The traditional way to define cosmic acceleration, denoted \( q \), relies on a comoving frame of reference within a 3D space-like coordinate system. This is the acceleration of the background metric in a particular frame rather than the actual acceleration between different observers on time-like geodesics. This traditional choice obscures the true physical processes, much like the Earth-centered model historically obscured the understanding of gravitational forces before the heliocentric shift. In this study, we introduce \( q_E \), a new metric defined by distances between causal events (i.e. acceleration between observes) in 4D null space. We compare \( q_E \) with \( q \) using observational data from supernovae (SN) and radial clustering of galaxies and quasars (BAO). Our results show that \( q_E \) offers a closer alignment with this data. Our analysis reveals that cosmic expansion, when viewed from the rest frame, is actually decelerating, confined by dynamics inside an Event Horizon, similar to conditions within a Black Hole interior. This indicates that \( \Lambda \) acts not as an agent of new dark energy or as a modification of gravity, but as a boundary term exerting an attractive force similar to a rubber band, which resists further expansion and prevents horizon crossing of events. We show how this interpretation of cosmic expansion as deceleration in the rest frame challenges conventional cosmological models and suggests that a reevaluation of these models is necessary.

Greek roots: "phos" (φῶς) - means "light" and "dynamis" (δύναμις) - means "force" or "power". Photodynamic therapy (PDT) is an innovative treatment method based on the ability of photosensitizers to produce reactive oxygen species after exposure to light of a specific wavelength range, either in the visible or near infrared range. This process results in damage to pathological cells, such as cancer cells, while minimizing the impact on healthy tissues. PDT is a promising direction in the treatment of many diseases, with particular emphasis on the fight against cancer and other diseases asso-ciated with excessive cell growth. The power of light contributed to the creation of phototherapy, whose history dates back to ancient times. It was then noticed that some substances exposed to the sun have a negative effect on the body, while others have a therapeutic effect. This work provides a detailed review of photodynamic therapy, from its origins to the present day. It is surprising how a seemingly simple beam of light can have such a powerful healing effect, which is used not only in dermatology, but also in oncology, surgery, microbiology, virology, and even dentistry. However, despite promising re-sults, photodynamic therapy still faces many challenges. The availability of this thera-py is limited due to the small number of centers offering this type of treatment and the high costs, which may be unaffordable for many patients. Moreover, photodynamic therapy requires further research and improvement.

Precipitation patterns are critical for understanding the hydrological and climatological dynamics of any region. Sicily, the largest island of the Mediterranean sea, with its diverse topography and climatic conditions, serves as an ideal case study for analyzing precipitation data to gain insights into regional water resources, agricultural productivity, and climate change impacts. This paper employs advanced statistical physics methods, particularly Tsallis q-statistics, to analyze sub-hourly precipitation data from 2002 to 2023, provided by the Sicilian Agrometeorological Informative System (SIAS). We investigate several critical variables related to rainfall events, including duration, depth, maximum record, and inter-event time. The study spans two decades (2002-2012 and 2013-2023), analyzing the distributions of relevant variables. Additionally, we examine the simple returns of these variables to identify significant temporal changes, fitting these returns with q-Gaussian distributions. Our findings reveal the scale-invariant nature of precipitation events, the presence of long-range interactions and memory effects, characteristic of complex environmental processes.

The mystery phenomenon of fungal bioluminescence has always captivated human curiosity, although more attempts need to be made, particularly to bring the new species to the surface. In this study, we devoted considerable space to the taxonomy of these fungi while discussing their biogeography, evolution, bioluminescence mechanism, and potential ecological roles. We provide a detailed explanation of how these fungi produce light, including the role of the enzyme luciferase and luciferin. We also discussed their applications. Here, we presented an updated list of 122 bioluminescent fungi identified from five distinct evolutionary lineages viz. Armillaria, Eoscyphella, Lucentipes, Mycenoid, and Omphalotus worldwide, mainly in tropical and subtropical areas. The bioluminescent fungi descended from the last common ancestor of the mycenoid and the marasmioid clades of Agaricales, which have been maintained for at least 160 million years of evolution. We highlighted the need for further research to understand the ecological role of bioluminescent fungi. Applying bioluminescent fungi in various areas (e.g., environmental and medicinal) demonstrates their validity.

Quinacridone (QA) and 2,9-dimethylquinacridone (DQA) are synthetic substances suitable as a hard, abrasion-resistant, self-organizing gliding layer on ice, snow, and water. For sustainable use, a large number of parameters must be considered to demonstrate that these non-biogenic substances and their by-products and degradation products are harmless to humans and the environment in the quantities released. For this task, available experimental data are used and supplemented for all tautomers by numerous relevant physical, chemical, toxicological and ecotoxicological estimated values based on various Quantitative Structure Activity Relationship (QSAR) methods. On the one hand, the low solubility of QA and DQA leads to stable gliding layers and thus low abrasion and uptake by plants, animals, and humans. On the other hand, the four hydrogen bond forming functional groups per molecule allow nanoparticle decomposition and enzymatic degradation in natural environments. All available data justify a sustainable use of QA and DQA as a gliding layer. The assessment of the toxicological properties is complemented with an investigation of the size and morphology of DQA particles as well as field tests indicating an excellent performance as a gliding layer on snow.

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.

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.

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.

We develop an action principle for producing a single fluid, two-constituent system with dissipation in general relativity. The two constituents in the model are particles and entropy. The particle flux creation rate is taken to be zero, while the entropy creation rate is non-zero. Building on previous work, it is demonstrated that a new term (the proper time derivative of the matter space ``metric'') is required in the Lagrangian in order to produce terms typically associated with bulk and shear viscosity. Equations of motion, entropy creation rate, and energy-momentum-stress tensor are derived. Using an Onsager approach of identifying thermodynamic ``forces'' and ``fluxes'' a model is produced which delivers the same entropy creation rate as the standard, relativistic Navier-Stokes equations. This result is then contrasted with a model generated in the spirit of the action principle, which takes as its starting point a specific Lagrangian and then produces the equations of motion, entropy creation rate, and energy-momentum-stress tensor. Unlike the equations derived from Onsager reasoning, where the analogs of the bulk and shear viscosity coefficients are prescribed ``externally'', we find that the form of the coefficients in the second example are a direct result of the specified Lagrangian. Furthermore, the coefficients are shown to satisfy evolution equations along the fluid worldline; also a product of the specific Lagrangian.

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.

Plant activators have emerged as promising alternatives to conventional pesticides for crop disease manage-ment due to their unique mode of action. By priming the plant's innate immune system, these compounds can induce systemic acquired resistance against a broad spectrum of pathogens without directly inhibiting their proliferation. Key advantages of plant activators include prolonged defense activity, lower effective dosages, and negligible risk of developing pathogen resistance. Among the various defensive pathways tar-geted, the salicylic acid (SA) signaling cascade has been extensively explored, leading to the successful devel-opment of commercial activators like benzothiadiazole for widespread application in crop protection. While the action sites of many SA-targeting activators have been preliminarily mapped to different steps along the pathway, a comprehensive understanding of their precise mechanisms remains elusive. This review provides a historical perspective on plant activator development and outlines diverse screening strategies employed across multiple levels, from whole-plant bioassays to molecular and transgenic approaches. We expound on the intricate components, biological relevance, and regulatory circuits governing the SA pathway, while criti-cally examining the structural features, bioactivities, and proposed modes of action of classical activators such as benzothiadiazole derivatives, salicylic acid analogs, and other small molecules. Insights from field trials as-sessing their practical applicability are also discussed. Furthermore, we highlight the current status, challenges, and future prospects in the realm of SA-targeting activator development globally, with a focus on recent en-deavors in China. Collectively, this comprehensive review aims to synthesize existing knowledge and provide a roadmap for future research toward developing more potent and mechanistically understood plant activa-tors that fortify crop immunity against disease.

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.

Depressions containing partially molten rocks were investigated in Quaternary pebbly sedi-ments in Alpine foreland in Bavaria, Germany. Ruins of limekilns from 18-19th centuries are abundant around Seeshaupt. They are usually associated with earthworks for fuel feeding and protection from wind. Depressions contain partially molten stones from furnace walls, with lime and burnt loam remnants. On the surface of pebbles (typically gneisses), green glass formed with chemical composition possibly affected by moderately volatile components of wood biomass, mainly K and Cu. Thermoplastic deformation of pebbles is limited and the sur-face melt deformation points to slow flow. At Emmerting, on the other hand, two walled circu-lar depressions which lack additional earthworks have been identified as possible impact cra-ters. Thermally affected pebbles show much more intense deformation. Colorless to greenish glass, also K and Cu enriched, usually forms only thin surface coatings, in places covered by younger melt extruded from pebble interior. Burnt loam is missing. At Grabenstätt-Kaltenbach, a depression of unclear origin was investigated. Morphologically, it matches craters rather than limekilns, but anthropogenic contamination (brick-like material) is probable. The rare molten samples do not display extreme deformation features. The thermally affected stones, mainly those from Emmerting, have elevated magnetic susceptibility.

To enhance the applicability of dual-phase high-entropy alloys (HEAs) like Fe32Cr33Ni29Al3Ti3, fabricated via selective laser melting (SLM), a focus on improving their mechanical properties is essential. As part of this effort, heat treatment was explored. This study compares the microstructure and mechanical properties of the as-printed sample with those cooled in water after undergoing heat treatment at temperatures ranging from 1000 to 1200 ℃ for 1 hour. Both pre- and post-treatment samples reveal a dual-phase microstructure comprising FCC and BCC phases. Although heat treatment led to a reduction in tensile and yield strength, it significantly increased ductility compared to the as-printed sample. This strength-ductility trade-off is related to changes in grain sizes with ultrafine grains enhancing strength and micron grains optimizing ductility, also the influence of the content of FCC/BCC phases and dislocation density. In particular, the sample heat-treated at 1000 °C for 1 hour and then water-cooled exhibited a better combination of strength and ductility, a yield strength of 790 MPa, and an elongation of 13%. This research offers innovative perspectives on crafting dual-phase HEA of Fe32Cr33Ni29Al3Ti3, allowing for tailorable microstructure and mechanical properties through a synergistic approach involving SLM and heat treatment.

Induction heating is a fast, reproducible, and efficient heating method used in various manufacturing processes. However, there is no established additive manufacturing (AM) process based on induction heating using wire as feedstock. This study investigates a novel approach to AM based on inductive heating, where a steel wire is melted and droplets are detached periodically using a two-winding induction coil. The process parameters and energy input into the droplets are characterized. The induction generator exhibits sluggish response to the excitation voltage, resulting in a lag in the coil current. The process is captured using a high-speed camera, revealing regular droplet formation and uniform size and shape when operated within an appropriate process window. Larger drops and increased spatter formation occur outside this window. The proposed method allows for the production of droplets with almost spherical shapes. Further analysis and characterization of droplet formation and energy input provide insights into process optimization and overall efficiency.

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

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.

Antibacterial bone cements (ABCs), such as antibiotic-loaded bone cements (ALBCs), have been widely utilized in clinical treatments. Currently, bone cements loaded with vancomycin, gentamicin, tobramycin, or clindamycin are approved by the US Food and Drug Administration. However, traditional ALBCs exhibit drawbacks like burst release and bacterial resistance. Therefore, there is a demand for the development of antibacterial bone cements containing novel agents. In this review, we summarize the latest advancements in ABCs. More importantly, we provide an overview and outlook on novel antibacterial agent-loaded bone cements, including metallic antibacterial agents, pH-switchable antibacterial agents, cationic polymers, N-halamines, non-leaching acrylic monomers, antimicrobial peptides, etc. Offering novel perspectives for designing ABCs and treating bone infections.

Abstract: Lipidic carriers employed for the entrapment, encapsulation and precise targeting the bioactive compounds offer significant advantages to the biomedical, pharmaceutical, nutraceutical and cosmeceutical industries. These lipid and phospholipid-based vesicles can improve the solubility, permeation, pharmacokinetics, pharmacodynamics and bioavailability of the encapsulated material. As a matter of fact, nano-sized phospholipid vesicles have attained the highest success rate in commercialization among the available drug encapsulation technologies. Nevertheless, developing industrially acceptable products still remains a challenge. Among the main disadvantages of conventional lipidic carriers are their instability in the biological environments, and their sensitivity to changes in the pH, temperature and enzymes. To overcome these problems, the new generation of phospho/lipid-based carrier systems was developed using ingredients from microorganisms living in extremely harsh environments (i.e., archeaeobacteria). The present entry aims to review unique features of archaeolipids and recent developments in their application for the encapsulation of genetic material as well as their role and function as adjuvants and vaccine candidates.

This paper explores the transformative impact of computational pharmaceutics, integrating AI, multi-scale modeling, quantum computing, AI-driven drug discovery, and blockchain frameworks. Molecular dynamics simulations provide insights into atomic behaviors crucial for drug design. Quantum computing reduces computational costs for simulating protein-drug interactions. AI and Graph Neural Networks accelerate drug discovery and personalized medicine. Blockchain frameworks facilitate secure pharmacogenetic data sharing. These advancements revolutionize drug development, offering unprecedented efficiency, innovation, and personalized treatments.

The separation of sister chromatids during anaphase is the culmination of mitosis and one of the most strikingly beautiful examples of cellular movement. It consists of two distinct processes: Anaphase A, the movement of chromosomes toward spindle poles via shortening of the connecting fibers, and anaphase B, separation of the two poles from one another via spindle elongation. I focus here on anaphase A chromosome-to-pole movement. The chapter begins by summarizing classical observations of chromosome movements, which support the current understanding of anaphase mechanisms. Live cell fluorescence microscopy studies showed that poleward chromosome movement is associated with disassembly, or ‘melting’ of the kinetochore-attached microtubule fibers that link chromosomes to poles. Microtubule-marking techniques established that kinetochore-fiber disassembly often occurs through a ‘pac-man’ mechanism, where tubulin subunits are lost from kinetochore-attached plus ends and the kinetochore appears to consume its microtubule track as it moves poleward. In addition, kinetochore-fiber disassembly in many cells occurs partly through ‘flux’, where the microtubules flow continuously toward the poles and tubulin subunits are lost from minus ends. Molecular mechanistic models for how load-bearing attachments are maintained to disassembling microtubule ends, and how the forces are generated to drive pac-man and flux-based movements, are discussed.

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.

Fingerprint recognition systems have achieved widespread integration into various technological devices, including cell phones, computers, door locks, and time attendance machines. Nevertheless, individuals with worn fingerprints encounter challenges when attempting to unlock original fingerprint systems, resulting in disruptions to their daily activities. This study explores two distinct methods for fingerprint backup: traditional fingerprint impression and 3D printing technologies. Unlocking tests were conducted on commonly available optical fingerprint lock-equipped cell phones to assess the efficacy of these methods, particularly in unlocking worn fingerprints. The research findings indicated that traditional fingerprint impression method exhibited high fidelity in reproducing fingerprint patterns, achieving an impressive unlocking success rate of 97.8% for imprinting unworn fingerprints. However, when dealing with worn fingerprints, traditional fingerprint impression technique showed a reduced unlocking success rate, progressively decreasing with increasing degrees of finger wear. In contrast, 3D printed backup fingerprints, with image processing and optimization of ridge height, mitigated the impact of fingerprint wear on unlocking capability, resulting in an unlocking success rate of 84.4% or higher. Thus, the utilization of 3D printing technology proves advantageous for individuals with severely worn or incomplete fingerprints, providing a viable solution for unforeseen circumstances.

Sea level rise due to global warming is a continuing and, disappointingly, accelerating process, which has already affected and will further impact coastal lowlands and the social and economic activities in these areas. Delos Island, situated in the middle of the Cyclades in the Aegean Sea, was considered the most sacred of all islands in ancient Greek culture and a trading hub for the entire eastern Mediterranean. Uninhabited since the 7th century AD, and consistently the focus of research and touristic attention, the island is designated as an archaeological site and inscribed on the Unesco World Heritage List. Previous studies on the relative sea level (rsl) changes suggest a steadily rsl rise during the last 6,300 years, starting from a sea level at -4.80±0.20m in the Late Neolithic. The seafront of the ancient city of Delos is subject to the effects of the rsl rise, which have caused significant coastline retreat and exposure to the northerly winds and waves, whereas parts of the coastal lowland where the remains of the ancient city lie are inundated, forming extended wetlands. The future impacts of rsl rise on the seafront of ancient Delos are illustrated on very high-resolution digital surface models, evaluating both the flooding risk under different climatic projections, as provided by the IPCC AR6 report, and the ongoing land subsidence, as recorded by GNSS data. An rsl rise ranging from 87cm (SSP1-2.6 scenario) to 148cm (SSP5-8.5 scenario) is anticipated by 2150, requiring both resilience strategies and adaptation solutions as well as mitigation policies to cope with the effects of climate change.

The interconnection between the objectives of territorial development and the agro-ecological transition highlights the value of past knowledge in the sustainable management of resources and agro-ecological systems. However, retrospection in rural areas presents difficulties due to a lack of data. This paper contributes to the search for such knowledge from the past by developing an interactive methodology capable of combining heterogeneous sources of information and the activation of local collective memory. Its effectiveness is based on ensuring the interoperability of information and communication in an environment simultaneously shaped by geoinformatics and 3D geo-visualizations. This virtual environment fosters participation and interactivity, supported by representations of the paleo-landscape. Furthermore, synergies were achieved between information sources and their integration into local spatial systems. The application example involved identifying a rice field that existed from the 15th to the 19th century in Thessaly, Greece. It is an interesting case because the location and organization of cultivation in combination with its spatio-temporal coordination ensures the sustainable use of natural resources. It appears that the interplay between information and communication facilitates community participation and the activation of its collective memory as a source of information that enriches the search and local intelligence.

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.

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.

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.

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

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

The 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.

Residual stress (RS) is the most challenging problem in metal additive manufacturing (AM) since the build-up of high tensile RS may influence the fatigue life, corrosion resistance, crack initiation, and failure of the additively manufactured components. While tensile RS is inherent in all the AM processes, fast and accurate prediction of stress state within the part is extremely valuable and would result in optimization of the process parameters in achieving a desired RS and control of the build process. This paper proposes a physics-based analytical model to rapidly and accurately predict the RS within the additively manufactured part. In this model, a transient moving point heat source (HS) is utilized to determine the temperature field. Due to the high temperature gradient within the proximity of the melt pool area, material experience high thermal stress. Thermal stress is calculated by combining three sources of stresses known as stresses due to the body forces, normal tension, and hydrostatic stress in a homogeneous semi-infinite medium. The thermal stress determines the RS state within the part. Consequently, by taking the thermal stress history as an input, both the in-plane and out of plane RS distributions are found from incremental plasticity and kinematic hardening behavior of the metal by considering volume conservation in plastic deformation in coupling with the equilibrium and compatibility conditions. In this modeling, material properties are temperature-sensitive since the steep temperature gradient varies the properties significantly. Moreover, the energy needed for the solid-state phase transition is reflected by modifying the specific heat employing the latent heat of fusion. Furthermore, the multi-layer and multi-scan aspects of metal AM are considered by including the temperature history from previous layers and scans. Results from the analytical RS model presented excellent agreement with XRD measurements employed to determine the RS in the Ti-6Al-4V specimens.

This manuscript reviews three case studies from Brazil, Panama, and Portugal that illustrate Nature-based Solutions. The Tijuca Forest in Rio de Janeiro is a remarkable story of centuries of forest management that today is recognized as a UNESCO World Heritage Site. The Panama Canal Watershed produces water for Canal operations, electricity generation, and drinking water for half the country´s population. Traditional windmills and weirs near streams in the Alentejo Region, Portugal, have largely been abandoned due to the damming of the Guadiana River. Yet today, weirs are increasingly recognized for their important contribution to water provisioning in this dry region. All have a primary goal related to water provisioning, yet their ecosystem benefits are multiple. The cases offer important lessons for adaptation to climate change, cultural benefits from traditional human activities, and concerns about social equity.

Along with density and mass variations of the oceans driven by global warming, Glacial Isostatic Adjustment (GIA) in response to the last deglaciation still contributes significantly to present-day sea-level change. Indeed, in order to reveal the impacts of climate change, long term observations at tide gauges and recent absolute altimetry data need to be decontaminated from the effects of GIA. This is now realized by means of global models constrained by the observed evolution of the paleo-shorelines since the Last Glacial Maximum, which account for the complex interactions between the solid Earth, the cryosphere and the oceans. In the recent literature, past and present-day effects of GIA are often expressed in terms of fingerprints describing the spatial variations of several geodetic quantities like crustal deformation, the harmonic components of the Earth's gravity field, relative and absolute sea level. However, since it is driven by the sluggish readjustment occurring within the viscous mantle, GIA shall taint the pattern of sea-level variability also during the forthcoming centuries. The shapes of the GIA fingerprints reflect inextricable deformational, gravitational, and rotational interactions occurring within the Earth system. Using up-to-date numerical modeling tools, our purpose is to revisit and to explore some of the physical and geometrical features of the fingerprints, their symmetries and intercorrelations, also illustrating how they stem from the fundamental equation that governs GIA, i.e., the Sea Level Equation.

In this study, AlSi12 alloy was fabricated using the selective laser melting (SLM) technique to produce high density components with complex and customized parts for railway applications. Nonetheless, the production of dense samples necessitates the optimization of production process parameters. As a statistical design of experimental technique, the response surface methodology was used to optimise different combination of SLM parameters. The results were analysed using analyse of variance (ANOVA) and the signal-to-noise(S/N) ratios. The relationship between the hardness response to the process parameters (scanning speed and lase power) for determining the optimal processing conditions were examined. A hardness value of 133 HV was obtained. The process parameters were successfully optimized and the relationship between the parameters and the structures of the fabricated samples were reported.

Few studies have paid attention to the industrial lands along the Chinese Grand Canal from a cultural per-spective, but cities along the route like Hangzhou have relied on the Canal system to promote industrializa-tion over the past hundred years, and relocated, transformed, or demolished the factories to construct cul-tural space or products mostly after industrial recession at the beginning of 21st century. To deeply analyze this process is quite helpful to understand the typical cultural change and its gain and loss along the Canal especially after cultural and creative industries have been established as the pillar industries of China's na-tional economy. Therefore, along the Hangzhou section of the Canal, we dynamically monitored the land use of the selected 10 industrial lands, with the analysis of high-resolution satellite imageries and the in-dustrial past, the areas of different uses in 2022 were compared. Meanwhile, along with archival data, fieldwork, and experts’ consultation, we designed a mark sheet with factors and scores to comprehensively assess cultural changes over those lands, and its reasons and influence also have been argued, and the prob-lems and suggestions have been offered. This study can contribute to a better understanding of public poli-cy choices in China regarding cities along the Grand Canal after the industrial decline, and provide new perspectives for cultural research, heritage conservation, and urban planning of canals or waterfront spaces.

G-protein-coupled receptors (GPCR) belong to a large family of molecules eliciting different responses to a variety of signaling molecules. These receptors participate in various physiologic pathways such as metabolism, growth, immune responses, inflammation, vision, taste, olfaction, neurotransmission and even and pathologic responses including chronic inflammatory and vascular diseases. Receptors contributing to the biological responses of renin-angiotensin system (RAS) are members of GPCR family. COVID-19-induced inflammatory cascade has been attributed to acute ACE2 downregulation and imbalance of proinflammatory ACE/AngII/AT1R and anti-inflammatory ACE2/angiotensin (1-7)/Mas axes in favor of the former. Some of the receptors contributing to activities of proteins in RAS including AT1R, AT2R and Mas receptors are members of GPCR family. It is notable that these receptors induce their effects both through G protein and β-arrestin pathway; the former exerts temporary and the latter more sustained effects. In addition to the imbalance of GPCR responses contributing to RAS activities, it has been suggested that SARS-CoV2 pathogenesis might be attributed to the activation of GPCRs or modulating G-proteins involved in adenosine-CFTR regulation system and epithelial Na channel function.This article includes a minireview about the physiological functions of GPCRs and their contribution to COVID-19.

Social support in working with beggars and vagrants has always been and still is a challenge for all social protection systems. This paper aims to analyze the social work system in working with vagrants and beggars, starting with the presentation of the concept and seeking to evaluate the evolution of this particular sector of the social protection system in Romania, presenting, on one hand, the legislative changes and, also, the situation found in reality which could be (slightly) different. In the paper we describe two research models, a case study, which starts from the situation found in Romania and is based on the model of good practice (social enterprises) developed by Nicolae Minovici in the interwar period (1934) and also presents the opinion of citizens from Craiova city, investigated during a sociological survey conducted in 2021-2022 on a sample of 1494 persons, on the opportunity to set up such centers for beggars and vagrants in Romania. The article seeks to extract the good practices used by the national system for the purpose of comparing and issuing proposals to regulate and improve the current situation in Romania.

Botanical living collections within botanical gardens represent a crucial global asset for plant diversity. Particular emphasis should be given to dendrological collections, considering their key role in contribution to biodiversity conservation, support scientific inquiry, enhance educational initiatives and support on involvement of the public. The introduction of plants, especially woody plants, is one of the important problems in botanical science, solved in botanical gardens and arboretums. Establishment and development of the Dendrological collections in Botanical gardens is a way to have a comprehensive representation of diverse plant species from different biogeographical regions and continents. Current paper first time presents establishment, development, current status and future perspective of dendrological collections of Yerevan Botanical Garden in the linkage to introduction of woody plants in Armenia.

With the development of industrialization, traditional manufacturing technologies are no longer able to meet the production needs of modern society. Additive manufacturing has successfully solved the problems existing in traditional manufacturing technology. Selective laser melting (SLM) is a powder bed melting technology that produces metal parts by selectively melting metal powders on a platform using a laser beam. It is widely used in additive manufacturing. This article introduces the characteristics and current development status of SLM technology, summarizes the main application fields and common defects of SLM, and finally explores and prospects the future development trend of SLM.

The utilization of selective laser melting (SLM) for high entropy alloys (HEAs) holds significant promise in commercial applications, and substantial experimental research efforts have been directed toward this domain. To take advantage of the reported experimental data of SLM manufactured (SLM-ed) HEAs and reduce unnecessary experimentation, this study incorporates machine learning (ML) techniques for the phase and tensile properties prediction of SLM-ed HEAs, thus presenting a novel avenue for accelerating the discovery of new SLM-ed HEAs. Through the adjustment of material descriptors and machine learning models, a model has been developed with an impressive accuracy of 93.8% in distinguishing between face-centered cubic (FCC), body-centered cubic (BCC), and dual-phase (FCC+BCC). Additionally, optimized models have been devised for the prediction of tensile properties, namely ultimate tensile strength (UTS), yield strength (YS), and elongation (δ), achieving noteworthy MAPEs (mean absolute percentage errors) of 10.33%, 8.55%, and 28.48%, respectively. Furthermore, several HEAs were fabricated using SLM, and the experimental outcomes exhibited a favorable alignment with the predicted results. These efforts carry significant implications in advancing the utilization of SLM for HEAs.

Habit theory suggests that behavior performed in the presence of consistent cues is a core ingredient for successful habit development, with the repeated presence of these consistent cues facilitating the activation of automatic responses in future. We tested this assumption in a sample of 68 undergraduate students who, at baseline, reported on their physical activity behavior over the past year then, two weeks later, responded to measures of cue consistency, habit, and physical activity performance over the previous two weeks. As expected, habit mediated the effects of past behavior on prospectively measured behavior. Moreover, the mediating effect of habit between past and future behavior was significantly stronger in those reporting undertaking physical activity at the same time of day, doing the same activity, and in the same mood. Consistent place, people, and part of routine did not moderate the effects of habit. Results provide formative evidence for a key assertion of habit theory, that consistent contextual and internal cues are a cornerstone of habitual development and action, but also indicate the importance of examining different forms of cues and their impact on the formation and enaction of habits as some cues over others may be more relevant.

Thousands of antibodies for diagnostic and other analytical purposes are on the market. However, it is often difficult to identify duplicates, reagent changes, and to assign the correct original publications to an antibody. This slows down scientific progress and might even be a cause of irreproducible research and a waste of resources. Recently, activities were started to suggest the sole use of recombinant antibodies in combination with the open communication of their sequence. In this case, such uncertainties should be eliminated. Unfortunately, this approach seems to be rather a long-term vision since the development and manufacturing of recombinant antibodies remain quite expensive in the foreseeable future. Also, nearly all commercial antibody suppliers may be reluctant to publish the sequence of their antibodies, since they fear counterfeiting. De-novo sequencing of antibodies is also not feasible today for a reagent user without access to the hybridoma clone. Nevertheless, it seems to be crucial for any scientist to have the opportunity to identify an antibody undoubtedly to guarantee the traceability of any research activity using antibodies from a third party as a tool. For this purpose, we developed a method for the identification of antibodies based on a MALDI-TOF-MS fingerprint. To circumvent lengthy denaturation, reduction, alkylation, and enzymatic digestion steps, the fragmentation was performed with a simple formic acid hydrolysis step. Eighty-nine unknown monoclonal antibodies were used for this study to examine the feasibility of this approach. Although the molecular assignment of peaks was rarely possible, antibodies could be easily recognized in a blinded test, simply from their mass-spectral fingerprint. A general protocol is given, which could be used without any optimization to generate fingerprints for a database. We want to propose that in most scientific projects relying critically on antibody reagents, such a fingerprint should be established to prove and document the identity of the used antibodies and to assign a specific reagent to a datasheet of a commercial supplier, a public database record or an antibody ID.

In archaea, the interaction of HerA helicase and NurA nuclease is required for 3' end resection during DNA double-stranded break repair, and its disruption results in unfaithful DNA repair. Interactions transpire by the four conserved domains, including the N-terminal HAS domain (HerA-ATP synthase), which serves as a binding site for the exonuclease NurA. As a HerA hexamer between its two subunits, the conserved C-terminal brace extension functions as an adjacent brace. DBD serves as a location for DNA binding, which causes the DNA strands to be propelled into the HerA pocket to begin unwinding. The putative pore entrance is made up of four helix coils, which provide a suitable charged surface for guiding DNA into the pore. The crystal structure of the complex HerA-NurA allows for the identification of key residues for protein-protein interaction. This allows us to predict that most archaeal HerA orthologs will be able to interact with one another. Archaeal HerA is a homo-hexameric assembly featuring a DNA-binding domain that is conserved. It also features distinctive ATP and NurA binding domains. Following the structure and sequence conservation criteria, we find one HerA ortholog in Pyrobaculum calidifontis and multiple HerA paralogs, but the role of none is established yet.Interestingly, orthologous HerA is part of an Mre11-Rad50 gene neighborhood while paralogous HerA is not, which could be misleading. As a result, it sought to describe the criteria that may be used as a possible fingerprint for identifying orthologous genes, as well as the cloning procedures and tactics that would aid in the confirmation of the HerA helicase in P. calidifontis. Their confirmation is based on PCR cloning and characterization following HerA construct creation.

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.

An improved method for Fluctuation Enhanced Sensing (FES) is introduced. We enhanced the old binary fingerprinting method, where the fingerprint bit values were ± 1, by introducing ternary fingerprints utilizing a reference odor. In the ternary method, the fingerprint bit values are -1, 0, and +1 where the 0 value stands for the situation where the slope of the spectrum is identical to that of the reference odor. The application of the reference odor spectrum makes the fingerprint relative to the reference. This feature increases the information entropy of the fingerprints. The method is briefly illustrated by sensing bacterial odor in cow manure isolates.

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

Fossils constitute the principal repository of data that allow for independent tests of hypotheses of biological evolution derived from observations of the extant biota. Traditionally, transformational series of structure, consisting of sequences of fossils of the same lineage through time, have been employed to reconstruct and interpret morphological evolution. More recently, a move toward an updated paradigm was fueled by the deliberate integration of developmental thinking in the inclusion of fossils in reconstruction of morphological evolution. The vehicle for this is provided by structural fingerprints – recognizable morphological and anatomical structures generated by (and reflective of) the deployment of specific genes and regulatory pathways during development. Furthermore, because the regulation of plant development is both modular and hierarchical in nature, combining structural fingerprints recognized in the fossil record with our understanding of the developmental regulation of those structures produces a powerful tool for understanding plant evolution. This is particularly true when the systematic distribution of specific developmental regulatory mechanisms and modules is viewed within an evolutionary (paleo-evo-devo) framework. Here, we discuss several advances in understanding the processes and patterns of evolution, achieved by tracking structural fingerprints with their underlying regulatory modules across lineages, living and fossil: the role of polar auxin regulation in the cellular patterning of secondary xylem and the parallel evolution of arborescence in lycophytes and seed plants; the morphology and life history of early polysporangiophytes and tracheophytes; the role of modularity in the parallel evolution of leaves in euphyllophytes; leaf meristematic activity and the parallel evolution of venation patterns among euphyllophytes; mosaic deployment of regulatory modules and the diverse modes of secondary growth of euphyllophytes; modularity and hierarchy in developmental regulation and the evolution of equisetophyte reproductive morphology. More generally, inclusion of plant fossils in the evo-devo paradigm has informed discussions on the evolution of growth patterns and growth responses, sporophyte body plans and their homology, sequences of character evolution, and the evolution of reproductive systems.

Available options to combat bacterial infections are getting scarce. We require innovative and imaginative approaches to enhance the identification and discovery of effective antimicrobials capable of combating bacteria resistant to multiple or all available drugs. These methods should either directly eliminate the resistant bacteria or influence their viability indirectly by inhibiting their virulence or reducing their resistance to antibacterial agents. One interesting approach is to analyze ancient remedies presumably used to treat bacterial infections, try formulating them, and test them against modern microbes. The field was recently named ancientbiotics. This approach allows us to take advantage of centuries of accumulated empirical knowledge, from several traditional medicines of various ancient cultures across the world. The strategy has already resulted in promising formulations to combat the ESKAPE group of nosocomial pathogens. Moreover, molecular de-extinction consists of genome analysis of extinct species in the search for useful antimicrobials, such as peptides. The de-extinction of simple organisms such as bacteriophages may eventually become a resource for novel tools to combat multidrug-resistant bacteria. In this review, we summarize and discuss the reported antimicrobial effects of ancient remedies and de-extinct molecules known to modern science, and discuss possible new strategies to further harness the potential of past remedies and molecules to help us fight the rise of superbugs.

There is a rich history of cancer treatments which provides a number of important lessons for present and future cancer therapies. We outline this history by looking in the past, reviewing the current landscape of cancer treatments, and by glancing at the potential future cancer therapies.

For several millennia, doctors and healers used therapeutic ingredients extracted from minerals, plants, and animals. Among the active remedies derived from animals, the placenta was among the most popular ones. The use of placenta-based remedies has retained its significance in our time. The placenta-based therapeutics are indicated for stimulating immunity, wound healing, reduction of skin pigmentation, treatment of various patients suffering from gynecological disorders, etc. By the beginning of the 21st century, the majority of specific functions and chemical ingredients of the placenta were identified and described. However, only now active proteins and peptides with molecular weight of about ten kDa were revealed. Presumably, they play an essential role during the therapeutic application of placental extract. Hopefully, this discovery will start a new era in the research and clinical application of organotherapeutic remedies, including placenta.

This paper examines the quantitative and qualitative situation of the current fixed and mobile Internet and its expected future. First, the number of users and penetration rate of the Internet, various types of services in different countries, the ranking of countries in terms of the mean and median download and upload Internet data speeds, Internet data volume, and number and location of data centers in the world are presented. The second task introduces and details twelve performance evaluation metrics for broadband Internet access. Third, different wired and wireless Internet technologies are introduced and compared based on data rate, coverage, type of infrastructure, and their advantages and disadvantages. Based on the technical and functional criteria, in the fourth work, two popular wired and wireless Internet platforms, one based on optical fiber and the other based on the 5G cellular network, are compared in the world in general and Australia in particular. Moreover, this paper has a look at Starlink as the latest satellite Internet candidate, especially for rural and remote areas. The fifth task outlines the latest technologies and emerging broadband Internet-based services and applications in the spotlight. Sixthly, it focuses on three problems in the future Internet in the world, namely the digital divide due to the different quality of the Internet and new Internet-based services and applications of emerging technologies, the impact of the Internet on social interactions, and hacking and insecurity on the Internet. Finally, some solutions to these problems are proposed.

Cellular substructure has been widely observed in the sample fabricated by laser powder bed fusion, while its growth direction and the crystallographic orientation have seldom been studied. This research tries to build a general model to construct the substructure from its two-dimensional morphology. All the three Bunge Euler angles to specify a unique growth direction are determined, and the crystallographic orientation corresponding to the growth direction is also obtained. Based on the crystallographic orientation, the substructure in the single track of austenitic stainless steel 316L is distinguished between the cell-like dendrite and the cell. It is found that, with the increase of scanning velocity, the substructure transits from cell-like dendrite to cell. When the power is 200 W, the critical growth rate of the transition in the single track can be around 0.31 ms^-1.

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

In a recent paper [1], I argued against backward in time effects used by several authors to explain delayed choice experiments. I gave an explanation showing that there is no physical influence propagating from the present to the past and modifying the state of the system at a time previous to the measurement. However, though the solution is straightforward in the case of delayed choice experiments involving only one particle, it is subtler in the case of experiments involving two entangled particles because they give rise to EPR-like situations. Considering that a measurement is not an actual change of the physical state of a system and is relative to the observer allows to understand that there is neither backward in time effects nor instantaneous collapse of the second system when the first one is measured, as is often postulated. This allows also to get rid of any non-locality [2]. In this paper, I want to go further into the consequences of this way of considering the measurement, that I have called Convivial Solipsism, and show that even if, in the usual sense, there is no physical effect of the present or of the future on the past, we must nevertheless consider that the observer’s past is sometimes not entirely determined and that it becomes determined only when certain measurements are done latter. This apparent contradiction disappears if one understand that each observer builds, through her own measurements, her own world (that I call the phenomenal world in Convivial Solipsism) which is different from what we are used to consider as the common world shared by everybody.

Selective laser melting is an emerging Additive Manufacturing (AM) technology for metals. Intricate three-dimensional parts can be generated from the powder bed by selectively melting the desired location of the powders. The process is repeated for each layer until the part is built. The necessary heat is provided by a laser. Temperature magnitude and history during SLM directly determine the molten pool dimensions, thermal stress, residual stress, balling effect, and dimensional accuracy. Laser-matter interaction is a crucial physical phenomenon in the SLM process. In this paper, five different heat source models are introduced to predict the three-dimensional temperature field analytically. These models are known as steady state moving point heat source, transient moving point heat source, semi-elliptical moving heat source, double elliptical moving heat source, and uniform moving heat source. The analytical temperature model for all of the heat source models are solved using three-dimensional differential equation of heat conduction with different approaches. The Steady state and transient moving heat source are solved using separation of variables approach. However, the rest of models are solved by employing the Green’s functions. Due to the high magnitude of the temperature in the presence of the laser, the temperature gradient is usually high which has a substantial impact on thermal material properties. Consequently, the temperature field is predicted by considering the temperature sensitivity thermal material properties. Moreover, due to the repeated heating and cooling, the part usually undergoes several melting and solidification cycles, this physical phenomenon is considered by modifying the heat capacity using latent heat of melting. Furthermore, the multi-layer aspect of metal AM process is considered by incorporating the temperature history from the previous layer since the interaction of the layers have an impact on heat transfer mechanisms. The proposed temperature field models based on different heat source approaches are validated using experimental measurement of melt pool geometry from independent experimentations. The detailed explanation of the comparison of models is also provided. Moreover, the effect of process parameters on the balling effect is also discussed.

Face recognition is one of the most active research fields of computer vision and pattern recognition, with many practical and commercial applications including identification, access control, forensics, and human-computer interactions. However, identifying a face in a crowd raises serious questions about individual freedoms and poses ethical issues. Significant methods, algorithms, approaches, and databases have been proposed over recent years to study constrained and unconstrained face recognition. 2D approaches reached some degree of maturity and reported very high rates of recognition. This performance is achieved in controlled environments where the acquisition parameters are controlled, such as lighting, angle of view, and distance between the camera-subject. However, if the ambient conditions (e.g., lighting) or the facial appearance (e.g., pose or facial expression) change, this performance will degrade dramatically. 3D approaches were proposed as an alternative solution to the problems mentioned above. The advantage of 3D data lies in its invariance to pose and lighting conditions, which has enhanced recognition systems efficiency. 3D data, however, is somewhat sensitive to changes in facial expressions. This review presents the history of face recognition technology, the current state-of-the-art methodologies, and future directions. We specifically concentrate on the most recent databases, 2D and 3D face recognition methods. Besides, we pay particular attention to deep learning approach as it presents the actuality in this field. Open issues are examined and potential directions for research in facial recognition are proposed in order to provide the reader with a point of reference for topics that deserve consideration.

Supply chain management requires regular updates of the location of assets, which can be enabled by low power wide area networks, such as Sigfox. While it is useful to localize a device simply by its communication signals, this is very difficult to do with Sigfox because of wide area and ultra narrowband nature. On the other hand, installing a satellite localization element on the device greatly increases its power consumption. We investigated using information about nearby Wi-Fi access points as a way to localize the asset over the Sigfox network, so without connecting to those Wi-Fi networks. This paper reports the location error that can be achieved by this type of outdoor localization. By using a combination of two databases, we could localize the device on all 36 test locations with a median location error of 39 m. This shows that the localization accuracy of this method is promising enough to warrant further study, most specifically the minimal power consumption.

The article continues the search for a general law that describes the physical properties of a solid body, represented as a complex compound, through the physical properties of its elements. For a set of mixtures of metal oxides (actinide oxides), their melting or solidification temperatures were described in terms of the atomic weighted sum of the melting/solidification temperatures of these metals and molecular oxygen, multiplied by a variable which depending on the crystal structure and properties of melt of the compound and on the atomic numbers of the elements that make up the compound.

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.

Minimal access cardiac surgery appears to be the future. It is increasingly desired by cardiologists and demanded by patients who perceive superiority. Minimal access coronary artery revascularisation has been increasingly adopted throughout the world. Here we review the history of minimal access coronary revascularization and see that it is almost as old as the history of cardiac surgery. Modern minimal access coronary revascularization takes a variety of forms – namely minimal access direct coronary artery bypass grafting (MIDCAB), hybrid coronary revascularisation (HCR) and totally Endoscopic Coronary Artery Bypass Grafting (TECAB). It is noteworthy that there is significant variation in nomenclature and approaches for minimal access coronary surgery and this truly presents a challenge to comparing the different methods. However, these approaches are increasing in frequency and proponents demonstrate clear advantages for their patients. The challenge that remains, as for all areas of surgery, is demonstrating superiority of these techniques over tried and tested open techniques which is very difficult. There is a paucity of randomized controlled trials to help answer this question, and the future of minimal access coronary revascularisation to some extent is dependent on such trials. Thankfully some are underway and the results eagerly anticipated.

The recent legalization of Cannabis sativa L. in many regions has revealed a need for effective propagation and biotechnologies for the species. Micropropagation affords researchers and producers methods to rapidly propagate insect/disease/virus free clonal plants, store germplasm, and forms the basis for other biotechnologies. Despite this need, research in the area is limited due to the long history or prohibitions and restrictions. Existing literature has multiple limitation: many publications use hemp as a proxy for drug-type Cannabis when it is well established that there is significant genotype specificity, studies using drug-type cultivars are predominantly op-timized using a single cultivar, most protocols have not been replicated by independent groups, and some attempts demonstrate a lack of reproducibility across genotypes. Due to culture decline and other problems the multiplication phase of micropropagation (stage 2) has not been fully developed in many reports. This review will provide a brief background on the history and botany of Cannabis as well as a comprehensive and critical summary of Cannabis tissue culture. Special attention will be paid to current challenges faced by researchers, the limitations of existing Cannabis micropropagation studies, and recent developments and future directions of Cannabis tissue culture technologies.

Genetic testing has expanded out of the research laboratory into medical practice and the direct-to-consumer market, and rapid analysis of the resulting genotype data can now have significant impact. We present a method for summarizing personal genotypes as ‘genotype fingerprints’ that meet these needs. Genotype fingerprints can be derived from any single nucleotide polymorphism (SNP)-based assay, and remain comparable as chip designs evolve to higher marker densities. We demonstrate that they support distinguishing types of relationships among closely related individuals and closely related individuals from individuals from the same background population, as well as high-throughput identification of identical genotypes, individuals in known background populations, and de novo separation of subpopulations within a large cohort through extremely rapid comparisons. While fingerprints do not preserve anonymity, they provide a useful degree of privacy by summarizing a genotype in a way that prevents reconstruction of individual marker states. Genotype fingerprints are therefore well-suited as a format for public aggregation of genetic information to support ancestry and relatedness determination without revealing personal health risk status.

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

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.

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 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.

The treatment of peptides has played an important role in clinical practice since the discovery of insulin therapy in the 1920s. Over 60 peptide drugs are approved in the United States (US and other regional mar-kets, and peptides continue to undergo drug discovery steadily. Peptide research and development has lev-eraged a wider range of structures known from other plant sources, via pharmacology and medicinal molecular biology, beyond its conventional focus on individual endogenous peptides. We build a comprehensive database of peptides that have met scientific studies with more than 150 constantly evolving peptides. Here we provide a simple overview of the peptide-based drug therapy environment, comprising evolutionary points of view, structural properties, operational thresholds, and explanation of the therapeutic area.

Gravitational data are the only ones able to provide otherwise hidden details of what happens below the surface. In this paper, several models are implemented to constrain them with the outer structure of Mars: firstly a Bouguer inversion to reduce gravitational residual, obtaining a crustal depth in the range 23.19-94.56 km. Successively, it was considered an Airy model providing for local buoyancy. Given that its configuration does not permit to evaluate properly the different flexural responses of the lithosphere, and that it overcompensates for the crust of the highest volcanic conformations, a flexural response function was used to filter this model. It uses the lithosphere elastic thickness T_e to scale especially the short wavelengths, correcting for local phenomena. Finally, an optimization was implemented to find the best-fitting values for T_e, using both an infinite plate and a thin shell approximation, and then obtain a global map for crustal density and thickness. Even if the Martian dichotomy is basically confirmed by all the models, along with the well-known anomalies localized at the major basin craters and volcanic Paterae, the Bouguer model supplies the best representation of the state-of-the-art knowledge about the outer layers of Mars and with further improvements can represent a future benchmark for the research on the Red Planet.

Understanding the structure and properties of MgCl2/TiCl4/ID nanoclusters is a key to uncover the origin of Ziegler-Natta catalysis. In this work MgCl2/TiCl4 nanoplatelets derived by machine learning and DFT calculations have been used to model the interaction with ethyl-benzoate EB (as internal donor) with available exposed sites of binary TixCly/MgCl2 systems. The influence of vicinal Ti2Cl8 and coadsorbed TiCl4 on energetic, structural and spectroscopic behaviour of EB has been considered. The adsorption of homogeneous-like TiCl4EB and TiCl4(EB)2 at the various surface sites have been also simulated. Calculations have been carried out by employing B3LYP-D2 and M06 functionals. The adducts have been characterized by computing IR and Raman spectra that have been found to provide specific fingerprints useful to identify surface species; IR spectra have been successfully compared to available experimental data.

Temperature field is an essential attribute of metal additive manufacturing in view of its bearings on the prediction, control, and optimization of residual stress, part distortion, fatigue, balling effect, etc. This work provides an analytical physics-based approach to investigate the effect of scan strategy parameters including time delay between two irradiations and hatching space on thermal material properties and melt pool geometry. This approach is performed through the analysis of the distribution of material properties and temperature profile in three-dimensional space. The moving point heat source approach is used to predict the temperature field. To predict the temperature field during the additive manufacturing process some important phenomena are considered. 1) Due to the high magnitude of temperature in the presence of the laser, the temperature gradient is usually high which has a crucial influence on thermal material properties. Consequently, the thermal material properties of stainless steel grade 316L are considered to be temperature-dependent. 2) Due to the repeated heating and cooling, part usually undergoes several melting and solidification cycles. This physical phenomenon is considered by modifying the heat capacity using the latent heat of melting. 3) The multi-layer aspect of metal AM process is considered by incorporating the temperature history from the previous layer since the interaction of the successive layers has an impact on heat transfer mechanisms. 4) Effect of heat affected zone on thermal material properties is considered by the superposition of material properties in regions where the temperature fields of two consecutive irradiations have an overlap since the consecutive irradiations change the behavior of the material properties. The goals are to 1) investigate the effects of temperature-sensitive material properties and constant material properties on the temperature field. 2) Study the behavior of thermal material properties under different scan strategies. 3) Study the importance of considering the effect of heat affected zone on thermal material through the prediction of melt pool geometry. 4) Investigate the effect of hatching space on melt pool geometry. This work is purely employed physics-based analytical models to predict the behavior of material properties and temperature field under different process conditions, and no finite element modeling is used.

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

A 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.

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.

Vit-106 is a promising zirconium-based alloy with high glass-forming ability and belongs to the so-called bulk metallic glasses (BMG). Workpieces with a size of around one centimeter in all three dimensions can be obtained from a BMG alloy by casting. However, further increasing the cast size decreases the cooling rate and thus induces crystallization. Selective laser melting (SLM) is a well-known technique to overcome the size limitations for BMGs because a workpiece is built by the addition of multiple melt portions where the cooling rate is kept above the critical one. Currently, BMG parts obtained by SLM suffer from partial crystallization. The present work studies the influence of SLM process parameters on partial crystallization of Vit-106 by metallography and the influence of the microstructure on mechanical properties by microhardness and wear resistance testing. Submicron crystalline inclusions are observed in an amorphous matrix of Vit-106 alloy obtained by SLM. The size and the concentration of the inclusions can be controlled by varying the laser scanning speed. It is shown that submicron crystalline inclusions formed in the amorphous matrix during SLM can favorably affect microhardness and wear resistance.

The energy transfer process of laser selective melting is very complex. To study the effect of la-ser selective melting on the microstructure and properties of 18Ni-300 martensitic steel, ABAQUS was used to simulate the temperature of laser cladding 18Ni-300 martensitic steel at different time points and different laser power. The results show that the cross-section shape of the molten pool changes from round to oval With the increase of laser power, the higher the peak value of temperature time curve, the greater the temperature gradient; and the laser clad-ding experiment of 18Ni-300 martensitic steel was carried out, and the microstructure and me-chanical properties of the samples under different laser power were analyzed. The results show that with the increase of laser power, the grain size of the cladding layer becomes smaller and the microstructure becomes more compact; the hardness of the side surface of the sample is higher than that of the upper surface, and the tensile strength and elongation show a trend of first increasing and then decreasing.

Although the concept of additive manufacturing has been proposed for several decades, momentum of selective laser melting (SLM) is finally starting to build. In SLM, density and surface roughness, as the important quality indexes of SLMed parts, are dependent on the processing parameters. However, there are few studies on their collaborative optimization in SLM to obtain high relative density and low surface roughness simultaneously in the previous literature. In this work, the response surface method was adopted to study the influences of different processing parameters (laser power, scanning speed and hatch space) on density and surface roughness of 316L stainless steel parts fabricated by SLM. The statistical relationship model between processing parameters and manufacturing quality is established. A multi-objective collaborative optimization strategy considering both density and surface roughness is proposed. The experimental results show that the main effects of processing parameters on the density and surface roughness are similar. It is noted that the effects of the laser power and scanning speed on the above objective quality show highly significant, while hatch space behaves an insignificant impact. Based on the above optimization, 316L stainless steel parts with excellent surface roughness and relative density can be obtained by SLM with optimized processing parameters.

Nowadays, the combination of fingerprinting methodology with friendly environmental and economical analytical instrumentation are becoming increasingly relevant in the food sector. In this study, a highly versatile portable analyser based on Spatially Offset Raman Spectroscopy (SORS) to obtain the edible vegetable oils (sunflower and olive oils) fingerprints was used to evaluate the capability of such fingerprints, obtained quickly, reliable and without any sample treatment, to discriminate/classify the analysed samples. After data treatment, not only HCA and PCA as unsupervised pattern recognition techniques but also SVM, kNN and SIMCA as supervised pattern recognition techniques, showed that the main effect over the discrimination/classification was associated to those regions of RAMAN fingerprint related to the free fatty acids content, especially oleic and linoleic acid. These facts allowed the discrimination attending to the original raw material used in the oil's elaboration. In all the model established, reliable qualimetric parameters were obtained.

When the skin is afflicted by disease such as cancer, these essential functions are disrupted, putting the entire person at risk. While the American Cancer Society lists 6 major cancer types, the National Institute of Arthritis and Musculoskeletal and Skin Diseases identifies 13 significant benign skin disorders, reflecting the diversity of skin conditions in dermatology. This topical review aims to provide an overview of the pathophysiology of these major skin cancers and disorders and summarize conventional diagnostic methods and current treatment approaches.

Wheat dwarf disease (WDD) is an important disease of monocotyledonous species, including economically important cereals. The causative pathogen, the wheat dwarf virus (WDV), is a monopartite Mastrevirus that has a circular single-stranded (ss)DNA genome and is transmitted persistently and propagatively mainly by the leafhopper Psammotettix alienus. The disease can induce high yield losses in many European countries in a range of 20-100%. Due to climate change the periods of vector activity increased and the vectors spread to new habitats, leading to an increased importance of WDV in large parts of Europe. In the light of integrated pest management approaches cultivation practices and the use of resistant/tolerant host plants are currently the only effective methods for controlling WDV. To date, there is limited knowledge of the pathosystem and epidemiology of the disease. The few sources of genetic tolerance, indicate the need for further research. Considering the economic importance of the disease, and its likely increasing relevance in the coming decades, this review was prepared to compile and update knowledge on aspects of WDV.

There have been several developments in the field of nanopore biosensor development and sequencing applications that address previous limitations that restricted widespread nanopore use. These innovations, paired with the large-scale commercialization of biological nanopore sequencing by Oxford Nanopore Technologies, are making these platforms a mainstay in contemporary research labs. Equipped with the ability to provide long and short-read sequencing information with quick turn-around times and simple sample preparation, nanopore sequencers are quickly improving our understanding of unsolved genetic, transcriptomic, and epigenetic problems. However, there remain some key obstacles that have yet to be improved. In this review, we provide a general introduction to nanopore sequencing principles, discussing biological and solid-state nanopore developments, obstacles to single-base detection, and library preparation considerations. We conclude with examples of important clinical applications to give perspective on the potential future of nanopore sequencing in the field of molecular diagnostics.

This paper presents a review of the electrical heating method for heavy oil recovery based on past, current, and future prospects of electrical heating. Heavy oil is one of the potential crude oil used as a link to reduce the crisis of light oil used today. The obstacle of heavy oil is a high viscosity and density in which thermal injection is a method for heavy oil recovery, but it results in economic and environmental issues. Electrical heating is one of the thermal methods by transferring heat into the reservoir. The basic process of electrical heating is to increase the mobility of the oil. Because the temperature rises, it can reduce oil viscosity and makes it easier for heavy oil to flow. The past and current developments have been carried out to fill up the gap of electrical heating projects. The future prospects must meet energy efficiency, and the excessive heat will damage formation that must be tackled in the future prospect. the works adopt several electrical heating projects and applications in the world where the works give a brief future prospect of electrical heating.

The high entropy alloy (HEA) of equiatomic composition CrNiFeCoMn and with FCC crystal structure was additively manufactured with a selective laser melting (SLM) process starting from mechanically alloyed powders. The as produced alloy shows finenitride and  phase pre-cipitates, which are Cr-rich and stable up to about 900 K. The precipitates increase in number and dimensions after long-period annealing at 900-1300 K, with a change in the HEA mechanical properties. Higher aging temperatures in furnace, above 1300 K, turn the alloy in a single FCC structure, with disappearance of the nitrate and  phase precipitates inside the grains and at the grain boundaries, but with still a presence of a finer Cr-rich nitride precipitation phase. These re-sults suggest that the as-produced HEA is a supersatured solid solution at low and intermediate temperature with nitrides and  nanostructures.

This study characterizes the microstructure and its associated crystallographic features of bulk maraging steels fabricated by selective laser melting (SLM) combined with a powder bed technique. The fabricated sample exhibited characteristic melt pools in which the regions had locally melted and rapidly solidified. A major part of these melt pools corresponded with the ferrite (alpha) matrix, which exhibited a lath martensite structure with a high density of dislocations. A number of fine retained austenite (gamma) with a <001> orientation along the build direction was often localized around the melt pool boundaries. The orientation relationship of these fine gamma grains with respect to the adjacent alpha grains in the martensite structure was (111) gamma // (011) alpha and [-101] gamma // [-1-11] apha (Kurdjumov–Sachs orientation relationship). Using the obtained results, we inferred the microstructure development of maraging steels during the SLM process. The results depict that new and diverse high-strength materials can be used to develop industrial molds and dies.

The increasing prevalence of depression worldwide requires more effectiveness in therapy approaches and a molecular understanding of antidepressants mode of action. We carried out untargeted metabolomics of the prefrontal cortex of rats exposed to chronic social isolation (CSIS), a rat model of depression, and/or fluoxetine treatment using liquid chromatography-high resolution mass spectrometry. The behavioral phenotype was assessed by the forced swim test. To analyze metabolomics data, univariate and multivariate analysis and biomarker capacity assessment using the classical receiver operating characteristic (ROC) curve were used. Support vector machine-linear kernel (SVM-LK), as a machine-learning algorithm was performed for binary classification. Upregulated myo-inositol following CSIS may represent a potential marker of depressive phenotype. Effective fluoxetine treatment reversed depressive-like behavior and increased sedoheptulose 7-phosphate, hypotaurine, and acetyl-L-carnitine contents, which were identified as potential markers. We identified 4 or 10 marker candidates with ROC curve greater than 0.9 for CSIS or fluoxetine effectiveness designation. SVM-LK has given accuracy of 61.50%, or 93.30%, and 7 or 25 predictive metabolites for CSIS vs. control and fluoxetine-treated CSIS vs. CSIS classification. Overall, metabolic fingerprints combined with ROC curve and SVM-LK may represent a new approach to identifying potential markers or predicting metabolites for group designation or classification.

We have much to learn from historic buildings. The fact that they are still standing is obvious, but unfortunately often not appreciated. In this paper the results obtained from a series of parametric analyses, where the influence that geometric and mechanical parameters have in the structural response of existing cob walls within an Irish context, are presented. A design of experiments using central composite designs was implemented along with analysis of variance following two computational approaches, namely, finite element method and kinematic limit analysis. As results, a series of response surfaces and parametric equations with which it is possible to compute safety factors and collapse multipliers (within the range of values studied) are provided. Based on the results obtained, it could be concluded that traditional cob walls in Ireland are very robust. Relatively high acceleration values, unlikely to happen in a low seismic hazard region such as Ireland, would be needed to start the collapse mechanisms studied or cause yielding in typical vernacular cob walls. Furthermore, the equations generated with the refined regression models, can be used by practitioners as a first approach to estimate the safety levels of existing cob buildings with similar characteristics.

Based on the prosed criterion of the type of heating, a classification of the sources of pulsed electron beams was carried out, for better understanding both the nature of the thermal processes occurring under irradiation and for predicting their suitability for certain applications. The melting thresholds of materials were calculated over the wide ranges of accelerating voltages and pulse durations. On the basis of calculations, a refractoriness series of metals for surface-volume pulsed heating was proposed.

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.

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.

There is a fast-growing interest in the use of selective laser melting (SLM) for metal/alloy additive manufacturing. Our current knowledge of SLM printed 316 stainless steel (SS316) is limited and sometimes appears sporadic, presumably due to the complex interdependent effects of a large number of process variables of the SLM processing. This is reflected from the discrepant findings in the crystallographic textures and microstructures in this investigation with those reported in the literatures, which also vary itself. The as-printed material is macroscopically asymmetric in both the structures and crystallographic textures. The <101> and <111> crystallographic directions align parallel with the SLM scanning direction (SD) and build direction (BD), respectively. Like-wise, some characteristic low angle boundary features are reported crystallographic, while this investigation unequivocally proves them non-crystallographic since they always maintain an identical alignment with the SLM laser scanning direction irrespective of the matrix material’s crystal orientation. There is also 500±200 nm columnar or cellular features, depending on the cross-section, generally found all over the sample. These columnar or cellular features are formed with walls made of dense packing of dislocations entangled with Mn, Si and O enriched amorphous inclusions. They remain stable after the ASM solution treatments at 1050 °C temperatures, and therefore, are capable of hindering boundary migration events of recrystallization and grain growth. Thus, the nanoscale structures can be retained at high temperatures. Large 2-4 µm inclusions form during the solution treatment, within which the chemical and phase distribution are heterogeneous.

This review paper explores the multifaceted landscape of digital heritage preservation and presentation, focusing on various methods and technologies employed in the field. The introduction highlights the significance of digital heritage in preserving and showcasing cultural, historical, and natural assets. It emphasizes the non-destructive nature of digital preservation methods, enabling wider access and research possibilities. The paper also discusses the relevance of cultural computing in creating engaging user experiences and recognizes its potential in bridging cultural gaps. The literature review section presents a diverse range of technologies and tools, such as ZENetic Computer, C-Vyasa Sanskrit, Pandulipi Samshodhak, JATAN, and immersive projects like "Alice in Wonderland." The methods and technologies section delves into the technical aspects of digital heritage preservation. It explores photogrammetry, 3D depth sensing, 3D laser scanning, augmented reality, digital storytelling, focus stacking, and multiple view stereovision. Each technology is discussed in detail, highlighting its applications, benefits, and relevance in cultural heritage preservation. Finally, the comparative analysis section offers insights from various research papers and books, comparing different methodologies and approaches in the field. This review paper provides a comprehensive overview of digital heritage preservation, showcasing the diverse methods and technologies that contribute to the safeguarding and presentation of our cultural heritage for future generations.

Most of the commonly used Ionic Liquids (ILs) contain bulky organic cations with suitable anions. With our COMPLET (Concept of Melting Point Lowering due to Ethoxylation), we follow a different approach. We use simple, low-toxic, cheap and commercially available anions of the type Cx(EO)yCH2COO– to liquefy presumably any simple metal ion, independently of its charge. In the simplest case, the cation can be sodium or lithium, but synthesis of Ionic Liquids is also possible with cations of higher valences such as transition or rare earth metals. Anions with longer alkyl chains are surface active and form surface active ionic liquids (SAILs), which combine properties of ionic and nonionic surfactants at room temperature. They show significant structuring even in their pure state, i.e. in the absence of water or any other added solvent.

In the first year of its appearance, the 2019 coronavirus disease (COVID-19) has affected more than 150 million individuals and killed 3 million people worldwide. The pandemic has also triggered numerous global initiatives to tackle the newly emerging disease, including the development of SARS-CoV-2 vaccines and the attempt to discover potential pharmacological therapies. Nonetheless, despite the success of SARS-CoV-2 vaccines development, COVID-19 therapy remains challenging. Several repurposed drugs that were documented to be useful in small clinical trials have been shown to be ineffective in larger studies. Additionally, the pathophysiology of SARS-CoV-2 infection displayed the predominance of hyperinflammation and immune dysregulation in inducing multiorgan damage. Therefore, the potential benefits of both immune modulation and suppression in COVID-19 have been extensively discussed. Here, we reviewed the roles of immunomodulation as potential COVID-19 pharmacological modalities based on the existing data and proposed several new immunologic targets to be tested in the foreseeable future.

Groundnut (Arachis hypogaea L.) is a major food and cash crop in Burkina Faso. Due to growing demand for raw oilseeds, there is an increasing interest in groundnut production from traditional rain-fed areas to irrigated environments. However, despite implementation of many initiatives in the past to increase groundnut productivity and production, the groundnut industry still struggles to prosper, due to several constraints including minimal development research and fluctuating markets. Yield penalty due to drought and biotic stresses continue to be a major drawback for groundnut production. This review traces progress in the groundnut breeding that started in Burkina Faso before the country’s political independence in 1960 through to present times. Up to the 1980s, groundnut improvement was led by international research institutions such as IRHO (Institute of Oils and Oleaginous Research) and ICRISAT (International Crops Research Institute for the Semi-Arid Tropics). However, international breeding initiatives were not sufficient to establish a robust domestic groundnut breeding programme. This review also provides essential information about opportunities and challenges of groundnut research in Burkina Faso, emphasising the need for institutional attention to genetic improvement of the crop.

The utilization of tempered blast furnace (BF) slag through the direct fiber forming process to create high-value thermal insulation materials offers a dual benefit: it efficiently harnesses the latent heat within unused slag and substantially enhances the value of blast-furnace slag utilization. However, gauging the melting properties of iron slag under high temperatures is a challenge. In this study, we explore the melting behavior of SiO2 within a high-temperature molten pool. We employ dynamic visual data (video stream) captured via a non-contact charge coupled device (CCD) video recording system to extract SiO2 contours through image processing. The change in image centroid characteristics is used to establish a convolution function relationship, and MATLAB's traversal search algorithm determines SiO2's centroid position. Given that SiO2 is proportionate to crucible pixels, the area of SiO2 is calculated through pixel statistics within these contours. Subsequently, we propose a new indirect method to process image information, yielding SiO2 volume and mass at different time points. An exponential fitting yields the melting rate function of SiO2. Finally, we compare this indirect method with shape from shading (SFS), quantitative characterization, and dimensional analysis techniques. We also discuss the strengths and limitations of each method. Our findings reveal that the indirect solution method presented here boasts straightforward calculation steps and imposes minimal image format requirements. This research provides theoretical and technical support for blast-furnace slag's direct fiber forming process.

This article delves into the complex landscape of Bitcoin halving events, analyzing the historical context and implications of these pivotal occurrences within the cryptocurrency ecosystem and on its sustainability within the landscape of financial technologies. Through an examination of past halving events in 2012, 2016, and 2020, this study meticulously scrutinizes the conditions and prices of Bitcoin before and after each halving. By synthesizing data and trends from previous events, this article aims to uncover patterns and insights that illuminate the impact of Bitcoin halving on market dynamics and sustainability, movement of the price level, reached peaks and price troughs. Furthermore, this research presents a comparative analysis of past halving events, drawing parallels and distinctions to elucidate the evolving nature of Bitcoin's price movements and market sentiment surrounding these milestone events. Looking towards the future, this study estimates predictions and expectations for the upcoming Bitcoin halving. By unraveling the intricate relationship between Bitcoin halving events and market behavior, this article seeks to provide a comprehensive understanding of the broader implications for Bitcoin's trajectory and the evolving landscape of the cryptocurrency market and its sustainability.

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.