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.

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 rapid growth of the global wearable technologies market is projected to reach $61.30 billion by 2030 which reflects a shift towards personalised health monitoring embedded in everyday activities. This paper explores the potential of embroidered interdigitated transducer (IDT)-based sensors for non-invasive, continuous monitoring of human biomarkers, particularly glucose levels, in human sweat. The study employs innovative embroidery techniques to create flexible fabric-based sensors with gold-coated IDTs. Experimental results demonstrate the sensor’s capability to detect water droplets and glucose concentrations, showcasing promising applications for health monitoring. The embroidered IDT-based sensors offer a unique approach for seamless integration into clothing, paving the way for personalised, continuous health data capture.

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.

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.

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.

This work presents a novel approach for the study of the movement of droplets on inclined surfaces under the influence of gravity and chemical heterogeneities. The developed numerical methodology uses data-driven modeling to extend the applicability limits of an analytically derived reduced-order model for the contact line velocity. More specifically, while the reduced-order model is able to capture the effects of the chemical heterogeneities to a satisfactory degree, it does not account for gravity. To alleviate this shortcoming, datasets generated from direct numerical simulations are used to train a data-driven model for the contact line velocity, which is based on the Fourier neural operator and corrects the reduced-order model predictions to match the reference solutions. This hybrid surrogate model, which comprises of both analytical and data-driven components, is then integrated in time to simulate the droplet movement, offering a speedup of five orders of magnitude compared to direct numerical simulations. The performance of this hybrid model is quantified and assessed in different wetting scenarios, by considering various inclination angles and values for the Bond number, demonstrating the accuracy of the predictions as long as the adopted parameters lie within the ranges considered in the training dataset.

Plastic contamination of small dimensions (

Ti and its alloys are the most commonly used materials for biomedical applications. However, bacterial infection after implant placement is still one of the significant rising complications. Therefore, the application of the antimicrobial agents into implant surfaces to prevent implant-associated infection has attracted lots of attention. Scientific papers have shown that inorganic antibacterial metal element (e.g. Ag, Cu, Zn) can be introduced to implant surfaces with the addition of metal nanoparticles or metallic compounds into electrolyte via micro-arc oxidation (MAO) technology. In this review, the effects of the composition and concentration of electrolyte and process parameters (e.g. voltage, current density, oxidation time) on morphological characteristics (e.g. surface morphology, bonding strength), antibacterial ability and biocompatibility of MAO antimicrobial coating were discussed in detail. Anti-infection and osseo-integration can be simultaneously accomplished with the selection of the proper antibacterial elements and operating parameters. Besides, MAO assisted by magnetron sputtering (MS) to endow Ti-based implant materials with superior antibacterial ability and biocompatibility was also discussed. Finally, the development trend of MAO technology in the future was forecasted.

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.

With continuous increase in integration of the semiconductor devices, the requirements on size accuracy and surface quality of the etched lead frame are higher. The etchant is a key factor on etching process and etched surface quality, while effects of the difference in etchants on microscopic etched surface morphology of the Cu alloy have not been directly studied. In this study, the aqua regia, acidic FeCl3 and CuCl2 solutions were used as etchants, and the CuCrSn alloy specimens with different microstructure were etched and characterized. The results show that the etching rate in aqua regia is high, and the grain orientation, grain boundary (GB) and dislocation have significant influence on the local etching rate. The preferential etching of some atomic planes forms steps between grains with different orientations, and the preferential etching around the GB and dislocation group forms grooves, resulting in high surface roughness. For etching of the FeCl3 and CuCl2 etchants, the steps and grooves become blurred, and almost invisible on the surface etched by the CuCl2 etchant, thus the surface roughness is much lower. The CuCrSn alloy surface etched by the aqua regia is clean, with little Cr-rich particles, while high density Cr-rich particles are remained on the surfaces etched with the FeCl3 and CuCl2 etchants. For the same kind of etchant, the ion concentration can affect the etching mechanism and etching surface morphology.

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.

Public restrooms are often a hub of microbial contamination, and the examination of bacterial contamination in these facilities can serve as an important indicator of the transmission of infectious diseases. This study was conducted to determine the prevalence of bacterial contamination in public restrooms based on the economic class of the building. Samples were collected from various spots in 32 restrooms found in 10 shopping malls, classifying them into two categories: upper-end restrooms and lower-end restrooms. The findings showed that the level of contamination was higher in the lower-end restrooms, with the seat being the most contaminated area. The most dominant Gram-positive bacteria were coagulase-negative staphylococci species, making up 86% of the identified Gram-positive isolates. The most dominant Gram-negative bacteria identified were Klebsiella pneumoniae and Pseudomonas aeruginosa. The antibiotic sensitivity test results revealed the presence of multi-drug resistant bacteria among the Gram-positive and negative isolates, including Staphylococcus haemolyticus, Staphylococcus kloosi, Acinetobacter baumanii, and Pseudomonas aeruginosa. In conclusion, the study underscores the significance of monitoring bacterial contamination in public restrooms and the need for measures to reduce the spread of infectious diseases. Further research is crucial to gain a complete understanding of the bacterial contamination in public restrooms and their resistance patterns, to ensure the safety and health of the public. The implementation of improved cleaning practices and hands-free designs in restrooms can help reduce the risk of cross-contamination and prevent the spread of diseases.

This study aimed to evaluate the impact of Candida albicans on subgingival biofilm formation on dental implant surfaces. Scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM) were used to compare biofilm structure and microbial biomass in the presence and absence of the fungus after periods of 24, 48, and 72 h. Quantitative polymerase chain reaction (qPCR) was used to quantify the number of viable and total micro-organisms for each of the biofilm-forming strains. A general linear model was applied to compare CLSM and qPCR results between control and test conditions. The biofilm developed with C. albicans at 72 h had a higher bacterial biomass, with a significantly higher cell viability (p &lt; 0.05). After both 48 and 72 h of incubation, in the presence of C. albicans, there was a significant increase in counts of Fusobacterium nucleatum and Porphyromonas gingivalis and in the cell viability of Streptococcus oralis, Aggregatibacter actinomycetemcomitans, F. nucleatum, and P. gingivalis. Using a dynamic in vitro multispecies biofilm model, C. albicans exacerbated the development of the biofilm grown on dental implant surfaces, significantly increasing the number and cell viability of periodontal bacteria.

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.

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.

The study evaluated potassium peroxymonosulfate (PPMS) efficacy against rifampicin-resistant Salmonella Infantis (rif-SI), Escherichia coli (E. coli), Salmonella Infantis (SI), Newcastle disease virus (NDV) and avian influenza virus (AIV). The assessment encompassed varied concentrations, organic material conditions, and exposure durations to comprehensively evaluate PPMS efficacy. Moreover, PPMS’s efficacy was tested on diverse carrier surfaces and clothing to evaluate its bactericidal and virucidal potential. At the recommended concentrations (1X), PPMS effectively inactivated all pathogens within 5 sec, except for NDV, which required 30 sec in the presence of organic materials. At 0.5X, PPMS successfully inactivated E. coli, AIV and NDV within 5 sec in the absence of organic material. However, rif-SI and SI necessitated 30 sec for inactivation. Most pathogens were inactivated within 30 sec, with the exception for AIV, which was inactivated within 5 sec. PPMS effectively eliminated rif-SI on all carriers within 30 sec. Moreover, at both concentrations, PPMS successfully inactivated AIV on all carriers within 30 sec, except on stainless steel at 0.5X. Furthermore, PPMS at both concentrations required 5 and 30 sec, respectively, to inactivate AIV on the rayon sheet. Therefore, due to its demonstrated efficacy against a wide range of pathogens across diverse surfaces, PPMS emerges as a crucial alternative disinfectant significantly enhancing biosecurity on and around chicken farms. found in and around animal farms, slaughterhouses, and hospitals.

This paper presents an extension for principles of Differential Geometry on Surfaces (re-hashed through the budding field of CMS, the Calculus of Moving Surfaces). It analyzes mostly 2D Hypersurfaces with Riemannian Geometry and proposes the construction of a 3D Static Frame combining the Surface Basis Vectors with the Orthogonal Normal Field as a 3D Orthogonal Vector Frame. The paper introduces conventions for manipulating Tensors defined using this 3D Orthogonal Vector Frame as well as Curvature Connections associated with this Vector Frame. It then finally introduces Symbols and Tensors to describe Inner Products and Variance within the 3D Vector Frame and then extends all the above concepts to a surface which is Dynamic utilizing principles from CMS. This formulation has potential to extend identities and concepts from CMS and from Differential Geometry in a compact Tensorial Framework, which agrees with the new Framework proposed by CMS.

In the intricate dance between viruses and host cells, RNA-binding proteins (RBPs) serve as crucial orchestrators of gene expression and cellular processes. We will delve into the riveting realm of viral hijacking, where viruses deftly exploit host RBPs to manipulate cellular machinery for their replication and pathogenesis. Through a masterstroke of molecular subterfuge, viruses co-opt RBPs involved in various facets of RNA metabolism - from transcription to degradation - to promote viral gene expression and evade host immune defenses. This manipulation leads to global alterations in cellular RNA metabolism, impacting essential host genes vital for immune responses and homeostasis.Unveiling this clandestine alliance between viruses and RBPs is not just a scientific pursuit, but a critical imperative for devising innovative antiviral strategies to disrupt these interactions. By unraveling the intricate interplay between viral proteins and host RBPs throughout the viral life cycle - from entry to assembly - researchers aim to identify vulnerabilities that can be targeted for therapeutic intervention. Strategies such as disrupting viral protein-RBP interactions hold promise for inhibiting viral replication and curbing pathogenesis, offering a beacon of hope in the battle against viral infections.Our manuscript elucidates the indispensable roles played by RBPs in viral replication, translation, and pathogenesis, shedding light on the molecular mechanisms driving viral success. Delving deeper, it explores how viruses intricately entwine with host RBPs, manipulating cellular signaling pathways to create a hospitable environment for viral spread. By dissecting these manipulative tactics, researchers uncover new targets for antiviral therapy, envisioning a future where tailored interventions disrupt viral-host RBP interactions with precision and efficacy.As the narrative unfolds, the therapeutic implications of targeting RBPs or their interactions with viral proteins emerge as a promising frontier in the fight against viral infections. From small molecule inhibitors to RNA-based therapeutics, innovative approaches are on the horizon, offering new avenues for combatting viral diseases. We set the stage for future research, beckoning researchers to delve deeper into the molecular intricacies of viral hijacking of RBPs and charting a course towards novel therapeutic interventions that promise to reshape the landscape of antiviral therapy.\Ultimately, it beckons the scientific community to embark on a voyage of discovery, unraveling the secrets of viral hijacking of RBPs and paving the way for transformative advances in antiviral therapeutics. The stage is set for a new chapter in the battle against viral infections, where knowledge becomes the sword and innovation the shield against the pernicious machinations of viral pathogens.

The temporo-spatial theory of consciousness postulates that the brain implements its own inner time and space for conscious processing of outside world. In line with this hypothesis, I present a mechanistic model of mutually connected processes that encode the inner space and time. The model is used to elaborate the binding mechanism between two sets of processes representing the inner space and time, respectively. Further, a stochastic version of the model is developed to investigate the interplay between the binding strength and noise. The spectral entropy is used to characterize the noise effects on the systems of processes when the binding strength is varied. The stochastic modeling results reveal that the spectral entropy values for strongly bound systems have similar entropy values for weakly bound or even decoupled systems. Thus, the analysis performed in this study allows to conclude that the binding mechanism is noise-resilient.

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.

It is expected that scholars will continue to strengthen the depth and breadth of theoretical research on RIS, so as to provide a higher theoretical upper bound for the engineering application of RIS. While making breakthroughs in academic research, great progress has been made in engineering application research and industrialization promotion. This article will provide an overview of RIS engineering applications, mainly including the typical features, typical classifications, and typical deployment scenarios of RIS. Then the challenges and candidate solutions of the RIS are systematically and deeply analyzed, involving the cascade channel decoupling for solving the RIS beamforming, the influences and solutions of RIS regulation constraints, RIS system architecture of network controlled mode, the integrated channel regulation and information modulation, TDD mechanism used for RIS. Future trends and challenges are also provided.

The symmetries of a Riemann surface $\Sigma \setminus \{a_i\}$ with $n$ punctures $a_i$ are encoded in its fundamental group $\pi_1(\Sigma)$. Further structure may be described through representations (homomorphisms) of $\pi_1$ over a Lie group $G$ as globalized by the character variety $\mathcal{C}=\mbox{Hom} (\pi_1,G)/G$. Guided by our previous work in the context of topological quantum computing (TQC) and genetics, we specialize on the $4$-punctured Riemann sphere $\Sigma=S_2^{(4)}$ and the \lq space-time-spin' group $G=SL_2(\mathbb{C})$. In such a situation, $\mathcal{C}$ possesses remarkable properties (i) a representation is described by a $3$-dimensional cubic surface $V_{a,b,c,d}(x,y,z)$ with $3$ variables and $4$ parameters, (ii) the automorphisms of the surface satisfy the dynamical (non linear and transcendental) Painlev\'e VI equation (or $P_{VI}$), (iii) there exists a finite set of $1$ (\mbox{Cayley-Picard})+$3$ (\mbox{continuous platonic})+$45$ (\mbox{icosahedral}) solutions of $P_{VI}$. In this paper we feature on the parametric representation of some solutions of $P_{VI}$, (a) solutions corresponding to algebraic surfaces such as the Klein quartic and (b) icosahedral solutions. Applications to the character variety of finitely generated groups $f_p$ encountered in TQC or DNA/RNA sequences are proposed.

Proteins play a major role in biosensors in which they provide catalytic activity and specificity in molecular recognition. The immobilization process is however far from straightforward as it often affects the protein functionality. An extensive interaction of the protein with the surface or a significant surface crowding can lead to changes in the mobility and conformation of the protein structure. This review will provide an insight of how the analysis of the physico-chemical features of the protein surface features before the immobilization process can help to identify the optimal immobilization approach to preserve the functionality of the protein when on the surface of the biosensor.

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.

Many studies discuss carbon-based materials because of the versatility of its element. They include different opinions for scientific problems and discuss fairly at convincing and compelling levels within the scope and application. A gas-state carbon atom converts into various states depending on its conditions of processing. The electron transfer mechanism in the gas-state carbon atom is responsible to convert it into various states, namely, graphite, nanotube, fullerene, diamond, lonsdaleite and graphene. The shape of ‘energy trajectory’ enables transferring electrons from the left- and right-sides of an atom is like a parabola. That ‘energy trajectory’ is linked to states (filled state and suitable nearby unfilled state) where force-exertion along the poles of transferring electrons is remained balance. So, the mechanism of originating different states of a gas-state carbon atom is under the involvement of energy first. This is not the case for atoms executing confined inter-state electron-dynamics as the force is involved first. Graphite-, nanotube- and fullerene-state atoms ‘partially evolve partially develop’ (form) their structures. These possess one-dimensional, two-dimensional and four-dimensional ordering of atoms, respectively. Their structural formation also comprises ‘energy curve’ having a shape-like parabola. Transferring suitable filled state electron to suitable nearby unfilled state is under a balance force exerting along the poles. The graphite structure under only attained-dynamics of atoms can also be formed but in two-dimension. Here, binding energy between graphite-state carbon atoms is for a small difference of exerting forces along their opposite poles. Structural formation in diamond, lonsdaleite and graphene atoms involve energy to gain required infinitesimal displacements of electrons through which they maintain orientationally-controlled exerting forces along dedicated poles. In this study, the growth of diamond is found to be south to east-west (ground) where atoms bound ground to south. Thus, diamond atoms merge for a tetra-electron ground to south topological structure. Lonsdaleite atoms merge for a bi-electron ground to just-south topological structure. The growth of graphene is found to be north to ground where atoms bound ground to north. Thus, graphene atoms merge for a tetra-electron ground to north topological structure. Glassy carbon exhibits layered-topological structure where, tri-layers of gas-, graphite- and lonsdaleite-state atoms successively bind in repetitive order. Nanoscale hardness is also sketched based on different force-energy behaviors of different state carbon atoms. Here, structure evolution in each carbon state atom explores its own science.

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.

In this paper, we propose a reconfigurable intelligent surface (RIS) that can dynamically switch the transmission and reflection phase of incident electromagnetic waves in real time to realize the dual-beam or quad-beam and convert polarization of the transmitted beam. Such surfaces can redirect a wireless signal at will to establish robust connectivity when the designated line-of-sight channel is disturbed, thereby enhancing the performance of wireless communication systems by creating an intelligent radio environment. When integrated with a sensing element, they are integral to performing joint detection and communication functions in future wireless sensor networks. In this work, we first analyze the scattering performance of a reconfigurable unit element and then design a RIS. The dynamic field scattering manipulation capability of the RIS is validated by full-wave electromagnetic simulations to realize six different functions. The scattering characteristics of the proposed unit element, which incorporates two p-i-n diodes, have been substantiated through practical implementation. This involved the construction of a simple prototype and the subsequent examination of its scattering properties via the free-space measurement method. The obtained transmission and reflection coefficients from the measurements are in agreement with the anticipated outcomes from simulations.

This article develops algorithms for the characterization and the visualization of micro-scale features by using a small number of sample points, and with a goal to mitigate for the measurement shortcomings which are often destructive or time consuming. We implement the algorithms to rapidly examine the microscopic features of a Microelectromechanical System (MEMS) surface. Such images are highly dense; therefore, traditional image processing techniques might be computationally expensive. The contribution of this research include first, we develop local and global algorithm based on modified Thin Plate Spline (TPS) model to reconstruct high resolution images of the micro-surface’s topography, and its derivatives by using low resolution images. Second, we obtain a bending energy algorithm from our modified TPS model, and use it to filter out image defects. Finally, we develop a computationally efficient Windowing technique, which combines TPS and Linear Sequential Estimation (LSE), to enhance the visualization of images. The Windowing technique allows rapid image reconstruction based on the reduction of inverse problem.

A time-sequential working, spatially multiplexed autostereoscopic 3D display design consisting of a fast switchable RGB-color filter array is presented. The wavelength-selective filter barrier emits the light from a display over a larger active area than common autostereoscopic barrier displays. An optical modelling of wavelength-selective barriers has been used for instance to calculate the light ray distribution properties of that arrangement. To find well working display designs, automated searches by simulation and computational evaluation has been proceeded. Wavelength-selective filter barrier arrangements exhibit characteristics different from common barrier displays with similar barrier pitch and ascent. In particular, these constructions show strong angular luminance dependency under barrier inclination specified by correspondent slant angle. In time-sequential implementation it is important to avoid that quick eye or eyelid movement lead to visible color artifacts. In the millisecond regime tunable liquid crystal Fabry-Pérot color filters for the colors red, green and blue are presented. They consist of a sub-micrometer thick nematic layer sandwiched between dielectric mirrors and ITO-electrodes. These cells shall switch narrow-banding light of red, green or blue. An array for a glasses-free 3D display has to be equipped with several thousand switchable filter elements having different color apertures. The newly introduced design is usable as a multi user display as well as a single user system with user adaptive control.

We compare photoaligning properties of polymer layers fabricated from the same constituents: polymethyl-methacrylate (PMMA) and azo-dye Disperse Red 1 (DR1), either chemically attached to the PMMA main-chain, or physically mixed with it. Photoaligning properties depend on the preparation method drastically. This finding is supported by atomic force microscope (AFM) scans monitoring the light-induced changes at the polymer−air interface, and revealing a photoinduced mass transfer.

The objective of this work is to identify the mechanism of dropwise condensation on a smooth solid surface. We investigate the stable dropwise condensation that occurs at a droplet growth rate of 1 µm/s in diameter on a gold-coated glass surface. Additionally, we present our observations on unstable dropwise condensation, i.e., degradation of dropwise condensation of steam on a gold surface. The Surface Plasmon Resonance Imaging (SPRi) approach used in this study has lateral resolutions of 4-10 µm, thickness resolutions of 0.1-1 nm, and temporal resolutions of 200-10,000 frames per second (FPS). SPRi is used to evaluate the existence and structure of thin films and occurrence of initial nuclei during condensation. Visualization of the onset of stable dropwise condensation suggests droplets form at heterogeneous nucleation sites and that no film greater than a monolayer exists on the surface before the formation of droplets. Observation of the unstable dropwise condensation of steam shows the existence of water films that are several nanometers thick between droplets. This work shows that neither the nucleation theory or film rupture theory can individually explain the physics of dropwise condensation. Therefore, there is a need for a more comprehensive theory that can explain the mechanism of dropwise condensation.

The study aimed to identify different molds that grow on various food surfaces. As a result, we conducted a case study for the detection of mold on food surfaces based on the “you only look once (YOLO) v5” principle. In this context, a dataset of 2050 food images with mold growing on their surfaces was created. The dataset was trained using the pre-trained YOLOv5 algorithm. In comparison to YOLOv3 and YOLOv4, this current YOLOv5 model had better precision, recall, and average precision (AP), which were 98.10%, 100%, and 99.60%, respectively. The YOLOv5 algorithm was used for the first time in this study to detect mold on food surfaces. In conclusion, the proposed model successfully recognizes any kind of mold present on the food surface. Using YOLOv5, we are currently conducting research to identify the specific species of the detected mold.

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.

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.

Abstract: Plasma hemopexin (HPX) is the key antioxidant protein of the endogenous clearance pathway that limits the deleterious effects of heme released from hemoglobin and myoglobin. During intra-vascular hemolysis, heme partitioning to protein and lipid increases as the plasma concentration of HPX declines. Therefore, the development of HPX as a replacement therapy during high heme stress could be a relevant intervention for hemolytic disorders. A logical approach to enhance HPX yield involves recombinant production strategies from human cell lines. The present study focuses on a biophysical assessment of heme binding to recombinant human HPX (rhHPX) produced in the Expi293FTM (HEK293) cell system. In this report, we examine rhHPX in comparison with plasma HPX using a systematic analysis of protein structural and functional characteristics related to heme binding. Analysis of rhHPX by UV/Vis absorption spectroscopy, circular dichroism (CD), SEC-HPLC and catalase-like activity demonstrated a similarity to HPX fractionated from plasma. In particular, the titration of HPX apo-protein(s) with heme was performed for the first time using a wide range of heme concentrations to model HPX-heme interactions to approximate physiological conditions (from extremely low to more than 2-fold heme excess). The CD titration data showed an induced bisignate CD Soret band pattern typical for plasma and rhHPX versions at low heme-to-protein molar ratios and demonstrated that further titration is dependent on the amount of protein-bound heme to the extent that the arising opposite CD couplet results in a complete inversion of the observed CD pattern. The data generated in this study suggests more than one binding site in both plasma and rhHPX. Further, our study provides a useful analytical platform for detailed characterization of HPX-heme interactions and potentially, novel HPX fusion constructs.

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.

XPS and ARXPS characterization of surface layers resulting from the functionalization of polymers such as PVC modified with MPTMS and APTES is challenging due to the signals overlap, deriving both from the substrate and the functionalized layers. In this work, a freshly cleaved, ideally flat gold surface was used as carbon-free model substrate functionalized with MPTMS and subsequently grafted with APTES. Avoiding the overlap of signals from carbon atoms present in the substrate, the signals in the C1s, O1s, Si2p, S2p and N1s high-resolution spectra could be assigned to the MPTMS / APTES functionalized layer only and the curve fitting parameters could be determined. Quantitative analysis was in very good agreement with the expected stoichiometry of the functionalized layer, confirming the adopted curve fitting procedure. In addition, it was found that one molecule of APTES grafted two MPTMS via silane groups. ARXPS allowed determining the thickness of the functionalized layers: MPTMS thickness was found to be 0.5 (0.2) nm, MPTMS + APTES thickness 1.0 (0.2) nm in good agreement with Avogadro model calculations. This approach can be considered a powerful tool for characterising functionalized surfaces of more complex systems by XPS.

The three-dimensional morphology of frictional sub-surfaces holds significant importance for studying tribological issues. However, the uniformity of horizontal datum in 3D scanning is limited for curved surfaces, resulting in the inability to obtain accurate contour characterization parameters from the scanning results. This study aims to address this issue by constructing regular surface equations and normalizing the 3D profiler scanning results. By fitting the data, a "plane" surface representative of the surface features is obtained, and the paper demonstrates this approach on the surface morphology of different worn parts in the frictional area of spherical bearings located in the specific environment of the Three Gorges gate. The results indicate that the obtained "plane" effectively reconstructs the three-dimensional morphology map of the regular surface. Moreover, this reconstructed plane not only clearly illustrates the surface characteristics but also provides the foundation for analyzing the wear mechanism.

It is shown that the representation theory of some finitely presented groups thanks to their $SL_2(\mathbb{C})$ character variety is related to algebraic surfaces. We make use of the Enriques-Kodaira classification of algebraic surfaces and the related topological tools to make such surfaces explicit. We study the connection of $SL_2(\mathbb{C})$ character varieties to topological quantum computing (TQC) as an alternative to the concept of anyons. The Hopf link $H$, whose character variety is a Del Pezzo surface $f_H$ (the trace of the commutator), is the kernel of our view of TQC. Qutrit and two-qubit magic state computing, derived from the trefoil knot in our previous work, may be seen as TQC from the Hopf link. The character variety of some two-generator Bianchi groups as well as that of the fundamental group for the singular fibers $\tilde{E}_6$ and $\tilde{D}_4$ contain $f_H$. A surface birationally equivalent to a $K_3$ surface is another compound of their character varieties.

For a set of closed curved surfaces that resemble a Langmuir monolayer an energy is defined that depends only on the curvature of the surfaces interacting with the dimensions normal to the surfaces, that is, the thickness of these surfaces. The thickness, or depth, of the surfaces originates because of surface-particles with chains, that move freely on the inside of the surfaces at a certain depth. This is a purely geometrical description that does not depend on the introduction of ad hoc constants like the elastic constant. With a statistical mechanical model the equations of state are calculated for a gas of non-connected sphere-like surfaces in a volume. There are two states of which the lower temperature state is depending mostly on the interaction energy and surface properties, and the higher temperature state is depending mostly on sphere kinetic and volume properties. This results in aggregation of the sphere-like surfaces from many small ones to few large ones when lowering temperature and vice versa. The model allows for the calculation of the partition function and, when the emergence of the curvature - depth interaction is described as a phase-transformation, for the application of Noether’s theorem. Because of these properties the model is interesting in its own right apart from being an addition to existing elastic descriptions of surfaces.

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.

Different types of resonators are used to create acoustic metameterials and metasurfaces. Recent studies focused on the use of multiple resonators of dipole, quadrupole, octupole and even hexadecapole types. This paper considers the theory of an acoustic metasurface, which is a flat surface with a periodic arrangement of multiple resonators. The sound field reflected by the metasurface is determined. If the distance between the resonators is less than a half the wavelength of the incident plane wave, the far field can be described by a reflection coefficient that depends on the angle of incidence. This allows to characterize the acoustic properties of the metasurface by a homogenized boundary condition, which is a high order tangential impedance boundary condition. The tangential impedance depending on the multiple order of the resonators is introduced. In addition, we analyze sound absorption properties of these metasurfaces, which are a critical factor in determining their performance. The paper presents a theoretical model that accounts for the multiple orders of resonators and their impact on sound absorption. The maximum absorption coefficient for a diffuse sound field, as well as the optimal value for the homogenized impedance, are calculated for arbitrary multipole orders.

Chemical instability of liquid-repellent surfaces is one of the nontrivial hurdles that hinders their real-world applications. Although much efforts have been made to prepare chemically durable liquid-repellent surfaces, few attentions have been paid to exploit the instability for versatile use. Herein, we propose to create hydrophilic patterns on superhydrophobic surface by taking advantage of its chemical instability induced by acid solution treatment. Superhydrophobic Cu(OH)2 nanoneedles covered Cu plate that shows poor stability towards HCl solution (1.0 M) is taken as an example. Results show that 2.5 min of HCl solution exposure leads to the etching of Cu(OH)2 nanoneedles and partial removal of self-assembled fluoroalkyl silane molecular layer, resulting in the wettability transition from superhydrophobocity to hydrophilicity, and the water contact angle decreases from ~160° to ~30°. Hydrophilic dimples with different diameters are then created on the superhydrophobic surfaces by depositing HCl droplets with different volumes. Afterwards, the hydrophilic dimple patterned superhydrophobic surfaces are used for water droplet manipulations, including controlled transfer, merging and nanoliter droplets deposition. The results thereby verify the feasibility of creating wettability patterns on superhydrophobic surfaces by using their chemical instability towards corrosive solutions, which broadens the fabrication methods and applications of functional liquid-repellent surfaces.

Nanometer-curved surfaces are abundant in biological systems as well as in nano-sized technologies. Properly functionalized polymer-grafted nanoparticles (PGNs) adhere to surfaces with different geometries and curvatures. This work explores some of the energetic and mechanical characteristics of the adhesion of PGNs to surfaces with positive, negative and zero curvatures using Coarse-Grained Molecular Dynamics (CGMD) simulations. Our calculated free energies of binding of the PGN to the curved and flat surfaces as a function of separation distance show that curvature of the surfaces critically impacts the adhesion strength. We find that the flat surface is the most adhesive, and the concave surface is the least adhesive surface. This somewhat counterintuitive finding suggests that while a bare nanoparticle is more likely to adhere to a positively curved surface than a flat surface, grafting polymer chains to the nanoparticle surface inverts this behavior. Moreover, we studied the rheological behavior of PGN upon separation from the flat and curved surfaces under external pulling force. The results presented herein can be exploited in drug delivery and self-assembly applications.

Organic-organic interactions play important roles in the secondary organic aerosol formation, but the interactions are complex and poorly understood. Here we use environmental molecular beam experiments combined with molecular dynamics simulations to investigate the interactions between methanol and nopinone, as atmospheric organic proxies. In the experiments, methanol monomers and clusters are sent to collide with three types of surfaces, i.e., graphite, thin nopinone coating on graphite and multilayer surfaces, at temperatures between 140 K and 230 K. Methanol monomers are efficiently scattered from the graphite surface, whereas the scattering is substantially suppressed from nopinone surfaces. The desorption from the three surfaces is similar, suggesting that all the surfaces have weak or similar influences on the methanol desorption. The molecular dynamics results show that upon collisions the methanol clusters shatter, and the shattered fragments quickly diffuse and recombine to clusters. The desorption involves a series of processes, including detaching from clusters and desorbing as monomers. The experimental results also show that all trapped methanol molecules completely desorb within a short experimental time scale at temperatures of 180 K and above. At lower temperatures, the desorption rate decreases, and a long experimental time scale is used to resolve the desorption, where three desorption components are identified. The fast component is beyond the experimental detection limit. The intermediate component exhibits multi-step desorption character and has an activation energy of E_a = 0.18 ± 0.03 eV, in good agreement with simulation results. The slow desorption component is related to diffusion processes due to the weak temperature dependence.

The accurate calculation of real contact area between rough surfaces is a key issue in tribology. In this paper, based on the geometrical information of total contact area and the number of contact spots with respect to surface separation, a new method is proposed to determine the relation between real contact area and normal load. The contact of rough surfaces is treated as an accumulation of incremental multi-plateaus indentations with varying average contact radius. Comparisons with direct finite element calculations and some other theoretical predictions demonstrate the efficiency of this approach.

Functional ZnO nanostructured surfaces are important in a wide range of applications. Here we report facile fabrication of ZnO surface structures at near room temperature with morphology resembling that of sea urchins, with densely packed, μm-long, tapered nanoneedles radiating from the urchin centre. The ZnO urchin structures were successfully formed on several different substrates with high surface density and coverage, including silicon (Si), glass, polydimethylsiloxane (PDMS), and copper (Cu) sheets, as well as Si seeded with ZnO nanocrystals. Time-resolved SEM revealed growth kinetics of the ZnO nanostructures on Si, capturing the emergence of “infant” urchins at the early growth stage and subsequent progressive increase in the urchin nanoneedle length and density, whilst the spiky nanoneedle morphology was retained throughout the growth. ε-Zn(OH)₂ orthorhombic crystals were also observed alongside the urchins. The crystal structures of the nanostructures at different growth time were confirmed by synchrotron X-ray diffraction measurements. On seeded Si substrates, a two-stage growth mechanism was identified, with a primary growth step of vertically aligned ZnO nanoneedle arrays preceding the secondary growth of the urchins atop the nanoneedle array. The antibacterial, anti-reflective, and wetting functionality of the ZnO urchins—with spiky nanoneedles and at high surface density—on Si substrates was demonstrated. First, bacteria colonisation was found to be suppressed on the surface after 24 h incubation in Gram-negative E. coli culture, in contrast to control substrates (bare Si and Si sputtered with 20 nm ZnO thin film). Secondly, the ZnO urchin surface, exhibiting superhydrophilic property with a water contact angle ~0°, could be rendered superhydrophobic with a simple silanization step, characterised by a water static contact angle θ of 159° ± 1.4° and contact angle hysteresis ∆θ < 7°. The dynamic superhydrophobicity of the surface was demonstrated by bouncing-off of a falling 10 μL water droplet, with a contact time of 15.3 milliseconds (ms), captured using a high-speed camera. Thirdly, it was shown that the presence of dense spiky ZnO nanoneedles and urchins on the seeded Si substrate exhibited a reflectance R < 1% over the wavelength range λ = 200–800 nm. The ZnO urchins with unique morphology via a facile fabrication route at room temperature, readily implementable on different substrates, may be further exploited for multifunctional surfaces and product formulations.

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.

Taking a DNA-sequence, a word with letters/bases A, T, G and C, as the relation between the generators of an infinite group $\pi$, one can discriminate two important families: (i) the cardinality structure for conjugacy classes of subgroups of $\pi$ is that of a free group on $1$ to $4$ bases and the DNA word, viewed as a substitution sequence, is aperiodic. (ii) The cardinality structure for conjugacy classes of subgroups of $\pi$ is not that of a free group, the sequence is generally not aperiodic and topological properties of $\pi$ have to be determined differently. The two cases rely on DNA conformations such as A-DNA, B-DNA, Z-DNA, G-quadruplexes, etc. We found a few salient results: Z-DNA, when involved in transcription, replication and regulation in a healthy situation implies (i). The sequence of telomeric repeats comprising $3$ distinct bases, most of the time, satisfies (i). For $2$-base sequences in the free case (i) or non free case (ii), the topology of $\pi$ may be found in terms of the $SL(2,\mathbb{C})$ character variety of $\pi$ and the attached algebraic surfaces. The linking of two unknotted curves --the Hopf link-- may occur in the topology of $\pi$ in cases of biological importance, in telomeres, G-quadruplexes, hairpins and junctions, a feature we already found in the context of models of topological quantum computing. For $3$- and $4$ base sequences, other knotting configurations are noticed and a building block of the topology is the $4$-punctured sphere. Our methods have the potential to discriminate potential diseases associated to the sequences.

The selectivity in selective autophagy pathways is achieved via the selective autophagy receptors (SARs) – proteins that bind a ligand on the substrate to be degraded and the Atg8-family protein on the growing autophagic membrane, phagophore, effectively bridging them. In mammals, the most common ligand of SARs is ubiquitin, a small protein modifier that tags substrates for their preferential degradation by autophagy. Consequently, the most common SARs are the ubiquitin-binding SARs, such as SQSTM1/p62 (sequestosome 1). Surprisingly, there is only one SAR of this type in yeast – Cue5, which acts as a receptor for aggrephagy and proteaphagy – pathways that remove the ubiquitinated protein aggregates and proteasomes, respectively. However, recent studies described the ubiquitin-dependent autophagic pathways that do not require Cue5, e.g. stationary phase lipophagy for intracellular lipid droplets and nitrogen starvation-induced mitophagy for mitochondria. What is the role of ubiquitin in these pathways? Here, we propose that the ubiquitinated lipid droplets and mitochondria are recognized by the alternative ubiquitin-binding SARs. Our analysis identifies the proteins that could potentially fulfill this role in yeast. We think that matching of the ubiquitin-dependent (but Cue5-independent) autophagic pathways with the ubiquitin-and-Atg8-binding proteins enlisted here might uncover the novel ubiquitin-binding SARs in yeast.

Abstract: Background: Hemopexin (Hx) is a plasma glycoprotein that scavenges heme (Fe(III) protoporphyrin IX), Hx have important implication in hemolytic disorders and hemorrhagic condition because the release of hemoglobin increase labile heme, which is potentially toxic producing oxidative stress. Hx has been considered for therapeutic use and diagnostics. In this work, we analyzed and mapped interaction sequences of Hx with hemin and hemoglobin (2) Methods: Spot-synthesis technique was used to map human hemopexin (P02790) binding to hemin and human hemoglobin, a library of 15 amino acid peptides with a 10-amino acid overlap was designed to represent the entire coding region (aa 1-462) of hemopexin and synthesized onto cellulose membranes. In silico approach was performed to analyze amino acid frequency in identified interaction regions, and molecular docking was applied for protein-protein interaction (3) Results: Seven linear peptide sequences in Hx were identified to bind hemin (H1-H7), and five were described for Hb (Hb1-Hb5) interaction, with just two sequences shared between hemin and Hb. Amino acid composition of identified sequences demonstrated that Histidine residues are relevant for heme binding, H105, H293, H373, H400, H429, and H462 was distributed in H1-H7 peptide sequences, but other residues may also play an important role. Molecular docking analysis demonstrated Hx association with the β-chain of Hb, with several hot spot amino acids that coordinated interaction. (4) Conclusions: This study highlights new insights on Hx-hemin binding motifs and protein-protein interactions with Hb. Binding sequences and identified specific peptides can be used for therapeutic purposes and diagnostics, as hemopexin is under investigation to treat different diseases, and there is an urgent need for diagnostics of labile heme for monitoring hemolysis.

Dictyostelium discoideum is gaining increasing attention as a model organism for the study of calcium binding and calmodulin function in basic biological events as well as human diseases. After a short overview of calcium-binding proteins, the structure of Dictyostelium calmodulin and the conformational changes effected by calcium ion binding to its four EF hands is compared to its human counterpart, emphasizing the highly conserved nature of this central regulatory protein. The calcium-dependent and -independent motifs involved in calmodulin binding to target proteins are discussed with examples of the diversity of calmodulin binding proteins that have been studied in this amoebozoan. The methods used to identify and characterize calmodulin binding proteins is covered followed by the ways Dictyostelium is currently being used as a system to study several neurodegenerative diseases and how it could serve as a model for studying calmodulinopathies such as those associated with specific types of heart arrythmia. Because of its rapid developmental cycles, its genetic tractability, and a richly endowed stock center, Dictyostelium is in a position to become a leader in the field of calmodulin research.

The tailoring of the surface properties of cellulose nanocrystals (CNCs) to meet various requirements in environmental, food, and material areas has always been of great interest. In this study, the surface chemistry of CNCs was noncovalently modified by cetyltrimethylammonium bromide (CTAB), followed by characterizations and an application as a coating material for interfacial interaction investigation over various substrates. Due to the CTAB modification, the surface charge of the CNCs was neutralized, resulting in an increased size of each nanocrystal at the aqueous status and the aggregated microfibers when dried up. The CTAB modification not only decreased the crystallinity of the samples from 48.57% to 9.12% but also hydrophobized the CNCs and decreased their total surface energy. Finally, the adsorption behavior of the CNCs and CTAB-CNCs over nonionic, anionic, and cationic polymers was investigated by ellipsometry. Based on the thickness of the CNC and CTAB-CNC layers over 2-Hydroxyethyl cellulose (HEC), carboxymethyl cellulose (CMC), and polyethyleneimine (PEI), we proposed that the adsorption behavior was overall influenced by electrostatic interaction, hydrogen bonding, and van der Waals forces and the thickness of the adsorbed layers could be impacted by both the surface charge and the size of the crystals.

Shell-like, double curved and thus above-average performance structures, are usually produced monolithically on site. For industrial advancement, however, they must be divided into transportable modules which can be assembled on the construction site (design for assembly). Models are lattice shells made of steel and glass, in which predominantly flat sub-surfaces (modules) are used. Therefore, the main question is: Which modularizations are suitable for flow production with mineral building materials? In this paper designed free-form surface is going to be discretized as PQ circular mesh system, suitable modules for 3D concrete printing. Moreover, the multi-criteria optimization is done with Response Surface Methodology (RSM) in order to get optimal final shape. The goal is to start from the arbitrary shape, that can be generated from two curves, with possible two-way division into modules and compare it with the resulted discretized PQ circular mesh system, realized with new algorithm. The comparison can be defined through two main criteria: geometrical and structural.

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 presence of potentially pathogenic bacteria on veterinary clinic surfaces may be problematic. In this study we collected swab samples (Fisherbrand, double transport swabs with Stuart’s liquid medium) and water samples from five veterinary rehabilitation clinics. Swabs and water samples were transported to a microbiology lab for processing. At the lab swabs were used to inoculated Hardy’s Cdiff Banana broth (for Clostridium difficile [Cdiff]), and five different types of bacterial growth media, including: Hardy CHROM MRSA agar (methicillin resistant Staphylococcus aureus [MRSA], and S. pseudintermedius [SIM]), Mannitol Salt Agar (S. aureus), Eosin Methylene Blue agar (enterics [ENT]), Pseudomonas Isolation agar (Pseudomonas sp.), and Tryptic Soy Agar [TSA] (non-specific). The most prominent species cultured was Cdiff (on nearly 55% of swabs). Bacillus sp. and Enterics were encountered on nearly 35% of swabs, with MRSA and SIM on just over 10% of swabs. The most contaminated sample site was harnesses/life jackets used with the underwater treadmill (33% of swabs). Underwater treadmill water had total bacterial counts from 1.6 to 2.7 e3 cfu/ml. Of all bacterial species detected SIM tends to be more pathogenic for dogs. Targeted cleaning/disinfecting in these clinics could help reduce risks for both animals and caregivers utilizing these clinics.

This brief review introduces some general properties of lower atmospheric motions that may be exploited by birds, linking historical findings and current knowledge from both observational and modeling perspectives. The relative importance of turbulent mixing resulting from wind shear and that from buoyant thermals is emphasized as well as the determinants of the geometry of the resulting vertical motions.

One of the challenges facing the industrial adoption of additively manufactured parts is the surface roughness on the as-built part. The surface roughness of parts is frequently characterized by metrics specified by international standards organizations. However, these standards list many surface metrics that can make it unclear which to use to best describe the surface. In this work, the ability of the various surface metrics to successfully classify the as-built and post-processed surfaces is studied using linear classification models. Laser polishing via remelting and manual grinding are the post-processing techniques used to smooth the as-built surface. The ability of the linear classifier to successfully categorize the various surfaces is demonstrated, and the various surface metrics are ranked according to the strength of their individual ability to classify the surfaces. This work promotes the method as a potential way to autonomously classify as-built and laser polished surfaces.

Inspired by nature's examples such as lotus leaves and insect wings, superhydrophobic surfaces have been extensively studied and engineered. However, achieving superoleophobic surfaces, which repel oils, has proven to be more challenging due to the oils' lower surface tension than water. This article presents a novel, cost-effective technique for fabricating superoleophobic surfaces with enhanced durability. We demonstrate the effectiveness of this technique by using Perfluorooctyltriethoxysilane (PFOTES) and silicon dioxide nanoparticles on stainless steel mesh substrate. The resulting surfaces exhibit remarkable superoleophobic properties by incorporating re-entrant structures, low surface energy, and high surface roughness, making them ideal for oil-repellency applications.

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.

In an attempt to correct misunderstandings this article brings together the observations on Calcium, Myosin Binding Protein-C and Hypertrophic Cardiomyopathy in the basic function of cardiac muscle. A finding of many years ago is reiterated in a novel enzyme kinetic format with defined rate limiting step which makes CaATP the apparent substrate of the actomyosin cross-bridge. The relationship of these kinetics to recent observations on disruption of myosin binding protein-C is described along with how this bears on the understanding of the related cardiomyopathies.

At nuclear scale, we present three heuristic relations pertaining to strong and electroweak coupling constants. With these relations, close to beta stability line, it is possible to study nuclear binding energy with a single energy coefficient of magnitude $\left(\frac{1}{{\alpha }_s}\right)\left[\frac{e^2}{4\pi {\epsilon }_0{R}_0}\right]\approx 10.0\text{MeV}\text{.}$ With reference to up and down quark masses, it is also possible to interpret that, nuclear binding energy is proportional to the mean mass of $\left[\left(2m_u+m_d\right)\text{and}\left(m_u+2m_d\right)\right]\approx 10.0\text{MeV}.$

Computer extended Descriptive Geometry (CeDG) is a new approach to solve and build computer models of three dimensional (3D) geometrical systems through descriptive geometry procedures that have demonstrated reliability and accuracy. CeDG may calculate a parametric algebraic exact form for the spatial curves generated in the intersection of two surfaces, as well as of the flattened pattern of any developable surface involved in those encounters. This study presents first the theoretical foundations and methodology to calculate those parametric algebraic curves. Secondly, a compound hopper is defined and modelled through CeDG (implemented in GeoGebra) and CAD (Solid Edge 2023) approaches to evaluate the advantages of CeDG against CAD. The results demonstrate the robustness and accuracy of the CeDG technique for surfaces intersection and flattening and the advantages of CeDG against Solid Edge 2023 in solving the hopper case study.

This review focuses on Cu/TiO2 sequentially and Cu-TiO2 co-sputtered catalytic/photocatalytic surfaces leading to bacterial inactivation discussing their stability, synthesis, adhesion and antibacterial kinetics. The intervention of TiO2, Cu and the synergic effect of Cu and TiO2 on films prepared by a colloidal approach and other techniques is also reviewed leading to bacterial inactivation. Processes in aerobic media and anaerobic media leading to bacterial loss of viability on multidrug resistant (MDR) pathogens, Gram-negative (-) and Gram-positive(+) bacteria are described. Insight is provided for the interfacial charge transfer mechanism under solar irradiation occurring between TiO2 and Cu. surface properties of 2D TiO2/Cu and TiO2-Cu films are correlated with the bacterial inactivation kinetics observed in the dark and under light. The intervention of these antibacterial sputtered surfaces in health-care facilities leading to MRSA-isolates is described in the dark and under the actinic light. The synergic intervention of the Cu and TiO2 films leading to bacterial inactivation prepared by direct current magnetron sputtering (DCMS), pulsed direct current magnetron sputtering (DCMSP) and highly ionized pulse plasma magnetron sputtering (HIPIMS) is reported in a detailed way.

Cartilage degeneration is a characteristic of osteoarthritis (OA) which is often observed in aging populations. This degeneration is due to the breakdown of articular cartilage (AC) mechanical and tribological properties, primarily attributed to lubrication failure. Understanding the reasons behind these failures and identifying potential solutions could have significant economic and societal implications, ultimately enhancing the quality of life. This review provides an overview of developments in the field of AC, focusing on its mechanical and tribological properties. The emphasis is on the role of lubrication in degraded AC, offering insights into its structure and function relationship. Further it explores the fundamental connection between AC mechano-tribological properties and the advancement of its degradation and puts forth recommendations for strategies to boost its lubrication efficiency.

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.

Introduction: This study aims to elucidate the clinical diagnostic value of S100 Calcium Binding Protein beta (S100B) in epilepsy, a topic of ongoing debate among European and Asian epilepsy research centres.Methods and analysis: A structured long-term research plan was developed, comprising three phases. Phase one involves observational studies investigating the correlation between S100B levels in serum or cerebrospinal fluid and epilepsy. Phase two integrates observational and randomised controlled data to establish baseline S100B levels across diverse epilepsy demographics, underpinning the predictive value of S100B for epilepsy. Phase three focuses on randomised controlled trials to evaluate the diagnostic accuracy of S100B as an epilepsy biomarker.Ethics and dissemination: All enrolled patients will provide written consent. The ethics committee of the Second People’s Hospital of Gansu Province, Affiliated Hospital of Northwest Minzu University, China, approved the study (GSSEY2022-KY009-01).Registration: The study is registered with PROSPERO (CRD42023425431).

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.

Food processing and consumption involves multiple contacts between biological fluids and solid materials of processing devices of which steel is one of the most common. Due to complexity of these interactions, it is difficult to identify the main control factors in the formation of undesirable deposits on the device surfaces that may affect safety and efficiency of the processes. Mechanistic understanding of biomolecule-metal interactions involving food proteins could improve management of these pertinent industrial processes and consumer safety in food industry and beyond. In this work, we perform a multiscale study of formation of protein corona on iron surfaces and nanoparticles in contact with cow milk proteins. By calculating the binding energies of proteins with the substrate we quantify the adsorption strength and rank proteins by the adsorption affinity. We use a multiscale method involving all-atom and coarse-grained simulations as well as generation of 3D structures of the proteins for this purpose. Finally, using the adsorption energy results, we predict the composition of protein corona on iron nanoparticles and flat surfaces via a competitive adsorption model.

The mechanical properties and stability of hydrophobic surface structures prepared by traditional methods are still the main technical bottlenecks restricting the broad application of hydrophobic systems on workpiece surfaces. In this contribution, we propose a technique called selective laser shock peening (SLSP) to enable large-scale high efficient, low-cost manufacturing of hydrophobic metal surfaces with enhanced mechanical properties for durable applications. Using the method of experimental investigation combined with numerical calculation, the hydrophobic properties, mechanical properties, and tribological properties of the samples prepared under SLSP, all-laser shock peening (ALSP), and non-laser shock peening (NLSP) are studied. The SLSP process could prepare a 3D gradient structure material with surface structures, a two-phase (strong phase, soft phase) distribution on the surface, and a multi-level gradient distribution in the thickness direction. Compared with the 2D gradient structure prepared by the traditional process, 3D gradient structures by SLSP have more significant advantages in improving the wetting behavior and the mechanical properties of the material, which proves SLSP to be a novel method to fabricate functional metal surface structures, with highly high engineering application value.

Large intelligent surfaces (LIS) promises not only to improve the signal to noise ratio, and spectral efficiency but also to reduce the energy consumption during the transmission. We consider a base station equipped with an antenna array using the maximum ratio transmission (MRT), and a large reflector array sending signals to a single user. Each subchannel is affected by the Rayleigh flat fading, and the reflecting elements perform non-perfect phase correction which introduces a Von Mises distributed phase error. Based on the central limit theorem (CLT), we conclude that the overall channel has an equivalent Gamma fading whose parameters are derived from the moments of the channel fading between the antenna array and LIS, and also from the LIS to the single user. Assuming that the equivalent channel can be modeled as a Gamma distribution, we propose very accurate closed-form expressions for the bit error probability and a very tight upper bound. For the case where the LIS is not able to perform perfect phase cancellation, that is, under phase errors, it is possible to analyze the system performance considering the analytical approximations and the simulated results obtained using the well known Monte Carlo method. The analytical expressions for the parameters of the Gamma distribution are very difficult to be obtained due to the complexity of the nonlinear transformations of random variables with non-zero mean and correlated terms. Even with perfect phase cancellation, all the fading coefficients are complex due to the link between the user and the base station that is not neglected in this paper.

Two major uses of linear perspective are in planar paintings - the flat canvas is incongruent with the painted 3-D scene - and in forced perspectives, such as theater stages that are concave truncated pyramids, where the physical geometry and the depicted scene are congruent. Patrick Hughes pioneered a third major art form, the reverse perspective, where the depicted scene opposes the physical geometry. Reverse perspectives comprise solid forms (truncated pyramids and prisms) jutting toward the viewer, thus forming concave spaces between the solids. The solids are painted in reverse perspective: as an example, the left and right trapezoids of a truncated pyramid are painted as rows of houses; the bottom trapezoid is painted as the road between them and the top forms the sky. This elicits the percept of a street receding away, even though it physically juts toward the viewer. Under this illusion, the concave void spaces between the solids are transformed into convex volumes. This depth-inversion creates a concomitant motion illusion: when a viewer moves in front of the art piece, the scene appears to move vividly. Two additional contributions by the artist are discussed, in which he combines reverse perspective parts with forced and planar perspective parts on the same art piece. The effect is spectacular, creating objects on the same planar surface that move in different directions, thus “breaking” the surface apart, demonstrating the superiority of objects over surfaces. We conclude with a discussion on the value of these art pieces in vision science.

A finite-type immersion or smooth map is a nice tool to classify submanifolds of Euclidean space, which comes from eigenvalue problem of immersion. The notion of generalized 1-type is a natural generalization of those of 1-type in the usual sense and pointwise 1-type. We classify ruled surfaces with generalized 1-type Gauss map as part of a plane, a circular cylinder, a cylinder over a base curve of an infinite type, a helicoid, a right cone and a conical surface of $G$-type.

Intermolecular interactions are the fabrics underlying almost all processes in living organisms, where two cornerstone concepts, intermolecular binding affinity (K d ) and binding energy (ΔG), have long been established to physically describe the strengths of biomolecular interactions, e.g., drug-target K d and ΔG to describe the strength of drug-target interaction. The past two-three years saw a big step forward in the use of artificial intelligence (AI) in structural biology (e.g., AlphaFold for protein structure prediction) and drug discovery & design. In light of the roles of K d and ΔG in drug discovery & design, the speed of this AI progress raises a question of what’s next for its practical application in the pharmaceutical industry, in addition to a system-wide account of biomolecular structures and motions. Last August, the concept of a general intermolecular binding affinity calculator (GIBAC) was for the first time coined and proposed in an MDPI-published preprint. Here, this article puts forward an updated conceptual and practical framework of GIBAC, including its inception, definition, construction, practical applications, technical challenges and limitations, and future directions. Moreover, this article argues that the time is now ripe for the construction of such an accurate, precise and efficient GIBAC to be on the agenda of the entire drug discovery & design community, to ensure its applicability & reliability, and to enhance its value in drug R&D in future.

The brain’s ability to create a unified conscious representation of an object by integrating information from multiple perception pathways is called perceptual binding. Binding is crucial for normal cognitive function. Some perceptual binding errors and disorders have been linked to certain neurological conditions, brain lesions, and conditions that give rise to illusory conjunctions. However, the mechanism of perceptual binding remains elusive. Here, we present a computational model of binding using two sets of coupled oscillatory processes that are assumed to occur in response to two different percepts. We use the model to study the dynamic behavior of coupled processes to characterize how these processes can modulate each other and reach a temporal synchrony. We identify different oscillatory dynamic regimes that depend on coupling mechanisms and parameter values. The model can also discriminate different combinations of initial inputs that are set by initial states of coupled processes. Decoding brain signals that are formed through perceptual binding is a challenging task, but our modeling results demonstrate how crosstalk between two systems of processes can possibly modulate their outputs. Therefore, our mechanistic model can help one gain a better understanding of how crosstalk between perception pathways can affect the dynamic behavior of the systems that involve perceptual binding.