Layer-wise 3D surface morphology information is critical for the quality monitoring and control of additive manufacturing (AM) processes. However, most of the existing 3D scan technologies are either contact or time consuming, which are not capable of obtaining the 3D surface morphology data in a real-time manner during the process. Therefore, the objective of this study is to achieve real-time 3D surface data acquisition in AM, which is achieved by a supervised deep learning-based image analysis approach. The key idea of this proposed method is to capture the correlation between 2D image and 3D point cloud, and then quantify this relationship by using a deep learning algorithm, namely, convolutional neural network (CNN). To validate the effectiveness and efficiency of the proposed method, both simulation and real-world case studies were performed. The results demonstrate that this method has strong potential to be applied for real-time surface morphology measurement in AM, as well as other advanced manufacturing processes.

This paper deals with the problem of real-time management of Smart Grids. For this sake, the energy management is integrated with the power system through a telecommunication system. The use of Multiagent Systems leads the proposed algorithm to find the best-integrated solution, taking into consideration the operating scenario and the system characteristics. The proposed technique is tested with the help of an academic microgrid, so the results may be replicated.

An effective process monitoring strategy is a requirement for meeting the challenges posed by increasingly complex products and manufacturing processes. To address these needs, this study investigates a comprehensive scheme based on classical machine learning methods, deep learning algorithms, and feature extraction and selection techniques. In a first step, a novel deep learning architecture based on convolutional neural networks (CNN) and gated recurrent units (GRU) is introduced to predict the local weld quality based on mid-wave infrared (MWIR) and near-infrared (NIR) image data. The developed technology is used to discover critical welding defects including lack of fusion (false friends), sagging and lack of penetration, and geometric deviations of the weld seam. Additional work is conducted to investigate the significance of various geometrical, statistical, and spatio-temporal features extracted from the keyhole and weld pool regions. Furthermore, the performance of the proposed deep learning architecture is compared to that of classical supervised machine learning algorithms, such as multi-layer perceptron (MLP), logistic regression (LogReg), support vector machines (SVM), decision trees (DT), random forest (RF) and k-Nearest Neighbors (kNN). Optimal hyperparameters for each algorithm are determined by an extensive grid search. Ultimately, the three best classification models are combined into an ensemble classifier that yields the highest detection rates and achieves the most robust estimation of welding defects among all classifiers studied, which is validated on previously unknown welding trials.

What if oxygenic photosynthesis is a primordial process with roots at the origin of life? What would the impact of this change in perspective be on our understanding of the early Earth and of the emergence and diversification of life? In here, I will examine some of the historical context of the study of the evolution of photosynthesis, which led to the consolidation of the current notion that the origin of anoxygenic photosynthesis occurred before the origin of oxygenic photosynthesis. I will show with a few examples how the mainstream view on the evolution of photosynthesis traces back to Oparin’s ‘primordial soup’ scenario for the origin of life, fuelled by the century-old perception that oxygenic photosynthesis is a plant rather than a bacterial trait. However, it has become more evident than ever before that the mainstream view is not supported by the evolution of the photosystems. In other words, the origin of biological water oxidation appears to be the seed from where photosynthesis sprout. Somewhat troubling and contrary to all predictions that derive from the mainstream view, photosystem II—the water-splitting and oxygen-evolving enzyme—shows features that are better explained if photochemical reaction centres originated during the establishment of oxygenic photosynthesis. An urgent revision of the evolution of photosynthesis procured to be free from biases of interpretations and presuppositions is strongly encouraged from all angles of the Life and Earth Sciences.

The purpose of this paper was to analyze the development trend of hazardous chemical packaging towards low carbon economy from both qualitative and quantitative perspectives. Four types of relatively small volume packaging with volume/weight less than 450L/400kg, respectively, and three intermediate bulk containers (IBCs), which are widely used for hazardous chemicals were studied to calculate the carbon footprint (CF) from cradle to grave using life cycle assessment (LCA) method and to predict the future carbon emission of hazardous chemical packaging in the next five years (2016-2020), based on the export data of Tianjin Port in China. Grey model (GM) was adopted in the prediction. The results showed that majority of IBCs have lower carbon footprint than other types when the packaging contained same amount of same hazardous chemical. With the development of international trading, the demand of hazardous chemicals will increase as well. As the result, carbon emission generated by hazardous chemical packaging will increase accordingly. However, based on GM simulation result, increasing the amount of IBC use will effectively reduce the relative amount of carbon emission.

The deterioration of gait can be used as a biomarker for ageing and neurological diseases. Continuous gait monitoring and analysis are essential for early deficit detection and personalized rehabilitation. The use of mobile and wearable inertial sensor systems for gait monitoring and analysis have been well explored with promising results in the literature. However, most of these studies focus on the technologies for gait characteristic assessment, few of them have considered the data acquisition bandwidth of the sensing system. Inadequate sampling frequency will sacrifice signal fidelity, thus leading to an inaccurate estimation especially for spatial gait parameters. In this work, we developed an inertial sensor based in-shoe gait analysis system for real-time gait monitoring and investigated the optimal sampling frequency to capture all the information on walking patterns. An exploratory validation study was performed using an optical motion capture system on four healthy adult subjects, where each person underwent five walking sessions, giving a total of 20 sessions. Percentage mean absolute errors (MAE%) obtained in stride time, stride length, stride velocity, and cadence while walking were 1.19%, 1.68%, 2.08%, and 1.23%, respectively. In addition, an eigen-analysis based graphical descriptor from raw gait cycle signals was proposed as a new gait metric that can be quantified by principal component analysis to differentiate gait patterns, which has great potential to be used as a powerful analytical tool for gait disorder diagnostics.

Cyber Physical Systems (CPS) has been a popular research area in the last decade. The dependability of CPS is still a critical issue, and rare survey has been published in this domain. CPS is a dynamic complex system, which involves various multidisciplinary technologies. To avoid human error and to simplify management, self-management CPS (SCPS) is a wise choice. And to achieve dependable self-management, systematic solution is necessary to verify the design and to guarantee the safety of self-adaptation decision, as well as to maintain the health of SCPS. This survey first recalls the concepts of dependability, and proposes a generic environment-in-loop processing flow of self-management CPS, and then analyzes the error sources and challenges of self-management through the formal feedback flow. Focus on reducing the complexity, we first survey the self-adaptive architecture approaches and applied dependability means; then we introduce a hybrid multi-role self-adaptive architecture, and discuss the supporting technologies for dependable self-management at the architecture level. Focus on dependable environment-centered adaption, we investigate the verification and validation (V&V) methods for making safe self-adaptation decision and the solutions for processing decision dependably. For system-centered adaption, the comprehensive self-healing methods are summarized. Finally, we analyze the missing pieces of the technology puzzle and the future directions. In this survey, the technical trends for dependable CPS design and maintenance are discussed, an all-in-one solution is proposed to integrate these technologies and build a dependable organic SCPS. To the best of our knowledge, this is the first comprehensive survey on dependable SCPS building and evaluation.

Material efficiency is a key element of new thinking to address the challenges of reducing impacts on the environment and of resource scarcity, whilst at the same time meeting service and functionality demands on materials. Directly related to material efficiency is the concept of the Circular Economy, which is based on the principle of optimising the utility embodied in materials and products through the life cycle. Whilst steel, as a result of high recycling rates, is one of the most ‘circular’ of all manufactured materials, significant opportunities for greater material efficiency exist, which are yet to be widely implemented. In the field of Life Cycle Management, Life Cycle Assessment (LCA) is commonly used to assess the environmental benefits of recovering and recycling materials through the manufacturing supply chain and at end-of-life. As well as containing information to calculate environmental impacts, LCA models also provide the flows of materials through the product life cycle and can also be used to quantify material efficiency and the circularity of a product system. Using an example taken from renewable energy generation, this paper explores the correlation between product circularity and the environmental case for strategies designed to improve material efficiency. An LCA-based methodology for accounting for the recovery and re-use of materials from the supply chain, and at end-of-life, is used as the basis for calculating the carbon footprint benefits of five material efficiency scenarios. Resulting carbon footprints were then compared with a number of proposed material circularity indicators. Two conclusions from this exercise were that i) LCA methodologies based around end-of-life approaches are well placed for quantifying the environmental benefits of material efficiency and circular economy strategies and ii) when applying indicators relating to the circularity of materials these should also be supported by LCA studies.

Recently, significant events took place that added immensely to the sociotechnical pressure for developing sustainable composite recycling solutions, namely (1) a ban on composite landfilling in Germany in 2009, (2) the first major wave of composite wind turbines reaching their End-of-Life (EoL) and being decommissioned in 2019-2020, (3) the acceleration of aircraft decommissioning due to the COVID-19 pandemic, and (4) the increase of composites in mass production cars, thanks to the development of high volume technologies based on thermoplastic composites. Such sociotechnical pressure will only grow in the upcoming decade of 2020s as other countries are to follow Germany by limiting and banning landfill options, and by the ever-growing number of expired composites EoL waste. The recycling of composite materials will therefore play an important role in the future, in particular for the wind energy, but also for aerospace, automotive, construction and marine sectors to reduce environmental impacts and to meet the demand. The scope of this manuscript is a clear and condensed yet full state-of-the-art overview of the available composite recycling technologies of both low and high Technology Readiness Levels (TRL). TRL is a framework that has been used in many variations across industries to provide a measurement of technology maturity from idea generation (basic principles) to commercialization. In other words, this work should be treated as a technology review providing guidelines for the sustainable development of the industry that will benefit the society. The authors propose that one of the key aspects for the development of sustainable recycling technology is to identify the optimal recycling methods for different types of composites. Why is that the case can be answered with a simple price comparison of E-glass fibers (~2 $/kg) versus a typical carbon fiber on the market (~20 $/kg) – which of the two is more valuable to recover? However, the answer is more complicated than that – the glass fiber constitutes about 90% of the modern reinforcement market, and it is clear that different technologies are needed. Therefore, this work aims to provide clear guidelines for economically and environmentally sustainable End-of-Life (EoL) solutions and development of the composite material recycling.

Autonomous navigation of spacecraft necessitates innovative technologies, methods, and algorithms, particularly when orbiting in proximity of other space objects. Optimization methods are useful for autonomous spacecraft navigation, guidance, and control, but their performance is hampered by noisy multi-sensor technologies and poorly modeled system equations, and real-time on-board utilization is generally computationally burdensome. Some proposed methods use noisy sensor data to learn the optimal guidance and control solutions real-time (online), where non-iterative instantiations are preferred to reduce computational burdens. This study aims to highlight efficacy and limitations of several common methods for optimizing guidance and control while proposing a few more, where all methods are applied to the full, nonlinear, coupled equations of motion including cross-products of motion from the transport theorem. Five disparate types of optimum guidance and control algorithms are presented and compared to a classical benchmark. Comparative analysis is based on tracking errors (both states and rates), fuel usage, and computational burden. Real-time optimalization with singular switching plus nonlinear transport theorem decoupling proves superior by matching open-loop solutions to the constrained optimization problem (in terms of state and rate errors and fuel usage), while robustness is validated in the utilization of mixed, noisy state and rate sensors and uniformly varying mass and mass moments of inertia. State tracking errors are reduced one-hundred ten percent. Rate tracking errors are reduced one-hundred thirteen percent. Control utilization (e.g., fuel) is reduced eighty four percent, while computational burden in reduced ten percent simultaneously.

A programmable DC power supply with Real-time Digital Simulator (RTDS)-based photovoltaic (PV) Power Hardware-In-the-Loop (PHIL) simulators have been used to improve the control algorithm and reliability of PV Inverter. This paper proposes a supervisory control algorithm for PV PHIL simulator with non-RTDS device that is an alternative solution of high cost PHIL simulator. However, when such a simulator with conventional algorithm which is used in RTDS is connected to a PV inverter, the output is in the transient state and it makes it impossible to evaluate the performance of the PV Inverter. Therefore proposed algorithm controls the voltage and current target values according to the constant voltage (CV) and constant current (CC) modes to overcome the limitation of the Computing Unit, DC power supply and also uses a multi-rate system to account for the characteristics of each component of simulator. A mathematical models of a PV system, programmable DC power supply, isolated DC measurement device and Computing Unit are integrated to form a real-time processing simulator. Performance tests using a PV PHIL simulator which is applied proposed algorithm connected a PV inverter are carried out and proved superiority and utility of this method against conventional methods.

This article assumes that collaborators who adopt a positive-sum, prosocial perspective can build trust-based relationships, which is equivalent to collaborative ability (CA). To improve a collaborator’s CA, we anticipated that content based upon a model of positive-sum collaboration, founded upon ancestral behaviours presented as social norms, might alter a zero-sum, proself, collaborator’s perspective. However, we also postulated that learner’s willingness to engage in positive-sum content may rely on pre-existing prosociality. Intervention participant’s prosociality was assessed via self-assessment of their emotional intelligence (EQ), quality of life (QoL), and goal orientation (GO). Learner’s engagement in online content was assessed by the three stage reached: examine website front matter; examine website content; learn website content. Tukey’s multiple comparison showed a statistically significant difference between stages one and three, in the mean of respondent’s self-assessed QoL. This suggests that participants who wished to learn content had, on average, higher quality of life, and potentially therefore greater prosociality. In general, these findings support a claim that any intervention designed to increase individual prosociality may need to consider the target population’s reticence to engage.

In this paper we analyze the relationship between bankruptcy risk and the corporate life cycle in Pakistan from 2005 to 2014. For this purpose, we run a Hierarchical Linear Mixed Model (HLM) for a sample of 301 non-financial listed firms in 12 different sectors. The empirical outcomes reveal that firms during introduction, growth and, decline stages (mature stage) of life-cycle experience higher (lower) bankruptcy risk. Moreover, in juxtaposition with growth stage, bankruptcy risk is higher at the introduction stage of life-cycle. These findings suggest that financial managers should be cautious about the financial fragility of the firm at each stage of corporate life-cycle. The results also entail that Pakistani firms do not follow a sequential pattern in their life-cycle rather they have the tendency to revert to a previous stage or jump to the next stage of life-cycle. This is the first study that empirically examines the association between firm life-cycle stage and corresponding bankruptcy risk and asserts that managers must incorporate the life-cycle effects into their financial planning and decision making for sustainable working of an enterprise.

An exploratory Life Cycle Assessment was carried out to provide insight into the environmental impacts of using the green seaweed Ulva spp. as a feedstock for production of bioplastic. The study focused on the production of lactic acid as a precursor of polylactic acid. The studied production process consists of (1) the cultivation of Ulva spp. in Integrated Multitrophic Aquaculture, (2) the processing of the biomass for solubilisation of sugars, (3) the fermentation of the sugars to lactic acid and (4) isolation of lactic acid from the fermentation broth. The study identifies environmental hotspots and compares the experimental seaweed production chain with conventional feedstock. The main hotspot identified is electricity consumption during seaweed cultivation. This impact of electricity consumption can be lowered by reducing energy use and sourcing renewable energy, and by improving the material efficiency in the product chain. To improve understanding of the environmental impacts of the production process, future studies can broaden the system boundaries and broaden the scope of sustainability issues included in the environmental assessment.

Viruses are the most numerically abundant biological entities on Earth. As ubiquitous replicators of information molecules and agents of community change, viruses have potent effects on life on Earth and may play a critical role in human spaceflight missions, life detection missions to other planetary bodies, and in planetary protection. However, major knowledge gaps constrain our understanding of the Earth’s virosphere: 1) the role viruses play in biogeochemical cycles, 2) the origin(s) of viruses, and 3) the involvement of viruses in the evolution, distribution, and persistence of life. As viruses are the only replicators that span all known types of nucleic acids, an expanded experimental and theoretical toolbox built for Earth’s viruses will be pivotal for detecting and understanding life on Earth and beyond. Only by filling in these knowledge and technical gaps will we obtain an inclusive assessment of how to distinguish and detect life on other planetary surfaces. Meanwhile, space exploration requires life-support systems for the needs of humans, plants, and their microbial inhabitants. Viral effects on microbes and plants are essential for Earth’s biosphere and human health, but virus-host interactions in spaceflight are poorly understood. Viral relationships with their hosts respond to environmental changes in complex ways which are difficult to predict by extrapolating from Earth-based proxies. These relationships must therefore be studied in space to fully understand how spaceflight will modulate viral impacts on human health and life-support systems, including microbiomes. This review addresses key questions that must be examined to incorporate viruses into Earth system models, life-support systems, and life detection. Further, the results of tackling these questions will help in our efforts to develop planetary protection protocols and further our understanding of viruses in astrobiology.

The historic view of metadata as “data about data” is expanding to include data about other items that must be created, used and understood throughout the data and project life cycles. In this context, metadata might better be defined as the structured and standard part of documentation and the metadata life cycle can be described as the metadata content that is required for documentation in each phase of the project and data life cycles. This incremental approach to metadata creation is similar to the spiral model used in software development. Each phase also has distinct users and specific questions they need answers to. In many cases, the metadata life cycle involves hierarchies where latter phases have increased numbers of items. The relationships between metadata in different phases can be captured through structure in the metadata standard or through conventions for identifiers. Metadata creation and management can be streamlined and simplified by re-using metadata across many records. Many of these ideas are being used in metadata for documenting the life cycle of research projects in the Arctic.

Molecular autism research is evolving towards a biopsychosocial framework that is more informed by autistic experiences. In this context, research aims are moving away from correcting external autistic behaviors and towards alleviating internal distress. Autism Spectrum Conditions (ASCs) are associated with high rates of depression, suicidality and other comorbid psychopathologies, but this relationship is poorly understood. Here, we integrate emerging characterizations of internal autistic experiences within a molecular framework to yield insight into the prevalence of psychopathology in ASC. We demonstrate that descriptions of social camouflaging and autistic burnout resonate closely with the accepted definitions for early life stress (ELS) and chronic adolescent stress (CAS). We propose that social camouflaging could be considered a distinct form of CAS that contributes to allostatic overload, culminating in a pathophysiological state that is experienced as autistic burnout. Autistic burnout is thought to contribute to psychopathology via psychological and physiological mechanisms, but these remain largely unexplored by molecular researchers. Building on converging fields in molecular neuroscience, we discuss the substantial evidence implicating mitochondrial dysfunction in ASC to propose a novel role for mitochondrial allostatic load in the relationship between autism and psychopathology. An interplay between mitochondrial, neuroimmune and neuroendocrine signaling is increasingly implicated in stress-related psychopathologies, and these molecular players are also associated with neurodevelopmental, neurophysiological and neurochemical aspects of ASC etiology. Together, this suggests an increased exposure and underlying molecular susceptibility to ELS that increases the risk of psychopathology in ASC. This article describes an integrative framework shaped by autistic experiences that highlights novel avenues for molecular research into mechanisms that directly affect the quality of life and well-being of autistic individuals. Moreover, this framework emphasizes the need for increased access to diagnoses, accommodations, and resources to improve mental health outcomes in autism.

The mitochondrial network is a dynamic organization within eukaryotic cells that participates in a variety of essential cellular processes, such as ATP synthesis, central metabolism, apoptosis and inflammation. The mitochondrial network is balanced between rates of fusion and fission that respond to pathophysiologic signals to coordinate appropriate mitochondrial processes. Mitochondrial fusion and fission are regulated by proteins that either reside or translocate to the inner or outer mitochondrial membranes or are soluble in the inter-membrane space. Mitochondrial fission and fusion are performed by GTPases on the outer and inner mitochondrial membranes with the assistance of other mitochondrial proteins. Due to the essential nature of mitochondrial function for cellular homeostasis regulation of mitochondrial dynamics is under strict control. Some of the mechanisms used to regulate the function of these proteins are post-translational proteolysis and/or turnover and this review will discuss these mechanisms required for correct mitochondrial network organization.

The aim of the study was to determine the presence Fusarium species and mycotoxins in winter wheat grain in Poland. Grain samples from different locations in Poland in 2009 and 2010 were analysed for the content of biomass of Fusarium species and mycotoxins. In 2009 biomass of F. graminearum and F. poae was present in all samples, F. culmorum in 82% of samples, F. avenaceum in 55% of samples. F. sporotrichioides, F. tricinctum and F. equiseti were found only in individual samples. F. langsethiae was not detected. In 2010, five Fusarium species were detected with the exception of F. sporotrichioides. The highest content of biomass was found for F. graminearum followed by F. avenaceum, F. poae and F. langsethiae. The amount of F. culmorum biomass was very low. The most frequently occurring species was F. poae and F. graminearum. In 2009, deoxynivalenol was detected in all samples. In 2010, the average content of deoxynivalenol was lower than in 2009. Nivalenol was detected at very low concentration in both years. Significant correlations between content of F. graminearum biomass and deoxynivalenol concentration in grain and between content of F. poae biomass and nivalenol concentration in grain in 2009 were found. The most important finding of this study was that main Fusarium species infecting wheat kernels in Poland in both years was F. graminearum. The amount of biomass of F. graminearum was the highest in both years. It was present in the most samples. The other frequently detected species was F. poae, which in 2010 appeared in more samples than F. graminearum. However, the amount of F. poae biomass was lower. F. culmorum, species that was previously dominating as wheat pathogen in Poland, was found less frequently than F. graminearum. The amount of biomass of this species was the lowest in 2010.

Study nature of epidemiological risk factors and patterns of distribution of mortality from Alzheimer's (D_A) in 160 countries. An exponential Malthus model was used to construct adequate approximations of statistical data. Proportionality of average lifetime after 55 years (Δt) to education index (Ψ) was established. Ranking of countries by increasing value of ΨΔt showed that D_A depends exponentially on ΨΔt and all countries can be divided into three groups in accordance with level of their economic development. In series of countries of low, medium and highly developed, their average values of D_A increase exponentially. Growth of D_A in developed countries in post-industrial epoch was explained by emergence of a new risk factor Alzheimer's of a mental nature. A mismatch of complexity or, on contrary, primitiveness of profession with level of mental development of worker, provokes development of chronic stress in him, fraught with pathologies of cognitive function metabolism in elderly. The geography of Alzheimer's disease was explained by the dependence of the human mentality on latitudinal climate change and on the chiral factor of a solar nature acting at night on a sleeping person.

Given the high number of vehicle-crash victims, it has been established as a priority to reduce this figure in the transportation sector. For this reason, many of the recent researches are focused on including control systems in existing vehicles, to improve their stability, comfort and handling. These systems need to know in every moment the behavior of the vehicle (state variables), among others, when the different maneuvers are performed, to actuate by means of the systems in the vehicle (brakes, steering, suspension) and, in this way, to achieve a good behavior. The main problem arises from the lack of ability to directly capture several required dynamic vehicle variables, such as roll angle, from low-cost sensors. Previous studies demonstrate that low-cost sensors can provide data in real-time with the required precision and reliability. Even more, other research works indicate that neural networks are efficient mechanisms to estimate roll angle. Nevertheless, it is necessary to assess that the fusion of data coming from low-cost devices and estimations provided by neural networks can fulfill the reliability and appropriateness requirements for using these technologies to improve overall safety in production vehicles. Because of the increasing of computing power, the reduction of consumption and electric devices size, along with the high variety of communication technologies and networking protocols using Internet have yield to Internet of Things (IoT) development. In order to address this issue, this study has two main goals: 1) Determine the appropriateness and performance of neural networks embedded in low-cost sensors kits to estimate roll angle required to evaluate rollover risk situations. 2) Compare the low-cost control unit devices (Intel Edison and Raspberry Pi 3 Model B), to provide the roll angle estimation with this artificial neural network-based approach. To fulfil these objectives an experimental environment has been set up composed of a van with two set of low-cost kits, one including a Raspberry Pi 3 Model B, low cost Inertial Measurement Unit (BNO055 - 37€) and GPS (Mtk3339 - 53€) and the other having an Intel Edison System on Chip linked to a SparkFun 9 Degrees of Freedom module. This experimental environment will be tested in different maneuvers for comparison purposes. Neural networks embedded in low-cost sensor kits provide roll angle estimations very approximated to real values. Even more, Intel Edison and Raspberry Pi 3 Model B have enough computing capabilities to successfully run roll angle estimation based on neural networks to determine rollover risks situation fulfilling real-time operation restrictions stated for this problem.

The construction industry is responsible for 40 to 45% of primary energy consumption in Europe alone. Therefore, it is essential to find new materials with a lower environmental impact in order to attain sustainable housing. This study aims to determine and compare the environmental impact of two clay samples forming a basis for the manufacture of traditional brick, a standard material in building construction; traditional red clay brick and a brick based on clay mixed with a biological ingredient. The samples of fired clay were manufactured at the laboratory scale, the results being valid exclusively as indicators for the extrapolation of the analysis to other studies. The results of the environmental impact of these formulations have been examined through an evaluation of life-cycle analysis (LCA), observing that the incorporation of biological pore forming agents led to a decrease of around 15 to 20% of all impact categories studied. Thus, the suitability of using biological-based additives in clay bricks was confirmed both for their constructive characteristics (lighter material) and increased energy efficiency (better thermal insulation) considering the environmental point of view.

The increasing amount of municipal sludge in China requires safe and effective management to protect human health and ensure environmental sustainability. Pyrolysis is a thermochemical process that that decompose organic matter at elevated temperature and under anaerobic conditions, and it has attracted an increasing attention in sludge treatment in the recent years. However, comprehensive environmental and economic assessment of sludge pyrolysis in China's context is rare, due to the small quantities of full-scale sludge pyrolysis plant. In this paper, we applied our design and operation parameters of full-scale sludge pyrolysis plants to generate the material and energy consumptions of the pyrolysis system under various of conditions, including sludge organic content and moisture content, system size, system energy distribution, and whether or not heat substitution is applied. Life cycle assessment and techno-economic assessment were then applied to investigate the environmental and economic performance of the system Our results demonstrate the significant environmental and economic impacts associated with sludge properties and system size. Generally, sludge with higher organic content and lower moisture content requires less natural gas consumption, which leads to a simultaneous improvement of the system environmental and economic performance. The system economic performance is more sensitive to the system size, and centralized sludge handling using a larger pyrolysis is more economic favorable. In the most ideal case, the average global warming potential and minimum sludge handling price of sludge pyrolysis could be as low as -32.5 kg CO₂-Eq/t DS and 188.8 $/t DS, respectively. Based on these results, we discussed the pathways that could be taken to further optimize the environmental and economic performances of the pyrolysis system.

The maximization of entropy S within a closed system is accepted as an inevitability (as the second law of thermodynamics) by statistical inference alone. The Maximum Entropy Production Principle (MEPP) states that not only S maximizes, but $\dot{S}$ as well: a system will dissipate as fast as possible. There is still no consensus on the general validity of this MEPP, even though it shows remarkable explanatory power (both qualitatively and quantitatively), and has been empirically demonstrated for many domains. In this theoretical paper I provide a generalization of entropy gradients, to show that the MEPP actually follows from the same statistical inference, as that of the 2nd law of thermodynamics. For this generalization I only use the concepts of super-statespaces and microstate-density. These concepts also allow for the abstraction of 'Self Organizing Criticality' to a bifurcating local difference in this density, and allow for a generalization of the fundamentally unresolved concepts of 'chaos' and 'order'.

In factory automation systems, hybrid wired/wireless networks are often deployed to connect devices of difficult reachability such as those mounted on mobile equipment. A widespread version of these networks makes use of Access Points (APs) to implement wireless extensions of Real--Time Ethernet (RTE) networks via the IEEE 802.11 Wireless LAN (WLAN). Unfortunately, APs may introduce random delays in packet forwarding, mainly related to the their internal behaviors (e.g. code processing times) that negatively impact on the whole performance of the automation systems. Consequently, the knowledge of these delays represent a crucial design information. This paper presents an original and effective method to measure the delays introduced by APs, exploiting a hybrid loop-back link and a simple set-up with moderate instrumentation requirements. The method, which requires an initial calibration by means of a reference AP, has been successfully tested on some commercial APs. As it will be shown, the proposed measurement procedure is general and, as such, can be profitably adopted in even different scenarios.

The role of the submission was to find out what changes people think they need to make in their home because of getting older. At advanced age, the likelihood of different limitations such as vision impairment, hearing impairment or physical inability is increased. Currently, tenants are often forced to leave their long-term living space, as these spaces cannot serve “new” individual needs. This transition from the privacy of their home to the new environment often appears to be a painful change. They will not have a well-known environment because their homes cannot be adapted to their new needs. The aim is a comprehensive approach to the design of such an exterior and interior space which could serve people at all stages of their life, including the terms of mobility. This means that even if there is an unexpected situation and changes in movement abilities and physiological limitations of man, not only by natural aging, but according to accidents or disabilities we can adapt the living space to the given conditions. The survey results are presented in Germany and Slovakia. In the survey, respondents expressed their opinion on what they considered important in creating an adaptive environment considering various life changes. Results are processed graphically with explanation. The results could be of an interest to architects and designers of the environment. Based on the results of the questionnaire survey, studies of possible modifications of flats and houses were developed. The contribution brought these results to three age groups of respondents; people aged 35, 50 and over 50.

This research proposes a framework to assist wind energy developers to select the optimum deployment site of a wind farm by considering the Round 3 zones in the UK. The framework includes optimisation techniques, decision-making methods and experts’ input in order to help stakeholders with investment decisions. Techno-economic, Life Cycle Costs (LCC) and physical aspects for each location are considered along with experts’ opinions to provide deeper insight into the decision making process. A process on the criteria selections is also presented and seven conflicting criteria are being considered in TOPSIS methods in order to suggest the optimum location that was produced by the NSGAII algorithm. Seagreen Alpha was the most probable solution, followed by Moray Firth Eastern Development Area 1, which demonstrates by example the effectiveness of the newly introduced framework that is also transferable and generic. The outcomes are expected to help stakeholders and decision makers to make more informed and cost-effective decisions under uncertainty when investing in offshore wind energy in the UK.

In financial time series modelling and forecasting, combining ARMA and GARCH models tend to produce superior and reliable models for volatility persistence, half-life volatility and backtesting (application of model in real life). In Nigeria, banking stocks are mostly traded because of its potential benefits to investors. This study modelled and forecasted the Guaranty Trust (GT) Bank daily stock returns from January 2^nd 2001 to May 8^th 2017 data set collected from a secondary source. The ARMA-GARCH models, persistence, half-life and backtesting were used to analysed the collected data using student t and skewed student t distributions, and the analyses are carried out R environment using rugard and performanceAnaytics Packages. The study revealed that using the lowest information criteria values only could be misleading rather we added the use of backtesing. The ARMA(1,1)-GARCH(1,1) models fitted exhibited high persistency in the daily stock returns while the days it takes for mean-reverting of the models ranges from 5 days to 100 days but unfortunately the models failed backtesting. The results further revealed ARMA(1,1)-eGARCH (2,2) model with student t distribution provides a suitable model for evaluating the GT bank stock returns among the competing models while it takes less than 30 days for the persistence volatility to return back to its average value of the stock returns. This study recommended that researchers should adopt backtesting approach while fitting GARCH models while GT bank stocks investor should be assured that no matter the fluctuations in the stock market, the GT bank stock returns has the ability to returns to its mean price return.

Leaf temperature (T_leaf) influences photosynthesis and respiration. Currently, there is a growing interest on including lianas in productivity models due to their increasing abundance, and their detrimental effects on net primary productivity in tropical environments. Therefore, understanding the differences of T_leaf between lianas and trees is important for future of forest on whole ecosystem productivity. Here we determined the displayed leaf temperature (T_d= T_leaf – ambient temperature) of several species of lianas and their host trees during ENSO and non-ENSO years to evaluate if the presence of lianas affects the T_d of their host trees, and if leaves of lianas and their host trees exhibit differences in T_d. Our results suggest that close to midday, the presence of lianas does not affect the T_d of their host trees; however, lianas tend to have higher values of T_d than their hosts across seasons, in both ENSO and non-ENSO years. Although lianas and trees tend to have similar physiological-temperature responses, differences in T_d could lead to significant differences in rates of photosynthesis and respiration based temperature response curves. Future models should thus consider differences in leaf temperature between these life forms to achieve robust predictions of productivity.

The origin of life was a cosmic event happened on primitive Earth. A critical problem to better understand the origins of life in Earth is to glimpse in which chemical scenarios the basic building blocks of biological molecules could be produced. Classic works in pre-biotic chemistry frequently considered early Earth as a homogeneous atmosphere constituted by chemical elements such as methane (CH₄), ammonia (NH₃), water (H₂O), hydrogen (H₂) and hydrogen sulfide (H₂S). Under that scenario, Stanley Miller was capable to produce amino acids and solved the question about the origin of proteins. Conversely, the origin of nucleic acids has tricked scientists for decades as nucleotides are complex though necessary molecules to allow the existence of life. Here we review possible chemical scenarios that allowed not only the formation of nucleotides but also other significant biomolecules. We aim to provide a theoretical solution for the origin of biomolecules at specific sites named “Prebiotic Chemical Refugia”. A prebiotic chemical refugium should therefore be understood as a geographic site in prebiotic Earth on which certain chemical elements were accumulated in higher proportion than expected, facilitating the production of basic biomolecules. Plus, this higher proportion should not be understood as static, but dynamic; once the physicochemical conditions of our planet changed periodically. This different concentration of elements, together with geochemical and astronomical changes along days, synodic months and years provided somewhat periodic changes in temperature, pressure, electromagnetic fields, and conditions of humidity; among other features. Recent and classic works suggesting most likely prebiotic refugia on which the main building blocks of biological molecules might be accumulated are reviewed and discussed.

Genes and gene trees have been extensively used to study the evolutionary relationships among populations, species, families and higher systematic clades of organisms. This brought modern Biology into a sophisticated level of understanding about the evolutionary relationships and diversification patterns that happened along the entire history of organismal evolution in Earth. Genes however have not been placed in the center of questions when one aims to unravel the evolutionary history of genes themselves. Thus, we still ignore whether Insulin share a more recent common ancestor to Hexokinase or DNA polymerase. This brought modern Genetics into a very poor level of understanding about sister group relationships that happened along the entire evolutionary history of genes. Many conceptual challenges must be overcome to allow this broader comprehension about gene evolution. Here we aim to clear the intellectual path in order to provide a fertile research program that will help geneticists to understand the deep ancestry and sister group relationships among different gene families (or orthologs). We aim to propose methods to study gene formation starting from the establishment of the genetic code in pre-cellular organisms like the FUCA (First Universal Common Ancestor) until the formation of the highly complex genome of LUCA (Last UCA), that harbors hundreds of genes families working coordinated into a cellular organism. The deep understanding of ancestral relationships among orthologs will certainly inspire biotechnological and biomedical approaches and allow a deep understanding about how Darwinian molecular evolution operates inside cells and before the appearance of cellular organisms.

Climate change and development have increased urban flooding, requiring modernization of stormwater infrastructure. Retrofitting standard passive systems with controllable valves/pumps is promising, but requires real-time control (RTC). One method of automating RTC is reinforcement learning (RL), a general technique for sequential optimization and control in uncertain environments. The notion is that an RL algorithm can use inputs of real-time flood data and rainfall forecasts to learn a policy for controlling the stormwater infrastructure to minimize measures of flooding. In real-world conditions, rainfall forecasts and other state information, are subject to noise and uncertainty. To account for these characteristics of the problem data, we implemented Deep Deterministic Policy Gradient (DDPG), an RL algorithm that is distinguished by its capability to handle noise in the input data. DDPG implementations were trained and tested against a passive flood control policy. Three primary cases were studied: (i) perfect data, (ii) imperfect rainfall forecasts, and (iii) imperfect water level and forecast data. Rainfall episodes (100) that caused flooding in the passive system were selected from 10 years of observations in Norfolk, Virginia, USA; 85 randomly selected episodes were used for training and the remaining 15 unseen episodes served as test cases. Compared to the passive system, all RL implementations reduced flooding volume by 70.5% on average, and performed within a range of 5%. This suggests that DDPG is robust to noisy input data, which is essential knowledge to advance the real-world applicability of RL for stormwater RTC.

Analysis of Fatigue Strain, Fatigue Modulus and Fatigue Damage for the modeling of concrete plays a vital role in the evolution material behaviour which is heterogeneous and anisotropic in nature. In this paper, the Level-S nonlinear fatigue strain curve, fatigue modulus curve, residual strain curve of concrete in compression, tension, flexure and torsional fatigue loading were proposed using strain life approach. The parameters such as physical meaning, the ranges, and the impact on the shape of the curve were discussed. Then, the evolution model of fatigue modulus was established based on the fatigue strain evolution model, fatigue modulus evaluation model, residual strain evaluation model, secondary strain evaluation model. The hypothesis of fatigue modulus is inversely related with the fatigue strain amplitude. The fatigue evolution of concrete damages the bond between material grains, changed the orientation of structure of molecules and affects the elastic properties resulting in the reduction of material stiffness and modulus by utilizing strain life analysis, regarding stiffness degradation and inelastic deformation by formation of microcracking, macro cracking, cracking which is heterogeneous and anisotropic in nature . This paper presents the Fatigue Strain Life Model and analyses of fatigue strain, fatigue modulus and damage parameters of concrete which is capable of predicting stiffness degradation, inelastic deformation, strength reduction under fatigue loading. Hence, the obtainable results were compared with experimental results for the validation of the proposed model.

What is the function of cognition? On one influential account, cognition evolved to co-ordinate behaviour with environmental change or complexity (Godfrey-Smith 1996). Liberal interpretations of this view ascribe cognition to an extraordinarily broad set of biological systems – even bacteria, which modulate their activity in response to salient external cues, would seem to qualify as cognitive agents. However, equating cognition with adaptive flexibility per se glosses over important distinctions in the way biological organisms deal with environmental complexity. Drawing on contemporary advances in theoretical biology and computational neuroscience, we cash these distinctions out in terms of different kinds of generative models, and the representational and uncertainty-resolving capacities they afford. This analysis leads us to propose a formal criterion for delineating cognition from other, more pervasive forms of adaptive plasticity. On this view, biological cognition is rooted in a particular kind of functional organisation; namely, that which enables the agent to detach from the present and engage in counterfactual (active) inference.

We investigate wealth accumulation in forestry, assuming that revenues are re-invested. Three different optimization criteria are compared, two of which are based on cash flows, the third financially grounded. Direct optimization of wealth appreciation rate always yields best results. Procedures gained by maximizing internal rate of return are only slightly inferior. With external discounting interest rate, the maximization of net present value yields arbitrary results, with at worst devastating financial consequences.

World statistics demonstrate that around 970 million people around the globe suffer from mental health problems (Ritchie & Roser, 2019), a major proportion of which comprised of adolescents and young adults (UNODC, 2018). Also, because of increased mental health issues the problems like substance use, suicide, depression, anxiety, and stress are also increasing (Armstrong, 2019; Bandelow & Michaelis, 2015; Ritchie & Roser, 2018; United Nations Office on Drugs and Crime [UNODC], 2019). It is thus a dire need to address the issue. The present coneptual paper proposed the role of transpersonal gratitude, emotional intelligence, and life contentment for reducing mental health risk among the adolescents and young adults.

The nature of contemporary Spatial Data Infrastructures lies in the provision of geospatial information in an on-demand fashion. Though recent applications identified the need to react to real-time information in a time-critical way. In particular, research efforts in the field of geospatial Internet of Things have identified substantial gaps in this context, ranging from a lack of standardization for event-based architectures to the meaningful handling of real-time information as ''events''. This manuscript presents work in the field of Event-driven Spatial Data Infrastructures with a particular focus on sensor networks and the devices capturing in-situ measurements. The current landscape of Spatial Data Infrastructures is outlined and used as the basis for identifying existing gaps that retain certain geospatial applications from using real-time information. We present a selection of approaches - developed in different research projects - to overcome these gaps. Being designed for specific application domains, these approaches share commonalities as well as orthogonal solutions and can build the foundation of an overall Event-driven Spatial Data Infrastructure.

BACKGROUND Epidemiological sciences have been evolving at an exponential rate paralleled only by the comparable growth within the discipline of data science. Digital epidemiological studies are playing a vital role in medical science analytics for the past few decades. To date, there are no published attempts at deploying the use of real-time analytics in connection with the disciplines of Dentistry or Medicine. AIMS AND OBJECTIVES We deployed a real-time statistical analysis in connection with topics in Dental Anatomy and Dental Pathology represented by the maxillary sinus, posterior maxillary teeth, related oral pathology. The purpose is to infer the digital epidemiology based on a continuous stream of raw data retrieved from Google Trends database. MATERIALS AND METHODS Statistical analysis was carried out via Microsoft Excel 2016 and SPSS version 24. Google Trends database was used to retrieve data for digital epidemiology. Real-time analytics and the statistical inference were based on encoding a programming script using Python high-level programming language. A systematic review of the literature was carried out via PubMed-NCBI, the Cochrane Library, and Elsevier databases. RESULTS The comprehensive review of databases of the literature, based on specific keywords search, yielded 491813 published studies. These were distributed as 488884 (PubMed-NCBI), 1611 (the Cochrane Library), and 1318 (Elsevier). However, there was no single study attempting real-time analytics. Nevertheless, we succeeded in achieving an automated real-time stream of data accompanied by a statistical inference based on data extrapolated from Google Trends. CONCLUSION Real-time analytics are of considerable impact when implemented in biological and life sciences as they will tremendously reduce the required resources for research. Predictive analytics, based on artificial neural networks and machine learning algorithms, can be the next step to be deployed in continuation of the real-time systems to prognosticate changes in the temporal trends and the digital epidemiology of phenomena of interest.

The aim of this study was to determine whether a rowing training program improved the quantity and quality of physical activity and quality of life in female breast cancer survivors (stage I - 4.35%; II - 30.43%; III - 52.17%; and IV - 8.7%) diagnosed 6.57 ± 5.02 years previously, who had undergone a subsequent intervention (preservation 53.52%; total mastectomy 39.13% and double mastectomy 4.35%) and had a current mean age of 53.70 ± 7.88 years. The participants (N = 30) engaged in a 12-week training program, each week comprising three sessions and each session lasting 60-90 minutes. An anthropometric evaluation was performed before and after the program. The short form of the International Physical Activity Questionnaire (IPAQ-SF) and the Short Form 36 Health Survey (SF-36) were also administered. The results showed statistically significant improvements in levels of physical activity and in the dimensions of quality of life. We can conclude that a 12-week rowing training program tailored to women who have had breast cancer increases physical activity levels, leading to improved health status and quality of life.

Reinvigorated public interest in human space exploration has led to the need to address the science and engineering challenges described by NASA's Space Technology Grand Challenges (STGCs) for expanding the human presence in space. Here we define Space Bioprocess Engineering (SBE) as a multi-disciplinary approach to design, realize, and manage a biologically-driven space mission as it relates to addressing the STGCs for advancing technologies to support the nutritional, medical, and incidental material requirements that will sustain astronauts against the harsh conditions of interplanetary transit and habitation offworld. SBE combines synthetic biology and bioprocess engineering under extreme constraints to enable and sustain a biological presence in space. Here we argue that SBE is a critical strategic area enabling long-term human space exploration; specify the metrics and methods that guide SBE technology life-cycle and development; map an approach by which SBE technologies are matured on offworld testing platforms; and suggest a means to train the next generation spacefaring workforce on the SBE advantages and capabilities. In doing so, we outline aspects of the upcoming technical and policy hurdles to support space biomanufacturing and biotechnology. We outline a perspective marriage between space-based performance metrics and the synthetic biology Design-Build-Test-Learn cycle as they relate to advancing the readiness of SBE technologies. We call for a concerted effort to ensure the timely development of SBE to support long-term crewed missions using mission plans that are currently on the horizon.

In extant biology, biopolymers perform multiple crucial functions. The biopolymers are synthesized by enzyme-controlled biosystems that would not have been available at the earliest stages of chemical evolution and consist of correctly sequenced and/or linked monomers. Some of the abiotic “messy” polymers approximate some functions of biopolymers. Condensation polymers are an attractive search target for abiotic functional polymers since principal polymers of life are produced by condensation and since condensation allows for the accurate construction of high polymers. Herein the formation of hyperbranched polyesters that have been previously used in the construction of enzyme-like catalytic complexes is explored. The experimental setup compares between the branched polyesters prepared under mild continuous heating and the wet-dry cycle conditions. The results reveal that period wetting during which partial hydrolysis of the polyester occurs, helps control the chain growth and retards the gel transition. It is significant to the origin of life studies that environmental, prebiotically plausible conditions could achieve such control without enzymes or a skilled chemist. As expected in marginally controlled systems, the identification of each component of the heterogeneous system has proved challenging, but it is not crucial for drawing the conclusions.

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.

Recent studies have demonstrated silk fibroin’s ability to extend the shelf life of foods by mitigating the hallmarks of spoilage, namely oxidation and dehydration. Due to the potential for this protein to become more widespread, its safety was evaluated comprehensively. First, a bacterial reverse mutation test (Ames test) was conducted in five bacterial strains. Second, an in vivo erythrocyte test was conducted with Sprague Dawley rats at doses up to 1,000mg/kg-bw/day. Third, a range-finder study was conducted with Sprague Dawley rats at the highest consumption amount given solubility and oral gavage volume constrains (500mg/kg-bw/day). Fourth, a 28-day study in Sprague Dawley rats was conducted at the 500mg/kg-bw/day amount. Fifth, an in vitro pepsin digestion assay was performed to assess the potential for protein allergenicity. Sixth, allergenic potential was further assessed using liquid chromatography-mass spectroscopy for detection of allergenic insect proteins. Seventh, the protein sequences were subjected to bioinformatic analyses. Together, these studies raise no mutagenic, carcinogenic, toxicological, or allergenic concerns with the oral consumption of silk fibroin.

Most traditional theories of intelligence have little to do with the question of whether people with high intelligence can successfully address real world problems. A high IQ is correlated with many important outcomes (e.g., academic prominence, reduced crime), but it does not protect against cognitive biases, partisan thinking, reactance, confirmation bias, and even falling for discredited beliefs such as alchemy, cold fusion, and astrology. There are several newer theories that directly address the question about solving real-world problems. Prominent among them is Sternberg’s adaptive intelligence with “adaptation to the environment” as the central premise, a construct that does not exist on standardized IQ tests (e.g., Sternberg, 2019). Similarly, Stanovich and West (2014) argue that standardized tests of intelligence are not measures of rational thought—the sort of skill/ability that would be needed to address complex real-world problems. Halpern and Butler (2020) advocate for critical thinking as a better model of intelligence for addressing real-world problems than those that are based on psychometric properties of general intelligence. Yes, intelligence (i.e., critical thinking) can be enhanced and used for solving a real-world problem like Covid-19, which we use as an example of contemporary problems that need a new approach. Critical thinking may be an antidote for the chaos of the modern world.

Remaining service life (RSL) of pavement, as a sign of future pavement performance, has always received growing attention from pavement engineers. The RSL describes the time from the moment of pavement inspection until such a time when a major repair or reconstruction is required. The conventional approach to determining RSL involves using non-destructive tests. These tests, in addition to being costly, interfere with traffic flow and compromise users' safety. In this paper, surface distresses of pavement have been used to estimate the pavement’s RSL in order to eliminate the aforementioned problems and challenges. To implement the proposed theory, 105 flexible pavement segments were taken from Shahrood-Damghan Highway (Highway 44) in Iran. For each pavement segment, the type, severity, and extent of surface damage and pavement condition index (PCI) were determined. The pavement RSL was then estimated using non-destructive tests include Falling Weight Deflectometer (FWD) and Ground Penetrating Radar (GPR). After completing the dataset, the modeling was conducted to predict RSL using three techniques include Support Vector Regression (SVR), Support Vector Regression Optimized by Fruit Fly Optimization Algorithm (SVR-FOA), and Gene Expression Programming (GEP). All three techniques estimated the RSL of the pavement by selecting the PCI as input. The Correlation Coefficient (CC), Nash-Sutcliffe efficiency (NSE), Scattered Index (SI), and Willmott’s Index of agreement (WI) criteria were used to examine the performance of the three techniques adopted in this study. In the end, it was found that GEP with values of 0.874, 0.598, 0.601, and 0.807 for CC, SI, NSE, and WI criteria, respectively, had the highest accuracy in predicting the RSL of pavement.

The motivations for the move to electrified vehicles are discussed with reference to their improved energy efficiency, their potential for lower CO2 emissions (if the electricity system is decarbonized), their lower (or zero) NOx/particulate matter (PM) tailpipe emissions, and the lower overall costs for owners. Some of the assumptions made in life-cycle CO2 emissions calculations are discussed and the effect of these assumptions on the CO2 benefits of electric vehicles are made clear. A number of new tribological challenges have emerged, particularly for hybrid vehicles that have both a conventional internal combustion engine and a battery, such as the need to protect against the much greater number of stop-starts that the engine will have during its lifetime. In addition, new lubricants are required for electric vehicle transmissions systems. Although full battery electric vehicles (BEVs) will not require engine oils (as there is no engine) they will require a system to cool the batteries – alternative cooling systems are discussed, and where these are fluid based, the specific fluid requirements are outlined.

Prebiotic organic synthesis reactions catalyzed by Earth-abundant metal sulfides are key processes for understanding the evolution of biochemistry from inorganic molecules, yet the catalytic functions of sulfides have remained poorly explored in the context of the origins of life. Past studies on prebiotic chemistry have mostly focused on a few types of metal sulfide catalysts, such as FeS or NiS, which form limited types of products with inferior activity and selectivity. To explore the potential of metal sulfides on catalyzing prebiotic chemical reactions, here, the chemical diversity (variations in chemical composition and phase structure) of 304 natural metal sulfide minerals in a mineralogy database was surveyed and approaches to rationally predict the catalytic functions of metal sulfides are discussed based on advanced theories and analytical tools of electrocatalysis such as proton-coupled electron transfer, structural comparisons between enzymes and minerals, and in-situ spectroscopy. To this end, we introduce a model of geo-electrochemistry driven prebiotic synthesis for chemical evolution, as it helps us to predict kinetics and selectivity of targeted prebiotic chemistry under “chemically messy conditions”. We expect that combining the data-mining of mineral databases with experimental methods and theories developed in the field of electrocatalysis will facilitate the prediction and verification of catalytic performance under a wide range of pH and Eh conditions, and aid in the rational screening of mineral catalysts involved in the origins of life.

The building sector has a big potential to reduce the material resource demand needed for building construction and therefore, greenhouse gas (GHG) emissions. Digitalisation can help to make use of this potential and improve sustainability throughout the entire building’s life cycle. One way to address this potential is through the integration of Life-Cycle Assessment (LCA) into the building process by employing Building Information Modelling (BIM). BIM can reduce the effort needed to carry out an LCA and therefore facilitate the integration into the building process. A review of current industry practice and scientific literature shows two main approaches to address BIM-LCA integration. Either the LCA is performed in a simplified way at the beginning of the building process, or it is done at the very end when all the needed information is available, but it is too late for decision-making. One reason for this is the lack of methods, workflows and tools to implement BIM-LCA integration over the entire building process. Therefore, the main objective of this study is to develop an integrated BIM-LCA workflow implemented into a method for the whole building process using an existing structure for cost estimation. A tool is created and used in a case study in Switzerland to test the developed approach. The results of this study show that LCA can be performed continuously in each building phase over the entire building process using existing BIM modelling techniques. The main benefit of this approach is that the re-work caused by the need for re-entering data and the usage of many different software tools that characterise most of the current LCA practices is minimised. Furthermore, decision-making, both at the element and building levels, is supported.

The most widely accepted scientific theory for the origin of life on Earth is that prokaryotic microbes evolved from simple organic compounds in seawater under anoxic conditions. For about 1 billion years thereafter, these microbes consumed the same dissolved organic matter (DOM) from which they had evolved before scarcity of DOM forced the evolution of cyanobacterial photosynthesis followed by eukaryosis. Could the more efficient consumption of DOM have also stimulated the subsequent origin of multicellular animal life? In this report, we synthesize past and recent evidence to propose the “DOM uptake hypothesis” for the origin of metazoans. A choanoflagellate-like protozoan was the likely ancestor of the first sponge-like metazoan to evolve on Earth. Choanoflagellates have outwardly facing flagellae that are subject to viscous water movement, while sponges have choanocytes in chambers with flagellae directed to pump water with greater fluidity across an aquiferous system with a huge cellular surface area. While generally considered particle feeders, both choanoflagellates and sponges absorb DOM, with some sponges relying on DOM for as much as 90% of their diet. We propose that the earliest metazoans may have evolved to survive the dire nutritional conditions of the Cryogenian “snow-ball Earth” period (~700 million years ago) by developing a body plan with the enhanced ability to absorb low concentrations of DOM in seawater from sources such as the viral lysis of microbes, exudates of benthic stromatolites, or refractory DOM compounds. Additionally, species of extant sponges that have a high abundance of microbes living in their bodies consume the greatest amounts of DOM, suggesting that the DOM uptake hypothesis may also be dependent on microbial symbiosis.

Viruses were classically named after the very same Latin word virus, originally meaning poison or venom. Public understanding of viruses reinforces their “malign” aspects, especially nowadays under the COVID-19 global pandemic. It is our aim here to propose a new way to view viruses and understand their origins and evolution. First, viruses are the most abundant biological systems found on Earth. They can be found almost everywhere and form a subtle biological layer named virosphere. Second, viruses are probably the most important drivers of molecular evolution and they are active agents of ecosystems maintenance and homeostasis, allowing and driving their dynamic modification. A significant number of eukaryotic genomes are composed by genome elements similar to viruses and these endogenous viruses are continuously acting for our equilibrium and fitness. They are responsible for the origin of species-specific orphan genes that allow adaptation through the development of specific traits in separate lineages of eukaryotes. Accumulated evidence indicate that a viral infection was responsible to create the eukaryotic nucleus and, also, it is a syncytium structure caused by viral replication that allows the formation of the placenta. Therefore, viruses were fundamental for the evolutionary fate of eukaryotes and mammals. The presence of virus-specific genes that are absent in cellular organisms indicates that viruses existed before cells. Besides, such as progenotes, viruses are simply ribonucleoproteic entities and their capsids are orders of magnitude simpler than proteolipidic membranes. Here, we (i) propose a complete scenario to describe the major transitions in prebiotic evolution, (ii) present the possibility that viruses emerged before LUCA, and (iii) suggest that viruses originated at the age of progenotes. However, viruses do not form a monophyletic clade. They should be seen as an evolutionary stable strategy recurrently achieved by biological systems to survive. We propose that the word “VIRUS”, known as venom, is historically mistaken and introduce a new interpretation for their name as an acronym for “Very Important Replicator Unit and Symbiont”. But more than being “very important”, viruses are of “Utmost” relevance for the maintenance of life in biosphere, by which reason we suggest referring to them as “UIRUS” to reinforce their incredible role in symbiosis and their beneficial characteristics over the infectious ones.

The operation of electricity and natural gas transmission networks in the U.S. are increasingly interdependent, due to the growing number of installations of gas fired generators and the penetration of renewable energy sources. This development suggests the need for closer communication and coordination between gas and power transmission system operators in order to improve the efficiency and reliability of the combined energy system. In this paper, we present a co-simulation platform for examining the interdependence between natural gas and electricity transmission networks based on a direct current unit-commitment and economic dispatch model for the power system and a transient hydraulic gas model for the gas system. We analyze the value of day-ahead coordination of power and natural gas network operations and show the importance of considering gas system constraints when analyzing power systems operation with high penetration of gas generators and renewable energy sources. Results show that day-ahead coordination contributes to a reduction in curtailed gas during high stress periods (e.g., large gas offtake ramps) and a reduction in energy consumption of gas compressor stations.

The residential built form, including open space, provides the physical environment for social interaction. Understanding urban open space, including semi-public and public domains, through the lens of physical accessibility and visual permeability can potentially facilitate the building of a sense of community contributing to a better quality of life. Using an inner-city suburb in Perth, Western Australia as a case study, this research explores the importance of physical accessibility patterns and visual permeability for socialising in semi-public and public domains, such as the front yard and the residential streets. It argues that maintaining a balance between public and private inter-relationship in inner city residential neighbourhoods is important for creating and maintaining a sense of community.

We present the real number system as a natural generalization of the natural numbers. First, we prove the co-finite topology, $Cof(\mathbb N)$, is isomorphic to the natural numbers. Then, we generalize these results to describe the continuum $[0,1]$. Then we prove the power set $2^{\mathbb Z}$ contains a subset isomorphic to the non-negative real numbers, with all its defining structure of operations and order. Finally, we provide two different constructions of the entire real number line. We see that the power set $2^{\mathbb N}$ can be given the defining structure of $\mathbb R$. The constructions here provided give simple rules for calculating addition, multiplication, subtraction, division, powers and rational powers of real numbers, and logarithms. The supremum and infimum are explicitly constructed by means of a well defined algorithm that ends in denumerable steps. In section 5 we give evidence our construction of $\mathbb N$ and $\mathbb R$ are canonical; these constructions are as natural as possible. In the same section, we propose a new axiomatic basis for analysis. In the last section we provide a series of graphic representations and physical models that can be used to represent the real number system. We conclude that the system of real numbers is completely defined by the order structure of $\mathbb N$.}

Land surface albedo determines the splitting of downwelling solar radiation into components which are either reflected back to the atmosphere or absorbed by the surface. Land surface albedo is an important variable for the climate community and therefore was defined by the Global Climate Observing System (GCOS) as an Essential Climate Variable (ECV). Within the scope of the Satellite Application Facility for Land Surface Analysis (LSA SAF) of EUMETSAT, a near-real time (NRT) daily albedo product was developed in the last decade from observations provided by the SEVIRI instrument on board the geostationary satellites of the Meteosat Second Generation (MSG) series. In this study we present a new collection of albedo satellite products based on the same satellite data. The MSG Ten-day ALbedo (MTAL) product incorporates MSG observations over 31 days with a frequency of NRT production of 10 days. The MTAL collection is more dedicated to climate analysis studies compared to the daily albedo that was initially designed for the weather prediction community. For this reason, a homogeneous reprocessing of MTAL was done in 2018 to generate a Climate Data Record (CDR). The resulting product is called MTAL-R and has been made available to the community in addition to the NRT version of the MTAL product which has been available for several years. The retrieval algorithm behind the MTAL products comprises three distinct modules: one for atmospheric correction, one for daily inversion of a semi-empirical model of the bidirectional reflectance distribution function, and one for monthly composition that also determines surface albedo values. In this study the MTAL-R CDR is compared to ground surface measurements and concomitant albedo products collected by sensors on-board polar-orbiting satellites (SPOT-VGT and MODIS). We show that MTAL-R meets the quality requirements if MODIS or SPOT-VGT are considered as reference. This work leads to 14 years of production of geostationary land surface albedo products with a guaranteed continuity in the LSA SAF for the future years with the forthcoming third generation of European geostationary satellites.

Since electrical resistivity of concrete can be measured in a more rapid and simple way than chloride diffusivity, it should be primarily regular quality control of the electrical resistivity of concrete which provides the basis for indirect of quality control of concrete durability during the concrete construction. If this is realized, the electrical resistivity of concrete can be a crucial parameter to establish maintenance strategy for marine concrete structures. Electrical resistivity of concrete is important to estimate two processes involved in corrosion of reinforcement: initiation (chloride penetration) and propagation (corrosion rate). The resistivity of concrete structure exposed to chloride indicates the risk of early corrosion damage, because a low resistivity is related to rapid chloride penetration and to high corrosion rate. Concrete resistivity is a geometry-independent material property that describes the electrical resistance, which is the ratio between applied voltage and resulting current in a unit cell. The current is carried by ions dissolved in the pore liquid. While some data exist on the relationship between moisture content on electrical resistivity of concrete, very little research has been conducted to evaluate the effect of chloride on the conduction of electricity through concrete. The purpose of this study is to examine and quantify the effect of pore water and chloride content on surface electrical resistivity measurement of concrete. It was obvious that chloride content had influenced the resistivity of concrete and the relationship showed a linear function. That is, concrete with chloride ions had a comparatively lower resistivity. Chloride can lead to underestimate the electrical resistivity of concrete. Conclusively, this paper suggested the quantitative solution to depict the electrical resistivity of concrete with various chloride contents.

In Europe we can see a change in the social structure in the last period. Average life expectancy has increased dramatically over the last 50 years. Because of the improved life situation and advanced level of health care, older people are slower. With advancing age, the likelihood of experiencing a variety of constraints such as visual impairment, reduced hearing or physical ability increases. In such a life stage tenants are often forced to leave their long-term living space because these homes can not serve "new" individual needs and the resulting personal protection goal. This transition from the privacy of their home to the new environment often appears to be a painful change. They will take their familiar and well-known surroundings, because their homes can not be adapted to serve new needs. It must be the policy’s role to create a new inclusive social space and the requirement for architects and designers to create new goals for the design of an adaptable environment. This is a comprehensive approach to the design of the outer and inner space that could serve people even if there is an unexpected situation and changes in movement and physiological limitations of older people. The contribution shows the results of the survey conducted in Germany and Slovakia. In the survey respondents expressed their opinion on what they considered important in creating an adaptive environment. Results are processed graphically with explanation. The results were mainly for designers and developers of the indoor environment. Based on the results of the questionnaire survey, studies of possible modifications in the interior of the flats were then prepared. The contribution yielded these results in three age groups of respondents; i. people aged 35, 50 and over 50.

The specific demands inherent to supply chains built upon large IoT systems, make a must the design of a coordinated framework for cyber resilience provisioning intended to guaranteeing trusted supply chains of ICT systems, built upon distributed, dynamic, potentially insecure and heterogeneous ICT infrastructures. As such, the proposed solution is envisioned to deal with the whole supply chain system components, from the IoT ecosystem to the infrastructure connecting them, addressing security and privacy functionalities related to risks and vulnerabilities management, accountability and mitigation strategies as well as security metrics and evidence-based security assurance. In this paper we present FISHY, as a preliminary designed architecture, designed to orchestrate both existing and beyond state-of-the-art security appliances in composed ICT scenarios and also leveraging capabilities of programmable network and IT infrastructure through seamless orchestration and instantiation of novel security services, both in real-time and proactively. The paper also includes a thorough business analysis to go far beyond the technical benefits of a potential FISHY adoption as well as three real-world use cases where to strongly support the envisioned benefits of a FISHY adoption.

In this review, we explore a broad-based view of technologies for supporting human activities on the Moon. Primarily, we assess the state of life support systems technology beginning with physicochemical processes, waste processing, bioregenerative methods, food production systems and the robotics and advanced biological technologies that support the latter. We observe that the Moon possesses in-situ resources but that these resources are of limited value in CELSS – indeed, CELSS technology is most mature in recycling water and oxygen, the two resources that are abundant on the Moon. This places a premium on developing CELSS that recycles other elements that are rarified on the Moon including C and N in particular but also other elements such as P, S and K which might be challenging to extract from local resources. Although we focus on closed loop ecological life support systems, we also consider related technologies that involve the application of biological organisms to bioregenerative medical technologies and bioregenerative approaches to industrial activity on the Moon as potential future developments.

A portable urea sensor for use in the fast flow condition was fabricated using porous polytetrafluoroethylene (PTFE) membranes coated with amine-functionalized parylene, parylene-A, by vapor deposition. To generate a specific electrochemical sensor signal from urea, the urea-hydrolyzing enzyme urease was immobilized on the parylene-A-coated PTFE membranes via chemical crosslinking using glutaraldehyde. The urease-immobilized membranes were assembled in a polydimethylsiloxane (PDMS) fluidic chamber, and a screen-printed carbon three-electrode system was used for electrochemical measurements. The success of urease immobilization was confirmed using fluorescence microscopy, scanning electron microscopy, and Fourier-transform infrared spectroscopy. The optimum concentration of urease for immobilization on the parylene-A-coated PTFE membranes was determined to be 48 mg/mL, and the optimum number of membranes in the PDMS chamber was found to be 8. Using these optimized conditions, we fabricated the urea biosensor and monitored urea samples under various flow rates ranging from 0.5 to 10 mL/min in the flow condition using chronoamperometry. To test the applicability of the sensor for physiological samples, we used it for monitoring urea concentration in the waste peritoneal dialysate of a patient with chronic renal failure, at a flow rate of 0.5 mL/min.

Neonatal palliative care (NPC) is an integrated and holistic approach that is an integral part of the contemporary neonatal treatment delivery paradigm. It is the highest fulfillment of the notion of beneficence (doing or creating 'good') that has otherwise been neglected/underestimated by the focus of modern medicine on technology and instrumental treatments by its commitment to alleviating patient pain and quality of life. For decades, the Double-Effect Doctrine (DDE) has been used to consider and address a range of ethically questionable circumstances, often at the end of life, including euthanasia, termination of pregnancy to save maternal life, and morally justified warfare. The theory has continued to be mired in controversy as ethicists, legal scholars, theologians, and philosophers discuss the abstract concepts of moral reasoning, purpose, foresight, and other underlying moral theories. In this paper, the moral theory of DDE is discussed in its clinical application to the ethical decision-making process in neonatal palliative and end-of-life treatment, specifically 1) the administration of opioids as required for symptom control and 2) the use of palliative sedation for intractable symptom care.

Abstract: Discussed is an expansion of SRT to fourth-order of space-time including any velocities and possible negative kinetic energies by real rest mass in analogy of the model amplitude of enforced damped oscillation. This paper serves an introduction to developed SRT including superluminar translating velocities without tachyons or imaginary restmass. Focused is on those parts, which develop the elaborated lorentz-transformations. Discussed are the problems of this theory.

Despite the development of technologies, modern methods of disposal of end-of-life tires most often represent either the incineration in cement kilns or the destruction of tires in special landfills, showing a lack of sustainable recycling of this valuable material. The fundamental role of recycling is evident, and the development of high-efficiency processes represents a priority for the European market. Therefore, investigation of end-of-life rubber processing methods is of high importance for manufacturers and recyclers of rubber materials. In this paper, methods of processing of end-of-life tires are reviewed in order to obtain rubber crumb, which can later be used in the production of new industrial rubber goods and composite The processes of separation end-of-life tire into fractions by type of materials using mechanical processing methods along with mechanochemical and mechanical processes of processing the materials of used tires in order to obtain crumb rubber of various fractions and chemical reactivity are considered.

With the advent of real-time MRI, the motion and passage of cerebrospinal fluid can be visualized without gating and exclusion of low-frequency waves. This imaging modality gives insights into low-volume, rapidly oscillating cardiac-driven movement as well as sustained, high-volume, slowly oscillating inspiration-driven movement.Inspiration means a spontaneous or artificial increase in the intrathoracic dimensions independent of body position. Alterations in thoracic diameter enable the thoracic and spinal epidural venous compartments to be emptied and filled, producing an upward surge of cerebrospinal fluid inside the spine during inspiration; this surge counterbalances the downward pooling of venous blood toward the heart.Real-time MRI, as a macroscale in vivo observation method, could expand our knowledge of neurofluid dynamics, including how astrocytic fluid preloading is adjusted and how brain buoyancy and turgor are maintained in different postures and zero gravity.Along with these macroscale findings, new microscale insights into aquaporin-mediated fluid transfer, its sensing by cilia and its tuning by nitric oxide will be reviewed. By incorporating clinical knowledge spanning several disciplines, certain disorders—congenital hydrocephalus with Chiari malformation, idiopathic intracranial hypertension and adult idiopathic hydrocephalus—are interpreted and reviewed according to current concepts, from the basics of the interrelated systems to their pathology.

Remotely Piloted Aircraft Systems (RPAS) are increasingly becoming relevant actors flying through the airspace and will assume much more importance in the future perspective. In order to allow their safe integration with manned conventional traffic in non-segregated airspaces, in accordance with the overall Air Traffic Management (ATM) paradigm, specific enabling technologies are needed. As well known, among the enabling technologies identified as crucial for RPAS integration into the overall ATM system, the Detect and Avoid (DAA) technology is fundamental. In the meantime, to support extended surveillance, the universal introduction on-board of aircraft of cooperative Automatic Dependent Surveillance – Broadcast (ADS-B) is increasingly implemented, having the potential to allow coverage of the whole airspace also in remote areas not usually covered by conventional radar surveillance. In this paper, the experimental results are presented and discussed that have been obtained through the real-time validation, with hardware and human in the loop (RTS-HIL) simulations, of an automatic ADS-B based Separation Assurance and Collision Avoidance System aimed to support RPAS automatic operations as well as remote pilot decision making. In the paper, after an introductory outline of the Concept of Operations (ConOps) of the system and of its architectural organization, while also providing basic information about the main system functionalities, the description is reported of the tests that have been carried out and the obtained results are described and discussed, in order to emphasize the performances and limitations of the proposed system. In particular, not only the quantitative performances obtained are reported and commented but also the feedbacks received by the pilots in order to improve the system are described, for instance in terms of preferred typology of conflict resolution manoeuver elaborated by the system.

This research presents alternative solutions for an Energy Efficiency Management System (EEMS) serving as a framework for optimizing the energy consumption algorithm and lowering energy consumption. First, a monitoring Wireless Sensor and Actuator Network (WSAN) is used for sensing, measuring, gathering data, and modeling all the dynamic disturbance parameters of the rooms in the building. Second, integrated software for metering and controlling the processes of digital data flow is used. Third, an alternative solution is proposed to reduce energy consumption. The primary benefits of this system are real-time monitoring; rapid, alternative solutions; and the ability to make a prudent decision on how to lower energy consumption. The system shows instant and accumulated solutions for short and long-term time planning. The solutions identified can be implemented in the same buildings under the same circumstances. The universities of Majmaah and Philadelphia have buildings with similar infrastructure. The system was applied to the buildings at Philadelphia University. The results were generalized to both universities. After implementation, the energy consumption of the EEMS using WSAN (based on the monitoring was reduced up to 23% when compared to that of the initial state.

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

Adolescence is a critical developmental period associated with an increase in stress, the appearance of anxiety and depressive symptoms, and changes in sleep patterns. Even though the disruption of sleep patterns in stress and anxiety and depressive disorders is well known, the independent effects of childhood trauma and stressful life events on sleep patterns are less understood. We tested the independent effects of stress (childhood trauma and stressful life events) while controlling for anxiety and depression on adolescent sleep patterns. Seven hundred fifty-two adolescents completed self-report questionnaires about childhood trauma, stressful life events, anxiety, and depression. Four sleep factors identifying movement during sleep, sleep regularity, sleep disturbances and sleep pressure were extracted in the principal component analysis of sleep questions. Both childhood trauma and recent stressful life events were significantly associated with sleep disturbances before and after controlling for anxiety and depression.

A Life Cycle Analysis was performed considering three existing power plants of comparable size operating with different sources of renewable energy: geothermal, solar and wind. Primary data were used for building the life cycle inventories. The geothermal power plant includes emissions treatment for removal of hydrogen sulfide and mercury. The scenario about the substitution of natural emissions from geothermal energy, with specific reference to the greenhouse effect, is also investigated performing a sensitivity analysis. The results are characterized employing a wide portfolio of environmental indicators employing the Recipe 2016 and the ILCD 2011 Midpoint+ methods; normalization and weighting are also applied using the Recipe 2016 method at endpoint level. The results demonstrate a good eco-profile of geothermal power plant with respect to other renewable energy systems and allow for a critical analysis to support potential improvements of the environmental performances.

Quantitative differential phase contrast (qDPC) imaging has become an important method of optical measurement and life science research in microscopy because of its high reconstruction resolution and non-invasive, high-contrast and quantitative imaging of biological samples. Despite the continuous development of the principle and algorithm, the frame rate of the existing qDPC algorithm is still much lower than that of camera acquisition, so it is hardly applied to real-time image the fast-moving biological samples. In this paper, based on color-coded multiplexing strategy, a compact real-time quantitative phase imaging system is designed to realize multi-mode imaging. The system employs a programmable LED array to illuminate directly, and the phase reconstruction algorithm is deployed in the graphics processing unit (GPU) of the laptop to accelerate the calculation. The system can achieve high-speed quantitative phase imaging of non-stained biological samples, and the frame rate can reach 60fps. The device has the advantages of compact structure, low cost and portability. Thus, it is suitable for mobile medical applications.

The application of instrumented indentation to assess material properties like Young’s modulus and micro-hardness has become a standard method. In recent developments, indentation experiments and simulations have been combined to inverse methods, from which further material parameters as yield strength, work hardening rate, and tensile strength can be determined. In this work, an inverse method is introduced by which material parameters for cyclic plasticity, i.e. kinematic hardening parameters, can be determined. To accomplish this, cyclic Vickers indentation experiments are combined with finite element simulations of the indentation with unknown material properties, which are then determined by inverse analysis. To validate the proposed method, these parameters are subsequently applied to predict the uniaxial stress-strain response of a material with success. The method has been validated successfully for a quenched and tempered martensitic steel and for technically pure copper, where an excellent agreement between measured and predicted cyclic stress-strain-curves has been achieved. Hence, the proposed inverse method based on cyclic nanoindentation, as a quasi-non-destructive method, could complement or even substitute the resource-intensive conventional fatigue testing in the future for some applications.

Background: The reference test for SARS-CoV-2 detection is the reverse transcriptase real time PCR (real time RT-PCR). However, evidences reported that real time RT-PCR has a lower sensitivity compared with the droplet digital PCR (ddPCR) leading to possible false negative in low viral load cases. Methods: We used ddPCR for viral genes N1 and N2 on 20 negative (no detection) samples from symptomatic hospitalized COVID-patients presenting fluctuating real time RT-PCR results and 10 suspected samples (Ct value>35) from asymptomatic not hospitalized subjects. Results: ddPCR performed on RNA revealed 65% of positivity for at least one viral target in the hospitalized patients group of samples (35% for N1 and N2, 10% only for N1 and 20% only for N2) and 50% in the suspected cases (30% for N1 and N2, while 20% only for N2). On hospitalized patients’ samples, we applied also a direct ddPCR approach on the swab material, achieving an overall positivity of 83%. Conclusion: ddPCR, in particular the direct quantitation on swabs, shows a sensitivity advantage for the SARS-CoV-2 identification and may be useful to reduce the false negative diagnosis, especially for low viral load suspected samples.

Abstract: The promotion of sustainable packaging is part of the European Green Deal and plays a key role in the EU’s social and political strategy. One option is the use of renewable resources and biomass waste as raw materials for polymer production. Lignocellulose biomass from annual and perennial industrial crops and agricultural residues are a major source of polysaccharides, proteins, and lignin, and can also be used to obtain plant-based extracts and essential oils. Therefore, these biomasses are considered as potential substitute for fossil-based resources. Here, the status quo of bio-based polymers is discussed and evaluated in terms of properties related to packaging applications such as gas and water vapor permeability as well as mechanical properties. So far, their practical use is still restricted due to lower performance in fundamental packaging functions that directly influence food quality and safety, the length of shelf life and thus the amount of food waste. Besides bio-based polymers, this review focuses on plant extracts as active packaging agents. Incorporating extracts of herbs, flowers, trees, and their fruits is inevitable to achieve desired material properties that are capable to prolong the food shelf life. Finally, the adoption potential of packaging based on polymers from renewable resources is discussed from a bioeconomy perspective.

Using the culture-work-health model, this study investigates the factors influencing the quality of life of maritime workers. This study conducted a survey of 320 maritime workers who have experience living and working on a ship for more than six months. This self-administered questionnaire included questions on organizational culture and support, self-efficacy, perceived fatigue, as well as the quality of work life. Organizational culture and self-efficacy were identified as factors affecting the quality of work life, while organizational support was found to have an indirect effect after passing through self-efficacy and perceived fatigue. The final model accounts for 63.1% of the variance in maritime workers’ quality of life. As such, this study shows that self-efficacy is important for the quality of life of maritime workers, having both direct and indirect effects. Moreover, organizational support may prove the primary intervention point for relieving perceived fatigue and enhancing self-efficacy, thus improving the quality of work life.

The COVID-19 pandemic affects not only physical health but also deteriorates mental health resulting in sleep problems, depression, and traumatic stress. Our research investigates the level of posttraumatic stress, perceived social support, opinions on positive and negative consequences of the pandemic, sense of security, and sense of meaning among nurses in the face of new and not fully understood global epidemiological phenomena. For this purpose, computer-assisted web interviewing methods were conducted between May 1 and May 15, 2020. Participating nurses completed the following research tools: The Impact Event Scale-Revised (IES-R), The Multidimensional Scale of Perceived Social Support (MSPSS), The Changes in Outlook Questionnaire (CIOQ), The Safety Experience Questionnaire (SEQ) and The Meaning in Life Questionnaire (MLQ). Three hundred and twenty-five nurses working throughout Poland joined the study of an average age of 39.18 ± 11.16 years. The average overall IES-R score in the study group was 1.78 ± 0.65. Among the dimensions of traumatic stress, the highest score was obtained in the dimension Avoidance 1.86 ± 0.73, then in the dimensions Hyperarousal 1.8 ± 0.78 and Intrusion 1.74 ± 0.83. Amongst studied nurses, the highest support rates were provided by significant others (22.58 ± 5.22), then from friends (21.91 ± 5) and family (21.45 ± 4.4). Among the surveyed nurses, higher average scores were noted in the subscale measuring positive psychological changes (18.56 ± 4.04). In contrast, a higher average level of assessment was noted on the Reflection on the safety dimension (4.21 ± 0.49). The mean MLQ score was 5.33 ± 0.87. A slightly higher result was observed in the subscale Presence (5.35 ± 1.14). The results of the research implemented during the period of severe psychological pressure associated with the COVID-19 pandemic provided information on symptoms of traumatic stress in the examined group of nurses. Their sense of security has been lowered and accompanied by an intensified reflection on issues concerning security. However, the sense of meaning (currently felt) in life remains higher than the tendency to searching for it. The surveyed nurses perceive individual support from the so-called significant others (apart from family and friends). They see positive changes resulting from painful experiences related to the COVID-19 pandemic, which can be characterized by adaptation in the form of posttraumatic growth.

Nowadays, security is a top priority. In fact, biometrics uses cutting-edge technologies to identify terrorists and criminals. But the practice of distinguishing humans based on intrinsic physical or behavior traits goes back thousands of years. With the widespread use of computers in the late 20th century, new possibilities for digital biometrics emerged and new technologies were generously used. Among these, we remember high resolution security video cameras and drones. So, the aim of the present project is to study and explain the features of these technologies, especially the ones of the the Phantom 4 Pro+ aircraft and analyze its operating methods in order to identify human faces during live streaming of videos. For this purpose, it will be used Paul Viola and Michael Jones’ face detection algorithm, which includes Haar features and cascade classifiers to identify faces, eyes and ears of an individual.

This paper proposes a real-time local positioning system (RT-LPs) utilizing a mobile platform equipped with three anchor nodes placed in a right-angle triangle formation for a real-time locating system (RTLS). After deriving an analytic formula to calculate the target position utilizing the measured distances among anchor nodes and the target node, we find that four parameters have an effect on the position error of the target node. The spacing between anchors is a design parameter that must be large enough to the reduce position error. However, the distance from the anchor node to the target node is an operation parameter that must be small enough to reduce the position error. Additionally, the measured ranges among the anchors and the target node have probabilistic distributions with a mean and variance, which are dominant parameters that have effects on the position error. A comparison study was conducted to determine the effects of the parameters of the target position in both a simulation and an experiment, showing rates of approximately 4% ~ 10%. These findings indicate that our simulation can work properly with the proposed method after assuming that the distance error is a Gaussian model.

Since the beginning, humans advanced their civilization by making better tools to improve their lives. Tools and products were designed for better living considering manufacturing issues, cost and time as predominant criteria. It has become clear that not considering environment and society, both at local/global levels, has now become a major impediment affecting living conditions on a large portion of the Earth and in many societies. Design methodologies should lead to creative solutions with consideration to engineering and economics for practicality but also to environmental and social constraints for sustainability. We propose a comprehensive design methodology based on multidisciplinary design to include the knowledge of humanities, environmentalists, science and engineering, and allowing for experts’ inputs from these areas to provide a holistic approach to engineering design . For example, experts in humanities are expected to interact with stakeholders to evaluate their value systems to provide guidance for the design. The methodology that we synthesize is new and combines (i) Societal level impacts at all scales, (ii) Environmental impacts and (iii) Engineering design with economic impacts, including uncertainty considerations. The proposed design methodology is called Social-Environmental-Economical-Engineering Framework (SEEEF). It can utilize concepts and tools such as Circular Design, Doughnut Economics, design based on environmental life cycle analysis, among others. SEEEF is quantity based and provides steps for evaluating any project or product in an objective manner and will help train engineers in design for sustainability. It also provides non-engineers with a significant role in design to increase their understanding of the hard constraints of engineering. Ultimately, SEEEF allows society to take an informed decision considering short/long term and local/global impacts of the design and the pertinent uncertainties.

Nutrient depletion in Tanzanian sisal production has led to yield decreases over time. We use nutrient mass balances embedded within a life cycle assessment to quantify the extent of nutrient depletion for different production systems, then used circular economy principles to identify potential cosubstrates from within the Tanzanian economy to anaerobically digest with sisal wastes. The biogas produced is then used to generate bioelectricity and the digestate residual can be used as a fertilizer to address the nutrient depletion. If no current beneficial use of the cosubstrate was assumed, then beef manure and marine fish processing waste were the best cosubstrates. If agricultural wastes were assumed to have a current beneficial use as fertilizer, then marine fish processing waste and human urine were the best cosubstrates. The largest reduction in environmental impacts resulted from bioelectricity replacing electricity from fossil fuels in the national electricity grid and improved onsite waste management practices. There is significant potential to revitalize Tanzanian sisal production by applying circular economy principles to sisal waste management and bioenergy production.

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

The urgency to develop vaccines against Covid-19 is putting pressure on the long and expensive development timelines which are normally required for development of lifesaving vaccines. There is a unique opportunity to take advantage of new technologies, smart and flexible design of clinical trials, and evolving regulatory science to speed up vaccine development against Covid-19 and transform vaccine development altogether.

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.

The last few decades have witnessed a surge of interest in adventure sports, and an emerging research focus on these activities. However, recent conceptual analyses and scientific reviews have highlighted a major, fundamental question that remains unresolved: what constitutes an adventure sport (and are they ‘sports’ at all)? Despite several proposals for definitions, the field still seems to lack a shared conceptualization. This deficit may be a serious limitation for research and practice, restricting the development of a more nuanced theoretical explanation of participation and prac-tical implications within and across adventure sports. In this article we address another crucial question, how can adventure sports be better understood for research and practice? We briefly summarize previous definitions to address evident confusion and lack of conceptual clarity in the discourse. Alternatively, we propose how an ecological perspective on human behaviors, as in-teractions with the environment, may provide an appropriate conceptualization to guide and enhance future research and practice, using examples from activities such as freeride skiing / snowboarding, white-water kayaking, climbing, mountaineering and the fields of sport science, psychology and avalanche research and education. We draw on ecological dynamics as a trans-disciplinary approach to discuss how this holistic framework presents a more detailed, nuanced, and precise understanding of adventure sports.

The circumstances arising from the exceptional situation caused by the COVID-19 pandemic have affected all socioeconomic areas in the last two years. The field of Education has not been an exception and the management of the situation seems to have caused an increase in the level of perceived stress of university students. On this basis, this research that aims, first, to analyze the student’s level of perceived stress during the de-escalation and return to normality period, secondly, to evaluate its relationship with life satisfaction and, finally, to detect the students' needs in stress management, has been developed. An exploratory-descriptive study of quantitative and cross-sectional nature has been carried out. 222 university students of the Childhood and Primary Education Degrees of the University of Jaén (Spain) have participated. The instruments, Perceived Stress Scale (PSS) and Satisfaction with Life Scale (SWLS) have been used. The results show a moderate and partial relationship among the dimensions of the used instruments. The obtained coefficients of determination are, Academic Performance (r² = .019) and Life Satisfaction (r² = .402), with a mean square error (SRMR) of .079. These findings show the need to develop actions within the university training program in effective stress management strategies.

The remaining capacity can only be measured with offline method. This brings great challenge for the online prediction of Li-ion battery’s RUL. A novel online prediction method for Li-ion battery’s RUL was proposed, which is based on multiple health indicators (HIs) and can be derived from the batteries’ historical operation data. Firstly, four indirect HIs were built according to the battery’s operation current, voltage and temperature data respectively. On that basis, a generalized regression neural network (GRNN) was developed to estimate the battery’s remaining capacity, and the non-linear autoregressive approach (NAR) was utilized to predict the battery’s RUL based on the estimated capacity value. Furthermore, to reduce the interference, twice wavelet denoising were performed with different thresholds. A case study is conducted with a NASA battery dataset to demonstrate the effectiveness of the method. The result shows that the proposed method can obtain Li-ion batteries’ RUL effectively.

Rapid growth of IoT applications and their interference in our daily lives led to many different IoT devices which generates enormous data. The IoT devices’ resources are very limited, so storing and processing IoT data in the devices is very inefficient. Several resources of cloud-computing are efficiently used to handle some IoT resources issues. While using resources in the cloud centers cause some other issues, like latency in the IoT applications, which are time-critical. Thus, the technology of edge cloud has evolved recently. This technology permits storage and data processing at the network edge. This paper studies edge computing in-depth for timeless sensitive devices in IoT. In-depth, cutting-edge IoT computing systems (ECAs-IoT) are evaluated and characterized in this paper according to numerous criteria, such as information placement, improvisation facilities, reliability, and data visualization. Moreover, according to distinctive properties, the paper aims at comparing each structure in detail. The paper also highlights the significant limitations of the new ECAs-IoT and recommends solutions to them. The studies also introduce and propose solutions to some of the most important restrictions of the current ECAs-IoT. Consequently, in the edge computing domain, this survey outlines the IoT implementations. Lastly, with the use of IoT implementations for ECAs-IoT, the paper suggests four distinct scenarios.

Systems Chemistry has been a key component of origin of life research, invoking models of life’s inception based on evolving molecular networks. One such model is the Graded Autocatalysis Replication Domain (GARD) formalism embodied in a Lipid World scenario, which offers rigorous computer simulation based on defined chemical kinetics equations. GARD suggests that the first pre-RNA life-like entities could have been homeostatically-growing assemblies of amphiphiles, undergoing compositional replication and mutations, as well as rudimentary selection and evolution. Recent progress in Molecular Dynamics has provided an experimental tool to study complex biological phenomena such as protein folding, ligand-receptor interactions and micellar formation, growth and fission. The detailed molecular definition of GARD and its inter-molecular catalytic interactions make it highly compatible with Molecular Dynamics analyses. We present a roadmap for simulating GARD’s kinetic and thermodynamic behavior using various Molecular Dynamics methodologies. We review different approaches for testing the validity of the GARD model, by following micellar accretion and fission events and examining compositional changes over time. Near future computational advances could provide empirical delineation for further system complexification, from simple compositional non-covalent assemblies towards more life-like protocellular entities with covalent chemistry that underlies metabolism and genetic encoding.

The importance of the contribution from tourism to climate change was pointed out by the International Tourism Organization (UNWTO). By combining process-based Life Cycle Assessment (LCA) and Input-output analysis, several researches have tried to evaluate the impacts of the tourism industry as well as its products and services. Indeed, the tourism sector has a wide range of industries including travel and tour, transportation, accommodation, food and beverage, amusement, souvenirs etc. However, the existing cases did not show a breakdown of the impact on climate change. In this paper, the carbon footprint (CFP) of the Japanese tourism industry was calculated based on tourist consumption, using the Japanese Input-output table and the Japanese tourism industry. It was shown that the total emissions were approximately 136 million t-CO2 per year. The contribution ratio of each stage is as follows: Transport 56.3%, Souvenirs 23.2%, Petrol (direct emissions) 16.9%, Accommodation 9.8%, Food and Beverage 7.5%, Activities 3.0%. Then, in the breakdown, the impact is high in the following order Air transport 24.7%, Petrol (direct emissions) 16.9%,Accommodation 9.8%, Food and Beverage 7.5%, Petrol 6.1%, Textile products 5.3%, Food items 4.9%, Confectionery 4.8%, Rail transport 3.9%, Cosmetics 1.9%, Footwear 1.8%, etc. In addition to transportation, this research also highlighted especially the contribution from souvenirs, accommodation, food and beverages.

The search for molecular biosignatures at the surface of Mars is complicated by an intense irradiation in the mid- and near- ultraviolet (UV) spectral range for several reasons: (i) many astrobiologically relevant molecules are electronically excited by efficient absorption of UV radiation and rapidly undergo photochemical reactions; (ii) even though the penetration depth of UV radiation is limited, aeolian erosion continually exposes fresh material to radiation; and (iii) UV irradiation generates strong oxidants such as perchlorates that can penetrate deep into soils and cause subsurface oxidative degradation of organics.As a consequence, it is crucial to investigate the effects of UV radiation on organic molecules embedded in mineral matrices mimicking the martian soil, in order to validate hypotheses about the nature of the organic compounds detected so far at the surface of Mars by the Curiosity rover, as well as organics that will be possibly found by the next rover missions Mars 2020 and ExoMars 2020. In addition, studying the alteration of possible molecular biosignatures in the martian environment will help to redefine the molecular targets for life detection missions and devise suitable detection methods.Here we report the results of mid-UV irradiation experiments of Mars soil analog samples obtained adsorbing relevant organic molecules on a clay mineral that is quite common on Mars, i.e. montmorillonite, doped with 1 wt% of magnesium perchlorate. Specifically, we chose to investigate the photostability of a plausible precursor of the chlorohydrocarbons detected on Mars by the Curiosity rover, namely phthalic acid, along with the biomarkers of extant life L-phenylalanine and L-glutamic acid, which are proteomic amino acids, and adenosine 5’-monophosphate, which is a nucleic acid component.We monitored the degradation of these molecules adsorbed on montmorillonite through in situ spectroscopic analysis, investigating the reflectance properties of the samples in the Near InfraRed (NIR) spectral region. Such spectroscopic characterization of molecular alteration products provides support for two upcoming robotic missions to Mars that will employ NIR spectroscopy to look for molecular biosignatures, through the instruments SuperCam on board Mars 2020, ISEM, Ma_Miss and MicrOmega on board ExoMars 2020.

Future cyber-physical systems may extend over broad geographical areas, like cities or regions, thus requiring the deployment of large real-time networks. A strategy to guarantee predictable communication over such networks is to synthesize an offline time-triggered communication schedule. However, this synthesis problem is computationally hard (NP-complete), and existing approaches do not scale satisfactorily to the required network sizes. This article presents a segmented offline synthesis method which substantially reduces this limitation, being able to generate time-triggered schedules for large hybrid (wired and wireless) networks. We also present a series of algorithms and optimizations that increase the performance and compactness of the obtained schedules while solving some of the problems inherent to segmented approaches. We evaluate our approach on a set of realistic large-size multi-hop networks, significantly larger than those considered in the existing literature. The results show that our segmentation reduces the synthesis time up to two orders of magnitude.

There are many ‘faces’ of early life adversity (ELA), such as childhood trauma, institutionalization, abuse or exposure to environmental toxins. These have been implicated in the onset and severity of a wide range of chronic non-communicable diseases later in life. The later-life disease risk has a well-established immunological component. This raises the question as to whether accelerated immune-ageing mechanistically links early-life adversity to the lifelong health trajectory resulting in either ‘poor’ or ‘healthy’ ageing. Here we examine observational and mechanistic studies of ELA and inflammageing, highlighting common and distinct features in these two life stages. Many biological processes appear in common including reduction in telomere length, increased immuno-senescence, metabolic distortions and chronic (viral) infections. We propose that ELA shapes the developing immune, endocrine and nervous system in a non-reversible way, creating a distinct phenotype with accelerated immuno-senescence and systemic inflammation. We believe that ELA acts as an accelerator for inflammageing and age-related diseases. Furthermore, we now have the tools and cohorts to be able to dissect the interaction between early life adversity and later life phenotype. This should, in the near future, allow us to identify the ecological and mechanistic processes that are involved in ‘healthy’ or accelerated immune-ageing.

Background: Breast cancer is the second type of cancer diagnosed in women and is the first cancer in women worldwide. Breast cancer also causes high morbidity and mortality in women and becomes a heavy burden due to the incidence of disability due to the disease. Purpose: This literature review aims to examine how social support affects anxiety, depression and quality of life in breast cancer sufferers. Method: The data were obtained by searching for reputable and trustworthy journals. have high quality criteria, namely Scopus, Proquest, Science Direct, Elsevier, Pubmed. Journals or articles used in this review literature are searched using keywords and Boolean operators (AND, OR NOT, or AND NOT). Keywords in this review literature are as follows: social support OR family support, quality of life OR Quality, anxiety OR depression, AND Cancer OR cancer treatment OR Chronic disease. Results: The results of this literature review show that there is a significant influence between the social support received by breast cancer patients on the improvement of their quality of life. The social support provided is also able to reduce anxiety and depression in breast cancer sufferersConclusion: Social support given to breast cancer patients is proven to have an effect on improving the quality of life, reducing anxiety and depression.

For Interferometry Synthetic Aperture Radar (InSAR), the normal baseline is one of the main factors that affect the accuracy of the ground elevation. For Gaofen-3 (GF-3) InSAR processing, the poor accuracy of the real-time orbit determination resulting in a large baseline error, leads to the modulation error in azimuth and the slope error in range for timely Digital Elevation Model (DEM) generation. In order to address this problem, a baseline estimation method based on external DEM is proposed in this paper. Firstly, according to the characteristic of the real-time orbit of GF-3 images, orbit fitting is executed to remove the non-linear error factor. Secondly, the height errors are obtained in slant-range plane between Shuttle Radar Topography Mission (SRTM) DEM and the GF-3 generated DEM after orbit fitting. At the same time, the height errors are used to estimate the baseline error which has a linear variation. In this way, the orbit error can be calibrated by the estimated baseline error. Finally, DEM generation is performed by using the modified baseline and orbit. This procedure is implemented iteratively to achieve a higher accuracy DEM. Based on the results of GF-3 interferometric SAR data for Hebei, the effectiveness of the proposed algorithm is verified and the accuracy of GF-3 real-time DEM products can be improved extensively.

It remains poorly understood how the life history strategies and transmission ecologies of viruses of plants, arthropods, and vertebrates are interrelated. The present analysis hinges on the virus transmission success. Virus transmission reflects where in the host-body viruses are retained or replicating. Plants, arthropods, and vertebrates share a protective outer-layer, a circulatory system, and reproductive organs. The latter enables vertical virus transmission and associates with virus-host mutualism. Two broadly opposing virus life history strategies are considered. Acute viruses tend to be replicative and are swiftly transmitted to the next host. Instead, persistent viruses keep virus replicating costs and host damage to a minimum. The intertwined life histories and transmission ecologies are accordingly pieced together, based on the virus mono- or instead dual-host tropism, the location of virus retention or replication on or in the host-body, the presence of cyclical or mechanical transmission by arthropods, and of horizontal and vertical host-to-host transmission modes. It is shown that in the arthropod and in the vertebrate animal host, virus circulation in the hemocoel or blood circulation goes hand-in-hand with vertical transmission. Instead, plant phloem viruses do not transmit via seed. The latter is the rule for the plant-only viruses. The risk management implications are discussed in brief.

The use of nanomaterials has been increasing in recent times, and they are widely used in industries such as cosmetics, drug, food, water treatment and agriculture. The rapid development of new nanomaterials demands a set of approaches to evaluate the potential toxicity and risks related to them. In this regard, nanosafety has been using and adapting already existing methods (toxicological approach), but the unique characteristics of nanomaterials demand new approaches (nanotoxicology) to fully understand the potential toxicity, immunotoxicity and (epi)genotoxicity. Also, new technologies, such as organ-on-chip and sophisticated sensors, are under development and/or adaptation. All the information generated is used to develop new in silico approaches trying to predict the potential effects of newly developed materials. The overall evaluation of how from the production to final disposition chain of nanomaterials is evaluated under Life Cycle Assessment (LCA), which is becoming an important element of nanosafety considering sustainability and environmental impact. In this review we give an overview of all these elements of nanosafety.

Current cellular facts allow us to follow the link from chemical to biochemical metabolites, from the ancient to the modern world. In this context, the "RNA world" hypothesis proposes that early in the evolution of life, the ribozyme was responsible for the storage and transfer of genetic information and for the catalysis of biochemical reactions. Accordingly, the hammerhead ribozyme (HHR) and the hairpin ribozyme, belong to a family of endonucleolytic RNAs performing self-cleavage that might occur during replication. Furthermore, regarding the ultraconserved occurrence of HHR in several genomes of modern organisms (from mammals to small parasites and elsewhere), these small ribozymes have been regarded as living fossils of a primitive RNA world. They fold into 3D structures that generally require long-range intramolecular interactions to adopt the catalytically active conformation under specific physicochemical conditions. By studying viroids as plausible remains of ancient RNA, we recently demonstrated that they replicate in non-specific hosts, emphasizing their adaptability to different environments, which enhanced their survival probability over the ages. All these results exemplify ubiquitously features of life. Those are the versatility and efficiency of small RNAs, viroids and ribozymes, as well as their diversity and adaptability to various extreme conditions. All these traits must have originated in early life to generate novel RNA populations.

A revitalized practice of natural philosophy can help people to live a better life and promote a flourishing ecosystem. Such a philosophy is natural in two senses. First, it is natural by seeking to understand the whole of nature, including mental phenomena, In particular, a comprehensive natural philosophy should address the phenomena of sentience by embracing first- and second-person methods of investigation. Moreover, to expand our understanding of the world, natural philosophy should embrace a full panoply of explanations, similar to Aristotle’s four causes. Second, such a philosophy is natural by being grounded in human nature, taking full account of human capacities and limitations. Future natural philosophers should also make use of all human capacities, including emotion and intuition as well as reason and perception, to investigate nature. Finally, since the majority of our brain's activities are unconscious, natural philosophy should explore the unconscious mind with the aim of deepening our relation to the rest of nature and enhancing well-being.

Health information and communication are key elements that allow patients and family members to make decisions about end-of-life process and guarantee a death with dignity. Objective: To understand carers’ experiences regarding health information and communication during the illness and death of family members. Methods: This qualitative study was conducted in Andalusia based on the paradigm of hermeneutic phenomenology. Participants were carers who had accompanied a family member at the end of life for over 2 months and less than 2 years. Five nominal groups and 5 discussion groups were established, and 41 in-depth interviews with 123 participants were conducted. Atlas.ti 7.0 software was used to analyse the discourses. Results: Four dimensions of the dying process emerged: differences in carers’ perceptions of information and communication, a conspiracy of silence, consequences of the absence or presence of information, and the need for a culture change. Conclusions: Poor management of health information and communication at the end of life suffering and discomfort patients and their families. The culture of denying and avoiding death is still present today. A change in education about death would better enable health professionals to care for patients at the end of life.

Using hierarchical regression analysis within a mediation model framework, the present study explores direct and indirect (through life satisfaction) causal impacts of commuting stress on turnover intention of employees from 29 business organizations in six populous cities of Turkey. A semi-random heterogeneous sample of 214 employees with different demographics was surveyed in winter and summer times for also capturing seasonal variations of variables. The results supporting the partial mediating role of life satisfaction in the positive relationship between commuting stress and turnover intention infer that commuting stress induces turnover intention directly and indirectly (by reducing life satisfaction). The analysis of variance reveals that demographic characteristics of employees such as gender, marital status, age, and family size together with commuting type and commuting duration matter for their perceived commuting stress, life satisfaction, and turnover intention levels. Commuting stress perception is relatively higher in summer time whereas the other magnitudes are consistently and significantly invariant between two survey implementations. The study concludes with a call for the consideration of commuting stress and life satisfaction together with environmental and demographic factors when analyzing the antecedents and consequences of employee turnover intention.

Background: Improving patients’ quality of life (QoL) is a principal objective of all treatment in any clinical setting, including oncology practice. Cancer-associated inflammation is implicated in disease progression and worsening of patients’ QoL. Conventional anticancer therapeutics while selectively eliminating cancerous cells, are evaded by stem cell-like cells, and associated with varying degrees of adverse effects, thus reducing patients’ QoL. This necessitates novel therapeutic approaches with enhanced efficacy, minimal or no treatment-related adverse effects, and improved QoL in patients with cancer, especially those with metastatic/advance stage disease. Methods: Sequel to our team’s previous publication, the present study explores probable effects of Astragalus polysaccharides (PG2) on cancer-related inflammatory landscape and known determinants of QoL, as well as the probable link between the two to provide mechanistic insight. In exploratory double blind randomized controlled trial using patients with metastatic disease (n=23), we comparatively evaluated the therapeutic efficacy of high (500mg) or low (250mg) dose PG2 administered intravenously (i.v.), with particular focus on its suggested anti-inflammatory function and the probable effect of same on QoL indices at baseline, then at weeks 4 and 8 post-PG2 treatment. Results: All 23 patients with metastatic disease treated with either low or high PG2 experienced reduced pain, nausea, vomiting and fatigue, as well as better appetite and sleep, culminating in improved global QoL. This was most apparent in the high dose group, with significant co-suppression of pro-inflammatory interleukin (IL)-1β, IL-4, IL-6, IL-13, IL-17, monocytes chemotactic protein (MCP)1, granulocyte-macrophage colony-stimulating factor (GM-CSF), vascular endothelial growth factor (VEGF), tumor growth factor (TGF)-β1, interferon (IFN)-γ, and immune suppressors IL-10, and IL-12. Univariate and multivariate analyses revealed that IL-1β, IL-13 and GM-CSF are independent prognosticators of improved QoL. Conclusion: This proof-of-concept study provides premier evidence of functional association between PG2 anti-inflammatory effects and improved QoL in patients with advanced stage cancers, laying the groundwork for future larger cohort blinded controlled trials to establish the efficacy of PG2 as adjuvant anticancer therapy in metastatic or advanced stage clinical settings.

This study aims to investigate the changes in the structural relationship between alienation in physical education (PE) class, school happiness, and future healthy life expectancy in Korean adolescents after the COVID-19 pandemic. The data were collected from adolescents in the Republic of Korea using scales for these factors. The collected data were analyzed with frequency analysis, reliability analysis, validity analysis, independent t-test, and path analysis. The key results were as follows. First, there were partial changes in each of the parameters since the outbreak of COVID-19. Second, before the pandemic, alienation in PE class negatively affected school happiness, and school happiness positively affected future healthy life expectancy; however, alienation in PE class did not affect future healthy life expectancy showing a complete mediating effect. Third, during the pandemic, alienation in PE class negatively affected school happiness, and school happiness positively affected future healthy life expectancy; alienation in PE class negatively affected future healthy life expectancy, showing a partial mediating effect. These findings emphasize the importance and potential of school education, especially PE, in promoting happiness and healthy life in adolescents. We expect these findings to have practical implications for future research by presenting theoretical and empirical data.