Material identification based on R_value (transparency natural logarithm ratio of low-energy to high-energy) of line-scan dual-energy X-ray transmission (DE-XRT) has a good prospect for industrial application. Unfortunately, the DE-XRT signals before attenuation cannot be directly measured, whereas their precision is very important to R_value. Therefore, a context-based signal synthesis method which takes the filtered signals that remove high-frequency noises and retain low-frequency actual fluctuations as the reference value, and takes into account the vertical (forward/column) direction and horizontal (scanning/row) direction anisotropy of line-scan images was proposed. The vertical is a time series with continuity of signal trend; the horizontal is a spatial characteristic with the fluctuation synchronization within the same row signals. The special synthesis evaluations of curve synthesis difference and surface synthesis difference were also proposed. Experimental results show that the tow evaluations are both only about 0.0007, and it only takes 35 ms to complete the surface synthesis of 119×119 pixels on the CPU with 3.4 GHz main frequency. The presented method can achieve high signal synthesis precision and calculation real-time, so as to facilitate DE-XRT material identification. It can be extended to improve the precision of numerical synthesis in other line-scan uncomplete signals.

The study of the surface thermodynamic properties of solid materials is primordial for the determination of the dispersive surface energy, polar enthalpy of adsorption and Lewis’s acid base properties of solid particles. Inverse gas chromatography technique (IGC) at infinite dilution is the best surface technique for the determination of the surface physicochemical properties of materials. (1) Background: This paper was devoted to study the surface properties of solid materials such as alumina particles by using IGC technique. (2) Methods: Different methods and molecular models such as spherical, cylindrical, van der Waals, Redlich-Kwong, Kiselev and geometric models, were used to determine the London dispersive surface energy of solid surfaces. Hamieh model was also used and highlighted the thermal effect on the surface area of solvents. (3) Results: The variations of the dispersive surface energy and the free energy of adsorption were determined for alumina particles as a function of the temperature as well as their Lewis’s acid base constants. Alumina surfaces were proved to exhibit a strong Lewis amphoteric character three time more basic than acidic (4) Conclusions: The new methodology based on Hamieh model gave the more accurate results of the physicochemical properties of the particle surfaces.

The paper describes a new formula for calculating the mutual inductance between a thin conical sheet inductor and a filamentary circular loop, which are coaxial. The presented formula is derived semi-analytically using the complete elliptic integrals of the first, second, and the third kind, along with the integral term which will be solved numerically. The results are validated using double and single integration methods, as well as the semi-analytical formula. The mutual inductance between a thin wall solenoid and a filamentary circular loop can be obtained using the new formula for the conical coil and circular loop. Presented formulas can be useful in various applications, such as broadband RF and wireless power transfer systems that utilize conical inductors. Overall, the paper presents a valuable contribution to the field of inductor design and can be useful in various applications involving conical inductors.

Currently, Korea is experiencing localized extreme rainfall, which accounts for more than 80% of flood-related disasters, and is increasing in small river basins, where more than 60% of flood-related casualties occur. These events are caused by climate change and geological factors and their impact is becoming more severe. As a result, an effective measurement system is required to mitigate their impact, particularly in small stream basins that are especially vulnerable due to their steep slopes, small catchment areas, and lack of maintenance and management capacity. In addition, a Flood Early Warning Framework (FEWF) that forecasts discharge and depth during flood events is crucial for reducing casualties. Therefore, this research is focused on developing the FEWF using the nomograph and rating curve methods, which are established by the robust constrained nonlinear equation solver and are suitable for small streams. The FEWF is evaluated using real-time data observed over 7-years period from the Closed-circuit Television-based Automatic Discharge Measurement Technology (CADMT), and the results show that the FEWF is effective in forecasting discharge and depth during flood events. The use of CADMT technology for real-time data can develop an accurate and reliable FEWF, which can help mitigate the impacts of extreme rainfall events and reduce the number of flood-related casualties in small stream basins.

Although, Artificial intelligence (AI) helps experts with crime analysis, research, and understanding, it has a favourable influence on cyber security. It strengthens the tools that businesses use to safeguard their networks, clients, and workers against dangerous online behaviour. However, artificial intelligence is infamous for requiring a lot of resources. It may not, however, always be relevant. Additionally, it can provide hackers a new tool and advance their abilities. Actually, the VPN industry benefits from AI in the same way. The threat posed by machine learning in AI to user data privacy may be lessened by using a VPN on all of your devices. Because they use machine learning algorithms, VPNs are better equipped to shield their users from internet-based threats. Artificial intelligence (AI) has reportedly being investigated as a means of enhancing internet security for a considerable amount of time, according to Smart Data Collective. We anticipated that AI and machine learning will have a substantial impact on the future of cyber security around two years ago.

Nuclear technologies have a strong potential and a unique role to play in delivering reliable low carbon energy for a future net-zero society. However, to assure the sustainability required for the long-term success, nuclear will need to deliver innovative solutions as proposed in iMAGINE. One of the most attractive features, but also a key challenge for the envisaged highly integrated nuclear energy system is the need for a demand driven salt clean-up system. The work described provides an insight into the interplay between a potential salt clean-up system and the reactor operation in a plutonium started core in a dynamic approach. The results presented will help to optimize the parameters for the salt clean-up process as well as to understand the differences which appear between a core started with enriched Uranium and Plutonium as the fissile material. The integrated model is used to investigate the effects of the initial fissile material on core size, achievable burnup, and long term operation. Different approaches are tested to achieve a higher burnup in the significantly smaller Pu driven core. The effects of different clean-up system throughputs on the concentration of fission products in the reactor salt and its consequences are discussed for general molten salt reactor design. Finally, an investigation of how a plutonium loaded core could be used to provide fuel for future reactors through fuel salt splitting is presented with the outcome that one Pu started reactor of the same size as a uranium started core could deliver fuel for 1.5 new cores due to enhanced breeding. The results provide an essential understanding for the progress of iMAGINE as well as the basis for inter-disciplinary work required for optimizing iMAGINE.

This article analyzes and compares the integration of two different maximum power point tracking (MPPT) control methods, which are tested under partial shading and fast ramp conditions. These MPPT methods are designed by Improved Particle Swarm Optimization (IPSO) and a combination technique between Neural Network and Perturb & Observe method (NN_P&O). These two methods are implemented and simulated for photovoltaic systems (PV), where various system responses, such as: voltage and power are obtained. The MPPT techniques were simulated using Matlab/Simulink environment. A comparison of the performance of IPSO and NN_P&O algorithms is carried out to confirm the best accomplishment of the two methods in terms of speed, accuracy and simplicity.

The study of long-term average weather patterns is known as climatology. It is a distinct field of study from meteorology and can be broken down into several subdivision. In order to predict the future, the knowledge of climatology is essential. In other words, with the help of climatology, we can figure out how likely it is that snow and hail will fall to the ground, and how much solar thermal radiation can reach a certain location etc. Climatology often focuses on how the climate has changed over time and how it has affected people and events. Both meteorology and climatology fall under the general term "meteorology", in particular, they are subdivision of research in the same field. In case of predicting the weather, meteorologists use variables such as humidity, air pressure, and temperature. This article's primary objective is to familiarize engineers with the fundamentals of climate and its processes so that they can effectively apply this knowledge to comprehend the climatic impact on water resources systems.

This study determines the threshold for the computational rate of actuator motor controllers for unmanned underwater vehicles necessary to accurately follow discontinuous square wave commands. Motors must track challenging square-wave inputs, and identification of key computational rates permit application of deterministic artificial intelligence (D.A.I.) to achieve tracking to a machine-precision degree of accuracy in direct comparison to other state-of-art approaches. All modeling approaches are validated in MATLAB simulations where the motor process is discretized at varying step-sizes (inversely proportional to computational rate). At a large step-size (fast computational rate), discrete D.A.I. shows a mean error more than three times larger than that of a ubiquitous model-following approach. Yet, at a smaller step size (slower computational rate), the mean error decreases by a factor of 10, only three percent larger than that of continuous D.A.I. Hence, the performance of discrete D.A.I. is critically affected by the sampling period for discretization of the system equations and computational rate. Discrete D.A.I. should be avoided when small step-size discretization is unavailable. In fact, continuous D.A.I. has surpassed all modeling approaches which makes it the safest and most viable solution to future commercial applications in unmanned underwater vehicles.

The aim of this study is to empirically examine the link between foreign direct investment (FDI) and domestic investment (DI) in South Africa over the period of 41 years (1975-2016). Accurately, it attempts to determine whether FDI crowds in or crowds out DI in South Africa. DI is sub-divided into private domestic investment (credit to domestic private sector) and public corporation investment (state owned enterprises). We used the Autoregressive Distributed Lag-Error Correction Model (ARDL-ECM) technique to ascertain long run and short run effects concurrently after establishing that the variables were stationary (using the PP test). The results of the unit root test shows that all variables are integrated of order zero I(0) or integrated of order one I(1), indicating that the series of variables are stationary in the level or first difference form. The findings revealed that variables are cointegrated in the long run. The ARDL model found a negative link between FDI and domestic investment. The result implies that FDI crowds out domestic investment. Moreover, the long run estimate revealed that domestic investment is crowded in by government investment expenditure (GINV). Other findings uncovered that, GDP crowds out private domestic investment while crowding in public corporation investment. Moreover, the long run estimate revealed that domestic investment is crowded in by gross domestic savings (SAV). On the other hand, the real exchange rate (EXCR) crowds out private domestic investment while crowding in public corporation investment. Trade openness (TRA) crowds out domestic investment. Additionally, the short run estimate uncovered that private domestic investment is crowded out by FDI, EXCR, and TRA whereas GINV, GDP and SAV is crowding in private domestic investment. Other findings discovered that, in the short run, public corporation investment is crowded out by FDI, GDP, EXCR and TRA, while GINV and SAV crowd in public corporation investment. The CUSUM confirms that the models are structurally firmness.

Although research has long established that the interaction with the natural environment is associated with better overall health and well-being outcomes, the Western model mainly focuses on treating the symptoms. In Aotearoa-New Zealand, the Indigenous Māori have long demonstrated significantly more negative health outcomes than non-Māori. Little research has examined the causes compared to Western populations or the role of the natural environment in health outcomes for Māori. An exploration of rongoā Māori (traditional healing system) was conducted to ascertain the importance of landscape in the process of healing. Eight rongoā healers or practitioners took part in semi-structured narrative interviews from June to November 2020. Transcribed interviews were analysed using an interpretative phenomenological analysis and Kaupapa Māori techniques. The findings show how rongoā is underpinned by a complex set of cultural values and beliefs, drawing from the connection to wairua (spirit), tinana (body), tikanga and whakaora (customs and healing), rākau (plants), whenua (landscape) and whānau (family). Incorporating such constructs into the landscape can foster our understanding of health and well-being and its implications for conceptualising therapeutic environments and a culturally appropriate model of care for Māori and non-Māori communities.

Adverse childhood experiences are known to program children for disrupted biological cycles, premature aging, microbiome dysbiosis, immune-inflammatory misregulation, and chronic disease multimorbidity. To date, the microbiome has not been a major focus of deprogramming efforts despite its emerging role in every aspect of ACE-related dysbiosis and dysfunction. This article examines: 1) the utility of incorporating microorganism-based, anti-aging approaches to combat ACE-programmed chronic diseases (also known as noncommunicable diseases and conditions, NCDs) and 2) microbiome regulation of core systems biology cycles that affect NCD comorbid risk. In this review microbiota influence over three key cyclic rhythms (circadian cycles, the sleep cycle, and the lifespan/longevity cycle) as well as tissue inflammation and oxidative stress are discussed as an opportunity to deprogram ACE-driven chronic disorders. Microbiota, particularly those in the gut, have been shown to affect host-microbe interactions regulating the circadian clock, sleep quality, as well as immune function/senescence and regulation of tissue inflammation. The microimmunosome is one of several systems biology targets of gut microbiota regulation. Furthermore, correcting misregulated inflammation and increased oxidative stress is key to protecting telomere length and lifespan/longevity and extending what has become known as the healthspan. This review article concludes that to reverse the tragedy of ACE-programmed NCDs and premature aging, managing the human holobiont microbiome should become a routine part of healthcare and preventative medicine across the life course.

The minimum energy structures of the Si3C5 and Si4C8 clusters are planar and contain planar tetracoordinate carbons (ptCs). These species have been classified, qualitatively, as global () and local () aromatics according to the adaptive natural density partitioning (AdNDP) method, which is an orbital localization method. This work evaluates these species' aromaticity, focusing on confirming and quantifying their global and local aromatic character. For this purpose, we use an orbital localization method based on the partitioning of the molecular space according to the topology of the electronic localization function (LOC-ELF). In addition, the magnetically induced current density is analyzed. The LOC-ELF-based analysis coincides with the AdNDP study (double aromaticity, global and local). Besides, the current density analysis detects global and local ring currents. The strength of the global and local current circuit is significant, involving 4n+2 - and -electrons, respectively. The latter implicates the Si-ptC-Si fragment, which would be related to the 3c-2e -bond detected by the orbital localization methods in this fragment.

Adult neural stem and progenitor cells (NSPCs) contribute to learning, memory, maintenance of homeostasis, energy metabolism and many other essential processes. They are highly heterogeneous populations that require input from a regionally distinct microenvironment including a mix of neurons, oligodendrocytes, astrocytes, ependymal cells, NG2+ glia, vasculature, cerebrospinal fluid (CSF), and others. The diversity of NSPCs is present in all three major parts of the CNS, i.e., the brain, spinal cord, and retina. Intrinsic and extrinsic signals, e.g., neurotrophic and growth factors, master transcription factors, and mechanical properties of the extracellular matrix (ECM), collectively regulate activities and characteristics of NSPCs: quiescence/survival, proliferation, migration, differentiation, and integration. This review discusses the heterogeneous NSPC populations in the normal physiology and highlights their potentials and roles in injured/diseased states for regenerative medicine.

Complex modeling has received significant attention in recent years and is increasingly used to explain the statistical phenomenon with increasing and decreasing fluctuations such as the similarity or difference of spike protein charge patterns of coronaviruses. Different from the existing covariance or correlation coefficient methods in traditional integer dimension construction, this study proposes a simplified novel fractional dimension derivation with the exact Excel tool algorithm. It involves the fractional center moment extension to covariance, which ends up a complex covariance coefficient that is better than the Pearson correlation coefficient, in the sense that the nonlinearity relationship can be further depicted. The spike protein sequences of coronaviruses were obtained from the GenBank and GISAID database, including the coronaviruses from pangolin, bat, canine, swine (three variants), feline, tiger, SARS-CoV-1, MERS, and SARS-CoV-2 (including the strains of Wuhan, Beijing, New York, German, and UK variant B.1.1.7) were used as the representative examples in this study. By examining the values above and below the average/mean based on the positive and negative charge patterns of the amino acid residues of the spike proteins from coronaviruses, the proposed algorithm provides deep insights into the nonlinear evolving trends of spike proteins for understanding the viral evolution and identifying the protein characteristics associated with viral fatality. The calculation results demonstrate that the complex covariance coefficient analyzed by this algorithm is capable of distinguishing the subtle nonlinear differences in the spike protein charge patterns with reference to Wuhan strain SARS-CoV-2 for which the Pearson correlation coefficient may overlook. Our analysis reveals the unique convergent (positive correlative) to divergent (negative correlative) domain center positions of each virus. The convergent or conserved region may be critical to the viral stability or viability; while the divergent region is highly variable between coronaviruses suggesting high frequency of mutations in this region. The analyses show that the conserved center region of SARS-CoV-1 spike protein is located at amino acid residues 900, but shifted to the amino acid residues 700 in MERS spike protein, and then to amino acid residues 600 in SARS-COV-2 spike protein, indicating the evolvement of the coronaviruses. Interestingly, the conserved center region of the spike protein in SARS-COV-2 variant B.1.1.7 shifted back to amino acid residues 700, suggesting this variant is more virulent than the original SARS-COV-2 strain. Another important characteristic our study reveals is that the distance between the divergent mean and the maximal divergent point in each of the viruses (MERS>SARS-CoV-1>SARS-CoV-2) is proportional to viral fatality rate. This algorithm may help to understand and analyze the evolving trends and critical characteristics of SARS-COV-2 variants, other coronaviral proteins and viruses.

The goods and services produced by forest and vegetation ecology system is the power by which human society can be promoted fast in high-quality and sustainable way. With the increase of population and economic development in water-limited regions, there is an increasing demand for the quantity and variety of forest vegetation ecosystem products and services. To meet the demands of this situation, most of the original forest has changed into farmland, non-native forest and grass land. As a result, water-plant relationship changed from equilibrium to non-equilibrium, which led to soil drought, soil degradation and vegetation decline in dry years or waste of soil water in rainy years in most of water-limited regions. In order to solve the questions and realize the sustainable utilization of soil water resources and the high quality and sustainable development of social economy, it is necessary to apply the utilization limit theory of soil water resources by plants and the theory of soil water carrying capacity for vegetation to adjust the relationship between plant growth and soil moisture to obtain the maximum yield and benefit of vegetation and serve high-quality and sustainable development.

Fiber reinforced thermoplastics (FRTP), which is reinforced with glass or carbon fibers, are used to improve the mechanical strength of injection-molded products. However, FRTP has problems such as the formation of weld lines, the deterioration of the appearance due to the exposure of fibers on the molded product surface, and the deterioration of the strength of molded products due to the fiber orientation in the molded products. We have designed and fabricated an injection mold capable of melt flow control and induction heating and cooling that has the functions of both heating and cooling the injection mold as well as the function of controlling the melt flow direction using a movable core pin. In this study, the above-mentioned mold was used for the molding of carbon fiber reinforced semi-aromatic polyamide. As a result, we found that increasing the heating temperature of the mold and increasing melt flow control volume contribute to the prevention of the generation of a weld line and the exposure of fibers on the molded product surface, as well as to the formation of a flat surface and increased bending strength. The relationships of these results with the carbon fiber orientation in the molded products and the crystallization of semi-aromatic polyamide were also examined in this study.

In the paper, by virtue of convolution theorem for the Laplace transforms, Bernstein's theorem for completely monotonic functions, and other techniques, the author finds necessary and sufficient conditions for a difference constituted by four derivatives of a function involving trigamma function to be completely monotonic.

Finding new, safe strategies to prevent and control rheumatoid arthritis is an urgent task. Of particular interest in this regard are bioactive peptides and peptide-rich protein hydrolyzates, which represent a new trend in the development of functional foods and nutraceuticals. The resulting tissue hydrolyzate of the chicken embryo (CETH) has been evaluated for acute toxicity and tested against chronic arthritis induced by Freund's full adjuvant in rats. The anti-arthritic effect of CETH was studied on the 28th day of the experiment after two weeks of oral administration of CETH at doses of 60 and 120 mg/kg body weight. Arthritis was evaluated on the last day of the experiment on the injected animal paw using X-ray computerized microtomography and histopathology analysis methods. The CETH effect was compared with the non-steroidal anti-inflammatory drug diclofenac sodium (5 mg/kg). Oral administration of CETH was accompanied by effective dose-dependent correction of morphological changes caused by the adjuvant injection. CETH had relatively high recovery effects in terms of parameters for reducing inflammatory edema, inhibition of osteolysis, prevention of osteophitosis, reduction of the inflammatory reaction of periarticular tissues, and cartilage degeneration. This study presents a potential theoretical strategy for the safe correction of this pathological process and, for the first time, shows that CETH may be a powerful potential nutraceutical agent or bioactive component of functional products in the treatment of rheumatoid arthritis.

This paper discovers that current canonical variational principle and canonical Noether theorem of (in)finite freedom systems for different physics systems have neglected doublet extreme value processes of the general extreme value functional that both is derived by variational principle and is necessarily be taken in deriving all ( quantum ) physics laws in phase space, but which have not been done for over one century since Noether's showing her distinguished theorem, which lead to the crisis deriving all (quantum) physics laws (necessary) in phase space. We discover there is the hidden logic cycle that people assume canonical equations, and then they finally deduce canonical equations by the equivalent relation in the whole processes in all current references. We correct the current key mistake concepts that when physics systems take the variational extreme values, the appearing processes of the physics systems are real physics processes, otherwise, are virtual processes in all current references. The real physics should be what after taking the physics systems' variational extreme values, the physics systems' general extremum functional needs to further take the general extremum functional's minimum absolute extremum zero, otherwise, the appearing processes of physics systems still are virtual processes. Conservation current equations and conservation currents, in phase space, of general canonical variational principle and general canonical Noether theorem are, respectively, deduced for the first time. Using the general extremum functionals' doublet extreme value processes, the hidden logic cycle and the crisis in current canonical variational principle and current canonical Noether theorem are solved. Consequently, the new mathematical pictures, classical and quantum new physics in phase space and the new mathematical and physical doublet extremum processes for (in)finite freedom systems are discovered. General canonical variational principle and general canonical Noether theorem naturally are given, which would rewrite all the different sciences in phase space, as key tools of studying and dealing with them.

Space-time evolution is briefly explained by using the 3-dimensional quantized space model (TQSM) based on the 4-dimensional (4-D) Euclidean space. The energy (mass), charges and absolute time are newly defined based on the 4-D Euclidean space. The photons and gravitons are understood as the 2-D space fluctuations along the space axes and 1-D time fluctuations along the time axis, respectively. This indicates that the electromagnetic (EM) and gravitational (G) waves can be unified into the so called gravityelectromagnetic (GEM) wave which has both space and time fluctuations. The photon with zero force fields is the 2EM wave because an EM wave corresponds to a charged fermion. The dark matter bosons, weak force bosons, strong force bosons are the 1-D time fluctuations which can be expressed by the G waves. This indicates that all five forces are unified by the GEM wave. It is called as the super unification theory in the present work. And the force carrying bosons and mesons are, for the first time, proposed as the possible candidates of the magnetic monopoles like the fermions and baryons are the electric monopoles. The signs of the magnetic charges quantized as q_m=cq are newly defined. The big bang is understood by the space-time evolution of the 4-D Euclidean space but not by the sudden 4-D Minkowski space-time creation. The big bang process created the matter universe with the positive energy and the partner anti-matter universe with the negative energy from the CPT symmetry.

The dominant paradigm holds that spontaneous and therapeutically induced anti-tumor responses are mediated mainly by CD8 T cells and directed against tumor-specific antigens (TSAs). The presence of specific TSAs on cancer cells can only be proven by mass spectrometry analyses. Bioinformatic predictions and reverse immunology studies cannot provide this type of conclusive evidence. Most TSAs are coded by unmutated non-canonical transcripts that arise from cancer-specific epigenetic and splicing aberrations. When searching for TSAs, mass spectrometry analyses must therefore interrogate not only the canonical reading frame of annotated exome but all reading frames of the entire translatome. The majority of aberrantly expressed TSAs (aeTSAs) derive from unstable short-lived proteins that are good substrates for direct MHC I presentation but poor substrates for cross-presentation. This is an important caveat because cancer cells are poor antigen-presenting cells and the immune system therefore depends on cross-presentation by dendritic cells (DCs) to detect the presence of TSAs. We therefore postulate that, in the untreated host, most aeTSAs are undetected by the immune system. We present evidence suggesting that vaccines inducing direct aeTSA presentation by DCs represent an attractive strategy for cancer treatment.

Africa was the only continent not to achieve the 2015 Millennium Development Goal of 50% poverty reduction. This paper asks whether Africa will fare better in meeting Sustainable Development Goals (SDGs) addressing poverty and hunger by 2030. To answer this question we examine literature, including our field research published over the last thirteen years. We find that ‘sustainable development’ is a failed concept immersed in the contemporary global economic system that favors growth over ecosystem stability and patriarchal systems of governance that undervalue women’s capacity for sustainability in their care-work as food providers. We examine barriers to women’s farming (climate change, gender bias, limited access to land, technology, finance) and provide examples of women’s innovative strategies for overcoming these barriers in their care practices toward family and community well-being and ecosystem health. We conclude that sustainability is only possible through transformation of thinking away from approaches that value profit over people and ecosystems and toward gender-based approaches for achieving the goals laid out in the SDGs through holistic, integrative systems of ecosystem fit.

SARS-CoV-2 is a newly emerging, highly transmissible, and pathogenic coronavirus in humans, which has caused global public health emergency and economic crisis. To date, millions of infections and thousands of deaths have been reported worldwide, and the numbers continue to rise. Currently, there is no specific drug or vaccine against this deadly virus; therefore, there is a pressing need to understand the mechanism through which this virus enters the host cell. Viral entry into the host cell is a multistep process in which SARS-CoV-2 utilizes the receptor binding domain of the spike glycoprotein (S) to recognize ACE2 receptors on the human cells; this initiates host cell entry by promoting viral-host cell membrane fusion through large scale conformational changes in the S protein. Receptor recognition and fusion are critical and essential steps of viral infections and are key determinants of the viral host range and cross-species transmission. In this review, we summarize the current knowledge on the origin and evolution of SARS-CoV-2 and the roles of key viral factors. We discuss the RNA dependent RNA polymerase structure of SARS-CoV-2, its significance in drug discovery, and explain the receptor recognition mechanisms of coronaviruses. We provide a comparative analysis of the SARS-CoV and SARS-CoV-2 S proteins, receptor-binding specificity, and discuss the differences in their antigenicity based on biophysical and structural characteristics.

As there exist no repulsive forces in strong interaction, in a hypothetical approach, strong interaction can be assumed to be equivalent to a large gravitational coupling. Based on this concept, strong coupling constant can be defined as a ratio of the electromagnetic force and the gravitational force associated with proton, neutron, up quark and down quark. With respect to the product of strong coupling constant and fine structure ratio, we review our recently proposed two semi empirical relations and coefficients 0.00189 and 0.00642 connected with nuclear stability and binding energy. We wish to emphasize that- by classifying nucleons as ‘free nucleons’ and ‘active nucleons’, nuclear binding energy can be fitted with a new class of ‘three term’ formula having one unique energy coefficient. Based on the geometry and quantum nature, currently believed harmonic oscillator and spin orbit magic numbers can be considered as the lower and upper “mass limits” of quark clusters.

We examined special roles of the Central Nervous System (CNS) in an attempt to resolve the puzzle that chronic diseases cannot be cured by medicine. By exploring a skill-learning model, we found that the CNS is able to remember certain information reflecting biochemical and cellular (B&C) processes in the body. From the skill using ability, we found that the CNS is able to control basic B&C processes that drive and power the skill. From the ability to adjust forces and force direction of a physical act, we found that the CNS is able to adjust B&C processes that drive the physical act. From this adjustment capability, we further inferred that the CNS must also store information on the baseline B&C processes. As a whole, we found that the CNS can maintain information on baseline B&C processes, up-regulate or down-regulate the processes, and make comparisons in performing its regulatory functions. We found that chronic diseases are the results of deviated baseline B&C processes. Per the proved hypothesis, the CNS maintains deviated baseline B&C processes, and thus protects the body states of fully developed diseases. We then used the three CNS roles to explain that cancer progresses with increasing malignancy, cancer quickly returns after a surgery, cancer cells repopulate after chemotherapy and radiotherapy, cancer develops drug resistance inevitably, immune cells rebound after suppression, generally poor benefits of cancer drugs such as beta-blockers, etc. We further showed that long-term exercises generally push most, if not all, baseline B&C processes in diametrical opposing directions against the diseased B&C processes, implying that exercises play unique roles in reversing chronic diseases. Finally, we proposed several strategical approaches to resetting the CNS’ state memory as the essential condition for curing chronic diseases.

A smart city is a futuristic approach that evolves with new technologies. It can start as a simple community and evolve into future cities. In most developing countries, where the population growth is faster, and where the organization and the urbanization are slower, there is a serious need for a framework for progressive change towards sustainable cities. This article discusses the level of intelligence of smart city components and proposes indicators as well as a methodology for measuring intelligence based on the objectives to be achieved as well as a certain number of technical requirements and some cognitive processes implemented.

Building energy consumption plays an essential role in urban sustainability. The prediction of the energy demand is also of particular importance for developing smart cities and urban planning. Machine learning has recently contributed to the advancement of methods and technologies to predict demand and consumption for building energy systems. This paper presents a state of the art of machine learning models and evaluates the performance of these models. Through a systematic review and a comprehensive taxonomy, the advances of machine learning are carefully investigated and promising models are introduced.

Computation of Common Middle Point seismic sections and their subsequent time migration and diffraction imaging provides very important knowledge about the internal structure of 3D heterogeneous geological media and are key elements for successive geological interpretation. Full-scale numerical simulation, that computes all single shot seismograms, provides a full understanding of how the features of the image reflect the properties of the subsurface prototype. Unfortunately, this kind of simulations of 3D seismic surveys for realistic geological media needs huge computer resources, especially for simulation of seismic waves’ propagation through multiscale media like cavernous fractured reservoirs. In order to significantly reduce the query of computer resources we propose to model these 3D seismic cubes directly rather than the shot-by-shot simulation with subsequent CMP stacking. To do that we modify the well known "exploding reflectors principle" for 3D heterogeneous multiscale media by use of the finite-difference technique on the base of grids locally refined in time and space. To be able to simulate realistic models and acquisition we develop scalable parallel software, which needs reasonable computational costs. Numerical results for simulation of Common Middle Points sections and their time migration are presented and discussed.

Celiac disease (CD) is a genetically conditioned autoimmune process that appears in susceptible people. It can affect people of any age, and slightly predominates in females. It has a fairly homogenous global distribution, with an average prevalence of 1-2%, the frequency having increased in recent decades. The only effective treatment is a strict and permanent gluten-free diet (GFD), although the level of compliance with it is poor, at about 50% of cases. To monitor the effectiveness of the GFD, several procedures involving various approaches are employed: a) periodic interviews by nutritionists; b) clinical follow-up; c) serological controls of specific antibodies; d) endoscopies with collection of duodenal biopsies; e) structured questionnaires; f) determination of gluten peptides derived from gluten in feces and/or urine. All of these procedures are useful when applied, alone or in combination, depending on the cases. Some patients will only need to consult to their doctors, while others will require a multidisciplinary approach to assess their compliance with the GFD. In children, normalization of duodenal mucosa was achieved in 95% of cases within 2 years, while it is more delayed in adults, whose mucosa take longer to heal completely.

This essay studies Afro-Asian sociocultural interactions in cultural production by or about Asian Latin Americans, with an emphasis on Cuba and Brazil. Among the recurrent characters are the black slave, the china mulata, or the black ally who expresses sympathy or even marries the Asian character. This reflects a common history of bondage shared by black slaves, Chinese coolies, and Japanese indentured workers, as well as a common history of marronage. These conflicts and alliances between Asians and blacks contest the official discourse of mestizaje (Spanish-indigenous dichotomies in Mexico and Andean countries, for example, or black and white binaries in Brazil and the Caribbean), which, under the guise of incorporating the Other, favored whiteness, all the while attempting to silence, ignore, or ultimately erase their worldviews and cultures.

Ferrocenium (Fc+) inherits a number of molecular/electronic properties from the neutral counterparts’ ferrocene (Fc) including the high symmetry. Both Fc+ and Fc prefer the eclipsed structure (D5h) over the staggered structure (D5d) by an energy of 0.36 kcal·mol-1. The present study using the recently developed excess orbital energy spectrum (EOES) shows that the open shell Fc+ cation exhibits similar conformer dependent configurational changes to the neutral Fc conformer pair. A further energy decomposition analysis (EDA) discloses that the reasons for the preferred structures are different between Fc+ and Fc. The dominant differentiating energy between the Fc+ conformers is the electrostatic energy (EEstat), whereas in neutral Fc, it is the quantum mechanical Pauli repulsive energy (EPauli). Within the D5h conformer of Fc+, the EOES reveals that the -electrons of Fc+ experience more substantial conformer dependent energy changes than the -electrons (assumed the hole is in a β orbital).

In this work we identify combinations of technological activities that signal the presence local capabilities in a country to successfully export a product. We use country-level patent and trade data to generate a multi-layer network, and we apply maximization of entropy to generate synthetic data to effectively divide signal from noise. We show that in several sectors the signal far exceed the noise. Our exercise provides robust evidence of the presence of synergies between technologies to explain trade performances in specific markets. This can be highly useful for policy makers, to inform industrial and innovation policies.

In this paper we obtain some inequalities of Hermite-Hadamard type for composite convex functions. Applications for AG, AH-h-convex functions, GA, GG, GH-h-convex functions and HA, HG, HH-h-convex function are given.

The Bayes filters, such as Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of the unknowns. Efficient integration of multiple sensors requires deep knowledge of their error sources and it is not trivial for complicated sensors, such as Inertial Measurement Unit (IMU). Therefore, IMU error modelling and efficient integration of IMU and Global Navigation Satellite System (GNSS) observations has remained a challenge. In this paper, we develop deep Kalman filter to model and remove IMU errors and consequently, improve the accuracy of IMU positioning. In other words, we add modelling step to the prediction and update steps of Kalman filter and the IMU error model is learned during integration. Therefore, our deep Kalman filter outperforms Kalman filter and reaches higher accuracy.

Congenital insensitivity to pain with anhidrosis (CIPA), also known as hereditary sensory and autonomic neuropathy type IV (HSAN IV), is an exceedingly rare genetic disorder characterized by the inability to perceive pain, inability to sweat, and various neurological and orthopedic complications. This is a case report of a 3-year-old female patient diagnosed with CIPA syndrome who presented repeatedly to Children’s Clinical University Hospital (CCUH) in Riga, Latvia with severe orthopedic manifestations. The patient had repeated fractures, several surgeries, and extensive spread of the disease throughout the left leg, which caused significant functional impairment and decreased quality of life. Despite aggressive orthopedic interventions including surgical interventions and physical therapy, the patient's condition remained challenging to manage due to the inherent limitations posed by the insensitivity to pain. The council of doctors discussed the patient's condition and changes, deciding that reconstructive surgery is not feasible, and amputation is recommended. Through this case report, we aim to highlight the unique orthopedic challenges encountered in the management of CIPA patients, emphasizing the importance of a multidisciplinary approach involving orthopedic surgeons, pediatricians, geneticists, and physiotherapists. Additionally, we discuss the need for further research to elucidate optimal management strategies and improve outcomes in this rare and complex patient population.

The Supportive and Palliative Indicators Tool (SPICT) was developed for timely identifying patients who may benefit from supportive and palliative care for a better treatment review, care plan discussion, and end-of-life care. Although the SPICT has been validated in different languages and patients living in different settings, it has not been validated in patients receiving home-based medical care (HBMC), or in the context of using traditional Chinese characters. The present study aimed to validate the Taiwan version of SPICT (SPICT-TW) and to measure its ability to predict six-month mortality in patients who received HBMC in Taiwan. Seven HBMC agents (five clinics and two hospitals) participated in this validation study. We recruited 129 patients aged ≥50 years who had been consistently receiving HBMC for > two months. The results revealed that the SPICT-TW demonstrated similar reliability and validity compared to other language versions of SPICT. It may be an appropriate tool for healthcare professionals to timely detect the needs of palliative care in older people who received home healthcare. Furthermore, we found that a combination of four general indicators and one clinical indicator in SPCIT-TW has the best prediction ability at predicting six-month mortality in these HMBC recipients. This multicenter study validated the SPICT-TW among HBMC recipients in Taiwan. SPICT-TW demonstrated high reliability and validity and may be a practical tool for identifying older people at risk of dying within six months who would benefit from palliative care.

The American Civil War has been commemorated with a great variety of monuments, memorials, and markers. These monuments were erected for a variety of reasons, beginning with memorialization of the fallen and later to honor aging veterans, commemoration of significant anniversaries associated with the conflict, memorialization sites of conflict, and celebration of the actions of military leaders. Sources reveal that during both the Jim Crow and Civil Rights eras, many were erected as part of an organized propaganda campaign to terrorize African American communities and distort the past by promoting a ‘Lost Cause’ narrative. Through subsequent decades, to this day, complex and emotional narratives have surrounded interpretive legacies of the Civil War. Instruments of commemoration, through both physical and digital intervention approaches, can be provocative and instructive, as the country deals with a slavery legacy and the commemorated objects and spaces surrounding Confederate inheritances. Today, all of these potential factors and outcomes, with internationally relevance, are surrounded by swirls of social and political contention and controversy, including the remembering/forgetting dichotomies of cultural heritage. The modern dilemma turns on the question: In today’s new era of social justice, are these monuments primarily symbols of oppression, or can we see them, in select cases, alternatively as sites of conscience and reflection encompassing more inclusive conversations about commemoration? What we save or destroy and assign as the ultimate public value of these monuments rests with how we answer this question. In this essay, drawing from the testimony of scholars and artists, I address the conceptual landscape of approaches to the presentation and evolving participatory narratives of Confederate monuments that range from absolute expungement and removal to more restrained ideas such as in situ re-contextualization, removal to museums, and preservation-in-place.

Several cities are experiencing an increase in flood hazard and exposure, and consequentially in flood risk, attributable to the coupled effect of climate change and urbanization. Non-structural protection strategies demonstrate significant potential in the short term for mitigating hydraulic risk in urban areas, particularly where the implementation of structural measures is impeded by a complex urban environment. This work proposes an Early Warning System (EWS) for fluvial floods developed for the city of Palermo (Italy). It is based on the preliminary definition of po-tential Flood Event Scenarios (FESs) as a function of typical potential precursors. Each FES pre-dicts first points of flooding, flood areas and water depths, also providing specific hazard maps for people, vehicles, and buildings. The EWS uses rainfall depth-duration thresholds to assess the expected hydrograph as a function of rainfall forecasts and the water stage observed in real time at an upstream section of the river crossing the city. This last also allows for estimating the ante-cedent wetness conditions. Based on this information, the EWS retrieves an expected FES from a pre-built library with a preannouncement time up to 36 h. The EWS is here successfully tested on a historical flood event.

Objective: To evaluate audiological outcomes, quality of life, and complications in patients implanted with Active middle ear implants (AMEI). The secondary objective is to investigate the required duration after implantation to reach satisfactory outcomes. Methods: This retrospective study included 31 patients implanted with Active middle ear implants (AMEI) with different methods of floating mass transducer attachment. Patients with incomplete medical records and those who did not respond to postoperative follow-up were excluded. Patients were assessed preoperatively, and at one, three, and six months postoperatively. The assessment included Pure Tone Average (PTA4), Speech Reception Threshold (SRT) and Speech Discrimination Score (SDS). The Speech Spatial and Qualities of Hearing scale (SSQ12) was also used to evaluate levels of satisfaction. Result: There are no significant differences found in PTA and SRT between the 3-, 6-, and 12-month visits. The speech reception threshold (SRT) showed a statistically significant improvement at 3, 6, and 12 months post-operative measures compared to pre-operative. Additionally, the SDS exhibited a significant increase only after 12 months, compared to the 3-month time point. However, satisfaction levels did not significantly differ between the 6-month and 12-month measurements following surgery. Conclusion: Vibrant Sound bridge improves subjective satisfaction scores and audiological test scores in patients with different types of hearing loss. AMEI has a low risk of medical or surgical complications, the ease of using a hearing implant, and the social benefits of good hearing and communication.

Aquaculture is expected to play a vital role in solving the challenge of sustainably providing the growing world population with healthy and nutritious food. Pathogen outbreaks are a major risk for the sector, so early detection and a timely response are crucial. This can be enabled by monitoring of pathogen levels in aquaculture facilities. This paper describes a photonic biosensing platform based on silicon nitride waveguide technology with integrated active components, which could be used for such applications. Compared to the state of the art, the current system presents improvements in terms of miniaturization of the Photonic Integrated Circuit (PIC), and the development of wafer level processes for hybrid integration of active components and for material-selective chemical and biological surface modification. Furthermore, scalable processes for integrating the PIC in a microfluidic cartridge have been developed, as well as a prototype desktop readout instrument. Three bacterial aquaculture pathogens (Aeromonas salmonicida, Vagococcus salmoninarum, and Yersinia ruckeri) were selected for assay development. DNA biomarkers were identified, corresponding primer-probe sets designed, and qPCR assays developed. The biomarker for Aeromonas was also detected using the hybrid PIC platform. This is the first successful demonstration of biosensing on the hybrid PIC platform.

Background: The exacerbation of psychosocial problems among children and adolescents during the coronavirus disease 2019 (COVID-19) pandemic necessitates an assessment of the long-term mental health impact of pandemic interventions. Focusing on both pandemic-related factors and demographic variables, such as gender and daily habits, an analysis was conducted to under-stand how these elements continue to affect young populations in the post-pandemic era. Methods: In April 2023, a comprehensive online survey was administered to families in South Tyrol, Italy, with children aged 7–19 years, to ensure age and gender representation. The survey included par-ent ratings and adolescent (11–19 years) self-reports using standardized instruments to measure the symptoms of mental health problems (Strengths and Difficulties Questionnaire, SDQ), anxiety (Screen for Child Anxiety Related Emotional Disorders, SCARED), and depression (Patient Health Questionnaire-2, PHQ-2). Statistical analyses included descriptive statistics, chi-square tests, and unadjusted odds ratios (ORs). Results: Of the 4,525 valid responses, 1,831 were self-reported by adolescents. Notable gender differences in mental health outcomes were identified, along with significant demographic predictors, such as age, single parenthood, parental mental health problems, and immigrant background. Negative effects were associated with reduced family climate and increased screen time, whereas physical activity showed beneficial effects. Proxy reports overestimated adolescents' mental health problems, whereas self-report tended to underestimate them. Conclusions: Persistent mental health problems and gender disparities high-light the need for a public health approach. This should include accessible support services, resili-ence building, targeted support for vulnerable families and gender-specific interventions.

The global steel industry is a major contributor to greenhouse gas emissions, and the adoption of green hydrogen in Direct Reduced Iron (DRI) production has the potential to significantly reduce CO2 emissions and support climate targets. This review explores the environmental, economic, technological, and social implications of using green hydrogen in DRI processes. The findings suggest that green hydrogen can reduce emissions by up to 90% compared to traditional methods, enhance energy security, and stimulate local economic development. However, high initial costs, energy efficiency concerns, and social acceptance issues remain significant barriers. The review also highlights the importance of integrating carbon capture and storage technologies, addressing logistical challenges, and considering the geopolitical implications of a shift towards green hydrogen. Green hydrogen presents a promising solution for decarbonising the steel industry but continued research, investment in infrastructure, and strategic planning are essential to overcome the challenges and drive widespread adoption.

Effective waste elimination is critical for the success of construction projects. Although several studies have focused on various aspects of construction waste, limited efforts have investigated the dynamic effect of Making-Do (MD) practices on productivity, rework, defects, and materials wastage. From a lean construction perspective, this study aims to address MD waste using the Last Planner System (LPS) and BIM. First, the casual structure that can cause MD in construction projects was expressed in a casual loop diagram (CLD), and thematic analysis uncovered the strategies of LPS-BIM to eliminate MD identified by reviewing the literature. Secondly, twenty-five strategies from the LPS and BIM strategies to address MD using Structural Equation Modeling (SEM) were assessed. Subsequently, a system dynamics model (SDM) for investigating LPS-BIM strategies on MD decisions in a construction project was formulated based on the underlying causal loop diagrams and the mathematical relations among the variables. Finally, the model was applied to three projects, and simulations for four LPS-BIM scenarios were carried out. The findings show that dynamic interactions among diverse production planning and control factors are critical in evaluating MD impacts on a construction project. The results demonstrate that the LPS-BIM approach resulted in an average 43.8% reduction in the tasks performed with MD, 45.3% of constraints, 66.5% of construction waste, increasing 13.7% completion rate, and 29.3% cost reduction, demonstrating that LPS-BIM as a more efficient solution for MD mitigation and construction planning.

Molecular dynamics simulations were performed to examine the impact of temperature (ranging from 250K to 350K) on the structural behavior of cellulose chains when dissolved in an aqueous cuprammonium hydroxide Cuam solvent system. By monitoring the root mean square deviation (RMSD) and radius of gyration (Rg) values at each temperature, we found that the geometric deformation of the cellulose chains changed significantly at T=300K. In contrast, Rg and RMSD values remained stable at temperatures in the range of 250K, 270K and the range of 330K, 350K. Calculating the interaction energy between the solvent and cellulose chains revealed that temperature significantly influences the cellulose dissolution process in the Cuam solvent system and that T=300K is an efficient temperature for its dissolution. The number of intra- and interchain hydrogen bonds was also calculated as a function of temperature, and the analysis confirmed that there is no breakage of these bonds at temperatures below 300 K (i,e: 250K, 270K) and above 310 K (I,e, : 330K and 350K) either between two native chains or between a native chain and another derivative.

Calcium sulphate (CS) is currently used as a bioabsorbable, completely synthetic and sterile material in the management of infected tissues and dead spaces (DS) mainly resulting from surgical procedures. Residual DS in the postoperative, may create an environment where hematomas fill up and bacteria can proliferate, leading to a high incidence of postoperative infections. Considering the available reviews in the literature, CS has been mainly studied in orthopedic surgery mostly giving brilliant results and low complication rates. Nowadays, orthopedists avail it in the form of pearls both as a bone void filler and as an “off-label” delivery agent for antibiotics in arthroplasty, chronic osteomyelitis and open fractures, paving the way of its application in many other contexts given its natural dis-position to biodegradation. In the last years, CS beads have been gaining ground in the general, vascular and endocrinological surgical specialties. Despite its clear potential and the increasing number of scientific evidences on the safety and effectiveness of CS application in the prophylaxis and treatment of infections, there are not many studies reporting on its application in fields other than orthopedics, with a substantial paucity in plastic and reconstructive surgery literature. This is some-how surprising, since reconstructive surgery often deals with complex wounds secondary to bone and soft tissue exposure, suture dehiscence, trauma, and surgical site infections. As far as we know this is the first updated systematic review assessing the state of the art, indications and new perspectives on the application of CS beads in plastic and reconstructive surgery.

The Epithelial-Mesenchymal-Transition (EMT) phenotype, identified as a significant clinical indicator in cancer, manifests as a biological process where cells transition from epithelial to mesenchymal characteristics. Physiologically, EMT plays a crucial role in tissue remodeling, promoting healing, repair, and responding to various tissue damages. This study investigates the impact of BNE-RRC on oral cancer cells (KB) and reveals its significant effects on cancer cell growth, migration, invasion, and EMT. BNE-RRC induces the epithelial-like morphology in KB cells, effectively reversing EMT to Mesenchymal-Epithelial Transition (MET). Extraordinarily, sustained culture of cancer cells with BNE-RRC for 14 days maintains an epithelial status even after treatment withdrawal, suggesting BNE-RRC as a potential therapeutic agent for cancer. These findings highligh the promise of BNE-RRC as a comprehensive therapeutic agent in cancer treatment by inhibiting cancer cell growth, migration, and invasion, while also orchestrating a reversal of the EMT process. The study proposes that BNE-RRC could be effective agent for cancer treatment.

The exploration of three-dimensional (3D) DNA structures marks a pivotal shift in genomics, offering unprecedented insights into the intricacies of cellular regulation, disease genesis, and the potential for novel diagnostic and therapeutic strategies. This study delves into the dynamic nature of 3D genome organization, investigating how these structures influence cellular functions in response to environmental changes and over time. Through a combination of real-time imaging and advanced computational models, we aim to unravel the complex interplay between 3D DNA structures, non-coding RNAs, and chromatin organization, and their collective impact on gene expression and cellular differentiation. A significant focus is placed on understanding the role of 3D DNA structures in the development and progression of genetic disorders. By employing comprehensive genomic and epigenomic profiling, this research seeks to identify structural aberrations linked to diseases, paving the way for the development of targeted diagnostics and therapies. Additionally, the study explores the potential of genome editing technologies, such as CRISPR-Cas systems, in correcting these structural abnormalities, while also addressing the ethical, legal, and social implications (ELSI) of such interventions. Integrating data from various genomic analyses, we propose the development of advanced computational models to predict the effects of 3D DNA structures on gene expression and cellular function. This integrative approach not only promises to enhance our understanding of genomic regulation but also sets the stage for groundbreaking advances in genomics-based diagnostics and therapeutics. The findings of this study have the potential to revolutionize our approach to treating genetic disorders, offering a new frontier in personalized medicine.

Antisense oligonucleotides (ASOs) are short oligodeoxynucleotides designed to bind to specific regions of target mRNA. ASOs can modulate pre-mRNA splicing, increase levels of functional proteins and decrease levels of toxic proteins. ASOs are being developed for the treatment of several diseases, including motor neuron diseases (MNDs), a group of neurodegenerative disorders characterised by the loss of motor neurons, including spinal muscular atrophy (SMA), amyotrophic lateral sclerosis (ALS) and spinal and bulbar muscular atrophy (SBMA). The biggest success has been the ASO known as nusinersen, the first effective therapy for SMA, able to improve symptoms and slow disease progression. Another success is tofersen, an ASO designed to treat ALS patients with SOD1 gene mutations. Both ASOs have been approved by the FDA and EMA. On the other hand, ASO treatment in ALS patients with the C9orf72 gene mutation did not show any improvement in disease progression. The aim of this review is to provide an up-to-date overview of ASO research in MND, from preclinical studies to clinical trials and, where available, regulatory approval. We highlight the successes and failures, underline the strengths and limitations of the current ASO research, and suggest possible approaches that could lead to more effective treatments.

Background. The markerless motion capture system (MLS) is a new technology that uses deep learning to detect body segments from digital images. This study tested the agreement between the MLS and a force-plate based system (FPS, “gold standard”) to quantify stability control and motor performance (MP) during gait initiation (GI). Methods. Healthy adults (young and elderly) and patients with Parkinson’s disease (PD) performed GI series at spontaneous and maximal velocity on an FPS while being filmed by an MLS. Signals from both systems were used to compute the peak of forward center-of-mass velocity (indicator of MP) and the braking index (BI, indicator of stability control). Results. Descriptive statistics indicated that both systems detected between-groups differences and velocity effects similarly, while a Bland-Altman (BA) plot anal-ysis showed that BI and MP mean biases were virtually zero in all groups and conditions. Bayes factor 01 indicated strong (for BI) and moderate (for MP) evidence that both systems provided equivalent values. However, trial-by-trial analysis of BA plots revealed the possibility of differ-ences > 10% between the two systems. Conclusion. Although non-negligible differences do occur, MLS appears to be as efficient as FPS in detecting PD and velocity condition effects on BI and MP

Understanding and predicting damage progression within thin plain-woven CFRP components is an essential issue for scheduling maintenance intervals and structural inspections, and typically require extensive test series. However, uncertainties always remain and result in conservative design and unnecessary downtimes due to the repeated inspections of a healthy structure. SHM can be used to reduce these uncertainties, as it allows to evaluate the condition of a mechanical structure during operation. Numerous SHM methods are developed , that achieve different levels of damage identification but are often investigated at small coupons with non-realistic structural damages and loading conditions on both, structure and sensor. The present research investigates the electrical impedance tomography (EIT) featuring an elastoresistive thin-film sensor to evaluate damage that propagates from a circular hole in a large plate under cyclic tensile-tensile multi-block loading. Applied fatigue loads were increased multiple times up to a total number of two million cycles. During the loading damage initiated at the hole and continuously propagated into the plate. Repeated EIT evaluations of the applied sensor and validating evaluations by means of digital image correlation clearly revealed the robustness of the hardware and the potential of the SHM method for damage evaluation of plain-woven CFRP components.

Irrational belief is a product of complex personality traits and Machiavellianism Intelligence. The present study is conducted to trace the significance of predictive nature of personality characteristics and Machiavellianism Intelligence (Mach Intelligence) on irrational beliefs among chronically ill older people. The research method is cross-sectional with correlational design, purposive sampling with a total of 200 chronically ill older people aged between 40–60 years with disease type such as Systemic lupus erythematosus, Complicated Diabetes, Glomerulonephritis and Chronic Heart Failure. The analysis revealed that personality characteristics and irrational belief subscales such as worrying, rigidity, problem avoidance and Mach Intelligence are significantly positively correlated; however, Emotional irresponsibility has significant negative correlation with personality characteristics and Mach Intelligence. Gender differences revealed that males are high on all the subscales of personality characteristics, irrational beliefs (except emotional irresponsibility) and Mach Intelligence as com-pared to female chronically ill older people. Predictive analysis also revealed that overall personality characteristics explained a total of 67% variance in irrational beliefs. Moreover, Mach Intelligence predicts irrational beliefs. Future health related recommendations should be planned accordingly.

Viruses rely on host cells to replicate their genomes and assemble new viral particles. Thus, they have evolved intricate mechanisms to exploit host factors. Host cells, in turn, have developed strategies to inhibit viruses, resulting in a nuanced interplay of co-evolution between virus and host. This dynamic often involves competition for resources crucial for both host cell survival and virus replication. Iron and iron-containing cofactors, including iron-sulfur clusters, are known to be a heavily battled resource during bacterial infections where control over iron can tug the war in favor of the pathogen or the host. It is logical to assume that viruses also engage in this competition. Surprisingly, our knowledge about how viruses utilize iron (Fe) and iron-sulfur (FeS) clusters remains limited. The handful of reviews on this topic primarily emphasize the significance of iron in supporting the host immune response against viral infections. The aim of this review, however, is to organize our current understanding of how viral proteins utilize FeS clusters, to give perspectives on what questions to ask next and to propose important avenues for future investigations.

This review is a first attempt at bringing together various concepts from research on wall- and magnetically-bounded turbulent flows. Brief reviews of both fields are provided: The main similarities identified are coherent (turbulent) structures, flow generation and transport barriers. Examples are provided and discussed.

The goal of this study was to evaluate the feasibility of methods based on the Worldwide Harmonized Light-Duty Vehicles Test Procedure Brake Cycle to measure brake wear particle emissions for currently used electrified vehicles. Our results indicated that reducing brake friction work reduced brake wear particle emissions. Commercially available, plug-in hybrid electric vehicles reduced emissions by 85% for PM₁₀, 78% for PM_2.5, and 87% for particle numbers (PNs) compared to vehicles with internal combustion engines. Brake friction work showed a linear relationship with PM₁₀ and PM_2.5. Nanoparticle PM emissions tended to increase slightly with regenerative braking, but did not contribute significantly to the overall PM percentage. the emission events of high number concentrations of nuclei mode particles (<20 nm in diameter) in electric vehicle brake assemblies designed for regenerative braking use under high-temperature, high-load braking conditions with full-friction brakes. The nuclei mode particles amplified the PN emissions and led to a high variability. In strict regulatory certification tests, where measurement reproducibility and stability are required, it is appropriate to measure PNs under brake conditions appropriate for the actual use of electric vehicles rather than under full-friction brake conditions or to remove particle measurements smaller than 20 nm.

ackground: The swift assimilation of Artificial Intelligence (AI) across multiple industries is altering the worldwide economic terrain. Unprecedented opportunities and difficulties are brought about by this revolutionary technology, which has an impact on innovation, trade, labor markets, and security. Objective: The goal of this study is to thoroughly investigate the economic effects of AI by exploring how it may affect labor markets, innovation, trade internationally, and security. The goal is to offer insights that support strategic decision-making and policy formation by examining current trends, opportunities, and difficulties. Results: The research highlights the dual character of artificial intelligence's influence, highlighting both its potential to spur economic expansion and its drawbacks, including the loss of jobs, a lack of standards, and security issues. The study highlights how crucial cooperation is to overcoming these obstacles and realizing AI's full potential. Conclusion: The balancing opportunities and risks becomes critical as AI continues to change the economic landscape. The report promotes proactive steps including ethical AI design guidelines, ongoing worker retraining, and flexible regulatory strategies. As we shape an AI future that puts inclusion, creativity, and responsible governance first, collaboration emerges as a key theme.

This study investigated co-constructed research poetry as a way to understand the lived experiences of people affected by rarer dementia and as a means to use poetry to convey those experiences to healthcare professionals. Using mixed-methods, 71 people living with rarer dementia and care-partners (stakeholders) contributed to co-constructing 27 poems with professional poets; stakeholders’ verbatim words were analysed with descriptive qualitative analysis. Stakeholders were also surveyed and interviewed about their participation. Healthcare professionals (n = 93) were surveyed to elicit their responses to learning through poetry and its acceptability as a learning tool. Poems conveyed a shared narrative of different aspects of lived experience, often owing to atypical symptoms, misunderstandings by professionals, lack of support pathways, and a continuous struggle to adapt. Stakeholder surveys indicated it was a valuable experience to both co-create and respond to the poems, whilst group interviews revealed people’s experiences of the research poetry were characterised by reflection on lived experience, curiosity and exploration. Healthcare professionals’ responses reinforced the poetry’s capacity to stimulate cognitive and affective learning specific to rare dementia support and prompt both empathy and critical thinking in practice. As the largest poetry-based study that we are aware of, this novel accessible approach of creating group poems yielded substantial information about the experiences and needs of those affected by rarer dementia and how poetry can contribute to healthcare education and training.

Metabolic dysfunction-associated fatty liver disease (MAFLD) has now affected nearly one third of global population and became the number one cause of chronic liver disease in the world because of the obesity pandemic. Chronic hepatitis resulting from hepatitis B virus (HBV) and hepatitis C virus (HCV) also remain significant challenges to liver health even in the 21st century. The coexistence of MAFLD and chronic viral hepatitis can markedly alter the disease course of individual diseases and can complicate the management of each of these disorders. Thorough understanding of the pathobiological interlink and interactions between MAFLD and these two chronic viral hepatitis infections are crucial for appropriate management of patients. We update these interlinks in this comprehensive clinical review.

Since the advent of the Internet, there has been a significant shift from wired to wireless communication between devices. The volume of data transmitted has surged, primarily driven by the exponential growth of network services, Internet of Things (IoT) devices, and online users. This trend became especially pronounced with the onset of the COVID-19 pandemic, as the Internet's role and significance expanded dramatically. People began to spend more time online, engaging in activities like e-learning, remote work, and online shopping. Concurrently, concerns about the security of wireless communication channels have escalated. As more data is stored and transmitted over the Internet, cybercriminals are actively seeking unauthorized access to it to further their malicious objectives. Through a comprehensive literature review in the realm of wireless network security and privacy, it has become evident that several factors render these networks susceptible to vulnerabilities. The aim of this paper is to shed light on the major and common security and privacy challenges faced by existing wireless networks. Additionally, it seeks to demonstrate the array of techniques available to mitigate these issues. Ultimately, this paper will culminate in an in-depth analysis of cybersecurity measures to address the issues in wireless networks.

The ever-evolving landscape of technology continually drives the demand for more robust and secure systems. Intrusion Detection and Prevention Systems (IPS) play a pivotal role in safeguarding digital infrastructures. IPS harnesses a blend of cutting-edge technologies, specifically Network-Based, Wireless-Based, and Host-Based Intrusion Detection Systems (IDS), to fortify network security. This multifaceted approach enhances the system's capacity to scrutinize incoming data and network traffic, effectively reducing the risk of intrusion. In the realm of malicious activity detection, IPS employs a diverse array of techniques and mechanisms. Our proposed IPS integrates both anomaly-based and signature-based analysis approaches. In signature-based analysis, intrusions are identified by matching data collected from various activities with pre-defined signatures, employing rule-based methods to detect anomalies effectively. In the anomaly-based analysis approach, the system juxtaposes current activities with a baseline of normal behaviour to flag any deviations. This is achieved through distance-based methods, ensuring a well-rounded approach to threat detection. Our comprehensive prevention system encompasses a suite of security measures, including anti-virus software, Deep Packet Inspection, and Quarantine. These components work in synergy to detect and thwart malicious activities effectively. Even when concealed or hidden, the IPS remains a reliable sentinel, ensuring the integrity of your digital ecosystem. This review delves into the intricate web of terminologies and concepts surrounding Intrusion Detection and Prevention Systems, shedding light on the evolving technology landscape and the critical role IPS plays in bolstering cybersecurity.

The persistence of geographic inequities in vaccination coverage often evidences the presence of zero-dose and missed communities and vulnerabilities to vaccine-preventable diseases. These inequities were exacerbated in many places during the COVID-19 pandemic, due to severe disruptions to vaccination services. Understanding changes in zero-dose prevalence and associated risk factors in the context of the COVID-19 pandemic is, therefore, critical to designing effective strategies to reach vulnerable populations. Using data from nationally representative household surveys conducted before the COVID-19 pandemic in 2018 and during the pandemic in 2021 in Nigeria, we fitted Bayesian geostatistical models to map the distribution of three vaccination coverage indicators: receipt of DTP1, MCV1 and any of the four basic vaccines (BCG, OPV0, DTP1 and MCV1), and corresponding zero-dose estimates independently at 1x1 km resolution and the district level during both time periods. We also explored changes in the factors associated with non-vaccination at the national and regional levels using multilevel logistic regression models. Our results revealed no increases in zero-dose prevalence due to the pandemic at the national level, although considerable increases were observed in a few districts. We found substantial subnational heterogeneities in vaccination coverage and zero-dose prevalence both before and during the pandemic, showing broadly similar patterns in both time periods. Areas with relatively higher zero-dose prevalence occurred mostly in the north and a few places in the south in both time periods. We also found consistent areas of low coverage and high zero-dose prevalence using all three zero-dose indicators, revealing areas in greatest need. At the national level, risk factors related to socioeconomic/ demographic status (e.g., maternal education), maternal access to and utilization of health services and remoteness were strongly associated with the odds of zero dose in both time periods, while those related to communication were mostly relevant before the pandemic. These associations were also supported at the regional level, but we additionally identified risk factors specific to zero dose in each region; for example, communication and cross-border migration in the northwest. Our findings can help guide tailored strategies to reduce zero-dose prevalence and boost coverage levels in Nigeria.

Regional anesthesia in postoperative pain management have developed in recent years, especially with the advent of fascial plane blocks. This study aims to compare the ultrasound-guided bilateral erector spinae plane block (ESPB) versus bilateral transversus abdominis plane block (TAPB) on postoperative analgesia after laparoscopic or robotic urologic surgery. This was a retrospective observational study; 97 patients (ESPB-group) received bilateral ultrasound-guided ESPB with 20 mL of ropivacaine 0.375% plus 0.5 mcg/kg of dexmedetomidine in each side at the level of T7-T9, and 93 patients (TAPB-group) received bilateral ultrasound-guided TAPB with ropivacaine 0.375% or 0.25%. The primary outcome was post-operative numeric rating scale (NRS) pain score, which was significantly lower in the ESPB-group on postoperative days 0, 2, and 3 (p=0.012, p=0.016 and p=0.004). Concerning the secondary outcomes, consumption of ropivacaine was significantly lower in ESPB-group (p<0.001) and the total amount of analgesic rescue doses was significantly lower in the ESPB-group than TAPB-group in postoperative days from 2 to 4 (1 vs 3, p>0.001). Incidence of postoperative nausea and vomiting was higher in the TAPB-group and no block related complications were observed. We conclude that ESPB provide better postoperative pain control with less consumption of local anesthetic and less total rescue analgesic therapies.

The development of mineral resources in China has gradually entered the stage of deep mining. Rock burst, collapse and other ground pressure disasters caused by deep high stress have become major hidden dangers restricting mine safety production. Microseismic monitoring technology is an important means of ground pressure risk prediction. In this paper, the wavelet coefficient threshold denoising method in time-frequency domain, STA/LTA method, AIC method, Skew and Kurtosis method are studied, and the automatic P-phase onset time picking model based on noise reduction and multiple detection indexes is established. Through the effect analysis of microseismic signals collected by microseismic monitoring system of coral Tungsten Mine in Guangxi, automatic P-phase onset time picking is realized. the reliability of the P-phase onset time picking method proposed in this paper based on noise reduction and multiple detection indexes is verified. The picking accuracy can still be guaranteed under the severe signal interference of background noise, power frequency interference and manual activity underground mine, Which is of great significance to the data processing and analysis of microseismic monitoring.

Fractional differential systems have received much attention in recent decades likely due to its powerful ability in modeling memory processes, which are mostly observed in real world. Fractional models have been widely investigated and applied in many fields such as physics, biochemistry, electrical engineering, continuum and statistical mechanics. It is shown by many researchers that fractional derivatives can provide more accurate models than integer order derivatives do. Obviously, bang-bang property is of a significant importance in optimal control theory. In this paper a Bang-Bang property and time-optimal control problem for time-Fractional Differential System (FDS) is under consideration. First we formulate our problem and we prove the existence theorem. We state and prove the bang-bang theorem. Finally we give the optimality conditions that characterized the optimal control. Some illustrate applications are given to clarify our results.

The main objective of this article was to evaluate the repercussions of the crises resulting from the COVID-19 pandemic and the war in Ukraine on changes in the European Union's reliance on energy raw material imports, particularly from Russia. Furthermore, several specific objectives were outlined: to ascertain the EU's energy balance and any alterations therein, to identify changes in the concentration of energy raw material imports among EU countries during the crises, to determine the level and fluctuations in energy raw material import dependence within the EU and individual member states throughout the crises, and lastly, to assess changes in the concentration of energy raw material imports from Russia in EU countries during the crises. The research encompassed all 27 EU Member States as of 31st December 2022, and the examination period spanned from 2010 to 2022. The information sources included relevant literature on the subject and data sourced from Eurostat. In conducting the analysis and presenting the data, several methodologies were employed, including descriptive, tabular, and graphical techniques. Additionally, quantitative measures such as the Gini structure concentration coefficient and concentration analysis through the Lorenz curve were utilized. During the COVID-19 pandemic, the EU experienced a slight reduction in dependence on energy raw material imports. However, this reduction was short-lived and mainly attributed to the decrease in energy demand caused by the pandemic. Conversely, the war in Ukraine had a substantial impact, leading to a notable surge in energy raw material imports as a result of stockpiling efforts and the need to safeguard against further disruptions in the energy market. Notably, the EU's reliance on energy imports from Russia was already considerable. Following the outbreak of the conflict in Ukraine, imports of oil, petroleum products, and solid fossil fuels experienced significant decline due to imposed sanctions. Nonetheless, restrictions on natural gas imports were comparatively less severe.

While human activities and climate change are threatening available natural ecosystems, targeted studies on the biological cycle, propagation, and cultivation of threatened species are crucial both for their conservation and sustainable exploitation. This study was designed to bridge extant research gaps regarding the vulnerable local endemic Campanula pelviformis, a wild edible green traditionally consumed in Crete (Greece) with agro-alimentary and medicinal interest as well as ornamental value. New knowledge was obtained on the abiotic environmental conditions prevailing in its wild habitats (natural distribution mapped in Geographical Information Systems and linked with open-source databases). We collected seeds from wild-growing populations (three lowland, two semi-mountainous), we tested their germination at four different temperatures (10, 15, 20 and 25oC) and under different light conditions (light/dark and darkness), and we performed fertilization trails [integrated nutrient management (INF), chemical fertilization (ChF), control] examining morphological and physiological characteristics, above- and below-ground macro- and micronutrients contents, as well as their phenol content and antioxidant capacity. There were population and temperature effects on seed germination and their interaction was statistically significant. Campanula pelviformis germinated better at 10 and 15 oC (&gt;85% for all populations) with no preference on light conditions (98.75% and 95% in light and dark conditions). The INF application increased root dry mass, chlorophyll content index and chlorophyll fluorescence compared to other treatments and was beneficial for macro- and micronutrients concentrations in above-ground parts compared to previously studied wild-growing material, while below-ground parts were positively impacted by both fertilization types. Total phenols and antioxidant capacity were both increased by ChF fertilization. The data furnished herein led to the re-evaluation and upgrade of the feasibility and the readiness timescale for its sustainable exploitation in different economic sectors.

People from Black and Asian backgrounds are more likely to die from Covid-19 but less likely to be vaccinated, threatening to exacerbate health inequalities already experienced by ethnic minority groups. Literature suggests that mistrust rooted in structural inequality may be a key barrier to Covid-19 vaccine uptake. We need to better understand how structural inequalities influence vaccine confidence. Understanding and addressing these processes is likely to lead to longer-term impacts than information alone. We draw on health and sociological theories of structure and agency to inform our understanding of structural factors. We conducted qualitative interviews and focus groups with 22 people from London and surrounding areas in December 2021 to March 2022. Fifteen participants were members of the public from ethnic minority backgrounds and 7 were professionals working with the public to address concerns and encourage vaccine uptake. Our findings suggest that people from ethnic minority backgrounds make decisions regarding Covid-19 vaccination based on a combination of how they experience external social structures (including political authority, social positioning and racial inequality) and internal processes (what they believe and understand about Covid-19 vaccines). We may be able to support knowledge accumulation through the provision of reliable and accessible information, particularly through primary and community care. But we recommend a number of changes to research, policy and practice which address structural inequalities. These include working with communities to improve ethnicity data collection, increasing funding allocation to health conditions where ethnic minority communities experience poorer outcomes, greater transparency and public engagement in the vaccine development process, and culturally adapted research recruitment processes.

Methane (CH4), produced endogenously in animals and plants, has recently been suggested to play a role in cellular physiology, potentially influencing the signaling pathways and regulatory mechanisms involved in nitrosative and oxidative stress responses. In addition, it has been proposed that supplementation of CH4 to organisms may be beneficial for the treatment of several diseases, including ischemia, reperfusion injury, and inflammation. However, it is still unclear if and how CH4 is produced in mammalian cells without the help of microorganisms, and how CH4 might be involved in physiological processes in humans. In this study, we provide first proof of the principle that CH4 is formed non-microbially in the human body by applying isotopically labeled methylated sulfur compounds, such as dimethyl sulfoxide (DMSO) and methionine, as carbon precursors to confirm cellular CH4 formation. A volunteer applied isotopically labeled (2H and 13C) DMSO on the skin, orally, and to blood samples. Monitoring of stable isotope values of CH4 convincingly showed the conversion of the methyl groups, as isotopically labeled CH4 was formed during all experiments. Based on these results, we consider several hypotheses about endogenously formed CH4 in humans, including physiological aspects and stress responses involving reactive oxygen species (ROS). While further and broader validation studies are needed, the results may unambiguously serve as a proof of concept for the endoge-nous formation of CH4 in humans by a radical-driven process. Furthermore, these results might encourage follow up studies to decipher the potential physiological role of CH4 and its bioactiv-ity in humans in more detail. Of particular importance is the potential to monitor CH4 as an ox-idative stress biomarker if the observed large variability of CH4 in breath air is an indicator for physiological stress responses and immune reactions. Finally, the potential role of DMSO as a radical scavenger to counteract oxidative stress caused by ROS might be considered in the health sciences. DMSO has already been investigated for many years, but its potential positive role for medical use remained highly uncertain.

This study investigates the efficiency of a biogas-powered cooling system through the utilization of energy and exergy calculations. Biogas, which can be generated and stored in small-scale plants as needed, serves as a viable fuel source for absorption cooling systems. The present research focuses on the biogas consumption of a triple-effect absorption cooling system, specifically designed to supply a fixed cooling load of 100 kW under varying operational conditions. The study highlights the COP (Coefficient of Performance) and ECOP (Exergetic Coefficient of Performance) values of the system, along with the exergy destruction rates of its individual components, at the optimal temperatures of operation. Furthermore, to determine the necessary biogas consumption, the study explores the establishment of dedicated farms for various animal species, ensuring an adequate number of animals for biogas production. The findings reveal a COP of 1.78 and an ECOP of 35.4% at the optimized operating temperatures. The minimum mass flow rate of biogas is determined to be 0.0034 kg/s, facilitating the operation of the boiler with a methane content of 65%. The study concludes that a total of 290 head of cattle is required to generate the annual biogas consumption necessary for the cooling system. Also, number of the cattle is enough to establish 284 biogas plants in Bursa province in Türkiye.

This study proposes a machine-learning-based framework for detecting mechanical damage in pipelines, utilizing physics-informed datasets collected from simulations for mechanical damage. The framework provides an effective workflow from dataset generation to damage detection and identification for three types of pipeline events: welds, clamps, and corrosion defects. While the study initially focused on optimizing the CNN structure using various advanced optimizers, it also investigated the impact of sensing systems on data classification and the effect of noise on classification performance. The study's analysis highlights the importance of selecting the appropriate sensing system for the specific application. The authors also found that the proposed framework is robust to experimentally relevant levels of noise, suggesting its applicability in real-world scenarios where noise is present. Overall, this study contributes to the development of a more reliable and effective method for detecting mechanical damage in pipelines. The proposed framework provides an effective workflow for damage detection and identification, and the findings on the impact of sensing systems and noise on classification performance add to its robustness and reliability.

Background: In this study, we aimed to evaluate the effect of s-FLT-1 and PlGF concentrations in women in the first trimester of pregnancy on the pulsatility index of the ductus venosus and the right and left uterine arteries. Methods: A total of 108 pregnant women in their first trimester were included in the study, with 87 assigned to the experimental group and 21 to the control group. Ultrasound examination were performed to measure the uterine artery pulsatility index, resistance index, ductus venosus pulsatility index, and blood sampling levels of biomarkers such as b-HCG; PAPP-A; s-FLT-1 and PlGF. Results: There was a significant negative relationship between PAPP-A concentration and the risk of fetal growth restriction, and a significant negative relationship between PlGF concentration and the risk of preeclampsia and fetal growth restriction in women in their first trimester of pregnancy. There was also a significant positive relationship between sFLT-1/PLGF ratio and the risk of developing preeclampsia. No significant relationships were found between the concentrations of biomarkers beta-HCG, PAPP-A, sFLT-1, PlGF, and any of the parameters PIUARt, PIUALt, Mean uterine arteries, and DVPI. Summary: In conclusion, this study did not find conclusive evidence to support the hypothesis that beta-HCG, PAPP-A, s-FLT-1, and PlGF concentrations in women in the first trimester of pregnancy have a significant effect on the Pulsatility Index of the ductus venosus and the Right and left Uterine Arteries. Further research is needed to investigate these potential associations.

The selection equation (replicator equation) has been independently discovered not only in various fields of biology (population genetics, ecology, prebiotic evolution, and sociobiology), but also in laser theory, where it accounts for the emergence of coherent light. Selection theory (replicator dynamics) is an ensemble theory, i. e., it describes the entire system rather than individual events, neglecting details in favor of a statistical view. However, the underlying processes at the individual level are well known in biology. For light quanta, this is not the case, because quantum theory says nothing about individual events. In the Copenhagen interpretation even the existence of causality on "quantum level" is denied. A large number of recent publications, however, makes this interpretation seem questionable.In the present paper, therefore, an attempt is made to describe the basic interactions between light and matter, as far as they are relevant for the emergence of coherent light in the laser (a photon pair interaction mediated by matter is postulated), and to apply replicator dynamics on this basis. Starting point are papers of A. Einstein about the interaction of light and matter as well as the photoelectric effect. Both theories are slightly modified. Furthermore, the double-slit experiment is investigated and finally the emergence of coherent light by density-dependent selection of photons of different phase in a laser-like model. The relationship between “mean fitness”, information content of the photon ensemble and the amplitude of the light is also analyzed.

Digital federated platforms and data cooperatives for secure, trusted and sovereign data exchange will play a central role in the construction industry of the future. With the help of platforms, cooperatives and their novel value creation, the digital transformation and the degree of organization of the construction value chain can be taken to a new level of collaboration. The goal of this research project was to develop an experimental prototype for a federated innovation data platform along with a suitable exemplary use case. The prototype is to serve the construction industry as a demonstrator for further developments and form the basis for an innovation platform. It exemplifies how an overall concept is concretely implemented along one or more use cases that address high-priority industry pain points. This concept will create a blueprint and a framework for further developments, which will then be further established in the market. The research project illuminates the perspective of various governance innovations to increase industry collaboration, productivity and capital project performance and transparency as well as the overall potential of possible platform business models. However, a comprehensive expert survey revealed that there are considerable obstacles to trust-based data exchange between the key stakeholders in the industry value network. The obstacles to cooperation are predominantly not of a technical nature, but of a competitive, predominantly trust-related nature. To overcome these obstacles and create a pre-competitive space of trust, the authors therefore propose the governance structure of a data cooperative model, which is discussed in detail in this paper.

Aerogel-based adsorbents present extraordinary sorption capacity for hexavalent uranium that can be as high as 8.8 mol kg–1 (2088 g kg–1). The adsorption data follow generally the Langmuir isotherm model and the kinetic data are better described by the pseudo-second-order kinetic model, which is associated with chemisorption. Evaluation of the thermodynamic data reveals that the adsorption is generally an endothermic, entropy-driven process (ΔHo, ΔSo > 0). Spectroscopic studies (e.g., FTIR, XPS) indicate that the adsorption is based on the formation of in-ner-sphere complexes between surface active moieties and the uranyl cation. Regeneration and uranium recovery by acidification and complexation using carbonate or chelating ligands (e.g., EDTA) have been found to be successful. The application of aerogel-based adsorbents to uranium removal from industrial processes and uranium-contaminated waste waters was also successful, assuming that these materials could be very attractive as adsorbents in water treatment and uranium recovery technologies. However, the selectivity of the studied materials towards hexavalent uranium is limited suggesting further development of aerogel materials which could be modified by surface derivatization with chelating agents (e.g., salophen, iminodiacetate) presenting high selectivity for uranyl moieties.

This research program investigated the effects of layer thickness (50 and 100 microns) on the microstructure and mechanical properties of electron beam powder bed fusion (EBPBF) additive manufacturing of Inconel 625 alloy. The as-built 50 and 100 micron layer thickness components were also heat treated at temperatures above 1100 oC, which produced a recrystallized grain structure containing annealing twins in the 50 micron layer thickness components, and a duplex grain structure consisting of islands of very small equiaxed grains dispersed in a recrystallized, large-grain structure containing annealing twins. The heat treated component microstructures and mechanical properties were compared with the as-built components in both the build direction (vertical) and perpendicular (horizontal) to the build direction. Vickers microindentation hardness (HV) values for the vertical and horizontal geometries averaged 227 and 220 for the as-built 50 and 100 micron layer components, and 185 and 282 for the corresponding heat treated components. The yield stress values were 387 MPa and 365 MPa for the as-built layer horizontal and vertical 50 micron layer geometries, and 330 MPa and 340 MPa for the as-built 100 micron layer components. For the heat treated 50 micron components, the yield stress values were 340 and 321 MPa for the horizontal and vertical geometries, and 581 and 489 MPa for the 100 micron layer components, respectively. The elongation for the 100 micron layer as-built horizontal components was 28% in contrast to 65% for the corresponding 100 micron heat treated layer components, an increase of 132% for the duplex grain structure. However, the coarse grains containing annealing twins and the equiaxed small grain islands in the duplex structure for the heat treated components contained continuous carbides in the grain boundaries, and this may indicate sensitization and a reduction in corrosion resistance. These findings point to the potential mechanical property advantage for heat treatment of Inconel 625 alloy 100 micron layer thickness components fabricated by EBPBF.

The paper discusses how joint damage and deterioration affect the seismic response of existing reinforced concrete frames with sub-standard beam-column joints. The available simplified modeling techniques are critically reviewed to propose a robust, yet computationally efficient technique for simulating the nonlinear behavior of substandard beam-column joints. Improvements over the existing models include simulation of the cyclic deterioration of joint stiffness and strength as well as pinching in the hysteretic response, implemented considering a deteriorating hysteretic rule. A fibre-section forced-based inelastic beam-column element is developed; considering improved material models and fixed-end rotation due to bond failure, rebars-slip and inelastic extension, to simulate the deteriorating cyclic behavior of existing pre-cracked beam-column members. For the assessment of frames with substandard exterior beam-column joints, a nonlinear model for the exterior joint is developed and validated through a full-scale quasi-static cyclic test performed on a substandard T-joint connection. The proposed model allows considering structural performance in risk assessment while accounting for true inelastic mechanisms at the joints.

The II law of thermodynamics is most often given in three supposedly equivalent formulations: two Clausius (I and II) and one Kelvin. The most general and indisputable entropy formulation belong to Clausius (II). The earlier Clausius I principle determines the natural direction heat flow between bodies at different temperatures. On the other hand, the Kelvin principle states that it is impossible to completely convert heat into work. The author argues that the Kelvin principle is a weaker statement (or more strictly non-equivalent) than Clausius I principle, and the latter is a weaker statement than Carnot principle, which is equivalent to Clausius II principle. As a result, the Kelvin principle and the Clausius I principle are not exhaustive formulations of the II law of thermodynamics. At the same time, it turns out that the Carnot principle becomes such a formulation. Apart from providing a complete set of proof and disproof, the author, indicates where the methodological errors were made in the alleged proof of the equivalence of the Kelvin principle and both Clausius principles.

Online digital mental health communities can contribute to users’ mental health positively and negatively. Yet the measurement of outcomes and impact relating to digital mental health communities is difficult to capture. In this paper we demonstrate the development of an online experience measure for a specific children and young people’s community inside a digital mental health service. The development is informed by three phases: (i) item reduction through Estimate-Talk-Estimate modified Delphi methods, (ii) user testing with participatory action research and (iii) a pilot within the digital service community to explore its use. Rounds of experts talks help to reduce the items. User experience workshops helped to inform the usability and appearance, wording, and purpose of the measure. Finally, the pilot results highlight completion rates, difference in scores for age and community roles and a preference to ‘relate to others’; as a mechanism of support. Outcomes frequently selected in the measure show the importance of certain aspects of the community, such as safety, connection, and non-judgment previously highlighted in the literature. Self-reported helpfulness scales like this one could be used as indicators of meaningful engagement within the community and its content but further research is required to ascertain its acceptability and validity. Phased approaches involving stakeholders and participatory action research enhances the development of digitally enabled measurement tools.

Traumatic spinal cord injury (SCI) elicits an acute inflammatory response which comprises numerous cell populations. It is driven by the immediate response of macro-phages and reactive M1 microglia, which triggers activation of genes responsible for the dysregulated microenvironment within the lesion site and in the spinal cord parenchyma immediately adjacent to the lesion. Recently published data indicate that microglia induces astrocyte activation and determines the fate of astrocytes. Conversely, astrocytes have the potency to trigger microglial activation and control their cellular functions. Here we review current information about the release of diverse signaling molecules (pro-inflammatory vs anti-inflammatory) in individual cell phenotypes (microglia, astrocytes, blood inflammatory cells) in acute and subacute SCI stages, and how they contribute to delayed neuronal death in a the surrounding spinal cord tissue which is spared and functional but reactive. In addition, temporal correlation in progressive degeneration of neurons and astrocytes and their functional interactions after SCI are discussed. Finally, the review highlight the time-dependent transformation of reactive mi-croglia (M1) and astrocytes (A1) into their neuroprotective phenotypes (M2a, M2c and A2) which are crucial for spontaneous post-SCI locomotor recovery. We also provide sug-gestions on how to increase functional outcome after SCI and discuss key therapeutic approaches.

A quantitative analysis of X-ray emission from an electron cyclotron resonance (ECR) plasma was performed to probe the spatial properties of electrons having energy for effective ionisation. A series of measurements were taken by INFN-LNS and ATOMKI, capturing spatially and spectrally resolved X-ray maps as well as volumetric emissions from argon plasma. Comparing the former with model generated maps (involving space-resolved phenomenological electron energy distribution function and geometrical efficiency calculated using ray-tracing MC routine) furnished information on structural aspects of the plasma. Similarly, fitting a model composed of bremsstrahlung and fluorescence to the volumetric X-ray spectrum provided valuable insight into the density and temperature of confined and lost electrons. The latter can be fed back to existing electron kinetics models for simulating more relevant energies, consequently improving theoretical X-ray maps and establishing the method as an excellent indirect diagnostic tool for warm electrons, required for both fundamental and applied research in ECR plasmas.

Sustaining learners’ motivation to keep learning has been concerned for over 60 years in education and SLA. Most research focusing on Japanese university students has contributed lots of theoretical and practical developments, but research focusing on motivations of non-traditional adult learners and those under 18-year-old to learn Chinese is still little even though previous research findings have proved age is one of the key variables influencing learning besides nationalities and Chinese language levels. In order to find an effective treatment for sustainable Chinese language learning in Japan, this study utilized a survey method to analyze the types of Japanese learners’ motivation to learn Chinese via analysis of a moment structures (AMOS), and to compare the differences of the motivation via one-way ANOVA. This study revealed that Japanese learners’ motivation to learn Chinese consists of eight common types, which are “instrumental motivation”, “personal orientation”, “identified regulation”, “Chinese cultural productions”, “integrating into Chinese community”, “external regulation”, “social responsibility”, and “Chinese for academic purposes”. Also, there are similarities and differences existing in the eight motivation types among the Japanese children, adolescents, (non-) traditional adult learners of Chinese as a foreign language (CFL). The findings contribute the understanding of motivation types and differences among the four aged Japanese learners to teachers of teaching Chinese to speakers of other languages (TCSOL), and to future research further exploring how differently aged Japanese learners can have and use a higher motivation as a main drive to learn Chinese language as a lifelong business.

Cross-border e-commerce is an opportunity for micro, small and medium sized enterprise (MSMEs) in developing countries. Based on a resource-based approach, this research studied how to support resource lacking enterprises with export marketing strategy. It dealt with actual business cases of Mongolian entrepreneurs trying to export Mongolian products to Korean market. Multiple source data including interviews, internal documents, and group discussions, were matched with theories to come up with strategies and validated by supporting organizations in Mongolia and Korea. The research suggests that MSMEs should rely on third party digital platforms rather than setting up their own. For product strtategy of the marketing mix, sellecting competitive product categories and supporting them adjusting to foreign markets and quality assurance is needed. For price strategy, loccally high priced products should use a price penetration strategy with a lower price compared to competing foreign products. For place strategy, supporting organizations should partner with exporters for collective delivery. For promotion strategy, they need to support the capacity of MSMEs enabling them to use digital marketing tools effectivly. These strategies were validated and adopted by supporting organizations in Monglia and Korea.

proposal for a fundamental theory is described in which classical and quantum physics as a representation of the universe as a gigantic dendrogram are unified. The latter is the explicate order structure corresponding to the purely number-theoretical implicate order structure given by p-adic numbers. This number field was zero-dimensional, totally disconnected, and disordered. Physical systems (such as electrons, photons) are sub-dendrograms of the universal dendrogram. Measurement process is described as interactions among dendrograms; in particular, quantum measurement problems can be resolved using this process. The theory is realistic, but realism is expressed via the the Leibnitz principle of the Identity of Indiscernible. The classical-quantum interplay is based on the degree of indistinguishability between dendrograms (in which the ergodicity assumption is removed). Depending on this degree, some physical quantities behave more or less in a quantum manner (versus classic manner). Ideologically, our theory is very close to Smolin’s dynamics of difference and Rovelli’s relational quantum mechanics. The presence of classical behavior in nature implies a finiteness of the Universe-dendrogram. (Infinite Universe is considered to be purely quantum.) Reconstruction of events in a four-dimensional space type is based on the holographic principle. Our model reproduces Bell-type correlations in the dendrogramic framework. By adjusting dendrogram complexity, violation of the Bell inequality can be made larger or smaller.

Background: The use of technology in paediatrics is increasing, and new health technology will change the way in which paediatric care is delivered in the future. This review is part of the Royal College of Paediatrics and Child Health Paediatrics 2040 project, which is developing a credible vision for the future of paediatrics in the UK. Aims: To summarise the impact of health technology on the delivery of paediatric care over the last ten years. To learn from existing technology use and make recommendations for future implementation. Methods: A search strategy was developed and two databases (Cochrane Library and PubMed) were systematically searched in August 2019 for relevant publications in English. Searches were limited to papers published between January 2009 and August 2019 (with further rapid review of papers published between September 2019 and November 2020). We included papers that studied young people up to the age of 24 or on those providing care for this population. A thematic synthesis of the data from the included studies was undertaken using seven domains of paediatric care. Results: 128 studies were included, grouped by domain of care. Most included studies were defined as digital (n=55) or communication (n=37). Studies looked at the different types of health technology used within different domains of care, including secondary and tertiary care (n=39), public health and prevention (n=29), and community (n=20). Studies were assessed on delivery of care outcomes using positive, negative, mixed and no effect. The most common outcomes reported were adherence and satisfaction. Discussion: This review highlights the growing importance of technology in delivering paediatric care. Six themes emerged: the importance of clear guidelines, continuity of care, confidentiality and privacy, digital poverty, using a personalised approach, and using technology to supplement rather than replace. In future, technology development should involve the end user throughout the design process.

Background. Epidemiological and clinical studies demonstrated that excessive salt intake causes severe hypertension and exacerbated organ derangement such as chronic kidney disease (CKD). In this study, we focused on evaluating histological and gene-expression findings in the kidney using stroke-prone spontaneously hypertensive rats (SHRSP) with high-salt intake and thromboxane A2/ prostaglandin H2 receptor (TPR) blocker ONO-8809. Methods. SHRSP aged 6 weeks were divided into three groups eating normal chow containing 0.4% NaCl, 2.0%NaCl, or 2.0%NaCl +ONO-8809 (0.6mg/kg p.o. daily). Histological analyses with immunohistochemistry and a gene-expression assay with a DNA kidney microarray were performed after 8 weeks. Results. The following changes were observed with high-salt intake. Glomerular sclerotic changes were remarkably observed in the juxtaglomerular cortex areas. ED1, MCP-1, nitrotyrosine, and HIF-1α staining areas were increased in the glomeruli and interstitial portion. Tbxa2r which encodes TPR, Prcp, and Car7 were significantly underexpressed in the kidney. The plasma 8-isoprostane level was significantly elevated, and was attenuated with ONO-8809 treatment. Conclusion. TXA2 and oxidative stresses exaggerated renal dysfunction in salt-loading SHRSP, and ONO-8809 as a TPR blocker suppressed these changes. Therefore, ONO-8809 is a candidate drug to prevent CKD for hypertensive patients associated with high-salt intake.

While current studies have focused on adoption and the relevant content of the app to become a decision support system, very few studies have focused on the farmer's intention and initial decision to adopt. Based on a survey of 394 smallholder farmers this study investigated Mexican farmers’ willingness to adopt an agricultural advice app. A Structural Equation Modelling approach, based on the Unified Theory of Acceptance and Use of Technology (UTAUT) was applied. To understand farmers’ adoption decision, extended constructs were studied (e.g. mastery-approach goals) along with farmers’ age and participation in an innovation hub. Results showed that the intention to adopt the app is predicted by how farmers believe that technical infrastructure exists and by the expectation of the farmers using the app to acquire new knowledge. The multi-group analysis revealed that performance expectancy is a relevant predictor of the intention to adopt, whereas the mastery-approach goal is relevant only for younger and farmers not connected to the innovation hub. The results may well be a baseline to research further suitable non-financial incentives for different farmers’ groups, then encourage initial adoption and enhance uptake. The findings are useful for practitioners and app developers designing digital decision support tools.

Height assignment is an important problem for satellite measurements of Atmospheric Motion Vectors (AMVs) that are interpreted as winds by forecast and assimilation systems. Stereo methods assign heights to AMVs from the parallax observed between observations from different vantage points in orbit while tracking cloud or moisture features. In this paper, we fully develop the stereo method to jointly retrieve wind vectors with their geometric heights from geostationary satellite pairs. Synchronization of observations between observing systems is not required. NASA and NOAA stereo-winds codes have implemented this method and we have processed large datasets from GOES-16, -17, and Himawari-8. Our retrievals are validated against rawinsonde observations and demonstrate the potential to improve forecast skill. Stereo winds also offer an important mitigation for the loop heat pipe anomaly on GOES-17 during times when warm focal plane temperatures cause infra-red channels that are needed for operational height assignments to fail. We also examine several application areas, including deep convection in tropical cyclones, planetary boundary layer dynamics, and fire smoke plumes, where stereo methods provide insights into atmospheric processes. The stereo method is broadly applicable across the geostationary ring where systems offering similar Image Navigation and Registration (INR) performance as GOES-R are deployed.

Research on the chemical mechanism and reciprocal behavior of the coronavirus relate to living organisms, engaging in the give and take of electrochemical mediators, is a very important, controversial and vital issue. What we should accept is the chemical identity of this scenario, and not preferably a characteristic of a biological system. This chemical reaction should be familiar, referring to the theory of chemical pathways involved in DNA/proteins in the body against aggressive guests (such as viruses). From the point of view of a chemist, this simple reaction is nothing more than an oxidation-reduction reaction (redox-stress signaling) which conducted and carried out by coronavirus in a biointerface medium. Thereby, oxidizing as well as reducing reagents should be very constructive, promoting development in such chemical process. We understand redox reactions as switchable thiol/disulfide exchanges (formation and cleavage of inherent disulfide bonds), then, we can hugely profit from redox-responsive nano-surfaces equipped with multiple new ionic and covalent interactions. This game-changing idea can substantiate by surface modified-nanoparticles to play powerful roles in synthesis of nano oxidizers as well as reducing agents in nanomedicine. Chemists and pharmacists must then explore new thoughts and present modern experiences/approaches of preparation nanoparticles and nanocomposites to create novel vaccines as well as coronavirus drugs. In this regard, this experience can also be so helpful for HIV/AIDS, which is caused by viruses.

The complexity of urban spatial configuration, which affects human-well being and landscape functioning, needs acquisition and 3d visualisation data to inform decision-making process better. One of the main challenges in sustainability research is to conceive spatial models which are capable of adapting to changes in scale and recalibrating the related indicators depending on the degree of detail and data availability. In this perspective, the inclusion of the third dimension into Urban Ecosystem Services (UES) assessment studies highlights the details of urban structure-function relationships, improves modelling and visualisation of data and impacts, aiding decision-makers to localise, assess and manage urban development strategies. The main goal of the proposed framework concerns mapping, evaluating and planning of the UES within a 3d-virtual environment to improve the visualisation of the spatial relationships among the services allocation and the urban fabric density.

Vitamin C is an essential nutrient that must be obtained through the diet in adequate amounts to prevent hypovitaminosis C and the potentially fatal deficiency disease scurvy. Global vitamin C status and prevalence of deficiency has not previously been reported, despite vitamin C’s pleiotropic roles in both non-communicable and communicable disease. This review highlights the global literature on vitamin C status and the prevalence of hypovitaminosis C and deficiency. Related dietary intake is reported if assessed in the studies. We also explore if global vitamin C status has changed over time. Overall, the review illustrates the shortage of high quality epidemiological studies of vitamin C status in many countries, particularly low- and middle-income countries. The available evidence indicates that vitamin C deficiency is common in low- and middle-income countries and not uncommon in high income settings. Further high quality studies are required to confirm these findings, including in the countries not yet represented, and to fully understand associations with a range of disease processes. Our findings suggest a need for interventions to prevent deficiency in a range of at risk groups and regions of the world.

Tumor growth, progression, and therapy resistance are crucial factors in the prognosis of cancer. Properties of three-dimensional tumor-like organoids (tumoroids) more closely resemble in vivo tumors compared to two-dimensionally cultured cells and are therefore effectively used for assays and drug screening. We here established a repurposed drug for novel anticancer research and therapeutics using a tumoroid-based screening system. We screened 6 pharmacologically active compounds by using an original tumoroid-based multiplex phenotypic screening system with matrix metalloproteinase 9 (MMP9) promoter-driven fluorescence reporter for the evaluation of both tumoroid formation and progression. The effects of one of the hit compounds were examined on tumor formation and progression in vitro and in vivo. Antiparkinson drug benztropine was the most effective compound uncovered by the screen. Benztropine significantly inhibited in vitro tumoroid formation, cancer cell survival, and MMP9 promoter activity. Benztropine also reduced the activity of oncogenic signaling transducers and trans-activators for MMP9, including STAT3, NF-κB, and β-catenin, and properties of cancer stem cells / cancer-initiating cells. Benztropine and GBR-12935 directly targeted the dopamine transporter DAT/SLC6A3, whose genetic alterations such as amplification were correlated with poor prognosis for cancer patients. Benztropine also inhibited tumor growth, circulating tumor cell (CTC) number, and rate of metastasis in a tumor allograft model in mice. In conclusion, we propose the repurposing of benztropine for anticancer research and therapeutics that can suppress tumor progression, CTC, and metastasis of aggressive cancers by reducing key pro-tumorigenic factors.

Parental stresses are normal responses to raising children. They are affected by stresses parents and children accumulate and bring to their interrelations. Background factors like economic difficulties or the relations between the parents may affect parental stresses as well as demographic and environmental factors like noise and access to urban parks. Most studies on parental stress are based on a verified psychological questionnaire. We suggest using frequency domain heart rate variability index (HRV) to measure parental stress enabling, by thus, the measurement of physiological aspects of stress and risk to health. Parental stress is measured as the difference between HRV accumulated at home while staying with the children and without the husband and HRV measured in the neighborhood while staying without the children and the husband. We use the index to compare differences among Muslim and Jewish mothers in exposure to maternal stress at their homes and to expose the factors that predict differences in maternal stress. We found that Muslim mothers suffer from home-related maternal stress while Jewish mother do not. Number of children and ethnically related environmental aspects predict differences in maternal stress between Muslim and Jewish mothers. Muslims' lower access to parks stems from lack of home garden and parks in their neighborhoods in the Arab towns but mainly by restrictions on Muslim women's' freedom of movement to parks. Despite differences in levels of noise at home and in the status of the mother in the household, these factors did not predict differences in parental stress. Instead, the study highlights the crucial role of greenery and freedom of movement to parks in moderating home-related maternal stress.

In recent years, demand has been increasing for target detection and tracking from aerial imagery via drones using onboard powered sensors and devices. We propose a very effective method for this application based on a deep learning framework. A state-of-art embedded hardware system empowers small flying robots to carry out the real-time onboard computation necessary for object tracking. Two types of embedded modules were developed: one is designed using a Jetson TX or AGX Xavier, and the other is based on an Intel Neural Compute Stick. These are suitable for real-time onboard computing power on small flying drones with limited space. A comparative analysis of current state-of-art deep-learning-based multi-object detection algorithms was carried out utilizing the designated GPU-based embedded computing modules to obtain detailed metric data about frame rates as well as the computation power. We also introduce an effective target tracking approach for moving objects. The algorithm for tracking moving objects is based on the extension of simple online and real-time tracking. It was developed by integrating a deep-learning-based association metric approach (Deep SORT), which uses a hypothesis tracking methodology with Kalman filtering and a deep-learning-based association metric. In addition, a guidance system that tracks the target position using a GPU-based algorithm is introduced. Finally, we demonstrate the effectiveness of the proposed algorithms by real-time experiments with a small multi-rotor drone.

This work discusses laboratory measurements of atomic and diatomic molecular species in laser-plasma generated in gases. Noticeable self-absorption of the Balmer series hydrogen alpha line occurs for electron densities of the order of one tenth of standard ambient temperature and pressure density. Emission spectra of selected diatomic molecules in air or specific gaseous mixtures at or near atmospheric pressure reveal minimal plasma re-absorption. Abel inversion of the plasma in selected gases and gas mixtures confirm expansion dynamics that unravel regions of atomic and molecular species of different electron temperature and density. Time resolved spectroscopy diagnoses self-absorption of hydrogen alpha and hydrogen beta lines in ultra-high pure hydrogen gas. Radiation from a Nd:YAG laser device induces micro-plasma for pulse widths in the range of 6 ns to 14 ns, energies in the range of 100 mJ to 800 mJ, and for peak irradiance of the order 1 to 10 TW/cm². Atomic line profiles yield electron density and temperature from fitting of line profiles to wavelength and sensitivity corrected spectral radiance data. Analysis of measured diatomic emission data yields excitation temperature of primarily molecular recombination spectra. Applications of the laboratory experiments extend to investigations of stellar astrophysics white dwarf spectra.

Water electrolysis provides efficient and cost-effective production of hydrogen from renewable energy. Currently, the oxidation half-cell reaction relies on noble-metal catalysts, impeding widespread application. In order to adopt water electrolyzers as the main hydrogen production systems, it is critical to develop inexpensive and earth-abundant catalysts. This review discusses the proton exchange membrane (PEM) water electrolysis (WE) and the progress in replacing the noble-metal catalysts with earth-abundant ones. Researchers within this field are aiming to improve the efficiency and stability of earth-abundant catalysts (EACs), as well as to discover new ones. The latter is particularly important for the oxygen evolution reaction (OER) under acidic media, where the only stable and efficient catalysts are noble-metal oxides, such as IrO_x and RuO_x. On the other hand, there is significant progress on EACs for the hydrogen evolution reaction (HER) in acidic conditions, but how many of these EACs have been used in PEM WEs and tested under realistic conditions? What is the current status on the development of EACs for the OER? These are the two main questions this review addresses.

Ecklonia cava (E.cava) can alleviate vascular dysfunction in diseases associated with poor circulation. E. cava contains various polyphenols with different functions, but few studies have compared the effects of these polyphenols. Here, we comparatively investigated four major compounds present in an ethanoic extract of E. cava. These four major compounds were isolated and their effects were examined on monocyte-associated vascular inflammation and dysfunctions. Pyrogallol-phloroglucinol-6,6-bieckol (PPB) significantly inhibited monocyte migration in vitro by reducing levels of inflammatory macrophage differentiation and of its related molecular factors. In addition, PPB protected against monocyte-associated endothelial cell death by increasing the phosphorylations of PI3K-AKT and AMPK, decreasing caspase levels, and reducing monocyte-associated vascular smooth muscle cell proliferation and migration by decreasing the phosphorylations of ERK and AKT. The results of this study show that four compounds were effective for reduction of monocyte-associated vascular inflammation and dysfunctions, but PPB might be more useful for the treatment of vascular dysfunction in diseases associated with poor circulation.

Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application in unsupervised, complex multidimensional problems which cannot be solved using traditional deterministic algorithms. The canonical particle swarm optimizer is based on the flocking behavior and social co-operation of birds and fish schools and draws heavily from the evolutionary behavior of these organisms. This paper serves to provide a thorough survey of the PSO algorithm with special emphasis on the development, deployment and improvements of its most basic as well as some of the very recent state–of-the-art implementations. Concepts and directions on choosing the inertia weight, constriction factor, cognition and social weights and perspectives on convergence, parallelization, elitism, niching and discrete optimization as well as neighborhood topologies are outlined. Hybridization attempts with other evolutionary and swarm paradigms in selected applications are covered and an up-to-date review is put forward for the interested reader.

Rapid and extensive urbanization has adversely impacted humans and ecological entities in the recent decades through a decrease in surface permeability and the emergence of urban heat islands (UHI). While detailed and continuous assessments of surface permeability and UHI are crucial for urban planning and management of landuse zones, they have mostly involved time consuming and expensive field studies, and single sensor derived large scale aerial and satellite imageries. We demonstrated the advantage of fusing imageries from multiple sensors for landuse and landcover (LULC) change assessments as well as for assessing surface permeability and UHI emergence in Tirunelveli, Tamilnadu, India. Cartosat-2 and Landsat-7 ETM+ imageries from 2007 and 2017 were fused and classified using a Rotation Forest (RF), while surface permeability and temperature were quantified using Soil-Adjusted Vegetation Index (SAVI) and Land Surface Temperature (LST) index, respectively. Fused images exhibited higher classification accuracies than non-fused images, i.e. overall kappa coefficient values 0.83 and 0.75, respectively. We observed an overall increase of 20 km2 (45%) in the coverage of urban (dry, real estate plots and built-up) areas, while a decrease of 27 km2 (37%) for vegetated (cropland and forest) areas in Tirunelveli between 2007 and 2017. The SAVI values indicated an extensive decrease in surface permeability for Tirunelveli overall (0.4) and also for almost all LULC zones. The LST values exhibited an associated overall increase (1.30C) of surface temperature in Tirunelveli with the highest increase (2.40C) for urban built-up areas between 2007 and 2017. The SAVI-LST combined metric depicted the Southeastern built-up areas in Tirunelveli as a potential UHI hotspot, while a caution for the Western riparian zone for UHI emergence in 2017. Our results provide important metrics for surface permeability and UHI monitoring, and inform urban and zonal planning authorities about the advantages of satellite image fusion.

Drug functionalization through formation of hydrophilic groups is the norm in phase I metabolism of drugs for modification of drug action. The reactions involved are mainly oxidative catalyzed mostly by CYP isoenzymes. The benzene ring, as phenyl or fused with other rings, is the most common hydrophobic pharmacophoric moiety in drug molecules. On the other hand the alkoxy group (mainly methoxy) bonded to the benzene ring assumes an important and sometimes essential pharmacophoric status in some drug classes. Upon metabolic oxidation, both moieties, i.e. the benzene ring and the alkoxy group, produce hydroxy groups; the products are arenolic in nature. Through a pharmacokinetic effect, the hydroxy group enhances the water solubility and elimination of the metabolite with the consequent termination of drug action. However, through hydrogen bonding, the hydroxy group may modify the pharmacodynamics of the interaction of the metabolite with the site of parent drug action (i.e. the receptor). Accordingly, the expected pharmacologic outcome will be enhancement, retaining, attenuation, or loss of activity of the metabolite relative to the parent drug. All the above issues have been presented and discussed in this review using selected members of different classes of drugs with inferences regarding mechanisms, drug design and drug development.

Due to the complexity, high-risk, and conservative character of construction companies, advanced digital technologies do not become widely adopted in the short term, while vendors make determined efforts to overcome this and disseminate their technologies. This paper presents the methods of an investigation addressing the extremely complex issues related to the current practices of digital technology adoption in construction. It discusses how construction companies follow a specific logical process linked to need, project objectives, characteristics of the adopting organization, and the characteristics of the new technology to be adopted. The study aims to demonstrate a novel method of data collection and analysis including data and methodological triangulation techniques including the use of NVivo and AHP to explore how companies make the decision to uptake a new technology (e.g. advanced crane, tunnel boring machine or drones) by focusing on customer and vendor activities, their interactions, contributing factors, and people involved in the process. The major original contribution of this paper is to develop an innovative methodological Cube for investigating the Construction Technology Adoption Process (CTAP) covering technology adoption, acceptance, diffusion and implementation concepts. CTAP is a framework that delineates the phases of the process that customer organizations use when deciding to adopt a new digital technology and the parallel vendor activities. The significance of these contributions is that they enable vendors to understand how to match their strategies with customer expectations in each phase of the CTAP. It also provides a benchmark for new construction companies to use the current best practice of decision making. Future research is warranted to more clearly delineate any differences with developing nations or related industries such as mining and property management.