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Land subsidence in the Netherlands, mainly occurring in its western and northern peat and clay soils, causes significant damage to houses and infrastructure, estimated at EUR 17 billion until 2050, through differential settlement of shallow foundations, negative skin friction and fungal decay of timber piles. Various studies and reports both in The Netherlands and abroad have addressed the potential economic impacts of subsidence on houses: yet, these studies lack spatially detailed data and instead rely on generic assumptions on expected damage restoration costs. By using a hedonic pricing model, this study examines the impact of subsidence on housing prices in the Dutch cities of Rotterdam and Gouda. In contrast to earlier studies, subsidence and its impact on property values are examined at house level. We test for the effect of subsidence with data related to (i) general (uniform) subsidence (mm yr−1), (ii) differential subsidence of a building and (iii) subsidence of the surrounding area in relation to the house. Results show that uniform subsidence has the largest impact on property values with approximately −6 %, while “differential” and “surrounding” subsidence show respectively −2 % and no effect. These results could prove useful to policymakers, homeowners and housing corporations by generating a better understanding of the impact of subsidence on property values and subsequently to create awareness and spur investments in measures to mitigate damage. It should be noted that these results are specific to the research area are therefore not immediately scalable to other cities as local conditions differ.

In the Netherlands, subsidence of peat and clay soils due to (artificial) lowering of the groundwater table and loading of soft soils is commonplace, causing extensive damage to exposed and vulnerable assets. Awareness of subsidence-related damage to buildings has recently increased in the Netherlands, particularly after reported damages due to the 2018 extremely long dry period. However, despite this being a major concern to homeowners and public authorities, an integrated and systematic risk assessment on regional or national scale is currently lacking which inhibits concrete and meaningful action. In this paper, we propose a methodology for the systematic regional or countrywide assessment of two subsidence-related damage mechanisms to buildings: differential settlement of buildings on shallow foundation, and timber pile degradation due to low groundwater levels. The methodology is set up in a modular, systematic way – initially based on expert judgement and validation with available local detailed information and allows for future improvements. Progress in individual contributing factors to damages can be seamlessly integrated for the systematic improvement of damage estimates. This approach can be replicated for other damage mechanisms and detailed to provide a more local risk assessment. We expect results to be a valuable input for public or private decision making, e.g. in awareness raising and evaluating interventions.

This paper presents the approach and outcomes of an exploratory cost-benefit analysis of subsidence mitigation strategies in the inner city of Gouda, the Netherlands. Results indicate that especially the strategy focusing on reducing damage, rather than a strategy aiming to halt subsidence altogether, might have a positive economic rationale.

Over the last decade, advanced statistical inference and machine learning have been used to fill the gaps in sparse surface ocean CO2 measurements (Rödenbeck et al., 2015). The estimates from these methods have been used to constrain seasonal, interannual and decadal variability in sea–air CO2 fluxes and the drivers of these changes (Landschützer et al., 2015, 2016; Gregor et al., 2018). However, it is also becoming clear that these methods are converging towards a common bias and root mean square error (RMSE) boundary: “the wall”, which suggests that pCO2 estimates are now limited by both data gaps and scale-sensitive observations. Here, we analyse this problem by introducing a new gap-filling method, an ensemble average of six machine-learning models (CSIR-ML6 version 2019a, Council for Scientific and Industrial Research – Machine Learning ensemble with Six members), where each model is constructed with a two-step clustering-regression approach. The ensemble average is then statistically compared to well-established methods. The ensemble average, CSIR-ML6, has an RMSE of 17.16 µatm and bias of 0.89 µatm when compared to a test dataset kept separate from training procedures. However, when validating our estimates with independent datasets, we find that our method improves only incrementally on other gap-filling methods. We investigate the differences between the methods to understand the extent of the limitations of gap-filling estimates of pCO2. We show that disagreement between methods in the South Atlantic, southeastern Pacific and parts of the Southern Ocean is too large to interpret the interannual variability with confidence. We conclude that improvements in surface ocean pCO2 estimates will likely be incremental with the optimisation of gap-filling methods by (1) the inclusion of additional clustering and regression variables (e.g. eddy kinetic energy), (2) increasing the sampling resolution and (3) successfully incorporating pCO2 estimates from alternate platforms (e.g. floats, gliders) into existing machine-learning approaches.

Resolving and understanding the drivers of variability of CO2 in the Southern Ocean and its potential climate feedback is one of the major scientific challenges of the ocean-climate community. Here we use a regional approach on empirical estimates of pCO2 to understand the role that seasonal variability has in long-term CO2 changes in the Southern Ocean. Machine learning has become the preferred empirical modelling tool to interpolate time- and location-restricted ship measurements of pCO2. In this study we use an ensemble of three machine-learning products: support vector regression (SVR) and random forest regression (RFR) from Gregor et al. (2017), and the self-organising-map feed-forward neural network (SOM-FFN) method from Landschützer et al. (2016). The interpolated estimates of ΔpCO2 are separated into nine regions in the Southern Ocean defined by basin (Indian, Pacific, and Atlantic) and biomes (as defined by Fay and McKinley, 2014a). The regional approach shows that, while there is good agreement in the overall trend of the products, there are periods and regions where the confidence in estimated ΔpCO2 is low due to disagreement between the products. The regional breakdown of the data highlighted the seasonal decoupling of the modes for summer and winter interannual variability. Winter interannual variability had a longer mode of variability compared to summer, which varied on a 4–6-year timescale. We separate the analysis of the ΔpCO2 and its drivers into summer and winter. We find that understanding the variability of ΔpCO2 and its drivers on shorter timescales is critical to resolving the long-term variability of ΔpCO2. Results show that ΔpCO2 is rarely driven by thermodynamics during winter, but rather by mixing and stratification due to the stronger correlation of ΔpCO2 variability with mixed layer depth. Summer pCO2 variability is consistent with chlorophyll a variability, where higher concentrations of chlorophyll a correspond with lower pCO2 concentrations. In regions of low chlorophyll a concentrations, wind stress and sea surface temperature emerged as stronger drivers of ΔpCO2. In summary we propose that sub-decadal variability is explained by summer drivers, while winter variability contributes to the long-term changes associated with the SAM. This approach is a useful framework to assess the drivers of ΔpCO2 but would greatly benefit from improved estimates of ΔpCO2 and a longer time series.

The Southern Ocean accounts for 40 % of oceanic CO2 uptake, but the estimates are bound by large uncertainties due to a paucity in observations. Gap-filling empirical methods have been used to good effect to approximate pCO2 from satellite observable variables in other parts of the ocean, but many of these methods are not in agreement in the Southern Ocean. In this study we propose two additional methods that perform well in the Southern Ocean: support vector regression (SVR) and random forest regression (RFR). The methods are used to estimate ΔpCO2 in the Southern Ocean based on SOCAT v3, achieving similar trends to the SOM-FFN method by Landschützer et al. (2014). Results show that the SOM-FFN and RFR approaches have RMSEs of similar magnitude (14.84 and 16.45 µatm, where 1 atm = 101 325 Pa) where the SVR method has a larger RMSE (24.40 µatm). However, the larger errors for SVR and RFR are, in part, due to an increase in coastal observations from SOCAT v2 to v3, where the SOM-FFN method used v2 data. The success of both SOM-FFN and RFR depends on the ability to adapt to different modes of variability. The SOM-FFN achieves this by having independent regression models for each cluster, while this flexibility is intrinsic to the RFR method. Analyses of the estimates shows that the SVR and RFR's respective sensitivity and robustness to outliers define the outcome significantly. Further analyses on the methods were performed by using a synthetic dataset to assess the following: which method (RFR or SVR) has the best performance? What is the effect of using time, latitude and longitude as proxy variables on ΔpCO2? What is the impact of the sampling bias in the SOCAT v3 dataset on the estimates? We find that while RFR is indeed better than SVR, the ensemble of the two methods outperforms either one, due to complementary strengths and weaknesses of the methods. Results also show that for the RFR and SVR implementations, it is better to include coordinates as proxy variables as RMSE scores are lowered and the phasing of the seasonal cycle is more accurate. Lastly, we show that there is only a weak bias due to undersampling. The synthetic data provide a useful framework to test methods in regions of sparse data coverage and show potential as a useful tool to evaluate methods in future studies.

Black gram is a widely grown pulse crop in Asia, prized for its nutritional value and compatibility with various cropping systems. However, the occurrence of powdery mildew, Erysiphe polygoni DC disease poses a significant challenge to black gram production, resulting in potential yield losses in Tamil Nadu. Over a six-year period, spanning from 2017-2018 to 2022-2023, field experiments were conducted during the rabi season at the black soil farm of the Agricultural Research Station in Kovilpatti. The primary objective was to evaluate the incidence of powdery mildew in black gram and establish a statistical model by correlating it with weather variables. Notably, observations of disease index were most frequent during the flowering and pod development stages of the crop. Among the eleven weather parameters considered in the study, maximum temperature, afternoon relative humidity, and sunshine hours emerged as the key contributors to explaining the variation in the Disease Index. Further, a betareg model was developed using these selected variables to predict powdery mildew incidence in black gram.

Superconducting (SC) tokamak JT-60SA plays an essential role in fusion research and development by supporting and complementing the ITER project, providing directions to the DEMO design activity and fostering next generation scientists and engineers. Since the short circuit incident at the terminal joints of equilibrium field coil #1 during the integrated commissioning (IC) in March 2021, both EU and JA implementing agencies (IAs) have examined how to ensure safe operation of JT-60SA by mitigating the risk of possible discharge occurrence inside the cryostat. Based on the experience of the global Paschen tests, the IAs have established a strategy of risk mitigation measures, which is a combination of (i) reinforcement of insulation, (ii) avoiding unnecessary voltage application to the coil systems and (iii) immediate de-energization of the coils when deteriorated vacuum conditions are detected. Thanks to the considerable efforts of the Integrated Project Team members, the IC restarted in May 2023. After confirmation of the SC state of the coil systems (TF, EF and CS), the coil energization test and the plasma operation phase 1 (OP-1) started. The first plasma was successfully achieved on 23 October 2023 with a limited value of voltage and current applied to the coils. The plasma configuration control was also confirmed with low plasma current and low auxiliary heating power conditions. Based on the IO–F4E–QST collaboration, activities of JT-60SA have been shared with the IO and provided an important lesson for ITER assembly and commissioning, and will provide an outstanding contribution to fusion research at large. After OP-1, maintenance & enhancement phase 1 (M/E-1) starts from January 2024, in which in-vessel components are installed, and heating and diagnostic systems are extensively upgraded to allow a high power heating experiment planned in OP-2. In order to make the best use of JT-60SA, a newly organized JT-60SA experiment team will refine the research plan for the future high heating power operation phase.

In the context of increasing requirements for the effectiveness of teaching in primary school, the problems of purposeful development of cognitive abilities of students using the possibilities of digitalization of school education are becoming highly relevant. The article analyzes the process and results of digitalization of education. The authors consider the course of formation of the digital educational environment and the didactic potential of modern information technologies. The features of the development of cognitive abilities of primary school students in the context of the main aspects of cognitive processes (memory, thinking, attention, imagination) and the advantages and opportunities of the digital educational environment in this area are also highlighted.

The experiments were conducted at Agro Climate Research Centre, TNAU, Coimbatore. Calibration and validation of AquaCrop model was done using Winter and Kharif, 2022 data. Calibration showed that AquaCrop accurately simulated the canopy cover by low RMSE≤13.1%, good E≤0.76, high d≤0.94 and high R2 values ≥0.98 and biomass development by low RMSE≤13.2%, high E≤0.92, good d≤0.68 and high R2 values ≥0.95. During calibration, model well-simulated the CC under second sowing (D2) and biomass under third sowing (D3). Validation showed almost good fit of CC by low RMSE≤22.0%, good E≤0.68, high d≤0.84 and high R2 values ≥0.97 and biomass development with low RMSE≤7.1%, good E≤0.66, good d≤0.60 and high R2 values ≥0.98. During Validation, model well-simulated the CC and biomass under third sowing (D3). Model showed good fit of yield during first sowing window (D1) with a less deviation for both calibration and validation (15.6% and 5.8% respectively). From the result it could be concluded that sowing windows influence on baby corn production was accurately simulated using AquaCrop during calibration (R2=0.94) and validation (R2=0.98). Hence, AquaCrop proved to be a feasible tool for maximizing the Baby corn yield under different sowing windows.

Thrombosis is the most common and a life-threatening complication in patients with Paroxysmal Nocturnal Hemoglobinuria. One-third of patients with PNH experience at least one thromboembolic event during the course of the disease, with thrombosis being the most common cause of death in these patients. The mechanism of thrombosis in PNH is complex and continues to be of great research interest. Since the introduction of C5 complement inhibitors in the treatment of PNH, the incidence of thromboembolic events has decreased substantially. We retrospectively analyzed data concerning the thrombotic episodes of 41 patients with PNH from 14 different national hematology centers in Greece. Sixteen patients (39%) experienced at least one episode of thrombosis, including, seven (43.8%) at diagnosis, seven (43.8%) during the course of the disease and two (12.5%) patients prior to PNH diagnosis. Nearly half of these individuals (n=7, 43.8%) had multiple episodes of thrombosis during the course of their disease. The most common sites of thrombosis were intra-abdominal veins. Three out of 26 patients developed thrombosis while on eculizumab. In none of the 16 patients, the thrombotic event was fatal. Our findings, despite the small number of patients, confirmed that thrombosis continues to be a significant complication of PNH affecting more than one third of the patients.

Precision measurement plays an important role in frequency metrology and optical communications. Here the authors compare two geographically separate ultrastable lasers at 7 × 10−17 fractional frequency instability over a 2220 km optical fibre link and these measurements can be useful for dissemination of ultrastable light to distant optical clocks.

Maize is an important base crop in intensive irrigated cereal based cropping system because of its wider climatic acclimatization. In contrast, a certain microclimate is needed for commercial mushroom production. Favourable microclimatic condition that prevails in maize field created a greater opportunity to grow the warm loving Paddy Straw Mushroom “Volvariella volvacea” as intercrop. In this context, a comparative study was taken up at Tamil Nadu Agricultural University to determine the performance of paddy straw mushroom as intercrop under different microclimate created in irrigated maize and polyhouse during summer and kharif 2022. Study concluded that the microclimate variables during kharif season was more favourable for obtaining higher straw mushroom yield as maize intercrop, but the summer season was also an economically viable one. The study found that the most ideal limits of microclimate variables such as morning and afternoon temperature, morning and afternoon RH for paddy straw mushroom was 26 to 29oC, 29 to 33oC, 80 to 98 per cent and 66 to 88 per cent, respectively. The polyhouse showed its superiority in providing controlled favourable microclimate for paddy straw mushroom than the fluctuating microclimate under maize canopy, however the higher infrastructural investment in polyhouse farming is not affordable for the small and marginal farmers. The microclimate prevailed in between maize rows could support paddy straw mushroom intercropping as a viable system, which had Land Equivalent Ratio of more than 1.6 and double the time of Crop Equivalent Yield when compare to sole cropped maize.

An experiment was designed in Coimbatore, Tamil Nadu during two successive summer seasons, 2021 and 2022, to investigate the effects of high night temperature (HNT) (ambient+3oC) and CO2 (600ppm) on the yield and seed quality parameters of green gram under ten treatments in SPAR (Soil Plant Atmospheric Research) and ambient conditions. The objective of this research was to i) quantify the short-term effects of HNT and CO2 on yield contribution factors and (ii) quantify seed quality parameters employing biochemical analysis. Green gram yield and quality parameters were significantly reduced under HNT and CO2 when compared to ambient condition. Pooled data from two successive summer seasons revealed that when stress was imposed from (i) 43 to 49 DAS (Day After Sowing), the number of flowers dropped per plant significantly increased by 41.3% (ii) 29 to 35 DAS, pod setting percentage decreased by 18.5% (iii) 36 to 42 DAS, grain yield and biomass/plant decreased by 26.9 % and 29.3%respectively. In aspects of seed quality parameters, data revealed that under stress (i) Seed protein decreased by 20.5% from 50 to 56 DAS. (ii) Total sugars, polyphenols, calcium and iron decreased by 17.7, 19.9, 19.9 and 37.3%, respectively from 43 to 49 DAS. (iii) Seed moisture was reduced by 19.7% during 57 to 63 DAS. (iv) The levels of proline and phytic acid increased by 64.3 and 33.8%, respectively, from 50 to 56 DAS and 43 to 49 DAS. Overall, green gram yield was adversely affected on three treatments from 35 to 56 DAS (flower initiation stage to pod filling stage) and seed quality parameters such as protein, total sugars, polyphenols, seed moisture, proline, phytic acid, calcium and iron were reduced under HNT and CO2 from 50% flowering to pod development stage (42 to 56 DAS).

Introduction Both theoretical conceptualizations (M.&E. Laufers, E. Furman, J. Maltsberger, etc. ) and empirical studies (I. Orbach) suggest an important role body image plays in the dynamics of adolescent suicidal attempts. Objectives To study the relationships between body image vulnerability and attachment attitudes concerning early care and current relationships. Methods Participants were 100 adolescents with suicidal behavior (46 with suicidal ideation only, 54 with suicide attempts) compared to 100 controls (12-17 years). Body attitudes were assessed with Body Investment Scale (BIS), perceived early care was assessed by Parental Bonding Inventory (PBI), current attachments experiences were assessed with Attachment Style Questionnaire (ASQ). Results Adolescents with suicidal manifestations scored significantly lower on BIS Body Care (p

Background: This study assessed the diagnostic reliability of automated office blood pressure (OBP) measurements in treated hypertensive patients in primary care by evaluating the prevalence of white coat hypertension (WCH) and masked uncontrolled hypertension (MUCH) phenomena. Methods: Primary care physicians, nationwide in Greece, assessed consecutive hypertensive patients on stable treatment using OBP (1 visit, triplicate measurements) and home blood pressure (HBP) measurements (7 days, duplicate morning and evening measurements). All measurements were performed using validated automated devices with bluetooth capacity (Omron M7 Intelli-IT). Uncontrolled OBP was defined as ≥140/90 mmHg, and uncontrolled HBP was defined as ≥135/85 mmHg. Results: A total of 790 patients recruited by 135 doctors were analyzed (age: 64.5 ± 14.4 years, diabetics: 21.4%, smokers: 20.6%, and average number of antihypertensive drugs: 1.6 ± 0.8). OBP (137.5 ± 9.4/84.3 ± 7.7 mmHg, systolic/diastolic) was higher than HBP (130.6 ± 11.2/79.9 ± 8 mmHg; difference 6.9 ± 11.6/4.4 ± 7.6 mmHg, p

Timely and accurate medium range weather information is critical to conquer the impact of highly dynamic next few days’ weather on the farming. Advances in weather forecast models, as well as their increased resolution, have resulted in more accurate and realistic forecasts. An attempt was made during 2019 – 2021 at Agro Climate Research Centre, Tamil Nadu Agricultural University, Coimbatore to develop cluster of village level (@ 3km resolution) Medium Range Weather Forecast (MRWF) for Tamil Nadu with higher accuracy. In this study, Weather Research and Forecast Model (WRF v4.2.1) with four microphysics viz., Kessler, WSM3, WSM5, WSM6 schemes were tested for Tamil Nadu during CWP, HWP, SWM and NEM 2020. The MRWF generated from the WRF model v4.2.1 with WSM3 had better BSF, higher Forecast Accuracy Index (FAI) and Forecast Usability Percent (FUP) for Tamil Nadu followed by Kessler scheme. The WSM5 and WSM6 were poor performer during the study. In general, CWP had higher FAI followed by HWP, NEM & SWM. The FAI from WSM3 was 0.65 - 0.74 during NEM and 0.55 - 0.69 during SWM. Among the season, the MRWF generated during SWM were over forecasted the rainfall quantity, where the NEM and HWP had better rainfall forecast nearing actuals. The FUP was higher in NEM followed by CWP, SWM & HWP, which was 57 – 88 per cent during NEM and 46 – 82 per cent during SWM. A decreasing trend in the quantitative FUP was observed with increase in lead times, irrespective of the microphysics and seasons. Finally, the study concluded that the accuracy of village level medium range rainfall forecasts from WRF model v4.2.1 varied temporally by season and the WSM3 microphysics option having superiority in all seasons.

Continuum description of flows in micro- and nano-systems requires ad hoc addition of effects such as slip at walls, surface diffusion, Knudsen diffusion and others. While all these effects are derived from various phenomenological formulations, a sound theoretical ground unifying these effects and observations is still lacking. In this paper, adopting the definition and existence of various type of flow velocities beyond that of the standard mass velocity, we suggest derivation of model boundary conditions that may systematically justify various diffusion process occurring in micro- and nano-flows where the classical continuum model breaks down. Using these boundary conditions in conjunction with the classical continuum flow equations we present a unified derivation of various expressions of mass flow rates and flow profiles in micro- and nano-channels that fit experimental data and provide new insights into these flow profiles. The methodology is consistent with recasting the Navier–Stokes equations and appears justified for both gas and liquid flows. We conclude that these diffusion type of boundary conditions may be more appropriate to use in simulating flows in micro- and nano-systems and may also be adapted as boundary condition models in other interfacial flow modelling.

Abstract Background Physical activity in adolescence is promoted for its multi-dimensional health benefits. However, too intensive sports participation is associated with an increased injury risk. Our aim was to compare the occurrence of acute and overuse injuries in Finnish sports club members and non-members and to report training and competing habits associated with a higher injury risk in sports club members. Methods In this cross-sectional survey targeted at 14–16-year-old adolescents, a structured questionnaire was completed by 1077 sports club members and 812 non-members. The main outcome measures were self-reported acute and overuse injuries, their location and type. Results At least one acute injury in the past year was reported by 44.0% of sports club members and 19.8% of non-members (P

Abstract Background Pretreatment loss to follow-up (PTLFU) is a barrier to tuberculosis (TB) control in India’s Revised National TB Control Programme (RNTCP). PTLFU studies have not been conducted in India’s mega-cities, where patient mobility may complicate linkage to care. Methods We collected data from patient registries for May 2015 from 22 RNTCP designated microscopy centers (DMCs) in Chennai and audited addresses and phone numbers for patients evaluated for suspected TB to understand how missing contact information may contribute to PTLFU. From November 2015 to June 2016, we audited one month of records from each of these 22 DMCs and tracked newly diagnosed smear-positive patients using RNTCP records, phone calls, and home visits. We defined PTLFU cases as including: (1) patients who did not start TB therapy within 14 days and (2) patients who started TB therapy but were lost to follow-up or died before official RNTCP registration. We used multivariate logistic regression to identify factors associated with PTLFU. Results In the audit of May 2015 DMC registries, out of 3696 patients evaluated for TB, 1273 (34.4%) had addresses and phone numbers that were illegible or missing. Out of 344 smear-positive patients tracked from November 2015 to June 2016, 40 (11.6%) did not start TB therapy within 14 days and 36 (10.5%) started therapy but were lost to follow-up or died before official RNTCP registration, for an overall PTLFU rate of 22.1% (95%CI: 17.8%—26.4%). Of all PTLFU patients, 55 (72.4%) were lost to follow-up and 21 (27.6%) died before starting treatment or before RNTCP registration. In the regression analysis, age > 50 years (OR 2.9, 95%CI 1.4—6.5), history of prior TB (OR 3.9, 95%CI 2.2—7.1), evaluation at a high patient volume DMC (OR 3.2, 95% CI 1.7—6.3), and absence of legible patient contact information (OR 4.5, 95%CI 1.3—15.1) were significantly associated with PTLFU. Conclusions In an Indian mega-city, we found a high PTLFU rate, especially in patients with a prior TB history, who are at greater risk for having drug-resistance. Enhancing quality of care and health system transparency is critical for improving linkage of newly diagnosed patients to TB care in urban India.

In the present study, grape pomace (GP) was used as feed additive in the diet of weaned piglets in order to develop innovative feedstuffs and to investigate their potential beneficial effects on welfare, productivity and meat quality. For examining the antioxidant capacity of the experimental feeds, 24 piglets of 20 days old were assigned to two experimental groups receiving standard or experimental diet for 30 days. Blood and tissues collections were performed at four different time-points, 2, 20, 35 and 50 days post birth. The collected tissues were brain, heart, kidney, liver, lung, quadriceps muscle, pancreas, spleen and stomach. The following oxidative stress markers were assessed: reduced glutathione (GSH), catalase activity, total antioxidant capacity (TAC), thiobarbituric acid reactive substances (TBARS), protein carbonyls (CARB) and H2O2 decomposition activity. The effect on bacterial growth was assessed by examining microbial populations in piglets’ fecal microbiota. Furthermore, the average daily gain (ADG) was calculated and the fatty acid profile of quadriceps muscle was assessed. The results showed that piglets fed with the diet supplemented with GP, had significantly increased antioxidants mechanisms in almost all the tissues as shown by increases in GSH, H2O2 decomposition activity and TAC compared with control group. Piglets fed with the experimental diet exhibited decreased oxidative stress-induced damage to lipids and proteins as shown by decreases in TBARS and CARB in GP group compared with control. In addition, the experimental diet increased significantly ADG (by 23.65%) (P

Toll-like receptor (TLR) are responsible for recognizing various molecular patterns associated with pathogens. Their expression have been detected in skin cells such as keratinocytes and melanocytes. Numerous experimental studies demonstrate the key role of TLRs in the pathogenesis of immune diseases, including psoriasis. The objective of this study is to analyze the associations of polymorphisms in TLR7 gene and the risk of psoriasis development. DNA samples were collected from 138 patients with psoriasis and 317 healthy controls. Genotyping of rs179003, rs179008, rs179020, rs850632, rs12013728 polymorphic loci in TLR7 gene was performed using the SNPlex™method (AB, USA). SNP in the TLR7 gene rs179008 (Gln11Leu) was associated with psoriasis in entire psoriasis, late onset and sporadic subgroups (Рс = 0.0065, OR = 1.95; Рс = 0.0004, OR = 2.50; Рс = 0.0078, OR = 2.2, respectively). In conclusion, this study is the first to identify genetic variants of the TLR7 gene significantly associated with psoriasis.

Comparing the frequency of two distant optical clocks will enable sensitive tests of fundamental physics. Here, the authors compare two strontium optical-lattice clocks 690 kilometres apart to a degree of accuracy that is limited only by the uncertainty of the individual clocks themselves.

Dodecanethiol-functionalized gold nanoparticles were incorporated into the polymer matrix of diurethane-methacrylate monomer mixture in the presence of SiO2 nanoparticles (8 wt %) and a new reactive organic luminescent material ACAIN (1-N-(2-acryloyloxy-3-chloroprop-1-yl)-amino-5-isocyanonaphthalene, 1 wt %). This way, a new, probably multifunctional, polymer nanocomposite was obtained. It was shown that the addition of SiO2 nanoparticles enhances the fluorescent intensity of ACAIN by 1.5 times in the 450-550 nm spectral range. Furthermore, an additional fluorescence enhancement up to 4.5 times was observed when Au nanoparticles were added to this nanocomposite in a rather low (0.12 wt %) concentration.

A generalized model to study dislocation loops growth in irradiated binary Zr-based alloys is presented. It takes into account temperature effects, efficiencies of loops to absorb point defects dependent on the loop size, an influence of locality of grain boundary sink strength, and concentration of the alloying element. This model is used to describe the dynamics of loop radii growth in zirconium-niobium alloys under neutron irradiation at reactor conditions. A growth of both loop radii and strains is studied at different grain sizes, location from grain boundaries, and concentration of niobium. It is shown that locality of grain boundary sinks results in a non-uniform deformation of the crystal inside the grains. Additionally, an introduction of niobium as an alloying element decreases the loop radii but promotes the growth of local strains inside the grains.