In the paper, by virtue of a Lévy–Khintchine representation and an alternative integral representation for the weighted geometric mean, the authors establish a Lévy–Khintchine representation and an alternative integral representation for the Toader–Qi mean. Moreover, the authors also collect an probabilistic interpretation and applications in engineering of the Toader–Qi mean.

The concept of genetic improvement in relation to biological control involves the exploitation of natural genetic variation for the benefit of existing biological control agents (BCAs). Despite recent calls for this process to be adopted in biological control research, there is no clear overview of the current state of research into genetic variation within a biological control context, including quantifiable estimates such as narrow-sense heritability (h²). In this systematic review, we aim to determine the current state of research on the genetic variation of biological control traits in natural enemies. After the searching process, screening for papers that can deliver on our research question reduced the initial 2,927 search hits to only a mere 69 papers for data extraction. Of these, the majority (73.6%) did not report quantitative values for genetic variation. Extracting the traits measured in these papers, we categorized them according to two approaches; the first related to fitness components, and the second related to biological control importance. This systematic review highlights the need for more rigorous reporting of the quantitative values of genetic variation to enable the successful genetic improvement of biological control agents.

Three dimension (3D) Multi-input-multi-output (MIMO) scheme, which exploits another dimension of the spatial resource, is one of the enabling technologies for the next generation mobile communication. As the elevation angle in 3D-MIMO channel model might varies against the height of the base station transmit antenna, it has to be taken into account carefully. In this paper, the impact of antenna height on the channel characteristics of 3D MIMO channel is investigated by using the intelligent ray launching algorithm (IRLA). Three typical street scenarios, i.e., the straight street, the fork road and the cross road, are selected as benchmarks. On the basis of simulations, joint and marginal probability density functions (PDFs) of both the elevation angle of departure (EAoD) and the elevation angle of arrival (EAoA) are obtained. The elevation angle spread (AS) and the delay spread (DS) under various antenna heights are also discussed. Simulation results indicate that the PDFs of EAoD and EAoA vary characteristics under different street scenarios. Moreover, the minimum value of the DS can be achieved when the antenna height is half of the building height.

Early diagnosis, prioritization, screening, clustering and tracking of COVID-19 patients, and production of drugs and vaccines are some of the applications that have made it necessary to use a new style of technology to involve, to manage and deal with this epidemic. Strategies backed by artificial intelligence (AI) and the Internet of Things (IoT) have been undeniable to understand how the virus works and try to prevent it from spreading. Accordingly, the main aim of this survey article is to highlight the methods of ML, IoT and the integration of IoT and ML-based techniques in the applications related to COVID-19 from the diagnosis of the disease to the prediction of its outbreak. According to the main findings, IoT provided a prompt and efficient approach of following the disease spread. Most of the studies developed by ML-based techniques for handling COVID-19 based dataset provided performance criteria. The most popular performance criteria, is related to accuracy factor. It can be employed for comparing the ML-based methods with different datasets. According to the results, CNN with SVM classifier, Genetic CNN and pre-trained CNN followed by ResNet, provided highest accuracy values. On the other hand, the lowest accuracy was related to single CNN followed by XGboost and KNN methods.

For a wide field of view (FoV) wavefront coding athermalized infrared imaging system with a single decoding kernel, the off-axis aberration tends to cause artefacts. In order to correct off-axis aberration, many pieces of lenses will reduce the transmission efficiency and increase the weight and cost. To meet requirements for wide FoV, wide operating temperature and low weight of infrared imaging systems, this paper reports a wide-FoV wavefront coding athermalized infrared imaging system with a two-piece lens. Its principle, design, manufacture, measurement and performance validation are successively discussed. This paper constructs an optimization problem which maximizes the weighted mean of PSF consistency for both the FoV and operating temperature range. The two-piece lens contains four surfaces, where three aspheric surfaces are introduced to reduce optical off-axis aberrations and a cubic surface is introduced to achieve athermalization. The optical phase mask containing an aspheric surface and a cubic surface is manufactured by nano-metric machining of ion implanted material(NiIM). Experimental results validate that our wide-FoV wavefront coding athermalized infrared imaging system has a full FoV of 26.10° and an operating temperature over -20°C to +70°C.

We address the need for a model by considering two competing theories regarding the origin of life: (i) the Metabolism First theory and (ii) the RNA World theory. We discuss two inter-related points. (I) Models are valuable tools in understanding both the processes and intricacies of the origin of life issues. (II) Insights from models also help us to evaluate the core objection to origin of life theories called “the inefficiency objection” commonly raised by proponents of both the Metabolism First theory and the RNA World theory against each other. We use Simpson’s paradox as a tool for challenging this objection. We will use models in various senses ranging from taking them as representations of reality to treating them as theories/accounts that provide heuristics for probing reality. In this paper, we will frequently use models and theories interchangeably. Additionally, we investigate Conway’s Game of Life and contrast it with our Simpson’s Paradox (SP)-based approach to emergence of life issues. Finally, we discuss some of the consequences of our view. A scientific model is testable in three senses: (i) a logical sense, (ii) a nomological sense, and (iii) a current technological sense. The SP-based model is testable in the logical sense. It is also testable nomologically. However, it is not currently feasible to test it.

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

Abstract: Afghanistan witnessed rapid urbanization in recent decades due to the post-war recovery process. When the war ended in 2001 by fall of Taliban regime, most Afghans refugees returned to urban areas of Afghanistan, especially in Kabul city. Moreover, the rapid urbanization, migration from rural areas, and population growth impacted on Kabul city with the manifestation of informal settlement. The residents of informal settlements suffer social and economic exclusion from the benefit and opportunity of an urban environment. Furthermore, the residents of informal settlements experience disadvantages by geographical marginalization, shortage of basic infrastructure, improper governance framework, vulnerability into the effect of poor environment, and natural disasters. With all the above, the problems of informal settlements are considered enormous challenges for informal residents. Therefore, this paper aims to identify the proper approaches to addressing informal settlement problems in District 13 of Kabul city. To reach the aim of the research, the interview and questionnaires survey used as an instrument in data collection. Consequently, the finding of this paper indicates that through the resident’s preferences, government capacity, and District 13 physical condition there are three approaches which can be implemented and adopted for improvement of informal settlement in District 13 of Kabul city, which is settlement upgrading as the first option, the land readjustment as the second option and urban redevelopment as the last option.

The study investigates the determinants of mobile Internet banking adoption among Gen-Y in Malaysia. Align the issue of the study and research objectives, and the study underpinned Technology Acceptance Model (TAM) as the main guideline or a blueprint to analyze the research model. The study applied survey research design and analyzed using Structural Equation Modelling (SEM) under the PLS-SEM technique with SmartPLS 2.0. A total of 358 mobile internet banking users in Malaysia were random proportional selected as respondents and analyzed. Results from the partial least square structural equation modeling (PLS-SEM) revealed that perceived ease of use, perceived usefulness, facilitating condition, and personal innovativeness in IT have significantly influenced the attitude of mobile internet banking adoption in Malaysia. Additionally, perceived ease of use and facilitating conditions found to have a significant influence on the perceived usefulness of Mobile Internet Banking. Lastly, facilitating conditions and personal innovativeness in IT are significantly influence the perceived ease of use of mobile internet banking among Gen-Y in Malaysia

This paper presents an improved indoor localization system based on RF and ultrasonic signal which we named SNSH system. This system composes of a transmitter mounted in a mobile target, and a series of receiver nodes which are managed by a coordinator. By measuring Time Delay of Arrival (TDoA) of RF and ultrasonic signal from the transmitter, distance from target to receiver node is calculated and sent to the coordinator through CAN network, and all the information are gathered in PC to estimate 3D position of the target. Sine wave detector and dynamic threshold filter are applied to provide excellent accuracy of range measurement from TDoA result, and multilateration algorithms is realized to optimize coordinate determination accuracy. Specifically, Linear Least Square and Non-linear Least Square techniques are implemented to contrast their performances in target coordinate estimation. RF signal encoding/decoding time, time delay in CAN network and math calculating are carefully considered to ensure optimal system performance and get ready for field application. Experiments show that sine wave detector algorithm has greatly improved range measurement accuracy, with mean error at 2.2mm and maximum error at 6.7 mm, for distance below 5m. In addition, 3D position accuracy is greatly enhanced by multilateration methods, with mean error in position stay under 15mm, and 90% confident error values at 23mm for LLS, 20mm for NLS. Overall system update period has been verified in real system operation, with maximum rate at 25ms, and compared with other existing researches.

Background: Obesity among pregnant women is common, and their offspring are predisposed to obesity, insulin resistance, and diabetes. Circulating metabolites that are related to insulin resistance and are associated with this decreased tissue-specific uptake are unknown. Here, we assessed metabolite profiles in elderly women and who were either female offspring from obese mothers (OOM) or offspring of lean mothers (OLM). Metabolic changes were tested for associations with metrics for insulin resistance. Methods: 37 elderly women were separated into an elderly offspring from obese mothers (OOM; n = 17) and elderly offspring from lean/normal weight mothers (OLM; n = 20) groups. We measured plasma metabolites using 1H-NMR and also insulin-dependent tissue specific glucose uptake in skeletal muscle were assessed. Associations were made between metabolites and glucose uptake. Results: Compared to the OLM group, we found that the 22:6 docosahexaenoic acid percentage of the total long chain n-3 fatty acids (DHA/FA) was significantly lower in OOM (P = 0.015). DHA/FA associated significantly to skeletal muscle GU (P = 0.031) and M-value in the OLM group only (P = 0.050). Conclusions: DHA/FA is associated with insulin-dependent skeletal muscle glucose uptake and that this association is significantly weakened in the offspring of obese mothers.

Renewable energy sources will play a central role in the sustainable energy systems of the future. Scenario analyses of such hypothesized energy systems require sound knowledge of the techno-economic potential of renewable energy technologies. Although there have been various studies concerning the potential of offshore wind energy, higher spatial resolution, as well as the future design concepts of offshore wind turbines, has not yet been addressed in sufficient detail. Here, we aim to overcome this gap by applying a high spatial resolution to the three main aspects of offshore wind potential analysis, namely ocean suitability, the simulation of wind turbines and cost estimation. A set of constraints is determined that reveal the available areas for turbine placement across Europe’s maritime boundaries. Then, turbine designs specific to each location are selected by identifying turbines with the cheapest levelized cost of electricity (LCOE), restricted to capacities, hub heights and rotor diameters of between 3-20 MW, 80-200 m and 80-280 m, respectively. Ocean eligibility and turbine design are then combined to distribute turbines across the available areas. Finally, LCOE trends are calculated from the individual turbine costs, as well as the corresponding capacity factor obtained by hourly simulation with wind speeds from 1980 to 2017. The results of cost-optimal turbine design reveal that the overall potential for offshore wind energy across Europe will constitute nearly 8.6 TW and 40.0 PWh at roughly 7 €_ct kWh^-1 average LCOE by 2050. Averaged design parameters at national level are provided in an appendix.

Repair mortar is commonly used to rehabilitate reinforced concrete structures or components that exhibit a relatively high level of distresses. Yet, this repair mortar can be contaminated by salt from its service environment. This work employs a two-dimensional finite element model to investigate the transport behavior of ionic species in salt-contaminated and water-saturated repair mortar under an externally applied electric field. The model was experimentally validated and then utilized to evaluate the effectiveness of electrochemical chloride extraction (ECE) with or without electrical injection of corrosion inhibitor (EICI). In the case study, both the ECE alone and the ECE+EICI treatment was found effective in decontaminating the zone in front of the steel rebar. In both techniques, the magnitude of current density has a significant effect on removing chloride out of the mortar and increasing the pH of the pore solution near the rebar, whereas the treatment time any not have a significant effect under some scenarios. The injection of the organic corrosion inhibitor significantly slowed down the removal of chloride. Changes in the ionic distribution in the mortar were generally beneficial in reducing the corrosion risk of the steel rebar and thus extending the service life of the repair mortar.

Modularity is arguably one of the most influential theses guiding research on brain and cognitive function since phrenology. This paper considers the following question: is modularity entailed by recent Bayesian models of brain and cognitive function, especially the predictive processing framework? It starts by considering three of the most well-articulated arguments for the view that modularity and predictive processing work well together. It argues that all three kinds of arguments for modularity come up short, albeit for different reasons. The analysis in this paper, although formulated in the context of predictive processing, speaks to broader issues with how to understand the relationship between functional segregation and integration and the reciprocal architecture of the predictive brain. These conclusions have implications for how to study brain and cognitive function. Specifically, when cognitive neuroscience works within an acyclic Markov decision scheme, adopted by most Bayesian models of brain and cognitive function, it may very well be methodologically misguided. This speaks to an increasing tendency within the cognitive neurosciences to emphasise recurrent and reciprocal neuronal processing captured within newly emerging dynamical causal modelling frameworks. The conclusions also suggest that functional integration is an organising principle of brain and cognitive function.

Objective: To investigate the correlation between engagement and quality of life at work in nursing professionals, from a public hospital in the interior of the state of São Paulo, Brazil, at the beginning of the Covid-19 pandemic. Methods: Cross-sectional, descriptive, and correlational study, with nursing professionals, conducted between December 2020 and January 2021. We used the Brazilian versions of the Utrecht Work Engagement Scale and the Walton Model scale. Results: The nursing professionals obtained a strong and positive correlation (r≥0.70) between the social integration domain of QWL and vigor dimension of work engagement (r=0.88; p=<0.001); moderate positive correlation (r≥0.40≤0.69) between QWL working conditions and vigor (r=0.40; p=<0.001), dedication (r=0.40; p=<0.001) and overall score (r=0.41; p=<0.001) of the work engagement. The correlations were positive and weak (r≤0.39) for the other domains of QWL and dimensions of work engagement. Conclusion: Professionals with satisfactory levels of quality of life tended to have higher levels of engagement at work. Professionals were strongly engaged and satisfied with their quality of life at work at the beginning of the Covid-19 pandemic.

An approximation-free and fully quantum optic formalism for parametric processes is presented. Phase-dependent gain coefficients and related phase-pulling effects are identified for quantum Rayleigh emission and the electro-optic conversion of photons providing parametric amplification in small scale integration of photonic devices. These mechanisms can be manipulated to deliver, simultaneously, sub-Poissonian distributions of photons as well as phase-dependent amplification in the same optical quadrature of a signal field.

The rapid increase in metabolic diseases occurred in the last three decades in both industrialized and developing countries has been related to the rise in sugar-added foods and sweetened beverages consumption. An emerging topic in the pathogenesis of metabolic diseases related to modern nutrition is the role of Advanced Glycation Endproducts (AGEs). AGEs can be ingested with high temperature processed foods, but also endogenously formed as consequence of a high dietary sugars intake. Animal models of high sugars consumption, in particular fructose, have reported AGEs accumulation in different tissues in association with peripheral insulin resistance and lipid metabolism alterations. The in vitro observation that fructose is one of the most rapid and effective glycating agent when compared to other sugars has prompted the investigation of the in vivo fructose-induced glycation. In particular, the widespread employment of fructose as sweetener has been ascribed by many experimental and observational studies for the enhancement of lipogenesis and intracellular lipid deposition. Indeed, diet-derived AGEs have been demonstrated to interfere with many cell functions such as lipid synthesis, inflammation, antioxidant defences, and mitochondrial metabolism. Moreover, emerging evidences also in humans suggest that this impact of dietary AGEs on different signalling pathways can contribute to the onset of organ damage in liver, skeletal and cardiac muscle, and brain, affecting not only metabolic control, but global health. Indeed, the here reviewed most recent reports on the effects of high sugars consumption and diet-derived AGEs on human health suggest the need to limit the dietary sources of AGEs, including added sugars, to prevent the development of metabolic diseases and related comorbidities.

Riemann’s method is one of the definitive ways of solving Cauchy’s problem for a second order linear hyperbolic partial differential equation in two variables. The first review of Riemann’s method was published by E. T. Copson in 1958. This study extends that work. Firstly, three solution methods were overlooked in Copson’s original paper. Secondly, several new approaches for finding Riemann functions have been developed since 1958. Those techniques are included here and placed in the context of Copson’s original study. There are also numerous equivalences between Riemann functions that have not previously been identified in the literature. Those links are clarified here by showing that many known Riemann functions are often equivalent due to the governing equation admitting a symmetry algebra isomorphic to $SL(2,R)$. Alternatively, the equation admits a Lie-Bäcklund symmetry algebra. Combining the results from several methods, a new class of Riemann functions is then derived which admits no symmetries whatsoever.

A plasmonic refractive index (RI) sensor based on metal-insulator-metal (MIM) waveguide coupled with concentric double rings resonator (CDRR) is proposed and investigated numerically. Utilizing the novel supermodes of the CDRR, the FWHM of the resonant wavelength can be modulated, and a sensitivity of 1060 nm/RIU with high figure of merit (FOM) 203.8 is realized in the near-infrared region. The unordinary modes as well as the influence of structure parameters on the sensing performance are also discussed. Such plasmonic sensor with simple framework and high optical resolution could be applied to on-chip sensing systems and integrated optical circuits. Besides, the special cases of bio- sensing and triple rings are also discussed.

Social distancing, washing hands and good hygiene are essential and currently the most potent methods available to curb down the unprecedented speed by which the new coronavirus is spreading across the globe. Even under lockdown, which is necessary to significantly reduce the number of people that get infected by an ill person, are there additional measures that each of us can embrace to even further reduce the risk of infection and the severity of the COVID-19 disease? Given the lack of licensed drugs that target SARS-CoV-2 specifically, we have to look into additional non-specific defense mechanisms that animals and humans evolved to protect themselves from pathogen invasions. The goal of this article is to describe how various of our non-specific defense mechanisms work, which actually precede the inflammatory response, and to discuss whether we can exploit the unique features of the coronavirus envelope and the self-cleaning machinery of the human respiratory tract to strengthen our self-defense. The challenge is to actively interfere with supportive measures during the short time window between getting exposed and before an inflammatory response gets initiated.

A basic problem in all postulated pathways of prebiotic chemistry is the low concentration which generally is expected for interesting reactants in fluid environments. Even though compounds like nucleobases, sugars or peptides principally may form spontaneously under environmental conditions, they will always be rapidly diluted in an aqueous environment. In addition, any such reaction leads to side products which often exceed the desired compound and generally hamper the first steps of a subsequent molecular evolution. Therefore, a mechanism of selection and accumulation of relevant prebiotic compounds seems to be crucial for molecular evolution. A very efficient environment for selection and accumulation can be found in the fluid continuum circulating in tectonic fault zones. Vesicles which form spontaneously at a depth of approximately 1 km present a selective trap for amphiphilic molecules, especially for peptides composed of hydrophilic and hydrophobic amino acids in a suitable sequence. The accumulation effect is shown in a numeric simulation on a simplified model. Further, possible mechanisms of a molecular evolution in vesicle membranes are discussed. Altogether, the proposed scenario can be seen as an ideal environment for constant, undisturbed molecular evolution in and on cell-like compartments, the latter offering preferential starting conditions for a subsequent RNA world.

Modern day construction is widely influenced using concrete-steel composite columns. A lot of research on concrete-steel composite columns is being carried out around the world. The rapid growth in concrete-steel composite construction has widely decreased the use of conventional reinforced cement concrete construction (R.C.C), and the steel construction practices. The concrete-steel composite construction has obtained an extensive receiving around the globe. As Pakistan is a developing country, so, it is relatively a new concept for its construction industry when compared with the developed countries around the globe. Although, the R.C.C construction is suitable and economical for construction of framing systems of low-rise buildings, however, the increased dead load, span restrictions, less stiffness and risky formwork makes it uneconomical and unviable when it comes across the construction of intermediate to high-rise buildings. This research is an effort to learn the cost effectiveness, increased or decreased stiffness, and change on the functionality of the composite construction for intermediate to high-rise buildings constructed in Pakistan. A Base + Ground + 11 storey commercial building is selected for this study. A comparison is made between conventional R.C.C columns structure and concrete-encased composite columns structure. The equivalent static nonlinear analysis is performed using ETABS 2017 software. Although, for Base + Ground + 11 storey building, the construction cost of concrete-encased composite structure is 7.7% more than the conventional R.C.C columns structure, but the concrete-encased composite structure will have 13.013% more constructed floor area. This increased floor area helps to settle the cost difference between the two structures.

This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things computing. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSN. Then, using the CUDA Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes’ diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services.

The present examination explored the impact of work spirituality and procedural justice on work locus of control, worker work fulfillment and representative authoritative duty among workers from private establishments of high learning in South Africa. Due to limited researches that have concentrated on the impact of workplace spirituality and procedural justice on work locus of control, employee job satisfaction and employee organisational commitment in developing countries especially in Southern Africa. A review was done and information was accumulated by methods for surveys on a sample of 150 academics and support staff in a private university setting in Gauteng, South Africa. Structural equation modelling was employed to analyse data using the Smart Partial Least Squares (PLS) software. By means of a partial least squares structural equation modeling approach, this study validates that elements such as workplace spirituality, procedural justice and work locus of control are instrumental in stimulating the employee job satisfaction and employee job commitment. The present investigation offers suggestions for academicians in the field of resource management by upgrading their comprehension of the how workplace spirituality and procedural justice impacts work locus of control, employee job satisfaction and employee organisational commitment

Artificial Intelligence innovations, such as chatbots and specialized education suggestion tools, provide potential interactive and on-demand pedagogical engagement between non-Christians and Christians with Christianity. However, there is little empirical research on the readiness, acceptance, and adoption of A.I.'s involvement in religious education in a secular state, such as Vietnam. This research addresses the literature gap by providing an entrepreneurial analysis and customer perspectives on the ideas of A.I.'s involvement in religious education. Specifically, the study explores whether the Vietnamese across different ages and religious orientations accept and have enough skills to adopt A.I.'s religious education innovation. The interview sample is 32 participants, selected based on their religious orientation (Christians & Non-Christians) and age (Generation X, Generation Y & Generation Z). Most respondents are open to A.I. application in religious education except for the Church's personnel. However, only gen Z generations are fully prepared to adopt this innovation. Theoretically, the research customizes the Unified Theory of Acceptance and Use of Technology model into religious innovation context. Practically, this research acts as market research on the demand for A.I.'s religious innovation in Vietnam, an insight for future religious tech entrepreneurs.

The Estimation of systemic risk in India is still in its infancy stage. There are several methods which are available but none of the methods are fully compatible to forecast the systemic risk since under different circumstances the factors responsible for the risk differs. In this paper the systemic risk estimation in India being carried out based on spread in daily stock market price(Difference between the bid and ask price of a share) of the top 100 firms in India according to market capitalization for the period of July2007 to March 2016. The results were compared with the Financial Stability Report published by Reserve Bank Of India for the period of March 2010 to June 2016.The results clearly indicates that there exits relationship between market illiquidity represented by spread and risks associated with the Financial System. In most of the cases the Z score (deviation from the mean/Standard Deviation) of the spread has become negative which provides the spread which is farther from the mean, also a good indicator of volatility in market and risk to financial system. It is also seen that the Systemic Risk Survey conducted by Reserve Bank of India which started during October 2011 has supported the results.

To eliminate the influence of the inconsistency on the cycle life and the available capacity of the battery pack, and improve the balancing speed, a novel inductor-based layered bidirectional equalizer (IBLBE) is proposed. The equalizer is composed of the bottom balancing circuits and the upper balancing circuits, and the two layer circuits both consist of a plurality of balancing sub-circuits, which allow the dynamic adjustment of equalization path and equalization threshold. The battery string is modularized by layered balancing circuits to realize fast active equalization, especially for long battery strings. By controlling the bottom balancing circuits, the individual cells can be balanced in each module. At the same time, the equalization between battery modules can be realized by controlling the upper balancing circuits. Simulation and experimental results demonstrate that the proposed equalizer can achieve fast active equalization for a long battery string, and has the characteristics of multi balancing path, large balancing current and high accuracy. The advantages of the proposed equalizer are further verified by a comparison with existing active equalizer.

How did life begin on Earth? And is there life elsewhere in the Cosmos? Challenging questions, indeed. The series of conferences established by NoR CEL in 2013, addresses these very same questions. The basis for this paper is the summary report of oral presentations that were delivered by NoR CEL’s network members during the 2018 Athens conference and, as such, disseminates the latest research which they have put forward. More in depth material can be found by consulting the contributors referenced papers. Overall, the outcome of this conspectus on the conference demonstrates a case for the existence of “probable chemistry” during the prebiotic epoch.

Synthetic Aperture RADAR (SAR) is a radar imaging technique in which the relative motion of the sensor is used to synthesize a very long antenna and obtain high spatial resolution. Standard SAR raw data processing techniques assume uniform motion of the satellite (or aerial vehicle) and a fixed antenna beam pointing sideway orthogonally to the motion path, assumed rectilinear. Despite SAR data processing is a well established imaging technology that has become fundamental in several fields and applications, in this paper a novel approach has been used to exploit coherent illumination, demonstrating the possibility of extracting a large part of the ancillary data information from the raw data itself, to be used in the focusing procedure. In this work an effort has been carried out to try to focus the raw SAR complex data matrix without the knowledge of anyof the parameters needed in standard focusing procedures as Range Doppler (RD) algorithm, ω - K algorithm and Chirp Scaling (CS) algorithm. All the literature references regarding the algorithms needed to obtain a precise image from raw data use such parameters that refer both to the SAR system acquisition geometry and its radiometric specific parameters. In [12], authors introduced a preliminary work dealing with this problem and able to obtain, in the presence of a strong point scatterer in the observed scene, good quality images, if compared to the standard processing techniques. In this work the proposed technique is described and performances parameters are extracted to compare the proposed approach to RD.

Objective: In this pilot study, we described the gross motor development of infants aged 4 to 24 months with congenital heart disease (CHD) and assessed through a systematic develop­mental screening programme, with individualised motor interventions. Methods: Thirty infants who had cardiac repair underwent gross motor evaluations using the AIMS at 4 months, and the Bayley-III at 12 and 24 months. Results: Based on AIMS, 80% of 4-month-old infants had a delay in gross motor development and required physical therapy. Gross motor abilities significantly improved by 24 months. Infants who benefited from regular physiotherapy tended to show better improvement in motor scores. Conclusion: Our study highlights the importance of early motor screening in infants with CHD and suggests a potential benefit of early physical therapy in those at-risk. Further research is needed to assess the effectiveness of systematic developmental screening and individualized inter­vention programmes at identifying at risk patients, and their impact on developmental outcomes.

Warren Weaver, writing about the function that science should have in mankind’s developing future, ideas and ideals, proposed to classify scientific problems into ‘problems of simplicity’, ‘problems of disorganised complexity’, and ‘problems of organised complexity’ — the huge complementary class to which all biological, human, and social problems belong. Problems of simplicity have few components and variables and have been extensively addressed in the last 400 years. Problems of disorganised complexity have a huge number of individually erratic components and variables, but possess collective regularities that can be analysed by resourcing to stochastic methods. Yet, problems of organised complexity do not yield easily to classical or statistical treatment since interrelations among phenomenon elements change during its evolution alongside commonly used state variables, affecting behaviour and outcome. Moreover, organisation, the focal point in this complementary class, is still an elusive concept despite the gigantic efforts undertaken since a century ago to tame it. This paper addresses the description, representation and study of phenomena in the ‘problems of organised complexity’ class. Grounded on relational mathematical constructs, a theoretical framework providing operational definitions and schemes for formally modelling organisations and interaction of organisations is introduced. This framework extends the general systems’ concept and provides a novel perspective for addressing organised complexity phenomena as a collection of interacting organisations.

We present information theoretic search strategies for single and multi-robot teams to localize the source of biochemical contaminants in turbulent flows. The robots synthesize the information provided by sporadic and intermittent sensor readings to optimize their exploration strategy. By leveraging the spatio-temporal sensing capabilities of a mobile sensing network, our strategies result in control actions that maximize the information gained by the team while optimizing the time spent localizing the position of the biochemical source. By leveraging the team's ability to obtain simultaneous measurements at different locations, we show how a multi-robot team is able to speed up the search process resulting in a collaborative information theoretic search strategy. We validate our proposed strategies in both simulations and experiments.

In order to establish a new discipline specializing in accident science from the perspective of safety science. Under the guidance of the current research theories and methods of safety science, combined with the research paradigm of humanities and social medicine, this paper puts forward new viewpoints, new theories and new models about accident research. First of all, through literature retrieval, this paper analyzes the relevant research results of accidents at home and abroad, and expounds the existing problems and the basic trend of accident science research. Secondly, it puts forward eight kinds of attribute relations of the accident, and makes clear the characteristics and connotation of the accident. In the study of accident types, a hierarchical classification model based on accident cognition is created for the first time. It also points out the logical relevance of five levels of accident science research and the realistic relevance of three levels. At the same time, according to the thought of science of science, this paper puts forward a new definition of safety under the thinking of accident science and other basic concepts related to safety science, and explains the connotation. In addition, it creates and constructs the basic concept of accident science, establishes the conceptual model of accident science, and points out the “3-4-5” model of accident science research and its connotation. Thirdly, draw lessons from the interdisciplinary paradigm to study the relevant theoretical basis and discipline classification relationship of accident science, and construct the tree of accident science. Finally, the research contents of three main aspects of accident science are summarized. The results show that the research results in this paper not only play a fundamental role in the basic construction of accident science, but also further enrich and perfect the discipline system of safety science, which has a certain theoretical significance.

Mechanical forces and mechanical energy are prevalent in living cells. This may be because mechanical forces and mechanical energy preceded chemical energy at life’s origins. Mechanical energy is more readily available in non-living systems than the various forms of chemical energy used by living systems. Two possible prebiotic environments that might have provided mechanical energy are hot pools that experience wet/dry cycles and mica sheets as they move, open and shut, as heat pumps or in response to water movements.

There is limited evidence for the association between malnutrition and hospital mortality as well as Intensive Care Unit length-of-stay (ICU-LOS) in critically ill patients. We aimed to examine the aforementioned associations by conducting a prospective cohort study in an ICU of a Singapore tertiary hospital. Between August 2015 and October 2016, all adult patients with ≥24 h of ICU-LOS were included. The 7-point Subjective Global Assessment (7-point SGA) was used to determine patients’ nutritional status within 48 hours of ICU admission. Multivariate analyses were conducted in two ways: 1) presence versus absence of malnutrition, and 2) dose-dependent association for each 1-point decrease in the 7-point SGA. There were 439 patients of which 28.0% were malnourished, and 29.6% died before hospital discharge. Malnutrition was associated with an increased risk of hospital mortality [adjusted-RR 1.39 (95%CI: 1.10–1.76)], and this risk increased with a greater degree of malnutrition [adjusted-RR 1.09 (95%CI: 1.01–1.18) for each 1-point decrease in the 7-point SGA]. No significant association was found between malnutrition and ICU-LOS. Conclusion: There was a clear association between malnutrition and higher hospital mortality in critically ill patients. The association between malnutrition and ICU-LOS could not be replicated and hence requires further evaluation.

Introduction: Despite more than one year passed since the first cases of SARS-CoV-2 were reported, there is still no consensus on the definition and clinical management of post-acute-COVID-19. The condition has heterogeneously been named as Chronic COVID syndrome, Post COVID-19 Syndrome, post-acute sequela of SARS-CoV-2 (PASC), and the more familiar long COVID. Method: In order to capture all relevant published studies, we undertook a multi-step search with no language restriction. The following four-step search strategy was utilized: First, a preliminary (limited) search was conducted on January 20, 2021, in Google Scholar and PubMed to identify the appropriate keywords. Then, on January 30, 2021, we adopted a search strategy of electronic databases from Cochrane Library, PsycINFO, PubMed, Embase, Scopus, and Web of sciences, using those keywords. Then, after duplicate removal, we screened all titles, abstracts, and full texts. This resulted in 66 eligible studies. Subsequently, after a forward and backward search of their references and citations an additional 54 publications were found, resulting in a total of 120 publications that formed the basis of the present analysis. The titles, abstracts, and full-texts of non-English articles were translated using Google Translate for further evaluation. We conducted our scoping review based on the PRISMA-ScR Checklist.Results: We found only one randomized clinical trial in our search. Of the 67 original studies, 22 were cohort and 28 were cross-sectional studies totaling 74.6% of the original studies. Of the total of 120 publications, 59 (49.1%) focused on signs and symptoms, 28 (23.3%) were focused on management, and 13 (10.8%) focused on pathophysiology. Ten (9%) publications focused on imaging studies. Ninety-one percent of the original investigations came from high and upper-middle-income countries, highlighting the scarcity of reports originating from low-income and lower-middle-income countries.Conclusion: The predominant symptoms among those with the so-called “Long COVID” were: fatigue, breathlessness, arthralgia, sleep difficulties, and chest pain. Recent reports also point to the risk of long-term sequela with cutaneous, respiratory, cardiovascular, musculoskeletal, mental health, neurologic, and renal involvement in those who survive the acute phase of the illness. The ambiguity and controversies in its definition have impaired proper recognition and management of those requiring additional support following the resolution of the acute phase of this infection. This has resulted in long-standing distress for the patients and their families. Our findings highlight the need for a multidisciplinary approach, support, and rehabilitation for these patients in terms of long-term mental and physical health.

In this paper, we study the well-posedness and asymptotics of a one-dimensional thermoelastic laminated beam system either with or without structural damping, where the heat conduction is given by Fourier's law effective in the rotation angle displacements. We show that the system is well-posed by using Lumer-Philips theorem, and prove that the system is exponentially stable if and only if the wave speeds are equal, by using the perturbed energy method and Gearhart-Herbst-Prüss-Huang theorem. Furthermore, we show that the system with structural damping is polynomially stable provided that the wave speeds are not equal, by using the second-order energy method.

The calculation of the vapour pressure of organic molecules at 298.15K is presented using a commonly applicable computer algorithm based on the group-additivity method. The basic principle of this method rests on the complete breakdown of the molecules into their constituting atoms, further characterized by their immediate neighbour atoms. The group contributions are calculated by means of a fast Gauss-Seidel fitting algorithm using the experimental data of 2036 molecules from literature. A ten-fold cross-validation procedure has been carried out to test the applicability of this method, which confirmed excellent quality for the prediction of the vapour pressure, expressed in log(pa), with a cross-validated correlation coefficient Q2 of 0.9938 and a standard deviation  of 0.26. Based on these data, the molecules' standard Gibbs free energy G°vap has been calculated. Furthermore, using their enthalpies of vaporization, predicted by an analogous group-additivity approach published earlier, the standard entropy of vaporization S°vap has been determined and compared with experimental data of 1129 molecules, exhibiting excellent conformance with a correlation coefficient R2 of 0.9598, a standard error  of 8.14 J/mol/K and a medium absolute deviation of 4.68%.

The 21^st century has witnessed precipitous changes spanning from the way of life to the technologies that emerged. We have entered a nascent paradigm shift (industry 4.0) where science fictions have become science facts, and technology fusion is the main driver. Thus, ensuring that any advancement in technology reach and benefit all is the ideal opportunity for everyone. In this study, disruptive technologies of industry 4.0 was explored and quantified in terms of the number of their appearances in published literature. The study aimed at identifying industry 4.0 key technologies which have been ill-defined by previous researchers and to enumerate the required skills of industry 4.0. Comprehensive literature survey covering the field of engineering, production, and management was done from multidisciplinary databases: Google scholar, ScienceDirect, Scopus, Sage, Taylor & Francis and Emerald insight. Results of the electronic survey showed that 35 disruptive technologies were quantified and 13 key technologies: Internet of things, Big data, 3D printing, Cloud computing, Autonomous robots, Virtual and Augmented reality, Cyber physical system, Artificial intelligence, Smart sensors, Simulation, Nanotechnology, Drones and Biotechnology were identified. Both technical and personal skills to be imparted into the human workforce for industry 4.0 were reported. The study identified the need to investigate the capability and the readiness of developing countries in adapting industry 4.0 in terms of the changes in the education systems and industrial manufacturing settings. The study proposes the need to address integration of industry 4.0 concepts into the current education system.

First, this paper broaches the epistemological status of scientific tenets and approaches: phenomenological (descriptive only), well-founded (solid first principles, conducive to deep understanding), provisional (can be falsified if universal and verified if existential), and imaginary (fictitious entities or processes, conducive to empirically unsupported beliefs). The ΛCDM “concordance model” involves such beliefs: the emanation of the universe out of a non-physical stage, cosmic inflation (invented ad hoc), Λ (fictitious energy), and exotic dark matter. Big Bang cosmology further faces conceptual and pragmatic problems in delimiting what expands from what does not. The problems dissolve after untying inertia from space. The cosmology that emerges appears immediately compatible with the considered observations and the ‘perfect cosmological principle’. Waves and field perturbations that propagate at c expand exponentially with distance (a gravitational effect). The cosmic web of galaxies does not. Potential -Φ varies as H/(cz) instead of 1/r. Inertial forces arise from the gravitational action of the rest of the universe. Due to dilatation, they are reduced disproportionately at low accelerations. A cut-off value a₀ = 0.168 cH is deduced. This explains the successful description of galaxy rotation curves by MoND. A fully elaborated physical theory is still pending. Wider implications are briefly discussed.

Nietzsche is almost always regarded as one of the thinkers who advocate extreme individualism, totally indifferent to or exclusively polemical towards the public human dimension. While this is very difficult to contradict, if we read his texts carefully we can see how his constant celebration of the individual runs parallel to an acute awareness of living in a new era, which he defined as ‘the century of the multitude and the masses’. The herd, conformism, mediocrity, public opinion: a civilisation in which community attempts suffocate all individual inspiration, and which therefore seems to row in the opposite direction. Although Nietzsche often uses collective life merely as a negative pole for more effectively emphasising the individual, his provocative words—pushed to the limits of the inexorable victory of the herd and of the paradoxical impossibility of all that is ‘public’—offer us a direct testimony of the tragic way of life of the man of his time. This provides us with an extremely clear and interesting phenomenological cross-section of the social sphere, as well as a very finely tuned and valuable seismograph for the continual monitoring of our everyday coexistence with and perception of the constantly incumbent dangers of its degeneration.

The heavy demand of water resources from the Zarqa River Basin (ZRB) has resulted in a base-flow reduction of the River from 5m³/s to less than 1m³/s. This paper aims at predicting Curve Numbers (CN) as a baseline scenario and proposing restoration scenarios for ZRB. The method includes classifying the soil type and land use, predicting CNs, and proposing CN restoration scenarios. Prediction of existing CNs will be in parallel with the runoff prediction using the US Army Corps of Engineers HEC-1 Model, and Rainfall-Runoff Model (RRM). The models have been set up at the land use distribution of 0.3% water body, 9.3% forest and orchard, 71% mixture of grass, weeds, and desert shrubs, 7.0% crops, 4.0% urban areas, and 8.4% bare soil. The results show that CN under dry condition are 59, 78 under a normal condition and 89 under a wet condition. During vegetation period, CN are 52, 72 and 86 for the dry, normal and wet condition respectively. The restoration scenarios; CN decreases runoff, and increases soil moisture when using the contours, terraces and crop residues. Analyzing results of CN scenarios will be a fundamental tool to support end-users related to their targets to achieve watershed restoration.

An effective battery management system (BMS) is indispensable for any lithium-ion battery (LIB) powered systems such as electric vehicles (EVs) and stationary grid-tied energy storage systems. Massive wire harness, scalability issue, physical failure of wiring, and high implementation cost and weight are some of the major issues in conventional wired-BMS. One of the promising solutions researchers have come up with is the wireless BMS (WBMS) architecture. Despite research and development on WBMS got momentum more than a decade ago, it is still in a preliminary stage. Significant further upgradation is still required towards developing an industry-ready WBMS, especially for high-power LIB packs. Therefore, an in-depth survey exclusively on WBMS architectures is presented in this article. The aim is to provide a summary of the existing developments as well as to present an informative guide to the research community for future development by highlighting the issues, emerging trends, and challenges. In-depth analysis of the existing WBMS topologies will not only help the researchers to understand the existing challenges and future research scopes clearly while at the same time enthuse them to focus their research inclination in the domain of WBMS.

A decade ago, non-radiative wireless power transmission reemerged a promising alternative to deliver electrical power to devices where a physical wiring proved to be unfeasible. However, conventional coupling-based approaches are neither scalable nor efficient when multiple devices are involved, as they are restricted by factors like coupling and external environments. Zenneck waves are excited at interfaces, like surface plasmons and have the potential to deliver electrical power to devices placed on a conducting surface. Here, we demonstrate, efficient and long range delivery of electrical power by exciting non-radiative waves over metal surfaces to multiple loads.Our modeling and simulation using Maxwells equation with proper boundary conditions shows Zenneck type behavior for the excited waves and are in excellent agreement with experimental results. In conclusion, we physically realize a radically different power transfer system, based on a wave, whose existence has been fiercely debated for over a century.

Autonomous and cooperative vehicle systems represent a key priority in the automotive realm. Networked driving simulation can be utilized as a safe, cost-effective experimental replica of real traffic environments in order to support and accelerate the development of such systems. In networked driving simulation, different independent systems collaborate to achieve a common task: multi-driver traffic scenario simulation. Yet distinct system complexity levels are necessary to fulfill the requirements of various application scenarios, such as development of vehicle systems, analysis of driving behavior, and training of drivers. With myriad alternatives of available systems and components, developers of networked driving simulation are typically confronted with high design complexity. There are no systematic approaches to date for the design of networked driving simulation in accordance with the specific requirements of the concerned application scenarios. This paper presents a novel design method for networked driving simulation. The method consists mainly of a procedure model that is accompanied by a configuration software. The procedure model includes the necessary phases for the systematic design of application-oriented platforms for networked driving simulation. The configuration software embeds supportive decision-making processes that enable developers to apply the design method and easily create different system models. The design method was validated by generating system models and developing platforms of networked driving simulation for three different application scenarios.

Simultaneous measurement of different substances from a single sample is an emerging issue to achieve efficient and high-throughput detection in several fields of application. Although immunoanalytical techniques have well-established and prevailing advantages over alternative screening analytical platforms, one of the incoming challenges for immunoassay is exactly multiplexing. The Lateral Flow Immunoassay (LFIA) is a leading immunoanalytical technique for onsite analysis thanks to its simplicity, rapidity and cost-effectiveness. Moreover, LFIA architecture is adaptable to multiplexing and therefore candidates as a possible answer to the pressing demand of multiplexing point-of-need analysis. The review present an overview of diverse approaches for multiplex LFIA, with a special focus on strategies based on new types of magnetic, fluorescent and colored labels

Activities in the digital economy driven by information technology have rapidly increased in scope and speed in the aftermath of COVID-19. Meanwhile, social isolation accelerated by quarantine measures has increased concerns about individuals’ mental health. However, little is known about the specific consequences of online interactions, especially when applied in online fan community-based relationships where loyal community members are prevalent. Therefore, we examined whether a sense of virtual community (SOVC) can link fans’ online activities with their mental well-being and behavioral loyalty to the platform. For this purpose, we focus on BTS fandom “Adorable Representative MC for Youth” (ARMY) behaviors and attitudes on the fan community platform Weverse. With 202 valid data samples acquired from global ARMY, this study conducted a partial least squares–structural equation modeling analysis. The empirical findings reveal that SOVC in Weverse is significantly influenced by the intensity of online interactions with other fans and parasocial relationships with celebrities. SOVC is found to be the direct predictor of fans’ behavioral loyalty and mental well-being. When considering fans’ perceptions of other social media platforms, dissatisfaction with previous online fan communities enhances the intensity of online interactions with other fans in Weverse.

Building a social security system to ensure Singapore residents have peace of mind in funding for retirement has been at the top of Singapore Government’s policy agenda over the last decade. Implementation of the Lifelong Income For the Elderly (LIFE) scheme in 2009 clearly shows that the government spares no effort in improving its pension scheme to boost its residents’ income after retirement. Despite the recent modifications to the LIFE scheme, Singapore residents must still choose between two plans: the Standard and Basic plans. To enhance the flexibility of the LIFE scheme while maintaining its simplicity, we propose some plan modifications such that scheme members do not face a dichotomy of plan choices. Instead, they select two age parameters: the Payout Age and the Life-annuity Age. This paper provides an actuarial framework for determining members’ payouts and bequests based on the proposed age parameters. We analyze the net cash receipts and internal rate of return (IRR) for various plan-parameter configurations. This information helps members make their plan choices. To address cost-of-living increases we propose to extend the plan to accommodate an annual step-up of monthly payouts. By deferring the Payout Age from 65 to 68, members can enjoy an annual increase of about 2% of the payouts for the same first-year monthly benefits.

It is argued that if the non-unitary measurement transition, as codified by Von Neumann, is a real physical process, then the ‘probability assumption’ needed to derive the Second Law of Thermodynamics naturally enters at that point. The existence of a real, indeterministic physical process underlying the measurement transition would therefore provide an ontological basis for Boltzmann’s Stosszahlansatz and thereby explain the unidirectional increase of entropy against a backdrop of otherwise time-reversible laws. It is noted that the Transactional Interpretation (TI) of quantum mechanics provides such a physical account of the non-unitary measurement transition, and TI is brought to bear in finding a physically complete, non-ad hoc grounding for the Second Law.

In the paper, the authors present an explicit form for a family of inhomogeneous linear ordinary differential equations, find a more significant expression for all derivatives of a function related to the solution to the family of inhomogeneous linear ordinary differential equations in terms of the Lerch transcendent, establish an explicit formula for computing all derivatives of the solution to the family of inhomogeneous linear ordinary differential equations, acquire the absolute monotonicity, complete monotonicity, the Bernstein function property of several functions related to the solution to the family of inhomogeneous linear ordinary differential equations, discover a diagonal recurrence relation of the Stirling numbers of the first kind, and derive an inequality for bounding the logarithmic function.

Nowadays, the study of preparing silica/rubber composites, which can be used in “green tire”, in energy saving method is fast-growing. In our work, silica modified by using alcohol polyoxyethylene ether (AEO) and 3-Mercaptopropyltriethoxysilane (K-MEPTS) together were investigated. Thermal gravimetric analyzer (TGA) result indicated that both AEO and K-MEPTS could be grafted on the silica surface. Raman spectroscopy confirmed that the AEO could generate a certain steric hindrance for the mercaptopropyl group on K-MEPTS. Silica modified by using AEO and K-MEPTS together can be completely co-coagulated with the rubber in preparing silica/natural rubber (NR) composites by latex compounding method. AEO can form a physical interface between silica and rubber; meanwhile, K-MEPTS can form a chemical interface between silica and rubber. The effects of chemical and physical interface between silica and rubber on dynamic and mechanical performances of silica/NR composites were also given in this research. A proper combination of physical and chemical interface between silica and NR can improve performances of silica/NR composites.

The asymmetry in the dynamics of an electro-pneumatic actuating device consisting of an electro-pneumatic transducer and a single-action pneumatic actuator was unexpectedly found experimentally. This asymmetry manifests in response to large step excitations. The dynamic asymmetry effect is understood as a change in the shape of the response of an actuator depending on the direction of the actuators stem movement. The questions appears: How to explain this effect? Does this phenomenon reflect thermodynamic air processes? Is it connected with air-to-mechanical energy conversion? Together, six working hypotheses explaining this effect were formulated. The asymmetry was studied in detail using analytical and simulation modeling, as well as experimental research. In this respect, a nonlinear analytical model was developed, tuned, and later solved using simulations. The simulation model was verified based on the experiment data. In addition, the problem of the efficiency in the energy conversion of a single-action actuator was discussed and, in result, the maximum theoretical energy efficiency was determined. Subsequently, all six working hypotheses were verified. Finally, the hypothesis explaining asymmetry as an effect of the different thermodynamic air processes in both actuator’s stem travel directions was confirmed.

The Galleon was considered a masterpiece of shipbuilding in the sixteenth century, but from a modern point of view, the shape of her hull looks archaic and primitive. However, how accurate is this perception? Is the hull form of Galleon primitive? What were the reasons for its unique design features? This article investigates these questions by directly analysing the hull’s features from the point of view of modern ship’s theory, as well as from a historical perspective. A careful evaluation of specific design criteria of a typical Galleon, together with analysing a 3D model of its hull on modern software, with further insight for the seakeeping behaviour of Galleon with a comparison to more modern full-rigged ship (Barque of 19 CE), showed that these features were not random, but instead had a good rationale behind it, and served specific and carefully decided functions, required at the time.

Identifying the determinants of human behavior is useful to adjust interventions and lead the civil society towards a stronger commitment with climate change mitigation and adaptation objectives, achieving greater support for successfully implementing environmental policies. Existing research has largely focused on case studies of pro-environmental behaviors (PEBs) in developed economies but there is yet very little evidence for developing countries. This study provides estimations of the effect of internal factors, such as sociodemographic variables, and four psychological dimensions (climate change knowledge, environmental attitudes, self-efficacy, trust in sources of environmental information) on PEBs. Data was obtained through a survey applied with future decision makers - university students - from Colombia (n = 4769) and Nicaragua (n = 2354). Indices were generated for PEBs and the psychological dimensions using z-scores and Principal Component Analysis. Partial correlations were evaluated through the Ordinary Least Squares method. Our results suggest that, in order to reach the planned emission reduction targets, policy approaches should more strongly focus on educating and motivating citizens and prepare them for contributing to the environmental cause, as well as provide individual solutions to combat climate change, rather than providing only information on its causes and consequences.

Additive manufacturing (AM) provides customization of the microstructure and mechanical properties of components. Selective laser melting (SLM) is the commonly used technique for processing high strength Aluminum alloys. Selection of SLM process parameters could control the microstructure of fabricated parts and their mechanical properties. However, process parameter limits and defects inside the as-built parts present obstacles to customized part production. This study is the second part of a comprehensive work that investigates the influence of SLM process parameters on the quality of as-built Al6061 and AlSi10Mg parts. The microstructure of both materials was characterized for different parts processed over a wide range of SLM process parameters. The optimized SLM parameters were investigated to eliminate the internal microstructure defects. Mechanical properties of the parts were illustrated by regression models generated with design of experiment (DOE) analysis. The results reported in this study were compared to previous studies, illustrating how the process parameters and powder characteristics could affect the quality of produced parts.

The Italian Peninsula, a natural pier across the Mediterranean Sea, witnessed intricate population events since the very beginning of human occupation in Europe. In the last few years, an increasing number of modern and ancient genomes from the area has been published by the international research community. This genomic perspective started unveiling the relevance of Italy to understand the post-Last Glacial Maximum (LGM) re-peopling of Europe, the earlier phase of the Neolithic westward migrations, and its linking role between Eastern and Western Mediterranean areas after the Iron Age. However many open questions are still waiting for more data to be addressed in full. With this review, we summarize the current knowledge emerging from the available ancient Italian individuals and, by re-analysing them all at once, we try to shed light on the avenues future research in the area should cover. In particular, open questions concern i) the fate of pre-Villabruna Europeans and to what extent their genomic components were absorbed by the post-LGM hunter-gatherers; ii) the role of Sicily and Sardinia before LGM; iii) to what degree the documented genetic structure within the Early Neolithic settlers can be described as two separate migrations; iv) what are the population events behind the marked presence of an Iranian Neolithic-like component in Bronze Age and Iron Age Italian and Southern European samples.

In the paper, by virtue of techniques in combinatorial analysis, the authors simplify two families of nonlinear ordinary differential equations in terms of the Stirling numbers of the first kind.

The analytical method for the calculation of the properties of a bolted connection established by the structural Eurocodes proposes the T-stub as a component for the characterization of the tension and compression zones in moment joints. In this article, a review of the state of the art on the T-stub component is developed, where the works developed since it was initially defined, and from the perspectives of formulation, experimentation and numerical simulation are summarized and discussed. Additionally, possible future lines of work are proposed.

Tanzania like any other developing countries is depending on uncertain rainfall for their subsistence and commercial agriculture. In this paper the start and end of rains for Mbeya Meteorological Station in Tanzania Mainland was analyzed and critically examined. Data were kindly given by Tanzania Meteorological Agency (TMA) during face to face Statistics in Applied Climatology (fSIAC) workshop which was held at Sokoine University of Agriculture (SUA) the year 2013 prior to online Course on Statistics in Applied climatology (eSIAC). In this study data were analyzed using Instat (for windows version 3.3.7) package developed by the Statistical Services Centre of the University of Reading. The analysis showed that much of rains start early December all the way to May. There is also 50 percent chance of having below and above the mean for both total annual rainfall and number of rains, in other word one in two years the total rains are below means likewise the number of rain days.

Maximum entropy production principle (MEPP) has been formulated in the mid-twentieth century, and today it has acquired the status of an important principle of science, which is extremely effective in considering various non-equilibrium problems. In this study, for the first time, definition of life is based on an easily measurable physical quantity that is entropy production. Life and evolution are discussed from the point of view of MEPP and the Universe, but not a human

Panel data of our interest consist of a moderate number of panels, while the panels contain a small number of observations. An estimator of common breaks in panel means without a boundary issue for this kind of scenario is proposed. In particular, the novel estimator is able to detect a common break point even when the change happens immediately after the first time point or just before the last observation period. Another advantage of the elaborated change point estimator is that it results in the last observation in situations with no structural breaks. The consistency of the change point estimator in panel data is established. The results are illustrated through a simulation study. As a by-product of the developed estimation technique, a theoretical utilization for correlation structure estimation, hypothesis testing, and bootstrapping in panel data is demonstrated. A practical application to non-life insurance is presented as well.

Aim: The aim of this study was to assess the performance of the SF-36 health survey (SF-36) in a sample of subjects with physical disabilities. Material and Methods: 305 patients recruited using the convenient sampling method from September 2019 to March 2020 in Kermanshah, Iran. Another similar 300 patients were selected to assess the confirmatory factor analysis (CFA). Results: The Cronbach’s α ranged from 0.70 to 0.93, and intra-class correlation coefficients from 0.71 to 0.88; and with the no ceiling and floor effect for two main subscales. Convergent validity was supported by moderate to good correlation between SF-36 subscales and Moorong self-efficacy subscales (r= 0.25- 0.53). The SF-36 divergently validated with HADS total score and subscales (r= -0.24- -0.65), concurrently validated with its subscales (r=0.49- 0.88), and physically discriminated between persons with different level of disability (t-test: p<0.001). Factorial analysis identified seven factors, confirmed with second-order in another 300 samples (chi-square (χ2/df) = 2.61(p < .001); RMSEA = 0.07 (90% CI = 0.07–0.08); AGFI=0.75; GFI = 0.78; CFI= 0.85; and NFI = 0.78). Conclusions: the SF-36 is a reliable and valid tool in physical disables. However, SF-36 shows insufficient eight-factor validity. Future studies should focus on evaluating other psychometric properties, such as sensitivity to change in subjects with physical disabilities.

We are calling for a paradigm shift in engineering education. In times of the Fourth Industrial Revolution (“4IR”), a myriad of potential changes is affecting all industrial sectors leading to increased ambiguity that makes it impossible to predict what lies ahead of us. Thus, incremental culture change in education is not an option any more. The vast majority of engineering education and training systems, having remained mostly static and underinvested in for decades, are largely inadequate for the new 4IR labor markets. Some positive developments in changing the direction of the engineering education sector can be observed. Novel approaches of engineering education already deliver distinctive, student centered curricular experiences within an integrated and unified educational approach. We must educate engineering students for a future whose main characteristics are volatility, uncertainty, complexity and ambiguity. Talent and skills gaps across all industries are poised to grow in the years to come. The authors promote an engineering curriculum that combine timeless didactic tradition, such as Socratic inquiry, project-based learning and first-principles thinking with novel elements (e.g. student centered active and e-learning by focusing on the case study and apprenticeship pedagogical methods) as well as a refocused engineering skillset and knowledge. These capabilities reinforce engineering students’ perceptions of the world and the subsequent decisions they make. This 4IR engineering curriculum will prepare engineering students to become curious engineers and excellent communicators better navigating increasingly complex multistakeholder ecosystems.

This study investigated how fashion is expressed on social media platforms from a media ecology perspective of sustainable digital space-time, as society evolves into a digital ecosystem. Media ecology concerns how the media environment transforms human experience and impacts society and culture. A theoretical review of media ecology was conducted, and the Instagram account of global fashion influencer Susanna Lau (@susiebubble) was analyzed as a case study. In total, 300 fashion-related images were collected out of 5,817 uploaded to Lau’s Instagram between May 2012 and June 2019. These were analyzed—alongside their titles, content, hashtags, and commentaries—for visual phenomena conveying everyday divisions between spatiality and temporality, public and private, real and virtual, and geography and culture, which demonstrate ambiguous boundaries. The analysis revealed that the images reflect nuances of digital time and space as they emerge in social media, and represent a nonboundary of style across the binaries of work and leisure, public and private, real and virtual, and geography and culture—signifying a sustainable digital lifestyle. These findings illustrate how our changing daily lives are visualized through fashion on a sustainable digital platform, and suggest ongoing research into the practical impact of technological advances on fashion.

In the weak-field approximation of covariant theory of gravitation the problem of 4/3 is formulated for internal and external gravitational fields of a body in the form of a ball. The dependence of the energy and the mass of the moving substance on the energy of field accompanying the substance, as well as the dependence on the characteristic size of the volume occupied by the substance are described. Additives in the energy and the momentum of the body, defined by energy and momentum of the gravitational and electromagnetic fields associated with the body are explicitly calculated. The conclusion is made that the energy and the mass of the body can be described by the energy of ordinary and strong gravitation, and through the energies of electromagnetic fields of particles that compose the body.

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

REDD+ (Reducing Emissions from Deforestation and Forest Degradation) aims to achieve its purpose by working across multiple sectors and involving multi-level actors in reducing deforestation and forest degradation in tropical countries. By contrast, the European Union (EU) Action Plan on Forest Law Enforcement, Governance and Trade (FLEGT) and its Voluntary Partnership Agreements (VPAs) focus on forestry and functions at bilateral state level. The FLEGT Action Plan specifically aims to tackle illegal logging, legalise timber production and trade improve forest governance in countries exporting tropical timber to the EU. Since illegal logging is just one driver of deforestation and forest degeneration, and legalisation of logging does not necessarily reduce deforestation and forest degradation, the two instruments differ in scale and scope. However, by addressing the causes of deforestation and forest degradation and their underlying governance issues, the EU FLEGT and REDD+ share many functional linkages at higher levels of forest policy and forest governance. The contribution and participation of civil society organisations (CSOs) and other actors is imperative to both processes. Our study is based on a survey of key actors (national and international) in REDD+ and FLEGT VPA processes in the Lao People’s Democratic Republic. Our analysis was guided by the theoretical perspectives of the policy arrangement approach and examination of two specific dimensions of this approach, namely resources and rules of the game. This paper argues that participation of CSOs in both processes is crucial as it facilitates and nurtures the very much needed cooperation between other national and international actors. The paper also argues that participation of CSOs feeds valuable information and knowledge into REDD+ and FLEGT VPA processes, thus contributing to increased legitimacy, justice and transparency.

Nearly 50 years ago, Francis Crick propounded the frozen accident scenario for the evolution of the genetic code along with the hypothesis that the early translation system consisted primarily of RNA. Under the frozen accident perspective, the code is universal among modern life forms because any change in codon assignment would be highly deleterious. The frozen accident can be considered the default theory of code evolution because it does not imply any specific interactions between amino acids and the cognate codons or anticodons, or any particular properties of the code. The subsequent 49 years of code studies have elucidated notable features of the standard code, such as high robustness to errors, but failed to develop a compelling explanation for codon assignments. In particular, stereochemical affinity between amino acids and the cognate codons or anticodons does not seem to account for the origin and evolution of the code. Here I expand Crick’s hypothesis on RNA-only translation system by presenting evidence that this early translation already attained high fidelity that allowed protein evolution. I outline an experimentally testable scenario for the evolution of the code that combines a distinct version of the stereochemical hypothesis, in which amino acids are recognized via unique sites in the tertiary structure of proto-tRNAs, rather than by anticodons, expansion of the code via proto-tRNA duplication and the frozen accident.

Multi-criteria decision analysis (MCDA), one of the prevalent branches of operations research, aims to design mathematical and computational tools for selecting the best alternative among several choices with respect to specific criteria. In the cloud, MCDA based online brokers uses customer specified criteria to rank different service providers. However, subjected to limited domain knowledge, the customer may exclude relevant or include irrelevant criterion, which could result in suboptimal ranking of service providers. To deal with such misspecification, this research proposes a model, which uses notion of factor analysis from the domain of unsupervised machine learning. The model is evaluated using two quality-of-service (QoS) based datasets. The first dataset i.e., feedback from customers, was compiled using leading review websites such as Cloud Hosting Reviews, Best Cloud Computing Providers, and Cloud Storage Reviews and Ratings. The second dataset i.e., feedback from servers, was generated from cloud brokerage architecture that was emulated using high performance computing (HPC) cluster at University of Luxembourg (HPC @ Uni.lu). The simulation runs in a stable cloud environment i.e. when uncertainty is low, shows that online broker (equipped with the proposed model) produces optimized ranking of service providers as compared to other brokers. This is due the fact that proposed model assigns priorities to criteria objectively (using machine learning) rather than using priorities based on subjective judgments of the customer. This research will benefit potential cloud customers that view insufficient domain knowledge as a limiting factor for acquisition of web services in the cloud.

Bayesian analysis for masked data under competing risk frameworks is studied for the purpose of assessing the impact of covariates on the hazard functions when the failure time is exactly observed for some subjects but only known to lie in an interval of time for the remaining subjects. Such data, known as partly interval-censored data, usually result from periodic inspection. Dirichlet and Gamma processes are assumed as priors for masking probabilities and baseline hazards. The Markov Chain Monte Carlo (MCMC) technique is employed for the implementation of the Bayesian approach. The effectiveness of the proposed model is tested through numerical studies, including simulated and real data sets.

Recent evidence indicates that the risk of being diagnosed with cancer in a tissue is strongly correlated (0.80) with the number of stem cell divisions accumulated by the tissue. Since cell division can generate random mutations during DNA replication, this correlation has been used to propose that cancer is largely caused by the accumulation of unavoidable mutations in driver genes. However, no correlation between the number of gene mutations and cancer risk across tissues has been reported. Because many somatic mutations in cancers originate prior to tumor initiation and the number of cell divisions occurring during tumor growth is similar among tissues, here I use whole genome sequencing information from 22,086 cancer samples and incidence data from the largest cancer registry in each continent to study the relationship between the number of gene mutations and the risk of cancer across 33 tissue types. Results show a weak positive correlation (mean = 0.14) between these two parameters in each of the five cancer registries. The correlation became stronger (mean = 0.50) when gender-related cancers were excluded. Results also show that 1,003 samples from 29 cancer types have zero mutations in genes. These data suggest that cancer etiology can be better explained by the accumulation of stem cell divisions than by the accumulation of gene mutations. Possible mechanisms by which the accumulation of cell divisions in stem cells increases the risk of cancer are discussed.

Wave steepness is presented as an extension and a valuable add-on to the conventional set of sea state parameters retrieved from satellite altimetry data. Following physical model based on recent advances of weak turbulence theory wave steepness is estimated from directly measured spatial gradient of wave height. In this way the method works with altimetry trajectories rather than with point-wise data. Moreover, in contrast to widely used parametric models this approach provides us with instantaneous values of wave steepness and period. Relevance of single-track estimates of wave steepness (period) is shown for wave climate studies and confirmed by a simple probabilistic model. The approach is verified via comparison against buoy and satellite data including crossover points for standard 1 second data of Ku-band altimeters. High quality of the physical model and robustness of the parametric ones are examined in terms of global wave statistics. Prospects and relevance of both approaches in the ocean wave climate studies are discussed.

The loss of integrity and adverse effect on mechanical properties can be concluded as attributing miro/macro-mechanics damage in structures, especially in composite structures. Damage as a progressive degradation of material continuity in engineering predictions for any aspects of initiation and propagation requires to be identified by a trustworthy mechanism to guarantee the safety of structures. Besides the materials design, structural integrity and health are usually prone to be monitored clearly. One of the most powerful methods for the detection of damage is machine learning (ML). This paper presents the state of the art of ML methods and their applications in structural damage and prediction. Popular ML methods are identified and the performance and future trends are discussed.

In previous studies we found that generalized functions can be smooth, discrete, periodic or discrete periodic and they can either be local or global and they are regular or generalized functions. We also saw that these properties were related to Poisson’s summation formula on one hand and to Heisenberg’s uncertainty principle on the other. In this paper, we interlink these studies and show that scalars (real or complex numbers) considered as trivial functions are discrete and periodic, local and global as well as regular and generalized, simultaneously. However, this is also a paradox because it means that Dirac’s δ and 1 (its Fourier transform) coincide. They both are unity. We show that δ and 1 coincide in the sense of scalars (real or complex numbers) but they differ in the sense of (generalized) functions. This result can moreover be related to Max Born’s principle of reciprocity. It also answers an open question in present-day quantum mechanics because it means that the Dirac delta squared is simply delta.

New developments in broadcast technology, such as the ad hoc wireless network and the detection devices that work, enable daily connections to the Internet, commonly referred to as the Internet of Things (IoT). IoT saw this as a support for the development of creative and contextual services and applications. The service can respond to the user's environment and preferences. Finite state machines are recently making waves when the issue of self-controlling systems come into the picture of designs. This research focuses on the design of a fault tolerant system that controls random failures impressed on the network. The method comprises of diodes, Resistors, Optocouplers, ESP8266 WI-FI Module Webpage with button, and two Arduinos which in effect will determine iteratively who to handle a failure at hand modelled as when the button on the webpage is pressed. In this work, a Heartbeat Detection and Monitoring System will be made using Arduino that detect the electrical state using the Pulse Sensor and show the readings in Beats Per Minute on the LED connected a microcontroller. It sends the texts to the server using the Wi-Fi module ESP8266 to signals can be monitored from the monitoring zone via the internet. This is reflected by the declaration of a master state by either of two Arduinos whenever the push button is pressed as observed on the codes. The result obtained from the research shows apparently, the state of the fault tolerance system none power deny of heartbeat condition connected to the LED.

The County of Avon in England was abolished in 1996 and replaced by four unitary planning authorities. Recently the authorities have been working closely to develop a West of England Joint Spatial Plan to facilitate better integration of policies on transport, housing, the environment etc. The Joint Spatial Plan team commissioned a multidisciplinary study to investigate whether the West of England has special characteristics of 'place' that engender shared interest and regional affinity, i.e. ‘sense of place’, to which emerging planning policies might positively respond. In this regard the present article is particularly focused on identifying whether the West of England has unique and unifying landscape characteristics, relating to topography, rural scenery, and flora and fauna, which combine with human experiences to distinguish the Region from adjoining areas. It is concluded that the West of England does indeed have real geographical integrity, being bound on all sides by attractive and prominent landscape features - the Mendip Hills, Cotswold Hills and Severn Estuary – that contribute to a sense of identity and belonging among its inhabitants. The alternating limestone ridges and broad clay vales that prevail across the Region’s heart, combined with low lying flatlands on the Region’s western fringe, provide further contrast with neighbouring regions, reinforcing the emotional bond to the landscape. Furthermore, it is suggested that the inhabitants of the West England show a particularly special environmental consciousness that sets them apart from neighbouring populations, complementing the influence of the physical environment in making the Region a special place to live.

Targets detection in synthetic aperture radar (SAR) remote sensing images, which is a fundamental but challenging problem in the field of satellite image analysis, plays an important role for a wide range of applications and is receiving significant attention in recent years. Besides, the ability of human visual system to detect visual saliency is extraordinarily fast and reliable. However, computational modeling of SAR image scene still remains a challenge. This paper analyzes the defects and shortcomings of traditional visual models applied to SAR images. Then a visual attention model designed for SAR images is proposed. The model draws the basic framework of classical ITTI model; selects and extracts the texture features and other features that can describe the SAR image better. We proposes a new algorithm for computing the local texture saliency of the input image, then the model constructs the corresponding saliency maps of features; Next, a new mechanism of feature fusion is adopted to replace the linear additive mechanism of classical models to obtain the overall saliency map; Finally, the gray-scale characteristics of focus of attention (FOA) in saliency map of all features are taken into account, our model choose the best saliency representation, Through the multi-scale competition strategy, the filter and threshold segmentation of the saliency maps can be used to select the salient regions accurately, thereby completing this operation for the visual saliency detection in SAR images. In the paper, several types of satellite image data, such as TerraSAR-X (TS-X), Radarsat-2, are used to evaluate the performance of visual models. The results show that our model provides superior performance compared with classical visual models. By further contrasting with the classical visual models, Our model reduce the false alarm caused by speckle noise, and its detection speed is greatly improved, and it is increased by 25% to 45%.

A method of direction-of-arrival (DoA) estimation for FMCW radars is presented. In addition to MUSIC and ESPRIT, which are well-known high-resolution DoA estimation algorithms, deep learning has recently emerged as a very promising alternative. It is proposed in this paper to use a 3D convolutional neural network (CNN) for DoA estimation. The 3D-CNN extracts from the radar data cube spectrum features of the region of interest (RoI) centered on the potential positions of the targets, thereby capturing the spectrum phase shift information, which corresponds to DoA, along the antenna axis. Finally, the results of simulations and field experiments are provided to demonstrate the superior performance, as well as the limitations, of the proposed 3D-CNN.

This paper presents an approach to the Kirchhoff-Love plate theory (KLPT) using the finite difference method (FDM). The KLPT covers the case of small deflections, and shear deformations are not considered. The FDM is an approximate method for solving problems described with differential equations. The FDM does not involve solving differential equations; equations are formulated with values at selected points of the structure. Generally in the case of KLPT, the finite difference approximations are derived based on the fourth-order polynomial hypothesis (FOPH) and second-order polynomial hypothesis (SOPH) for the deflection surface. The FOPH is made for the fourth and third derivative of the deflection surface while the SOPH is made for its second and first derivative; this leads to a 13-point stencil for the governing equation. In addition, the boundary conditions and not the governing equations are applied at the plate edges. In this paper, the FOPH was made for all of the derivatives of the deflection surface; this led to a 25-point stencil for the governing equation. Furthermore, additional nodes were introduced at plate edges and at positions of discontinuity (continuous supports/hinges, incorporated beams, stiffeners, brutal change of stiffness, etc.), the number of additional nodes corresponding to the number of boundary conditions at the node of interest. The introduction of additional nodes allowed us to apply the governing equations at the plate edges and to satisfy the boundary and continuity conditions. First-order analysis, second-order analysis, buckling analysis, and vibration analysis of plates were conducted with this model. Moreover, plates of varying thickness and plates with stiffeners were analyzed. Finally, a direct time integration method (DTIM) was presented. The FDM-based DTIM enabled the analysis of forced vibration of structures, with damping taken into account. In first-order, second-order, buckling, and vibration analyses of rectangular plates, the results obtained in this paper were in good agreement with those of well-established methods, and the accuracy was increased through a grid refinement.

This paper predict and effectively control the temperature distribution of the steady-state and transient states of anisotropic four-layer composite materials online, knowing the density, specific heat, heat conductivity and thickness of the composite materials. Based on the transfer function, a mathematical model was established to study the dynamic characteristics of heat transfer of the composite materials. First of all, the Fourier heat transfer law was used to establish a one-dimensional Fourier heat conduction differential equation for each composite layer, and the Laplace transformation was carried out to obtain the system function. Then the approximate second-order transfer function of the system was obtained by Taylor expansion, and the Laplace inverse transformation was carried out to obtain the transfer function of the whole system in the time domain. Finally, the accuracy of the simplified analytical solutions of the first, second and third order approximate transfer functions was compared with computer simulation. The results showed that the second order approximate transfer functions can describe the dynamic process of heat transfer better than others. The research on the dynamic characteristics of heat transfer in the composite layer and the dynamic model of heat transfer in composite layer proposed in this paper have a reference value for practical engineering application. It can effectively predict the temperature distribution of composite layer material and reduce the cost of experimental measurement of heat transfer performance of materials.

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

The use of Supplementary Cementitious Material (SCM) is widely used in production of sustainable concrete. Blended cements, incorporating SCM such as Pulverized Fly Ash (PFA) and Ground Granulated Blast Furnace Slag (GGBFS) have been widely used to reduce the cement contents and avoid adverse environmental impacts of CO2 produced during cement manufacturing. The analysis of various structural properties of concrete such as compressive strength, flexural strength and modulus of elasticity is important for its structural application. In this research, flexural strength of 100mmx100mmx500mm beams made from blended cement were tested under three curing conditions i.e. winter, summer and under water and the flexural strength was calculated using EN-12390-5 at the ages of 28 days and 56 days. For modulus of elasticity, concrete cylinders 150mmx300mm were tested as per procedure described in BS 1881-121(1983) at the age of 28 days. The compressive strength, flexural strength and modulus of elasticity for blended cement incorporating PFA and GGBFS has been increased under summer curing environment. The experimental values of Modulus of Elasticity are compared with the provision of BS 1881.

Flavonoids, compounds present in many dietary supplements, affect growth of different bacterial species when tested as purified or synthetic substances. Here, we asked if soy isoflavone extracts, commonly used in many products sold as anti-menopausal dietary supplements, influence bacterial growth similarly to synthetic isoflavone, genistein. Four commercially available products were tested in amounts corresponding to genistein concentrations causing inhibition of growth of Vibrio harveyi (a model bacterium sensitive to this isoflavone) and Escherichia coli (a model bacterium resistant to genistein). Differential effects of various extracts on V. harveyi and E. coli growth, from stimulation, through no changes, to inhibition, were observed. Moreover, contrary to genistein, tested extracts caused a decrease (to different extends) in viability of human dermal fibroblasts. These results indicate that effects of various soy isoflavone extracts on bacterial growth and viability of human cells are different, despite similar declared composition of the commercially available products.

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

Previous studies implied the different behavioral intention formation of a specific object for individuals in different age groups, but few research to Chinese consumers’ sustainable fast fashion behaviour were found considering the enormous amount of consumption and waste of fast fashion products in China. Meanwhile, as a fast developing country, it might be insufficient to conduct research ignoring the consequences of different education level and growing environment among different generations. Thus, to generate in-depth and heuristic Chinese consumers information, this study developed proposed theoretical framework (TORA) based on research by Fishbein and Ajzen (1975), while the validity among Chinese consumers was tested as well. Following the TORA model, this study aims to investigate if consumers’ age will moderate the relationship between attitude and intention, and the relationship between subjective norms to behavioral intention. Through structural equation modelling in AMOS, it was found that the model has a well fit to large sample of Chinese consumers, while the moderation effect of age was not significant in the whole sample. Further hierarchical regression analysis conducted in SPSS and Process was able to locate the moderation effect of if divide the consumers into groups by age. Which is, age is significantly and positively moderating the path subjective norms to intention in younger generation (18-25), but significantly positive moderating attitude to intention in consumers aged 26-39. Implications in marketing and to policy makers are discussed at the end of this research.

Lipophilicity can be measured with different methods, such as Shake-Flask or liquid chromatography. HPLC presents the advantage of overcoming solubility issues and therefore extending the range of lipophilicity to high values. A specific HPLC method, called ELogD, had been developed 20 years ago on a C₁₆-amide stationary phase, enhancing hydrophobic and hydrogen bond interactions to mimic octanol-water partition. The emergence of novel stationary phases added to the need for a less complex mobile phase has led to the development of a new HPLC assay called alphaLogD, applicable to neutral and basic compounds at pH 7.4, that combines superficially porous particles, a high number of equilibriums between solutes and stationary phase, and results in a lower number of isocratic methods to determine the logk’_w at a higher throughput. Statistical studies have been run to successfully evaluate the alphaLogD method compared to the Shake-Flask method and to allow this lipophilicity measurement into the so-called Beyond-Rule-of-5-molecules space.

This study revisits the Reynolds-averaged Navier--Stokes equations (RANS) and finds that the existing literature is erroneous regarding the primary unknowns and the number of independent unknowns in the RANS. The literature claims that the Reynolds stress tensor has six independent unknowns, but in fact the six unknowns can be reduced to three that are functions of the three velocity fluctuation components, because the Reynolds stress tensor is simply an integration of a second-order dyadic tensor of flow velocity fluctuations rather than a general symmetric tensor. This difficult situation is resolved by returning to the time of Reynolds in 1895 and revisiting Reynolds' averaging formulation of turbulence. The study of turbulence modeling could focus on the velocity fluctuations instead of on the Reynolds stress. An advantage of modeling the velocity fluctuations is, from both physical and experimental perspectives, that the velocity fluctuation components are observable whereas the Reynolds stress tensor is not.

With the increasing of copper consumption, the in-use stock of copper tends to increase. This paper used the “average use life method” to quantify the amount of copper in-use stock, and calculated the average age of in-use stock. It was indicated that the total in-use stock had an overall smooth trends, and reached its peak in 2007 was about 68.9 Mt (million tons), in addition, in-use stock per capita reached its peak ,234 kg/capita in 2001. The results demonstrated that during the period 1992-2002, the average age of copper in-use stock was continually decreased, but gradually increased since the year 2003. The fixed assets depreciation method used in this paper is applied to analyze depreciated copper in-use stock, and to analyze the relationship with economic indicator (GDP). It is demonstrated that it was inconsistent with the theory of Environmental Kuznets Curve (EKC) before 2000, this might be the demand for copper in the service sector is greater than the reduced strength of alternatives. Finally, scenario analysis of future copper in-use stock and depreciated copper in-use stock per capita in the U.S. were presented. The corresponding average age of the in-use stock will have a slight rise in the next decade.

Deep learning has taken over - both in problems beyond the realm of traditional, hand-crafted machine learning paradigms as well as in capturing the imagination of the practitioner sitting on top of petabytes of data. While the public perception about the efficacy of deep neural architectures in complex pattern recognition tasks grows, sequentially up-to-date primers on the current state of affairs must follow. In this review, we seek to present a refresher of the many different stacked, connectionist networks that make up the deep learning architectures followed by automatic architecture optimization protocols using multi-agent approaches. Further, since guaranteeing system uptime is fast becoming an indispensable asset across multiple industrial modalities, we include an investigative section on testing neural networks for fault detection and subsequent mitigation. This is followed by an exploratory survey of several application areas where deep learning has emerged as a game-changing technology - be it anomalous behavior detection in financial applications or financial time-series forecasting, predictive and prescriptive analytics, medical imaging, natural language processing or power systems research. The thrust of this review is on outlining emerging areas of application-oriented research within the deep learning community as well as to provide a handy reference to researchers seeking to embrace deep learning in their work for what it is: statistical pattern recognizers with unparalleled hierarchical structure learning capacity with the ability to scale with information.

In recent years, due to their frequent use and widespread use, IoT (Internet of Things) devices have become an attractive target for hackers. As a result of their limited network resources and complex operating systems, they are vulnerable to attacks. Using a honeypot can, therefore, be a very effective way of detecting malicious requests and capturing samples of exploits. The purpose of this article is to introduce honeypots, the rise of IoT devices, and how they can be exploited by attackers. Various honeypot ecosystems will be investigated further for capturing and analyzing information from attacks against these IoT devices. As well as how to leverage proactive strategies in terms of IoT security, it will provide insights on the attack vectors present in most IoT systems, along with understanding attack patterns.

The aim of the study was to determine the possibility of suppression of the prostaglandin synthesis by new derivatives of N-phenylanthranilic acids; they inhibit the activity of the microsomal prostaglandin E synthase-1 (mPGES-1) enzyme using the method of a flexible molecular docking. For the docking studies the crystallographic structural models with high resolution from Protein Data Bank were used: mPGES-1 in the complex with glutathione (pdb code 4AL0). A flexible molecular docking was carried out using the Molecular Operating Environment (MOE) software package. According to the results of the docking studies four scoring functions were calculated (Affinity dG Scoring, Alpha HB Scoring, London dG Scoring, GBVI/WSA dG Scoring). The values of the scoring functions calculated indicate the thermodynamic probability and energy favorability of forming complexes between molecules of the substances under research and the specified receptor, in which arrangement of ligands in the active site of the receptor and residues of amino acids of side chains are of similar geometry and types of binding of the known inhibitors of mPGES-1 determined on the basis of the crystallographic studies.

The aim of this paper is to present a comprehensive overview of the main aims and scopes in screening of botanicals, a task which thin-layer chromatography (TLC) is on an everyday basis confronted with and engaged in. Stunning omnipresence of this modest analytical technique (both in its standard format (TLC) and the high-performance one (HPTLC), either hyphenated or not) for many analysts might at a first glance appear chaotic and random, with an auxiliary rather than leading role in research, and not capable of issuing meaningful final statements. Based on these reflections, our purpose is not to present a general review paper on TLC in screening of botanicals, but a blueprint rather (illustrated with a selection of practical examples), which highlights a sovereign and important role of TLC in accomplishing the following analytical tasks: (i) solving puzzles related to chemotaxonomy of plants, (ii) screening a wide spectrum of biological properties of plants, (iii) providing quality control of herbal medicines and alimentary and cosmetic products of biological origin, and (iv) tracing psychoactive plants under forensic surveillance.

The violation of Bell's theorem is a very simple way to see that there is no underlying classical interpretation of quantum mechanics. The measurements made on the photons shows that light signal (information) could travel between them, hence completely eliminating any chance that the result was due to anything other than entanglement. Entanglement has been studied extensively for understanding the mysteries of non-classical correlations between quantum systems. It was found that violation of Bell's inequalities could be trivially calculated and for sets of nonmaximally entangled states of two qubits, comparing these entanglement measures may lead to different entanglement orderings of the states. On the other hand, although it is not an entanglement measure and not monotonic under local operations, due to its ability of detecting multipartite entanglement, quantum Fisher information (QFI) has recently received an intense attraction generally with entanglement in the focus. In this work, we visit violation of Bell's inequalities problem with a different approach. Generating a thousand random quantum states and performing an optimization based on local general rotations of each qubit, we calculate the maximal QFI for each state. We analyze the maximized QFI in comparison with violation in Bell's inequalities and we make similar comparison of this violation with commonly studied entanglement measures, negativity and relative entropy of entanglement. We show that there are interesting orderings for system states.

Multi-view stereo (MVS) employs multi-point photography for image point positioning and three-dimensional reconstruction technology. Recently, this technology has been introduced into the monitoring of road slopes due to advances in photography and computing technology. In general, the various phases of post-image processing procedures are applied to various photographic data. In this study a novel, automated image-monitoring system is proposed to improve the ability of automatic processing. First, an Internet of things (IoT)-based digital photography system architecture was constructed to provide automatic control of camera photography and real-time transmission of image data. In addition, a visual SfM-MVS 3D reconstruction technique was used to develop related software and hardware interfaces based on the built-in Python computing framework of Photoscan Pro. The software integrates fully automatic photography, image transmission, monitoring of data processing and product release programs. The experimental results show that the system architecture can be applied to fully automatic three-dimensional monitoring of road slopes.

Many patients with Coronavirus disease 2019 (COVID-19) suffer from shortness of breath and severe chest pain. Here we report successful therapy of a patient with diagnosis of COVID-19, severe chest pain and significant shortness of breath, using radial extracorporeal shock wave therapy (rESWT). The latter started seven days after beginning of symptoms and drug therapy without success, and involved daily application of 15.000 to 20.000 radial extracorporeal shock waves over the intercostal muscles as well as the paravertebral muscles of the thoracic and lumbar spine, diaphragm and flanks. Immediately after the first rESWT session the patient experienced significant pain relief and improvement of breathing. Four days later the pain had completely subsided and breathing was largely normalized. This type of noninvasive, non-pharmacologic treatment could help many COVID-19 patients or patients who still suffer from breathing problems weeks after having been infected with SARS-CoV-2, giving them back quality of life.

The purpose of this study is to determine the relationship between grit and parenting style of mother among Indian rural adolescents. Parental Authority Questionnaire [1] and Short Grit Scale [2] was used to meet objectives of the paper. A sample of 60 adolescents was chosen from private institution located at Bathinda (Punjab) by using convenience sampling technique. Results of correlation analysis revealed that significant (negative) relationship exists between mother’s authoritarian parenting style (only) and grit. This is true for both genders and for adolescents who comes from joint families. Educational implication of the study signifies that the suitable informative and counseling sessions should be organised for the parents to make them conscious of the appropriate parenting style for the development of gritty adolescents.

The aim of the study is to assess enjoyment and intensity of physical exercise while practicing physical activity (PA) in immersive virtual reality (IVR) using innovative training devices (omni-directional Omni treadmill and Icaros Pro flight simulator). The study also contains the results of subjective research on the usefulness of such a form of PA in the opinion of users. In total, 61 adults (10 women and 50 men) took part in the study. To assess the enjoyment level (EL) Interest/Enjoyment subscale of Intrinsic Motivation Inventory (IMI) was used. Exercise intensity was assessed during 10-minute sessions of active video games (AVGs) in IVR based on heart rate (HR). The average enjoyment level during physical exercise in IVR on the tested training devices was relatively high (Omni 5.74 points, Icaros 5.60 points). In the opinion of the majority of participants, AVGs on IVR training devices constitute a sufficiently useful form of movement to meet the needs of PA practiced in free time, and they can even replace some of the classic forms of movement. Intensity of PA during games on training devices was at the level recommended for health benefits for 92% (Omni) and 84% (Icaros Pro) of its duration. Based on the conducted research, it can be assumed that AVGs in IVR using a multi-directional treadmill and a flight simulator can be an effective tool for increasing participation in health-oriented PA.

Alena Tensor is a recently discovered class of energy-momentum tensors that provides a mathematical framework in which the description of a physical system in curved spacetime and its description in a flat spacetime with fields are equivalent. As demonstrated in previous publications, in curved spacetime this tensor reproduces Einstein Field Equations and in flat Minkowski spacetime, it describes physical system with fields that can be widely configured. Thanks to the obtained compliance with QM and QED, the use of the discussed tensor may significantly simplify Quantum Field Theory equations and a new interpretation of the Schrödinger equation is possible. In the article it has also been shown that the use of Alena Tensor for the electromagnetic field takes into account effects related to the particle's spin, Abraham–Lorentz effect and, in the curvilinear description, this excludes non-physical phenomena such as the black hole singularity. The article contains a method for verifying Alena Tensor within QM, proposing an explanation for the discrepancy between the Dirac and Klein-Gordon solutions. It also discusses prospects for the application of Alena Tensor in unification theories against the background of existing research directions.

When the antioxidants in our immune system cannot neutralize or convert Reactive oxygen species into safe molecules at the rate at which it is produced then this imbalance is termed as “oxidative stress”. It is related with a wide array of diseases that includes cancer, diabetes, cardiovascular diseases, hypertension etc. These ROS species however are utmost essential for the proper functioning of human body which are produced as a consequence of partial oxidation of cellular metabolism performing essential functions such as protein phosphorylation, activation of several transcriptional factors, apoptosis, immunity, and differentiation. The sources by which these are produced can be broadly classified are intrinsic and extrinsic sources. There are variety of natural antioxidant enzymes of human body that combat against this oxidative stress. The extrinsic sources of ROS include the use of natural plants, extracted flavonoids and vitamins. In this review we will briefly explain how the sources of ROS, its essential function in human body, its elevation and associated damage to organs and effect on various diseases, and a hope of finding a way of how this oxidative stress can be exploited for therapeutic potential.

This paper develops Bayesian inference in reliability of a class of scale mixtures of log-normal failure time (SMLNFT) models with stochastic (or uncertain) constraint in their reliability measures. The class is comprehensive and includes existing failure time (FT) models (such as log-normal, log-Cauchy, and log-logistic FT models) as well as new models that are robust in terms of heavy-tailed FT observations. Since classical frequency approaches to reliability analysis based on the SMLNFT model with stochastic constraint are intractable, the Bayesian method is pursued utilizing a Markov chain Monte Carlo (MCMC) sampling based approach. This paper introduces a two-stage maximum entropy (MaxEnt) prior, which elicits a priori uncertain constraint and develops Bayesian hierarchical SMLNFT model by using the prior. The paper also proposes an MCMC method for Bayesian inference in the SMLNFT model reliability and calls attention to properties of the MaxEnt prior that are useful for method development. Finally, two data sets are used to illustrate how the proposed methodology works.