortensen, Erik Lykke & Hansen, Ole, 1993, In: Journal of Clinical Oncology. 11, 10, p. 2043-2049 7 p.
The Prenatal Development Project
Reinisch, J. M., Mortensen, Erik Lykke & Sanders, S. A., Apr 1993, In: Acta Psychiatrica Scandinavica. 87, 370 S, p. 54-61 8 p.
Ramadan model of intermittent fasting for 28 d had no major effect on body composition, glucose metabolism, or cognitive functions in healthy lean men
Trends in adult body-mass index in 200 countries from 1975 to 2014: A pooled analysis of 1698 population-based measurement studies with 19.2 million participants


How to disable the two-factor authentication in Instagram?
Google Authenticator For Other Websites ?
WhatsApp is rolling out the PIP mode for Android today!
WhatsApp introduced Picture-in-Picture (PIP) mode to watch streamable videos without leaving the app. While the PIP mode is not yet made available through the regular app; you can get it through through the latest WhatsApp beta app.
With this new feature, the user can watch streamable videos from the popular sites including Youtube, Facebook, Twitter, Instagram, and others.
The user no longer needs to leave the app to watch videos and can even scroll through the chat while watching the videos in PIP mode. However, the PIP video will disappear when you leave that particular chat.
As of now, the new PIP feature is exclusive to Android OS. When the PIP feature on Android comes out of the beta, it might also be introduced in the iOS version.
Since today, WhatsApp is rolling out for all Android users (having Android 4.4 and newer) the Picture in Picture feature!
Also Read: Is Mi Band 3 really worth upgrading to?
Unfortunately, when you switch to another chat, the PiP disappears. This doesn't happen on iOS, so we count to see an update for Android that will fix this small issue.
You need to update your WhatsApp version to the 2.18.301 Android beta update, in order to use the Picture in Picture mode.
Every time you reinstall WhatsApp, the most updated configurations from the server are downloaded, enabling the feature for you.
← Is Mi Band 3 really worth upgrading to?
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Start with the right drain.
The better and more efficient your drain, the less chance you have of drain buildup. Shop the selection of bathroom and bathtub faucets and bathtubs and shower fixtures at Modern Bathroom, and find options that make it harder for clogs to occur.
Stop large clumps of hair or soap from falling down the drain by setting a screen or grate over the opening. Today's market has options for every fixture — including drains for bathtubs or vanity sinks. Set it in place and pull out the items that get caught regularly.
If you can get into the habit, run hot water through your sink after each use. Hot water can help any oils caught in your drain move rather than build up and cause clogs.
Shake in some baking soda.
Once a month or so, throw a handful of baking soda in your sink drain and chase it with a kettle full of hot water. Baking soda is a powerful odor absorber and cleaning agent, which may help prevent drain buildup.
The acidic nature of vinegar makes it a great tool for removing the crud that builds up in your pipes. Pour a cup of it down the drain, wait a half-hour, and pour in some extremely hot water.
Pull out the big guns for clogs.
If you notice a clog in your drain, act quickly. Pour a 1/2 cup each of salt and baking soda down the drain, and follow it with a 1/2 cup of vinegar. This combination will foam a little. Wait a minute and pour in 2 quarts of boiling water. Nobody likes clogged bathroom drains — but the good news is, they can be prevented with a few basic habits. Implement the six suggestions above to protect your pipes and keep water freely flowing at home!
Whether you cut your finger or skin your knee, you shouldn't have to waste time trying to find your first-aid supplies. Keep them in your bathroom cabinet so they're always at the ready for emergencies.
Most people know what it's like to wake up in the middle of the night with a throbbing headache. Save yourself the extra steps of trekking to the kitchen, and keep over-the-counter pain medication in your bathroom cupboard.
Another common malady is a stomachache. Be prepared for indigestion when it strikes, and keep antacids in your bathroom stash, too.
You never know when the common cold is coming, so be ready for it with basic cold medicine in your bathroom. Keep cough medicine, a decongestant and throat lozenges as staples.
If you're coming down with the flu or are just feeling funny, having a thermometer is a must. Keep it in your bathroom cabinet so you always know where to find it when illness arrives.
The only thing worse than dealing with an allergic reaction is not being prepared to treat it. Keep antihistamines and hydrocortisone cream on hand, as well as calamine lotion, so you can respond to any allergic or itching issues that arise.
In a world where skin cancer is rampant, it's hard to be too careful about sun protection. Store sunscreen in your medicine cabinet so it's easy to shield your skin from UV damage.
A healthy mouth starts with good oral hygiene. Stock a toothbrush, plus an extra or two in case an overnight guest needs one. Likewise, have toothpaste, floss and mouthwash available.
Whatever you use to get ready each day, keep it supplied and organized in your bathroom. This includes makeup, hair products, moisturizers, shaving cream, etc.
Even if you don't use cotton swabs and cotton balls every day, it's nice to have them available. Likewise, stash feminine products and other personal paper products in your bathroom storage so they're there when you need them. The better stocked your bathroom cabinet items, the more prepared you are for life's unexpected changes. Use the tips above to organize your space. If you're designing or renovating a bathroom and looking for new components, visit Modern Bathroom to learn more about the best in bathroom storage and bathroom vanities!
Yes, it's really that simple. You can wash a plastic shower liner right in your washing machine. Just make sure to remove the hooks first so they don't damage the machine's interior.
Since the liner is plastic, you don't want to take any chances of it melting. Always use the coldest water setting available.
While you can probably use regular laundry detergent with success, using either vinegar or baking soda (not both!) instead will usually produce better results. These cleaners are proven to tackle stubborn mildew with ease. NOTE: Do not use liquid fabric softener on the liner — it will do nothing but make your shower liner smell like chemicals.
Before starting the load, add a couple of bath towels. The towels will help provide additional agitation during the cleaning process to help scrub the mildew off while it is being washed.
• Open the bathroom door when your shower is over to help the moisture dissipate.
• Open a window while you are showering to help the steam escape.
• Turn on the exhaust fan both during and after the shower.
• Spread the shower liner completely when you're done showering, so the entire surface area has a chance to dry.
Now that you know how simple it is to clean your shower liner, there is no reason not to do it regularly (it is recommended every three months). With a clean liner, you can keep your bathroom shower smelling great without having to worry about inhaling dangerous toxins — that's a win-win and definitely worth the effort.
Anyone who's experienced bad breath can tell you it's an embarrassing condition. Smelly breath is distracting, makes others uncomfortable, and limits the intimacy of close conversation or kissing. That's exactly why, if you're dealing with this frustrating problem and wondering what to do, it's time to think about tongue scraping. Believe it or not, this simple step can make a big difference in freshening your breath and oral health! Here's a look at what tongue scraping is, why it's beneficial, and how often you should do it for the best benefits.
Tongue scraping is exactly what it sounds like: using a designated tool to scrape your tongue, removing bacteria and dead cells in the process. Because the particles on your tongue can cause bad breath, removing them through tongue scraping may also eliminate the accompanying odor. Tongue scraping helps you get rid of more odor-causing bacteria than you could with just brushing.
A tongue scraper can help remove harmful bacteria on the tongue, leading to a lessening of bacteria in the mouth as a whole.
Because bacteria such as mutans streptococci and lactobacilli are sometimes associated with bad breath, lessening them is a step toward a fresher, better-smelling mouth.
Removing bacteria is not only good for preventing bad breath, but also tooth decay, gum disease and other conditions.
Another surprising benefit of tongue scraping regards taste. The cleaner your tongue, the better you may be able to distinguish and enjoy bitter, sweet, salty, etc., foods.
At minimum, scrape your tongue every time you brush your teeth. This can help prevent ongoing bacteria buildup. Keep in mind, however, that scraping your tongue only removes the current bacteria in your mouth — it doesn't prevent future bacteria (or bad breath) from developing. If you're fighting breath odor, you'll have best results from scraping your tongue after every meal. For a simple, effective way to improve your breath and oral health, add tongue scraping to your hygiene routine. When combined with an overall dental care plan, it can be a great solution for better breath.


text:
ATMs, ISPs hit by Slammer worm spread
John Leyden Mon 27 Jan 2003 // 12:26 UTC
The bandwidth-crunching Slammer worm caused all manner of damage since its appearance on the Net in the early hours of Saturday morning.
On Saturday, the spread of the worm was so severe that the majority of Bank of America's 13,000 automatic teller machines "were unable to process customer transactions", the
Washington Post reports. The paper quotes the bank saying it was able to restore services on Saturday evening but a Seattle-based Reg reader tells us he was "unable to make a deposit to my Bank of America Account on Sunday at about noon Pacific time".
"I observed several others having similar problems accessing their accounts," he adds.
Over in Redmond, Windows XP activation servers were thrown offline while in Korea (whose Net connections were particularly hard hit by the worm) shares in the country's two largest ISPs, KT Corp and Hanaro Telecom Inc, fell sharply while computer security stock rose sharply, Reuters reports.
The news agency states "almost all KT customers lost their connections during the attack".
The DDoS potential of the worm on Net access was also felt in Europe.
In Portugal over 300.000 subscribers to Cable ISP Netcabo were without Internet access for more than 12 hours due to the worm, Reg reader Nuno Alves tells us.
Slammer hammers Net
The Slammer (aka Sapphire) worm, takes advantage of a six-month-old vulnerability in MS SQL Server 2000 (a server resolution service buffer overflow flaw), to spread.
Although Slammer is not destructive to an infected host (like Code Red it only exists in memory), it generates a damaging level of network traffic when it scans for additional targets. The worm continuously sends 367 bytes of exploit and propagation code across port 1434/UDP until the SQL Server process is shut down. Unlike Nimda these attacks are not directed towards local sub-nets but spread across the wider Internet.
During peak hours of infection, security firm Symantec observed more than 22,000 unique systems infected by the worm. Infection rates have, thankfully, dropped markedly since but that still leaves a labour-consuming mop-up operation ahead.
On Saturday we reported that afflicted servers are relatively easy to cure, once identified. Although Microsoft has supplied a patch fixing the problem turns out to be far from trivial, as IT staff who spent an unscheduled weekend at work in the City have found.
"Well, after spending the weekend in the office (thanks to the SQL Slammer worm), I can confirm that at least two City investment banks have been severely impacted by this," one technician, who asked to remain anonymous, tells us.
"Of course, Microsoft have made our jobs easier (not!) by having two different patches that need to be installed for SQL Server 2000 and Microsoft Data Engine (MSDE), although there's very little to tell the difference between the two installations so as to target them correctly. Not to mention conflicting security bulletins, and a service pack that needs to be installed before the patch can be applied," he adds.
Security firms recommend that all MS-SQL server system admins audit their machines for known security vulnerabilities. Since Slammer spreads on UDP port 1434, users are been urged to update firewall or router tables to block this traffic as a workaround, prior to putting patches in place. ®
SQL worm slams the Net
SQL Slammer worm advisory by security tools firm ISS
More on the SQL Server 2000 vulnerability Slammer exploits, alert by Next Generation Security Software


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