The conventional measure of cosmic acceleration, denoted as \( q \), relies heavily on the frame of reference and operates within a 3D space-like coordinate system, potentially leading to misinterpretations of underlying physics. In this study, we propose a novel measure, \( q_E \), grounded in distances between causal events in 4D null space. We compare \( q_E \) with the standard \( q \) using observational data from supernovae (SN) and radial galaxy/quasar (QSO) clustering (BAO) to find a better alignment of data with \( q_E \). Our analysis indicates that cosmic expansion, when viewed in the rest frame, is decelerating, with events confined by an Event Horizon akin to that of a Black Hole interior. Rather than invoking new dark energy or modified gravity, we propose that \( \Lambda \) corresponds to a boundary term exerting an attractive influence, analogous to a rubber band resisting further expansion and preventing horizon crossing of events. Contrary to prevailing notions, interpreting current cosmic expansion measurements as deceleration, rather than acceleration, offers a more accurate depiction of observed phenomena and the underlying physics. This reevaluation prompts further investigation into the nature of cosmic expansion, as well as the exploration of alternative frameworks and measures in cosmology.

The aims of the review were to elucidate the spatial variation in sea ice algae primary production rates and biomasses (Chl a) in the Canadian Arctic – Greenland region, characterized by comparable physical settings. A database was compiled from 30 studies of sea ice algae primary production rates, biomasses (Chl a), snow and ice thicknesses, ice types, nutrient (Si(OH)4, PO4, (NO3+NO2), and (NH4) concentrations in ice and below ice from the region. Production rates were significantly high (463 mg C m-2 d-1) in Resolute Bay and in Northern Baffin Bay (317 mg C m-2 d-1) both in Canadian Arctic, as compared to a rate of 0.2 mg C m-2 d-1 in northeast Greenland. The biomasses reached 340 mg Chl a m-2 in Resolute Bay in comparison to a 0.02 mg Chl a m-2 in southwest Greenland. Primary production at other Canadian and Greenland sites were comparable but sea ice Chl a was higher (15.0 ± 13.4 mg Chl a m-2) at Canadian sites as compared to Greenland (0.8 ± 0.5 mg Chl a m-2). Resolute and Northern Baffin Bays production rates were significantly higher when compared to other Arctic Ocean sites outside the studied region. The review concludes that high production rates and biomasses in Resolute and Northern Baffin Bay’s were related to inflow and mixing of nutrient rich waters of Pacific origin. A conceptual model with drivers and inhibitors of sea ice algae primary production is projected, and the database compiles a dataset of published data for further studies.

Poultry litter was converted to biochar by torrefaction and to hydrochar by hydrothermal carbonisation. Many parameters were measured for the resulting chars, to investigate the effect of production method and production temperature. SEM showed the presence of large quantities of crystalline material on the surface of the biochars. The elemental composition of some crystals was determined as 35% K and 31% Cl. This was confirmed as sylvite (KCl) crystals, which explains the high levels of water extractable potassium in the biochar and may also be important in germination inhibition. Biochars almost totally inhibited germination, whilst hydrochars decreased germination. Although germination occurred on hydrochar, root growth was severely inhibited. Consequently, germination index may be better to determine total phytotoxicity as it measures both effects and could be used as a bioassay for chars used as soil amendments. Washing removed germination inhibition in a low temperature char (3500C), possibly by removing KCl, however root toxicity remained. There were very low levels of heavy metals, suggesting they are not the source of toxicity. In biochars, pore mean size decreased with temperature from 3500C to 6000C, due to changes in pore size distribution. Mean pore size was measured directly using SEM. The merits of this method are discussed. Low temperature biochars seem best suited for fuel as they have high calorific value, high hydrophobicity, low ash content and high yield. Higher temperatures are better for soil amendment and sequestration applications with a smaller mean pore size, higher surface area, and higher pH.

Euler-Poisson equations of a charged symmetrical body in external constant and homogeneous electric and magnetic fields are deduced starting from the variational problem, where the body is considered as a system of charged point particles subject to holonomic constraints. The final equations are written for the center-of mass-coordinate, rotation matrix and angular velocity. General solution to the equations of motion is obtained for the case of a charged ball. For the case of a symmetrical charged body (solenoid), the task of obtaining the general solution is reduced to the problem of a one-dimensional cubic pseudo-oscillator. Besides, we present a one-parametric family of solutions to the problem in elementary functions.

Two coupled climate models which participated the CMIP6 project (Coupled Model Intercomparison Project Phase 6), the Earth System Model of Chinese Academy of Sciences version 2 (CAS-ESM2-0) and the Nanjing University of Information Science and Technology Earth System Model version 3 (NESM3), were assessed in terms of the impact of four new sea ice parameterization schemes. These four new schemes are related to air-sea heat flux, radiation penetration and absorption, melt ponds, ice-ocean flux, respectively. To evaluate the effectiveness of these schemes, key sea ice variables with and without these new schemes, such as sea ice concentration (SIC) and sea ice thickness (SIT), were compared against observation and reanalysis product from 1980 to 2014. The simulations followed the design of historical experiments within the CMIP6 framework. The results revealed that both models demonstrated improvements in simulating Arctic SIC and SIT when the new parameterization schemes were implemented. The model bias of SIC in some marginal sea ice zones of Arctic was reduced, especially during March. The SIT was increased and the transpolar gradient of SIT was reproduced. The changes of spatial pattern of SIC and SIT after adding new schemes bear similarities between the two coupled models. This suggests that the new schemes have potential for broad application in climate models, especially for those with underestimated SIT.

Seaweeds are considered as one of the largest biomass producers in marine environment that is rich in bioactive metabolites and a source of natural ingredients for functional foods. The potential antioxidant activity and the potential inhibition of Caco2 cell proliferation, of crude extracts of: Chlorophyta (Ulva lactuca, and Codium tomentosum), Phaeophyta (Cystoseira crinita, Cystoseira stricta, and Sargassum vulgare), and Rhodophyta (Gelidium latifolium, Hypnea musciformis, and Jania rubens) collected from western Libyan coast were evaluated in vitro. The antioxidant activity was determined by reducing power and DPPH assays while cell proliferation, morphological changes and the cell cycle arrest were assessed by MTT, inverted light microscope and flow cytometry methods respectively. The polyphenols and flavonoids rich extracts showed remarkable reducing power and antiradical properties. After exposure of Caco2 cells to; various concentrations of extracts (50, 100,150 and 200 µg/mL) especially from brown algae for 72 h, significantly reduced cell proliferation. The antiproliferative effect of algae extracts was correlated with their polyphenol and flavonoid contents. Cell cycle analysis further showed that cells were arrested in G phases along with an increment in sub-diploidal cell population (sub-G) after extract application. These results imply that seaweeds which are rich in bioactive compounds may be in anticancer drug research programs. However, further investigations are essential to reveal the molecular mechanisms of the anticancer activities of these algae.

Currently, algae arouse a growing interest in the pharmaceutical and cosmetic area due to the fact that they have a great diversity of bioactive compounds with the potential for pharmacological, cosmetic, and nutraceutical applications. Many of these bioactive compounds are secondary metabolites whose amounts in the algae vary with varying environmental conditions. Free radicals and other active oxygen derivatives are recognized as a natural by-product of aerobic metabolism. However, reactive oxygen species directly participate in mechanisms related to various pathological states such as cancer, diabetes, atherosclerosis, Alzheimer's, and Parkinson's, among others. Diabetes mellitus (DM) is a metabolic disease resulting from changes in glucose metabolism and/or deficient production/action of insulin. This review has as its main objective to reveal the potential antioxidant and antidiabetic capacity of algae extracts.

Recreational water activities are widely recognized to have a positive impact on our physical and mental well-being. However, recreational water sources and their management are also a risk factor for human health, due to different agents, including the overgrowth of cyanobacteria and algae. These organisms have the potential to metabolize organic matter and produce thermophilic and thermotolerant toxins. Different species of algae participate in biofilm formation and impact on maintenance of equipment for water treatment. We reviewed the state of the art by providing basic definitions, taxonomy and the epidemiological and clinical issues related to the recreational uses of waters. Methods for treatments and monitoring are summarized, considering both traditional and innovative strategies. Public health and surveillance perspectives impose to focus on the detection of toxins, the formation of biofilms, the understanding of the benthonic and planktonic components as part of a larger microbial biodiversity.

Ice-binding proteins (IBPs) have several functions that permit their hosts to thrive in the presence of ice. The ability of IBPs to control ice growth makes them potential additives in various industries ranging from food storage and cryopreservation to anti-icing systems. For IBPs to be used in commercial applications, however, methods are needed to produce sufficient quantities of high-quality proteins. Here, we describe a new method for IBP purification, termed falling water ice purification (FWIP). The method is based on the affinity of IBPs for ice. A crude IBP solution is allowed to flow continuously over the large chilled vertical surface of a commercial ice machine. The temperature of the surface is lowered gradually until ice crystals are produced, to which the IBPs bind but other solutes do not. As in other ice affinity methods, FWIP does not require molecular tags and is suitable for purifying recombinant IBPs as well as IBPs from natural sources. The advantage of FWIP over other ice affinity methods is that it exploits an ice machine designed to produce large volumes of clear ice daily. This system can be easily scaled up and suits the purification of industrial quantities of IBPs. The FWIP method significantly advances the use of IBPs in research and industry.

Ice-binding proteins are crucial for adaptation of various organisms to low temperatures. Some of these, called antifreeze proteins, are usually thought to inhibit growth and/or recrystallization of ice crystals. However, prior to these events, ice must somehow appear in the organism, either coming from outside or forming inside through the nucleation process. Unlike most other works, our paper is focused on ice nucleation rather than the behavior of the already existing ice. The nucleation kinetics is studied both theoretically, with special attention paid to ice nucleation on ice-binding surfaces, and experimentally. For experimental studies, we use the ice-binding protein mIBP83, a previously constructed mutant of a spruce budworm Choristoneura fumiferana antifreeze protein. We show that mIBP83 does not affect the ice nucleation temperature in the buffer in test tubes, but hinders the impact of potent ice nucleators of various chemical natures, namely CuO powder and ice-nucleating bacteria Pseudomonas syringae. Additional experiments on human cells show that mIBP83 is concentrated in some regions, but only in cooled cells. Thus, the antifreeze protein not only binds to ice, but also blocks various sites that act or can act as ice nucleators. Such ice-preventing binding may be the crucial biological task of antifreeze proteins.

In the context of improving aircraft safety, this study focuses on the development and evaluation of a graphene-based ice detection system using an environmental chamber. The research is driven by the need for more accurate and efficient ice detection methods, crucial in mitigating in-flight icing hazards. The methodology employed involves testing flat graphene-based sensors in a controlled environment, simulating a variety of climatic conditions that could be experienced in an aircraft during its entire flight. The environmental chamber enabled precise manipulation of temperature and humidity levels, thereby providing a realistic and comprehensive test bed for sensor performance evaluation. The results were significant, revealing the graphene sensors’ heightened sensitivity and rapid response to the subtle changes in environmental conditions, especially the critical phase transition from water to ice. This sensitivity is the key to detecting ice formation at its onset, a critical requirement for aviation safety. The study concludes that graphene-based sensors, tested under varied and controlled atmospheric conditions, exhibit a remarkable potential in enhancing ice detection systems for aircraft. Their lightweight, efficient and highly responsive nature makes them a superior alternative to traditional ice detection technologies, paving the way for more advanced and reliable aircraft safety solutions.

The purpose of the present study was to investigate anti-staphylococcal activity of liposomal daptomycin, against four biofilm-producing S. aureus and S. epidermidis clinical strains, three of which are methicillin resistant. Neutral and negatively charged Daptomycin-loaded liposomes were prepared by three methods thin film hydration (TFH), DRV and microfluidic mixing (MM), and characterized for drug encapsulation (EE%), size distribution, zeta-potential, vesicle stability, drug release and drug integrity. Interestingly, whilst drug loading in THF and DRV nanosized (by extrusion) vesicles was around 30-35, very low loading (~4%) was possible in MM vesicles, requiring further explanatory investigations. Liposomal encapsulation protected daptomycin from degradation and preserve its bioactivity. Quantitative microtiter plate (crystal violet, CV), methylthiazoltetrazolium (MTT), and growth curve (GC) assays evaluated antimicrobial activity of neutral and negative charge daptomycin-liposomes towards planktonic bacteria and biofilms. Neutral liposomes exhibited dramatically enhanced inhibition of bacteria growth (compared to free drug) for all species studied, while negative charged liposomes were totally inactive. Biofilm prevention and treatment studies revealed high antibiofilm activity of liposomal daptomycin. Neutral liposomes were more active for prevention and negative charge ones for treating established biofilms. Planktonic bacteria as well as matured biofilms of low daptomycin susceptible MRSE and MRSA strains were almost completely eradicated by liposomal-daptomycin indicating the need for their further exploration as antimicrobial therapeutics.

The HER2 overexpression occurs in 10–20% of breast cancer patients. HER2+ tumors are characterized by increase in Ki67, early relapse and increased metastasis. There is little known about factors influencing early stages of HER2- tumorigenesis and diagnostic markers. Previously, it was shown that deletion of NEDD9 in mouse models of HER2 cancer interferes with tumor growth, but the role of NEDD9 upregulation is currently unexplored. We report that NEDD9 is overexpressed in a significant subset of HER2+ breast cancers and correlates with limited response to anti-HER2 therapy. To investigate the mechanisms through which NEDD9 influences HER2-dependent tumorigenesis, we generated MMTV-Cre-NEDD9 transgenic mice. The analysis of mammary glands shows extensive ductal epithelium hyperplasia, increased branching, and terminal end bud expansion. The addition of oncogene Erbb2 (neu) leads to development of early hyperplastic benign lesions earlier (~16 weeks) with a significantly shorter latency than the control mice. Similarly, NEDD9 upregulation in MCF10A-derived acini leads to hyperplasia like DCIS. This phenotype is associated with activation of ERK1/2 and AURKA kinases leading to an increased proliferation of luminal cells. These findings indicate that NEDD9 is setting permissive conditions for HER2-induced tumorigenesis, thus identifying this protein as a potential diagnostic marker for early detection.

In this work, backscattering signatures of snow-covered lake ice and sea ice from X- and Ku-band synthetic aperture radar (SAR) data are investigated. The SAR data were acquired with the ESA airborne SnowSAR sensor in winter 2012 over Lake Orajärvi in northern Finland and over landfast ice in the Bay of Bothnia of the Baltic Sea. Co-incident with the SnowSAR acquisitions in-situ snow and ice data were measured. In addition, time series of TerraSAR-X images and ice mass balance buoy data were acquired for the Lake Orajärvi in 2011-12. The main objective of our study was to investigate relationships between SAR backscattering signatures and snow depth over lake and sea ice, with the ultimate objective of assessing the feasibility of retrieval of snow characteristics using X- and Ku-band dual-polarisation (VV and VH) SAR over freshwater or sea ice. This study constitutes the first comprehensive survey of snow backscattering signatures at these two combined frequencies over both lake and sea ice. For lake ice, we show that X-band VH-polarized backscattering coefficient (σo) and the Ku-band VV/VH-ratio exhibited the highest sensitivity to the snow depth. For sea ice, the highest sensitivity to the snow depth was found from the Ku-band VV-polarised σo and the Ku-band VV/VH-ratio. However, the observed relations were relatively weak, indicating that at least for the prevailing snow conditions, obtaining reliable estimates of snow depth over lake and sea ice would be challenging using only X- and Ku-band backscattering information.

For many years marine algae has been subject of numerous researches and as a source of natural products with antiviral activity, such as terpenes, alkaloids and sulphated polysaccharides. However, the anti-Zika virus (ZIKV) potential of algae has not been studied. In this study we evaluated extracts seven species of the three major classes of seaweeds (Phaeophyceae, Chlorophyceae and Rhodophyceae) against ZIKV. All seaweeds tested are native of the Brazilian coast, except for Kappaphycus alvarezii that can be cultivated. ZIKV a mosquito-borne flavivirus, has become a public health problem. In recent years there has been an increase in the number of cases and a strong association between ZIKV outbreak and the spread of cases of Guillain-Barré Syndrome and microcephaly. All seaweed extracts tested in this work inhibits ZIKV replication in a dose-dependent manner. Caulerpa racemosa, Kappaphycus alvarezii and Osmundaria obtusiloba extracts were able to inhibit viral replication at low concentrations with EC₅₀ values ranging from 1.38 to 1.98 µg/mL. We observed that O. obtusiloba presented a significant virucidal effect. Our results suggest that extracts of C. racemosa, K. alvarezii and O. obtusiloba presented very promising results, being excellent candidates for further studies, demonstrating that marine algae are an interesting source for the development of novel anti-ZIKV agents.

Quorum sensing (QS) describes a process by which bacteria can sense the local cell density of their own species, thus enabling them to coordinate gene expression and physiological processes on a community-wide scale. Small molecules called autoinducers or QS signals, which act as intraspecies signals, mediate quorum sensing. As our knowledge of QS has progressed, so too has our understanding of the structural diversity of QS signals, along with the diversity of bacteria conducting QS and the range of ecosystems in which QS takes place. It is now also clear that QS signals are more than just intraspecies signals. QS signals mediate interactions between species of prokaryotes, and between prokaryotes and eukaryotes. In recent years, our understanding of QS signals as mediators of algae–bacteria interactions has advanced such that we are beginning to develop a mechanistic understanding of their effects. This review will summarize the recent efforts to understand how different classes of QS signals contribute to the interactions between planktonic microalgae and bacteria in our oceans, primarily N-acyl-homoserine lactones, their degradation products tetramic acids, and 2-alkyl-4-quinolones. In particular, this review will discuss the ways in which QS signals alter microalgae growth and metabolism, namely as direct effectors of photosynthesis, regulators of the cell cycle, and as modulators of other algicidal mechanisms. Furthermore, the contribution of QS signals to nutrient acquisition is discussed, and finally how microalgae can modulate these small molecules to dampen their effects.

In winter 2008-2009, Lake Occhito, a strategic multiple-uses reservoir in South Italy, was affected by an extraordinary Planktothrix rubescens bloom. P. rubescens is a filamentous potentially toxic cyanobacterium which has recently colonized many environments in Europe. A number of studies is currently available on the use of remote sensing techniques to monitor different fresh water cyanobacteria species. By contrast no specific applications are available on the remote sensing monitoring of P. rubescens. In this paper we present a specific algorithm, based on Water Leaving Reflectances (WLR) from MERIS data, atmospherically corrected using the Aerosol Optical Thickness (AOT) retrieved by MODIS data, to detect P. rubescens blooms. The high accuracy in AOT data, provided by MOD09 surface reflectance product, at 1km spatial resolution, allowed obtaining a good correlation between the WLR and the P. rubescens chlorophyll-a concentrations measured in the field, through multiple stations fluorometric profiles. A modified Normalized Difference Chlorophyll index (NDCI) algorithm is presented. The performance of the proposed algorithm has been successfully compared with other specific algorithms for turbid productive waters. We demonstrated how important is to verify the spectral behaviour of bio-optical parameters in order to develop an ad hoc algorithm that better performs with respect to standard algorithms.

Recently, ice with the stacking disorder structure, consisting of random sequences of cubic ice (Ic) and hexagonal ice (Ih) layers, is reported to be more stable than pure Ih/Ic. While, due to a much lower free energy barrier of heterogeneous nucleation, in practice, the freezing process of water is usually controlled by heterogeneous nucleation which is triggered by an external medium. Herein, molecular dynamic simulations were carried out to explore the polymorph dependence of ice on the lattice structure of substrates. It turns out that, during the nucleation stage, the polymorph of ice nuclei can be severely altered by the graphene substrate, on which the Ih was found to occupy an absolute majority in new-formed ice. This can be attributed to the structure similarity between graphene and basal face of Ih. Besides the nucleation stage, our results suggest that the substrate can not affect the polymorph of ice which is far from the graphene surface. The polymorph selectivity of graphene to Ih will diminish with the growth of ice layer.

The energy efficiency of ice hockey arenas is a central concern for the administrations, as these buildings are well known to consume a large amount of energy. Since they are composite, complex systems, solutions to such a problem can be approached from many different areas, from managerial to technological to more strictly physical. In this paper we consider heat transfer processes in an ice hockey hall, during operating conditions, with a bottom-up approach based upon on-site measurements. Detailed heat flux, relative humidity and temperature data for the ice pad and the indoor air are used for a heat balance calculation in the steady-state regime, which quantifies the impact of each single heat source. We then solve the heat conduction equation for the ice pad in transient regime, and obtain a generic analytical formula for the temperature profile that can be used in practical applications. We then apply this formula to the resurfacing process for validation, and find good agreement with an analogous numerical solution. Since it is given with implicit initial condition and boundary conditions, it can be used not only in ice hockey halls, but in a large variety of engineering applications.

Beyond their significant contribution to the dietary and industrial supplies, marine algae are considered to be a potential source of some unique metabolites with diverse health benefits. The pharmacological properties, such as antioxidant, anti-inflammatory, cholesterol homeostasis, protein clearance and anti-amyloidogenic potentials of algal metabolites endorse their protective efficacy against oxidative stress, neuroinflammation, mitochondrial dysfunction, and impaired proteostasis which are known to be implicated in the pathophysiology of neurodegenerative disorders and the associated complications after cerebral ischemia and brain injuries. As was evident in various preclinical studies, algal compounds conferred neuroprotection against a wide range of neurotoxic stressors, such as oxygen/glucose deprivation, hydrogen peroxide, glutamate, amyloid β, or 1-methyl-4-phenylpyridinium (MPP+) and, therefore, hold therapeutic promise for brain disorders. While a significant number of algal compounds with promising neuroprotective capacity have been identified over the last decades, a few of them have had access to clinical trials. However, the recent approval of an algal oligosaccharide, sodium oligomannate, for the treatment of Alzheimer's disease enlightened the future of marine algae-based drug discovery. In this review, we briefly outline the pathophysiology of neurodegenerative diseases and brain injuries for identifying the targets of pharmacological intervention, and then review the literature on the neuroprotective potentials of algal compounds along with the underlying pharmacological mechanism, and present an appraisal on the recent therapeutic advances. We also propose a rational strategy to facilitate algal metabolites-based drug development.

Marine algae have been considered as abundant source of bioactive compounds with cosmeceutical potential. Recently, a great deal of interest has focused on the health-promoting effects of marine bioactive compounds. Carbohydrate is a major and abundant constitute of marine algae that have been utilized in cosmetic formulations, such as moisturizing and thickening agents. In addition, marine carbohydrates have been suggested as promising bioactive biomaterials for various skin beneficial properties, such as anti-oxidant, anti-melanogenic and anti-skin aging. Therefore, marine algae carbohydrates have potential of skin health benefits for value-added cosmeceutical application. The present review focused on the various biological capacities and potential skin health benefits of bioactive marine carbohydrates.

In the context of circular economy that recommends the most efficient use of waste, algae wastes have a huge potential for valorisation. In this study, algae wastes obtained after alkaline extraction of active compounds from two types of marine algae (green algae – Ulva sp. and red algae – Callithamnion sp.), were used as biosorbents to remove metal ions from aqueous effluents. Their efficiency in the biosorption processes was tested for Zn(II), Cu(II) and Co(II) ions, considered technologically valuable metal ions. The batch mono-component experiments performed under optimal conditions (pH = 5.0; 4.0 g biosorbent/L; 22 ± 1C), showed that more than 75 % of the metal ions are removed when their initial concentration is less than 1.25 mmol/L. The very good fit of the experimental data with the pseudo-second order kinetic model and Langmuir isotherm model, and the high values obtained for the maximum biosorption capacity (qmax: Cu(II) (0.52 mmol/g) > Zn(II) (0.41 mmol/g) > Co(II) (0.39 mmol/g) for G-AWB, and qmax: Cu(II) (1.78 mmol/g) > Zn(II) (1.72 mmol/g) > Co(II) (1.66 mmol/g) for R-AWB) highlights the potential use of these biosorbents to remove such technologically valuable metal ions from industrial wastewater. This possibility was tested using industrial wastewater samples obtained from the metal coating industry. Quantitative removal (> 91 %) of Zn(II), Cu(II) and Co(II) ions was obtained when their initial concentration was adjusted to 50 mg/L. Also, the rapid and efficient desorption of these metal ions from loaded-biosorbents, by simple treatment with small volumes of HNO3 (10-1 mol/L), further emphasizes the possibility of their recovery and reuse in the technological circuit. The results included in this study indicate that algae wastes have the potential to be used in industrial effluents decontamination processes and opens new perspectives for the implementation of circular economy principles.

Article contents the analytical model of the drift of a separate ice field under action of wind and current, which velocities and directions can vary during time. Model takes into account the mass of ice, added mass of sea water and the effects of the wind and current on the ice field in form the friction on its upper and underwater surfaces and frontal resistance on its end (forward and backward) surfaces. Results of performed the steady wind drift of the ice fields modelling show the drift velocity exceeds considerable known velocity of a compact ice cover wind drift. Drifting ice field has the certain kinetic energy that should be released when collision with unmovable obstacle and spent on brittle breakdown of part of the ice field. Volume of formed small ice pieces (fragments of ice field) was estimated by comparison of the specific energy of the sea ice brittle destruction and the kinetic energy of drifting ice field. Article presents the results of estimation of possible volume of the ice pieces and the scales of formed piles as result of collision with an obstacle depending on initial dimensions of ice field and wind speed. Developed models and the results of computer modelling can be used to estimate the ice pile sizes near the stationary platforms and terminals on the Arctic seas.

The aim of the study was to assess the effect of the addition of inulin and the replacement of part of inulin with apple fiber on the physicochemical and organoleptic properties. Moreover, the survival of Bifidobacterium animalis ssp. Lactis Bb-12 and Lactobacillus rhamnosus was studied in sheep milk ice cream. There was no effect of apple fiber and the type of bacteria on the number of bacteria of the probiotics after fermentation. As a result of freezing, mixture containing Bifidobacterium animalis ssp. Lactis Bb-12, there was a significant reduction in the bacterial from 0.39 log cfu g −1 to 0.46 log cfu g −1. In all ice cream on the 21st day of storage, it exceeded 10 log cfu g –1, which means that the ice cream retained the status of probiotic products. The Lactobacillus rhamnosus ice cream showed a lower yellow colour compared to the Bifidobacterium Bb-12 ice cream. The overrun of sheep's milk ice cream was within a range from 78.50% to 80.41%. The appearance of sheep's milk ice cream is influenced considerably by the addition of fiber and the type of bacteria and the interaction between the type of bacteria and the addition of fiber and storage time and fiber.

A brown seaweed consumed worldwide, Fucus vesiculosus, has been used to prevent atherosclerosis and hypercholesterolemia, among other uses, however, the mechanisms of action that lead to these effects are not yet fully understood. An F. vesiculosus aqueous extract, prepared as a soup was characterized as rich in sev-eral bioactive compounds, mainly phlorotannin and peptides. This work aims to study the in vitro effect of this extract on the expression of different proteins involved in the synthesis and transport of cholesterol in HepG2 cells, though a proteomic analysis, western blot and qRT-PCR. The results demonstrated that, in liver cells, the extract decreases the expression of 4 proteins involved in cholesterol biosynthesis process and also decrease the expression of two important transporters proteins of cholesterol, NPC1L1 and ABCG5, as well as decrease the NPC1L1 mRNA levels. Our study demonstrates some mechanisms of action of bioactive com-pounds from F. vesiculosus that may explain its previously reported hypocholesterolemic effect.

A recently developed thermodynamic theory for the determination of the driving force of crystallization and the crystal–melt surface tension is applied to the ice–water system employing the new Thermodynamic Equation of Seawater TEOS-10. The deviations of approximative formulations of the driving force and the surface tension from the exact reference properties are quantified, showing that the proposed simplifications are applicable for low to moderate undercooling and pressure differences to the respective equilibrium state of water. The TEOS-10 based predictions of the ice crystallization rate revealed pressure-induced deceleration of ice nucleation with an increasing pressure, and acceleration of ice nucleation by pressure decrease. This result is in, at least, qualitative agreement with laboratory experiments and computer simulations. Both the temperature and pressure dependencies of the ice–water surface tension were found to be in line with the le Chatelier–Braun principle, in that the surface tension decreases upon increasing degree of metastability of water (by decreasing temperature and pressure), which favors nucleation to move the system back to a stable state. The reason for this behavior is discussed. Finally, the Kauzmann temperature of the ice–water system was found to amount TK=116K, which is far below the temperature of homogeneous freezing. The Kauzmann pressure was found to amount pK=-212MPa, suggesting favor of homogeneous freezing upon exerting a negative pressure on the liquid. In terms of thermodynamic properties entering the theory, the reason for the negative Kauzmann pressure is the higher mass density of water in comparison to ice at the melting point.

ICEpMERPH, the first integrative conjugative element [ICE] of the SXT/R391 family isolated in the United Kingdom and Europe was analyzed to determine the nature of its adaptive functions, its genetic structure and homology to related elements normally found in pathogenic Vibrio or Proteus species. Whole Genome Sequencing of Escherichia coli isolate KH802 [which contains the ICE pMERPH] was carried out using Illumina sequencing technology. ICEpMERPH has a size of 110 Kb and has 112 putative open reading frames [ORFs], the “Hotspot regions” of the element were found to contain putative restriction digestion systems, insertion sequences and heavy metal resistance genes that encode resistance to mercury, as previously reported but also surprisingly to arsenate. A novel arsenate resistance system was identified in Hotspot 4 of the element, and unrelated to other SXT/R391 elements. This arsenate resistance system is potentially linked to two genes, orf 69, encoding an organoarsenical efflux MFS transporter-like protein related to ArsJ and orf70, encoding an NAD-dependent glyceraldehyde-3-phosphate dehydrogenase. Phenotypic analysis using isogenic strains of AB1157 with and without the ICE revealed resistance to low levels of arsenate in the range 15-25 mM. This novel, low level resistance may have an important adaptive function in polluted environments, which often contain low levels of arsenate contamination. Bioinformatic analysis on the novel determinant and the phylogeny of ICEpMERPH is presented.

The removal of metal ions by biosorption on inexpensive materials is still a challenge for environmental engineering research. In this study, marine green algae biomass (Ulva lactuca sp.) and the biochars obtained from this biomass, at 320 C (BC-320) and 550 C (BC-550), were used as biosorbents for the removal of Cu(II) ions from aqueous solution. In addition to comparing the biosorption capacities, the determination of the thermodynamic parameters allows the choice of the most suitable material for the biosorption processes. The experimental results, obtained for Cu(II) ions biosorption on each biosorbent (algae biomass (AB), BC-320 and BC-550), at three different temperatures (10, 30 and 50 C) were analyzed using Langmuir and Freundlich isotherm models, while pseudo-first order, pseudo-second order and intra-particle diffusions models were used to model the kinetic data. The biosorption of Cu(II) ions is best described by the Langmuir model and the pseudo-second kinetic model, regardless of the type of biosorbent. The maximum biosorption capacity (qmax, mg/g) depends on the temperature, but also on the type of biosorbent, and follow the order: BC-320 < AB < BC-550. Using the experimental isotherms, the thermodynamic parameters (G0, H0 and S0) for the biosorption of Cu(II) ions on each biosorbent were calculated. The analysis of the obtained values constitutes the main arguments in choosing BC-550 as the most effective biosorbent for the removal of Cu(II) ions from aqueous media.

In Bangkok, the capital city of Thailand, air pollution is a significant problem, and efforts are needed to define organisms that may be used as bioindicators of air pollution. Epiphytic subaerial algae, which grow on the surface of trees, may have a potential as bioindicators of urban air quality. Algae were collected from randomly selected tree trunks in five parks in Bangkok, and the air pollutants CO, NO2, O3, SO2, PM2.5, and PM10 were measured. Analysis of the subaerial algal communities was performed by metagenomics. Diversity indexes were determined for the algal taxa detected, which were separated into groups corresponding to different collection sites by cluster analysis. Relationships between taxa and air pollutants were analyzed by PCA and the Pearson correlation coefficient (r). The results showed a high diversity of epiphytic subaerial al-gae. We recorded 101 taxa belonging to the Cyanophyta (70 taxa), Chlorophyta (21 taxa), Char-ophyta (5 taxa), Bacillariophyta (3 taxa), and Eustigmatophyta (2 taxa). The most abundant taxon was Chroococcidiopsis sp. 1, for which up to 13,254 individuals/cm2 were recorded. The Shan-non–Weaver index ranged between 1.37 and 2.51, the Margalef index between 3.84 and 4.75, and the Pielou index between 0.30 and 0.54. The similarity index was between 8.00% and 64.82% ac-cording to the cluster analysis results for three groups. The PCA indicated that all air pollutants affected the diversity and abundance of the epiphytic subaerial algae. Cyanothece sp. 2 is consid-ered a potential bioindicator of air pollution. It was negatively related to O3 and positively related to NO2 and CO

Algaecides are chemicals that cause serious health problems. Conventional paints contain algaecides to improve the algae resistance on the paint film. Present research has suggested an environmental friendly paint formulation that focuses on developing algae resistance without having algaecides. In this research, Algae growth on newly developed paint is modeled by incorporating dirt resistance of paint and natural phenomena including humidity, temperature and time respectively. The fitted Model revealed explained variation of 59.65% in the average algae growth, of which, Dirt Resistance, Humidity and temperature and some of their interactions play significant role in this variation. Model suggests that the proposed newly developed paint without algaecides is more resilient to algae growth and significantly decreased the average algae growth rate by 0.53% as compared to conventional paints. Keeping the effect of all other factors constant, if dirt resistance of paint (D_c value) increases by one percent, average algae growth decreases by 12.98%; when temperature increases by 1^oC, average algae growth decreases by 22.4%; a positive unit change in the joint linear effect dirt resistance, temperature and humidity caused a decrease in average algae growth by 0.0031%. It was also observed that the individual effect of humidity variable was inversely related with average algae growth. However the combination of humidity and temperature, humidity and dirt resistance, humidity and time, and the quadratic effect of humidity were found to increase the average algae growth rate. The cubic effect of temperature variable by one degree centigrade resulted in decrease of average algae growth by 0.000907%.

Sea ice extraction and segmentation of remote sensing images is the basis for sea ice monitoring. Machine learning-based image segmentation methods rely on manual sampling and require complex feature extraction. Deep-learning semantic segmentation methods have the advantages of high efficiency, intelligence, and automation. Sea ice segmentation using deep learning methods faces the following problems: in terms of datasets, the high cost of sea ice image label production leads to fewer datasets for sea ice segmentation; in terms of image quality, remote sensing image noise and Severe weather conditions affects image quality, which affects the ac-curacy of sea ice extraction. To address the quantity and quality of the dataset, this study used multiple data augmentation methods for data expansion. To improve the semantic segmentation accuracy, the SC-U2-Net network was constructed using multi-scale inflation convolution and a multi-layer Convolutional Block Attention Module (CBAM) attention mechanism for the U2-Net network. The experiments showed that (1) data augmentation solved the problem of an insuffi-cient number of training samples to a certain extent and improved the accuracy of image seg-mentation. (2) This study designed a multilevel Gaussian noise data augmentation scheme to improve the network's ability to resist noise interference and achieve a more accurate segmenta-tion of images with different degrees of noise pollution. (3) The inclusion of a multi-scale inflation perceptron and multi-layer CBAM attention mechanism improved the ability of U2-Net network feature extraction and enhanced the model accuracy and generalization ability.

A typical vibrational spectrum in the ice phase has four separate bands: translation, libration, bending and stretching. Ice X, the final ice phase under high pressure, shows an exotic vibrational spectrum. Theoretically, an ideal crystal of ice X only has one peak at 998 cm-1 for Raman scattering and two peaks at 450 cm-1 and 1507 cm-1 for infrared absorption in this work. These three characteristic peaks are indicators of the phase transition between ice VII/VIII and ice X. Despite much experimental and theoretical work on ice X, only this study has clearly indicated these characteristic peaks in the region of the IR band. The phonon density of states shows quite different features than ice VIII, which could be verified by inelastic neutron scattering in the future. The dynamic processes of 15 vibrational normal modes are discussed and the typical hydrogen bonds are missing.

It is always a difficult task to assign the peaks recorded from vibrational spectrum. Herein we explored a new pathway of density functional theory (DFT) simulation to present three kinds of spectra of ice XIV and can be referenced as inelastic neutron scattering (INS), IR, and Raman experimental spectrum. The INS spectrum is proportional to phonon density of states (PDOS) while the photon scattering signals reflect the normal vibration frequencies near the Brillouin zone (BZ) center. Based on good agreements with experimental data, we identified the relative frequency and made scientific assignments by normal vibration modes analysis. The debating two hydrogen bond (H-bond) peaks among ice phases from INS have been discussed and the dynamic process of H-bond vibrations were found to be classified into two basic modes. we deduce that two H-bond modes are a general rule among ice family and more works are ongoing to investigate this subject.

Diabetes and its complications are a global health burden, necessitating novel therapeutic approaches. Natural products and derivatives are gaining attention as potential agents for managing diabetes due to their diverse constituents and pharmacological activities. Algae, in particular, offer promising bioactive compounds with antidiabetic properties. This review provides an overview of natural products derived from algae in diabetes management, including advancements and future prospects. It highlights the significance of natural products in diabetes, explores algae's diversity, bioactive compounds, and mechanisms of action. The challenges, limitations, and strategies for optimizing algae-based interventions are discussed, alongside future research directions. Algae's multifaceted pharmacological activities and chemical constituents make them attractive for developing novel antidiabetic therapeutics. Further research and optimization of algae-based interventions have the potential to address the global burden of diabetes and improve patient outcomes.

This literature review found that it is doubtful that there is water ice in the polar craters on the Moon. In the course of this review, the following findings were found: (1) The absorption strength of hydroxyl radicals and hydroxyl groups are all 2.9μm, so it is easy to confuse hydroxyl radicals and hydroxyl groups when interpreting M³ spectra data. I do not doubt the ability of LCROSS to detect OH from water, but only suspect that LCROSS is unable to distinguish between hydroxyl radicals from water ice and hydroxyl groups from Moon's methanol due to ignore their spectral identity; (2) The water brought by comets and asteroids and the one caused by solar wind has been exhausted by reacts with the widespread methanol on the Moon in the presence of Pt/α-MoC or Pt/C catalysts. These reacts form large amount of hydrogen, thus clarifying a question NASA raised that "Scientists have long speculated about the source of vast quantities of hydrogen that have been observed at the lunar poles"; (3) The vast quantities of hydrogen in lunar polar craters at extremely low temperatures might be in liquid or solid state now, easy to confuse with water ice. It seems that all our previous misconceptions about water ice in the lunar polar craters might be due to the neglect of the widespread chemical role of lunar methanol. It is necessary to conduct in-depth research in this field in the future.

Annually, millions of people worldwide are affected by skin diseases, and current therapeutic approaches have limited efficacy. Advances in the treatment of exosomes have led to the development of new therapeutic methods that hold promising potential for improving the treatment options for skin diseases. The aim of this study is to produce pharmaceutical and cosmetic compounds based on exosomes for the treatment of skin conditions such as eczema, pigmentation disorders, skin sagging and aging, cellular skin regeneration, increased skin moisture, and prevention of skin shedding, among others. This study examines the effects of exosomes derived from plants, humans, medicinal algae, and fungi to treat skin diseases. Spectrophotometric analysis reveals the presence of nucleic acids and proteins in exosome samples, indicating their cargo composition. TEM micrographs demonstrate that the exosome isolation process preserves the integrity of the membrane and the crucial spherical structure for their functionality. DLS analysis confirms that isolated exosomes have a size similar to typical exosome dimensions. MTT assays indicate concentration-dependent cytotoxic effects of exosomes on skin cells, with a calculated IC50 representing a significant decrease in cell viability. Real-time PCR shows higher gene expression levels of collagen I and collagen III, indicating the potential of exosomes to enhance collagen synthesis. Tyrosinase enzyme expression analysis demonstrates the influence of exosome treatments on pathways related to melanin production. The use of exosomes derived from various sources provides a promising platform for developing new drugs in the treatment of skin diseases. Additionally, exosomes can be utilized in the treatment of autoimmune diseases and cancer, transforming them into a hopeful field of research. Plant-derived exosomes are environmentally friendly and can serve as the next generation of drug delivery systems for treating various diseases.

Terrestrial algae are the group of photosynthetic organisms, which can survive in extreme conditions. pH is one of the most important factor, influencing on distribution of algae, both in aquatic and terrestrial ecosystems. The influence of different pH levels on cell volume and other morphological characters of authentic and reference strains of Chlorella vulgaris, Bracteacoccus minor, Pseudoccomyxa simplex, Chlorococcum infusionum, and Vischeria magna were studied. Chlorella vulgaris and Pseudoccomyxa simplex were the most resistant species, retaining its morphology in range of pH 4-11,5. The change of pH towards acidic and alkaline levels caused the increase of volume of Pseudoccomixa simplex and Vischeria magna cells according to polynomial regression model. Volume of Chlorella vulgaris cells increased from low to high pH according to linear regression model. Changes of pH levels did not have a significant impact on volume of Bracteacoccus minor and Chlorococcum infusionum cells. Low and high levels of pH caused thickening of cell walls of Chlorococcum infusionum and increase of oil containing substances in Vischeria magna and Bracteacoccus minor cells. Our study revealed a high resistance of studied species to extreme level of pH, which allow recommend these strains for broader use in biotechnology and natures protection.

Thorium (Th) is a natural radioactive element present in the environment and has a potential to be used as a nuclear fuel. Relatively little is known about the influence and toxicity of Th in the environment. In the present study, the toxicity of Th to the green algae Chlorella pyrenoidosa (C. Pyrenoidosa) was evaluated by algal growth inhibition, biochemical assays and morphologic observations. In the cultural medium (OECD TG 201), Th(NO₃)₄ was transformed to amorphous precipitation of Th(OH)₄ due to hydrolysis. Th was toxic to C. Pyrenoidosa, with a 96 h half maximum effective concentration (EC₅₀) of 10.4 μM. Scanning electron microscopy shows that Th-containing aggregates were attached onto the surface of the algal cells, and transmission electron microscopy indicates the internalization of nano-sized Th precipitates and ultrastructural alterations of the algal cells. The heteroagglomeration between Th(OH)₄ precipitation and alga cells and enhanced oxidative stress might play important roles in the toxicity of Th. To our knowledge, this is the first report of the toxicity of Th to algae with its chemical species in the exposure medium. This finding provides useful information on understanding the fate and toxicity of Th in the aquatic environment.

Ice formation on aircraft surfaces poses significant safety risks, and current detection systems often struggle to provide accurate, real-time predictions. This paper presents the development and comprehensive evaluation of a smart ice control system using a suite of machine learning models. The system utilizes various sensors to detect temperature anomalies and signal potential ice formation. We trained and tested supervised learning models (Logistic Regression, Support Vector Machine, Random Forest), unsupervised learning models (K-means clustering), and neural networks (Multi-Layer Perceptron) to predict and identify ice formation patterns. Experimental results demonstrate that our smart system, driven by machine learning, accurately predicts ice formation in real-time, optimizes de-icing processes, and enhances safety while reducing power consumption. This solution holds the potential for improving ice detection accuracy in aviation and other critical industries requiring robust predictive maintenance.

The discovery of water ice on the moon has revolutionized our understanding of lunar science and has profound implications for future space exploration and habitation. Through a comprehensive analysis of remote sensing data, isotopic studies, and neutron detection experiments, this research elucidates the presence, distribution, and origins of lunar water ice. Radar observations from missions like Clementine and Chandrayaan-1 reveal distinct polar regions with elevated circular polarization ratios, indicative of volatile ice deposits. Spectral detections by instruments such as M3 and Diviner further confirm the presence of water ice in lunar-shadowed regions, with estimates suggesting reserves of up to 300 million tons at the poles. Neutron detection experiments on lunar orbiters like LRO provide additional evidence, detecting hydrogen signals consistent with water ice below the lunar surface. Isotopic analyses offer insights into the origin and evolution of lunar water ice, with comparisons to cometary and asteroidal sources. Proposed missions, such as Artemis-3 and Artemis-4, aim to collect samples from the lunar South Pole for detailed isotopic analysis, furthering our understanding of lunar water ice's composition and history. Scientific data, including the lunar bulk water content and estimated water ice reserves, underscore the significance of lunar water ice as a critical resource for future space exploration endeavors. Calculations estimating the total water-ice area and water abundance near specific lunar features provide valuable insights into the potential utilization of lunar water ice for sustained human presence on the Moon and beyond.

The surface velocity of the Amery Ice Shelf (AIS) is vital to assessing its stability and mass balance. Previous studies have shown that the AIS basin has a stable multi-year average surface velocity. However, spatiotemporal variations in the surface velocity of the AIS and the underlying physical mechanism remain poorly understood. This study combined offset tracking and DInSAR methods to extract the monthly average surface velocity of the AIS and obtained the inter-annual surface velocity from the ITS_LIVE product. An uneven spatial distribution in inter-annual variation of the surface velocity was observed between 2000–2022, although the magnitude of variation was small at less than 20.5 m/yr. The increase and decrease in surface velocity on the eastern and western-central sides of the AIS, respectively, could be attributed to the change in the thickness of the AIS. There was clear seasonal variation in monthly average surface velocity at the eastern side of the AIS between 2017–2021, which could be attributed to variations in the area and thickness of fast-ice and also to variations in ocean temperature. This study suggested that changes in fast-ice and ocean temperature are the main factors driving spatiotemporal variation in the surface velocity of the AIS.

This document describes the theoretical basis of the algorithms used to determine properties of snow and ice from the measurements of the Ocean and Land Color Instrument (OLCI) onboard Sentinel-3 satellites within the Pre-operational Sentinel-3 snow and ice products (SICE) project: http://snow.geus.dk/. The code used for the SICE retrieval and its documentation can be found at https://github.com/GEUS-SICE/pySICE. The algorithms were developed after the work from Kokhanovsky et al. (2018, 2019, 2020).

Arctic feedbacks will accelerate climate change and could jeopardise mitigation efforts. The permafrost carbon feedback releases carbon to the atmosphere from thawing permafrost and the sea ice albedo feedback increases solar absorption in the Arctic Ocean. A constant positive albedo feedback and zero permafrost feedback have been used in nearly all climate policy studies to date, while observations and models show that the permafrost feedback is significant and that both feedbacks are nonlinear. Using novel dynamic emulators in the integrated assessment model PAGE-ICE, we investigate nonlinear interactions of the two feedbacks with the climate and economy under a range of climate scenarios consistent with the Paris Agreement. The permafrost feedback interacts with the land and ocean carbon uptake processes, and the albedo feedback evolves through a sequence of nonlinear transitions associated with the loss of Arctic sea ice in different months of the year. The US’s withdrawal from the current national pledges could increase the total discounted economic impact of the two Arctic feedbacks until 2300 by $25 trillion, reaching nearly $120 trillion, while meeting the 1.5 °C and 2 °C targets will reduce the impact by an order of magnitude.

A numerical mechanism connecting ice algal ecodynamics with the buildup of organic macromolecules is tested within modeled pan-Arctic brine channels. The simulations take place offline in a reduced representation of sea ice geochemistry. Physical driver quantities derive from the global sea ice code CICE, including snow cover, thickness and internal temperature. The framework is averaged over ten boreal biogeographic zones. Computed nutrient-light-salt limited algal growth supports grazing, mortality and carbon flow. Vertical transport is diffusive but responds to pore structure. Simulated bottom layer chlorophyll maxima are reasonable, though delayed by about a month relative to observations due to uncertainties in snow variability. Upper level biota arise intermittently during flooding events. Macromolecular concentrations are tracked as proxy proteins, polysaccharides, lipids and refractory humics. The fresh biopolymers undergo succession and removal by bacteria. Baseline organics enter solely through cell disruption, so that the internal carbon content is initially biased low. By including exudation, agreement with dissolved organic or individual biopolymer data is achieved given strong release coupled to light intensity. Detrital carbon then reaches hundreds of micromolar, sufficient to support structural changes to the ice matrix.

In the process of modernization and development, a human being always needed energy, which increased the dependency on the available sources of fossil fuel. Tetraselmis, a green algal genus belong to the order Chlorodendrales, are described by their strong green coloured chloroplast, flagellated cell bodies, and the occurrence of a pyrenoid within the chloroplast. In this study, four different strains of Tetraselmis species were successfully isolated from the saltpans Kovelong, Chennai, Tamil Nadu, India. The isolated strains were cultured in the normal basal medium and their morphological features were subsequently studied. The species of Tetraselmis straiata (T. straiata) Butcher BBRR1 was confirmed using molecular identification of 18S rRNA gene analysis and its observed systematic position. Among the four different isolates, T. straiata Butcher BBRR1 recorded a highest biomass concentration of 0.58 ± 0.021 g L^-1, 15% lipids, 19% proteins and 17% carbohydrates when it grown under laboratory condition. Whereas, in open raceway ponds, T. straiata BBRR1 produced 0.95 ± 0.06 g L^-1 biomass, 19% lipids, 28% proteins and 21% carbohydrates in an modified CFTRI I medium. The fatty acids profile of T. straiata Butcher BBRR1showed the presence of 33.14 % Palmitic acid, 22.64% 11- Octadecenoic acid and 21.94% Heptadecanoic acid. Since T. straiata BBRR1 can be cultivated in open ponds without a major contaminations, this species can be used as novel biomass feedstock to produce biofuels. This study may suggest the potential of T. straiata BBRR1 for biofuel production and could compete the energy demand in the future. In addition, this species contains healthful components of carotenoids, lipids and proteins, all these may provide a health benefits beyond basic nutrition.

Cosmogenic nuclides are widely used to constrain the landscape history of glaciated areas. At nunataks in continental polar regions with extremely arid conditions, cosmogenic nuclides are often the only method available to date the ice thinning history of the glacier. However, the amount of cosmogenic isotopes accumulated at the surface of nunataks depends not only on the length of time that rock has been exposed since the last deglaciation, but on the full history of the surface, including muon production under ice, exposure during previous interglacials, subaerial weathering rate, glacial erosion rate, and uplift rate of the nunatak. The NUNAtak Ice Thinning model (NUNAIT) simulates the cosmonuclide accumulation on vertical profiles, fitting the aforementioned parameters to a set of multi-isotope apparent ages from samples taken at different elevations over the ice-sheet surface. The NUNAIT calculator is an easy-to-use tool that constrains parameters that describe the geological history of a nunatak from a set of surface exposure ages.

Albedo is a key variable in the response of glaciers to climate. In Iceland, large albedo variations in the ice caps may be caused by the deposition of volcanic ash (tephra). Sparse in situ field measurements are insufficient to characterize the spatial variation of albedo over the ice caps. Here we evaluate the latest MCD43 MODIS albedo product (collection 6) to monitor albedo over the Icelandic ice caps using albedo from ten automatic weather stations in Vatnajökull and Langjökull as ground truth. We examine the influence of the albedo variability within MODIS pixels by comparing the results with a collection of Landsat scenes. The results indicate a good ability of the MODIS product to characterize the seasonal and interannual albedo changes with correlation coefficients ranging from 0.47 to 0.90 (median 0.84) and a small bias ranging from -0.07 to 0.09. The root-mean square errors (RMSE) ranging from 0.08 and 0.21, is larger than that from previous studies, but we did not discard the retrievals flagged as bad quality to maximize the amount of observations given the frequent cloud obstruction in Iceland. We find a positive but non-significant relationship between the RMSE and the subpixel variability as indicated by the standard deviation of the Landsat albedo within the MODIS pixel (R=0.48). The summer albedo maps and time series computed from the MODIS product show that the albedo decreased significantly after the Eyjafjallajökull and Grímsvötn eruptions in 2010 and 2011 in all the main ice caps (except the northernmost Drangajökull), with albedo reduction up to 0.6 over large regions of the accumulation areas. Following this validation, these data will be assimilated in an energy and mass balance model of to better understand the relative influence of the volcanic and climate forcing to the ongoing mass losses of Icelandic ice caps.

The construction of large-scale water diversion projects alleviated effectively the current situa-tion of uneven distribution of water resources in China. However, due to the siltation of very fine sediment and organic matter on the side wall of the open channel, and the slow velocity of the side wall flow field, it is easy to produce epipelic algae, which affects water quality. For the prototype observation cannot be used to predict the series of flow in real time, and the mathe-matical model calculation is affected by parameter limitations, these two methods often cannot truly reflect the hydrodynamic characteristics of open channel with epipelic algae. Therefore, by referring to the design parameters of the water diversion project channel, this paper takes the epipelic algae growing on the side wall of the open channel as the research object, and uses the scale of 1:30 to carry out the generalized flume experiment. Through the analysis of the physical characteristics of the prototype sample, and the simulation of the cohesive force between the oblique side wall and the epipelic algae, the multi-group and multi-series hydrodynamic tests are carried out. The flow velocity distribution law and the development and change of the tur-bulent vortex on the side wall are analyzed. It has important scientific guiding significance and practical value for water quantity regulation water regulation and water quality safety protec-tion of long-distance projects.

Over the last decades, microalgal biomass has gained a significant role in the development of different high-end (nutraceuticals, colorants, food supplements, and pharmaceuticals) and low-end products (biodiesel, bioethanol, and biogas) due to rapid growth and high carbon fixing efficiency. Therefore, microalgae are considered a useful and sustainable resource to attain energy security while reducing our current reliance on fossil fuels. From the technologies available for obtaining biofuels using microalgae biomass, thermochemical processes (pyrolysis, HTL, gasification) have proven to be processed with higher viability, because they use all biomass. However, because of the complexity of the biomass (lipids, carbohydrates , and proteins), the obtained biofuels from direct thermochemical conversion have large amounts of heteroatoms (oxygen, nitrogen , and sulfur). As a solution, catalyst-based processes have emerged as a sustainable solution for the increase in biocrude production. This paper's objective is to present a comprehensive review of recent developments on catalyst mediated conversion of algal biomass. Special attention will be given to operating conditions, strains evaluated, and challenges for the optimal yield of algal-based biofuels through pyrolysis and HTL.

Over the last decades, microalgal biomass has gained a significant role in the development of different high-end (nutraceuticals, colorants, food supplements, and pharmaceuticals) and low-end products (biodiesel, bioethanol, and biogas) due to rapid growth and high carbon fixing efficiency. Therefore, microalgae are considered a useful and sustainable resource to attain energy security while reducing our current reliance on fossil fuels. From the technologies available for obtaining biofuels using microalgae biomass, thermochemical processes (pyrolysis, HTL, gasification) have proven to be processed with higher viability, because they use all biomass. However, the biocrudes obtained from direct thermochemical conversion have substantial quantities of heteroatoms (oxygen, nitrogen, and sulfur) due to the complexity of the biomass's content of chemical components (lipids, carbohydrates, and proteins). As a solution, catalyst-based processes have emerged as a sustainable solution for the increase in biocrude production. This paper's objective is to present a comprehensive review of recent developments on catalyst mediated conversion of algal biomass. Special attention will be given to operating conditions, strains evaluated, and challenges for the optimal yield of algal-based biofuels through pyrolysis and HTL.

In the history of civil aircraft transportation, ice formation has been identifies as a key factor in the safety of flight. Anti-icing and deicing system have emerged through the years with the aim to prevent or to eliminate ice formation on wing airfoil, control surface and probes. Modern flying machine demand more efficiency in order to reduce the carbon footprint and increase the sustainability of flight transport. In order to achieve this goal the need to have efficient aircraft with efficient and low power consuming system is fundamental. This paper proposes a new model for ice accretion using computational fluid dynamics (CFD). This model permits to simulate the shape of the ice formed over a profile varying boundary conditions (i.e.- speed, liquid water content and so on). The proposed model takes into account also the amount of heat transferred between water and the surrounding environment and includes the effects of air turbulence on the ice formation process. The CFD simulations have been validated with NASA experimental outcome and show good agreement. The proposed model can be also used to investigate the effects of various parameters such as air speed, Liquid Water Content and air temperature on the ice formation process. The results evidences that the proposed model can accurately predict ice formation process and is suitable to optimize the design of anti-icing or deicing system for aircraft and helicopters. This approach is not limited to aerospace but can also be exported to other applications such as transportation, wind turbine, energy management and infrastructure.

Accurate detection of players and teams in ice hockey games is crucial to the tracking of individual players on court and team tactical decisions, which is therefore becoming an important task for coaches and other analysts. However, hockey is a fluid sport due to complex dynamics and frequent substitutions by both teams, resulting in various body positions of players. Few traditional player detection models from other team sports take these characteristics into account, especially for the detection of teams without prior annotations. Here, we design a two-phase cascaded Convolutional Neural Network (CNN) model coupling between individual players position information and team uniform colors to hierarchically detect players in ice hockey games. Our model filters most of disturbing information, such as audience and sideline advertising bars, in Phase I, and refines the detection of targeted players in Phase II, which is efficient and accurate with a precision rate of 91.30% and a recall rate of 95.60% for individual players detection, and an average accuracy of 93.05% in team classification from a self-built dataset of collected images in the 2018 Winter Olympics. Meanwhile, we also present results based on the images and real-time detection from broadcasting videos of 2019-20 NHL regular games covering all 31 teams to show the robustness of our model.

Automatic ice charting can not be achieved using only SAR modalities. It is fundamental to combine information from other remote sensors with different characteristics for more reliable sea ice characterization. In this paper, we employ principal feature analysis (PFA) to select significant information from multimodal remote sensing data. PFA is a simple yet very effective approach that can be applied to several types of data without loss of physical interpretability. Considering that different homogeneous regions require different types of information, we perform the selection patch-wise. Accordingly, by exploiting the spatial information, we increase the robustness and accuracy of PFA.

The aim of this study was to investigate the size of the change in fatigability of gluteus maximus muscles during difficult endurance training in dynamic conditions. The research covered involved eight female athletes of the Polish National Team in short track, which had been prepared to the Olympic Games in PyeongChang. The sEMG system was used to measure fatigue of right and left gluteus maximus muscles, in the modified Biering-Sorensen test. The test was conducted five times during the training: before training, after warmup, and after each of 3 series of the endurance training. Comparing the mean frequency of the surface electromyography power spectrum of the first and the last seconds of the test, statistically significant reduction (p<0.05) of the average frequency value of the right muscle from 55.61±7.08 Hz to 48.64±4.48 Hz and left muscle from 58.78±4.98 Hz to 53.18±4.62 Hz was reported. In the conducted Biering-Sorensen test, the value of the muscle signal frequency measured by surface electromyography decreases, which may prove the muscle fatigue. Reductions in the frequency measured in the first and the last second of the test, was higher of the right lower limb. The size of the d Cohen effect in fatigue drops along with subsequent five tests during the training.

Radar altimetry provides valuable measurements to characterize the state and the evolution of the Antartica and Greenland ice sheet cover. Global Navigation Satellite System Reflectometry (GNSS-R) has the potential capacity of complementing the dedicated radar altimeters incrementing the temporal and spatial resolution of the surface height measurements. In this work we perform an study of the Greenland ice sheet using data obtained by the GNSS-R instrument aboard the British TechDemoSat-1 (TDS-1) satellite mission, designed primarily to provide sea state information, like sea surface roughness or wind, but not altimetric products. The data has been analyzed with altimetric methodologies, already proved in aircraft based experiments, to extract signal delay observables to be used to infer the topography of the Greenland cover. The penetration depth of the GNSS signals into ice has also considered. The topographic signal obtained is consistent with those obtained with other passive or active microwave sensors. The main conclusion derived from this work is that GNSS-R also provides valuable measurements of the ice sheet cover and, as taken at a variety of geometries and at least two frequency bands, they prospect different depths into the ice. They have thus potential to complement our understanding of the ice firn and its evolution.

Fixed offshore wind turbines continue to be developed for high latitude areas where not only wind and wave loads need to be considered, but also moving sea ice. Current rules and regulations for the design of fixed offshore structures in ice-covered waters do not adequately consider effects of ice loading and its stochastic nature on fatigue life of the structure. Ice crushing on such structures results in ice-induced vibrations, which can be represented by loading the structure using a variable-amplitude loading (VAL) sequence. Typical offshore load spectra are developed for wave and wind loading. Thus, a combined VAL spectrum is developed for wind, wave, and ice action. To this goal, numerical models are used to simulate the dynamic ice-, wind-, and wave-structure interaction. The stress time-history at an exemplarily selected critical point in an offshore wind energy monopile support structure is extracted from the model and translated into a VAL sequence, which can then be used as a loading sequence for the fatigue assessment or fatigue testing of welded joints of offshore wind turbine support structures. This study presents the approach to determine combined load spectra and standardized time series for wind, wave, and ice action.

The Greenland ice sheet is a major contributor to sea level rise, adding an estimated 0.47 +/− 0.23 mm/yr to global mean sea level between 1991 and 2015 (van den Broeke et al., 2016). Making sea level rise projections for the future and understanding the processes controlling current observed rates of sea level rise are crucially dependent on understanding the present-day state of the ice sheet. Here, we provide an overview of the current state of the mass budget of Greenland based on satellite gravimetry and remote sensing observations of surface elevation change, ice sheet velocity and calving front positions. We also combine these essential climate variables with a regional climate model (RCM) output from an ice sheet model (ISM) to gain insight into poorly understood ice sheet dynamical and surface mass processes. On average from 1992 to 2017 the ice sheet in some locations has lost up −2.65 m/yr in elevation based on ESA Radar altimetry analysis. Calving fronts have retreated all around Greenland since the 1990s and in only two out of 28 study locations have they remained stable. The locations of grounding lines at 5 key glaciers with floating ice tongues have remained stable over the observation period. However a detailed case study at Petermann glacier with an ice fracture model shows the sensitivity of these floating ice shelves to future climate change. GRACE gravimetric mass balance (GMB) data allows us to tie together disparate lines of evidence showing that Greenland has lost about 265 +/− 25 Gt/yr of ice over the period 2002 to 2015. RCM and ISM simulations show that surface mass processes dominate the overall Greenland ice sheet mass budget except for areas of fast ice sheet flow but marked differences between models and between models and observations indicate that not all processes are captured accurately, indicating areas of greater uncertainty and directions of future research for future sea level rise projections.

The key objective of the experiment was to show the environmental based of copper nanoparticles which counters the growth of bacterial pathogens such as Pseudomonas aeruginosa, and Staphylococcus aureus. To begin with the experiments, root extract of Asparagus racemosus was used to synthesise Copper nanoparticles. To confirm the formation of Cu-NPs, it was subjected to characterization such as Ultra Violet analysis, X-ray Diffraction method, Fourier Transform Infrared Spectroscopy and Scanning electron microscope images. Later the antibacterial activity of Cu-NPs was studied by incorporating it into two bacterial pathogens (Pseudomonas aeruginosa and Staphylococcus aureus). The outcome displayed a satisfactory antibacterial activity against the bacterial pathogens by the biosynthesized copper nanoparticles. To boost up the enzyme inhibition property of the Cu NPs, Antioxidant and Antidiabetic assay were also performed. The biosynthesised Cu NPs displayed a satisfied result in Antifouling function. The result was used assessed with green algae bloom water.

Two-dimensional (2D) ice I is an atomic-level ice that is composed of two interlocked atom-ic layers saturated with hydrogen bonds. It has recently been experimentally observed but its properties have yet to be clarified. Accordingly, we theoretically studied the hydrophobic properties of 2D ice I. On the contrary, simulation of a hydrogen fluoride molecule on a 2D ice surface manifested that it destroyed the 2d ice structure and connected new hydrogen bonds with water molecules. Investigations of the interfacial effect between 2D and three-dimensional (3D) ice films indicated that the network structure of 2D ice was not de-stroyed by a 3D ice surface, as the former was saturated with hydrogen bonds. However, the surface of 3D ice reorganized to form as many hydrogen bonds as possible. Thus, the 2D ice film was hydrophobic and inhibited the growth of 3D ice. This shows that if 2D ice can be produced on an industrial scale, it could be used as an anti-3D-icing agent under low tem-perature.

Overhead power transmission line icing (PTLI) disasters are one of the most severe dangers to power grid safety. Automatic iced transmission line identification is critical in various fields. However, existing methods primarily focus on the linear characteristics of transmission lines, employing a two-step process involving edge and line detection for PTLI identification. Nonetheless, these traditional methods are often difficult when confronted with challenges such as background noise or variations in illumination, leading to incomplete identification of the target area, missed target regions, or misclassification of background pixels as foreground. We propose a new iced transmission line identification scheme to overcome this limitation. In the initial stage, we integrate the image restoration method with image filter enhancement to restore the image's color information. This combined approach effectively retains valuable information and preserves the original image quality, thereby mitigating noise presented during the image acquisition. Subsequently, in the second stage, we introduce an enhanced multi-threshold algorithm to separate background and target pixels. After image segmentation, we enhance the image and obtain the region of interest (ROI) through connected component labeling modification and mathematical morphology operations, eliminating background regions. Our proposed scheme achieves an accuracy value of 97.72%, a precision value of 96.24%, a recall value of 86.22%, and the specificity value of 99.48% based on the average value of test images. Through object segmentation and location, the proposed method can avoid background interference, effectively solve the problem of transmission line icing identification, and achieve 90% measurement accuracy compared to manual measurement on the collected PTLI dataset.

Sentinel-1 (S1) extra-wide (EW) swath data in cross-polarization (horizontal-vertical, HV or vertical-horizontal, VH) are strongly affected by the scalloping effect and thermal noise, particularly over areas with weak backscattered signals, such as sea surfaces. Although noise vectors in both the azimuth and range directions are provided in the standard S1 EW data for subtraction, the residual thermal noise still significantly affects sea ice detection by the EW data. In this paper, we improve the denoising method developed in previous studies to remove the additive noise for the S1 EW data in cross-polarization. Furthermore, we propose a new method for eliminating the residual noise (i.e. multiplicative noise) at the sub-swath boundaries of the EW data, which cannot be well processed by simply subtracting the reconstructed 2-D noise field. The proposed method of removing both the additive and multiplicative noise was applied to EW HV-polarized images processed using different Instrument Processing Facility (IPF) versions. The results suggest that the proposed algorithm significantly improves the quality of EW HV-polarized images under various sea ice conditions and sea states in marginal ice zone (MIZ) of the Arctic. This is of great support for the utilization of cross-polarization SAR images in wide swaths for intensive sea ice monitoring in polar regions.

The pile foundation in the permafrost region is in a negative temperature environment, so the concrete is affected by the negative temperature of the surrounding soil.It not only affects the formation of concrete strength, but also leads to engineering quality accidents in serious cases.Based on the actual measurement of temperature at different strata depths and the comprehensive consideration of surface temperature, terrestrial heat flux and other parameters, the law curve of temperature change along depth in Greater Khingan is established.The calculated results of the curve are consistent with the measured results of ground temperature.The results show that the variation trend of ground temperature along the strata depth at different monitoring sites is basically the same. From June to November, the ground temperature at different depths tends to be constant.From December to May, the ground temperature at any depth within the depth range of 0 to 5.5m follows the law of the cosine function.Below 5.5m, the earth temperature no longer varies with depth.The research results can be used as reference for pile foundation construction under negative temperature environment.

On January 8, 2005, a surface melt event began on the interior portion of Ross Ice Shelf. While many surface melt events on Ross Ice Shelf are caused by the advection of warm air onto the shelf from the Ross Sea, surface winds during this event were directed offshore and the spatial pattern of surface melt was inconsistent with the Southern Ocean serving as a heat source. Rather, due to the interior location of the surface melt coupled with prevailing wind direction and surface temperature data it is thought that adiabatic warming of Föhn winds is the driving cause of this melt event. Passive Microwave (SSM/I) imagery was used to determine surface melt occurrence and the event’s extent. Spatial patterns of surface melt were then compared to NCEP/NCAR reanalysis output for several synoptic weather variables including surface temperatures, sea level pressure and surface vector winds. Synoptic-scale weather conditions were consistent with those that would produce downsloping wind (föhn) conditions in the interior of the Ross Ice Shelf where the anomalous surface melt was located.

The Greenland Ice Sheet is now the largest land ice contributor to global sea level rise, largely driven by increased surface meltwater runoff from the ablation zone, i.e. areas of the ice sheet where annual mass losses exceed gains. This small but critically important area of the ice sheet has expanded in size by ~50% since the early 1960s, and satellite remote sensing is a powerful tool for monitoring the physical processes that influence its surface mass balance. This review synthesizes key remote sensing methods and scientific findings from satellite remote sensing of the Greenland Ice Sheet ablation zone, covering progress in 1) radar altimetry, 2) laser (lidar) altimetry, 3) gravimetry, 4) multispectral optical imagery and, 5) microwave and thermal imagery. Physical characteristics and quantities examined include surface elevation change, gravimetric mass balance, reflectance, albedo, and mapping of surface melt extent and glaciological facies and zones. The review concludes that future progress will benefit most from methods that combine multi-sensor, multi-wavelength, and cross-platform datasets designed to discriminate the widely varying surface processes in the ablation zone. Specific examples include fusing laser altimetry, radar altimetry, and optical stereophotogrammetry to enhance spatial measurement density, cross-validate surface elevation change, and diagnose radar elevation bias; fusing optical imagery, radar imagery, and microwave scatterometry to discriminate between snow, liquid water, refrozen meltwater, and bare ice near the equilibrium line altitude; combining optical reflectance with laser altimetry to map supraglacial lake, stream, and crevasse bathymetry; and monitoring the inland migration of snowlines, surface melt extent, and supraglacial hydrologic features.

Thunderstorm electrification has been studied for hundreds of years. Several mechanisms have been proposed to elucidate the electrification, including convective charging, inductive precipitation charging, and ice crystal-graupel collision charging. Field observations and model studies have demonstrated the vital roles that graupel and ice crystals play in the electrification, but the mechanism of the collision charging is still unclear. The fundamental essence of relative growth rate theory used for explaining the tripole charge structure in thunderclouds also needs a further exploration. We analyze the processes of ice crystal-graupel collision charging from charge migration inside hydrometeors to charge separation between two hydrometeors. The driving effects of temperature gradient and chemical potential gradient in charge migration are clarified, as well as the applicability of the relative growth rate theory, thermoelectric effect and surface tension gradient in different humidities. Based on the understanding from these electrification mechanisms, we propose that the essence of charge separation is driven by non-thermal equilibrium, and future studies on thunderstorm electrification should focus on the dynamical non-thermal equilibrium of cloud particles.

Sea ice surface roughness affects ice-atmosphere interactions, serves as an indicator of ice age, shows patterns of ice convergence and divergence, affects the spatial extent of summer melt ponds, and ice albedo. We have developed a method for mapping sea ice surface roughness using angular reflectance data from the Multi-angle Imaging SpectroRadiometer (MISR) and lidar-derived roughness measurements from the Airborne Topographic Mapper (ATM). Using an empirical data modeling approach, we derived estimates of Arctic sea ice roughness ranging from centimeters to decimeters meters within the MISR 275-m pixel size. Using independent ATM data for validation, we find that histograms of lidar and multi-angular roughness values are nearly identical for areas with roughness <20 cm but that for rougher regions, the MISR-derived roughness has a narrower range of values than the ATM data. The algorithm is able to accurately identify areas that transition between smooth and rough ice. Because of its coarser spatial scale, MISR-derived roughness data have a variance of about half that ATM roughness data.

Various products of the Integrated Multisatellite Retrievals for GPM (IMERG) and passive mi-crowave (PMW) sensors are assessed with respect to near-surface wet-bulb temperature (Tw), precipitation intensity, and surface type (i.e., with and without snow and ice on the surface) over the CONUS and using Stage-IV product as reference precipitation. IMERG products include precipitation estimates from infrared (IR), combined PMW, and their combination. PMW products generally have higher skills than IR over snow- and ice-free surfaces. Over snow- and ice-covered surfaces (1) PMW products (except AMSR-2) show a higher correlation coefficient than IR, (2) IR and PMW precipitation products tend to overestimate precipitation, but at colder temperatures (e.g., Tw<-10oC) PMW products tend to underestimate and IR product continues to show large overestimations, and (3) PMW sensors show higher overall skill in detecting precipitation oc-currence, but not necessarily at very cold Tw. The results suggest that the current approach of IMERG (i.e., replacing PMW with IR precipitation estimates over snow- and ice-surfaces) may need to be revised.

When the epipelic algae group growing on the concrete inclined side wall, which is typical of urban rivers and open diversion channels, enters the water flow, it will seriously affect the func-tion of the rivers or the channels. It is urgent to predict the transport capacity of epipelic algae group with water flow. However, the current research on the transport of pollutants is mostly based on mathematical models, and the study of the transport of flake epipelic algae group is extremely rare. A generalized hydrodynamic experimental model of a flume with sidewall epi-pelic algae group was established. Through a series of hydraulic experiments, the physical movement form and transport capacity of the suspended epipelic algae group on the side wall of the channel were studied qualitatively and quantitatively by taking the thickness, sheet size and flow rate of the epipelic algae group as the influencing factors. The key influencing factors of the suspension of epipelic algae are clarified, so as to quantitatively analyze the critical conditions of its suspension. Through flow scheduling, the probability of epipelic algae gathering some-where is increased. It provides a theoretical basis for realizing the long-distance migration of epipelic algae and optimizing the mathematical model.

Wound healing involves a complex cascade of cellular, molecular, and biochemical responses and signaling processes. It consists of successive interrelated phases, the duration of which depends on multifactorial processes. Wound treatment is a major healthcare issue that can be resolved by development of effective and affordable wound dressings based on natural materials and biologically active substances. Proper use of modern wound dressings can significantly accelerate wound healing with minimal cosmetic defects. The innovative biotechnologies for creating modern natural interactive dressings are based on sulfated polysaccharides from seaweeds with their unique structures and biological properties, the availability of their sources in the form of wild bushes, and in the form of aquaculture, as well as with a high potential for participation in process control wound healing. These natural biopolymers are a novel and promising biologically active source for designing wound dressings based on alginates, fucoidans, carrageenans, and ulvans, which serve as active and effective therapeutic tools. The aim of this review is to summarize available information about the modern wound dressing’s technologies based on seaweed-derived polysaccharides, including those successfully implemented in commercial products, with the emphasis on promising and innovative designs. The further prospect of using marine biopolymers is related to the need to analyze the results of numerous in vitro and in vivo experiments, summarize clinical trial data, develop a scientifically based approach and relevant practical recommendations for the treatment of wounds.

Oxygen and hydrogen isotopes (18O and 2H) in polar ice offer strong evidence of both long-term and abrupt climate changes. However, reliably estimating surface air temperatures from past climates has proven difficult because the relationship between 18O and temperature cannot be calibrated. In this study, we investigated the 17O and 18O of modern rain and ice cores using published data. We found that precipitation 17O is influenced by two factors: mass-dependent fractionation (MDF) that occurs during ocean evaporation, and mass-independent fractionation (MIF) that happens in the stratosphere. The MDF contribution remains constant and can be understood from studying tropical rain, as the overall movement of mass in the tropics is upward towards the stratosphere. On the other hand, the MIF effect comes from the mixing of stratospheric air in the troposphere, which is a result of the Brewer-Dobson circulation. This MIF effect on precipitation 17O increases from the tropics towards the poles. Therefore, the relative 17O and 18O composition, denoted as '17O, in modern precipitation can be calibrated with surface air temperature, creating a new, independent tool for estimating past temperatures. We used this calibration along with '17O of Antarctic and Greenland ice cores and our results for past temperatures are in excellent agreement with those from borehole thermometry or gas phase analysis of air trapped in the ice. The 17O method overcomes the problems associated with using 18O for paleothermometry. Our findings align with climate models that suggest a weakening of the Brewer-Dobson circulation during the Last Glacial Maximum. Furthermore, our method could be used to monitor future changes in response to a warming climate caused by increasing greenhouse gases.

This is an exercise to explore the concentration of Lithium, Lithium-7 isotope and the possible presence of black dirty ice in the lunar surface using spectral data obtained from the Clementine mission. The main interest in tracing the lithium and presence of dark ice in the lunar surface are closely related to future human settlement missions in the Moon. We investigate the distribution of Lithium and 7 Li isotope on the Lunar surface, employing spectral data from the Clementine images. We utilized Visible (VIS-NIR) imagery at wavelengths of 450, 750, 900, 950, and 1000 nm, along with Near-Infrared (NIR-SWIR) at 1100, 1250, 1500, 2000, 2600, and 2780 nm, encompassing 11 bands in total. This dataset offers a comprehensive coverage of about 80% of the lunar surface, with resolutions ranging from 100 to 500 meters, spanning latitudes from 80°S to 80°N. In order to extract quantitative abundance of Lithium, ground truth sites were used to calibrate the Clementine images. Samples (12045, 15058, 15475, 15555, 62255, 70035, 74220 and 75075) returned from Apollo missions 12, 15, 16 and 17 have been correlated to the Clementine VIS-NIR bands and five spectral ratios. The 5 spectral ratios calculated synthesize the main spectral features of sample spectra that were grouped by their Lithium and 7 Li content using Principal Component Analysis. The ratios spectrally characterize substrates of anorthosite, silica-rich basalts, olivine-rich basalts and High-T mare basalts and Orange soils. Our findings reveal a strong linear correlation between the spectral parameters and the lithium content in the 8 Apollo samples. With the values of the 11 Clementine bands and the 5 spectral ratios for each of the 8 lunar soils we performed linear regression models to estimate the concentration of Lithium and 7 Li. Also, we calculated Digital Terrain Models (DTMs; Altitude, Slope, Aspect, DirectInsolation and WindExposition) from LOLA-DTM to discover relations between relief and spatial distribution of the extended models of lithium and 7 Li. The analysis was conducted in a mask polygon extracted from Lunar Orbiter Laser Altimeter (LOLA) and located around the Apollo 15 landing site. This analysis seeks to uncover potential 7 Li enrichment through spallation processes, influenced by varying exposure to solar wind. To explore the possibility of find ice mixed with regolithe (black ice) we used a spectral library (350-2500nm) form ices dirty with different concentration of volcanic particles.

Lake ice thickness (LIT) is a sensitive indicator of climate change identified as a thematic variable of Lakes as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS). Here, we present a novel and efficient analytically based retracking approach for estimating LIT from high-resolution Ku-band (13.6 GHz) synthetic aperture radar (SAR) altimetry data. The retracker method is based on the analytical modeling of the SAR radar echoes over ice-covered lakes that show a characteristic double-peak feature attributed to the reflection of the Ku-band radar waves at the snow-ice and ice-water interfaces. The method is applied to Sentinel-6 Unfocused SAR (UFSAR) and Fully Focused SAR (FFSAR) data, with their corresponding tailored waveform model, referred to as the SAR_LITand FFSAR_LITretracker, respectively. LIT retrievals from Sentinel-6 SAR data at different posting rates are evaluated against those obtained from thermodynamic lake ice model simulations and Low Resolution Mode (LRM) Sentinel-6 and Jason-3 data over two ice seasons during the tandem phase of the two satellites, allowing precise assessment of the continuity between LRM and SAR LIT retrievals. Consistency checks of the Sentinel-6 SAR LIT estimates are also performed using optical/radar images that provide information on the snow/ice conditions on the same dates. The analysis is performed on Great Slave Lake and Baker Lake (Canada) that differ in terms of lake size, bathymetry, snow/ice properties, and seasonal evolution of LIT. The accuracy of the LIT estimates with the SAR LIT retrackers is on the order of 5 cm once the ice is well established on the lakes, meeting the GCOS requirements of LIT measurement uncertainty, which is a factor of 2 to 3 times better than that of LIT obtained with LRM data, bringing a further improvement compared to previous analyses and methods. The SAR LIT retrackers presented are promising tools for monitoring the inter-annual variability and trends in LIT from current and future SAR altimetry missions.

Macroalgae and macroalgae-associated bacteria together constitute the most efficient metabolic cycling system in the ocean. Their interactions, especially the responses of macroalgae-associated bacteria communities to algae in different geographical locations, is mostly unknown. In this study, metagenomics was used to analyze the microbial diversity and associated algal polysaccharide-degrading enzymes on the surface of red algae among three remote regions. There were significant differences in the macroalgae-associated bacteria community composition and diversity among the different regions. At the phylum level, Proteobacteria, Bacteroidetes, and Actinobacteria had a significantly high relative abundance among the regions. From the perspective of species diversity, samples from China had the highest macroalgae-associated bacteria diversity, followed by those from Antarctica and Indonesia. In addition, in the functional prediction of the bacterial community, genes associated with amino acid metabolism, carbohydrate metabolism, energy metabolism, metabolism of cofactors and vitamins, and membrane transport had a high relative abundance. Canonical correspondence analysis and redundancy analysis of environmental factors showed that, without considering algae species and composition, pH and temperature were the main environmental factors affecting bacterial community structure. Furthermore, there were significant differences in algal polysaccharide-degrading enzymes among the regions. Samples from China and Antarctica had high abundances of algal polysaccharide-degrading enzymes, while those from Indonesia had extremely low abundances. The environmental differences between these three regions may impose a strong geographic differentiation regarding the biodiversity of algal microbiomes and their expressed enzyme genes. This work expands our knowledge of algal microbial ecology, and contributes to an in-depth study of their metabolic characteristics, ecological functions, and applications.

The increasing concern regarding climate change continues to motivate research in the Arctic. Within the delicate cycle of the cryosphere, leads are an important kinematic feature that regulate heat balances in the Arctic. Therefore, it is necessary to quantify the genesis of leads over time to identify when and where changes are occurring. The use of a principal component analysis (PCA) is one such tool that is used to identify the characteristics of seasonal ice variability. The PCA not only identifies “normal” or “dominant” conditions or features, but also extract anomalous spatial features from an archive of long-term sequence of images.

This study investigated a novel probiotic-enriched ice cream containing fermented white kidney bean homogenate to explore its potential health benefits. We assessed the viability of various probiotic strains during ice cream production and storage, focusing on their potential to reach the gut, and evaluated the overall antioxidant activity using DPPH, ABTS, FRAP, and TPC assays. The incorporation of fermented white bean homogenate significantly increased antioxidant capacity compared to the control group. Notably, strains like L. rhamnosus GG and L. plantarum 299v demonstrated the most pronounced effects on antioxidant activity, suggesting potential synergistic benefits between probiotics and bioactive compounds in fermented white beans. Although all probiotic strains experienced decreased viability during storage, certain strains, particularly L. plantarum 299v and L. casei DN-114001, showed promising survival rates even after 6 months. These results suggest the potential for developing probiotic ice cream containing viable bacteria capable of reaching the gut and contributing to a healthy gut microbiota. This could potentially improve digestion, reduce inflammation, and boost the immune system. Overall, this study highlights the potential of probiotic-enriched ice cream with fermented white kidney bean homogenate to combine the established benefits of probiotics for gut health with the enjoyment of consuming ice cream.

This paper describes new horizons in the diversity and taxonomy of negev-like viruses encoding the membrane-embedded SP24 protein. First, our data extend the known host range of SP24-encoding negev-like viruses to include brown algae, fungi, green plants, the phylum Entoprocta, the phylum Mollusca, and vertebrates. Second, our phylogenetic analysis suggests that the evolution of the SP24 gene family may have involved frequent events of inter-order virus genome shuffling. Third, the identification of 2-3 copies of SP24 protein genes in some virus RNAs shows that virus genomes may have acquired additional SP24 genes during the evolutionary process due to duplications or new acquisition steps. Forth, the broad host specificity of some SP24-encoded viruses may be related to an important adaptive role of SP24. Fifth, insect and nematode genomes may acquire viral SP24 genes by putative horizontal transfer from negev-like viruses known to infect species of both taxa.

Light-gated ion channel and ion pump rhodopsins are widely used as optogenetic tools and these can control the electrically excitable cells as: (1) they are a single-component system i.e., their sensor and effector functions are encoded by the 7-transmembrane domains and (2) they show fast kinetics with small dark-thermal recovery time. In cellular signaling, a signal receptor, modulator and effector components are involved for attaining synchronous multicomponent regulation. Optical modulation of this network requires either receptor to effector encoded in a single ORF or direct modulation of the effector domain through bypassing all upstream players. Recently discovered modular rhodopsins like rhodopsin guanine cyclase (RhoGC) and rhodopsin phosphodiesterase (RhoPDE) paves the way to establish proof of concept. Light sensor coupled modular system could be expressed in a precise cell type and which holds great potential in the advancement of optogenetics 2.0. It would enable manipulating entire relevant cell signaling system. Here, we had identified 50 novels modular rhodopsins with variant rhodopsins domain and its diverse cognate signaling cascades encoded in a single ORF, which are associated with specialized functions in the cells. These novel modular algal rhodopsins have been characterized functionality based on their sequence and structural homology with previously characterized rhodopsins. Presented novel modular rhodopsins with various effector domains hold potential to expand optogenetics tool kit to regulate various cellular signaling pathways across the diverse biological model systems.

Arctic sea ice prediction holds significant importance for facilitating Arctic route planning, optimizing fisheries management, and advancing the field of sea ice dynamics research. While various deep learning models have been developed for sea ice prediction, they predominantly operate at the seasonal or sub-seasonal scale, often focusing on localized areas, and few cater to full-region daily scale prediction. This study introduces the use of spatiotemporal sequence data prediction models, namely, the convolutional LSTM (ConvLSTM) and predictive recurrent neural network (PredRNN), for the prediction of sea ice concentration (SIC). Our analysis reveals that, when solely utilizing SIC historical data as the input, the ConvLSTM model outperforms the PredRNN model in SIC prediction. To enhance the model's capacity to capture spatiotemporal relationships between multiple variables, we expanded the range of input data types to form the ConvLSTM-multi and PredRNN-multi models. Experimental findings demonstrate that the ConvLSTM-multi model excels in assimilating the influence of reanalysis data on sea ice within the sea ice edge region, thus exhibiting superior performance in predicting daily Arctic SIC over the subsequent 10 days. Furthermore, sensitivity tests on various model parameters highlight the substantial impact of sea surface temperature and prediction date on the accuracy of daily sea ice prediction. Additionally, meteorological and oceanographic parameters primarily affect the prediction accuracy of the thin ice region at the edge of the sea ice.

This paper presents the light scattering matrices of atmospheric aggregated hexagonal ice particles appearing in cirrus clouds. In this work aggregates consist of the same particles with different spatial orientation and number of these particles. Two types of particle shape were studied: (1) hexagonal column; (2) hexagonal plate. For both shapes we study compact and non-compact cases of arrangement of particles in aggregates. As a result, four sets of aggregates were made: (1) compact columns; (2) non-compact columns; (3) compact plates; (4) non-compact plates. Each set consists of eight aggregates with different number of particles from 2 to 9. For practical reason the bullet-rosette and the aggregate of hexagonal columns with different sizes was also calculated. The light scattering matrices were calculated for the case of arbitrary spatial orientation within the geometrical optics approximation for sets of compact and non-compact aggregates and within the physical optics approximation for two additional aggregates. It was found that light scattering matrix elements for aggregates are depend on arrangement of particles they are consisted.

For the water bodies of the Lena Delta Nature Reserve, 413 taxa were known. In 14 small tundra reservoirs in its vicinity, we identified 385 taxa, which in the compilatory list made up a significant diversity (666 taxa including definitions to the genus level) of diatoms. Thus, the species composition of diatoms in the reserve and adjacent territories was replenished by 278 species. The predominance of species of the genera Pinnularia (57) and Eunotia (51) at the family and generic levels was revealed. Index of intraspecific variability Ssp./Sp. for the lakes of the reserve was 1.11, and for the lakes of the Tiksi region 1.14, which is typical for high-latitude and high-mountain communities. The number of rare or endangered species varied in different lakes within 1-10, totaling 42 species for the entire study area. Bioindication has shown that potentially threatened species prefer moderate temperatures, slightly acidic or neutral environments free from organic pollution. A comparative analysis of the species composition of diatoms in the vicinity of the Lena Delta and other northern water bodies of Yakutia and the Arctic Islands showed that the species composition of each lake in the Arctic is strictly individual. The indicator characteristics show a certain response of the species composition of diatoms to changes in salinity, pH, and organic pollution. A number of regularities in the spatial distribution of diatoms in the study area were found in connection with the physicochemical parameters of their habitat, height above sea level, and relation to a particular catchment basin. Statistical mapping of indicators of community and habitat diversity revealed a strong reaction to point one-time pollution and made it possible to assume the influence of summer northeast winds on the species composition. We suggest that the high diversity inherent in the diatom lakes of the Tiksi coastal zone, which can even be replenished in further studies, can be considered as a property of coastal biota inherent in ecotones. Since it is in the coastal Tiksi region that a surge in the number of species is observed, this region can be considered not only an ecotone, but also a hotspot of diatom diversity. The results of the study are important for developing the basis for monitoring biodiversity under the conditions of anthropogenic and climatic changes in the Arctic.

This study explores the application of numerical analysis and material models to predict ice impact loads on ships and offshore structures operating in polar regions. An explicit finite element analysis (FEA) approach was employed to simulate an ice and steel plate collision experiment conducted in a cold chamber. The pressure and strain history during the ice collision were calculated and compared with the experimental results. Various material model configurations were applied to the FEA to account for the versatile behavior of ice—whether ductile or brittle—its elastic-plastic yield criteria, and its dynamic strain rate dependency. In addition to the standard linear elastic perfectly plastic and linear elastic-plastic relationships, this study incorporated the crushable foam and Drucker-Prager models, based on the specific ice yield criteria. Considering the ice’s strain rate dependency, collision simulations were conducted for each yield criteria model to compute the strain and reaction force of the plate specimens. By comparing the predicted pressures for each material model combination with the pressures from ice collision experiments, our study proposes material models that consider the yielding, damage, and behavioral characteristics of ice. Lastly, our study proposes a combination of ice material properties that can accurately predict collision force.

Although the dry ice method used to synthesize exfoliated graphite/graphene is little known and used, it has significant advantages over others: it is low cost, simple, and a large quantity of material can be obtained using some inorganic and highly available acids (which can be reused). Despite the above advantages, the main reason for its incipient development is the resulting presence of magnesium oxide in the final product. In the present work, three different treat-ments were tested to remove this remnant using some acid chemical leaching processes, making use of hydrochloric acid, aqua regia, and piranha solution. Based on the experimental evidence, it was found that using aqua regia and combining the leaching process with mechanical milling was the most efficient way of removing such a remnant, the residue being only 0.9 wt.%. This value is low when compared to that obtained with the other acid leaching solutions and purifi-cation process (2.8 - 29.6 wt.%). A mandatory high-energy mechanical milling stage was neces-sary during this treatment, in order to expose and dissolve the highly insoluble oxide without secondary chemical reactions on the graphenes. High-energy mechanical milling is an effective route to exfoliate graphite/graphene, which allows the magnesium oxide to be more susceptible to acid treatment. The obtained surface area was 504 m2g-1; this high value resulting from the in-tense exfoliation can potentiate the use of this material for a wide variety of applications.

The emergence of the coronavirus 19 (COVID-19) has posed a major challenge to healthcare systems worldwide, especially as COVID-19 mutations complicate the development of vaccines and antiviral drugs. Therefore, the search for natural products with broad anti-COVID-19 capabilities is an important option for the prevention and treatment of infectious diseases. Lectins, which are widely recognized as antiviral agents, could contribute to the development of anti-COVID-19 drugs. In this study, we evaluated the binding ability of a total of six lectins, including MVL from Microcystis viridis NIES-102, to the spike protein RBD of the original (wild) COVID-19 and it’s three mutants: alpha, delta, and omicron. As a result, two lectins, MVL from Microcystis viridis NIES-102 and jacalin from Artocarpus altilis, showed distinct binding ability to the RBDs of the four COVID-19 strains. The other lectins (DB1, ConA, PHA-M and CSL3) did not show any binding ability. Although the glycan specificities of the two lectins, MVL and Jacalin, were different, they showed the same affinity for the RBDs of the four COVID-19 strains, i.e., alpha &gt; delta &gt; original &gt; omicron. The verification of glycan-specific inhibition revealed that jacalin binds to RBDs by glycan-specific recognition, whereas MVL binds to RBDs by protein-protein interactions in addition to glycan-specific recognition.

Some optimal control problems need metaheuristics in searching for the optimal solution, especially when the process has certain characteristics like the Photobioreactor for Algae Growth (distributed parameter, nonlinearities, etc.). Particle Swarm Optimization (PSO) algorithms within control structures are a realistic approach; their task is often to predict the optimal control values working with a process model (PM). Owing to numerous numerical integrations, there is a big computational effort that is reflected in a large controller execution time. The authors propose to replace the PSO predictor with a machine learning model that has “learned” the quasi-optimal behavior of the couple (PSO, PM); the training data is obtained through closed-loop simulations over the control horizon. The new controller should preserve the process’s quasi-optimal control. In identical conditions, the process evolutions must also be quasi-optimal. The multiple Linear Regression and the Regression Neural Networks were considered as predicting models. The paper first proposes algorithms for collecting and aggregating data sets for the learning process. Algorithms for constructing the machine learning models, implementing the controllers, and closed-loop simulations are also proposed. The simulations prove that the two machine learning predictors have learned the PSO predictor’s behavior such that the process evolves almost identically. The resulting controllers’ execution time drastically decreased while keeping their optimality.

Ice and snow on roads in winter endanger traffic safety. The existing methods of snow and ice removal have various drawbacks, which need further research. Aiming at solving limitations about high labor intensity, low efficiency, serious environmental pollution of traditional snow and ice removal methods, the anti-icing coating technology of high-voltage conductors is used for reference, and in view of the characteristics of asphalt pavement deicing, an ice-suppressing material that can effectively reduce the adhesion between snow, ice and pavement is successfully developed. As there is no perfect evaluation index and method for ice-suppressing materials at present, this paper further evaluates the performance of ice-suppressing materials from the aspects of deicing performance, durability, adhesion and the impact of ice-suppressing materials on pavement performance. The test results show that the ice-suppressing material can effectively reduce the adhesion between the ice layer and the specimen, making it easier to remove. The ice-suppression material has good slow-release performance, and the specimens still have good deicing performance after 7 cycles of tests.

Arctic sea ice characteristics have been changing rapidly and significantly in the last few decades. Using a long-term time series of sea ice products from satellite observations - the extended AVHRR Polar Pathfinder (APP-x), trends in sea ice concentration, ice extent, ice thickness, and ice volume in the Arctic from 1982 to 2020 are investigated. Results show that the Arctic has become less ice-covered in all seasons, especially in summer and autumn. Arctic sea ice thickness has been decreasing at the rate of -3.24 cm per year, resulting in about a 52% reduction in thickness from 2.35 m in 1982 to 1.13 m in 2020. Arctic sea ice volume has been decreasing at the rate of -467.7 km³ per year, resulting in about a 63% reduction in volume, from 27590.4 km³ in 1982 to 10305.5 km³ in 2020. These trends are further examined from a new perspective, where the Arctic Ocean is classified into open water, perennial, and seasonal sea ice-covered areas based on the sea ice persistence. The loss of the perennial sea ice-covered area is the major factor in the total sea ice loss in all seasons. If the current rates of sea ice changes in extent, concentration, and thickness continue, the Arctic is expected to have ice-free summer by the early 2060s.

The study of exogenous metabolites of algae-bacterial communities in the laboratory accumulative culture obtained from natural river water was done using gas chromatography-mass spectrometry. Exometabolites of the algae-bacterial community (including microalgae and cyanobacteria) in the culture medium were represented by saturated, unsaturated, and aromatic hydrocarbons, carboxylic acids, phenolic, and terpene compounds and their derivatives. Possible biological activities of the discovered exometabolites are considered. The study has demonstrated that an increase in the number of main groups of microorganisms, along with changes in the composition of algae and cyanobacteria, are responsible for the increase in the composition and concentration of metabolites in the microecosystem's culture medium after one month of cultivation. The presence of octacosane in high concentration (0.0603 mg/l; 23.78% of the total content of low molecular weight organic compounds) by the end of exposure accumulative culture is associated with the strong development of the cyanobacterium Gloeocapsa sp. in the presence of diatom algae of the genus Navicula and green algae of the genera Chlorella and Scenedesmus. Due to the need to comprehend the ecological and biochemical mechanisms of the formation and functioning of algae-bacterial communities, as well as to predict potential paths of transformation and evolution of aquatic ecosystems, the specificity of exometabolite complexes of algae and microorganisms, as well as their allelopathic and other biochemical interactions in freshwater ecosystems, requires further serious study.

Lattice structures have emerged as promising materials for aerospace structures applications due to their high strength-to-weight ratios, customizable properties, and efficient use of materials. These properties make them at-tractive for use in anti-ice systems, where lightweight and heat exchanging are essential. This paper presents an extensive experimental investigation into mechanical compression properties of lattice trusses fabricated from AlSi10Mg powder alloy, a material commonly used in casted aerospace parts. The truss structures were manufactured using additive manufacturing Selective Laser Melting technique and subjected to uniaxial compressive loading to assess their performance. The results demonstrate that AlSi10Mg lattice trusses exhibit remarkable compressive strength with strong correlations depending upon both topology and cells’ parameters setup. The finding described highlights the potential of AlSi10Mg alloy as a promising material for custom truss fabrication, offering customizable cost-effective and lightweight solutions for aerospace market. The paper also emphasizes the role of additive manufacturing in producing complex structures with pointwise tailored mechanical properties.

The amplified Arctic warming is one of several factors influencing atmospheric dynamics. In this work, we consider a series of numerical experiments to identify the direct role of the Arctic sea ice reduction process in forming climatic trends in the northern hemisphere. Aimed at this, we used two more or less independent mechanisms of ice reduction. The first is traditionally associated with increasing the concentration of carbon dioxide in the atmosphere from the historic level of 360 ppm to 450 ppm and 600 ppm. This growth increases air temperature and decreases the ice volume. The second mechanism is associated with a reduction in the reflectivity of ice and snow. We assume that comparing the results of these two experiments allows us to judge the direct role of ice reduction. The most prominent consequences of ice reduction, as a result, were the weakening of temperature gradient at the tropopause level in mid-latitudes, the slower zonal wind at 50-60∘N, intensification of wave activity in Europe, Western America, and Chukotka, and its weakening in the south of Siberia and Kazakhstan. We also consider how climate change may alter regimes such as blocking and stationary Rossby waves. The study used the INM-CM48 climate system model .

Helmholtz energy of ice VII-X is determined in a pressure regime extending to 450 GPa at 300 K using local basis functions in the form of b splines. The new representation for the equation of state is embedded in a physics-based inverse theory framework of parameter estimation. Selected pressures as a function of volume from 14 prior experimental studies and two theoretical studies constrain the behavior of Helmholtz energy. Separately measured bulk moduli, not used to construct the representation, are accurately replicated below about 20 GPa and above 60 GPa. In the intermediate range of pressure, the experimentally determined moduli are larger and have greater scatter than values predicted using the Helmholtz representation. Although systematic experimental error in the experimental elastic moduli is possible and likely, the alternative hypothesis is a slow relaxation time associated with changes in proton mobility or the ice VII to X transition. A correlation is observed between anomalies in the pressure derivative of the predicted bulk modulus and previously suggested higher-order phase transitions. Improved determinations of elastic properties at high pressure would allow refinement of the current equation of state. More generally, the current method of data assimilation is broadly applicable to other materials in high-pressure studies.

Variance-driven decomposition based on the singular spectrum analysis of the European Project for Ice Coring in Antarctica (EPICA) dD, CO2 and CH4 records allowed a novel quantitative structural interpretation of all glacial/interglacial cycles and glacial terminations of the last 800 kyr. This bottom-up approach used the response components of EPICA stacked records to reconstruct the envelope of the thermal response through a physical interference model. The aim was to improve the understanding regarding the features of intensity, amplitude, and asymmetry of 73 marine isotope stages (MIS) and seven terminations. The Antarctic stack record can be described by a variance-weighted interference model of ten thermal waves of different origins (mid-term oscillation, orbitals and suborbitals) that stochastically interfere at a given time according to their relative differences in frequency, intensity, and polarity. Interglacial/glacial stages resulted from constructive interference and bipolar amplification of warming/cooling responses, respectively. The low intensity MISs (including 90% of substages) and the unbiased-dated terminations fell in the low interference regions where dominant destructive patterns minimise the thermal envelope. The positive skewness of the EPICA stack resulted from the constructive interference with a strong bias in the warming direction, especially after the Mid-Brunhes Event. Duration analysis of short eccentricity hemicycles exhibited an intrinsic unexpectedly prolonged mean cooling in the nominal solution (5.8 kyr) and its EPICA response as well (8.6 kyr), along with an interference-induced asymmetry (21.1 kyr). The overall effect resulted in the saw-tooth shape of glacial cycles which is heavily induced by interference and related to the intermediate feedback mechanisms controlled by short eccentricity.

The paper presents the results of modeling the problem of injecting liquid sulfur dioxide into a porous reservoir initially saturated with methane and ice. The model presented in the paper assumes the formation of three different regions, namely, the near one, saturated with liquid SO2 and its hydrate; the far one, containing methane and ice, and the intermediate one, saturated with methane and water. The effects of various parameters of the porous medium and injected SO2 on the nature of the course of the hydrate formation process have been studied. It is shown that with a decrease in reservoir permeability or injection pressure, the length of the intermediate region decreases, which in the limiting case means the formation of SO2 hydrate in the mode without the formation of an extended region saturated with methane and water. It is shown that such a regime is also typical for the case of high initial injection pressures, as well as low values of the initial reservoir temperature and injection temperature.

A novel method of investigating the temperature dependent variation of aspects of the complex refractive index n* in samples in the THz range using continuous, non-polarised, synchrotron radiation is presented. The method relies on the use of ATR apparatus, and retains the advantage of minimal sample preparation, which is a feature of ATR techniques. The method demonstrates the viability of rapidly monitoring temperature reflectance whilst continuously heating or cooling samples by using a temperature variable Thermal Sample Stage. The method remains useful when the refractive index of the sample precludes attenuated total reflection study. This is demonstrated with the water reflectance experiments. The temperature dependent ATR reflectance of tissue-representative fats (lard and Lurpak® butter) was investigated with the novel approach. Both are within the ATR range of the diamond crystal in a “true” ATR mode. Lard showed no clear temperature variation between -15 0C and 24 0C at 0.7 to 1.15 THz or 1.70 to 2.25 THz. Lard can be regarded as having invariable, constant, dielectric properties within mixtures when biological substances are being assessed for temperature dependent dielectric variation within the stated THz ranges. Lurpak® butter (water content 14.7%) displayed temperature dependent reflectance features with a steady decline in reflectivity with increasing temperature. This is in line with the temperature-dependent behaviour of liquid water. There is no rapid change in reflectance, even at -20 0C, suggesting that emulsified water retains liquid-water-like THz properties at freezing temperatures.

Background Legionella pneumophila is one of the causes of legionellosis. Water environments serve as the natural habitat and the main sources of Legionella pneumophila. Objectives The aims of this study was to understand the differences of Legionella pneumophila serogroups distribution in well water, tap water, ice cubes, hospital and hotel water in East Java-Indonesia. Methods a total of 60 water samples in east java-Indonesia; from well water (n=25), tap water (n=5), ice cubes (n=5), water from the hospital (n=16), and hotel water (n=9) were detected using polymerase chain reaction with mip gene spesific primers and then it was analyzed by phylogenetic tree. Results For the 60 water samples collected in East Java, 12% of the samples (7/60) were positively contaminated by L. pneumophila. In details, there was 8% of the well water samples (2/25), 2% of the tap water samples (1/5), 2% of the ice cubes samples (1/5), 0% of the hospital water samples (0/16) and 33.33% of the hotel water samples (3/9). The phylogenetic tree showed that Legionella pneumophila contaminating well water isolate 1 from Surabaya and tap water isolate from Sidoarjo was closer to L.pneumophila serogroup 2, 4, 6, 8, 10, 12, isolates from Brazil, China, Spain and Australia. L.pneumophila contaminating the ice cubes from Sidoarjo was closer to serogroup 1, 2, 4, 7, 8, 11, 13, 14, while the bacteria contaminating well water isolate 2 from Sidoarjo as well as water in hotel of Surabaya (hotel water isolate 1, 2 and 3) classified into their own group. Conclusion There is a difference in the distribution of L. pneumophila serogroups between well water, tap water, ice cubes, and hotels.

The efficiency of performance in various sports has the development of certain specific skills at its core. In ice hockey, both the technical aspects (techniques, stance) and the cognitive ones (keeping attention on the puck, game strategy, etc.) are highly important. This study is aimed at the identification of specific features that determine the performance efficiency of professional hockey players. We used virtual reality (VR) to study the differences between professional ice hockey players and novices in terms of motor responses to the puck’s presentation on different levels of difficulty. The study involved 22 participants, 13 of them being professional ice hockey players (M_age=20±2.9; mean age of training experience М=14.18±3.8) and 9 being not experienced participants (M_age=20±1.4). The study showed that the stick response time of professional hockey players is significantly higher (0.98 ms vs 1.5 ms, p≤0.05) in more difficult situations close to a real game. Moreover, professionals proved to have more stable movement patterns of the knee and hip joints. They also make fewer head movements as a response to stimuli during all runs (0.66 vs 1.25, p≤0.05). Therefore, the results indicate specific spatial-temporal, technical and tactical, and energetic determinants, that ensure higher performance efficiency in hockey players

The aim of the research was to evaluate various fertilisation programs in increasing plant resistance to abiotic stress such as drought. It was tested whether the algal biostimulator provides the same tolerance to drought stress in highbush blueberry plants as regular fertilisers without biostimulation. The research was conducted in 2022 in a greenhouse in controlled drought conditions. Three-year-old highbush blueberry bushes (12 pieces) were used in the experiment. Highbush blueberry bushes (Vaccinium corymbosum) 'Brigitta Blue' cultivars were planted in plastic pots with a capacity of 10 dm3 containing an acidic substrate and placed in a greenhouse. Controlled lighting conditions were maintained using sodium lamps and a temperature of 25°C/20°C day/night. The substrate in pots was maintained at 80% of field water capacity by manual watering and weekly supply of nutrient solution for 5 weeks until water deficit occurred. Half of the plants were sprayed weekly with a biostimulant based on seaweed extract. Seven days after the third application of the product, half of the untreated and treated plants were subjected to water deficit stress by restricting water supply to 40% of field capacity. The tested biostimulator impacted on stimulating the activity of antioxidant enzymes but had no effect on the chlorophyll content in the leaves or the concentration of nutrients in the leaves. The effect of marine algae products on the yield quantity and high quality is related among other to bioactiv substances witch helps to prevent drought stress.

Yogurt ice cream (YIC) containing Bifidobacterum longum subsp. longum TISTR 2195 (B. longum) with different fat contents (2 and 10% fat) and prebiotics (galacto-oligosaccharide, GOS and fructo-oligosaccharide, FOS) was investigated for its physicochemical properties, microstructure, and survival of B. longum during storage time and in a simulated gastrointestinal tract. Fat contents affected pH, fat particle size, hardness, melting rate, and solid-like characteristic of ice cream while FOS seemed to enhance the hardness and elasticity of YIC better than GOS due to less solubility and denser microstructure which exhibited more solid-like properties than YIC containing GOS. The interaction effect of fat content at 10% fat and FOS in YIC seemed to promote more sensorial acceptance than the ice cream containing 2% fat and GOS. The fat content, concentration of prebiotics, and type of prebiotics were attributed to the survival of B. longum in YIC. Moreover, the survival number of B. longum in YIC during storage for 180 days and in the simulated gastrointestinal tract was still in 106 CFU g-1, which is considered to benefit human health. Finally, probiotic YIC in this study could be used as a guide for functional ice cream manufacture future.

The study focuses on conducting a quantitative comparison of sea ice thickness data obtained through satellite-based remote sensing and in-situ observations in the eastern Arctic Ocean from September 2013 to September 2015 as part of the Nansen and Amundsen Basins Observational System (NABOS) program. Upward-looking sonar observations from an oceanographic mooring at the northern slope of the Laptev Sea (78°25’N, 125°04’E) were used for comparing instrumental measurements of ice thickness with data from the remotely sensed CryoSat-2 and CryoSat2/SMOS datasets. The comparison results indicate a significant tendency for satellite products to overes-timate sea ice thickness by more than 40 cm, particularly for moderate and thick ice conditions. Caution is advised when using these satellite-based measurements. Sea ice ridging is identified as one of the possible factors contributing to the observed discrepancy. The continental slope of the Laptev Sea experienced a prevalence of ridged ice over level ice during the period from 2013 to 2015. In the spring season (March-May), ridged ice was observed approximately 60% of the time, while level ice was observed around 40% of the time. However, the most significant relative contribution of ridging to ice thickness was observed during the initial ice formation period (from October through December) when sea ice is thin (<1 m). During these months, the relative difference between the mean and modal ice thickness, which reflects the mean variation between the deformed and thermodynamically grown level sea ice, could be as high as 70%.

We present the update of the Snow and Ice (SICE) property retrieval algorithm proposed initially by Kokhanovsky et al. (2019). The algorithm is based on the spectral measurements of Ocean and Land Color Instrument (OLCI) onboard Sentinel-3 satellites combined with the asymptotic radiative transfer theory valid for weakly absorbing turbid media. The main improvements include the introduction of a new atmospheric correction, retrieval of snow impurity load and properties, retrievals for partially snow-covered ground and also accounting for various thresholds to be used to assess the retrieval quality. The algorithm is available as python and Fortran packages at https://github.com/GEUS-SICE/pySICE. The technique can be applied to various optical sensors (satellite and ground-based) operated in the visible and near infrared regions of electromagnetic spectra.

We calculate the hydrodynamic forces exerted on an oscillating circular cylinder when it moves translationally perpendicular to its axis in the infinitely deep water covered by compressed ice. The cylinder can oscillate both horizontally and vertically. In the linear approximation, we find a solution for the steady wave motion generated by the cylinder within the hydrodynamic set of equations for the incompressible ideal fluid. We show that depending on the rate of ice compression, the normal and anomalous dispersion can occur in the system. In the latter case, the group velocity can be opposite to the phase velocity in a certain range of wavenumbers. We investigate the dependences of the hydrodynamic loads (added mass, damping coefficients, wave resistance, and lift force) exerting on the cylinder on the translational velocity and frequency of oscillation. It is shown that there is a possibility of the appearance of negative values for the damping coefficients at the relatively big cylinder velocity; then the wave resistance decreases with increasing of cylinder velocity. The theoretical results are underpinned by the numerical calculations for the real parameters of ice and cylinder motion.