Many Greenland glaciers have been attacked by the ocean from below and, in turn, contributed to sea-level rise from the ice sheet. The retreat and acceleration of Greenland glaciers since the mid-1990s have been attributed to the enhanced intrusion of warm Atlantic Waters (AW) into fjords, but this assertion has not been quantitatively tested on a Greenland-wide basis or included in models. Here, we investigate how AW influenced retreat at 226 marine-terminating glaciers using ocean modeling, remote sensing, and in situ observations. We identify 74 glaciers in deep fjords with AW controlling 49% of the mass loss that retreated when warming increased undercutting by 48%. Conversely, 27 glaciers calving on shallow ridges and 24 in cold, shallow waters retreated little, contributing 15% of the loss, while 10 glaciers retreated substantially following the collapse of several ice shelves. The retreat mechanisms remain undiagnosed at 87 glaciers without ocean and bathymetry data, which controlled 19% of the loss. Ice sheet projections that exclude ocean-induced undercutting may underestimate mass loss by at least a factor of 2. The Greenland Ice Sheet has contributed substantially to sea-level rise over the past few decades. Since 1972, approximately two-thirds of the ice sheet’s contribution to sea-level rise resulted from increased glacier flux with the remaining one-third from anomalous surface melt (The warming of subsurface waters at the turn of the 21st century was caused by the spreading of ocean heat from the subpolar gyre during a transition in the North Atlantic Oscillation (NAO) from a high positive phase to a low-to-negative phase . Since 2Estimates of ocean-induced melt from numerical models and in situ data indicate an average melt intensity for the submerged part of the glaciers comparable to, yet generally smaller than, the mean rate of ice advection  to begin annual measurements of ocean temperature and salinity with ship-based and airborne expendable conductivity-temperature-depth (CTD) sensors (2015–2019), coastal bathymetry in fjords and on the continental shelf from ship-based multibeam echo sounding (2015–2019) and airborne gravity (2016), and glacier thinning from airborne interferometric surface topographic surveys (2016–2019) (12 kg) of mass and 2452 km2 of grounded ice , perennial floating ice shelves (107 km2), while four glaciers already in a state of retreat (SR) contributed another 26 km2: Kofoed-Hansen Bræ, Academy, Kjer, and the southernmost branch of Upernavik Isstrøm. During the warming period 1998–2007, TF increased by +1.5° to 2°C in SE, central east (CE), and N; +2° to 3°C in southwest (SW) and NW; and more than +3°C in central west (CW) (2/year. NW accounted for most of the loss (327 km2), followed by N (229 km2) and SE (163 km2). Many ice shelves broke up during this period in front of Jakobshavn Isbræ in CW, Zachariæ Isstrøm in NE, C. H. Ostenfeld and Hagen Bræ in N, and Alison in NW. During the cooling period 2008–2017, TF decreased by 0° to 1°C in CE, NE, and N; 1.5°C in SE, SW, and NW; and 2.1°C in CW, but grounded ice continued to decline at 119 km2/year or 14% higher than the previous period. Significant changes persisted on glaciers with ice shelves, with grounded ice retreating at 26 km2/year. Petermann and Steensby, in particular, lost large portions of their ice shelves during this period.During the stable period 1992–1997, grounded ice retreated 180 kmest (CW) . Groundeqm), (ii) ice front retreat caused by glacier thinning (qs), (iii) ice advection (qf), and (iv) residual calving of grounded ice blocks (qc) required to match (v) the observed ice front retreat (qr) . Conservation of mass dictates that qr balances ablation from qm, qs, and qc, with advection from qf.To quantify the role of the ocean in controlling the evolution of these glaciers, we calculate the balance of fluxes at the grounded ice fronts that includes (i) grounded ice removed by the ocean   . From thon areas  and the qs, and its cumulative anomaly, qf, and the cumulative anomaly, qr, and the cumulative retreat, qc, and its anomaly, To quantify the anomaly in undercutting, we use a reference rate, To simplify the analysis of the relationship between glacier undercutting and the onset and progression of glacier retreat, we group the 226 glaciers into six categories. Four categories are based on the fjord/ice geometry and the detected presence of AW, pertaining to 135 glaciers that have sufficient measurements to characterize bathymetry and water properties: (i) 74 glaciers terminating in deep warm water (DW) with the detected presence of AW; (ii) 27 glaciers that break into icebergs on shallow ridges [calving ridges (CR)], independent of the presence of AW; (iii) 24 glaciers that stand in shallow cold (SC) (<100-m depth) fjords with polar water; and (iv) 10 glaciers with long (>10 km) floating extensions (FE). We partition the 91 remaining glaciers into two additional categories: (v) four glaciers already in an SR in 1992–1997 and (vi) 87 noncategorized (NC) glaciers due to a lack of bathymetry and ocean temperature data. The glacier distribution follows geography and precipitation regime . DW glac2 in 1992–2017, with a 30-fold increase from 1992–1997 (13.5 km2) to 1998–2017 (602 km2)  . In the ass loss . In contass loss . In thisass loss  contribuass loss .qm averaged 0.69 m/day, and grounded ice loss averaged 2 km2/year , ice front undercutting and retreat increased when TF increased. During the stable 1992–1997 period, km2/year . In the qm of 0.3 m/day, i.e., comparable to the natural variability of the ice front, qm.We find a broad agreement between the timing of enhanced undercutting above the range of natural variability of the calving front position, glaciers . For exaers , we estimate minor changes in qm, consistent with a lack of retreat. For Waltershausen in NE, For glaciers calving off a ridge at the terminus (CR), re in CW  and Kongre in CW , calve o retreat . For FE This study demonstrates that a large, abrupt ∼1.9°C warming of subsurface ocean waters around Greenland in 1998–2007 relative to 1992–1997 triggered a widespread mass removal at the front of marine-terminating glaciers, which forced them into an state of retreat. Cumulative anomalies in undercutting of 74 major glacier fronts standing in deep warm fjords increased mass removal at the ice front. For these glaciers, 62% of anomalous grounded ice removal was caused by ocean-induced undercutting, while the remainder was split between thinning-induced retreat (12%) and anomalous dry calving (26%). DW glaciers contributed 61% of Greenland’s loss from ice dynamics and 49% of the total loss. FE glaciers contributed 19% of the loss from ice dynamics and 15% of the total loss. NC glaciers contributed 10 and 20%, respectively. Many of the NC glaciers have likely been affected by ocean warming because their retreat rate increased 10-fold between the stable and warming periods, but we lack the oceanographic data required to quantify this relationship. The remaining glaciers  contributed 11% of the loss from ice dynamics and 17% of the total mass loss. DW glaciers therefore played a dominant role in the changes in ice dynamics in Greenland and, in turn, on the total ice sheet mass loss. Their retreat broadly coincided with the warming of subsurface ocean waters in location, time, and magnitude of undercutting.As ocean warming paused in 2008–2017, the net ice discharge from Greenland glaciers kept increasing, ice fronts kept retreating, and the rate of undercutting remained higher than in the previous decade. In effect, the changes in ocean conditions that took place in the mid-1990s did not revert to their initial state and had a profound influence on the stability and evolution of Greenland glaciers. We posit that the sustained dynamic thinning at glacier margins, particularly after 2000 (table S1), led to an unstable configuration of the glaciers, which could not reach a new equilibrium state.In this study, we document changes in the calving rates associated with changes in ice advection rates near the terminus by deducing them from the mass balance equation. We cannot identify the particular mechanisms that lead to dry calving, e.g., extensive longitudinal stretching or rotation of grounded ice blocks near floatation; hence, care must be exercised when comparing our dry calving rates to those from other studies. We also do not have an independent method to determine the uncertainty in dry calving or undercutting. If we consider glaciers for which the cumulative anomaly in ice advection Our results have implications for the projection of ice sheet mass loss with oceanic and atmospheric forcing scenarios. First, when glaciers are perturbed at their terminus by increased undercutting rates, the glaciers speed up and thin, which is conducive to more retreat if the ice fronts are close to floatation and not calving on a ridge. This feedback cannot be captured by a linear approximation of retreat based on regional ocean forcing . Second,Ice front retreat is manually digitized from level 1 Landsat 5, 7, and 8 products from 1985 to 2018. The resolution of Landsat data is 30 m for Landsat 5 (1985–1999) and 15 m for Landsat 7 and 8 . Ice front positions digitized as part of this project were supplemented with those publicly available from ] simulations using the MITgcm ocean model  are averaged across the submerged calving face and updated monthly, yielding a monthly record of undercutting in meters per day. After selection of a reference undercutting value, Qm, in meters.Ice front undercutting, qm combines uncertainties in water depth, b (10 m); subglacial discharge, qsg (20%); and TF (0.3°C), with a 15% uncertainty due to the unknown spatial distribution of subglacial discharge as calculated in  at 5.5-km spatial resolution, statistically downscaled to 1 km /20, which is +1 at the start of the simulation in 1992 and 0 at the end of the simulation in 2012. The mean adjustment to the 4-km solution, δ4km, is listed in table S1. The LLC270 product, derived to match regional oceanographic observations, does not have sufficient spatial resolution to reproduce off-the-shelf to on-the-shelf ocean heat transport processes. To correct for biases in the LLC270 solution, a depth-dependent mean difference profile is deduced from a comparison with the 4-km solution in each calibration area during the overlapping period 2001–2011. The LLC270 solution is adjusted with this mean profile for the entire series 2001–2017. The mean adjustment for the LLC270 is listed in table S1. The horizontally averaged model solutions are merged using a linear weighting over 2009–2011 to create a seamless TF series. The merged time series are then adjusted with an absolute shift applied to the entire time series to best match the CTD data from the OMG campaign  and other sources  a high-resolution (4 km) forward model in an Arctic domain run from an initial state for the period 1992–2011 . The 4-kqs, is calculated using a simple, geometrically derived relationship for grounding line migration rate as a function of surface elevation change: qs = dh/dt/[(1 − ρw/ρi)βs − αs] , ρw is the density of seawater, ρi is the density of ice, βs is the basal slope at the ice front (or grounding line for ice shelves), and αs is the slope of the glacier surface at the ice front (or grounding line for ice shelves). We apply this formula using DEMs from three time periods: (i) 1978–1987 /ρi, where ρw is the density of seawater and ρi is the density of ice. Thinning-induced retreat distance is calculated over the time period after which the glacier thinned to floatation, δts, and multiplied by the thinning-induced retreat rate, qs, i.e., dh/dt ≥ 0), we use δts = 0.Surface and basal slopes, αqr = qm + qs + qc − qf. We measure qr and qf, calculate qm and qs, and deduce qc from the mass balance equation. When integrated over the entire period into cumulative anomalies, we verify that qr and qs (no retreat and no thinning in a state of equilibrium) and reference states for qm, qc, and qf based on the reference time period 1992–1997 when most glaciers were close to a state of mass balance (see table S1).Mass conservation at the ice front dictates that


Oncholaimus; Daptonema) while from site G we reported diversity values comparable to that of the inactive sites. We hypothesized that site G presented a condition of “intermediate disturbance” that could maintain a high nematode diversity. Environmental features such as sediment temperature, pH, total organic carbon and interstitial waters ions were found to be key factors influencing patterns of meiofauna and nematofauna assemblages at SdF. Even though the general theory is that nematodes inhabiting shallow vent areas include a subset of species that live in background sediments, this was not the case for SdF vent area. Due to a marked change in nematode composition between all sites and to the presence of many exclusive species, every single investigated site was characterized by a distinct nematofauna reflecting the high spatial heterogeneity of SdF.Hydrothermal venting is rather prevalent in many marine areas around the world, and marine shallow vents are relatively abundant in the Mediterranean Sea, especially around Italy. However, investigations focusing on the characterization of meiofaunal organisms inhabiting shallow vent sediments are still scant compared to that on macrofauna. In the present study, we investigated the meiobenthic assemblages and nematode diversity inhabiting the Secca delle Fumose (SdF), a shallow water vent area located in the Gulf of Naples . In this area, characterized by a rapid change in the environmental conditions on a relative small spatial scale , we selected four sampling sites: one diffusive emission site (H); one geyser site (G) and two inactive sites . Total meiofauna abundance did not vary significantly between active and inactive sites and between surface and deeper sediment layers due to a high inter-replicate variability, suggesting a pronounced spatial-scale patchiness in distribution of meiofauna. Nematofauna at site H presented the typical features of deep-sea vents with low structural and functional diversity, high biomass and dominance of few genera (i.e.,  Scientific explorations have demonstrated the importance of hydrothermally influenced habitats both in the deep-sea and in shallow coastal habitat . ShallowDifferently from deep-sea hydrothermal vents based exclusively on chemosynthetic primary production, shallow-water vents are characterized by the presence of light that coupled with that of geothermal fluids, promotes both photo- and chemosynthetic primary production . Most ecAt deep-sea hydrothermal vents, an increase in number of meiobenthic animals coupled with a reduction in the diversity compared to non-vent areas has been reported . NematodShallow vents are characterized by non-endemic meiofauna that show higher diversity and abundance than in background sediments . While dHydrothermal venting in shallow water is a common phenomenon and marine shallow vents are abundant in the Mediterranean, in particular in the Tyrrhenian Sea . The preThe peculiarity of this active area is the rapid change in the extreme environmental conditions, from the diffusive vent site and geyser site with hot temperatures to inactive sites (see below), at a relatively small spatial scale that is, 100 m. SdF can be considered an example of how hydrothermal flux can vary at small scale in the vent habitat , creatinThe present article reports a first insight into the meiofaunal and nematode communities of SdF shallow vent area and describes the distribution and diversity of meiobenthic organisms in relation to seawater chemistry and sediment characteristics. Due to changes in stress regime and environmental conditions, we expect different meiofauna and nematofauna assemblages inhabiting the distinct sampling sites.The study area of SdF is located in the north-west side of the Gulf of Naples  characterized by the presence of white microbial mats covering the soft bottom; one geyser site  at 65 m distance from the H site, with surrounding rocky substrate covered by yellow sulfur deposits and with hot water emissions reaching 80 °C at the sediment surface; two inactive sites (CN and CS) located at a distance of 100 m from the active sites H and G  and heavy metal  concentrations, sediment grain size  and TOC are reported in All details on the environmental variable analyses considered in the present study that is, interstitial waters ion . Species richness (SR) was calculated as the total number of species collected at each site; the expected number of species for a theoretical sample of 51 specimens, ES(51), was selected and Sediment samples were sieved through a 1,000 µm mesh, and a 30 µm mesh was used to retain the smallest organisms. The fraction remaining on the latter sieve was re-suspended and centrifuged with Ludox HS40 according to g12 + g22 + g32… + ng2, where g is the relative contribution of each trophic group to the total number of individuals and n is the number of trophic groups  to 1.0 . To identify the life strategy of nematodes, the maturity index (MI) was calculated according to the weighted mean of the individual genus scores: MI = Σν(i)i(i), where ν is the c–p value (colonizers–persisters) of genus i as given in the appendix of i(i) is the frequency of that genus.Furthermore, nematode genera were categorized in four feeding guilds based on their buccal cavity morphology as described by c groups . For n =X+1) and Euclidean similarity matrices .Uni- and multivariate analyses were carried out in order to assess differences in several descriptors of meiofauna  and nematode assemblage composition , J′, ITD and MI) between sites and layers. Faunal data were LogThe sampling design included two fixed and orthogonal factors: site  and layer . The distance-based permutation analysis of variance  to determine the contribution of each species . The divMultivariate multiple regression analyses  and pH (8.1) values were comparable to the surrounding environment. All sampling sites were clearly differed due to many environmental features that changed over a relatively small spatial scale (100 m) and indicating a marked spatial heterogeneity  at CN site to 2,023 ± 1,270.2 ind./10 cm2 at G site , Foraminifera (12–13%) and Polychaeta (4–8%) (nauplii were the most represented groups (41%) followed by Ciliata (29.5%) and Nematoda (24%). SIMPER analysis on meiofaunal taxonomic composition characterizing the four sampling sites reported a dissimilarity percentage between site H and all the other sites ranging from 27% to 31%. The dissimilarity was mainly due to a different contribution of taxa, in term of abundances, at the different sampling sites and secondly to the absence of Tardigrada and Gastrotricha at the diffusive site (H). Ostracoda, Polychaeta, Gasteropoda and Halacarida, occurred frequently (2–8%) at sites G, CN and CS; other taxa, such as Ciliata and Copepoda were found in high abundances at site H (nauplii), on the opposite, decreased deepening into the sediment. These patterns characterized all sampling sites , followed by Copepoda Harpacticoida and their a (4–8%) ; Fig. 5.t site H ; Fig. 5.ng sites ; Fig. 6.A complete list of nematodes identified and total biomass values at each sampling site and at different sediment depth layers are reported in (51); J), and functional diversity indices  are reported in (51)) and equitability (J′) compared to all the other sites; while the inactive site CS was characterized by significant lower values for J′ index compared to CN and G. Overall, a total of 33 families and 2 subfamilies; 156 genera and 165 species  were identified.Nematode diversity indices  and by the presence of Elzalia sp1, Linhystera sp2 and Parastomonema sp1 as exclusive species. The geyser site G was characterized by the presence of five abundant species Chromadorita sp1, Desmodora sp1, Leptolaimus sp1, Microlaimus sp1 and Paradesmodora sp1 and by 22 exclusive species  and a high abundance of Spirinia sp1 at CS , Chromadoridae (21 genera), Cyatholaimidae (14 genera), Comesomatidae (11 genera) and Xyalidae (10 genera). Four families, represented only by one genus, were encountered just in one of the investigated sites: Ceramonematidae (site G), Siphonolaimidae (site H), Rhabdolaimidae and Rhadinematidae (site CS) . A total species . The inap1 at CS .The trophic structure of nematode assemblages was dominated by predators/omnivores  at site H and by epistrate feeders (2A) at sites G (72%) and site CN (71%); the inactive site CS was characterized by the co-dominance of the groups 2A (38%) and 2B (40%) . SignifiT °C and TOC content) and interstitial water  variables considered in our investigation might explain the meiofauna and nematofauna variability in different percentage and depending on the meiofauna and nematode descriptors considered (T °C (higher at H site), pH (more acid at H site) and NO32− and Cu concentrations. All these variables could explain the 73% of variability in meiofauna composition . A combination of sediment  the diffusive emission site (H) in which we reported the highest temperature, acidic conditions as a result of CObubbling  and the In the deep-sea, vent emissions negatively impact fauna abundance , 2005, wAt SdF vent area active and inactive sites did not differ significantly in total meiofauna abundance, contrarily to the drastic drop registered for the macrobenthic density at active sites compared to the inactive sites at SdF . OverallMeiofauna distribution can vary more along the sediment vertical profile than along a horizontal axe . Only fe2 emissions. Moreover, the presence of white microbial mat at site H could provide food for vent obligate copepods, which have developed specific adaptation to feeding on bacterial mats , the lowest nematode diversity (SR) and functional diversity (trophic diversity). In this case, and as reported in At the diffusive emission site H, where we reported the most extreme conditions, nematode assemblage showed some typical traits of nematode assemblages inhabiting shallow  and deepOncholaimus) have been reported several times inhabiting sediments near to source of the emissions at shallow vents  and bacterial mat .Nematodes belonging to the family Oncholaimidae  was comparable to that at the inactive sites, even if the geyser hosted its own nematode community characterized by the highest number of exclusive species (22). While the macrobenthic assemblages around site G was defined as “simplified” community that represented a subset of the background biota , the preurbance” , across nt areas .Spirinia, Perspiria and Chromaspirina) was the most represented taxon. Those genera, and in particular different species of Spirinia and Chromaspirina, have been reported from different environments spanning from shallow (2S (At inactive sites (CN and CS) the family of Desmodoridae  to genus ratio of 1 as reported from deep-sea vent systems  were particularly clear in influencing patterns of meiofauna and nematofauna communities  was not surprising for vent systems. Other findings, however, appear to contradict some general accepted tenets of shallow water hydrothermal vents ecology. We reported higher values of meiofaunal abundance and diversity characterizing SdF shallow vent compared to other shallow vent areas. Nematodes inhabiting sediments of SdF were clearly different and each one of the investigated site was characterized by a distinct nematode community, that means that nematodes at SdF shallow vent did not constitute a subset of species that live in background sediments. In our study, we noticed a lack of dominance by the nematode genera usually found to be abundant at shallow and deep-sea vents, except for Oncholaimus genus, sustaining the presence of a typical nematofauna community at SdF.This study confirmed some of the trends often observed in vent-associated benthic communities, that is, a pronounced small-scale spatial variability of meiofauna and particularly nematode composition that reflect the natural patchy distribution of this benthic components and the high environmental heterogeneity of the study area, typically from extreme environments. We noticed a migratory response to deeper layers by the meiofauna due to sediment disturbance , this is also a common phenomenon reported from such a kind of environment. High nematode biomass values, low diversity and the dominance by the single highly tolerant genus 10.7717/peerj.9058/supp-1Supplemental Information 1Note: some replicate layers are missing beacuse of technical reasons during the sampling.All replicates are shown. Click here for additional data file.10.7717/peerj.9058/supp-2Supplemental Information 2Reported are families, genera and species , their abundances (as row number) and total biomass values (µG C) reported for each sampling site and at different sediment depth layer. In bold species identified as exclusive at sampling sites. All replicates are reported.Click here for additional data file.


Malnutrition is a major cause of child death, and many children suffer from acute and chronic malnutrition. Nigeria has the second-highest burden of stunting globally and a higher-than-average child wasting prevalence. Moreover, there is substantial spatial variation in the prevalence of stunting and wasting in Nigeria. This paper assessed the socioeconomic inequalities and determinants of the change in socioeconomic inequalities in child stunting and wasting in Nigeria between 2013 and 2018.Data came from the 2013 and 2018 Nigeria Demographic and Health Survey. Socioeconomic inequalities in stunting and wasting were measured using the concentration curve and Erreygers’ corrected concentration index. A pro-poor concentration index is negative, meaning that the poor bear a disproportionately higher burden of stunting or wasting than the wealthy. A positive or pro-rich index is the opposite. Standard methodologies were applied to decompose the concentration index (C) while the Oaxaca-Blinder approach was used to decompose changes in the concentration indices (ΔC).The socioeconomic inequalities in child stunting and wasting were pro-poor in 2013 and 2018. The concentration indices for stunting reduced from -0.298 (2013) to -0.330 (2018) (ΔC = -0.032). However, the concentration indices for wasting increased from -0.066 to -0.048 (ΔC = 0.018). The changes in the socioeconomic inequalities in stunting and wasting varied by geopolitical zones. Significant determinants of these changes for both stunting and wasting were changes in inequalities in wealth, maternal education and religion. Under-five dependency, access to improved toilet facilities and geopolitical zone significantly explained changes in only stunting inequality, while access to improved water facilities only significantly determined the change in inequality in wasting.Addressing the socio-economic, spatial and demographic determinants of the changes in the socioeconomic inequalities in child stunting and wasting, especially wealth, maternal education and access to sanitation is critical for improving child stunting and wasting in Nigeria. Child malnutrition is a major cause of morbidity and mortality, with nutrition-related factors responsible for about 45% of all under-five deaths globally . In 2018The probability of nutritional deficiency is higher among children from poor homes, which may lead to a serious risk of an intergenerational perpetuation of the vicious cycle of poverty and undernutrition . TacklinNigeria has a significant burden of child malnutrition. Data from the 2018 National Nutrition and Health Survey show a national under-five stunting prevalence of 32%, the second-highest globally . Also, NChild malnutrition varies widely within countries and usually follows the fault line of economic deprivation . In NigeSome studies have analysed the socioeconomic inequalities in various health outcomes, including stunting and antenatal care services in Nigeria , 8. HoweData come from the 2013 and 2018 rounds of the nationally representative Nigeria Demographic and Health Survey (NDHS), the two most recent rounds of the NDHS. A stratified three-stage cluster design was used for the 2013 NDHS, comprising 904 primary sampling units (PSUs) which served as the clusters: 372 urban and 532 rural. The 2013 sample selected 40,680 households, where a minimum of 943 interviews were completed in each state. . A more detailed account of the dataset is also available elsewhere . The 201This paper used the Birth Recode data file, which contains information on every child ever born to each interviewed woman (up to a maximum of 20 children). This data file also links children to their mothers, and it contains other relevant household information.For each NDHS round, the analysis was restricted to the sample of children aged 0–59 months. After data cleaning, the final sample sizes were 23,992 and 11 150 children in the 2013 and 2018 NDHS, respectively.z-score that is less than the negative of twice the standard deviation of the WHO Child Growth Standards median is considered stunted. A child is wasted if the weight-for-height z-score is less than the negative of twice the standard deviation of the WHO Child Growth Standards median  interval. A negative (positive) index typically indicates a pro-poor (pro-rich) distribution of stunted or wasted children, while a zero index indicates perfect equality. A zero concentration index may also result from a complex relationship where the concentration curve crosses the line of equality [The concentration index, obtained from the concentration curve, is twice the covariance between the health outcome and the fractional rank in the wealth distribution, divided by the mean of the health outcome indicator –37:CH=2equality .EC) as follows [a and b refer to the lower and upper limits of the ordinal health indicator, respectively; and μH and CH remain as earlier defined.For categorical variables like indicators of stunting and wasting, the concentration index should be normalised as it may not lie between -1 and +1 . The Err follows :EC=4 and associated determinants (z) can be denoted as:φ and β are parameters, and ε is the error term. k-th explanatory variable, while Ck refers to the concentration index of the k-th explanatory variable. GCε refers to the generalised concentration index of the error term, and Socioeconomic inequalities in stunting and wasting were decomposed using the Wagstaff et al.’s  approacht indicates the time period (with the convention that t − 1 and t denote the first (i.e. 2013) and second (i.e. 2018) periods respectively, while other terms in While kηk,t, and another component that captures the changes in the elasticities of stunting or wasting with respect to these determinants: ∑kCk,t−1. The final term in ® [conindex routine was employed in obtaining the Erreygers’ normalised or corrected concentration indices, while accounting for the survey design  in each NDHS round [Eq  decomposomponent . Note thomponent , as an aomponent , 46 withonent [® . The conHS round .As shown in The unadjusted concentration curves in The (Erreygers’) normalised concentration indices depicted in For wasting, there was a general concentration of wasting on poorer children in the southern and northern zones with most of the statistically significant concentration indices pro-poor. It was only in the North-west zone that the concentration index switched from a statistically significant pro-rich to a statistically significant pro-poor index between 2013 and 2018, resulting in a significant pro-poor change. On the contrary, the North-east experienced a significant pro-rich change in inequality due to a less pro-poor index in 2018 relative to 2013.As shown in Conversely, the weighted pro-rich change due to under-five dependency in the household, the poorer and middle wealth quintiles (relative to the poorest), primary education and secondary education, Christian affiliation, access to improved toilet facilities and geopolitical zone of residence mitigated the pro-poorness of stunting between both years. Thus, the pro-rich changes in these variables mitigated the extent to which stunting was disproportionally borne by the poor over time. Geopolitical zone of residence accounted for the largest pro-rich effect (46%), followed by access to improved toilet facilities (19%) and Christian religious affiliation (18%). Other variables with similar effect, but with trivial and/or insignificant coefficients were the child’s age, the richer wealth quintile, female headship, mother’s marital status, access to an improved water source and urban residence.Belonging to the wealthiest quintile and access to improved water sources had statistically significant and nontrivial weighted pro-poor effects on wasting, accounting for 35% and 39% of the change, respectively. Given that wasting had a pro-rich change over time, these variables dampened the degree of pro-richness of the change in wasting between 2013 and 2018 (thereby disfavouring the poor relative to what would have otherwise been the case). Therefore, eliminating such changes would improve the pro-rich change in wasting over time. Other pro-poor determinants, which were numerically trivial and/or statistically insignificant, were the ages of the child and the household head, child’s sex, mother’s higher educational attainment, employment and marital status, and adherence to traditional/other religion. Conversely, belonging to the poorer and middle quintiles and attaining only primary education had weighted pro-rich changes, resulting in their accentuating the pro-rich change in wasting between 2013 and 2018. These variables accounted for 16%, 37%, and 28% of the observed changes in wasting concentration indices, respectively. Predictors with a similar sign but numerically trivial and/or statistically insignificant effects were the number of under-five children in the household, belonging to the richer quintile, mother attaining secondary education, Christianity, access to an improved toilet source, urban residence and geopolitical zone of residence.This paper has shown that stunting and wasting occur more frequently among poorer children in Nigeria. This finding was consistent in both 2013 and 2018. While the concentration of stunting and wasting is higher among poorer children, more of the poorer children are becoming stunted over time in Nigeria relative to their richer counterparts, resulting in a pro-poor change. Conversely, the extent to which poorer children bear the burden of wasting is declining, resulting in a pro-rich change.Children in the wealthiest quintile and mother’s attainment of higher education contributed to the worsening of the socioeconomic inequality in stunting over the period by increasing the degree of pro-poorness in stunting between 2013 and 2018. As expected, each of these results was due to a negative elasticity (i.e. weight) and (increasing) pro-rich socioeconomic inequality in these variables see . TherefoAs indicated in Tablswes 4 and 5, the weighted pro-rich change in maternal secondary education, Christianity, and geopolitical zone were due to a negative elasticity to stunting and less pro-richness in 2018 relative to 2013 while that of improved toilet facilities was due to a pro-rich change and a positive elasticity. The negative elasticities corroborate existing evidence of a negative relationship between these determinants and stunting in earlier studies. For instance, the negative elasticity of stunting to the geopolitical zone fixed effect concurs with prior evidence of the elevated probability of child mortality in northern Nigeria . MoreoveIn addition to maternal education that may lower stunting odds as reported in India , sanitatThe negative elasticity of wealth to nutritional health problems reported for stunting also applies to the pro-poor wealth effect on wasting, a finding which is in line with prior evidence from India . HoweverConversely, the weighted pro-rich effects of the poorer and middle wealth quintiles, as well as mothers only attaining primary education, were due to negative wasting elasticities and pro-poor changes in these predictors’ concentration indices. Thus, compared to the poorest group, children from poorer and middle wealth groups were less likely to be wasted, a finding that concurs with the negative relationship between wealth and wasting found elsewhere .Forty years since the Alma Ata Declaration, the state of child health remains dire in Nigeria, with a state of emergency already declared on maternal and child mortality . The couThis paper uses comparable datasets collected using the same methodology to compare the patterns in child stunting and wasting between 2013 and 2018. The paper demonstrates how socioeconomic inequalities in stunting and wasting in Nigeria have changed between both periods. Besides, the decomposition analysis allows for an assessment of factors that explain changes in socioeconomic inequalities, an issue of significance in the discourse of progressive realisation of child health as entrenched in the SDGs. Although this is the first study to assess these changes in socioeconomic inequalities in stunting and wasting in Nigeria, it has a few limitations. The DHS dataset that is standardised across countries limits its ability to fully account for the local context when designing questions . As showThis paper has shown that children from poorer backgrounds consistently bore a disproportionately higher burden of stunting and wasting in Nigeria between 2013 and 2018. Although the extent to which wasting occurs more frequently among poorer children in Nigeria declined over the study period, the burden of stunting disproportionately increased among the poor. Importantly, the significant factors that drive the changes in socioeconomic inequalities in stunting and wasting, especially family wealth, maternal education, sanitary conditions and location, lie outside the health sector. A deeper understanding of these social determinants of health inequalities and addressing them will significantly reduce the burden of child stunting and wasting and substantially improve child health outcomes in Nigeria.


Ice melting occurs at temperatures above Tm′ These transitions at temperatures above Tm′ can be used to estimate crystallization and recrystallization phenomena and their rates in frozen foods. Furthermore, frozen food deterioration accelerates above Tm′ and particularly as a result of temperature fluctuations during frozen food distribution and storage.Noncrystalline, freeze-concentrated structures are formed during food freezing. Such freeze-concentrated food materials often exhibit crystallization and recrystallization phenomena which can be related to the state of solutes and water. State diagrams are important tools in mapping the physical state and time-dependent properties of frozen materials at various storage temperatures. Transition of simple solutions, such as sucrose, can be used to describe vitrification and ice melting in freeze-concentrated materials. A maximally freeze-concentrated material often shows glass transition at T Food freezing is widely utilized as a food preservation technology, and it has its origins in cold climates, which allow for natural freezing and subsequent storage during winter seasons. Even early attempts for the development of food freezing technologies suffered from the slow freezing of water and development of large ice crystals . An induFood freezing provides an excellent food preservation technology for a wide range of applications. Obviously, the freezing of animal products, vegetables, berries and fruits is widely accepted and used by the food industry as well as by individual households and consumers. Likewise, formulated foods, such as ice cream, can be preserved by freezing and even consumed directly from the frozen state. The large range of food compositions and food components with significantly different physicochemical properties often challenge the frozen food industry, that is, the microbial quality may remain high, but food materials may change both chemically and physically quite differently during freezing and frozen storage .The main food preserving factors in food freezing are the dehydration of food solids because of the separation of water into dispersed ice crystals and a low temperature. A frozen food structure that is often dependent on the extent of freezing is temperature-dependent. This is because the freezing of water in biological materials occurs over a wide, composition-dependent temperature range. The freezing temperature depression of water in solutions is a well-established physicochemical property dictated by the fact that the chemical potential (μ) of a solvent at an equilibrium between two phases of the same substance must be equal. Typically, increasing molecular interactions decrease the chemical potential of solutions with a resultant freezing temperature depression .A glass transition is a property of a nonequilibrium material that occurs as a reversible transition between solid-like (glassy) and liquid-like  states of an amorphous (disordered) material. Foods in their frozen state contain ice crystals imbedded in a noncrystalline, amorphous, unfrozen fluid (syrup). This is typically because sugars or a mix of multiple solutes in the aqueous phase often show delayed or inhibited solute crystallization. At a low temperature, solutes in the absence of solute crystallization become highly freeze-concentrated, and such freeze-concentrated solutes with some unfrozen water vitrify without crystallization as temperature is sufficiently lowered ,5,6,7. Tm. Tm is the highest temperature at which ice may exist during the rewarming of a frozen solution, i.e., the last ice crystals dissolve at Tm. Ice in solutions and foods are formed as crystals that are made of water, and ice must have a lower chemical potential than water in the liquid state. The extent of freezing at normal frozen storage conditions of foods is primarily controlled by small solutes, such as sugars and dissociated salts. In other words, a temperature, Tm, can be found where ice and unfrozen water have the same chemical potential. Quite often foods are not maximally freeze-concentrated, and therefore at a typical food storage temperature (T), Tm of ice surrounded by the freeze-concentrated unfrozen phase must be equal to T, and the amount of ice also varies with temperature to satisfy μsolid = μliquid . The freezing of water in solutions is related to the chemical potential, μ, which must be the same in solid and liquid states of water at the equilibrium freezing/melting temperature, T μliquid . TypicalSugars are well-known glass formers, as was described by the early work of Parks and co-workers . The eviBiological and food materials often exhibit numerous phases in a frozen structure. The major phases include ice, hydrated macromolecules , freeze-concentrated solutes and ions, and crystallized or liquid lipids in a separate hydrophobic phase. Obviously, a structure of a particular frozen food is dependent on the type of the food and its physicochemical history. As water is the crystallizing solvent in frozen foods, ice formation results in a concentration of all dissolved substances and a partial separation of water from hydrated food components (dehydration). Simple aqueous solutions of highly soluble components, such as sugars, are often studied as models of food freezing to explain various thermal phenomena of nonequilibrium, amorphous states of freeze-concentrated solutes, and unfrozen water ,12,13,14g′) and for ice melting (Tm′) during the heating of a maximally freeze-concentrated material. Maximum ice formation produces a maximally freeze-concentrated state of solutes as described in g′. A single solute may concentrate in unfrozen water, and such an unfrozen phase forms a continuous matrix around ice crystals. During the heating of a maximally freeze-concentrated solution, the onset of an ice melting endotherm is found at Tm′. It should be noted that the glass transition occurs over a temperature range as a separate transition from ice melting. The glass transition may not complete as ice melting occurs above Tm′, and Tg′ and Tm′ may also coincide at the same temperature [g′, and its water content is given by Wg′ (unfrozen but not unfreezable water). The glass transition temperatures for various sugars and carbohydrates as shown in g′, Tm′, and Tm values for various foods was reported by Kumar et al. [Glass transitions of freeze-concentrated solutions often occur at low temperatures and well below the normal storage and distribution temperatures of frozen foods. Roos and Karel  used sucperature ,13,14. Tr et al. .g′ and Wg′, respectively. Roos and Karel [g′ of sucrose. Roos and Karel [g′ of these sugars. The study of Roos [g and Tg′ data included in The glass transition of a maximally freeze-concentrated solution is the property of the solute that is plasticized by unfrozen water. The respective quantities of the solute and unfrozen water are referred to as Cnd Karel  showed tnd Karel  showed t of Roos  investigm′. Consequently, it can be assumed that chemical potentials of unfrozen water and ice at Tm′ must be equal, but at temperatures T < Tm′ a lower chemical potential of water molecules hydrogen-bonded to sucrose must inhibit ice formation. Furthermore, vitrification occurs below Tm′ at temperatures below Tg′. It is also important to note that vitrified partially freeze-concentrated solutions do not show ice formation below their respective glass transitions, as nucleation and crystal growth become kinetically inhibited and spatially limited in the glassy state [Roos and Karel  showed tsy state ,12.A simple state diagram shows transition temperatures and other physicochemical properties of hydrophilic glass formers against solids mass fraction. State diagrams are also known as supplemented phase diagrams, which have been published over the years for food components and food products ,24,25,26g′ and Tm′ followed by equilibrium melting according to Tm, for freeze-concentrated sucrose solutions. The relaxation time data emphasize the importance of kinetic limitations of crystallization phenomena in the vicinity of the glass transition and Tm′. Furthermore, the dramatic effect of temperature on relaxation times and viscosity above Tm′ can be explained by a highly temperature-dependent extent of the freeze concentration. State diagrams provide guidance for food freezing and frozen storage as they particularly identify the conditions required for enhanced frozen state stability [tability ,27.m′. Temperatures above Tm′ show significant variations in unfrozen water content and therefore the increased rates of solute and solvent crystallization as well as other deteriorative changes. Simple state diagrams assume that the solid, glassy state is formed at temperatures below Tg. The viscosity of the glassy state is assumed to exhibit values >1012 Pa s  and solvent (water) crystallization, are not expected to occur within a glassy material because of kinetic and spatial limitations. According to Kumar et al. [g′ (state transition sensitivity) while a severe sensitivity is found to temperatures above Tm′ (phase transition sensitivity).Levine and Slade  emphasiz012 Pa s  while reFoods typically show complex interactions of concentrated constituents in the freeze-concentrated state. However, the chemical potential of water across food components at a given temperature must have the same value, and water distribution can be assumed to occur according to its fractional affinity to each constituent. Such assumption allowed Roos and Potes  to constm′ below −18 °C.Solute crystallization in frozen foods may be regarded as a harmful, spontaneous transition of noncrystalline solutes as they exhibit a thermodynamic driving force towards their equilibrium, crystalline state. Solute crystallization is typical of poorly soluble food components, such as lactose. As normal temperatures in frozen food storage are below −18 °C, solute crystallization is limited to food components with Tg′ as a result of supersaturation at a temperature below the eutectic temperature (solubility limit). Lactose exhibits a poor water solubility at low temperatures [g′ can become inhibited in blends with several sugars and by using hydrocolloids to increase the viscosity of the freeze-concentrated, unfrozen phase.Nickerson  pointed eratures ,33, and eratures . The crym. A rapid freezing of foods is often considered essential in the manufacturing of high-quality frozen foods with a large number of small crystals. The initial size of ice crystals is determined by nucleation: Rapid cooling during freezing to a low nucleation temperature may be used to obtain a large number of nuclei. As a result, a large number of small crystals occur in a rapidly frozen food. Such small crystals may remain stable at T < Tm′, but at temperatures above Tm′, and particularly as a result of temperature fluctuations, ice recrystallization leads to increasing the ice crystal size during frozen food distribution and storage [Ice formation in foods during freezing results from a thermodynamic driving force towards nucleation and crystal growth at T < T storage g′, occurs according to the Tm curve shown in m′ as the chemical potential of water molecules undergoing hydrogen bonding to solute molecules becomes less than that of ice. Such an assumption explains a sudden increase in the heat capacity associated with Tm′ of freeze-concentrated solutions during heating over the Tg′ and Tm′ temperature range [g may result in vitrification without ice formation. Such quench-cooled materials may not exhibit ice formation below the Tg as ice formation is kinetically and spatially inhibited within a glassy material. A quench-cooled material shows ice formation during reheating to above Tg. Such ice formation occurring during the reheating of a vitrified solution is known as devitrification [Ice formation at any concentration less than the mass fraction of solutes within a maximally freeze-concentrated solution, Cre range . On the fication . Ice forfication .m′ with rates increasing with temperature due to dissolving of ice crystals and a higher unfrozen water content. The main recrystallization types are known as isomass, migration, and accretive recrystallization [Isomass recrystallization—Isomass recrystallization refers to a change of a crystal without a change in mass. This is often seen as the rounding of crystals, as sharp edges exhibit a higher chemical potential of ice than round corners. In other words, crystal shape is rounded to minimize the free energy of water molecules.Migratory recrystallization—Migratory recrystallization is also known as Ostwald ripening. Migratory recrystallization occurs between several crystals of varying sizes as larger crystals size increases at the expense of smaller crystals.Accretive recrystallization—Accretion involves two or more crystals as they merge into a single, larger crystal.Recrystallization may be considered as a phenomenon occurring subsequently to crystal growth stage during a crystallization process where the shape and size of ice crystals are modified . Ice reclization ,19, whicg value. It can be assumed that dilution above Tm′ accelerates the recrystallization processes as viscosity becomes dependent on both temperature and dilution  crystallization and recrystallization during food storage. Solute crystallization decreases the quality of frozen-consumed foods, such as ice-cream. Recrystallization of ice may occur through various mechanisms as the viscosity of the unfrozen phase of a freeze-concentrated phase above Tm′ becomes temperature and dilution-dependent. Glass transition and ice-melting data are required for key food ingredients in order for the crystallization phenomena to be controlled during freezing, frozen food distribution, and frozen storage. Such data on glass transitions in frozen foods have significantly contributed to improvements in the manufacturing and storage of frozen foods, including ice cream and frozen desserts. Obvious improvements in manufacturing and product stabilization technologies have occurred through the selection of ingredients with known transition properties, control of ice crystal size, and reduced recrystallization during food distribution and storage.Ice formation in frozen food materials results in concomitant freeze concentration of solutes. At a sufficiently low temperature, an unfrozen phase with solutes and unfrozen water may vitrify. The onset temperature of ice melting of the maximally freeze-concentrated material, T


Hydrogen permeation techniques have been widely utilized to extract hydrogen effective diffusivity, as well as hydrogen trapping site characteristics in steels. Several methods have been proposed to examine reversible and irreversible trapping site characteristics. However, the inappropriate utilization of these simplified models, as well as incorrect value assignment to the key parameters, can result in several orders of magnitude difference in hydrogen trapping site density. Therefore, in order to evaluate these models and verify their application prerequisites, a serial of hydrogen permeation tests were numerically simulated and examined, separately considering reversible and irreversible hydrogen trapping sites. In the meantime, suggestions were given to conduct hydrogen permeation test more effectively, and evaluate hydrogen trapping site characteristics more precisely. In order to reduce resource consumption and improve the ecological environment, the successful development of ultra-high-strength steels, the development of modern zirconium-based, titanium-based and nickel-based alloys—that also face the problem of hydrogen embrittlement—and the implementation hydrogen energy economy to improve the global climate, make the study of hydrogen embrittlement mechanism in metallic materials and the design of anti-hydrogen embrittlement metallic materials  a current research hotspot ,2,3,4,5.effD is the hydrogen effective diffusivity examined in the experimental tests, LD is hydrogen diffusivity in matrix with trapping site effect; tN is trapping site density; LN is the density of interstitial site available for hydrogen in matrix; BE is the binding energy of hydrogen to trapping site and C0 is the hydrogen concentration at the charging side at hydrogen permeation test. Meanwhile, Equation (1) can be further transformed intoBesides fitting the experimental permeation curves, by means of the theoretical solution based on Fick’s diffusion law to obtain hydrogen effective diffusivity, the McNabb–Foster model  and OriaLN, LD and BE [Since the literature contains numerous disagreements about the values that should be assigned to parameters, such as L and EB , Equatio18/m3 to 1032/m3, which may be attributed to the intrinsic difference of the investigated materials and/or the methods difference for calculating the trapping site density [18/m3 [27/m3 [The magnitude of (reversible) hydrogen trapping site densities in steels, as well as pure irons, is reported to range from 10 density ,26. It hy [18/m3 . However3 [27/m3 . Such a Lc is hydrogen concentration in matrix; tN is trapping sites density; θt is hydrogen occupancy in trapping site; DL is hydrogen diffusivity in matrix; k and p represent the probabilities of hydrogen jumping from lattice to trapping site and hydrogen detrapping from trapping site, respectively; p0 and k0 are the pre-exponential factors of p and k, respectively; BE is the binding energy of hydrogen to trapping site; DE is the activation energy hydrogen diffusion in matrix; dE is the activation energy of hydrogen detrapping from trapping site; and D0 is the pre-exponential factor of LD. The McNabb–Foster model was utilized to simulate hydrogen diffusion behaviors incorporating hydrogen trapping site effects. To evaluate the application prerequisite of the traditional methods, the knowledge of the exact input parameters in the numerical simulation could eliminate the artificial error in fitting the experimental permeation curves. The McNabb–Foster model can be written as,29/m3 assuming the lattice constant of the steel matrix equal to 2.85 × 10−10 m. Then, hydrogen trapping site density of 4.89 × 1024/m3 under saturation represents 1 part per million (ppm) hydrogen in weight percentage. Taking pipeline X70, for example, the hydrogen charging concentration underneath the hydrogen entry side during the electrochemical permeation was reported to vary in a large range of 0.603–134 mol/m3 [The principle choice of the parameters follows our previous work . Binding4 mol/m3 , i.e., aIn the present work, the permeation curves influenced by reversible or irreversible trapping site were first numerically simulated with the assigned input of trapping site and charging condition. Traditional methods were then utilized to examine trapping site characteristic parameters based on the simulated permeation curves. Finally, the accuracy of traditional methods was evaluated by comparing the examined and input characteristic parameters of the strapping site. Tt) of the specimen with a trapping site can be related to the lag time (Lt), without considering trapping sites as [To understand the origin of above-mentioned simplified formulas, in analysis of hydrogen effective diffusivity, one should start with the McNabb–Foster model. One can deduce from this model that the lag time tTα and β can be rewritten asLN represents the tetrahedral interstitial sites for hydrogen accommodation. To ease the application of this model to experimental data, two extreme cases, dilute occupancy of trapping site and near saturation of trapping site, were examined asAccording to Equations (6) and (7), α into Equation (11), it can be further transformed into Equation (1). It is held assuming local equilibrium between hydrogen occupancy in matrix and hydrogen trapping site as well as a very limited hydrogen occupancy in trapping site. Substituting α and β into Equation (12), it can be transformed into Equation (2).Substituting α and 1 + 3α/β, based on these inputs. A trapping density of 0 cm−3 represents hydrogen diffusion simulation in pure matrix without considering the trapping effect. The lag time in pure matrix was examined as 17.8 s listed in the fifth row. The last row shows the ratio of lag time of the specimen with a trapping site to the one in pure matrix. It is clearly found that Equation (2) predicts the right ratio, comparing the third and sixth rows. However, Equation (1) gave totally wrong predictions, comparing the fourth and sixth rows. In another review work to evaluate hydrogen analysis methods utilized in steels by means of examining and fitting the experimental results [AN is the Avogadro’s constant. tN is in the unit of cm−3, instead of mol/cm−3 for better understanding. With the same purpose, the former unit was utilized in this paper.The irreversible hydrogen trapping site accommodates hydrogen until its saturation. Without changing the shape of the permeation curve, the irreversible trapping site simply delayed the whole permeation curve, as shown in  results , it was 25 was assumed. Therefore, 10.0 ppm hydrogen should be trapped, as the trapping site is saturated. However, the area enclosed by the two simulated permeation curves in The irreversible trapping site density was also suggested to be equal to the area difference between experimental permeation curve at the decay process and the one reproduced by examined effective diffusivity ,36,40,41D is hydrogen effective diffusivity examined at the build-up transient, and L is the thickness of the investigated specimen; pi is the measured current density at time (t) at specimen exit side; i0p is the initial steady-state current density (t = 0); i∞p is the new steady-state current density (t→∞), and n is the variable of summation series. In particular, for the complete decay process, i∞p= 0 and for the first hydrogen charging, i0p= 0.In α and 1 + 3α/β, based on these inputs. The fifth row shows the calculated hydrogen occupancy in trapping site near the entry side in each simulation, based on Oriani’s local equilibrium theory. The examined lag time of each simulated permeation curve is demonstrated in the sixth row. As previously introduced, lag time in pure matrix is 17.8 s. The last row shows the ratio of lag time in each specimen with trapping site to the one in the specimen without trapping site. Comparing the third and the last rows, it is obvious that Equation (1) gives a reliable prediction as hydrogen occupancy in trapping site is small and Equation (2) gives better prediction as hydrogen occupancy in trapping site is higher comparing the fourth and the last rows, which indicates that both Equations (1) and (2) work well under its own prerequisites. In conclusion, generally, as the type of hydrogen trapping site is not clear, the error caused by using Equation (2) is smaller.To evaluate the accuracy of Equations (1) and (2), in analyzing reversible trapping site density, four simulations with different trapping density and/or hydrogen charging concentration were conducted. The first four rows of Although the above-mentioned simplified formulas theoretically work well under its own prerequisite, practical analysis on permeation curves still face problems, such as the composite effects of irreversible and reversible trapping sites, as well as specimen surface related effects. As introduced above, multiple permeation is mainly utilized to separate irreversible and reversible trapping sites. However, to further eliminate surface related conditions, partial permeation method is suggested. As shown in A modified Fick’s second diffusion law was also proposed to fit the experimental permeation curves , as showtrapt is considered as the time consumed by hydrogen trapping behaviors. Obviously, Equation (16) should work in the case of irreversible hydrogen trapping sites since it demonstrates no effect on the shape of permeation curve, but retards the hydrogen permeation curve entirely, which also indicates that trapt can be further utilized to examine irreversible hydrogen trapping site density based on Equation (2). Inspired by the modified Fick’s second diffusion law, a delayed lag time method was introduced into the present work. Firstly, the traditional lag time is examined based on the entire experimental permeation curves, including the breakthrough stage. Secondly, to separate the effects of irreversible trapping sites, and eliminate specimen surface condition, a new delayed lag time could be produced by only fitting the shape characteristics of the experimental permeation curve. As shown in Here, In this present work, in order to conduct hydrogen permeation test more effectively, and evaluate hydrogen trapping site characteristics more precisely, a serial of hydrogen permeation tests were numerically simulated and examined, separately considering reversible and irreversible hydrogen trapping sites. The following conclusions can be drawn:(1) Application prerequisites of the traditional simplified methods in analyzing hydrogen trapping site characteristics should be satisfied. Equation (1) is for reversible trapping site, and Equation (2) is for irreversible trapping site.(2) Hydrogen content examined at the decay stage only accounts for hydrogen released at the specimen exit side, without considering hydrogen released at the specimen entry side. (3) The method to examine irreversible trapping site density at decay stage underestimates trapping site density by about 50%. Meanwhile, a delayed lag time method is proposed to fit experimental permeation curves and analyze irreversible trapping sites density.


Deterioration in kidney functioning is associated with aging and is a major risk factor for mortality and other poor health outcomes. Medicare expenses for poor kidney functioning are about 100 billion dollars every year. High Cystatin-C is an indicator of poor kidney functioning. We do not know if cystatin-C increases gradually as an individual ages. We use the Health and Retirement Study 2006/2008 Biomarker sample with follow-up for 8 years to examine this. Demographic and socioeconomic differences in trajectories of Cystatin-C trajectories were examined for 22,984 participants aged 50 and older. Growth curve models reveal that, although Cystatin-C increases with age , the annual increase varies by age , controlling for other socioeconomic variables. Cystatin-C increases faster for males than females. Cystatin-C of non-Hispanic Whites is lower than non-Hispanic Blacks but higher than Hispanics; there is no racial/ethnic difference in change over time. People who spent fewer years in school have higher Cystatin-C, and college graduates have slower growth in Cystatin-C compared to people who did not graduate from high school. These novel findings highlight the disparities in the process of kidney aging among older Americans.


Although infectious bronchitis virus (IBV) is the first coronavirus identified, little is known about which membrane protein of host cells could interact with IBV spike protein and facilitate the infection by the virus. In this study, by using a monoclonal antibody to the S1 protein of IBV M41 strain, we found that heat shock protein member 8 (HSPA8) could interact with spike protein of IBV. HSPA8 was found to be present on the cell membrane and chicken tissues, with highest expression level in the kidney. Results of co-IP and GST-pull-down assays indicated that the receptor binding domain (RBD) of IBV M41 could interact with HSPA8. The results of binding blocking assay and infection inhibition assay showed that recombinant protein HSPA8 and antibody to HSPA8 could inhibit IBV M41 infection of chicken embryonic kidney (CEK) cells. Further, we found that HSPA8 interacted with the N-terminal 19–272 amino acids of S1 of IBV Beaudette, H120 and QX strains and HSPA8 from human and pig also interacted with IBV M41-RBD. Finally the results of binding blocking assay and infection inhibition assay showed that recombinant HSPA8 protein and antibody to HSPA8 could inhibit IBV Beaudette strain infection of Vero cells that were treated with heparanase to remove heparan sulfate from the cell surface. Taken together, our results indicate that HSPA8 is a novel host factor involved in IBV infection. Coronaviridae, causing serious economic losses to the poultry industry (Infectious bronchitis virus (IBV) is a member of genus gamma-coronavirus in the family industry . IBV hasindustry . IBV is industry . Spike pindustry . The S1 industry .Interaction between virus protein and cellular receptor is the first step for virus infection . DiffereThough IBV was the first coronavirus discovered, study of its host cell receptor goes slowly. Previous studies showed that α-2,3 sialic acid and heparan sulfate (HS) were binding molecules for IBV onto the host cells . Recentl2 atmosphere. Vero and 293T cells were maintained in DMEM supplemented with 10% FBS at 37°C in 5% CO2 atmosphere. IBV M41 (GenBank: MK937830.1), H120 (GenBank: MK937831.1) and QX vaccine strains (GenBank: KY933090.1) were purchased from China Institute of Veterinary Drug Control and stored in our laboratory. IBV Beaudette strain was a gift from Prof. DingXiang Liu from South China Agricultural University, Guangdong, P.R. of China. Culture of IBV virus was carried out in bio-safety cabinet  in bio-safety level 2 plus (BSL2 +) laboratory.Chicken embryo kidney (CEK) cells were prepared from 17 to 19 day-old SPF embryonated chicken eggs and maintained in DMEM supplemented with 10% FBS at 37°C in 5% COIn-house mAbs against IBV S (1H1), M (2B3) and N (4C1) proteins were produced by our research group by the method described previously . mAb agaEcoRI and KpnI sites by homologous recombination. M41-S1-RBD (253), Beaudette-S1-253, H120-S1-253, QX-S1-253 gene fragments  were amplified from total RNA extracted from individual specific virus strain infected cells or infected chicken embryo allantoic fluid by RT-PCR with primers M41-S1-RBD(253)-F/R, Beaudette-S1-253-F/R, H120-S1-253-F/R, and QX-S1-253-F/R listed in EcoRI and BamHI sites by homologous recombination.HSPA8 gene fragments of different species were amplified from genomic DNA of CEK (chicken), 293T (human) and PK15 (pig) cells by PCR with primers Chicken-HSPA8-F/R, Human-HSPA8-F/R and Pig-HSPA8-F/R listed in The membrane proteins from IBV M41 infected CEK cells were extracted using Membrane protein extraction kit (Beyotime) following the manufacturer’s protocol. Membrane protein extracts were immunoprecipitated (IP) with mAbs 1H1 against IBV M41 S protein, as well as mAb against mouse IgG. The precipitated proteins were detected by silver staining and Western blotting using anti-S and anti-HSPA8 antibodies. 293T cells were cotransfected with flag-n/EGFP-C3-M41-RBD, flag-n-HSPA8/EGFP-C3-M41-RBD, flag-n-HSPA8/EGFP-C3-BD-253, flag-n/EGFP-C3-BD-253, flag-n-HSPA8/EGFP-C3-H120-253, flag-n/EGFP-C3-H120-253, flag-n-HSPA8/EGFP-C3-QX-253, flag-n/EGFP-C3-QX-253, flag-human-HSPA8/EGFP-C3-M41-253 and flag-pig-HSPA8/EGFP-C3-M41-253 and then flag-tagged HSPA8 was immunoprecipitated with flag antibody and captured by Sepharose A/G beads. The precipitated proteins were then detected by Western blotting using anti-flag and anti-GFP antibodies. On the other hand, 293T cells were cotransfected with flag-n-HSPA8/EGFP-C3-M41-RBD and flag-n-HSPA8/EGFP-C3 and then GFP-tagged M41-RBD immunoprecipitated with GFP antibody and captured by Sepharose A/G beads. The precipitated proteins were then detected by Western blotting using anti-flag and anti-GFP antibodies.Cell lysates and immunoprecipitated proteins in protein loading buffer were subjected to SDS-PAGE and transferred onto a nitrocellulose membrane. After being blocked with 5% skimmed milk, the membranes were incubated with the indicated primary antibodies at 4°C overnight. After three washes with PBS, the membranes were incubated with HRP-labeled secondary antibody at room temperature for 1 h. The protein bands were then visualized using enhanced chemiluminescence reagent and imaged using AI680 Imager .Specific band in silver stained gel was cut and sent for commercial mass spectrometry (LC-MS/MS) analysis carried out by Shanghai Applied Protein Technology Company.CEK, Vero and 293T cells were cultured in two 10 cm dishes and were harvested and washed three times with ice cold PBS. Then, 1 μg/ml of the mAb against HSPA8 (ab19136) was added into the cell suspensions and incubated for 30 min at 4°C. After that, the cells were washed 3 times by repeat centrifugation at 400 g for 5 min and the final pellets were resuspended in ice cold PBS. The fluorochrome-labeled secondary antibody was diluted (1:400) in 3% BSA/PBS and mixed with above cell suspension and again incubated for 30 min at 4°C in the dark. The cells were washed 3 times by centrifugation at 400 g for 5 min and resuspended in ice cold PBS. Finally, samples were analyzed by the flow cytometer (Beckman coulter FC500).Escherichia coli BL-21 and then purified using glutathione-sepharose beads and Ni-NTA agarose beads according to the manufacturer’s protocol. GST, GST-M41-RBD, and GST-HSPA8 recombinant proteins were bound to glutathione-sepharose beads at 4°C for 4 h. After washing five times with PBS, the beads were incubated for 12 h at 4°C with His-HSPA8 protein and EGFP-C3-M41-RBD cell lysates. After washing the beads five times, the protein complex was dissociated from the beads by boiling with 4xSDS-PAGE loading buffer for 10 min, run on SDS-PAGE, and subjected to Western blot analysis using antibodies against GST tag, 6xHis tag and GFP tag.GST, GST-M41-RBD, GST-HSPA8, and His-HSPA8 recombinant proteins were expressed in Total cellular RNA was isolated by the Trizol reagent (Vazyme) according to the manufacturer’s instructions. One microgram of total RNA was transcribed into cDNA using a reverse transcription kit (Vazyme). The relative abundance of viral RNA and mRNAs was analyzed using the ChamQ Universal SYBR RT-qPCR master mix (Vazyme) and the LightCycler 96 sequence detector system (Roche). Primers 5′-GAAGAAAACCAGTCCCAGA-3′ and 5′-TTACCAGCAACCCACAC-3′ were used to detect IBV viral RNA , the pri50 = 106.5/ml, 200 μl) was incubated with recombinant protein GST-HSPA8 (100 μg) and control recombinant protein GST (100 μg) at 37°C for 1 h. CEK cells cultured in 6-well plates were incubated with GST-HSPA8-treated virus and GST-treated virus at 4°C for 1 h. After the incubation, the cells were harvested after 3 washes with PBS. Cell-associated viral RNA was quantified by RT-qPCR which indicated the degree of inhibition of virus binding on the host cells caused by recombinant HSPA8. IBV-Beaudette strain (moi = 10) was incubated with recombinant GST-HSPA8 (100 μg) protein and control protein GST (100 μg) at 37°C for 1 h. Before addition of virus to the Vero cells, 400 μl of heparanase I (5 mIU/ml) was added to the cells and incubated at 37°C for 1 h. After washing with PBS, the cells were then incubated with GST-HSPA8-treated virus and GST-treated virus at 4°C for 1 h. After incubation, the cells were harvested after 3 washes with PBS. Cell-associated viral RNA was quantified by RT-qPCR which indicated the inhibition level of recombinant HSPA8 on IBV Beaudette binding to the Vero cells.IBV M41  at 4°C for 1 h, after three washes with PBS, the cells were then transferred to incubate at 37°C for 1 h or 24 h. The cells were harvested 1 hpi or 24 hpi after 3 washes with PBS and subjected to RT-qPCR (1 and 24 hpi) and Western blot analysis (24 hpi). The culture supernatants were also collected 24 hpi for TCID50 assay. For inhibition assay on IBV Beaudette strain, Vero cells were cultured in 6-well plates and incubated with 400 μl of heparinase I (5 mIU/ml) at 37°C for 1 h. After 3 washes with PBS, the cells were then incubated with polyclonal antibody against HSPA8  and rabbit-IgG  at 37°C for 1 h. The cells then incubated with IBV Beaudette strain (moi = 1) at 4°C for 1 h, after three washes with PBS, the cells were then transferred to incubate at 37°C for 1 or 24 h. Similarly, the cells were harvested 1 or 24 hpi after 3 washes with PBS and subjected to RT-qPCR (1 and 24 hpi) and Western blot analysis (24 hpi). The culture supernatants were also collected 24 hpi for TCID50 assay.CEK cells were cultured in 6-well plates, and incubated with polyclonal antibody against HSPA8  and rabbit-IgG  at 37°C for 1 h. The cells were then incubated with IBV M41 , P > 0.05.All data are presented as means ± standard deviations (SDs) and analyzed by GraphPad. Significant differences between two groups were analyzed using Student’s Up to now, little is known about which membrane proteins of CEK cells could interact with IBV spike protein and facilitate the infection by IBV. To address this question, the IBV-M41 strain was passaged in CEK cells to get a CEK culture adapted IBV M41 virus strain. As showed by Western blot analysis of the viral proteins, the expression level of S1 protein of IBV M41 reached a peak at 36 h post-infection , which wTo identify membrane proteins that may interact with IBV spike protein, immunoprecipitation assay was performed with membrane proteins from IBV M41-CEK infected cells using mAb 1H1 to IBV spike protein and mouse IgG. Immunoprecipated proteins were resolved by SDS-PAGE before silver staining . A speciTo verify whether HSPA8 is expressed on the cell surface, we performed indirect flow cytometry assay without cell permeabilization. As results shown in Furthermore, we checked the expression of HSPA8 in chicken tissues by RT-qPCR. The results showed that HSPA8 was found to be expressed in the tissues of kidney, liver, heart and lung of 1-day-old chickens with highest expression level in kidneys .To further verify the interaction between IBV M41 spike protein and HSPA8 of host cell, we performed immunoprecipitation assay with mAb 1H1 to spike protein in M41 infected CEK cells. As shown in in vitro GST-pull-down assay was also performed to further confirm the direct interaction between HSPA8 and M41-RBD. The results indicated that HSPA8 could specifically interact with M41-RBD, but not with the control GST protein  through its HS binding site in S2 subunit . To exclIn this study, we performed immunoprecipitation assay with membrane proteins from IBV M41 infected CEK cells and found that HSPA8 was involved in the interaction of host cell membrane and IBV spike protein . Then, wRBD of coronavirus S1 protein is primarily responsible for virus interaction with host cells. The N-terminal 19–272 amino acids of the S1 subunit of IBV-M41 was identified as a RBD . We founHowever, HSPA8 overexpression in the nonpermissive cells did not facilitate IBV infection  and the It has been widely known that HSPA8 has multiple functions including as a receptor for virus infection . In thisHS has been reported to co-localize with heat shock protein (HSP) 90 . To checE. coli could interact with HSPA8. Recent studies showed that the glycosylation of IBV M41-RBD is essential for its binding to chicken tracheal tissue and the removal of the glycosylation modification site of RBD may affect IBV binding to host cells .ML, JZ, and PZ designed the experiments. PZ, CL, and CF performed the experiments. PZ, ML, and JZ analyzed the data. HS, PX, and YY prepared the reagents. PZ, ML, and NK drafted the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The liquefaction at Petobo, Central Sulawesi affected at least 1.8 square kilometers, destroyed up to 744 houses, and caused more than 104 casualties. The data offered in this article are microtremor measurement datasets at the liquefaction site of Petobo, Central Sulawesi, Indonesia. The datasets were recorded using 3 component (3C) Guralp 6T-D broadband seismometer. There are 14 microtremor datasets, which consist of 10 datasets measured inside the liquefaction affected site and 4 datasets recorded outside the liquefaction affected site of Petobo, Central Sulawesi. Two to four datasets with 20 min length, were recorded at different times at each location. The microtremor data is crucial for horizontal to vertical (H/V) spectral ratio analysis, from which both the fundamental frequency and ellipticity curve at the measured site are deduced. The site fundamental frequency is useful for estimating the characteristics of the sub-surface condition at the measured site. The curve of the Rayleigh waves fundamental mode is needed to develop the shear wave (S-wave) velocity profile of the measured site. Specifications Table•The microtremor datasets can be used to enhance further tests at other liquefaction cases.•The microtremor datasets can be compared and related to different in-situ measurement tools or methods to provide a greater understanding of the liquefaction evaluation.•The H/V spectral ratio ellipticity curves can be enhanced by other researchers i.e. geophysics, geotechnical engineer, seismologist for further experiments•The datasets are significant to assess and validate the reliability of microtremor data analysis at the liquefaction site.1On 28 September 2018, there was amateur video evidence of liquefaction triggered by an earthquake at Petobo, Central Sulawesi, Indonesia. The liquefaction at Petobo affected at least 1.8 square kilometers , destroyMicrotremor measurement  is usefuOnsite/field conditions of the measured location were recorded during the raw data collection. Any events and potential disturbances to the recorded data i.e. near traffic, industrial noise sources, wind, rain, and a pedestrian were recorded in the field datasheet. One of the field data sheets is presented in Before producing the analyzed data format, a damping toolbox of Geospsy The H/V curves of 2The present paper focuses on microtremor measurement at the liquefaction site of Petobo, Central Sulawesi, Indonesia . In thisTo collect the data, a seismometer was deployed to the liquefaction site of Petobo, as shown in The data was collected using the Guralp CMG-6TD seismometer a. This sAs demonstrated in At least an hour noise measurement was recorded at every point. A sampling frequency of 100 Hz was set in the seismometer. The field conditions during the measurement were logged in a field data sheet ,11. The The experimental horizontal-vertical (H/V) spectral ratio is a technique to evaluate the dynamic characteristics of the measured site i.e. fundamental frequency, S-wave velocity profile. As aforementioned, this technique is an analysis of the spectral ratio of the horizontal (H) vibration Fourier amplitude spectrum over vertical (V) vibration Fourier amplitude spectrum of the recorded microtremor.0f must be greater than 10 divided by the window length of wI, which is 40 s in this paper, for the peak to be significant; (ii) the significant cycles number must be greater than 200; and (iii) the HVSR curve standard deviation amplitude, at a range frequency of 0.50f to 20f, must be less than two when 0f > 0.5 Hz, or < 3 when 0f < 0.5 Hz. All these three HVSR reliable criteria must be fulfilled before further analyses  and the resonance frequency of the S-wave has been outlined in The above findings are very useful for interpreting the experimental H/V peaks from seismic noise recordings. The experimental H/V peaks are clear for horizontally layered media with large impedance contrasts (> 4–5) and become more unclear in the case of decreasing the impedance contrasts