Input: Claim: Dark matter alone can explain all anomalies in astrophysics. [SEP] Text: As the big bang began and the matter expanded and clumps moved away from each other, an inflationary period took place in the expansion where the clumps, eventually to become stars and galaxies, moved away from each other much faster than the speed of light. After this rapid expansion much of the matter was separated by distances greater than the distance light could have ever traveled since the beginning of the universe. The distant regions of the universe could never again transfer information or have any influence upon each other (unless a deflationary period should occur). If the inflation theory, which after some modification is now widely accepted, can explain why the properties of similar objects in distant regions of the universe can be so uniform because they moved away from each other much faster than the speed of light, should not it also be able to explain why gravity could be “left behind”, so to speak, around objects that rapidly moved apart from each other faster than the speed of light? If the effects of gravity cannot travel through space faster than the speed of light, as is generally believed based on Albert Einstein’s of Relativity, and the matter separated faster than the speed of light, some of the gravity had to be “left behind”. And as we discussed earlier, the total amount of this gravity is 20. 7 times the amount produced by the real matter in our visible universe. This can be the gravity that exists in galaxies as dark matter, and the gravity that exists throughout the universe as dark energy. The following example may make it easier to understand how gravity can be “left behind”. Let us suppose that the early universe was similar to a very massive soccer ball with all the mass concentrated in the outer shell of the soccer ball, similar to our stage 1 model. There are indentations or seams in the soccer ball similar to a regular soccer ball, which usually has 20 hexagonal and 12 pentagonal sections. The shell of the soccer ball is a curved surface and all the regular hexagonal and pentagonal sections inside the seams of the soccer ball are likewise curved surfaces. 9. The size of the soccer ball determines the amount of curvature of the soccer ball as a whole, and also the curvature of each individual section of the soccer ball. For simplicity, let us now look at a cross-section of the soccer ball. 10. Figure 9. Soccer ball. Figure 10. Soccer ball cross-section.

Output: contrast


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: Sugar mixtures were analyzed by ion chromatography (IC) on the Dionex ICS2500 system with a CarboPac PA10 analytical column and an ED50 electrochemical detector (Dionex, Sunnyvale, USA). The column was washed with an isocratic elution of NaOH at a speed of 1 mL/min at 30°C. Structural carbohydrates and lignin content of corn stover were analyzed according to the procedures of the [24]. Total lipids of cells prepared by the SHELP process were extracted according to the chloroform/methanol method [13]. Total lipids of the SSLP and SSELP processes were obtained by extraction according to the chloroform/methanol method followed by a petroleum-ether partition step. Briefly, total mass containing cells and corn stover residues was harvested by centrifugation, washed twice with distilled water and determined gravimetrically after drying at 105°C for 24 hours. Crude lipids were extracted from dried total mass, dissolved again with petroleum ether and filtrated to recover the petroleum-ether solution. The solvents were removed by rotary evaporation, and the residue was dried at 105°C for 24 hours to give the total lipids [14]. Lipid content was expressed as gram total lipids per gram CDW. The lipid coefficient was defined as milligram total lipids produced per gram corn stover supplied, as has been adopted by others in this field [3]. Lipid fractionation was performed according to a published method, with minor modifications [25]. About 100 mg of the lipid sample was loaded on a silica gel column (Waters Sep-Pak™ Vac 6 cc Slilca-1 g (), eluted by 100 mL of 1,2-dichloroethane, 70 mL of 1,2-dichloroethane/acetone (1:10, v/v) and 35 mL of methanol in sequence. The solvents from each fraction were evaporated in a vacuum, and the weight of the residual lipid was determined. The fractions, in the order of elution, were neutral lipids (N), glycolipids plus sphingolipids (G + S) and phospholipids (P).

Output: pass


Input: Claim: Coral reefs are highly sensitive to changes in water temperature and acidity. [SEP] Text: Symbiont photophysiologyThe photophysiology of coral symbionts can be characterised by several parameters each having different responses depending on exposure to the various components that comprise a change in water quality. For example, the maximum quantum yield (F vF m) decreases with increasing exposure (duration and quantity) to sediment (Philipp and Fabricius 2003) and exposure to agricultural chemicals (Jones et al. 2003; Table 2), but appears not be influenced (for cultured symbionts) by exposure to elevated levels of dissolved inorganic nutrients (Rodriguez-Roman and Iglesias-Prieto 2005). Exposing the symbionts to a series of irradiances in short (10 s)-incremental steps producing a rapid light curve can also provide detailed information on photo-acclimatory responses of corals to changes in water quality (Ralph and Gademann 2005). Quantitative parameters derived from rapid light curves include maximum photosynthetic rate (PSmax), minimum saturating irradiance (E k) and light utilisation coefficients (α) of the initial rise of the curve. Symbionts acclimatised to high irradiances are characterised by high PSmax and E k, with low α, but the opposite occurs for symbionts acclimatised to low-irradiance as the symbionts attempt to optimise their light capture and utilisation capability (Anthony and Hoegh-Guldberg 2003; Cooper and Ulstrup 2009). However, these parameters are influenced by variation in seawater temperature (Coles and Jokiel 1977; Warner et al. 1996; Fitt et al. 2001), flow regime (Nakamura et al. 2005), diurnal changes in benthic irradiance (Jones and Hoegh-Guldberg 2001; Lesser and Gorbunov 2001) and symbiont genotype (Frade et al. 2008; Hennige et al. 2009). Thus, these factors must be accounted for when using symbiont photophysiology to infer changes in water quality. Nevertheless, photophysiological responses are rapid (i. e. timescales of minutes to days) making these measures particularly suitable as sublethal bioindicators of changes in water quality if confounding variables are controlled.

Output: corroborate


Input: Claim: Dark matter alone can explain all anomalies in astrophysics. [SEP] Text: Suppose the soccer ball undergoes a large expansion, and the seams or indentations are very thin and much weaker, but much more elastic than the material inside the seams. The material inside the seams is very strong and thick and not very flexible. As the soccer ball expands, the space between the hexagonal and pentagonal sections stretches so that the sections are now spaced 5 times further apart than they were before the expansion. Because of their thickness and strength, they are still approximately the same size and have about the same curvature as before the expansion. The radius of the soccer ball will now be 5 times as large, and the curvature of the cross-section of the soccer ball as a whole, which is a circle, will now be 5 times less than before the expansion (since it is inversely proportional to the radius), but the curvature of each hexagonal and pentagonal section will be approximately the same as before the expansion. 11. Let us now make the analogy between the soccer ball and our universe, but assume the universe has many, many more sections than the soccer ball since it is much, much larger. It follows that if the expansion of space occurs in the seams between the sections (space between the galaxies), the curvature (warped space-time) within the galaxies will remain about the same while the curvature (warped space-time) of the universe as a whole will be 5 times smaller (because the radius of the cross-section of the universe is now 5 times larger). Gravity, which is the force of attraction between the galaxies, and is also the warped space-time in and immediately around the galaxies, has been “left behind” in and around the galaxies as space has expanded between the galaxies. When we now look at the expanded universe where the galaxies are now 5 times farther apart then before, and calculate the amount of mass we can observe in the galaxies, it will be much less than is needed to account for the gravity (warped space-time) in and around the galaxies. Thus, the dark matter that is needed to exist in a spherical halo around the galaxies to account for the motions of the stars observed by our astronomers within the galaxies can be the gravity produced by all the galaxies when they were much closer together, that was “left behind” when the inflation occurred. 9.

Output: contrast


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: The fatty acid compositional profiles of lipid samples were determined on a 7890 F gas chromatography instrument (Instrument Co. Ltd. , Shanghai, China) after transmethylation according to a published procedure [26]. Statistical analysisAn analysis of variance (ANOVA) and multiple comparisons were performed to identify the significant differences of the experimental data. Tukey’s post hoc test was conducted to compute significant differences among the experimental data of various culture modes. Bonferroni’s post hoc test was adopted to calculate multiple comparisons of experimental data obtained under different hydrolysis or culture conditions. A P value of less than 0. 05 was considered statistically significant. Results and discussionSeparated hydrolysis and enhanced lipid production processThe chemical composition of raw corn stover samples used in this study contained 37. 9% glucan, 20. 1% xylan, 2. 3% arabinan, 0. 9% galactan, 0. 3% mannan and 20. 8% lignin. The alkaline pretreatment was efficient at removing lignin by disrupting the ester bonds cross-linking lignin and hemicellulose, as well as enhancing the enzyme accessibility of cellulose [21]. In a typical alkaline pretreatment process, the regenerated corn stover was received in a yield of 61. 6%. The chemical composition of the regenerated sample contained 56. 2% glucan, 16. 5% xylan, 3. 1% arabinan, 0. 5% galactan, 0. 5% mannan and 8. 2% lignin, indicating that more than 75% of lignin was removed. To ensure complete hydrolysis of the regenerated corn stover, different amounts of cellulolytic enzymes were used, and final concentrations of glucose and TRS after 48 hours are shown in Figure 1. It was clear that higher enzyme loadings afforded more products. When cellulase, β-glucosidase and xylanase were loaded at 5 FPU, 10 CBU and 40 U/g regenerated corn stover, glucose and TRS were only 26. 3 g/L and 53. 3 g/L, respectively. When enzymes loadings were all doubled, glucose and TRS increased significantly (P <0. 05) to 36. 3 g/L and 68. 6 g/L, respectively.

Output: pass


Input: Claim: Coral reefs are highly sensitive to changes in water temperature and acidity. [SEP] Text: Symbiont photophysiology is, therefore, ranked a high-priority bioindicator for use in long- and short-term monitoring programmes (Table 3). Chlorophyll a fluorometers can be used to quantify photophysiological responses although the application of these instruments as monitoring tools requires a high level of training and a theoretical understanding of their utility. Colony brightnessThe colour of scleractinian corals is determined by photosynthetic pigments contained in the algal endosymbionts and light-absorbing compounds in the coral tissue (e. g. Jeffrey and Haxo 1968; Salih et al. 2000; Dove et al. 2001), both of which are known to respond to changes in water quality. Concentrations of chlorophyll a (and hence colour brightness) increase in response to exposure to elevated nutrients (Hoegh-Guldberg and Smith 1989; Table 2) and reduced irradiance (Falkowski and Dubinsky 1981; Dubinsky et al. 1984) whereas symbiont density may decrease in response to sedimentation (Nugues and Roberts 2003) and exposure to pollutants, such as cyanide (Cervino et al. 2003). However, symbiont density also varies with season (Stimson 1997; Brown et al. 1999; Fagoonee et al. 1999) and seawater temperature, indicating a moderate specificity to changes in water quality. Correlating colony brightness to changes in water quality also requires large spatial and temporal replication in monitoring programmes because photo-acclimatory responses occur on short timescales (Anthony and Hoegh-Guldberg 2003). Changes in host pigmentation in response to changes in water quality are less well documented, although Salih et al. (2006) found a modal response in levels of fluorescent pigments across a depth gradient and suggested the possibility of a dual role for these host pigments; photo-protective at high irradiances and light-amplifying at low irradiance deep depths. Notwithstanding these caveats, colony brightness ranked a high-priority bioindicator for use in long- and short-term monitoring programmes (Table 3) because colour changes can be measured with simple tools, such as colour charts (Siebeck et al. 2006), making it a useful sublethal bioindicator and a trigger for more intensive studies.

Output: corroborate


Input: Claim: Dark matter alone can explain all anomalies in astrophysics. [SEP] Text: Dark energy is commonly defined as an unknown form of energy which permeates all of space, and tends to accelerate the expansion of the universe. space mission shows that it makes up 68. 3% of the universe. It is important to note that, although the Planck space mission collected its data from a detailed study of the Background (CMB) radiation, the values of 4. 9%, 26. 8%, and 68. 3% are the present day values extrapolated from the CMB data. They are not the percentages that existed when the CMB radiation was emitted from a 380,000 thousand year old universe. Current thought is that dark energy is a negative pressure spread throughout space as a part of space itself, which acts as an anti-gravity force. As space expands, the dark energy is not diluted. Instead, more dark energy is created as space is created. However, this is not how energy, in general, behaves. Our stage 2 model offers an alternative explanation. We can show with the model, that instead of dark energy Figure 11. Soccer ball expanded. increasing to cause the accelerated expansion of the universe, the total amount of matter in the universe is decreasing to cause the amount of gravity holding the universe together to decrease and allow the increased expansion. Here is the theory. We know from physics that the amount of energy in a certain volume is diluted as the volume increases. The volume of a given amount of space increases by the cube of the radius as it increases,. We also know from physics that the amount of gravity holding a given amount of space together decreases as the radius increases by square of the radius,. Thus, if we look at our stage 2 model, the energy spread throughout the volume is decreasing faster (by the cube of the radius) than the gravity holding it together is decreasing (by the square of the radius). This means that the expansion should be slowing down. However, if the amount of gravity is reduced by conversion of matter into energy by the equation, E = mc2, greater than the volume increases, the space will expand. We can use the model to calculate the numbers that will show this. How is the amount of matter (gravity) being decreased? There are many books and 13. 3 billion years ago, the total amount of matter in the universe has been decreasing. We can calculate how much matter has been transformed into energy every billion years to cause the expansion of the universe to accelerate about 6 billion years ago.

Output: contrast


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: Full size imageIt should be emphasized that no β-glucosidase was used, and cellulase and xylanase were loaded only 10 FPU and 80 U, respectively, per gram of alkaline-pretreated corn stover in the SSLP process, which were dramatically less than those in the SHELP process. Yet, lipid coefficient was increased by 12% compared to that of the SHELP process. A similar example with acid-pretreated corn stover using Trichosporon cutaneum as the lipid producer was recently reported [14], but lipid coefficient and lipid productivity were 32. 3 mg/g and 0. 86 g/L/d, respectively, which were much lower than our results. Simultaneous saccharification and enhanced lipid production processTo further improve lipid production efficiency, we tested the SSELP process, and the results are shown in Table 2. The evolution of glucose and TRS in the culture broth shared similar trends (Figure 3). There was an apparent sugar formation burst, followed by a short plateau and then a gradual decline. Higher enzyme loadings afforded longer plateau time and higher sugar concentrations. When enzyme loadings were relatively low, glucose was below the limit of detection for a longer culture time period. When cellulase, β-glucosidase and xylanase loadings were 5 FPU/g, 10 CBU/g and 40 U/g, the concentrations of glucose and TRS after 12 hours were 4. 0 g/L and 8. 6 g/L, respectively. Glucose was below the limit of detection and TRS was 2. 9 g/L after 36 hours, suggesting that the sugars became limiting for yeast utilization. TRS was only 1. 0 g/L at the end of the culture, indicating that C. curvatus had an exceptional capacity of assimilating different sugar components generated by enzymatic hydrolysis. Lipid titre, lipid coefficient and lipid productivity were 13. 2 g/L, 137. 9 mg/g and 4. 06 g/L/d, respectively (Table 2, Entry 1). When cellulase, β-glucosidase and xylanase were all doubled, the concentrations of glucose and TRS were 8. 0 g/L and 19. 3 g/L, respectively. At the end of the culture, no glucose was observed and TRS was only 1.

Output: pass


Input: Claim: Coral reefs are highly sensitive to changes in water temperature and acidity. [SEP] Text: Tissue thickness of massive coralsTissues of massive Porites have been found to be thicker on coastal reefs compared with offshore reefs, possibly because of the higher concentrations of nutrients and particulate organic matter in the coastal zone (Barnes and Lough 1992; Table 2). Many environmental factors, including irradiance, seawater temperature, water clarity, particulate and dissolved inorganic nutrient levels and sedimentation change from inshore to offshore locations, and previous studies have not resolved which of these factors is the most influential in affecting tissue thickness. Barnes and Lough (1992) suggested that massive Porites would have thicker tissue layers where particulate matter and other food items were not limited. Tissue thickness can change within a few weeks following a change in water quality (Cooper 2008), and hence this measure ranked a high-priority bioindicator for use in long- and short-term monitoring programmes (Table 3). Tissue thickness is best determined in massive Porites by removing a small core from the upward-facing surface and measuring the depth of the skeleton occupied by living tissue with callipers. However, as the thickness of the tissue layer can vary within a colony (Barnes and Lough 1992), sampling must be standardised and replicated. A limitation of this measure is that the sampling is intrusive, and so procedures that mitigate sampling effects, i. e. plugging core-holes to facilitate tissue regrowth, need to be considered. Surface rugosity of massive coralsThe surface rugosity of massive Porites increases when skeletal growth is unable to provide sufficient surface area to accommodate increased tissue growth. Several studies have shown that Porites colonies had a greater surface rugosity on coastal than offshore reefs of the Reef, potentially due to increased availability of nutrients and particulate organic matter (Darke 1991; Scoffin et al. 1992, Table 2), suggesting a high specificity to changes in water quality. Thus, surface rugosity ranked a high-priority bioindicator for use in long-term monitoring programmes (Table 3). It is, however, likely to be of limited use for short-term monitoring due to its slow response time. Surface rugosity can be determined by placing a piece of chain of known length on the upper surface of the colony and calculating the ratio between the horizontal and vertical chain length (Darke 1991). Coral growthIrradiance is a key determinant of coral growth (Goreau and Goreau 1959; Bak 1974).

Output: corroborate


Input: Claim: Dark matter alone can explain all anomalies in astrophysics. [SEP] Text: We first of all, have to have an estimate of the number and type of stars that exist in the universe, and we also have to have an estimate of how long the life cycle of the average star lasts. The astronomers, astrophysicists, and cosmologists who have studied the stars have come up with some detailed results. They have learned that the greater a star’s mass is when it formed, the faster it burns its fuel, and the shorter is its life cycle, which may be numbered in only millions of years. Many more stars, like the sun, will continue burning their fuel, and decreasing their mass, for about 10 billion years. The much smaller stars will burn their fuel much slower and may continue to do so for over 100 billion years. Way galaxy is estimated to contain between 200 - 400 billion stars, and there are estimated to be over 100 billion galaxies in the universe. Each of these stars is converting tremendous amounts of matter into energy every second of every day. It is also estimated that the life cycle of the average star in the galaxy is about 50 billion years. Astronomers can determine the age of stars in the universe very accurately. They have estimated that some of the stars in the galaxy have been in existence for over 13 billion years, thus, the galaxy must have been one of the earliest galaxies to form within the first billion years after the beginning of the universe. We can now calculate how much matter has been transformed into energy every billion years to cause the expansion to accelerate about 6 billion years ago when the universe was almost 8 billion years old. When the expansion of the universe began to accelerate at about 8 billion years after its beginning, most of the stars in the galaxy had already converted about 8 billion years worth of their 50 billion years of fuel, or about 16% of their matter, into energy. If the galaxy is an average size galaxy in the universe (estimates are that it is somewhat smaller than average), then the amount of matter in the universe has decreased by at least 16% when the expansion of the universe began to accelerate. In making the calculation, we need to realize that when the expansion of the universe began to accelerate, whatever was causing it was also accelerating. If it is in fact caused by the decreasing amount of matter in the universe, then the matter has to be decreasing at an accelerating rate.

Output: contrast


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: It was interesting to note that the best results were obtained in the absence of exogenous β-glucosidase (Table 2, Entry 2). The maximal glucose concentration was only 2. 9 g/L, and TRS was 1. 8 g/L at the end of culture. Lipid titre, lipid coefficient and lipid productivity reached 15. 1 g/L, 159. 4 mg/g alkaline-pretreated corn stover and 4. 69 g/L/h, respectively. Lipid coefficient was improved by 37. 9% and 23. 2% compared to that of the SHELP and SSLP processes, respectively. Such good results might be due to optimal nutrient limitation because of less enzyme loadings, and to well-matched rates between enzymatic hydrolysis and lipid production. Enzyme recoveryTo test enzyme stability during the culture process, enzyme samples were first incubated under identical conditions for 71 hours, and then loaded with 10% (w/v) alkaline-pretreated corn stover samples for hydrolysis. Glucose and TRS reached 42. 0 g/L and 73. 7 g/L after 36 hours, while the corresponding fresh enzymes gave glucose and TRS at 43. 7 g/L and 76. 9 g/L, respectively. These results suggested that the culture process had minor detrimental effects on enzyme stability. When the corn stover samples were treated by the spent culture supernatants of the SSELP process initially loaded with 10 FPU/g cellulase and 80 U/g xylanase, concentrations of glucose and TRS after 48 hours were 9. 3 g/L and 31. 2 g/L, respectively. However, hydrolysis with identical amounts of fresh enzymes gave glucose and TRS at 23. 3 g/L and 55. 5 g/L, respectively. These results indicate that substantial enzyme activities were recovered. To further demonstrate the possibility of enzyme recovery, the spent supernatants were loaded with 10% (w/v) alkaline-pretreated corn stover and C. curvatus cells equivalent to 0. 36 g of CDW for the second SSELP run. Lipid titre and lipid coefficient were 4. 9 g/L and 44. 1 mg/g, which were 32. 7% and 27. 9%, respectively, of those from the fresh enzymes used in the first run.

Output: pass


Input: Claim: Coral reefs are highly sensitive to changes in water temperature and acidity. [SEP] Text: However, coral growth is also indirectly affected by changes in irradiance due to variable turbidity and nutrient conditions (e. g. Marubini and Davies 1996). On the Reef, the growth parameters of massive Porites vary along cross-shelf gradients. For example, the skeletal density of massive Porites increases (Risk and Sammarco 1991), but the rate of linear extension and calcification decreases, with increasing distance from the coast (Lough and Barnes 1992; Table 2). However, coral growth is also influenced by variation in other parameters such as temperature, thermal stress and ocean acidification (Lough and Barnes 2000; Cooper et al. 2008a; De’ath et al. 2009) indicating a moderate specificity to changes in water quality. Coral growth ranked a medium-priority bioindicator for use in long-term monitoring, but was of low priority for short-term monitoring because of its slow response time (Table 3). Notwithstanding this, analysis of coral growth records provide important historical information on environmental changes over decades to centuries that can be used in combination with other bioindicators in long-term monitoring programmes. The coral growth parameters are generally derived from cores or slices of massive corals (Knutson et al. 1972), but can also be measured in corals with other growth forms (Ferrier-Pages et al. 2000; Table 2). Techniques for quantifying coral growth include gamma densitometry (Chalker and Barnes 1990) to determine skeletal density, with the distance between the peaks of adjacent density bands to determine linear extension, and the product of these two parameters, linear extension and density, to estimate calcification rate. Skeletal elemental and isotopic compositionChemical elements incorporated from the water column into the coral skeleton can be used as retrospective bioindicators of environmental conditions (e. g. Goreau 1977; Risk et al. 2001; Cohen and McConnaughey 2003; Cohen et al. 2004). Several studies have examined the utility of the ratio of the nitrogen isotopes 15N/14N (known as δ15N) to hindcast changes in water quality on coral reefs (Sammarco et al. 1999; Heikoop et al. 2000; Table 2). The main sources of anthropogenic nitrogen (sewage, organic nitrogen from soil erosion and synthetic fertilisers) each produce characteristic δ15N signatures that allow identification of the source of nitrogen (Heaton 1986).

Output: corroborate


Input: Claim: Dark matter alone can explain all anomalies in astrophysics. [SEP] Text: This is exactly what has been happening in our universe, when the initial dust and gas and clumps of matter in the early universe began to collapse and form the early stars and galaxies. As the stars and galaxies increased in numbers into the billions, they increasingly converted matter into energy, and the amount of matter in the universe decreased at an accelerating rate. If the amount of decrease in matter during the first billion years was only 1/2 of 1%, and it increased by only 1/2 of 1% every billion years, it would be sufficient to account for the accelerating expansion of the universe when it was almost 8 billion years old. This is when the rate of increase in volume of the universe (and corresponding decrease in energy) was less than the decrease of gravity holding it together. The ratio of the change in volume to the change in gravity, which had been much greater than one, was gradually decreasing as the matter in the universe decreased causing the decrease in gravity. Between 7 and 8 billion years, the ratio became less than one, and the expansion began to accelerate because gravity decreased at a greater rate than the amount of energy in the universe decreased. The following tables show how the changes (increase) in volume of the expanding universe (decrease in energy) compare to the changes in gravity (decrease) as the universe expanded over its almost 14 billion years of existence. Table 4 shows how the rate of change in volume of the universe changed as the rate of change in the radius of the universe stopped slowing down and began to accelerate. After decreasing for about 8 billion years, it began to increase at an accelerating rate. Table 5 shows how the amount of gravity in the universe decreased not only as the radius increased, but also as the amount of matter in the universe decreased. After about 8 billion years, the rate of decrease began to accelerate. This is caused by the increased acceleration in the loss of matter in the universe during the past 6 billion years (an additional increase of 1/2% every billion years) as shown in the Mass decrease column in the table. Table 6 shows how the change (increase) in volume became less than the change (decrease) in gravity after 7 to 8 billion years; i. e. , ratio less than one, thus causing the expansion of the universe to accelerate rather than slow down as it had been doing.

Output: contrast


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: It should be noted that alkaline-pretreated corn stover contained about 8. 2% lignin, which might entrap some enzymes and reduce enzyme recovery efficiency. Interestingly, desorption strategies were known to improve enzyme recovery from the biomass hydrolysis mixtures [29]. Therefore, it is expected that more enzymes can be recycled from the SSELP process upon further optimization. Comparison between processes for lipid production from corn stoverMicrobial lipid samples from different processes were analyzed and the results are shown in Table 3. It was found that fatty acids with 16 and 18 carbon atoms were the majority, and the fatty acid compositional profiles were similar to those of vegetable oils, suggesting that microbial lipids were suitable for biodiesel production [30]. Lipid samples from the SSLP and SSELP processes contained neutral lipids around 95%, which were apparently higher than that of the SHELP process. The difference was likely caused by an additional petroleum-ether extraction step used to extract lipids in the SSLP and SSELP processes, which removed major polar lipids including glycolipids, sphingolipids and phospholipids because of their poor solubility in petroleum ethers. Also, higher contents of unsaturated fatty acids, including oleic acid and linoleic acid, were found in lipid samples from the SSLP and SSELP processes. However, direct comparison on fatty acid compositional profiles were not appropriate because these samples were from different cultivation and extraction processes. Table 3 Lipid fractions and fatty acid compositions of lipid samples produced from corn stover by Cryptococcus curvatus under different culture modes Full size tableResults of three processes for lipid production from alkaline-pretreated corn stover by C. curvatus are summarized in Figure 4. A one-way ANOVA followed by Tukey’s post hoc test demonstrated that lipid coefficients increased significantly among different processes following the order of and SSELP (P <0. 05). The highest lipid coefficient of 15. 9 g/100 g alkaline-pretreated corn stover, equal to 9. 8 g/100 g raw corn stover, was obtained for the SSELP process, when 1. 0 kFPU cellulase and 8. 0 kU xylanase were used (Route C).

Output: pass


Input: Claim: Coral reefs are highly sensitive to changes in water temperature and acidity. [SEP] Text: Thus, measuring rates of change in partial mortality ranked a high-priority bioindicator for short-term monitoring and could be used as a trigger for a more intensive impact assessment. Partial mortality can be quantified by estimating the proportion of colony surface free of living tissue, or using photographic techniques to measure the area of lesions and colony surfaces. Mucus productionMucus is produced by some corals to clean the colony surface of sediments, or as a response to emersion during low tides, turbidity, pollutant exposure, changes in salinity and water temperatures and injury (Stafford-Smith and Ormond 1992; Stafford-Smith 1993; Brown and Bythell 2005). Some corals, however, will not produce mucus when stressed, or will stop producing mucus after prolonged stress. For example, sheets of mucus may only be produced by massive Porites to remove sediment when conditions are calm (Coffroth 1985), and fungid corals may cease producing mucus when cells become ‘exhausted’, despite ongoing exposure to stressors (Schuhmacher 1977). Mucus production by corals ranked a low priority bioindicator for use in long- and short-term monitoring programmes (Table 3). Mucus production is difficult to quantify and currently best recorded as qualitative observations. However, excess mucus production may be a useful qualitative bioindicator for short-term monitoring provided that complimentary evidence is obtained from quantitative methods. Population measuresPopulation structureThe structure of a population can be defined as the number of individuals at different life-history stages. The effects of changes in water quality on coral reefs have been inferred by quantifying changes in the structure of coral populations through time (e. g. Bak and Meesters 1999; Meesters et al. 2001; Gilmour 2004). Meesters et al. (2001) found that the size–frequency distributions of coral populations closest to urban centres were negatively skewed, having fewer juveniles and more large colonies than reference locations. For some species, however, differences in size–frequency distributions were related to their life-history strategies, such as the degree to which corals invest in different modes of sexual and asexual reproduction (Gilmour 2004), or species with small, short-lived colonies (Meesters et al. 2001).

Output: corroborate


Input: Claim: Dark matter alone can explain all anomalies in astrophysics. [SEP] Text: These are the numbers that show how dark energy, which is causing the expansion of the universe, does not have to be some kind of increasing energy spread throughout the universe, but rather, can be a decreasing amount of gravity which can no longer prevent the expansion from accelerating. Whatever energy that existed at the big bang to cause the initial expansion can be the energy that is causing its acceleration due to the decrease of matter and gravity. These numbers have been developed from the recent data obtained by telescope and space missions that have been analyzing and studying the stars and galaxies in the universe. The astronomers, astrophysicists, and cosmologists, should be able to show how realistic the numbers are in determining the amount of Table 4. Change in volume. Table 5. Change in gravity. Table 6. Ratio of change in volume to change in gravity. matter that stars, and galaxies, are converting into energy during their life cycles. It is not so much a matter of the stars creating a tremendous amount of energy during the fusion process, which may or may not be significant, but more a matter of the loss of matter. The amounts shown in the above tables appear to be in agreement with what can be extrapolated from the current literature. The tables were also developed from our model of the universe. They show how our model of the universe can explain dark energy. 10. have developed a model of the universe that can explain dark matter, dark energy, and the fourth space dimension. The model was developed by incorporating time into geometry by using time as a radius of an expanding sphere whose surface represented our entire universe. In the stage 1 model, all of space exists on the surface of the sphere, past history exists inside the sphere, and the future exists outside the sphere. The model shows that when we look out into space in any direction, we are looking back in time to the same point in space at the origin of our universe almost 14 billion years ago. It shows how light has been traveling through the expanding space of our universe for over 13. 4 billion years. It shows how we can depict both our visible universe and our entire universe as they exist at the present time. The stage 2 model was developed by rotating the surfaces of the stage 1 model in all directions about the observer. This was done because only 2 lateral space dimensions can be shown on a surface. For an observer to experience the third space dimension, the surface had to be rotated through a volume about the observer.

Output: contrast


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: It should be pointed out that the lipids were slightly underestimated for the SSLP and SSELP processes because polar lipids were partially removed by the petroleum-ether partition step. Therefore, lipid coefficient values of the SSLP and SSELP processes were conservative. Compared with the SHELP process, both cellulase and xylanase loadings were reduced by 50% and no β-glucosidase was used for the SSELP process. Lipid coefficient of 12. 9 g/100 g alkaline-pretreated corn stover, corresponding to 7. 9 g/100 g raw corn stover, was observed for the SSLP process. For the SHELP process, lipid coefficient was only 11. 6 g/100 g alkaline-pretreated corn stover (Route A). process gave the lowest lipid coefficient, likely due to TRS loss in the hydrolysates recovery step and the presence of more nutrients originating from higher enzyme loadings. Because β-glucosidase, additional equipment and longer time were required, the SHELP process was apparently less cost-effective than the other two processes. Figure 4Flow chart indicating mass balance of lipid production from corn stover by Cryptococcus curvatus under different culture modes. CBU, cellobiase unit; FPU, filter paper unit; SHELP, separated hydrolysis and enhanced lipid production; SSELP, simultaneous saccharification and enhanced lipid production; SSLP, simultaneous saccharification and lipid production. Full size imageRecently, lignocellulosic materials have been explored as feedstocks for microbial lipid production by different oleaginous microbes with different processes [3],[14],[31]-[34]. For example, enzymatic hydrolysis and lipid production by the yeast Trichosporon cutaneum were integrated in a 50 L stirred-tank bioreactor, where lipid titre, lipid coefficient and lipid productivity were only 3. 23 g/L, 32. 3 mg/g corn stover and 0. 86 g/L/d, respectively [14]. Lipid production by Microsphaeropsis sp. was carried out using steam-exploded wheat straw under solid-state culture conditions, and lipid coefficient was about 80 mg/g [33]. As shown in Table 4, the SSELP process had higher lipid coefficient and lipid productivity over those of previous results.

Output: pass


Input: Claim: Coral reefs are highly sensitive to changes in water temperature and acidity. [SEP] Text: Taxonomic richnessTaxonomic richness is defined as the number of taxa within a community. The taxonomic richness of hard corals, octocorals and macroalgae gradually change along water quality gradients in several coastal regions of the Reef (van Woesik et al. 1999; Fabricius et al. 2005). For example, the taxonomic richness of octocorals with zooxanthellae declined with increasing turbidity and sedimentation (Fabricius et al. 2005; Table 2). Existing studies suggest that the taxonomic richness of hard corals, octocorals and macroalgae have a high specificity to changes in water quality. In addition, decreases in taxonomic richness will occur in response to both chronic and acute reductions in water quality, either because of rapid mortality or reduced settlement success of the most susceptible species. Taxonomic richness is, therefore, considered a high-priority bioindicator for use in long- and short-term monitoring programmes (Table 3), although extensive and ongoing observer training is required to identify and quantify the different taxa and cross calibration is necessary to achieve any consistency. As with community structure, the methods to monitor taxonomic richness are established (English et al. 1997), but require high-level taxonomic expertise. Maximum depth of coral-reef developmentThe maximum depth of seagrass distribution has been used as a bioindicator of estuarine health (Abal and Dennison 1996), and a similar approach has been used for coral communities to infer changes in water quality on coral reefs (Kleypas 1996; van Woesik et al. 1999; Cooper et al. 2007). Coral growth and distribution is determined by available irradiance (Yentsch et al. 2002), and the maximum depth of coral reef development can be defined as the zone of transition from zooxanthellate hard corals to azooxanthellate filter feeders along a depth gradient. On the Reef, the maximum depth of coral-reef development increased almost fivefold within a group of inshore islands along a gradient from low irradiance and elevated nutrients at nearshore locations, to high irradiance and low nutrients at outer locations (Cooper et al. 2007; Table 2). The response time of changes in maximum depth of coral growth is most likely to be on a timescale of months to years.

Output: corroborate


Input: Claim: Dark matter alone can explain all anomalies in astrophysics. [SEP] Text: By doing this, we developed a fourth space dimension which we called orientation, which also incorporated time into space. It is shown that to locate and describe a point in space, 4 space dimensions are required. Height, width, depth, and orientation are required. However, we are 3-dimensional beings living in a 4-dimensional world. We can experience only one orientation at a time, just as a flat 2-dimensional being can experience only one particular height dimension at a time. The stage 2 model presents us a geometrical framework upon which we can calculate the volume (energy) and the amount of gravity that existed in our universe throughout its history. It thus presents us with a way to explain dark matter as the gravity produced by the real (baryonic) matter that exists throughout our entire universe. And it presents us with a way to explain dark energy as the energy that caused the original expansion of the universe at the big bang that is now accelerating due to the loss of matter and gravity in the universe. This model of our universe represents a dramatic shift in how we view our universe. It shows how you can not only visualize a 3-dimensional space and one time dimension universe in a model on a flat piece of paper, but can also visualize a 4-dimensional space and one time dimension universe in a model on a piece of paper. The model gives us new insights into the nature of our universe, and presents a framework upon which theories can be developed to explain dark matter, dark energy, and the fourth space dimension. As we continue to explore our universe, and study and analyze the stars and galaxies, we can produce the experimental data that can show that this model can indeed explain dark matter, dark energy, and the fourth space dimension. 1. 1 billion light years apart, how far will light have traveled from one galaxy to the other during the 1 billion years? We first of all, have to make the distinction that the two galaxies have not moved apart relative to each other due to their motion; they have moved apart due to space expanding between them. And secondly, space, or spacetime to be more accurate, is something upon which measurements can be made as it expands. Using the above example, this means that after 1/2 billion years, we can locate a point in space between the two galaxies that will be midway between them, or 0. 525 billion light years away from both of them.

Output: contrast


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: This was because the SSELP process had the advantage of a two-stage lipid production [35] together with those of simultaneous saccharification and fermentation process being widely explored in biorefinery research [11],[12]. As lipids are intracellular products, the SSELP process also provided an opportunity to recover and reuse cellulolytic enzymes more conveniently, which could further reduce enzyme consumption and wastewater discharge. Table 4 Lipid coefficients of lipid production from lignocellulosic materials by different oleaginous microorganisms Full size tableConclusionsThe current study compared three different processes for microbial lipid production from alkaline-pretreated corn stover by C. curvatus. It was found that the SSELP process was the most promising one, which consumed less enzymes and afforded higher lipid coefficient. Moreover, enzymes could be partially recovered by recycling the spent culture supernatants, which could further reduce enzyme dosage and wastewater discharge. These results provide valuable information for cost-effective lipid production from lignocelluloses. Authors’ contributionsZWG designed the study, performed the experiments, analyzed the results and drafted the manuscript. and HBX participated in the design of the study and commented on the manuscript. QW participated in sugar analysis. ZKZ coordinated the study and revised the manuscript. All authors approved the final manuscript. AbbreviationsCBU: Cellobiase unit CDW: Cell dry weight FPU: Filter paper unit G: Glycolipids IC: Ion chromatography N: Neutral lipids P: Phospholipids S: : Separated hydrolysis and enhanced lipid production SSELP: Simultaneous saccharification and enhanced lipid production SSLP: Simultaneous saccharification and lipid production TRS: Total reducing sugar YPD: Yeast peptone dextrose 139. 10. 1016/j. biotechadv. 2012. 08. 010136. 10. 1016/j. renene. 2011. 09. 0351049. 10. 1002/bit. 247731480. 10. 1016/j. biotechadv. 2012. 03. 002200. 10. 1007/s12155-010-9112-4406. 10. 1021/bp060354f910. 10. 1385/ABAB:124:1-3:09015. 10.

Output: pass


Input: Claim: Coral reefs are highly sensitive to changes in water temperature and acidity. [SEP] Text: Thus, the maximum depth of coral-reef development ranked a high priority for use in long-term monitoring, but was a low priority for use in short-term monitoring programmes (Table 3). The maximum depth of coral reef development can be quantified by visual estimates or with transects along a depth gradient. ConclusionsEach of the bioindicators identified here has a different response time (i. e. from near instantaneous to years) and specificity to changes in water quality, and the final choice of bioindicators must depend on the specific objective and timeframe available for a monitoring programme. Responses that are specific to disturbances such as nutrient availability, sedimentation and turbidity and that demonstrate a rapid response time, can provide an early warning of changes in water quality. In particular, sublethal bioindicators that reflect rapid changes at the genetic/colony level of selected species may be among the most effective ways to pre-empt mortality of corals and impacts to the wider community. In addition, understanding the processes acting within colonies and among the life-history stages of a selected species will provide a better understanding of the consequences of changes in water quality on populations and coral-reef communities. The comparison of responses from a composite of bioindicators will provide the most useful information on the status and trends of reef ecosystems. As the extent of water-quality degradation increases, so does the scale at which the responses are manifested, and the time taken for the system to return to its previous state when the stressors are removed. Responses to small changes in water quality may be best measured by focusing on rapid sublethal effects at the genetic/colony level in the most susceptible species or life stages; when the stressors are removed, then the condition of these organisms may rapidly return to their previous state. With further decreases in water quality, responses will be measured as partial mortality or mortality of organisms in an increasing number of species or life stages, which becomes evident at the scale of populations and communities, and these signals will remain measurable for months to years after the stressors are removed. Finally, extreme decreases in water quality produce widespread mortality across a range of organisms that will be evident at the level of entire communities and as a shift in ecosystem state; the time taken for the response to be manifest will vary between chronic or acute events, but recovery, when the stressors are removed, is likely to occur slowly.

Output: corroborate


Input: Claim: Dark matter has a directly observable effect on everyday objects. [SEP] Text: Journal of > Vol. 15 No. 5, April 2024 P10. 4236/jmp. 2024. 155028 70 Downloads 313 Views 612. doi: 10. 4236/jmp. 2024. 155028. 1. Introduction “Dark matter” has always been one of the big problems to be solved in physics. Astronomers found that the observed galaxy velocity can’t be explained by the Newton’s dynamics theory, and more gravitational sources are needed. So, they proposed to introduce “invisible” dark matter. The concept of dark matter is supported by a large number of astronomical and cosmological observations such as galaxy rotation curve, gravitational lens effect, bullet galaxy cluster, cosmic large scale structural and microwave background radiation etc. But after decades of searching, people have not found any dark matter p2. 3, the improvements of cosmic hydrodynamic equations and cosmic perturbation equations are discussed, respectively. The summary of this paper is concluded in Section 4. The natural unit system is adopted in this 2. Virtual P1. The red areas represent the highest concentrations of dark matter, the orange and yellow the next highest. The blue areas are voids where low densities of dark matter and clusters of galaxies are found. The existence of dark matter filamentary structures in the red, orange, and yellow colors is clearly manifested. The gray dots represent galaxy clusters, and the bigger the dot, the larger the cluster. The data come from [5]. The characteristics of this map are that the dark matter always envelops galaxies and clusters of galaxies, and the clusters are preferentially found in the dark matter areas, and orange and yellow filament structures. They are scarcely found in the blue voids. The explanation for this distribution characteristic is that EVPF follows the high-density ordinary matter (galaxy, galaxy cluster). ⑩ EVPF can explain galaxy rotation curve Here, the (MW), as a stable system with invariant mass distribution and constant parameter values ( l and η ), is taken as an example. The baryon matter of MW is bulge and disk. The gravitational field of the bulge is assumed to be depicted by the Plummer potential [6] φ b ( R ) = − G M b R 2 + z 2 + b 0 2. (2) where R = ( x 2 + y 2 ) 1 2.

Output: contrast


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: 1186/1754-6834-6-5380. 10. 1007/s10570-012-9653-0287. 10. 1007/s12010-009-8869-47. 10. 1186/1754-6834-1-7322. 10. 1016/j. jbiotec. 2013. 06. 01613. 10. 1186/1754-6834-7-1318. 10. 1016/j. biortech. 2012. 05. 0384538. 10. 1016/j. biortech. 2009. 04. 0229709. 10. 1016/j. biortech. 2011. 08. 0246140. 10. 1016/j. biortech. 2011. 02. 08136. 10. 1186/1754-6834-6-361996. 268. 1197. 10. 1016/j. fuproc. 2009. 05. 018579. 10. 1007/s002530050731428. 10. 1021/ac60147a0302008. 6129. 10. 1016/j. biortech. 2010. 02. 111317. 10. 1016/j. enzmictec. 2007. 02. 008192. 10. 1038/sj. jim. 700005451. 10. 1016/S0065-2164(02)51000-5298. 10. 1002/bit. 260340303780. 10. 1002/jctb. 1744458. 10. 1016/j. apenergy. 2011. 10. 0131210. 10. 1039/c2gc00033d3889. 10. 1016/j. biortech. 2007. 08. 0157562. 10. 1016/j. biortech. 2010. 04. 027188. 10. 1016/j. jbiotec. 2011. 02. 0104. 0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the licence, and indicate if changes were made. The images or other third party material in this 4. 0/. waiver ( applies to the data made available in this 10.

Output: pass


Input: Claim: Coral reefs are highly sensitive to changes in water temperature and acidity. [SEP] Text: This is best conceptualised when the bioindicators are represented against increasing levels of stressors, from sublethal stress to mortality (Fig. 2). Exposure to a low-level stress will first invoke a response at the genetic and colony level, such as symbiont photophysiology and coral brightness. As stress increases, either in terms of duration or intensity, responses at the population and community level may become evident through reduced juvenile densities, changes in the community structure, through the loss of susceptible species, increased macroalgal abundances, reduced abundances of large symbiont-bearing foraminifera, and a reduction in the maximum depth of coral-reef development. Response time is, therefore, a critical criterion that underpins bioindicator selection in any environmental monitoring. Moreover, exposure to changes in water quality may invoke different responses in some groups, e. g. elevated nutrient concentrations and turbidity decreases coral brightness, while sedimentation stress increases brightness (through bleaching) on upward facing surfaces. Hence, important information on the specific forms of stress can be gained by investigating the direction and magnitude of responses relative to reference conditions. Fig. 2Conceptual model of coral bioindicators to indicate increasing exposure to the key components of water quality. Responses are presented in increasing order of effect from stress to mortality resulting from increasing levels of stressors. Responses will depend on both the magnitude and duration of changes in the levels of stressors (e. g. Kuntz et al. 2005). All the responses will first be evident at the genetic/colony level and then in the wider community. Sublethal responses, therefore, may pre-empt more severe effects at the population and community level and can be used to describe shifts in ecosystem condition from healthy (green) to degraded (red) conditionsFull size image This review has identified 11 measures as high-priority bioindicators that should be considered for inclusion into long-term monitoring programmes. These are: symbiont photophysiology, colony brightness of corals, tissue thickness and surface rugosity of massive corals, skeletal elemental and isotopic composition, abundance of macro-bioeroders, coral recruitment, micro- and meiobenthic bioindicators such as foraminifera, macroalgal cover, taxonomic richness of corals and the depth of coral-reef development.

Output: corroborate


Input: Claim: Dark matter has a directly observable effect on everyday objects. [SEP] Text: (23) Here two subscripts 1 and 2 represent baryon matter and dark matter, respectively. The gravitational equations of baryon matter and dark matter are written separately in order to write the constraint condition. At large scale, ρ ¯ 1 ≪ ρ ¯ 2 the contribution of baryon matter can be ignored. In this case, (15), (16), (17), (21) and (23) can be omitted, only leaving (18), (19), (20) and (22) considered and simultaneously letting ϕ 1 = 0. This is the so-called “dark-matter-only simulation”. Whereas at small scale, in the comparison of average density, ρ ¯ 1 ∼ ρ ¯ 2 the contribution of baryon matter cannot be ignored, and (15)-(23) all need to be taken into account. That is to say, at large scale, we can only consider dark matter. But, at small scale, both dark matter and baryonic matter must be simultaneously taken into account in the simulation.

Output: contrast


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: Butanol production from lignocellulosic sugars by Clostridium beijerinckii in microbioreactors access Published: 30 January 2021 Butanol production from lignocellulosic sugars by Clostridium beijerinckii in microbioreactors : orcid. org/0000-0002-8176-67581,2, Kristin F. Degnes3, Sidsel Markussen3, Alexander Wentzel3 & …Håvard Sletta3 Show authors Biotechnology for Biofuels 29. 2 MJ/l compared to that of ethanol (19. 6 MJ/l) and methanol (16 MJ/l), and a lower heat of vaporization (0. 43 MJ/kg) than that of ethanol (0. 92 MJ/kg) and methanol (1. 2 MJ/kg) which provides an easier engine start [3]. Moreover, butanol run engines have lesser ignition problems due to a lower autoignition temperature of 385 °C compared to 434 °C and 470 °C for ethanol and methanol, respectively [3, 4]. In addition, diesel engines can run on pure butanol or diesel blends without any modifications and apparent damage [5]. Based on a recent report from Reuters (April 2019), the butanol market will register a 3. 5% CAGR (compound annual growth rate) in terms of revenue over the next 5 years (2019–2024), and the global market size will reach US$ 7. 7 billion by 2024, from US$ 6. 4 billion in 2019 [6]. The majority of butanol is produced via petrochemical reaction; the propylene hydroformylation, also known as oxo route [7, 8], creating a close link to the propylene market, thus to the price of crude oil [8]. Therefore, butanol production via the petrochemical route is not favorable due to environmental concerns as mentioned above, creating a greater interest in fermentative butanol production. Despite these driving factors, fermentative butanol production still faces multiple challenges such as feedstock availability, costly product recovery, and low product yield as discussed thoroughly in our literature review 34. 2–46. 4% glucose, 4. 9–24. 9% xylose, 1. 1–2. 9% arabinose, 0.

Output: pass


Input: Claim: Coral reefs are highly sensitive to changes in water temperature and acidity. [SEP] Text: For short-term monitoring programmes such as required for EIA that aim to quantify effects of acute disturbances on coral communities, eight priority bioindicators were identified as: symbiont photophysiology, colony brightness of corals, tissue thickness of massive corals, skeletal elemental and isotopic composition, partial mortality, micro- and meiobenthic bioindicators, coral recruitment and taxonomic richness of corals. The difference between the two suites of bioindicators primarily reflects differences in the response time. Short-term monitoring programmes would be best served with sublethal bioindicators or those evident in the most susceptible species, which have rapid response times. In the case of acute changes in water quality, the exceedence of some pre-determined threshold for a bioindicator may trigger a management response that could be used to limit further impacts. In contrast, monitoring the biological consequences of chronic exposure to lowered water quality as part of long-term monitoring programmes would be best based on bioindicators with slower response times coupled with a suite of sublethal bioindicators to provide an early indication of ecological change. Pomeroy et al. (2004) identified a range of measures that also included taxonomic richness and coral recruitment as priority biophysical indicators for assessing the effectiveness of marine protected areas. However, this review has also identified that sublethal measures have important applications in monitoring programmes. For either short- or longer-term monitoring programmes, assessments should be based on deviation from reference values (historic data or reference locations), while also controlling for other changes in physical and biological conditions that affect the specificity and variability of the response. In both cases, an assessment framework, such as the one suggested here, should provide the basis for the selection of a suite of bioindicators to be used when assessing the consequences of changes in water quality around coral reefs.

Output: corroborate


Input: Claim: Plant-based meat alternatives often have a lower environmental impact than beef. [SEP] Text: Plant-based meat market size, share & trends analysis report by source (soy, pea), by product (burgers, sausages), by type (chicken, fish), by end-user (retail, ), by storage, by region, and segment forecasts, 2020-2027. GVR-4-68039-145-9. . Hallinan, B. 2019. Plant-based burger taste test: We tried four vegan ‘meat’ brands ahead of grilling season. (Accessed 21 June 2021). Huffman, D. , and W. Egbert. 1990. Chemical analysis and sensory evaluation of the developed lean ground beef products. In: Advances in 606. Auburn University, Auburn, AL. p. 22–26. Ishmael, W. 2020. Feeding the demand for ground beef. (Accessed 7 June 2021). Council. 2021. Insights Final. (Accessed 24 March 2021). Kraft Foods. 2019. BOCA non-GMO soy all American veggie burgers. (Accessed 8 April 2021). Lucherk, L. W. , T. G. O’and M. F. Miller. 2017. Assessment of objective measures of beef steak juiciness and their relationships to sensory panel juiciness ratings. J. Anim. Sci. 95:2421–2437. doi: Marengo, K. 2020. What to know about the flexitarian diet. Ground beef patty cooked color guide. . . . Howe, M. Duvall, K. Y. Patterson, and J. L. Leheska. 2013. Nutrient database improvement project: The influence of U. S. D. A. Quality and on the separable components and proximate composition of raw and cooked retail cuts from the beef rib and plate. Meat Sci. 95:486–494. doi:. Boyle, and T. G. O’Quinn. 2017. Repeatability and accuracy of the Percentage method at sorting steaks into juiciness categories. Biol. 1:242–252. doi: Miller, M. , M. Andersen, C. Ramsey, and J. Reagan. 1993. Physical and sensory characteristics of low fat ground beef patties. J. Food Sci.

Output: pass


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: Moreover, such technology has the advantage of low power consumption, less space requirements, small quantities of reagents and cells per batch as well as flexibility and portability due their small size [17]. To exploit these advantages for studying fermentative butanol production on mixed sugars derivable from lignocellulosic biomass, we performed clostridial fermentation experiments in BioLector® microbioreactors. The BioLector® instrument (m2p-labs GmbH, Baesweiler, Germany) is a powerful tool with proven capabilities of high-throughput fermentation with simultaneous online monitoring of cell mass (by light scattering), fluorescence, pH and dissolved oxygen (DO) [18]. To our knowledge, the BioLector® has not been used for the purpose of studying fermentative butanol production before. Thus, the main objective of this study is to show the effect of different sugar mixtures on growth kinetics and butanol production together with the first general demonstration of the use of BioLector® for butanol production under anaerobic conditions in comparison to the widely used serum flasks. ResultsMonitoring of growth in BioLector® microbioreactor fermentationsThe growth, utilization of carbon source and butanol production was measured using 12 different conditions, namely the amount (5 or 10 g/l) and mixture [ratio between glucose (G) and xylose (X)] of C-sources. All glucose contained in the fermentation medium was utilized entirely in all 12 conditions of the fermentation experiment (79 h). On the other hand, there was residual xylose in 5 of 12 experiments which are 10-G80:X20, 10-G40:X60, 10-G20:X80, 10-G0:X100 and 5-G0:X100 with xylose amounts of 0. 040, 0. 037, 0. 060, 0. 086 and 0. 014 g/l, respectively. Figures 1, 2, 3 present online logged data of the fermentations done in BioLector® in terms of cell mass (scattered light), pH and DO (%) allowing the continuous monitoring of growth and acid production and utilization. Fig. 1Cell mass versus time plots of fermentations done in BioLector® using 5 and 10 g/l total sugar and varied glucose (G)-to-xylose (X) ratios.

Output: pass


Input: Claim: Preserving a single species can restore an entire ecosystem. [SEP] Text: Can we restore the Chilean "espinal" with guanacos? Root-BernsteinBacked by Meredith Root-Bernstein, Michele Root---Bernstein, and 8 other backersand de Ecología y : 10. 18258/1160$1,501Raised of $1,500 Goal100%Funded on 11/17/13Successfully Funded$1,501pledged100%fundedFundedon 11/17/13? How does this work? FollowOverviewMethods(13)Discussion (5)Project ResultsWe carried out an experiment to understand the effect of reintroduced guanacos (Lama guanicoe, the wild relative of llamas) on the growth of the espino tree (Acacia caven), a common tree in the central Chilean espinal silvopastoral system. The guanacos browsed on the trees and stimulated growth. The guanacos also had several unexpected ecosystem functions in the espinal habitat. Reintroducing them to restore central Chilean woodlands seems very promising. AbstractMeredith Root-BernsteinLab NoteMarch 29, 2017ProjectGuanacos, the wild cousins of llamas, lived throughout Chile until about 500 years ago. is a mediterranean climate biodiversity hotspot, with many endemic plant and animal species. This is a pilot project to rewild the "espinal" savannas of central Chile with guanacos. We expect guanacos to have positive ecological interactions with the main tree in espinal, the espino. Guanacos in espinal should restore this habitat, raise the profile of local biodiversity, and facilitate sustainable livestock production. Ask the ScientistsDiscussionWhat is the context of this research? In this pilot rewilding project we will introduce six castrated male guanacos into a small espinal in order to study their interactions with the espino tree. We expect guanacos to browse on espino branches, and to eat their seeds. We think this will have two effects: the espinos will show "compensatory growth" and grow larger; and the seeds that have passed through the guanaco gut will show a higher rate of germination. Our primary goal is to measure these responses, and to determine at what stocking density of guanacos they are optimized.

Output: corroborate


Input: Claim: Plant-based meat alternatives often have a lower environmental impact than beef. [SEP] Text: Department of Agriculture (2020) Beef, ground, 80% lean meat/ 20% fat, patty, cooked, broiled (FDC ID: 17197; NDB Number: 23573). Department of Health and Human Services, of Health (2020) Nutrient Recommendations: Intakes (DRI). Association of (1995) Official methods of analysis of AOAC International, 16th edition. . (1957) A simple method for the isolation and purification of total lipides from animal tissues. J 226: 497-509. Association of (2006) Official methods of analysis 18th Edition, Association of Chemists. Association of (2011) Official methods of analysis 19th Edition. Arlington. (1995) Assessment of vitamin E nutritional status in yearling beef heifers. J 73: 1440-1448. (2007) Bioavailability of vitamin A sources for cattle. J 85: 1235-1238. (1985) composition of some seed oils as determined by high- performance liquid chromatography with fluorometric detection. J 50: 121-124. (1983) content of feedstuffs determined by high- performance liquid chromatographic fluorescence. J Chem 31: 1130-1333. (1980) Influence of extraction techniques on determination of α-Tocopherol in animal feedstuffs. JAOAC 63: 1258-1261. (1959) A rapid method of total lipid extraction and purification. 37: 911-917. Parks P, Goins RE (1994) In situ preparation of fatty acid methyl esters for analysis of fatty acid composition in food. J 59: 1262-1266. Barkholt V, Jensen AL (1989) Amino acid analysis: determination of cysteine plus half-cystine in proteins after hydrochloric acid hydrolysis with a disulfide compound as additive. 177: 318-322. (2000) Rapid, accurate, sensitive, and reproducible HPLC analysis of amino acids, amino acid analysis using zorbax eclipse-AAA columns and the Agilent 1100 HPLC. Agilent Publication. Henderson JW, (2010) using 18 Columns for a Variety of Agilent LC Instrumentation and Separation Goals. Note.

Output: pass


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: a 5-G100:X0, b 5-G80:X20, c 5-G60:X40, d 5-G40:X60, e 5-G20:X80, f 5-G0:X100, and g 10-G100:X0, h 10-G80:X20, i 10-G60:X40, j 10-G40:X60, k 10-G20:X80, and l 10-G0:X100. Mean values of the 4 replicas are shown together with error bars representing standard deviation, and the magnified parts of each subplot are placed on top left cornerFull size imageFig. 2pH versus time plots of fermentations done in BioLector® using 5 and 10 g/l total sugar and varied glucose (G)-to-xylose (X) ratios. a 5-G100:X0, b 5-G80:X20, c 5-G60:X40, d 5-G40:X60, e 5-G20:X80, f 5-G0:X100, and g 10-G100:X0, h 10-G80:X20, i 10-G60:X40, j 10-G40:X60, k 10-G20:X80, and l 10-G0:X100. Mean values of the 4 replicas are shown together with error bars representing standard deviationFull size imageFig. 3Dissolved oxygen (%) versus time plots of fermentations done in BioLector® using 5 and 10 g/l total sugar and varied glucose (G)-to-xylose (X) ratios. a 5-G100:X0, b 5-G80:X20, c 5-G60:X40, d 5-G40:X60, e 5-G20:X80, f 5-G0:X100, and g 10-G100:X0, h 10-G80:X20, i 10-G60:X40, j 10-G40:X60, k 10-G20:X80, and l 10-G0:X100.

Output: pass


Input: Claim: Preserving a single species can restore an entire ecosystem. [SEP] Text: Over the long term, we expect increased espino reproduction and canopy cover to translate into greater herbaceous biomass, more water retention in the soil, an increase in biodiversity, and more efficient livestock (sheep and cattle) production in espinals. We also need to start thinking about how to scale up this project. That means considering how to incentivize and support local landowners to put guanacos in their espinals, finding long term funding, developing and disseminating outreach materials, and forming local partnerships with conservationists, guanaco wool artisans, ranchers, landowners, and others. Unlike many rewilding or reintroduction projects, we are studying the ecological interaction between the guanacos and their habitat, and we are also researching the socio-political context and public attitudes towards guanaco rewilding. Understanding these two aspects from the beginning of the project guarantee a locally acceptable and sustainable project. What is the significance of this project? Rewilding is a bold new paradigm that involves the reintroduction or introduction of megafauna to achieve ecological restoration towards a culturally meaningful baseline, whether pre-human or historical. Guanaco rewilding in espinal is the only project in South America, to our knowledge, that integrates research on the restoration ecology outcomes and social aspects of a megafaunal reintroduction. Guanacos can act as habitat restoration tools as well as conservation policy tools. Promoting restoration of the espinal silvopastoral system could provide a new model of conservation in Chile, focusing on Chile's cultural landscapes, and on developing a local model of sustainable, biodiversity-friendly agriculture. The espinal, although covering a large proportion of central Chile, is considered a marginal, degraded habitat. Its biodiversity and cultural legacy are widely undervalued. Because it is not considered native forest, it does not qualify for many conservation programs; because it is not considered high-yield agriculture, it is frequently converted to monocultural vinyards or avocado plantations. Novel approaches to conservation, restoration, and silvopastoral management in espinal are urgently required. What are the goals of the project? We need a good fence! One of the biggest conservation challenges in Chile today are feral dogs. Feral dogs are known to eat guanacos, which don't seem to have good defenses against dog packs. To keep dogs out, we need a fence that has a subterranean barrier.

Output: corroborate


Input: Claim: Plant-based meat alternatives often have a lower environmental impact than beef. [SEP] Text: Login | About this this for 2. 55% of beef is discarded because of discoloration. The results indicate that the US beef industry loses $3. 73 billion annually owing to discoloration. The total amount of beef discarded per year in the US corresponds to 194. 70 million kg, which represents wasting 780,000 animals and the associated natural resources used in their production. A 1% decrease in discolored beef in the US could reduce natural resource waste and environmental impact by 23. 95 billion L of water, 96. 88 billion MJ of energy consumed, and 0. 40 million tons of carbon dioxide equivalent emission along the beef upstream value chain. Therefore, improving the color stability of meat could increase the sustainability of beef production and limit the waste of nutritious beef, so the application of novel technologies to mitigate color deterioration should be imperative. Keywords: sustainability, beef color, economic loss, water, energy, emissions How to Cite: Ramanathan, R. ,. , Feuz, R. , Mafi, G. & Pfeiffer, M. , (2022) “Economic Loss, Amount of Beef Discarded, Wastage, and Due to Beef Discoloration”, Meat and 6(1): 13218, 1-8. doi: Downloads: 12316 Views 7055 Downloads 3 4. 0 amount of food loss and waste along the food supply chain has become a compelling issue stirring up concern from stakeholders in the food system and policymakers (Muth et al. , 2019). Forty percent of food produced is lost or wasted annually, costing the food industry $218 billion (Gunders, 2017). After harvest, various food products decrease in quality at a different rate depending on chemical composition (Hammond et al. , 2015). Visual perception plays an important role in consumer perception of quality. For example, beef color is an important quality attribute that consumers associate with freshness and wholesomeness; however, beef is a highly perishable product owing to its greater water content and nutrient-dense matrix (Mancini and Hunt, 2005; Ramanathan et al. , 2020, 2021).

Output: contrast


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: Mean values of the 4 replicas are shown together with error bars representing standard deviationFull size imageRight after inoculation, we observed a lag phase of approximately 1. 5 h and 1 h for cultures containing 5 and 10 g/l total sugar, respectively (Fig. 1), likely due to the adaptation of the cells to their new environment [19]. After the lag phase, exponential growth was observed for several hours, after which a phase of continuously decreasing growth rate occurred until stationary phase was reached. The pH of the fermentation broth (Fig. 2) decreased due to the production of acetic acid and butyric acid during the exponential growth phase [20]. pH subsequently increased again during the phase of decreasing growth rate as the produced acids were re-assimilated to form solvents. The experiments under anaerobic conditions were repeated under same conditions and they all exhibited increasing DO levels as the growth proceeded. The start of the experiments was successful in terms of achieving anaerobic conditions in all runs; however, an increase of DO was observed during the experiments (Fig. 3). Standard deviations were considerably smaller during lag and exponential growth phases compared to the rest of the fermentation for both cell mass and pH values while there was no apparent correlation with time for DO. Correlation of cell mass and dissolved oxygen in BioLector® microbioreactor fermentationsKendall’s tau correlation coefficient was used to determine the correlations between cell mass (scattering light) and DO (%) because it is able predict nonlinear relationships [21] and robust in presence of outliers in data [22]. The correlations are shown in Fig. 4 for all experiments. Fig. 4Correlations between cell mass and dissolved oxygen for fermentations done in BioLector®Full size imageThe coefficient has a value between + 1 and − 1, where 1 is total positive correlation, 0 is no correlation, and − 1 is total negative correlation. When the absolute value of the correlation coefficient is smaller than 0. 35, the correlation is considered to be weak; for values between 0. 36 and 0. 67, the correlation can be regarded as moderate; a correlation is strong for coefficient values greater than 0. 68 [23]. As can be seen in Fig. 4, correlations between cell mass and DO were positive and strong for all 12 experiments with no apparent relation with the glucose-to-xylose ratio or total sugar concentration.

Output: pass


Input: Claim: All ecosystems can fully recover from deforestation within a few years. [SEP] Text: In 1979, when he was 15 years old, a boy was going by train from his home in Windsor, Ontario, Canada, to join his parents who were visiting in Toronto, Ontario. He got off the train, carrying a heavy suitcase by his right hand. He walked the length of the train platform, down stairs, across the train station, then up stairs and across a wide plaza to where his parents were waiting to pick him up. He lifted the suitcase up into the trunk of the car, and got into the back seat. About 30 seconds later, as his father was making a left turn about a block from the train station, he fell over in the back seat, unconscious. He was taken to hospital in Toronto, and then a couple of days later was transferred to my hospital in London, Ontario because it was closer to his home. It turned out that he was born with an extra rib in his neck called a cervical rib This is a rare abnormality; it happens in about 1 in 500 people, and strokes from this are very rare. The heavy suitcase had pulled his collar bone down onto the extra rib, pinching the artery to his right arm for long enough that the blood clotted. The clot backed its way down into the main artery that goes to both the brain and the arm on the right side. Then pieces of the clot went into the main artery to the front of the brain as well as into the artery that goes up through the bones in the neck to the back of the brain, and he had a severe stroke (Figure 1). Figure 1 - How the stroke happened. The heavy weight of the suitcase pulled the collar bone down, compressing the artery to the arm against an extra rib in the neck A. This caused clotting that went back down into the brachiocephalic artery, also called the Innominate artery B. Clots broke off from both ends, going up the vertebral artery (black arrows, Panel C. ) and the carotid artery, blocking the right middle cerebral artery (black arrows, Panel D. ). Credits: A. Thoracic outlet: B. Brachiocephalic artery: C. Vertebral artery: D. Arteries at the base of the brain.

Output: pass


Input: Claim: Plant-based meats are generally lower in saturated fats than animal-based meats. [SEP] Text: of Novel Plant-Alternatives and Traditional Animal-Swing1, Thompson1, Octavio Guimaraes1, Ifigenia Geornaras1, Engle1, Belk1, Gifford2 and Nair1* 1 Center for meat safety and quality, Department of states2 Department of animal science, University of Wyoming, Laramie, United states *Corresponding Author(s): :+1 9704915622, Email:mahesh. narayanan_nair@colostate. edu Received Date: Jun 26, 2021 Accepted Date: Jun 30, 2021 Published Date: Jul 09, 2021 DOI:10. 24966/FSN-1076/100109 Abstract Plant-Alternatives (PBMA) are increasing in popularity and may provide essential nutrients for some populations. Therefore, different formulations of popular PBMAs, such as Burger (BMB1 and BMB2), Burger (IFB1 and IFB2), and Morning Star’s Burger (BBB), were assessed in comparison to traditional Animal-(ABM), such as 80/20 (GP) for nutrient composition. Sodium content was considerably greater (P<0. 05) in all PBMAs than GP, along with total saturated fat content being numerically greater when compared to GP. content of all PBMAs was numerically greater than ABMs. (EAA) content was numerically greater in BMB2 than in ABMs, although anabolically important EAA, such as methionine and lysine were substantially greater (P<0. 05) in GP. While PBMAs were comparable to ABMs in many nutrients, bioavailability should be further investigated. Keywords Animal-based meats; Essential amino acids; Nutrition; Plant-based proteins; Saturated fatty acids; nutrition and food insecurity are widespread challenges facing the world, with global estimations suggesting that, every year, over 2 billion people may suffer from a nutrient deficiency, 690 million people may suffer from hunger, 144 million children, under the age of 5, may suffer from stunted growth, and over 650 million people may suffer from obesity worldwide [1-4]. Additionally, an increasing global population, accompanied by changes in urbanization, industrialization, and globalization have compounded the challenges regarding poor nutrition and food insecurity as the global demand for animal proteins is expected to double by 2050 [5-7].

Output: contrast


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: Figure 5 shows that growth rate (h−1) values were higher for cultures with 10 g/l total sugar. Average growth rate values for cultures containing 5 and 10 g/l were 0. 240 and 0. 302 h−1, respectively. However, the change in growth rate with respect to glucose-to-xylose ratio exhibited the opposite trend for ratios of G100:X0, G80:X20 and G60:X40. Highest and lowest growth rates were 0. 376 and 0. 190 h−1 observed for 10-G100:X0 and 5-G40:X60 cultures. Fig. 5Growth rate (h−1) values during exponential growth for all 12 experiments done in the BioLector® setup were determined from the BioLector® online dataFull size imageComparison of BioLector® microbioreactor and serum flask fermentationsA comparative overview of the results for serum flask and microbioreactor setups is provided in this section. Both glucose and xylose contained in the fermentation medium were utilized entirely in all 12 conditions in serum flasks, while there was some residual xylose in microbioreactor experiments as given in the results above. Butanol concentration (g/l) and butanol yield (g butanol/g sugar) values for all are summarized in Fig. 6. Fig. 6Butanol concentration a and c, and butanol yield b and d values of fermentations done in BioLector® and serum flasks with 5 and 10 g/l total sugar, respectively. Mean values of the 4 replicas are shown together with error bars representing standard deviation for BioLector® resultsFull size imageFigure 6 shows that butanol concentrations and yields were higher for cultures containing 10 g/l total sugar for all 6 different glucose-to-xylose ratios in both setups. For the BioLector®, the average butanol concentration and butanol yield values of 6 experiments with 5 and 10 g/l were 0. 192 and 0. 664 g/l, 0. 043 and 0. 084 g/g, respectively. Both butanol concentrations and yields increased with increasing xylose ratios from 0 to 40, decreased when xylose ratio increased from 40 to 80, and increased again when the ratio was G0:100X for cultures with 5 and 10 g/l total sugar.

Output: pass


Input: Claim: Superposition allows quantum bits to hold multiple states simultaneously. [SEP] Text: Figure 1A sample encryption circuit of a plaintext block being encrypted with QPP using Qiskit on an IBM Quantum system. The initialization operator produces an initial state vector that corresponds to a given specified binary string. Operator encrypts the state vector to produce a cipher state, which is then measured. This illustration corresponds to our previous work [25, 26]Full size imageUpon receiving the binary file containing the ciphertext, Bob extracts the ciphertext as a binary string. Bob then generates an Pad, using the pre-shared secret key, which consists of Hermitian conjugates of the corresponding in the Permutation Pad. Similar to Alice, Bob separates the ciphertext into 2-bit ciphertext blocks and creates a decryption circuit for each such block. Similar to the encryption circuits, the initial state in each decryption circuit is set to reflect the corresponding ciphertext bits in each given 2-bit ciphertext block. The ciphertext quantum states are then acted on with the operators from the Pad. Operators are dispatched using the pre-shared secret key, one for each circuit. The dispatching procedure is the same for Bob and Alice to ensure that Bob dispatches precisely the Hermitian conjugates of the used by Alice. This process decrypts the ciphertext states and produces plaintext states. The plaintext states are then measured, to yield the binary message. Figure 2 illustrates the general form of a decryption circuit for each ciphertext block. Figure 3 depicts the general QPP symmetric scheme. Figure 2A sample decryption circuit of a ciphertext block being decrypted with QPP using Qiskit on an IBM Quantum system. The initialization operator produces an initial state vector that corresponds to a given specified binary string. conjugate of the decrypts the state vector to produce a message state, which is then measured. This illustration corresponds to our previous work [25, 26]Full size imageFigure 3A diagram illustrating the logical flow of the QPP encryption and decryption algorithm as described in our previous work [25, 26]Full size image2 Materials and methodsThe motivation for this work was a question of whether the 2-qubit QPP can be used to encrypt superposition states, rather than basis states, and whether adding the superposition into the framework increases the security. We present an implementation of QPP with 2-qubit applied to superposition states on the IBM quantum systems using the Qiskit software development kit.

Output: corroborate


Input: Claim: Plant-based meats are generally lower in saturated fats than animal-based meats. [SEP] Text: 86mg/g. A major finding of the fatty acid analysis was that the total saturated fatty acid content of PBMAs ranged between 43 and 44% for BMB2 and IFB2, while GP and GB ranged between 39 and 42% of the total fatty acids. Additionally, total monounsaturated fatty acid content of BMB2 and IFB2 was similar to GB (at less than 55%), whereas GP contained the most total polyunsaturated fatty acid content (approximately 24%). As previously mentioned, not only did crude fat content not differ (P>0. 05) between PBMAs and GP, but total saturated fatty acid content is in BMB2 and IFB2 was similar to GP and GB. Furthermore, raw and cooked GP and GB had higher numerical values for total mono-unsaturated and polyunsaturated fatty acids than BMB2 and IFB2. Component BMB1 BMB2 IFB1 IFB2 * Cholesterol <0. 01±0b <0. 01±0b <0. 01±0b <0. 01±0b <0. 02±0b 0. 7±0. 1a 0. 7 C8:0 1. 2±0. 2b ND 8. 4±0. 3a ND ND 0. 2±0. 5c ND C10:0 ND ND 7. 0±0. 8a ND ND 0. 1±0. 01b ND C12:0 3. 5±0. 8b ND 46. 8±1. 1a ND 0. 01±0c 0. 1±0. 02c 0. 1 C14:0 ND 5. 2±0. 9b 22. 8±1. 1a 5. 9±0. 8b 0. 1±0d 1. 4±0. 1c 3. 3 C16:0 7. 4±0. 6d 11. 8±0. 5b 2. 0±0. 3e 11. 8±1. 0b 8. 5±0. 1c 23. 9±0. 7a 23. 7 C18:0 5. 3±0. 4c 8. 4±0. 5b 2. 3±0. 2d 7. 9±1. 0b 2. 0±0. 02d 12. 8±1. 3a 13.

Output: contrast


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: 00025, respectively. On the other hand, significance of effects for total sugar concentration and sugar ratio was very similar for specific growth rate with p values of 3. 71E−05 and 2. 88E−05, respectively. Therefore, the specific growth rate was equally sensitive to both factors. Table 2 shows that the effects of total sugar concentration on butanol concentration and butanol yield were significant with p values smaller than 0. 05, while the sugar ratio did not have a significant effect. The effect of total sugar concentration was less pronounced in serum flasks than what was observed in the BioLector® setup. DiscussionFor the best understanding of carbon turnover and product formation, fermentation progress in standard bioreactors is followed continuously by online measurements of pH, DO, and off-gas CO2, while cell mass, sugar and product concentrations are usually determined intermittently by offline spectrophotometry and HPLC, respectively. Such experiments are, however, laborious and costly, and the first phase of process optimization, involving, e. g. , different parameters and strains, is therefore often performed in serum flasks. We used, to our knowledge for the first time, the BioLector® technology to perform 48 anaerobic fermentations with real-time monitoring of cell mass and pH to establish it as a potential alternative to serum flask cultivations. The cell mass monitoring allowed the direct calculation of growth rates during cultivations, whereas the pH measurements provided online information about sugar consumption and switching of clostridial metabolism from acetogenic to solventogenic phase. This represents an improvement over standard offline measurement methods in the evaluation of clostridial fermentations, even though off-gas CO2, sugars and product concentrations are still not measured online. The fermentation experiments under anaerobic conditions were repeated under same conditions and they all exhibited increasing DO levels as the growth proceeded. The start of the experiments was successful in terms of achieving anaerobic conditions in all runs; however, an increase was observed during the experiments. This observation can be explained by (i) a problem with the measurement and/or sensor and (ii) diffusion/leakage of O2 from the outside environment to the BioLector® chamber. The latter is prevented by use of a protective layer on the well plate as well as a sealing of the well plate in the anaerobic chamber screwed tightly where only openings are the gas (N2) inlet and outlet (Fig.

Output: pass


Input: Claim: Superposition allows quantum bits to hold multiple states simultaneously. [SEP] Text: The produced ciphertext corresponds to the one described in Sect. 3. 2. The decryption procedure returns the exact image as in the Fig. 4. 4 Analysis and discussionIn this work, we explore whether superposition states can be encrypted using the QPP algorithm with Qiskit on the IBM Quantum systems, and what are the implications of introducing the superposition in the framework of the QPP algorithm. Our previous work [24–26] described encryption of basis states with QPP, which can be considered a quantum counterpart of the classical QPP encryption algorithm from [23]. We were then curious to examine whether the quantum implementation of QPP can be extended to the framework that can not be replicated on a classical computer, such as encryption of the superposition states and entangled states using QPP. We were also wondering if implementing the QPP algorithm to act on superposition states or entangled states improves security. For one, we were curious whether the inherent randomness nature of superposition adds a new layer of security to the scheme. For this work, we focused only on the superposition states. Recall, that in the framework of the QPP symmetric scheme, the plaintext is segmented into 2-bit blocks due to the limitations of the current quantum computers. Each block is encrypted and decrypted, one at a time, using Python’s for loop. Thus, at any given moment the quantum system has only one quantum circuit to execute. Each such circuit has 2 qubits and 2 bits, which implies that the system can be in one of the 4 possible state vectors. Therefore, it is sufficient to discuss QPP in the context of a single sample circuit that is in one of the 4 possible states. In this section, we focus mainly on the techniques that are special to the current implementation and were not used in our previous work. 4. 1 Initial set up procedureRecall, that communicating parties must first pre-share a secret key k to effectively communicate using the QPP algorithm. As with most other symmetric schemes, the security of QPP does not depend entirely on the design of the scheme itself, but also the secure establishment of the pre-shared secret k as well as the randomness of k. That is, we require that k is truly random. To generate k a good source of QRNG can be used, and the randomness of k can be tested using the ENT randomness test.

Output: corroborate


Input: Claim: Plant-based meats are generally lower in saturated fats than animal-based meats. [SEP] Text: ND: Not Detected. Palmitic (C16:0) and stearic (C18:0) acid compositions were greater (P<0. 05) in GP than in the PBMAs, although, oleic (C18:1) acid content in BMB2 and IFB2 was greater (P<0. 05) than GP. Substantial increases (P<0. 05) in oleic (C18:1) and linoleic (C18:2) acid content from IFB1 to IFB2 may be a result of sunflower oil which was used in addition to coconut oil in the IFB2 formulation [67]. Cocoa butter was substituted in the BMB2 formulation for sunflower oil, which may explain the increase (P<0. 05) in oleic acid (C18:1) content from BMB1 and decrease (P<0. 05) in linoleic acid (C18:2) content from BMB1 [67,68]. Linoleic (C18:2) and a-linolenic (C18:3) acids, cannot be synthesized de novo and are essential for human growth and development [69]. The BMB1 and BBB products proved to be a potentially excellent sources of these essential fatty acids compared to the other PBMAs. Conversely, GP was an excellent source of linoleic (C18:2) and arachidonic (C20:4) acid compared to BMB2 and IFB2. Fatty acids are readily absorbed in the human body, but the presence of fibrous materials and various thickeners and binders incorporated into PBMA formulations may inhibit fatty acid absorption [70,71]. Amino acid analysis Results from amino acid analysis for previous and current formulations of raw and cooked samples are reported in tables 10 and 11, respectively. Total essential amino acid content of raw BMB1, BMB2, and IFB1 ranged between 70 and 76mg/g while total essential amino acid content of raw GP and GB ranged between 66 and 68mg/g. Histidine, methionine, and lysine concentrations were greater (P<0.

Output: contrast


Input: Claim: Bioengineered yeast can be designed to produce high yields of biofuels from sugars. [SEP] Text: 7). Moreover, C. beijerinckii are strict anaerobes which cannot grow in presence of oxygen, and they produce CO2 and H2 as they grow that also helps to maintain anaerobic conditions in the growth medium [24]. Therefore, it is more likely to be the first reason as evident also from the correlation analysis results; strong and positive correlations between cell mass and DO were found for all experiments, which is in line with the previous observations obtained from the study of online monitoring for high-throughput screening of microbial systems in the BioLector® system [25]. It is also important to note that CO2 is not possible to be measured in BioLector® even though it gives a good indication for the growth status. Therefore, interference of CO2 with DO measurement should be investigated in future studies. Fig. 7BioLector® anaerobic chamber (left), round-well plate, and a single well showing the sensors for dissolved oxygen (DO) and pH, and the area for detecting cell mass by means of light scattering and fluorescence (right)Full size imageUnderstanding the effect of the glucose-to-xylose ratio in substrate mixtures is necessary for successful design of efficient lignocellulosic biomass fermentations. For that reason, we first studied the effect of sugar ratio on cell mass growth rate. For experiments done in BioLector®, all cultures containing xylose had a slower growth rate than the cultures with glucose as the sole sugar, essentially due to glucose being the preferred carbon source over xylose and the effect of CCR [11]. Therefore, our observation confirms that cell mass growth was affected by CCR during the fermentation by C. beijerinckii NCIMB 8052. The growth rate decreased with decreasing glucose ratio in the medium. However, when xylose was the sole sugar (G0:X100), the growth rate was similar to that of G20:X80 cultures. This trend can be assigned to noncompetitive interaction between sugars and is consistent with the results in our earlier study [13]. The standard deviation values of cell mass data increased significantly in stationary phase compared to exponential growth phase as shown in Fig. 1. Different glucose-to-xylose ratios resulted in different standard deviations as well.

Output: pass