An association of food sources with odors prominently guides foraging behavior in animals. To understand the interaction of olfactory memory and food preferences, we used glucose-averse (GA) German cockroaches. Multiple populations of cockroaches evolved a gustatory polymorphism where glucose is perceived as a deterrent and enables GA cockroaches to avoid eating glucose-containing toxic baits. Comparative behavioral analysis using an operant conditioning paradigm revealed that learning and memory guide foraging decisions. Cockroaches learned to associate specific food odors with fructose (phagostimulant, reward) within only a 1 hr conditioning session, and with caffeine (deterrent, punishment) after only three 1 hr conditioning sessions. Glucose acted as reward in wild type (WT) cockroaches, but GA cockroaches learned to avoid an innately attractive odor that was associated with glucose. Olfactory memory was retained for at least 3 days after three 1 hr conditioning sessions. Our results reveal that specific tastants can serve as potent reward or punishment in olfactory associative learning, which reinforces gustatory food preferences. Olfactory learning therefore reinforces behavioral resistance of GA cockroaches to sugar-containing toxic baits. Cockroaches may also generalize their olfactory learning to baits that contain the same or similar attractive odors even if they do not contain glucose.

Based on hospital capacities, facts from past experience with the coronavirus disease 2019 (COVID-19) virus and the number of dark infections during the second wave (DII = 2D2), a reasonable limiting value of 140/D2 for the 7-day incidence per 100,000 persons (MSDIHT) and a second wave herd immunization threshold fraction value of 0.26 in Germany were calculated. If the MSDIHT is held below this limiting value, the German hospital system can cope with the number of new seriously infected persons without any triage decisions. On the basis of the SIRV epidemics model, the classical threshold values for herd immunization were calculated for 18 countries. For these countries, the dates regarding when herd immunization against the second COVID-19 wave will be reached were estimated

Flexible implementations of Monte Carlo Tree Search (MCTS), combined with domain specific knowledge and hybridization with other search algorithms, can be a very powerful for the solution of problems in complex planning. We introduce mctreesearch4j, a standard MCTS implementation written as a standard JVM library following key design principles of object oriented programming. We define key class abstractions allowing the MCTS library to flexibly adapt to any well defined Markov Decision Process or turn-based adversarial game. Furthermore, our library is designed to be modular and extensible, utilizing class inheritance and generic typing to standardize custom algorithm definitions. We demon- strate that the design of the MCTS implementation provides ease of adaptation for unique heuristics and customization across varying Markov Decision Process (MDP) domains. In addition, the implementation is reasonably performant and accurate for standard MDP’s. In addition, via the implementation of mctreesearch4j, the nuances of different types of MCTS algorithms are discussed.

Protected areas, such as natural World Heritage sites, RAMSAR wetlands, and Biosphere reserves are ecosystems within landscapes. Each site meets certain criteria that allow it to qualify as heritage or protected. Both climate change and human influence (e.g., incursion, increased tourist visitation) are altering biophysical conditions at many such sites. As a result, conditions at many sites are falling outside the criteria for their original designation. The alternatives are to change the criteria, remove protection from the site, change site boundaries such that the larger or smaller landscape meets the criteria, or manage the existing landscape in some way that reduces the threat. This paper argues for adaptive heritage, an approach that explicitly recognizes changing conditions. We discuss the need to view heritage areas as parts of a larger landscape, and to take an adaptive approach to management of that landscape. We offer five themes of adaptive heritage: 1) treat sites as living heritage, 2) employ innovative governance, 3) embrace transparency and accountability, 4) invest in monitoring and evaluation, and 5) manage adaptively. We offer the Australian Wet Tropics as an example where aspects of adaptive heritage currently are practiced, highlighting the tools being used. This paper offers guidance supporting decisions about natural heritage in the face of climate change and non-climatic pressures. Rather than delisting or lowering standards, we argue for adaptive approaches.

Using Directed Transfer Function (DTF) and Partial Directed Coherence (PDC) in their information version, this paper extends their theoretical framework to incorporate instantaneous Granger Causality (iGC)’s frequency domain description into a single unified perspective. We show that standard vector autoregressive models allow portraying iGC’s repercussions associated with Granger Connectivity where interactions mediated without delay between time series can be easily detected.

This paper analyzes the main variables which determines the relation between disinformation and the youth responsibility during the last stage of Covid-19 pandemic in Spain. The document presents relevant results on this subject. At the Introduction the reader will find the theoretical framework of the following concepts: disinformation, responsibility, credibility, and youth responsibility variables. The greatest interest, considering the authors specialization, falls in communication factors. The methods applied had been the reference review of the literature found about this subject, as well as a qualitative opinion research through discussion groups with young University students from Communication Schools in Madrid, both public and private. This recent study, held in June 2021, provide a very rich material for this paper. The main results and findings are the facts of being not satisfied with the information received about Covid-19; the knowledge about their most credible sources; the connection between information and responsibility, and some of the solutions said by youth to be more responsible in this context. As a conclusion, this paper confirms the first hypothesis of considering the disinformation as a variable which causes the lack of youth responsibility. Regarding the second hypothesis it is checked that young people consider communication as a solution for being more responsible.

Complex biological systems consist of large numbers of interconnected units, characterized by emergent properties such as collective computation. In spite of all the progress in the last decade, we still lack a deep understanding of how these properties arise from the coupling between the structure and dynamics. Here, we introduce the multiscale emergent functional state, which can be represented as a network where links encode the flow exchange between the nodes, calculated using diffusion processes on top of the network. We analyze the emergent functional state to study the distribution of the flow among components of 92 fungal networks, identifying their functional modules at different scales and, more importantly, demonstrating the importance of functional modules for information content of networks, quantified in terms of network spectral entropy. Our results suggest that the topological complexity of fungal networks guarantees the existence of functional modules at different scales keeping the information entropy, and functional diversity, high.

This paper presents an analysis of linear viscous stress Favre-Averaged turbulence models for computational fluid dynamics (CFD) of fully turbulent round jets with a long straight tube geometry in the near field. Although similar work has been performed in the past with very relevant solutions, considerations were not given for the issues and limitations involved with coupling between an Eulerian and Lagrangian phase, such as in fully two-way coupled CFD-DEM. These issues include limitations on solution domain, mesh cell size, wall modelling, and momentum coupling between the two phases in relation to the particles size. Therefore, within these considerations, solutions are provided to the Navier-Stokes equations with various turbulence models using a three-dimensional wedge long straight tube geometry for fully developed turbulence flow. Simulations are performed with a Reynolds number of 15000 and 50000 using two different tube diameters. It is found that a modified k−ε turbulence model achieved the most agreeable results for both the velocity and turbulent flow fields between these two flow regimes, while a modified k−ω SST/BSL also provided suitable results.

This article presents, for the first time, the kinetics and the general conversion features of a 3-component system, BT(BC)/iodonium/Amine, based on proposed mechanism of Liu et al, for both free radical polymerization (FRP) of acrylates and the free radical promoted cationic polymerization (CP) of epoxides using the new multi-functional initiator of benzophenone–triphenylamine (BT). The additives, iodonium and EDB, have the dual function of (i) regeneration BT and (ii) produce of extra radicals for improved FRP and CP. Analytic formulas are developed to explore the new features including: (i) the conversion efficacy (CE) of FRP is an increasing function of the light intensity, the effective absorption coefficient, and the concentration sum of each of the components, BT, Iod, amine, for transient state. However, CE at steady-state is independent to the light intensity; (ii) the trifunctional hybrid structures of BT3 leads to larger light absorption than other types of BT; it also provides more active sites for the H-abstraction in the presence of EDB, leading to high CE; (iii) the efficacy of FRP is an increasing function of the amine (EDB) concentration, in contrast to that of CP having an opposite dependence; (iv) the consumption rate of BT3 in the BT3/ Iod/EDB system is slower than that of the BT3/Iod system due to photoredox catalytic cycle, and the larger initiator regeneration (RGE)
in the three-component system. A comprehensive model is also proposed that the CE (for both FRP and CP) is governed by (N_jK_jbI), whereas more complex formulas are developed; where Kj is an effective rate constant proportional to the electron transfer quantum yield, and the combined effects of other coupling rate constants; b is an effective absorption coefficient given by the light absorption and excited state quantum yield.

History is part of the social sciences or humanities. In history, it studies events in the past which also determine what happens in the present and the future. With history, we can find out events and incidents in the past by reading books or by watching movies. Historical science provides many benefits for all circles. However, in this 21st century, which is a modern era, history is less desirable among millennials for various reasons. The purpose of writing this paper, the first is to find out what are the benefits of historical science in this millennial era, the second is to find out whether history is in demand or not among millennials, then what is the benefit of history in this millennial era. The third is to find a solution related to historical science learning so as not to be boring while maintaining its benefits. This research is to solve a common problem among millennials, namely whether millennials are interested in studying history and what can increase millennial interest in studying history. Researchers collect data to compile this paper with a qualitative method, which is to collect the latest journals for reference between 2019 and 2021 which are related to the urgency of 21st-century history for millennials. In addition, the researchers also looks for the latest data related to interest in studying historical science which is used to find out whether history is in demand or not among millennials. Thus, this research can find out what causes millennials to be less interested in history and find a solution, namely by using film media to increase millennial interest. This article is very useful in providing information about the urgency of learning history in the 21st century so that readers can use this article as material to conduct further research on this matter. As for this research, it has limitations, namely this research is only limited to millennials in relation to the urgency of historical science.

This article aims to examine the concept of historical thinking by looking at the development of historical learning from colonialism to reformation, as well as some examples of innovations in history learning through technology media. The development of history learning in Indonesia has a long story from the colonialism era to the reformation that changed from time to time. However, changes and reforms in the education system do not make students more interested in history. The 21st century, known as the digital century, makes students' attention more focused on the present and the development of the times. Therefore, there are many innovations that are in line with technological media to support and maintain history learning in this era. The question from this research is how is history learning not favored by students when technological innovations to support this learning have developed? By using the literature review method and a qualitative approach, this article provides a new perspective through existing data. Because innovation cannot run effectively before it is accompanied by historical thinking, so the results of the research are historical thinking must be instilled from the start to support innovations that develop and attract students' interest. Based on the study, it is recommended that have historical thinking to further optimize technology develops innovation more effectively and ask for more interest in history. Keywords: 21st Century, Historical Development, Paradigm

In modern times like today, technology and science are developing very fast. This has resulted in a condition known as globalization. This era has had a significant impact on every country globally, including in Indonesia, such as the spread of culture is solid. This flow has many benefits and advantages. However, this globalization can also have a negative impact. One of them is the erosion of native Indonesian culture compared to foreign cultures. Therefore, this research to find the origin, causes, and impacts of the influx of cultural globalization on the current culture of East Java because it is the province of origin of the researchers. Here the researchers asks about the impact of this modern culture and how influential culture is to the people of East Java. The method used by the researchers in making this paper is Literature Review using qualitative descriptive writing with quantitative data. The researchers findings as material in this paper amounted to 24 materials with the provisions of 20 journal article materials, 2 article materials online provided that they were published in the last three years, and 2 E-books for methods on this paper. This study's boundaries are a modern culture that the researchers takes about western culture (western) and South Korean culture (Hallyu). In addition, this study only discusses cultures originating in East Java, such as Javanese.

The article discusses the issues related to the safety of transport of dangerous goods by road. Research on accidents in transport unambiguously points to the human factor, which is most responsible for causing the accident. Determining the causes of driver unreliability in the hu-man-vehicle-environment system requires thorough research. Unfortunately, in this case, experimental research with human involvement is limited in scope. This leaves modeling and simulation of the behavior of the human factor, i.e., the driver transporting dangerous goods. The human being, due to its complexity, is a challenging element to parameterize. The literature presents various attempts to model human actions. In their work, the authors used heuristic methods, specifically fuzzy set techniques, to build a human factor model. In these models, human actions were specified using a verbal or linguistic description. The specificity of fuzzy sets allows to "naturally" limit the "precision" in describing human behavior. The model was built based on the author's questionnaire and expert research, based on which individual features were selected. Then, the traits were assigned appropriate states. The output parameter of the model is λL - the intensity of human error. The obtained values of the intensity of the accident caused by the driver's error were implemented into the author's method of risk assessment. They constituted one of the factors determining the probability of an accident in the transport of dangerous goods, which allowed to determine the optimal route of transport of these goods characterized by the lowest risk of an undesirable event on the route. The article presents the model's assumptions, structure, and features included in the model, which have the most significant influence on shaping the intensity of human error. The results of the simulation studies showed a diversified effect of the analyzed characteristics on the driver's efficiency.

Background: The rapid flow of globalization makes the world free from barriers so that the existence of globalization gives birth to a new concept of "World Without Borders". This situation puts the character of millennials on the brink of collapse and needs to be straightened out. Based on the problems above, the researcher determines the question: How is the role of civic education in shaping millennial character in the era of globalization? Purpose: The purpose of this study is to determine the impact of the current globalization on society, as a form of knowledge of the importance of citizenship education as a shield in the era of globalization, knowing the role of civic education in shaping the character of the millennial generation. Method: The method used in this research is literature review. The search for journals was carried out using the google scholar database with the keywords “citizenship educations”, “millennial generation”, and “globalization”. Feasibility studies are assessed based on title, abstract, and full text. Data analysis using qualitative analysis based on research findings. Results: The results of this study show the influence of globalization causes character problems in millennials increasing every year. The high nature of individualism, consumerism, and westernization shows the characteristics of Indonesia began to erode and eventually also impacted the moral damage. Therefore, prevention is necessary through citizenship education as the basis for character formation by the values of Pancasila.

Precipitation gauges are critical for measuring precipitation rates at regional and global scales and are often used to calibrate precipitation rates estimated from other instruments such as satellites. However, precipitation measured at the gauges is affected by gauge-undercatch that is often larger for solid precipitation. In the present work, two popular gauge-undercatch correction factors are assessed: one utilizes a dynamic correction model and is used in the Global Precipitation Climatology Centre (GPCC) Monitoring product and the other one employs a fixed climatology and is used in the Global Precipitation Climatology Project (GPCP) product. How much the choice of correction factors can impact the total estimate of precipitation was quantified over land at seasonal, annual, regional, and global scales. The correction factors are also compared as a function of the environmental variables used in their development, among those are near-surface air temperature, relative humidity, wind speed, elevation, and precipitation intensity. Results show that correction factors can increase the annual precipitation rate based on the gauges by ~9.5 % over the global land (excluding Antarctica), although this amount can vary from ~6.3% (in boreal summer) to more than 10% (in boreal winter), depending on the season and the method used for gauge-undercatch correction. Annual variations of correction factors can also be large, so the use of the fixed climatology correction factors requires caution. Given their magnitudes and differences, selection of appropriate correction factors can have important implications in refining the water and energy budget calculations.

Background:Boom in nanotechnology in current era has sketched unforeseen transformations in number of fields, such as medicine, health care, food, space, agriculture, etc. The synthesis of nanoparticles with different chemical compositions, sizes, shapes and controlled disparities is an important area of research in this field. Over the last decade, the biosynthesis of metal nanoparticles has received considerable attention due to their unusual and fascinating properties, with various applications, over their bulk counterparts.Hypothesis: The nanoparticle can have huge application in the field of food, pharmaceutical, and cosmetic industries and thus become a major area of research. Green synthesis of zinc oxide nanoparticles (ZnO NPs) using plant extracts offers an eco-friendly and promising substitute to the conventional methods of chemical synthesis. Conclusion: In the arena of nanoparticle phytosynthesis, novel materials have been produced that are eco-friendly, cost-effective and stable. In the current situation, nanotechnology inspires progress in all spheres of life, and therefore the phytosynthetic path of nanoparticle synthesis has emerged as a safe and best alternative to conventional methods. This review summarizes the recent work in the field of zinc nanoparticle phytosynthesis and critically discusses the mechanism proposed behind it.

Delay-tolerant networks (DTN) is an approach to deal with scarce network connectivity found in sparse mobile ad-hoc networks (MANETs) which makes the problem of routing messages a challenging task. DTNs have find their usefulness in many challenging environments such as tactical networks, underwater sensor networks, wildlife monitoring, disaster recovery etc. Pocket Switched Networks (PSNs) have emerged as a new application of the delay tolerant networks where network nodes are computing devices carried by humans. Hence, the study of how humans interact in their day-to-day life, the places they visit frequently, the people they meet frequently, the social groups in which they participate on regular basis etc. can help improve routing process in PSNs. This type of routing inspired from the way humans interact with each other is referred to as social based routing and had been a recent topic of research in the field of DTNs. This paper presents a comprehensive survey of the various social-based algorithms that have been designed for Delay Tolerant Networks.

The concept of a ‘just transition’ encompasses political and policy imperatives to minimise the harmful impacts of industrial and economic transitions on workers, communities and society more generally, and to maximise their potential benefits. This imperative has gained heightened importance as governments commit to reducing greenhouse gas emissions. A wide range of policies strategies and initiatives have been adopted by national and regional governments to facilitate and help manage a just transition. It is a concept that is increasingly being put into practice. This scoping study identifies and compares strategies, policies and practices that are presently being implemented in order to manage a just transition across 25 countries and 74 regions alongside European Union-level policies. This work develops a typology of policy instruments to manage just transitions and identifies implementation gaps and leading practices.

There is a crucial need for advancement in the online educational system due to the unexpected, forced migration of classroom activities to a fully remote format, due to the coronavirus pandemic. Not only this, but online education is the future, and its infrastructure needs to be improved for an effective teaching-learning process. One of the major concerns with the current video call-based online classroom system is student engagement analysis. Teachers are often concerned about whether the students can perceive the teachings in a novel format. Such analysis was involuntarily done in the offline mode, however, is difficult in an online environment. This research presents an autonomous system for analyzing the students' engagement in the class by detecting the emotions exhibited by the students. This is done by capturing the video feed of the students and passing the detected faces to an emotion detection mode. The emotion detection model in the proposed architecture was designed by finetuning VGG16 pre-trained image classifier model. Lastly, the average student engagement index is calculated. We received considerable performance setting reliability of the use of the proposed system in real-time giving a future scope to this research.

A long-standing problem in the understanding of deep-water turbidite reservoirs relates to how the three-dimensional evolution of deep-water channel systems evolve in response to channel filling on spatio-temporal scales, and how depositional environments affect channel architecture. The 3-D structure and temporal evolution of late Miocene deep-water channel complexes in the southern Taranaki Basin, New Zealand is investigated, and the geometry, distribution and stacking patterns of the channel complexes are analyzed. Two recently acquired 3-D seismic datasets, the Pipeline-3D (proximal) and Hector-3D (distal) are analyzed. These surveys provide detailed imaging of late Miocene deep-water channel systems, allowing for the assessment of the intricate geometry and seismic geomorphology of the systems. Seismic attributes resolve the channel bodies and the associated architectural elements. Spectral decomposition, amplitude curvature, and coherence attributes reveal NW-trending straight to low-sinuosity channels and less prominent NE-trending high-sinuosity feeder channels. Stratal slices across the seismic datasets better characterize the architectural elements. The mapped turbidite systems transition from low-sinuosity to meandering high-sinuosity patterns, likely caused by a change in the shelf-slope gradient due to localized structural relief. Stacking facies patterns within the channel systems reveal the temporal variation from a depositional environment characterized by sediment bypass to vertically aggrading channel systems.

Environmental genetics-related modern methods are shown as important indicators of various cyanotoxins syntheses, and their knowledge and use are critically analyzed. Microcystins and other cyanotoxins loads and syntheses are related to different drivers, like various chemical elements and compounds (especially nutrients, such as nitrogen and phosphorus, and their ratio), then to the light, conductivity, temperature, and other climatical and hydrological factors, to which spatial and geographical features (such as the surface of the water bodies) have to be added. The biotic relationships include different specific and supraspecific, uni- and bilateral links between the cyanobacteria, and subsequently their synthesized toxins, and protozoans (or protoctists), chromists, macrophytes, different systematical and ecological groups of zooplankton, and others. The importance of, but also the gaps in, the knowledge and the scarcity of studies involving ectocrines mediated interactions between different groups of algae and plants are highlighted. The paper ends with an interesting classification of lakes' trophicity, illustrated with conceptual diagrams, based on possible scenarios of cyanobacteria behavior.

The reality of people’s lives has shifted from rural to urban areas, where an ever-increasing proportion of the world’s population lives. Providing infrastructure to serve these areas, especially in the Global South, is a key task of sustainable development. A deep understanding of the spatial arrangement and scales of these urban structures and their temporal evolution can help to develop innovative solutions to issues of energy, water, or transportation infrastructures. For this purpose, in this work we study the temporal evolution of urban built-up structures (Global Artificial Impervious Area) and population distributions (Global Human Settlement Population) in four regions of the Global South (Argentina, India, Egypt, and Nigeria). We qualitatively analyze regularity through the pair correlation function and subsequently identify typical scales within the different interurban systems. In doing so, we identify that especially the large settlement objects arrange themselves in a regular way and thus typical scales exist in urban systems. Thus, settlement objects are usually located about 20 to 40 km apart from each other. This information can be used to develop sustainable infrastructure concepts, for example for passenger transport between settlements.

Followed by the aspect of respect for rights 20, the social and environmental issue has a score of 19.9, the dialogue issue is 19. In short, the proximity plan indicates that the policies used regarding the issue of generating employment and economic growth (Empresa Mantaro Perú SAC), continue to be the strategic variables in the first instance, but they are far from the social actors (rural communities of Aco, Vico, Cruz Pampa and others) and environmental (Junín environmental dialogue table) and Ombudsman's Office (rights) that are currently closer together. The actor from the Archbishop of Huancayo referred to communication is one of the driving variables of power. The proximity plan shows us that the policies used regarding the issue of generating employment and economic growth (Empresa Mantaro Perú SAC), continue to be the strategic variables in the first instance, but that they are far from the social actors (Rural Communities of Aco , Vico, Cruz Pampa and others) and environmental (Junín Environmental Dialogue Table) and Ombudsman's Office (rights) that are currently closer together. The actor from the Archbishop of Huancayo referred to communication is one of the driving variables of power. The proximity plan shows us that the policies used regarding the issue of generating employment and economic growth (Empresa Mantaro Perú SAC), continue to be the strategic variables in the first instance, but that they are far from the social actors (Rural Communities of Aco , Vico, Cruz Pampa and others) and environmental (Junín Environmental Dialogue Table) and Ombudsman's Office (rights) that are currently closer together. The actor from the Archbishop of Huancayo referred to communication is one of the driving variables of power. but they are far from the social actors (rural communities of Aco, Vico, Cruz Pampa and others) and environmental (Junín Environmental Dialogue Table) and the Ombudsman's Office (rights) that are closer together today. The actor from the Archbishopric of Huancayo referred to communication, is within the driving variables of power. but they are far from the social actors (rural communities of Aco, Vico, Cruz Pampa and others) and environmental (Junín Environmental Dialogue Table) and the Ombudsman's Office (rights) that are currently closer together. The actor of the Archbishopric of Huancayo referred to communication, is within the driving variables of power.

Transverse momentum spectra of +, p, Λ, Ξ or ¯Ξ+, Ω or ¯Ω+ and deuteron (d) in different centrality intervals in Gold-Gold (Au-Au) and Lead-Lead (Pb-Pb) collisions at 62.4 GeV and 2.76 TeV respectively, are analyzed by the blast wave model with Boltzmann Gibbs statistics. We extracted Kinetic freeze out temperature,transverse flow velocity and kinetic freezeout volume from the transverse momentum spectra of the particles. It is observed that the non-strange and strange (multi-strange) particles freezeout separately due to different reaction cross-sections. While the freezeout volume and transverse flow velocity are mass dependent which decrease with the rest mass of the particles. The present work reveals the scenario of double kinetic freezeout in collisions at STAR and ALICE Collaborations. Furthermore, the kinetic freezeout temperature and freezeout volume are larger in central collisions than the peripheral collisions and they decrease from central to periphery. However the transverse flow velocity remains almost unchanged from central to peripheral collisions.

With the now available vaccination against Covid-19 it is quantitatively explored how vaccination campaigns influence the mathematical modeling of epidemics. The standard susceptible-infectious-recovered/removed (SIR) epidemic model is extended to the fourth compartment V of vaccinated persons and the vaccination rate v(t) that regulates the relation between susceptible and vaccinated persons. The vaccination rate v(t) competes with the infection (a(t)) and recovery (\mu(t)) rates in determining the time evolution of epidemics. In order for a pandemic outburst with rising rates of new infections it is required that k+b<1-2\eta, where k=\mu_0/a_0 and b=v_0/a_0 denote the initial ratios of the three rates, respectively, and \eta << 1 is the initial fraction of infected persons. Exact analytical inverse solutions t(Q) for all relevant quantities Q=[S,I,R,V] of the resulting SIRV-model in terms of Lambert functions are derived for the semi-time case with time-independent ratios k and b between the recovery and vaccination rates to the infection rate, respectively. These inverse solutions can be approximated with high accuracy yielding the explicit time-dependences Q(t) by inverting the Lambert functions. The values of the three parameters k, b and \eta completely determine the reduced time evolution the SIRV-quantities Q(\tau). The influence of vaccinations on the total cumulative number and the maximum rate of new infections in different countries is calculated by comparing with monitored real time Covid-19 data. The reduction in the final cumulative fraction of infected persons and in the maximum daily rate of new infections is quantitatively determined by using the actual pandemic parameters in different countries. Moreover, a new criterion is developed that decides on the occurrence of future Covid-19 waves in these countries. Apart from Israel this can happen in all countries considered.

The Residential and Industrial zones as is, rely heavily, if not exclusively, on Hydrocarbons. Hydrocarbon thermal machinery such as Spark Ignition-Compression Ignition engines, Gasoline-Diesel generators, Coal-Lignite gasifiers, residential diesel-powered heating systems, Pyrolysis units and so on, are commonly met all around the planet. Such technology practically oxidizes Hydrocarbons to produce either heat, steam or useful mechanical work depending on the application, though energy losses are not, by any means, insignificant. Advanced material processing is an industrial sector who’s energy demand is significant and it is important for the general public to come to terms with the fact that by implementing Hydrogen technology to power such plant while at the same time improving the energy equilibrium of houses(advanced materials), communities would be taking major steps towards Climate Change effects debilitation. The downside of Hydrocarbon thermochemical exploitation can be described by the limited resources-reserves and the gaseous pollutant emissions (CO2, CO, NOx, SOx). In recent years, the Industrial zone as a whole has began taking a turn towards Electrification without having established the necessary infrastructure to support such a transition. Indicatively, at current rate of production, dead Lithium-Ion batteries are projected to reach as high as 11,000 metric tons by 2030, yet there is no recycling scheme in place, not to mention the prospect of that number rising even more, given the recent e-mobility trend. As it pertains to Electrification, such powertrains-machinery require electricity and a battery. Electricity production is mainly achieved through Coal-Lignite gasification, Batteries require metals, among others, for manufacturing, meaning that up-on mining, local water resources are contaminated, another very important ‘aspect’ of Lithium(per say) mining is that child labor is often associated with such processes, a truly despicable act. All of the above paint a crystal-clear picture as to how ‘environmentally friendly’ reckless-rushed Electrification really is. Climate Change is up-on us and it’s effects on the planet are obvious, the most important of which is glacier melting due to rising of the global Temperature. The COVID-19 crisis is a sign of what could come from glacier melting could as ice contains potentially harmful-toxic to humans, biological entities that are sure to be introduced to the general public if we were to continue exploiting mineral resources. Purpose of this paper is to provide a general overview of the technology around Hydrogen.

The purpose of this study is to examine the driving model of determinant factors that affects the performance of small and micro enterprises empirical evidence from Amhara Region, Ethiopia. The study used primary and secondary data from manufacturing, construction, urban agriculture, trade, and service entrepreneurs found in Bahirdar, Dessie & Gonder Cities using a purposive sampling technique. It also used the descriptive research design with a self-administered survey questionnaire. The Statistical analysis tools, SPSS and Amos, software were applied to analyze the data. Multiple regression model results revealed that access to credit, initial capital, working premises, industry category, market linkage, ICT adoption have a positive relationship and a major impact on the Amhara region's enterprise performance. Hence, the outcome variable, enterprise performance, is highly affected by all predicted variables. As the study finding shows, a lack of access to credit, , market linkage, working premises), initial capital, and information communication Technology problems are critical challenges of SMEs. The Regional Government, TVED Bureau, Micro Finance Institutions, , should take corrective action to provide sufficient credit and long-term loans to protect inflation. Moreover, this study proposed a sustainable cluster management approach that solves their challenges in an integrated way.

The purpose of this study is to examine the driving model of determinant factors that affects the performance of small and micro enterprises empirical evidence from Amhara Region, Ethiopia. The study used primary and secondary data from manufacturing, construction, urban agriculture, trade, and service entrepreneurs found in Bahirdar, Dessie & Gonder Cities using a purposive sampling technique. It also used the descriptive research design with a self-administered survey questionnaire. The Statistical analysis tools, SPSS and Amos, software were applied to analyze the data. Multiple regression model results revealed that access to credit, initial capital, working premises, industry category, market linkage, ICT adoption have a positive relationship and a major impact on the Amhara region's enterprise performance. Hence, the outcome variable, enterprise performance, is highly affected by all predicted variables. As the study finding shows, a lack of access to credit, , market linkage, working premises), initial capital, and information communication Technology problems are critical challenges of SMEs. The Regional Government, TVED Bureau, Micro Finance Institutions, , should take corrective action to provide sufficient credit and long-term loans to protect inflation. Moreover, this study proposed a sustainable cluster management approach that solves their challenges in an integrated way.

The use of probiotics in reproductive-related dysbiosis is an area of continuous progress due to the growing interest from clinicians and patients suffering recurrent reproductive microbiota disorders. An imbalance in the natural colonization sites related to reproductive health: vaginal, cervicovaginal, endometrial and also pregnancy-related altered microbiota could play decisive role in reproductive outcomes. Oral and vaginal administrations are in continuous discussion regarding the clinical effect pursued, but probiotics as oral supplement therapy is the route administration better studied. To complement and summarise with qualitative and quantitative information of vaginal probiotics clinical studies, the main objective of this work was to retrieve the standardised protocols commonly used and their microbiota modulation capacities. The studies selected were related to treat bacterial vaginosis (BV) as the most commonly disorder, few studies on vulvovaginal candidiasis (VVC) and also administration to stabilise microbiota before in vitro fertilisation (IVF). Probiotic doses administered were similar to oral probiotics protocols, ranging from ≥ 107 CFU/day to 2.5 x 1010 CFU/day, and variable regarding posology duration from 1 day to 12 weeks, being 1 week commonly applied. Moderate modulation was achieved regarding the relative abundance decrease of abnormal microbiota, coinciding with parallel increase in Lactobacillus species.

Amorphous chalcogenide (ChGs) glasses are intrinsically metastable, highly photosensitive, and therefore exhibit numerous lightinduced effects upon bandgap and sub-bandgap illumination. Depending on the pulse duration of the excitation laser, ChGs exhibit a series of lightinduced effects spanning over femtosecond to seconds time domain. For continuous wave illumination, the effects are dominantly metastable in terms of photodarkening (PD) and photobleaching (PB) that takes place via homopolar to heteropolar bond conversion. On the other hand, under nanosecond and ultrafast pulsed illumination, ChGs exhibit transient absorption (TA) that is instigated from the transient bonding rearrangements through self-trapped exciton recombination. In the first part of the review, we pay special attention to continuous wave lightinduced PD and PB, while in the second part we will focus on the TA and controlling such effects via internal and external parameters e.g., chemical composition, temperature, sample history etc.

Saliva has diverse functions in feeding behavior of animals. However, the impact of salivary digestion of food on insect gustatory information processing is poorly documented. Glucose-aversion (GA) in the German cockroach, Blattella germanica, is a highly adaptive heritable behavioral resistance trait that protects the cockroach from ingesting glucose-containing-insecticide-baits. In this study, we confirmed that GA cockroaches rejected glucose, but they accepted oligosaccharides. However, whereas wild-type cockroaches that accepted glucose also satiated on oligosaccharides, GA cockroaches ceased ingesting the oligosaccharides within seconds, resulting in significantly lower consumption. We hypothesized that saliva might hydrolyze oligosaccharides, releasing glucose and terminating feeding. By mixing artificially collected cockroach saliva with various oligosaccharides, we demonstrated oligosaccharide-aversion in GA cockroaches. Acarbose, an alpha-glucosidase inhibitor, prevented the accumulation of glucose and rescued the phagostimulatory response and ingestion of oligosaccharides. Our results indicate that pre-oral and oral hydrolysis of oligosaccharides by salivary alpha-glucosidases released glucose, which was then processed by the gustatory system of GA cockroaches as a deterrent and caused the rejection of food. We suggest that the genetic mechanism of glucose-aversion support an extended aversion phenotype that includes glucose-containing oligosaccharides. Salivary digestion protects the cockroach from ingesting toxic chemicals and thus could support the rapid evolution of behavioral and physiological resistance in cockroach populations.

Most of the existing influence maximization algorithms are not suitable for large-scale social networks due to their high time complexity or limited influence propagation range. Therefore, a D-RIS influence maximization algorithm is proposed based on the independent cascade model and combined with the reverse reachable set sampling. Under the premise that the influence propagation function satisfies monotonicity and submodularity, the D-RIS algorithm uses automatic debugging method to determine the critical value of the number of reverse reachable sets, which not only obtains a better influence propagation range, and greatly reduce the time complexity. The experimental results on the two real data sets of Slashdot and Epinions show that D-RIS algorithm is close to the CELF algorithm and higher than RIS algorithm, HighDegree algorithm, LIR algorithm and pBmH algorithm in influence propagation range. At the same time, it is significantly better than the CELF algorithm and RIS algorithm in running time, which indicates that D-RIS algorithm is more suitable for large scale social network.

We start out by deriving simple analytic expressions for all measurable amounts of cases and fatalities during a pandemic evolution exhibiting multiple waves, described by the semi-time SIR model. The approximant shares all relevant features with the exact solution, including time and position of the peak of daily new infections, as well as the asymptotic behaviors at small and large times. We derive exact analytic expressions for the early doubling time, late half decay time, and a half-early peak law, characterizing the dynamical evolution. We show, in particular, how the asymmetry of the first epidemic wave and its exponential tails are affected by the initial conditions; a feature that has no analogue in the all-time SIR model. We apply the approach to available data from different continents. Our analysis reveals that the immunity is very strongly increasing during the 2nd wave, while it was still at a very moderate level of a few percent in several countries at the end of the first wave. The wave-specific SIR parameters describing the infection and recovery rates we find to behave in a similar fashion, while their ratio k was decreasing only by a about 5% for most countries. Still, an apparently moderate change of k can have significant consequences for the relevant numbers like the final amount of infected or deceased population. As we show, the probability for an additional wave is however low in several countries due to the fraction of immune inhabitants at the end of the 2nd wave, irrespective the currently ongoing vaccination efforts. We compare with alternate approaches.

An earthquake of Mw6.4 hit the coastal zone of Albania on 26 November 2019, at 02:54:11 UTC. It was intensively felt at about 34km far away, in Tirana City, where damages and lives lost occurred. To emphasize a geomagnetic signature before the onset of this earthquake, the data collected on the interval 15 October–30 November 2019, at the Panagjurishte (PAG)-Bulgaria and Surlari (SUA)-Romania observatories are analyzed by using both the polarization parameter (BPOL)-time invariant in non-seismic conditions, becoming unstable before this seismic event, and the strain effect for geomagnetic signal identification. Consequently, BPOL time series and its standard deviations are performed for the both sites using ULF-FFT band-pass filtering. A statistical analysis, based on a standardized random variable equation, was applied to emphasize on the BPOL*(PAG) and ABS BPOL*(PAG) time series the anomalous signal’s singularity and, to differentiate the transient local anomalies due to Mw6.4earthquake, from the internal and external parts of the geomagnetic field, taken PAG observatory as reference. Finally, the ABS BPOL*(PAG-SUA) time series are obtained on the interval 1-30 November, 2019, where a geomagnetic signature greater than 2.0, was detected on 23 November and the lead time was 3 days before the onset of Mw6.4earthquake.

Four decades of proteasome research have yielded extensive information on ubiquitin-dependent proteolysis. The archetype of proteasomes is a 20S barrel-shaped complex that does not rely on ubiquitin as a degradation signal but can degrade substrates with a considerable unstructured stretch. Since roughly half of all proteasomes in most eukaryotic cells are free 20S complexes, ubiquitin-independent protein degradation may coexist with ubiquitin-dependent degradation by the highly regulated 26S proteasome. This article reviews recent advances in our understanding of the biochemical and structural features that underlie the proteolytic mechanism of 20S proteasomes. The two outer α-rings of 20S proteasomes provide a number of potential docking sites for loosely folded polypeptides. The binding of a substrate can induce asymmetric conformational changes, trigger gate opening, and initiate its own degradation through a protease-driven translocation mechanism. Consequently, the substrate translocates through two additional narrow apertures augmented by the β-catalytic active sites. The overall pulling force through the two annuli results in a protease-like unfolding of the substrate and subsequent proteolysis in the catalytic chamber. Although both proteasomes contain identical β-catalytic active sites, the differential translocation mechanisms yield distinct peptide products. Non-overlapping substrate repertoires and product outcomes rationalize cohabitation of both proteasome complexes in cells.

In recent years, soil addition with organic amendments, such as biochar and compost, has gained attention as an effective agronomic practice to sustain soil fertility, enhance plant growth and crop yield. Well known are the positive effects of compost on yield of a wide crop varieties, while both positive and negative responses are reported for biochar Therefore, the aim of the study was to verify the effect of biochar mixed with three types of compost on quanti-qualitative response of Swiss chard (Beta vulgaris L. cycla), a leafy green vegetable rich in dietary antioxidants, largely consumed worldwide. A factorial experiment in pots with two factors, including biochar (without biochar and with biochar from vine pruning residues) and compost (without compost, with compost from olive pomace, with vermicompost from cattle manure and with compost from cattle anaerobic digestate), was setup. Two growth cycles were considered and a set of quantitative (height of plants, number, area and fresh weight of leaves) and qualitative parameters (carotenoid, chlorophyll, total N and NO3-content of leaves) were analyzed. Biochar decreased plant growth and NO3- leaf content; on the contrary, it increased total N leaf content, while compost improved all the considered parameters. The interactive effect of biochar and compost was evident only on total N and NO3- leaf content. In our experimental conditions, the compost showed to be the best option to improve Swiss chard growth and increase the phytopigments content, while the biochar-compost mixtures didn’t produce the expected effect.

Abstract:Salmonella species (spp) and Escherichia coli (E. coli) are the most common infectious pathogens in poultry. Antimicrobials were given either for the treatment or growth promoters that can increase the possibility of emergence of bacterial resistance towards antimicrobials. The aim of this study was to determine the prevalence of antimicrobial resistant (AMR) Salmonella spp and E. coli isolated from a sample of broiler farms in East Coast Malaysia from 2018-2019. A total of 384 cloacal swabs were collected from broilers farms in Kelantan, Terengganu, and Pahang. The bacteria were isolated and confirmed by bacteriological and serological methods. Following that, confirmed isolates were subjected to antimicrobial susceptibility test. Salmonella spp and E. coli were recovered from the cloacal swabs samples with the overall prevalence of 6.5% and 51.8% respectively. In Kelantan, Terengganu and Pahang, the prevalence of Salmonella spp were 7%, 6.5% and 5.8% respectively, while the prevalence for E. coli were 50%, 48.3% and 58% respectively. Salmonella spp and E. coli displayed resistance towards the following antimicrobials: erythromycin (100% for both pathogens), chloramphenicol (76.2%, 84.5%), tetracycline (62%, 94.6%), ampicillin (47.7%, 87%), sulfamethoxazole/trimethoprim (42.9%, 83.3%), ciprofloxacin (4.8%, 23.8%), nalidixic acid (9.6%, 60.7%), streptomycin (19%,66%), and kanamycin (28.6%,57%), cephalotin (0%, 11%), gentamicin (0%, 20.2%) respectively. No resistance were recorded towards colistin for both pathogens. Multidrug resistance (MDR) was recorded in 82% of Salmonella spp and 100% of E. coli. These findings demonstrate the high prevalence of MDR Salmonella spp. and E. coli in broiler farms in East coast Malaysia. This could be attributed to the excessive use of antimicrobial agents by the poultry farm owners. Enhanced control measures and a strong monitoring system should be urgently implemented to reduce the emergence of antimicrobial resistance that is harmful to public health.

Evolutionary medicine argues that disease can arise because modern conditions do not match those in which we evolved. For example, a decline in exposure to commensal microbes and gastrointestinal helminths in developed countries has been linked to increased prevalence of allergic and autoimmune inflammatory disorders (the hygiene hypothesis). Accordingly, microbial and helminthic probiotic therapies have been explored as Darwinian treatments for these disorders. A further possibility is that loss of old friend commensals also increases the sterile, aging-associated inflammation known as inflammaging, that contributes to a range of age-related diseases, including cardiovascular disease, dementia and cancer. Interestingly, Crowe et al. (2020) recently reported that treatment with a secreted glycoprotein from a parasitic nematode can protect against murine aging by induction of anti-inflammatory mechanisms. Here, we explore the hypothesis that restorative helminth therapy would have anti-inflammaging effects. Could worm infections provide broad-spectrum protection against age-related disease?

Simulating the non-perturbative and non-Markovian dynamics of open quantum systems is a very challenging many body problem, due to the need to evolve both the system and its environments on an equal footing. Tensor network and matrix product states (MPS) have emerged as powerful tools for open system models, but the numerical resources required to treat finite temperature environments grow extremely rapidly and limit their applications. In this study we use time-dependent variational evolution of MPS to expore the striking theory of Tamescelli et al. that shows how finite temperture open dyanmics can be obtained from zero temperature, i.e. pure wave function, simulations. Using this approach, we produce a benchmark data set for the dynamics of the Ohmic spin-boson model across a wide range of coupling and temperatures, and also present detailed analysis of the numerical costs of simulating non-equilibrium steady states, such as those emerging from the non-perturbative coupling of a qubit to baths at different temperatures. Despite ever growing resource requirements, we find that converged non-perturbative results can be obtained, and we discuss a number of recent ideas and numerical techniques that should allow wide application of MPS to complex open quantum systems.

There is increasing evidence that rising temperatures and heatwaves in the United Kingdom are associated with an increase in heat-related mortality. This study aims to retrospectively quantify the impact of heatwaves on mortality during the 2019 summer period using daily death occurrences. Second, it compares excess mortality during the 2019 heatwaves to excess mortality during the 2018 and 2017 heatwave periods. Lastly, it compares the excess mortality in the 2017-2019 heatwaves to the estimated excess deaths for the same period in the Public Health England (PHE) Heatwave mortality monitoring Reports. The cumulative number of excess deaths during the summer 2019 heatwaves were minimal and were substantially lower than during the summer 2018 heatwaves (1,700 deaths) and summer 2017 heatwaves (1,489 deaths). All findings were at variance with the PHE Heatwave mortality monitoring reports which estimated cumulative excess deaths to be 892, 863 and 778 during the summer period of 2019, 2018 and 2017 respectively using provisional death registrations. Issues have been identified in the use of provisional death registrations for mortality monitoring and the reduced reliability of the ONS daily death occurrence database before 2019. These findings may identify more reliable ways to monitor heat mortality during heatwaves in the future.

Environmental decentralization (ED), or the allocation of environmental protection affairs and responsibilities among various administrative authorities, affects the effectiveness of environmental regulation in promoting green total factor productivity (GTFP). Based on panel data of 30 Chinese provinces from 2001 to 2015, this paper employs dynamic panel models to test the effects of environmental regulations (environmental protection investment, ENV; pollutant discharge fees, PDF) on GTFP, with or without being influenced by ED. Without the impact of ED, GTFP is significantly inhibited by ENV while significantly promoted by PDF. Considering the impact of ED, with the strengthening of ED, the negative effects of ENV on GTFP is significant; contrarily, the positive effects of PDF on GTFP is significant; improving provincial ED adds negative effects of ENV, while reduces the positive effects of PDF; increasing prefectural ED reduces negative effects of ENV; expanding county-level ED adds the positive effects of PDF. Therefore, to boost GTFP growth, prefectural environmental protection authorities should have more autonomy in ENV, while the county-level should have more autonomy in PDF.

Advances in machine learning (ML) and artificial intelligence (AI) are transforming the way we treat patients in ways not even imagined a few years ago. Cancer research is at the forefront of this movement. Infertility, though not a life-threatening condition, affects around 15% of couples trying for a pregnancy. Increasing availability of large datasets from various sources creates an opportunity to introduce ML and AI into infertility prevention and treatment. At present in the field of assisted reproduction, very little is done in order to prevent infertility from arising, with the main focus put on treatment when often advanced maternal age and low ovarian reserve make it very difficult to conceive. A shift from this disease-centric model to a health centric model in infertility is already taking place with more emphasis on the patient as an active participator in the process. Poor quality and incomplete data as well as biological variability remain the main limitations in the widespread and reliable implementation of AI in the field of reproductive medicine. That said, one of the areas where this technology managed to find a foothold is identification of developmentally competent embryos. More work is required however to learn about ways to improve natural conception, the detection and diagnosis of infertility, and improve assisted reproduction treatments (ART) and ultimately, develop clinically useful algorithms able to adjust treatment regimens in order to assure a successful outcome of either fertility preservation or infertility treatment. Progress in genomics, digital technologies and advances in integrative biology has had a tremendousimpact on research and clinical medicine. With the rise of ‘big data’, artificial intelligence, and the advances in molecular profiling, there is an enormous potential to transform not only scientific research progress, but also clinical decision making towards predictive, preventive, and personalized medicine. In the field of reproductive health, there is now an exciting opportunity to leverage these technologies and develop more sophisticated approaches to diagnose and treat infertility disorders. In this review, we present a comprehensive analysis and interpretation of different innovation forces that are driving the emergence of a system approach to the infertility sector. Here we discuss recent influential work and explore the limitations of the use of Machine Learning models in this rapidly developing area.

This study was conducted to propose the Green Economic Development Plan for Manufacturing S.M.E.s based on financial performance and operations thru Green Initiatives. The descriptive survey method used to gather data to determine the green initiative's implementation of small and medium (S.M.E.s) manufacturing enterprises. Green initiatives use as a basis for crafting a green economic development plan. Document analysis was also employed to obtain data from any available printed materials and records provided by the respondents. Such methods of gathering information used to validate data gathered from local and foreign-related literature. The observation also employed to survey the assets owned and validate any green initiatives practiced, including their implementation. The study's findings show that among the green initiatives implemented by SMMEs, which resulted in the reduction of total costs and expenses, were the proper disposal and segregation of waste materials, water management by recycling wastewater and using water-efficient equipment, natural resources, and raw materials management. SMMEs should encourage active participation and support of suppliers and customers in achieving G.E.D.'s objectives by developing incentive schemes.Furthermore, SMMEs should continue to benchmark with G.E.D. Practitioners are operating locally and abroad to adopt best greening strategies and regularly network with concerned government agencies for continuous updating on G.E.D. Initiatives that may benefit the firm. Further research may be conducted on green initiatives implemented by small and medium enterprises in other industry sectors.

This study takes as a starting point the importance and dependence of the media (Ball-Rokeach & DeFleur, 1976) to obtain information about the pandemic. The dependency theory of the media system was developed in the 1970s when mass media were the dominant source of information. Today, at a time when media choices have become abundant, studies are needed to understand the phenomenon of media dependence in light of new dimensions made important by the transformations that have taken place in the social and media fields - where the coexistence of mass media with social media platforms stands out. As large-scale crises rarely occur and the media environment changes rapidly, it is important to analyze how media dependence relates to choose and trust in different media (traditional media vs. social media) in times of crisis. Several questions arise. What is the trust attributed by individuals to social media as sources of information about the COVID-19? How well informed are the individuals who choose these sources as the main sources of information? From a questionnaire administered to 240 individuals in Portugal, during the first week of the state of emergency (March 2020), this research seeks to identify how people gained access to information about the COVID-19, how they acted critically towards the various sources and how they assess the reliability of different media. Finally, it analyzes the association between the type of medium chosen and adherence to misinformation content about the virus. The results reveal the existence of a phenomenon of dependence on the media, with a strong exposure (both active and accidental) to informative content, with conventional media being privileged as the main source, and positively distinguished in terms of confidence. Finally, a statistically significant association of a positive sign was identified between the use of social media as the main source and the acceptance of misinformation.

The Wave Mode (WM) is a unique imaging mode of spaceborne synthetic aperture radar (SAR), which is dedicatedly designed for global ocean surface wave observations. Since it was firstly achieved in the ERS-1/SAR satellite starting from 1991, the WM data over global oceans have been continuously acquired by the ESA’s SAR instruments onboard the satellites of ERS-2 (1997 – 2011), ENVISAT (2002 – 2012), Sentinel-1A(2014--)/1B(2016--) and the Chinese GaoFen-3 SAR (2016--), for nearly 30 years. Therefore, spaceborne SAR WM data have been a ‘big data’, which however, has not been widely exploited for global ocean wave measurements. In this study, we demonstrate its application on global ocean wave measurements based on the ten-year Advanced SAR (ASAR) WM data.

Information security plays a major role in the dynamics of today’s interconnected world. Despite the successful implementation and effectiveness of modern cryptographic techniques, their inherent limitations can be exploited by quantum computers. In this article we discuss Grover’s quantum searching algorithm and its impact on the security of modern symmetric ciphers. More specifically, we present its formal description and give an implementation of the algorithm using IBM’s Qiskit framework, which allows us to simulate and run the program on a real device. The developed program is modular and scalable, managing to properly run on any input state. We compare the performance of the algorithm running on the local simulator against its execution on a quantum processor from IBM’s lineup, noting the discrepancies between the results due to physical characteristics of the chip.

Ploidy is a significant type of genetic variation, describing the number of chromosome sets per cell. Ploidy evolves in natural populations, clinical populations, and lab experiments, particularly in fungi. Despite a long history of theoretical work on this topic, predicting how ploidy will evolve has proven difficult, as it is often unclear why one ploidy state outperforms another. Here, we review what is known about contemporary ploidy evolution in diverse fungal species through the lens of population genetics. As with typical genetic variants, ploidy evolution depends on the rate that new ploidy states arise by mutation, natural selection on alternative ploidy states, and random genetic drift. However, ploidy variation also has unique impacts on evolution, with the potential to alter chromosomal stability, the rate and patterns of point mutation, and the nature of selection on all loci in the genome. We discuss how ploidy evolution depends on these general and unique factors and highlight areas where additional experimental evidence is required to comprehensively explain the ploidy transitions observed in the field and the lab.

The bay is a space barrier for the development of island-type cities and a high-quality waterfront landscape resource. This study takes Xiamen a typical island city in China as an example. First, It use the method of satellite telemetry technology combined with GIS software and spatial syntax, respectively, from the material space level and social space level, to summarize the rapid urbanization process of this city since 1990-2018, focusing on the construction process of three large-scale waterfront park systems in the transition period of inter-island development in it, and comparing the similarities and differences of their spatial forms. Further, from the choice of the axis model and the integrated analysis results, we discuss the spatial efficiency changes. The construction of the three major bay waterfront park systems in this city reflects a huge change in development pattern from lagging construction, synchronous planning, to advanced layout, providing a continuous and variable spatial form for the development of the bay region and improving space efficiency, which one of the important ways to develop and transform island-type cities. We hope to provide the reference for the development including sustainable development of other island cities around the world

This work probes the combined effects of magnetic field and viscous dissipation on heat field and examine the second law analysis (entropy generation) in an electrically conducting fluid under the effect of wall mass transfer over continuous stretched non-isothermal surface with variable viscosity. The viscosity of the fluid is assumed to be an inverse linear function of temperature. The governing equation for the problem are changed to dimensionless ordinary differential equations by using similarity transformation and solved numerically by using Rung Kutta and Shooting technique. Velocity, concentration and temperature distribution are obtained and used to compute the entropy generation and the Bejan number in the flow field. The effect of variable viscosity, Schmidt number, Hartman and Reynolds number on the velocity, concentration, temperature, entropy generation and Bejan number are studied and discussed.

Nowadays, many political campaigns are using social influence (SI) in order to convince voters to support/oppose a specific candidate/party. In election control via SI problem, an attacker tries to find a set of limited influencers to start disseminating a political message in a social network of voters. A voter will change his opinion when he receives and accepts the message. In constructive case, the goal is to maximize the number of votes/winners of a target candidate/party, while in destructive case, the attacker tries to minimize them. Recent works considered the problem in different models and presented some hardness and approximation results. In this work, we consider multi-winner election control through SI on different graph structures and diffusion models, and our goal is to maximize/minimize the number of winners in our target party. We show that the problem is hard to approximate when voters' connections form a graph, and the diffusion model is the linear threshold model. We also prove the same result considering an arborescence under independent cascade model. Moreover, we present a dynamic programming algorithm for the cases that the voting system is a variation of straight-party voting, and voters form a tree.

Purpose: Recently introduced molecules namely long non-coding RNAs (lncRNAs) are associated with various diseases, including breast cancer, and they may have the potential to act as biomarkers. Invasive ductal carcinoma (IDC) is a frequently observed type of breast cancer that diagnosis through immunohistochemical methods. However, no reliable non-invasive markers such as circulating markers have been introduced for it, so far. Materials and methods: The relative quantitation (RQ) of two lncRNAs, RP11-445H22.4 and TINCR, was measured in tumoral tissues and paired adjacent non-tumoral tissues (PANTs) as well as in plasma samples using real-time polymerase chain reaction (RT-PCR). Furthermore, promoter methylation of the two lncRNAs genes was assessed using methylation-specific PCR (MSP). In order to compare the diagnostic values, plasma levels of CA 15-3 were measured as a conventional circulating biomarker using ELISA. The receiver operating characteristic (ROC) curve was used to illustrate the sensitivity and specificity of the potential biomarkers. Results: The RP11-445H22.4 and TINCR genes were upregulated in tumor tissues compared to PANTs (RQ_{RP11-445H22.4} = 2.7, RQ_TINCR = 4.4). Furthermore, the presence of RP11-445H22.4 and TINCR in the plasma of patients was significantly more than healthy controls (RQ_{c.RP11-445H22.4} = 4.12, RQ_c.TINCR = 4.16, P<0.001). The promoters of RP11-445H22.4 and TINCR genes were hypomethylated in the tumoral tissues with a negative correlation with their gene expression. Conclusion: Based on the findings, it can be speculated that the expression levels of these two lncRNAs as well as their promoter methylation can be considered as a therapeutic target and potential biomarker for breast carcinoma.

Emerging and reemerging pathogens is a global challenge for public health. Recently, a novel coronavirus disease emerged in Wuhan, Hubei province of China, in December 2019. It is named COVID-19 by World Health Organization (WHO). It is known to be caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that affects the lower respiratory tract and manifests as pneumonia in humans. Coronaviruses (CoVs) are structurally more complicated as compared to other RNA viruses. This viral epidemic has led to the deaths of many, including the elderly or those with chronic disease or compromised immunity. Viruses cause infection and diseases in humans of varying degrees, upper respiratory tract infections (URTIs) cause common cold while lower respiratory tract infections induce pneumonia, bronchitis, and even severe acute respiratory syndrome (SARS). The costs of COVID-19 are not limited. It equally affects all the medical, sociological, psychological, and economic aspects globally. This is regarded as the third deadly outbreak in the last two decades after Severe Acute Respiratory Syndrome SARS (2002–2003) and Middle East Respiratory Syndrome MERS (2012). Based on the sequence homology of SARS-CoV-2, different animal sources including bats, snakes, and pangolins have been reported as potential carriers of this viral strain. Real-time RT-PCR represents the primary method for the diagnosis of new emerging viral strain SARS-CoV-2. The transmission dynamics suggest that SARS-CoV-2 is transmitted from person-to-person through direct contact or coughing, sneezing, and by respiratory droplets. Several anti-viral treatments including lopinavir/ritonavir, remdesivir, chloroquine phosphate, and abidor are also suggested with different recommendations and prescriptions. Protective and preventive strategies as suggested by various health organization i.e. WHO and US Center for Disease Control and Prevention (CDC) must be adopted by everyone. This review covers the important aspects of novel COVID-19 including characteristics, virology, symptoms, diagnostics, clinical aspects, transmission dynamics, and protective measures of COVID-19.

A well known result for the interference of two single-mode fields is that the degree of coherence and the degree of indistinguishablity are same when we consider the detection of a single photon. In this article we present the relation between degree of coherence, path indistinguishability and the fringe visibility considering interference of multiple number of single-mode fields while being interested in the detection of a single photon only . We will also mention how Born’s rule of interference for multiple sources is reflected in these results.

This paper presents a comparative analysis of the ZVZCS soft switching technique with the ZVS and the ZCS counterpart. The generalization of the voltage-current crossover or the energy loss factor obtained from simulation of the prototype converter shows that the ZVZCS significantly reduces the loss and helps to improve the efficiency of the converter as compared to the ZVS or the ZCS. On the other hand, it is also found that the soft switching range of operation of the ZVS and the ZCS are largely affected by the maximum switch voltage and switch current respectively. In contrary, these factors have a negligible effect on the ZVZCS operation which results in an extended range of soft switching operation. Additionally, a detailed LTPICE simulation is performed for selected ZVS, ZCS and ZVSCS topologies from the recent literature and the switching losses in the main switches of the converters are measured. It is observed that the energy losses in the ZVZCS mode are reduced on average by approximately 26 % at turn on and 20 % at the turn off as compared to the ZVS and the ZCS. Besides, the low standard deviation in this mode confirms a stable low loss profile which renders extended soft switching range. An experimental test is also conducted by building the prototype converter to verify the simulation results. It is found that the switching losses are minimum while the converter is operated in the ZVZCS mode. Besides, the efficiency drop remains consistently low as compared to the ZVS and the ZCS in the whole operating range. Resultantly, the simulation and the experimental results are both found to be consistent.

As a result of identity prejudice, certain individuals are at higher risk for conflict and violence when they are in the field. At-risk individuals include minority identities of the following: race/ethnicity, sexual orientation, disability, gender identity, and/or religion. Everyone deserves to conduct fieldwork as safely as possible; therefore, it is paramount for anyone conducting fieldwork to be informed of the increased risk certain populations face when conducting field research and to define informed strategies. Research groups should adhere to best practices to minimize risk for all individuals who go into the field. Here we provide strategies that 1) acknowledge that some individuals encounter dangerous situations in the field due to their identity(ies), and 2) minimize the chance of conflict between and among researchers and other communities present at field sites. The inclusion of this document as a key resource in a research lab, a university department, or any active research or work environment sends a positive signal to at-risk individuals that their professional community acknowledges their risk and is willing to implement actions to ensure their safety. We suggest that this document be made freely available to anyone who is directly or indirectly involved in fieldwork. Supervisors who support the information in this document should publicly commit to promote a diverse and inclusive environment in order to maintain the safety of their researchers.

In this article we first write a brief review of supersymmetric quantum mechanics and then we discuss the equivalence of two co-existing formalisms viz. tensor product formalism and partner hamiltonian formalism for 1-D SUSY Harmonic oscillator. Finally, we present a Mathematica code with which one can calculate the eigenstates of any 1-D SUSY partner Hamiltonian along with two illustrated examples of 1-D SUSY HO and 1-D SUSY infinite potential box.

We revisit the Susceptible-Infectious-Recovered/Removed (SIR) model which is one of the simplest compartmental models. Many epidemological models are derivatives of this basic form. While an analytic solution to the SIR model is known in parametric form for the case of a time-independent infection rate, we derive an analytic solution for the more general case of a time-dependent infection rate, that is not limited to a certain range of parameter values. Our approach allows us to derive several exact analytic results characterizing all quantities, and moreover explicit, non-parametric, and accurate analytic approximants for the solution of the SIR model for time-independent infection rates. We relate all parameters of the SIR model to a measurable, usually reported quantity, namely the cumulated number of infected population and its first and second derivatives at an initial time t=0, where data is assumed to be available. We address the question on how well the differential rate of infections is captured by the Gauss model (GM). To this end we calculate the peak height, width, and position of the bell-shaped rate analytically. We find that the SIR is captured by the GM within a range of times, which we discuss in detail. We prove that the SIR model exhibits an asymptotic behavior at large times that is different from the logistic model, while the difference between the two models still decreases with increasing reproduction factor. This part A of our work treats the original SIR model to hold at all times, while this assumption will be released in part B. Releasing this assumption allows to formulate initial conditions incompatible with the original SIR model.

Many governments particularly in Europe are designing social interventions for the first post COVID-19 emergency phase. Definition of a ‘best practice’ for restriction release is urgent. Although data uncertainty generate difficulties, we believe near term analysis must shift from attempting to understand the numerous ‘unknowns’ to the clarification and interpretation of the few ‘knowns’, to create stepping stones towards rapid evidence-based decision making.Here, open access data on COVID-19 severity in three European countries were analyzed. Spain’s data were more comprehensive than those from Italy and Germany. Overall, COVID-19 severity shows a remarkable nonlinear growth with age that is significantly higher in adult males. Hence, age-adaptive and gender-balanced social interventions might represent efficient repopulation options for public health policymakers. Furthermore, we urge wider governmental effort for open access to relevant data. Their analysis will allow consolidation of existing trends, validation of key observations and thus facilitation of timely decisions.

There are abundant coal, oil and natural gas resources in "Golden Triangle" energy region. Energy resources development, coal chemical industry, coal power and other industries play an important role in promoting regional economic growth, but facing the insufficient water supply. Under the condition of marginal equilibrium of water resources, the paper firstly analyzes the water utilization, and calculates the potential water-saving amount. Then, the paper constructs a cooperative game model and allocates the newly increased GDP by using the weight distribution method. Finally, the paper puts forward some policy suggestions to reduce the efficiency gap of water utilization among regions.

This paper presents a multifunctional reflective digital metasurface of arbitrary base based on voltage tunable liquid crystal (LC). The reflective digital metamaterial can be multiplexed for different desirable functions by properly biasing the LC for different code patterns. Simulation results of three significant functions, beam steering with a steering elevation angle 27° at 75 GHz, RCS reduction of at least 15dB along the incident direction, and beam shaping with different beam shapes have been presented to prove the concept.

To live in the information society means to be surrounded by billions of electronic devices full of sensors that constantly acquire data. This enormous amount of data must be processed and classified. A solution commonly adopted is to send these data to server farms to be remotely elaborated. The drawback is a huge battery drain due to high amount of information that must be exchanged. To compensate this problem data must be processed locally, near the sensor itself. But this solution requires huge computational capabilities. While microprocessors, even mobile ones, nowadays have enough computational power, their performance are severely limited by the Memory Wall problem. Memories are too slow, so microprocessors cannot fetch enough data from them, greatly limiting their performance. A solution is the Processing-In-Memory (PIM) approach. New memories are designed that are able to elaborate data inside them eliminating the Memory Wall problem. In this work we present an example of such system, using as a case of study the Bitmap Indexing algorithm. Such algorithm is used to classify data coming from many sources in parallel. We propose an hardware accelerator designed around the Processing-In-Memory approach, that is capable of implementing this algorithm and that can also be reconfigured to do other tasks or to work as standard memory. The architecture has been synthesized using CMOS technology. The results that we have obtained highlights that, not only it is possible to process and classify huge amount of data locally, but also that it is possible to obtain this result with a very low power consumption.

Aggregating data is the main line of any discipline dealing with fusion of information from the knowledge-based systems to the decision-making. The purpose of aggregation methods is to convert a list of objects, all belonging to a given set, into a single representative object of the same set usually by an n-ary function, so-called aggregation operator. Since the useful aggregation functions for modeling real-life problems are limit, the basic problem is to construct a proper aggregation operator for each situation. During the last decades, a number of construction methods for aggregation functions have been developed to build new classes based on the well-known operators. This paper reviews some of these construction methods where they are based on transformation, composition and weighted rule.

We show that if $f$ is a non-negative superquadratic function, then $A\mapsto\mathrm{Tr}f(A)$ is a superquadratic function on the matrix algebra. In particular, \begin{align*} \tr f\left( {\frac{{A + B}}{2}} \right) +\tr f\left(\left| {\frac{{A - B}}{2}}\right|\right) \leq \frac{{\tr {f\left( A \right)} + \tr {f\left( B \right)} }}{2} \end{align*} holds for all positive matrices $A,B$. In addition, we present a Klein's inequality for superquadratic functions as $$ \mathrm{Tr}[f(A)-f(B)-(A-B)f'(B)]\geq \mathrm{Tr}[f(|A-B|)] $$ for all positive matrices $A,B$. It gives in particular improvement of Klein's inequality for non-negative convex function. As a consequence, some variants of the Jensen trace inequality for superquadratic functions have been presented.

The paper provides information on significant contamination of real laboratory water with hydrophilic microimpurities. This fact suggests that researchers are practically dealing with microdispersed systems. However, this fact is usually neglected in the discussions of the causes of the anomalous properties of water. We will show that, when exposed to various factors of physical nature, water demonstrates reactions of the same type, namely, increased pH and electrical conductivity, reduced redox potential and viscosity, and enhanced bioavailability. Each exposure is accompanied by the destruction of aggregates of the dispersed phase and its transition to a fine-dispersed state. The relationship between this phenomenon and the change in the physicochemical properties of water is discussed.

An analysis is presented of the possible existence of a second anomalous dipole moment of Dirac’s particle next to the angular one. It includes a discussion why, in spite of his own derivation, Dirac has doubted about its relevancy. It is shown why since then it has been overlooked and why it has vanished from leading textbooks. A critical survey is given on the reasons of its reject, including the failure of attempts to measure and the perceived violations of time reversal symmetry and chargeparity symmetry. It is emphasized that the anomalous electric dipole moment of the pointlike electron (AEDM) is fundamentally different from the quantum field type electric dipole moment of an electron (eEDM) as defined in the standard model of particle physics and that its measurement requires different instrumentation. A proposal has been described how to prove or disprove its existence by experiment. Moreover, by reference from literature, the possible impact is discussed in the nuclear domain and in the gravitational domain.

Complex blade responses such as a rotating stall or simultaneous resonances are common in modern engines and their observation can be a challenge even for state-of-the-art tip-timing systems and trained operators. This paper analyses forced vibrations of axial compressor blades, measured during the bench tests of the SO-3 turbojet. In relation to earlier studies conducted in ITWL with a small number of sensors, a multichannel tip-timing system let us observe simultaneous responses or higher-order modes. To find possible symptoms of a failure, blade responses in a healthy and unhealthy engine configuration with an inlet blocker were studied. The used analysis methods covered all-blade spectrum and the circumferential fitting of blade deflections to the harmonic oscillator model. The proposed modal solver can track the vibration frequency and adjust the engine order on the fly. That way, synchronous and asynchronous vibrations are observed and analysed together with an extended variant of least squares. The proposed approach helps to avoid common mistakes and saves a lot of work related to configuring the conventional solver.

Fragment-based drug discovery (FBDD) has become a major strategy to derive novel lead candidates for various therapeutic targets, as it promises efficient exploration of chemical space by employing fragment-sized (MW < 300) compounds. One of the first challenges in implementing a FBDD approach is the design of a fragment library, and more specifically, the choice of its size and individual members. A diverse set of fragments is required to maximise the chances of discovering novel hit compounds. However, the exact diversity of a certain collection of fragments remains underdefined, which hinders direct comparisons among different selections of fragments. Based on structural fingerprints, we herein introduced quantitative metrics for the structural diversity of fragment libraries. Structures of commercially available fragments were retrieved from the ZINC database, from which libraries with sizes ranging from 100 to 100,000 compounds were selected. The selected libraries were evaluated and compared quantitatively, resulting in interesting size-diversity relationships. Our results demonstrated that while library size does matter for its diversity, there exists an optimal size for structural diversity. It is also suggested that such quantitative measures can guide the design of diverse fragment libraries under different circumstances.

Freshwater fish represent half of all fish species and are the most threatened vertebrate group. Given their considerable passion and knowledge, aquarium hobbyists can play a vital role in their conservation. CARES is made up of many hobbyist organizations, whose purpose is to encourage aquarium hobbyists to the most endangered or extinct-in-the-wild freshwater fish to help ensure their survival. We found the CARES priority list contains nearly six hundred species from twenty families and two dozen species extinct-in-the-wild. The major families were typically the ones with largest hobbyist affiliations such as killifish, livebearers, and cichlids; which alone were half of CARES species. CARES contained every IUCN threatened species of Pseudomugilidae and Valenciidae, but only one percent of threatened Characidae, Cobitidae, and Gobiidae species. No Loricariidae in CARES were in the IUCN red list as they were not scientifically described. Tanzania and Mexico contained the largest amount of species, with the latter containing the most endemics. A large percent of species were classified differently than the IUCN, including a third of extinct-in-the-wild species classified as least concern by the IUCN. The vast disconnect exemplifies the importance of collaboration and information exchange required between hobbyists, the scientific community, and conservation organizations.

The study of values at European and global level has gained momentum along with the theory of values launched by Schwartz. Values are dormant, hidden, unobservable and impossible to measure directly. They exist somewhere within the human being, manifested by different attitudes, depending on their degree of generality. The paradigm of basic human values implies shared universal values that are encountered in cultures all over the world. The theory of values designed by Schwartz has refined the pool of 19 basic individual values representing principles in individuals and group, further describing the dynamic relationships among them. This study presents practical evidence of the dynamics between individual values, the dynamics theorized by Schwartz in 2012. Following the development of an online questionnaire made up of 46 items with online responses options on a Lickert scale from 1 to 6, where 1 represents less important and 6 represent very important, 220 young people from Western Romania voluntarily responded. By testing the hypothesis assuming the dynamic relationship between the two values through multiple regression analysis, the results demonstrate that in Model 1, which involves a linear relationship, health explains 42% of the variance in security with a F =161,215 significant at p <.01. In Model 2, which involves a curvilinear relationship, health explains 50% of the variance in security version with a F = 35,336 significant at p <.01. The incremental prediction optimization of 8% added by including the squared security accounts for the curve in the regression line, indicating the existence of a curvilinear relationship between security and health. The dynamic relationship demonstrates that upper limit and lower limit aspects of security, significantly influence the health value in a negative way. Normal levels of security trigger a high level of prioritization of health value. The implications of this type of relationship are discussed in explaining the value phenomenon at individual level. The study shows limits due to the selected sample, focusing exclusively on young people with higher education from the Western region of Romania. This sample was the target group of "The National Identity of Romanian Youth" project which designed this research.

Natural products from plants such as, chemopreventive agents attract huge attention because of their low toxicity and high specificity. The rational drug design in combination with structure based modeling and rapid screening methods offer significant potential for identifying and developing lead anticancer molecules. Thus, the molecular docking method plays an important role in screening a large set of molecules based on their free binding energies and proposes structural hypotheses of how the molecules can inhibit the target. Several peptide based therapeutics have been developed to combat several health disorders including cancers, metabolic disorders, heart-related, and infectious diseases. Despite the discovery of hundreds of such therapeutic peptides however, only few peptide-based drugs have made it to the market. Moreover, until date the activities of cyclic peptides towards molecular targets such as protein kinases, proteases, and apoptosis related proteins have never been explored. In this study we explore the in silico kinase and protease inhibitor potentials of cyclosaplin as well as study the interactions of cyclosaplin with other cancer-related proteins. Previously, the structure of cyclosaplin was elucidated by molecular modeling associated with dynamics that was used in the current study. Docking studies showed strong affinity of cyclosaplin towards cancer-related proteins. The binding affinity closer to 10 indicated efficient binding. Cyclosaplin showed strong binding affinities towards protein kinases such as EGFR, VEGFR2, PKB and p38 indicating its potential role in protein kinase inhibition. Moreover, it displayed strong binding affinity to apoptosis related proteins and revealed the possible role of cyclosaplin in apoptotic cell death. The protein-ligand interactions using LigPlot displayed some similar interactions between cyclosaplin and peptide-based ligands especially in case of protein kinases and a few apoptosis related proteins. Thus, the in silico analyses gave an insight of cyclosaplin as a potential apoptosis inducer and protein kinase inhibitor.

The ability to smell is crucial for most species as it enables the detection of environmental threats like smoke, fosters social interactions, and contributes to the sensory evaluation of food and eating behavior. The high prevalence of smell disturbances throughout the life span calls for a continuous effort to improve tools for quick and reliable assessment of olfactory function. Odor-dispensing pens, called Sniffin' Sticks, are an established method to deliver olfactory stimuli during diagnostic evaluation. We tested the suitability of a Bayesian adaptive algorithm (QUEST) to estimate olfactory sensitivity using Sniffin' Sticks by comparing QUEST sensitivity thresholds with those obtained using a procedure based on an established standard staircase protocol. Thresholds were measured twice with both procedures in two sessions (Test and Retest). Overall, both procedures exhibited considerable overlap with QUEST displaying slightly higher test-retest correlations, less variability between measurements, and reduced testing duration. Notably, participants were more frequently presented with the highest concentration during the QUEST which may foster adaptation and habituation effects. We conclude that further research is required to better understand and optimize the procedure for assessment of olfactory performance.

Autophagy is an evolutionarily conserved central process in host metabolism. Among its major functions are conservation of energy during starvation, recycling organelles, and turnover of long-lived proteins. Besides, autophagy plays a critical role in removing intracellular pathogens and very likely represents a primordial intrinsic cellular defence mechanism. More recent findings indicate that it has not only retained its ability to degrade intracellular pathogens, but also functions to augment and fine tune antiviral immune responses. Interestingly, viruses have also co-evolved strategies to manipulate this pathway and use it to their advantage. Particularly intriguing is infection-dependent activation of autophagy with positive stranded (+)RNA virus infections, which benefit from the pathway without succumbing to lysosomal degradation. In this review we summarise recent data on viral manipulation of autophagy, with a particular emphasis on +RNA viruses and highlight key unanswered questions in the field that we believe merit further attention.

The electrical and optical properties of sol-gel derived aluminum-doped0 zinc oxide thin films containing 2 at.% Al were investigated considering the modifying effects of 1) increasing the sol H₂O content; and 2) thermal treatment procedure with high-temperature approach followed by an additional heat-treatment step under a reducing atmosphere. According to the results obtained via the TG-DTA analysis, FT-IR spectroscopy, X-ray diffraction technique and four-point probe resistivity measurement, it is argued that the sol hydrolysis, decomposition of the deposited gel and crystallization of grains result in grains of larger crystallite size and stronger c-axis preferred orientation with slightly less microstrain in the modified sample. The consequent morphology and grain-boundary characteristics turn out as improved conductivity, implying higher values of concentration and mobility of charge carriers. A detailed investigation on samples optical properties, in terms of analyzing their absorption and dispersion behaviors through the UV-Vis-NIR spectroscopy, support our reasoning for the increase of the mobility, and to a lesser extent, the concentration of charge carriers, while causing only a slight degradation of optical transmission. Hence, an enhanced performance as a transparent conducting film is claimed for the modified sample by comparing the figure-of-merit values.

We investigate the flow structure and dynamics of moderate-Rayleigh-number ($Ra$) thermal convection in a two-dimensional inclined porous layer. Direct numerical simulations (DNS) confirm the emergence of $\mathit{O}(1)$ aspect-ratio large-scale convective rolls, with one `natural' roll rotating in the counterclockwise direction and one `antinatural' roll rotating in the clockwise direction. As the inclination angle $\phi$ is increased, the background mean shear flow intensifies the natural-roll motion, while suppressing the antinatural-roll motion. Moreover, our DNS reveal---for the first time in single-species porous medium convection---the existence of \emph{spatially-localized} convective states at large $\phi$, which we suggest are enabled by subcritical instability of the base state at sufficiently large inclination angles. To better understand the physics of inclined porous medium convection at different $\phi$, we numerically compute steady convective solutions using Newton iteration and then perform secondary stability analysis of these nonlinear states using Floquet theory. Our analysis indicates that the inclination of the porous layer stabilizes the boundary layers of the natural roll, but intensifies the boundary-layer instability of the antinatural roll. These results facilitate physical understanding of the large-scale cellular flows observed in the DNS at different values of $\phi$.

The PI3K-AKT-mTOR signal transduction pathway regulates a variety of biological processes including cell growth, cell cycle progression and proliferation, cellular metabolism and cytoskeleton reorganization. Fine-tuning of the PI3K pathway signaling output is essential for the maintenance of tissue homeostasis and uncontrolled activation of this cascade leads to a number of human pathologies including cancer. Inactivation of the tumour suppressor phosphatase PTEN and/or activating mutations in the proto-typical lipid kinase PI3K have emerged as some of the most frequent events associated with human cancer and as a result the PI3K pathway has become a highly sought-after target for cancer therapies. In this review we summarize the essential role of the PTEN-PI3K axis in controlling cellular behaviors by modulating activation of key proto-oncogenic molecular nodes and functional targets. Further, we highlight important functional redundancies and peculiarities of these two critical enzymes that over the last few decades have become a central part of the cancer research field and have instructed hundreds of pre-clinical and clinical trials to better cancer treatments.

The diffusion coefficient--a measure of dissipation, and the entropy--a measure of fluctuation are found to be intimately correlated in many physical systems. Unlike the fluctuation dissipation theorem in linear response theory, the correlation is often strongly non-linear. To understand this complex dependence, we consider the classical Brownian diffusion in this work. Under certain rational assumption, i.e. in the bi-component fluid mixture, the mass of the Brownian particle $M$ is far greater than that of the bath molecule $m$, we can adopt the weakly couple limit. Only considering the first-order approximation of the mass ratio $m/M$, we obtain a linear motion equation in the reference frame of the observer as a Brownian particle. Based on this equivalent equation, we get the Hamiltonian at equilibrium. Finally, using canonical ensemble method, we define a new entropy that is similar to the Kolmogorov-Sinai entropy. Further, we present an analytic expression of the relationship between the diffusion coefficient $D$ and the entropy $S$ in the thermal equilibrium, that is to say, $D =\frac{\hbar}{eM} \exp{[S/(k_Bd)]}$, where $d$ is the dimension of the space, $k_B$ the Boltzmann constant, $\hbar $ the reduced Planck constant and $e$ the Euler number. This kind of scaling relation has been well-known and well-tested since the similar one for single component is firstly derived by Rosenfeld with the expansion of volume ratio.

In order to evaluate the economy of superhighway, on the basis of the analysis of the cost of the ordinary expressway and high speed railway, the cost of superhighway is estimated. On this basis, the standard of the toll of superhighway at all levels is determined by reference to the standard of the construction cost and the toll collection standard of the ordinary expressway. According to the toll collection standard of superhighway and the fuel consumption cost of superhighway at all levels, the cost of single car and the single person cost of superhighway are calculated. Based on the analysis of highway passenger transport, railway passenger transport and civil aviation ticket price, the single person cost per kilometer of the above travel modes is calculated and compared with the single person travel cost per kilometer of superhighway. The results show that the single person cost of superhighway is between 0.29 and 0.47 yuan /km, which is 0.28 yuan /km higher than the highway bus, 0.18 yuan /km higher than the ordinary expressway self driving and 0.23 yuan /km higher than the express train, but 0.78 yuan/km lower than that of the first class seat of high-speed train, and is 0.92 yuan/km far lower than that of civil aviation flight economy class and 2.42 yuan/km lower than the business class. Therefore, the superhighway trip has certain advantages in economy.

In this paper we present a review of recent developments in AI towards the possibility of an artificial intelligence equals that of human intelligence. AI technology has always shown a stepwise increase in its capacity and complexity. The last step took place several years ago, with the increased progress in deep neural network technology. Each such step goes hand in hand with our understanding of ourselves and our understanding of human cognition. Indeed, AI was always about the question of understanding human nature. AI percolates into our lives, changing our environment. We believe that the next few steps in AI technology, and in our understanding of human behavior, will bring about much more powerful machines, flexible enough to resemble human behavior. In this context, there are two research fields: Artificial Social Intelligence (ASI) and General Artificial Intelligence (AGI). The authors also allude to one of the main challenges for AI, embodied cognition, and explain how it can viewed as an opportunity for further progress in AI research.

Most of the existing studies conducted on FRP-confined concrete considered circular and square concrete columns, while limited studies were on columns with rectangular sections. The studies have confirmed that the circular cross-sections exhibited higher confinement effectiveness, whereas in the case of non-circular cross-sections the efficiency of FRP confinement decreases with an increase of the sectional aspect ratio and there is no significant increase, particularly for columns with the aspect ratio of 2.0. As recently suggested by the researchers, to significantly increase the effectiveness of FRP-confinement for these columns is by modifying a rectangular section to an elliptical or oval section. According to the literature, most of the existing confinement models for FRP-confined concrete under axial compression have been proposed for columns with circular and rectangular cross-sections. However, modeling the axial strength and strain of concrete confined with FRP in elliptical cross-sections under compression is most limited. Therefore, this paper provides new expressions based on limited experimental data available in the literature. For a sufficient amount of FRP-confinement, the threshold value was proposed to be 0.02. Finally, the accuracy of the proposed model was verified by comparing its predictions with the same test database, together with those from the existing models.

Spatial data conflation plays a fundamental role in in many aspects of modern Geographic Information Systems (GIS) research and development such as geospatial data visualization, incremental updating of databases and disaster evaluation. The primary objective of conflation is to derive valuable information based on the comparison of multiple spatial data sources of homogeneous or heterogeneous nature. This paper reviews the state of art of the concept of conflation, feature matching, the most important progresses of conflation between image and road network data, and the complexity of spatial conflation.

The Science-Sustainability poses an interdisciplinary paradox. On the one hand, the science for sustainability has increased in OECD economies in and in China as well as in the US in particular; on the other hand; the sustainability situation has worsened (Co2 emission has risen). On the face value, the adverse correlation shows a paradox. However, without explicating the science-sustainability relationship, it leads to a premature conclusion. In this study, we have drawn on three concrete questions for concrete answers. First, whether and how interdisciplinary sciences—energy science and environmental science—contribute to the sustainability. Second, whether and how the Sino-US inter-institutional analysis varies in the science-sustainability paradox. The empirical analysis from a panel data in the interdisciplinary and inter-institutional context show mixed patterns in three ways. First, the increase in the environmental science shows an improvement in the sustainability; the energy science shows a decline in the sustainability. Second, the Chinese environmental science has a comparative advantage to American environment science for the sustainability development, and the Chinese energy science has a comparative disadvantage to the US in the sustainability development. Third, the environmental science mediates the energy science in the science-sustainability relationships. Standing alone, the increase in the energy science harms sustainability; mediated by environmental science, it benefits sustainability. The study explains the adverse role of energy science in Jevons Paradox. The study also offers some policy paths for further research how capitalisms differently innovate, form strategies, and implement the practice.

We construct a real square system related to a given over-determined real system. We prove that the simple real zeros of the over-determined system are the simple real zeros of the related square system and the real zeros of the two systems are one-to-one correspondence with the constraint that the value of the sum of squares of the polynomials in the over-determined system at the real zeros is identically zero. After certifying the simple real zeros of the related square system with the interval methods, we assert that the certified zero is a local minimum of the sum of squares of the input polynomials. If the value of the sum of the squares of the input polynomials at the certified zero is equal to zero, it is a zero of the input system. As an application, we also consider the heuristic verification of the isolated zeros of polynomial systems and their multiplicity structures. Notice that a complex system with complex zeros can be transformed into a real system with real zeros.

In this paper, we investigate the recently introduced degenerate Bernstein polynomials and operators and derive some of their properties. Also, we give some properties of the degenerate Euler numbers and polynomials and their connection with the degenerate Euler polynomials.

Over the years, artificial intelligence (AI) is spreading its roots in different areas by utilizing the concept of making the computers learn and handle complex tasks that previously require substantial laborious tasks by human beings. With better accuracy and speed, AI is helping lawyers to streamline work processing. New legal AI software tools like Catalyst, Ross intelligence, and Matlab along with natural language processing provide effective quarrel resolution, better legal clearness, and superior admittance to justice and fresh challenges to conventional law firms providing legal services using leveraged cohort correlate model. This paper discusses current applications of legal AI and suggests deep learning and machine learning techniques that can be applied in future to simplify the cumbersome legal tasks.

The structural, electronic and magnetochemical properties of the star-shaped polyoxopalladate [Pd₁₅O₁₀(SeO₃)₁₀]¹⁰⁻ (POPd) and its lanthanide functionalized derivatives have been investigated on the basis of density functional theory followed by a ligand field analysis using the Radial Effective Charge (REC) model. Our study predicts that heteroPOPd is a robust cryptand that enforces D_5h symmetry around the encapsulated Ln³⁺ centers. This rigid coordination environment favors interesting potential magnetic behavior in the Er and Ho derivatives, which may be of interest for molecular spintronics and quantum computing applications.

Health literacy describes skills and competencies that enable people to gain access to, understand and apply health information to positively influence their own health and the health of those in the social environment. In an increasingly media saturated and digitized world, these skill sets are necessary for accessing and navigating sources of health information and tools, such as television, the Internet, and mobile apps. The concepts of Media Health Literacy (MHL) and eHealth Literacy (eHL) describe the specific competencies such tasks require. This article introduces the two concepts, and then reviews findings on the associations of MHL and eHL with several contextual variables in the social environment such as socio-demographics, social support, and system complexity, as a structural variable. As eHL and MHL are crucial for empowering people to actively engage in their own health, a growing body of literature reports of the potential and the effectiveness of intervention initiatives to positively influence these competencies. From an ethical standpoint, equity is emphasized, stressing the importance of accessible media environments for all - including those at risk of exclusion from (digital) media sources. Alignment of micro and macro contextual spheres will ultimately facilitate both non-digital and digital media to effectively support and promote public health.

Boldine, a major aporphine alkaloid found in Chilean boldo tree, is a potent antioxidant. Oxidative stress plays a detrimental role in the pathogenesis of kidney damage in Renovascular hypertension (RVH). The activation of the Renin-Angiotensin System (RAS) is crucial in the development and progression of hypertensive renal damage and TGF-β is closely associated with the activation of RAS. In the present study, we assessed the effect of boldine on the progression of kidney disease using the 2K1C hypertension model and identifying mediators in the RAS such as TGF-β, that could be modulated by this alkaloid. Toward this hypothesis, rats (n=5/group) were treated with boldine (50mg/kg/day, gavage) for 6 weeks after 2K1C surgery (pressure≥180mmHg). Kidney function was evaluated by measuring of proteinuria/creatininuria ratio (U prot/U Crea), oxidative stress (OS) by measuring thiobarbituric acid reactive substances (TBARS). The evolution of systolic blood pressure (SBP) was followed weekly. α-SMA and Col III were used as markers of kidney damage; ED-1 and Osteopontin (OPN) as markers of inflammation. We also explored the effect in RAS mediators, such as ACE-1 and TGF-β. Boldine treatment reduced UProt/UCrea ratio, plasma TBARS and slightly reduced SBP in 2K1C hypertensive rats, producing no effect in control animals. In 2K1C rats treated with boldine the levels of α-SMA, Col III, ED-1 and OPN were lower when compared to 2K1C rats. Boldine prevented the increase in ACE-1 and TGF-β in 2K1C rats, suggesting that boldine reduces kidney damage. These results suggest that boldine could potentially be used as a nutraceutic.

Plants are such important keys of biological part of our environment, supply the human life and creatures. Understanding how the plant’s functions react with our surroundings, helps us better to make plant growth and development of food products. It means the plant phenotyping gives us bio information which needs some tools to reach the plant knowledge. Imaging tools is one of the phenotyping solutions which consists of imaging hardware such as the camera and image analysis software analyses the plant images changings such as plant growth rates. In this paper, we proposed a preprocessing algorithm to eliminate the noise and separate foreground from the background which results the plant image to help the plant image segmentation. The preprocessing is one of important levels has effect on better image segmentation and finally better plant’s image labeling and analysis. Our proposed algorithm is focused on removing noise such as converting the color space, applying the filters and local adaptive binarization step such as Niblack. Finally, we evaluate our algorithm with other algorithms by testing a variety of binarization methods.

Compared with conventional methods of fault diagnosis for power transformers, which have defects such as imperfect encoding and too absolute encoding boundaries, this paper systematically discusses various intelligent approaches applied in fault diagnosis and decision making for large oil-immersed power transformers based on dissolved gas analysis (DGA), including expert system (EPS), artificial neural network (ANN), fuzzy theory, rough sets theory (RST), grey system theory (GST), swarm intelligence (SI) algorithms, data mining technology, machine learning (ML), and other intelligent diagnosis tools, and summarizes existing problems and solutions. From this survey, it is found that a single intelligent approach for fault diagnosis can only reflect operation status of the transformer in one particular aspect, causing various degrees of shortcomings that cannot be resolved effectively. Combined with the current research status in this field, the problems that must be addressed in DGA-based transformer fault diagnosis are identified, and the prospects for future development trends and research directions are outlined. This contribution presents a detailed and systematic survey on various intelligent approaches to faults diagnosing and decisions making of the power transformer, in which their merits and demerits are thoroughly investigated, as well as their improvement schemes and future development trends are proposed. Moreover, this paper concludes that a variety of intelligent algorithms should be combined for mutual complementation to form a hybrid fault diagnosis network, such that avoiding these algorithms falling into a local optimum. Moreover, it is necessary to improve the detection instruments so as to acquire reasonable characteristic gas data samples. The research summary, empirical generalization and analysis of predicament in this paper provide some thoughts and suggestions for the research of complex power grid in the new environment, as well as references and guidance for researchers to choose optimal approach to achieve DGA-based fault diagnosis and decision of the large oil-immersed power transformers in preventive electrical tests.

A series of MgAl-layered double hydroxide (MgAl-HT), the calcined form at 500^oC (MgAlO_x) and the re-hydrated one at 25^oC (MgAl-HT-RH) were synthesized. Physicochemical properties of the catalysts were characterized by x-ray diffraction (XRD), scanning electron microscopy (SEM). Surface area of the as-synthesized, calcined and re-hydrated catalysts was determined by N₂ physisorption at -196^oC. CO₂-teperature programmed desorption (CO₂-TPD) was applied to determine the basic sites of catalysts. The catalytic test reaction was carried out using benzaldehyde and their derivatives with nitromethane and their derivatives. The Henry products (1-15) were obtained in a very good yield using MgAl-HT-RH catalyst either by conventional method at 90^oC in liquid phase, or under microwave irradiation method. The mesoporous structure and basic nature of re-hydrated solid catalyst were responsible for their superior catalytic efficiency. The robust nature was determined by using the same catalyst for five times, where the product % yield was almost unchanged significantly.

We explored the dynamics of the two interacting information systems. We show that for the Markovian marginal systems the driving force for information dynamics is determined by both the information landscape and information flux. While the information landscape can be used to construct the driving force to describe the equilibrium time reversible information system dynamics, the information flux can be used to describe the nonequilibrium time-irreversible behaviours of the information system dynamics. The information flux explicitly breaks the detailed balance and is a direct measure of the degree of the nonequilibriumness or time irreversibility. We further demonstrate that the mutual information rate between the two subsystems can be decomposed into the equilibrium time-reversible and nonequilibrium time-irreversible parts respectively. This decomposition of the mutual information rate (MIR) corresponds to the information landscape-flux decomposition explicitly when the two subsystems behave as Markov chains. Finally, we uncover the intimate relationship between the nonequilibrium thermodynamics in terms of the entropy production rates and the time-irreversible part of the mutual information rate. We found that this relationship and MIR decomposition still hold for the more general stationary and ergodic cases. We demonstrate the above features with two examples of the bivariate Markov chains.

Although floods, as well as other natural disasters, can be considered relevant causes of intra-generational inequalities, the frequent catastrophes and the resulting damages to territory reflect the generalized indifference about inter-generational justice. Societal concerns, such as land protection, typically involve the administrative system performing proactive policies in the perspective of inter-generational solidarity, but subsidiarity has made more and more independent the local communities. As a consequence, the attention toward the long run effects – typically concerning the territorial system, as a whole, at the geographical scale – has been dispersed, and the proactive policies coming from the central government has became more ineffective. Regarding the case of the flood happened in 2009 in the Fiumedinisi-Capo Peloro hydraulic basin, in the northeastern part of Sicily, Italy, we propose an economic valuation – carried out by performing the method of the imputed preferences – in order to compare the expenses incurred by the public authorities responsible for protecting the territory to the costs of the rehabilitation of the damaged areas. Some considerations about the economic significance of the proactive policies for the arrangement of territory are addressed according to the role played by the social discount rate in the inter-temporal economic calculation.

An acrobot is a planar robot with a passive actuator in its first joint. The control problem of the acrobot tries to make it rise from the rest position to the inverted pendulum position. This control problem can be divided in the swing-up problem, when the robot has to rise itself through swinging up as a human acrobat does, and the balancing problem, when the robot has to maintain itself on the inverted pendulum position. We have developed three controllers for the swing-up problem applied to two types of motors: small and big. For small motors, we used the SARSA controller and the PD with a trajectory generator. For big motors, we propose a new controller to control the acrobot, a PWM controller. All controllers except SARSA are tuned using a Genetic Algorithm.

Intuitionistic fuzzy set, which can be represented using the triangular intuitionistic fuzzy number (TIFN), is a more generalized platform for expressing imprecise, incomplete and inconsistent information when solving multi-criteria decision-making problems, as well as for reflecting the evaluation information exactly in different dimensions. In this paper, the TIFN has been applied for solving some multi-criteria decision-making problems by developing a new triangular intuitionistic fuzzy geometric aggregation operator, that is the generalized triangular intuitionistic fuzzy ordered weighted geometric averaging (GTIFOWGA) operator, and defining some triangular intuitionistic fuzzy geometric aggregation operators including the triangular intuitionistic fuzzy weighted geometric averaging (TIFWGA) operator, the ordered weighted geometric averaging (TIFOWGA) operator and the hybrid geometric averaging (TIFHWGA) operator. Based on these operators, a new approach for solving multicriteria decision-making problems when the weight information is fixed has been proposed. Finally, the proposed method has been compared with some similar existing computational approaches by virtue of a numerical example to verify its feasibility and rationality.

Regulators require financial institutions to estimate counterparty default risks from liquid CDS quotes for the valuation and risk management of OTC derivatives. However, the vast majority of counterparties do not have liquid CDS quotes and need proxy CDS rates. Existing methods cannot account for counterparty-specific default risks; we propose to construct proxy CDS rates by associating to illiquid counterparty liquid CDS Proxy based on Machine Learning Techniques. After testing 156 classifiers from 8 most popular classifier families, we found that some classifiers achieve highly satisfactory accuracy rates. Furthermore, we have rank-ordered the performances and investigated performance variations amongst and within the 8 classifier families. This paper is, to the best of our knowledge, the first systematic study of CDS Proxy construction by Machine Learning techniques, and the first systematic classifier comparison study based entirely on financial market data. Its findings both confirm and contrast existing classifier performance literature. Given the typically highly correlated nature of financial data, we investigated the impact of correlation on classifier performance. The techniques used in this paper should be of interest for financial institutions seeking a CDS Proxy method, and can serve for proxy construction for other financial variables. Some directions for future research are indicated.

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named interacting multiple model fifth-degree spherical simplex-radial cubature filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and fifth-degree spherical simplex-radial cubature filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with IMMUKF, IMMCKF and IMM5thCKF.

Constitutions as supreme legal authorities enshrine the principles of taxation which are often used as the guidance to the legislations related to fiscal aspect, requires to be explored critically so as to provide clear understanding on taxation. This article has explored the tax provisions in the constitutions of Ethiopia and Turkey from comparative perspective through the method of doctrinal legal analysis. Both the latest constitution of Turkey and Ethiopia comprise relatively related principles regarding taxation in spite of the disparities of taxation system in these two countries due to the fact that Turkey is a unitary state whereas Ethiopia is federal. In-fact, there are some disparities within these constitutions. For instance, the 1982 Constitution of Turkey specifies the citizens' duties to pay tax and the adjudication system of tax in different way than the Ethiopian 1995 constitution. The Ethiopian constitution enshrines the taxation power in detail among other things in line with the federal system of government.

In service economy, scholars and practitioners focus on the development and the appliance of innovative services. The importance of service innovation is rising in many sectors and among different organizations. Several disciplines (e.g. marketing, management, operations research, etc.) focus on this innovation, a concept widely used, but with different definitions. In this paper, service innovation has been analyzed according to SD Logic and a service ecosystem perspective. Literature still call for a deeper understanding of how new or renewed resources’ combination affect the shaping of service ecosystems. To contribute to fill this gap, the study explores the practices that different actors, internal and external to a healthcare service ecosystem, enact to co-create value in novel ways that is service innovation. The paper is structured as follows. In the next section, the main academic contributions on service research have been reviewed, focusing on healthcare service innovation. Follows, the research method and the discussion of research findings. Finally, theoretical and managerial implications have been detailed and an agenda for future research suggested. The paper offers interesting insights to develop new or renewed practices that foster the reshaping and maintaining of a healthcare service ecosystem. Some recommendations are included to support managers in the development of service innovation strategies.

In a search for a solution of the galaxy rotation problem, a novel view on cosmological gravity is developed. In this view, the origin of gravity is traced back to the basic nuclear field of energy, spread by quarks as elementary pointlike sources. This gives a common basis for gravity, electromagnetism, the strong nuclear force and the weak nuclear force. After a review on gravimagnetism and the causality problem of gravity, a hypothetical concept for the gravity field is proposed, which solves the rotation problem without the need to accept dark matter as the deus ex machina.

In recent decades, both in Italy and internationally, the phenomenon of abandoned industrial buildings has grown considerably, causing inevitable social, urban and economic impacts. At the same time, the cultural debate has increased awareness of the problem and the strategic role that abandoned industrial sites can play in responding to new needs. This contribution analyzes the dismantling process of the Akragas Montedison factory in Porto Empedocle, Sicily, examining the evolution of disused industrial areas from the 20th century to the present day and the possibilities of reconversion for appropriate reuse.