The recurrent coronavirus outbreaks in China (SARS-CoV and its relative, SARS-CoV-2) have raised speculations that perhaps Asians are somehow more susceptible to these coronaviruses. Here, we test this possibility based on an analysis of the lung-specific expression of ACE2, which encodes the known cell-entry receptor of both SARS-CoV and SARS-CoV-2. We show that ACE2 expression is not affected during tumorigenesis, supporting that the abundant transcriptomes in cancer genomic studies can be informatively used to study ACE2 expression among diverse individuals without cancer. We find that ACE2 expression in the lung increases with age, but is not associated with sex. Further, Asians do not differ from other populations for ACE2 expression and do not harbor unique genetic polymorphisms in the ACE2 locus. Thus, beyond illustrating an innovative method for assessing the potential impacts of demographic factors for non-cancer diseases from large-scale cancer sample datasets, our statistically robust findings emphasize that individuals of all races require the same level of personal protection against SARS-CoV-2.

Understanding how the coronaviruses invade our body is an essential point, and the expression profile of coronaviruses receptor may help us to find where the coronavirus infects our body. We found that the coronavirus receptors, including angiotensin-converting enzyme 2 (ACE2) for SARS-CoV and SARS-Cov-2, are digestion-related enzymes in human enterocytes. Coronaviruses are continually altering the binding receptor and binding modes during their evolution, but the potential target cell in the small intestine is constant when in the lung is inconstant. Enterocytes may act as a conserved cell reservoir for coronaviruses, which may be partially explained by the Red Queen hypothesis. We also found that coronaviruses receptors could be elevated in the presence of both invasive bacteria and their counterpart, probiotics. We demonstrated here that enterocytes act as a conserved cell reservoir for coronaviruses during their evolutions, which should not be ignored in the investigation of coronavirus diagnosis and treatment strategies.

Background: In the current era of globalization, the Indonesian government's problem today is the weakening of nationalism and patriotism among the millennial generation. The large number of foreign cultures that have entered Indonesia has caused a sense of nationalism and patriotism. In addition, Indonesia is also facing the problem of spreading the Covid-19 virus. During the pandemic, various policies set by the government received protests from some circles because they felt their freedom was restricted. Therefore, the awareness of millennial generation nationalism is needed, especially during the Covid-19 pandemic like today. This research aims to make millennials aware of nationalism sense, which mainly to prevent the spread of Covid-19. This research is used to answer the questions of what the problems that arise due to the waning of the spirit of nationalism during the pandemic are? and what efforts should be made to maintain the spirit of nationalism? Methods: This research is a qualitative study using the literature review method. The articles used are research published in 2019 to 2021 in Google Scholar, with keywords that match the topic of millennial generation nationalism in the Covid-19 pandemic. Results and Discussion: The results of the study found that the spirit of Indonesian nationalism during the Covid-19 pandemic was decreasing. The decline in the sense of nationalism is due to several government policies that impact the psychology of society and the Indonesian economy. As a result, society, particularly the millennial generation, must play a role in breaking the chain of the Covid-19 virus's propagation by following the government's health standards. Conclusion: The government and society need to work together to understand nationalism in the millennial generation, especially in dealing with problems caused by the Covid-19 pandemic. Based on this, various efforts need to be made to foster the spirit of nationalism and overcome the Covid-19 pandemic. So that later, it can produce a generation that upholds the value of nationalism in everyday life.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known to cause 2019-coronavirus disease (COVID-19) pandemic is a zoonotic coronavirus and crosses species to infect human populations, where an efficient transmission of virus occurs human-to-human. Nationwide lockdown is being adopted to stop public transport, keep people at their homes and out of their work, and maintain social distancing. In turn, large geographic areas in the world (including China, Italy, Spain, and USA) has been almost halted. This temporary halt is significantly slashing down the air pollution (air pollutants and warming gases) in most cities across the world. This paper: (i) introduces both COVID-19 and air pollution; (ii) overviews the relation of air pollution with respiratory/lung diseases; (iii) compiles and highlights major data appeared in media and journals reporting lowering of air pollution in major cities those have been highly impacted by the COVID-19; and also (iv) lists the way forward in the present context. Because COVID-19 is an ongoing pandemic and currently far from over, strong conclusions could not be drawn with very limited data at present. The temporary slashed down global air pollution as a result of COVID-19 restrictions are expected to stimulate the researchers, policy makers and governments for the judicious use of resources; thereby minimise the global emissions, and maintain their economies once the pandemic eases. On the other, lifting of the nationwide lockdown and eventual normalisation of the temporarily halted sectors may also reverse the currently COVID-19 pandemic-led significantly slashed down global air pollution that could make the future respiratory health crisis grimmer.

Background: COVID-19 pandemic has pulled us all a few steps back, were we never shake hands or hug each other when we meet our friends and family after a gap, but instead we greet them by saying Namaste and joining our hands together. As we all know, COVID-19 spreads through air and the only way to shield ourselves is by maintaining a safe distance from one another. Methodology: In order to conduct a meta-analysis on the number of COVID-19 cases in Kerala and India, the data was retrieved from various sites hosted by the government bodies. The data for analysis was collected from May 2020 to July 2020. The average number of days required to reach every 5000 fresh cases were also calculated using this data. COVID-19 has affected all the economy holistically regardless of financial, behavioral, or societal aspects. Conclusion: Lifting of the lockdown in a step by step process keeping in mind the necessities for the nation was a thoughtful act, but the people who mistook this opportunity and did not remain in quarantine after coming from abroad was recognized as the reasons behind the sudden and uncontrolled rise in the number of COVID-19 cases in Kerala, India. The government authorities had no other option but to lift the restrictions to reduce the economic burdens that had already affected the daily wage worker and farmers prompting them to give up their lives.

Background: Covid-19 was first reported in Wuhan, China in Dec 2019. Since then, it has been transmitted rapidly in China and the rest of the world. While Covid-19 transmission rate has been declining in China, it is increasing exponentially in Europe and America. Although there are numerous studies examining Covid-19 infection, including an archived paper looking into the meteorological effect, the role of outdoor air pollution has yet to be explored rigorously. It has been shown that air pollution will weaken the immune system, and increase the rate of respiratory virus infection. We postulate that outdoor air pollution concentrations will have a negative effect on Covid-19 infections in China, whilst lockdowns, characterized by strong social distancing and home isolation measures, will help to moderate such negative effect. Methods: We will collect the number of daily confirmed Covid-19 cases in 31 provincial capital cities in China during the period of 1 Dec 2019 to 20 Mar 2020 (from a popular Chinese online platform which aggregates all cases reported by the Chinese national/provincial health authorities). We will also collect daily air pollution and meteorology data at the city-level (from the Chinese National Environmental Monitoring Center and the US National Climatic Data Center), daily inter-city migration flows and intra-city movements (from Baidu). City-level demographics including age distribution and gender, education, and median household income can be obtained from the statistical yearbooks. City-level co-morbidity indicators including rates of chronic disease and co-infection can be obtained from related research articles. A regression model is developed to model the relationship between the infection rate of Covid-19 (number of confirmed cases/population at the city level) and outdoor air pollution at the city level, after taking into account confounding factors such as meteorology, inter- and intra-city movements, demographics, and co-morbidity and co-infection rates. In particular, we shall study how air pollution affects infection rates across different cities, including Wuhan. Our model will also study air pollution would affect infection rates in Wuhan before and after the lockdown. Expected findings: We expect there be a correlation between Covid-19 infection rate and outdoor air pollution. We also expect that reduced intra-city movement after the lockdowns in Wuhan and the rest of China will play an important role in reducing the infection rate. Interpretation: Infection rate is growing exponentially in major cities worldwide. We expect Covid-19 infection rate is related to the air pollution concentration, and is strongly dependent on inter- and intra-city movements. To reduce the infection rate, the international community may deploy effective air pollution reduction plans and social distancing policies.

A concise proof of the Riemann Hypothesis is presented by clarifying the Hadamard product expansion over the zeta zeros, demonstrating that the Riemann Hypothesis is true.

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

Origins of the time, mass, electric charges and magnetic monopoles are explained. The energies, electric charges and magnetic charges of the particles are defined as E = cDtDV and |q| = cDt = E/DV, and |q_m| = c²Dt, respectively, for the 3-D quantized spaces warped along the time axis direction of ct in the 4-D Euclidean space. The energy (or mass) and charges (or electric charges and magnetic charges) are the vectors along the time axis of ct in the 4-D Euclidean space. This new concept is closely connected to the wave function of the quantum mechanics. The electric charges, magnetic charges and energies have the property of the space direction independence. Magnetic monopoles (charges) are the force carrying bosons with the inside electric field time loop. Electric monopoles are the elementary fermions. Photon space fluctuations are explained with the quantized magnetic charges.

Three-dimensional quantized space model is newly introduced. Quantum mechanics and relativity theory are explained in terms of the warped three-dimensional quantized spaces with the quantum time width (Dt=t_q). The energy is newly defined as the 4-dimensional space-time volume of E = cDtDV in the present work. It is shown that the wave function of the quantum mechanics is closely related to the warped quantized space shape with the space time-volume. The quantum entanglement and quantum wave function collapse are explained additionally. The special relativity theory is separated into the energy transition associated with the space-time shape transition of the matter and the momentum transition associated with the space-time location transition. Then, the quantum mechanics and the general relativity theory are about the 4-dimensional space-time volume and the 4-dimensional space-time distance, respectively.

Currently available data are consistent with increased severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replication at temperatures encountered in the upper airways (25–33°C when breathing room temperature air, 25°C) compared to those in the lower airways (37°C). One factor that may contribute to more rapid viral growth in the upper airways is the exponential increase in SARS-CoV-2 stability that occurs with reductions in temperature, as measured in vitro. Because SARS-CoV-2 frequently initiates infection in the upper airways before spreading through the body, increased upper airway viral growth early in the disease course may result in more rapid progression of disease and potentially contribute to more severe outcomes. Similarly, higher SARS-CoV-2 viral titer in the upper airways likely supports more efficient transmission. Conversely, the possible significance of air temperature to upper airway viral growth suggests that prolonged delivery of heated air might represent a preventative measure and prophylactic treatment for coronavirus disease 2019.

This research paper aims to explicate the complex issue of the Riemann's Hypothesis and ultimately presents its elementary proof. The method implements one of the binomial coefficients, to demonstrate the maximal prime gaps bound. Maximal prime gaps bound constitutes a comprehensive improvement over the Bertrand's result, and becomes one of the key elements of the theory. Subsequently, implementing the theory of the primorial function and its error bounds, an improved version of the Gauss' offset logarithmic integral is developed. This integral serves as a Supremum bound of the prime counting function Pi(n). Due to its very high precision, it permits to verify the relationship between the prime counting function Pi(n) and the offset logarithmic integral of Carl Gauss. The collective mathematical theory, via the Niels F. Helge von Koch equation, enables to prove the RIemann's Hypothesis conclusively.

In this paper, we tackle air quality forecasting by using machine learning approaches to predict the hourly concentration of air pollutants (e.g., Ozone, PM_2.5 and Sulfur Dioxide). Machine learning, as one of the most popular techniques, is able to efficiently train a model on big data by using large-scale optimization algorithms. Although there exists some works applying machine learning to air quality prediction, most of the prior studies are restricted to small scale data and simply train standard regression models (linear or non-linear) to predict the hourly air pollution concentration. In this work, we propose refined models to predict the hourly air pollution concentration based on meteorological data of previous days by formulating the prediction of 24 hours as a multi-task learning problem. It enables us to select a good model with different regularization techniques. We propose a useful regularization by enforcing the prediction models of consecutive hours to be close to each other, and compare with several typical regularizations for multi-task learning including standard Frobenius norm regularization, nuclear norm regularization, ℓ_2,1 norm regularization. Our experiments show the proposed formulations and regularization achieve better performance than existing standard regression models and existing regularizations.

The worldwide spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has ubiquitously impacted many aspects of life. As vaccines continue to be manufactured and administered, limiting the spread of SARS-CoV-2 will rely more heavily on the early identification of contagious individuals occupying reopened and increasingly populated indoor environments. In this study, we investigated the utility of an impaction-based aerosol sampling system with multiple nucleic acid collection media. Heat-inactivated SARS-CoV-2 was utilized to perform bench-scale, short-range aerosol, and room-scale aerosol experiments. Through bench-scale experiments, AerosolSense Capture Media (ACM) and nylon flocked swabs were identified as the highest utility media. In room-scale aerosol experiments, consistent detection of aerosol SARS-CoV-2 was achieved at a concentration equal to or greater than 0.089 genome copies per liter of room air (gc/L) when air was sampled for eight hours or more at less than one air change per hour (ACH). Shorter sampling periods (~75 minutes) yielded consistent detection at ~31.8 gc/L of room air and intermittent detection down to ~0.318 gc/L at (1 and 6+ ACH respectively). These results support further exploration in real-world testing scenarios and suggest the utility of indoor aerosol surveillance as an effective risk mitigation strategy in occupied buildings.

The evolution of integrable classical systems leads to conserved quantities and vanishing Poisson brackets. In contrast, such invariants do not exist in the dynamics of non-integrable systems, which include (but are not limited to) deterministic models with long-term chaotic behavior. The object of this review is to briefly survey the mathematical background of nonintegrability and its role in the physics unfolding well-above the Standard Model (SM) scale.

Deep learning (DL) algorithms have recently emerged from machine learning and soft computing techniques. Since then, several deep learning (DL) algorithms have been recently introduced to scientific communities and are applied in various application domains. Today the usage of DL has become essential due to their intelligence, efficient learning, accuracy and robustness in model building. However, in the scientific literature, a comprehensive list of DL algorithms has not been introduced yet. This paper provides a list of the most popular DL algorithms, along with their applications domains.

The Affordable Care Act (ACA) is at the crossroads. It is important to evaluate the effectiveness of the ACA in order to make rational decisions about the ongoing healthcare reform, but existing research into its effect on health insurance status in the United States is insufficient and descriptive. Using data from the National Health Interview Surveys from 2009 to 2015, this study examines changes in health insurance status and its determinants before the ACA in 2009, during its partial implementation in 2010–2013, and after its full implementation in 2014 and 2015. The results of trend analysis indicate a significant increase in national health insurance rate from 82.2% in 2009 to 89.4% in 2015. Logistic regression analyses confirm the similar impact of age, gender, race, marital status, nativity, citizenship, education, and poverty on health insurance status before and after the ACA. Despite similar effects across years, controlling for other variables, youth aged 26 or below, the foreign-born, Asians, and other races had a greater probability of gaining health insurance after the ACA than before the ACA; however, the odds of obtaining health insurance for Hispanics and the impoverished rose slightly during the partial implementation of the ACA but somewhat declined after the full implementation of the ACA starting in 2014. These findings should be taken into account by the U.S. government in deciding the fate of the ACA.

Social distancing policies put in place during COVID-19 epidemic in addition to helping to limit the spread of the disease also contributed to improving urban air quality. Here we show a decrease in air pollutant concentration as a consequence of mobility reduction in São Paulo during the containment measure which began on 22^nd March 2020. When comparing to foregoing weeks to equivalent periods of 2019, the concentration of most air pollutants sharply decreased in the first days of mobility restriction, to then increase again after government officials downplayed the threat of the disease. This trend is also followed by a decrease in hospital admissions by SARS-influenza. Therefore, despite the great economic and social unrest caused by the pandemic, this unique situation shows that large-scale mobility reduction policy had a significant impact on air quality, benefiting, directly and indirectly, the public health system.

This paper investigates the influence of magnetic field for a two dimensional deformations on a two temperature problem at the free surface of a semi-infinite semiconducting medium under the effect of mechanical force during a photothermal theory and the effect of hydrostatic initial stress on the medium. The Harmonic Wave Method (Normal Mode Analysis) has been used to obtain the equations of elastic waves, heat conduction equation, quasi-static electric field, carrier density, two temperature coefficient, ratios, and constitutive relationships for the thermo-magnetic-electric medium. The effects of several parameters as thermoelastic and thermoelectric coupling parameters and two temperature parameter of this force on the displacement component, force stress, carrier density and temperature distribution has been depicted graphically.

Neurofibromatosis type1 (NF1) is an autosomal dominant disorder caused by mutations in the NF1gene. Although congenital pseudarthrosis of the tibia (CPT) has frequently been associated with NF1, the underlying molecular mechanism of CPT in these NF1 patients is yet ill-understood. The aim of the present study was to detect NF1 mutations from genomic DNA and to harbor variants associated with CPT in NF1 patients. Whole-exome sequencing was first carried out with samples from two patients with CPT in one NF1 family, and a novel mutation c.2324A>G (p.E775G) in NF1 gene was identified. Additionally, a missense variant c.455C>T (p.P152L) in BCOR gene completely co-segregated with the CPT phenotype within this family. Subsequently, NF1 and NF2 genes in four other unrelated patients with both NF1 and CPT were screened using targeted sequencing. Four mutations in NF1 gene, including two known mutations (c.2288T>C/p.L763P, c.574 C>T/p.R192*) and two novel mutations (c.768delT/p.F256Lfs*25, c.2229_2230delTG/ p.V744Qfs*23) were detected. Further study confirmed that CPT was present in NF1 families, and NF1 mutations were closely associated with these complex phenotypes. Moreover, the data from the current study indicated that male gender might be a susceptibility factor for CPT in NF1. Therefore, we speculated that BCOR variants might be related to CPT phenotype among male NF1 patients.

In this paper, quasi-static axial compression tests are performed on the nodal Moso bamboos to study the size effect on energy absorption of the bamboos and the damage pattern of the multiple bamboo columns. Experimental results show that under the same moisture content, growth age and growing environment, the specific energy absorption (SEA) of the test samples increases with the increase of the out-diameter and thickness of the bamboo columns, indicating that size effect exists for energy absorption of the Moso Bamboos. For the multiple bamboo columns, there are mainly three failure modes for the constituent single bamboo columns: splitting above the node, splitting below the node and splitting through the node. Also, the tensile tests are conducted on three kinds of dog-bone shaped bamboo samples to investigate the macroscopic tensile fracture mode in the longitudinal direction of Moso bamboos. Results show that there is no direct relationship between the fracture pattern and moisture content of the bamboos, as well as the growth age of the bamboos. However, the tensile loading rate and the shape of the dog-bone shaped bamboo sample could affect the macroscopic fracture pattern of the bamboos in some cases.

Artificial Intelligence (AI) play an important role in many fields, including medical education, practice, and research. Many medical educators started using ChatGPT at the end of 2022 for many purposes. The aim of this article was to explore the potential uses, benefits and risks of using ChatGPT in integrated pharmacotherapy of infectious disease module education. This study was an experimental study with content analysis of the potential applications of the ChatGPT model for integrated pharmacotherapy of infectious diseases module education was performed. The findings of this study shows that there are many potential uses, benefits and risks associated with the use ChatGPT. In conclusion, medical and health sciences educators can use ChatGPT as a guide in many aspects related to the integrated pharmacotherapy of infectious disease curriculum development, syllabus design, lecture notes preparation and exam preparation with caution.

The concept of economic self-reliance, widely known by Thai people as the philosophy of sufficiency economy, has been widely promoted in rural Thai societies. By practicing this philosophy, it is expected that the citizens’ quality of life and local environments could be sustainably improved. This study aims to explore the contribution of the community practices of the sufficiency economy philosophy to rural villagers’ quality of life improvement, and to investigate potential factors that determine the trust of villagers in the philosophy. With the purpose to propose strategies which could enhance trust and promote villagers’ practices of the philosophy, the study investigated influences of three relevant factors on trust towards the philosophy. Those factors included factors related to cognitive-based trust, factors related to emotional-based trust, and factors related to demographic characteristics. Questionnaire surveys and in-depth interviews with community leaders and local villagers were conducted in the Ban Jamrung community, in Thailand’s Rayong province. The results of the statistical analysis revealed that the residents who applied the sufficiency economy philosophy in their daily lives experienced a relatively better quality of life. Additionally, it was found that trust in the philosophy could be predicted more by rational factors than by emotional factors. These findings could be utilized to develop strategies to maintain and enhance the trust of the people in the philosophy of sufficiency economy.

Despite the use of commercial forest carbon protocols (CFCPs) for more than two decades, claiming ~566 MMtCO₂e and a market value of ~USD $15.7 billion, comparative analysis of CFCP methodology and offset results is limited. In this study, five widely used biometric-based CFCPs are characterized, and common characteristics and differences are identified. CFCP claims of net forest carbon sequestration are compared with results of directly measured CO₂ by eddy covariance, a meteorological method integrating gross vertical fluxes of forest and soil carbon, and the only alternative non-biometric source of net forest carbon sequestration data available. We show here that CFCPs share a structural feature delimiting forest carbon values by zero-threshold carbon accounting (gC m^-2 ≤ 0), a pattern opposite to natural emissions of forest CO₂ exchange based on direct measurement and a fundamental biological constraint on net forest carbon storage (i.e., soil efflux, ecosystem respiration). Exclusion of forest CO₂ sources to the atmosphere precludes net carbon accounting, resulting in unavoidable over-crediting of CFCP project offsets. CFCP carbon results are significantly different from global forest CO₂ net ecosystem exchange population results (FluxNet2015 gC m^-2) at the 95% to 99.99% confidence levels, inferring an annual median error of ~247% (gC m^-2), consistent with over-crediting. Direct CO₂ measurement provides an urgently needed alternative method for commercial forest carbon products that has the potential to harmonize global markets and catalyze the role of forests in managing climate change through nature-based solutions.

Aluminum wire is a common material for wire bonding due to its resistance to oxidation and low price. It does not melt when becoming a free air ball (FAB) during the electronic flame-off (EFO) process with wettability, and is applied by wedge bonding. This study used 20μm Zn-Coated Al-0.5wt.%Si (ZAS) wires to improve the FAB shape after the EFO process, while maintaining stability of the mechanical properties, including the interface bonding strength and hardness. In order to test circuit stability after ball bonding, the current-tensile test was performed. During the experiment, it was found that 80nm ZAS with wire bonding has lower resistance and higher fusing current. For the bias tensile test, the thicker Zn film diffused into the Al-Si matrix easily, after which the strength was reduced. The ball-bond interfaces had no change in their condition before and after the bias. Accordingly, ZAS could be a promising candidate for ball bonding in the future.

Deformation of the surface of diamagnetic liquid by magnetic field is called the “Moses Effect”. Physics and applications of the direct and inverse Moses effects are reviewed. Experimental techniques enabling visualization of the effects are surveyed. Impact of magnetic field on micro- and macroscopic properties of liquids is addressed. Influence of the surface tension on the shape of the near-surface dip formed in a diamagnetic liquid by magnetic field is reported. Floating of diamagnetic bodies driven by the Moses effect is treated. The effect of the “magnetic memory of water” in its relation to the Moses Effect is discussed. The dynamics of self-healing of near-surface dips due to the Moses Effect is considered.

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

This paper proposes an innovative mechatronic piezo-actuated module to control vibrations in modern machine tools. Vibrations represent one of the main issues that compromise seriously the quality of the workpiece. The active vibration control (AVC) device is composed by a host part integrated with sensors and actuators synchronized by a regulator, able to make a self-assessment and adjust to the environmental alteration. This study presents the mechatronic model based on the kinematic and dynamic analysis of the AVC device. To ensure a real time performance, a H2-LQG controller has been developed and validated by simulations involving machine tool, PZT actuator and controller models. The Hardware-in-the-loop (HIL) architecture is adopted to control and attenuate the vibrations. A set of experimental tests has been performed to validate the AVC module on a commercial machine tool. The feasibility of the real time vibration damping is demonstrated and the simulation accuracy is evaluated.

The way people innovate and create new ideas and bring them to the market is undergoing a fundamental change from closed innovation to open innovation. Why and how do firms perform open innovation? Firms’ open innovation is measured through the levels of firms’ joint patent applications. Next, we analyze network structures and characters of firms’ joint patent applications such as betweenness and degree centrality, structure hole, and closure. From this research, we drew conclusions as follows. First, the structure of collaboration networks has both direct and indirect effects on firms’ innovative performance. Second, in the process of joint patent applications, there is a long tail phenomenon in networks of joint patent applications. Third, the number of patents and International Patent Classification (IPC) subclasses together constitute a meaningful measure of the innovation performance of firms.

The ambient air quality data for particulate matter as well as criteria of gaseous pollutants were assembled during December 2013 to December 2015 from the Continuous Air Quality Monitoring Station (CAMS) located at Agrabad, Chittagong. The observation showed that during April- October, 24 hour average concentration of PM10 and PM2.5 were within the National Ambient Air Quality Standard (NAAQS) level but it increased occasionally by more than two and a half times during the whole non-monsoon period (November-March). The highest values found of PM2.5 were 321.1 µg/m³ in January, 2013 and 220.34 µg/m³ in December 2015. Whether, the highest alarming concentration of PM10 was reported as 474 µg/m3 in January 2007. The other gaseous pollutants such as SO₂, NO₂, O₃, CO and Hydrocarbons remain well within the permissible limit except dry non-monsoon period. The yearly average increase of Air Quality Index (AQI) value indicates the growth rate of air pollution in Chittagong city. The main responsible pollutant for air pollution is found PM_2.5.

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

An adequate representation of the water infiltration process in the soil allows improving the efficiency in application and the uniformity in surface irrigation. The Green and Ampt model has shown a good representation of the process, and researchers from the United States Department of Agriculture (USDA) determined the values of their parameters for soils of that country, which are shown in tables or through functional relationships and this information is used as reference in several parts of the world, although there is no certainty that they are representative of the soils in Mexico. In this study, the parameters of the Green & Ampt equation were determined and evaluated in some soils of agricultural importance in Mexico. The parameters were obtained in four ways: one of them applied a methodology adapted from Brooks and Corey to quantify the wetting front capillary pressure head and used an permeameter under constant hydraulic head to determine the saturated hydraulic conductivity, and the other three consisted in taking them from three studies reported by the USDA. The values of the parameters suggested in Mexico drastically underestimated the results with relative errors (RE) in a range of -49.0 to -94.0% and the most representative were those obtained with the methodology proposed in this research with RE of -15.0 to 6.0%.

Since the first description of bisphosphonate-related osteonecrosis of the jaw (BRONJ) numerous research groups have focused on possible pathological mechanisms including the suppression of the bone turnover of the jaw, antiangiogenic effects and soft tissue toxicity. In our review we focused on summarizing the role of the soft tissues in the development and progression of BRONJ. The biological behavior of fibroblasts can be significantly influenced by bisphosphonates (BP) such as a concentration dependent reduction of cell viability. High concentrations of BP can induce apoptosis and necrosis of the cells. Comparable effects could be detected for keratinocytes. Compared to non-nitrogen containing bisphosphonates nitrogen-containing BP have worse effects on cell biology by blocking the mevalonate pathway. Next to this the cell architecture and the expression levels of several genes and proteins are significantly disturbed by BP. These inhibitory effects of BP are in accordance with BP related reduced angiogenesis and neovascularization and could underline the hypothesis that inhibition of fibroblasts and keratinocytes results in delayed wound healing and can induce and trigger BRONJ.

The measurement of discrimination in employment is a key variable in understanding dynamics in the nature of and change in ‘race relations’. Measuring such discrimination using ‘situation’ and ‘correspondence’ tests was influenced by John Rex’s sociological analyses, begun in in England in the 1960s, and replicated in Europe and America in later decades. This literature is reviewed, and the methodologies of testing for employment discrimination are discussed. Recent work in Britain and The Netherlands is considered in detail in the light of changing social structures, and the rise of Islamophobia. Manchester, apparently the city manifesting the most discrimination in Britain, is considered for a special case study, with a focus on one individual, a Muslim woman seeking intermediate level accountancy employment. Her vita was matched with that of a manifestly indigenous, white Briton. Submitted vitas (to 1,043 potential employers) indicated significant discrimination against the Muslim woman candidate. Results are discussed within the context of Manchester’s micro-sociology, and Muslim women’s employment progress in broader contexts, drawing on our work in Jordan and Palestine. We conclude with the critical realist comment that the “hidden racism” of employment discrimination shows that capitalist societies continue to be institutionally racist, and the failure to reward legitimate aspirations of minorities pushes ethnic minorities into a permanent precariat, with implications for social justice and social control, which denies minority efforts to “integrate” in society’s employment systems.

Carotid atherosclerotic lesions are a major cause of cerebrovascular disease (CVD). Identification and quantification of carotid plaques are important for categorizing the vulnerability of plaques for rupture and assessing the impact of treatments. The irregularity of plaque surface is associated with previous plaque rupture and plays an important role in the risk of stroke. Thus, the aim of this study is to develop and validate novel vulnerability biomarkers from three-dimensional ultrasound (3DUS) images by analyzing the surface morphological characterization of carotid plaque using fractal geometry features. 3D box-counting and 3D blanket are the two types of 3D fractal dimension that were employed to describe the smoothness of plaques. This fractal dimension analysis tool was used to evaluate the effect of atorvastatin using 3DUS carotid images, which were acquired from 6 patients treated with atorvastatin with 80 mg daily and 5 patients with placebo. The Student's T Test results showed that those two fractal features were effective for detecting the statin-related changes in carotid atherosclerosis with p<0.0068 and p<0.015 respectively, suggesting that 3D fractal dimension measurements can be used effectively to analyze the surface characteristics of carotid plaques, especially for evaluating the impact of the treatment.

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

Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. We develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1˚ over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.00 μg/m^3 and R2 = 0.72) and outperforms either AOD-retrieved PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-retrieved PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides all-spacetime-covered predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.75 μg/m3, while averaged count of polluted days (PM2.5 > 75 μg/m3) was 81, across China during 2014. Fused estimates will be publicly available for future health-related studies.

Urbanization is considered as a main indicator of regional economic development due to its positive effect on promoting industrial development; however, many regions, especially developing countries, are troubled by its negative effect — the aggravating environmental pollution. Many researchers have indicated that rapid urbanization stimulated the expansion of industrial production scale and increased industrial pollutant emissions. However, this judgement contains a grave deficiency in that urbanization not only expands industrial production scales but can also increase industrial labour productivity and change the industrial structure. To modify this deficiency, we first decompose the influence which urbanization impacts on industrial pollutant emissions into the scale effect, the intensive effect and the structure effect by using the Kaya Identity and the LMDI Method; second, we perform an empirical study of the three effects’ impacts by applying the spatial panel model with data from 282 Chinese cities between 2003 and 2013. Our results indicate that (1) there are significant reverse U-shapes between Chinese urbanization rate and its industrial pollutant emissions; (2) the scale effect and the structure effect have aggravated Chinese industrial waste water discharge, sulphur dioxide emissions and soot (dust) emissions, while the intensive effect has generated a decreasing and ameliorative impact on that aggravated trend. The definite relationship between urbanization and industrial pollutant emissions depends on the combined influence of the scale effect, the intensive effect and the structure effect; (3) there are significant spatial autocorrelations of industrial pollutant emissions between Chinese cities, but the spatial spillover effect from other cities does not aggravate local urban industrial pollutant emissions, we offer an explanation to this contradiction that the vast rural areas surrounding Chinese cities have served as sponge belts and have absorbed the spatial spillover of cities’ industrial pollutant emissions. According to the results, we argue that this type of decomposition of the influence into three effects is necessary and meaningful, it establishes a solid foundation for understanding the relationship between urbanization and industrial pollutant emissions, and effectively helps to meet relative policy making.

This review chronicles the indirect transmission method which seems to be overlooked by most people and makes attempts to clearly document the various transmission ways with a hope that such information may strengthen the knowledge base of researchers towards methods of eradicating the pandemic. Current knowledge of transmission and exposure of SARS-CoV-2 has been explained. Various researchers have put forward different ways of exposure and transmission. Literature does not reveal whether the indirect transmission route is the dominant one. However total lockdown could be a veritable means to reduce both direct and indirect transmission routes. In many countries where the indirect transmission has been reduced, the scourge of the virus is less. The work creates awareness on the need to watch out for those routes of transmissions that may not be popular and suggested key knowledge gaps that needs to filled.

This paper investigates the impact of price and real exchange rate volatility on Foreign Direct Investment (FDI) inflows in a panel of 10 Latin American and Caribbean countries, observed between 1990 and 2012. Both price and exchange rate volatility series are estimated through the Generalized Autoregressive Conditional Heteroscedasticity model (GARCH). Our results, obtained employing the Fixed Effects estimator, confirm the theory of hysteresis and option value, in so far it is found a statistically significant negative effect of exchange rate volatility on FDI. Price volatility, instead, turns out to be positive but insignificant. Moreover, we show that human capital and trade openness are key for attracting foreign capital. From the policy perspective, our analysis suggests the importance of stabilization policies as well as the one of government credibility in promoting trade openness and human capital formation.

The most significant assumptions in the subdomain technique (i.e., based on the formal resolution of Maxwell's equations applied in subdomain) is defined by: “The iron parts (i.e., the teeth and the back-iron) are considered to be infinitely permeable so that the saturation effect is neglected”. In this paper, the author presents a new scientific contribution on improving of this method in two-dimensional (2-D) and in Cartesian coordinates by focusing on the consideration of iron. The subdomains connection is carried out in the two directions (i.e., x- and y-edges). For example, the improvement was performed by solving magnetostatic Maxwell's equations for an air- or iron-cored coil supplied by a direct current. To evaluate the efficacy of the proposed technique, the magnetic flux density distributions have been compared with those obtained by the 2-D finite-element analysis (FEA). The semi-analytical results are in quite satisfying agreement with those obtained by the 2-D FEA, considering both amplitude and waveform.

Current problem facing researchers globally is microplastics as well as toxic chemical pollution of the ecosystem. Microplastics carry toxic chemicals in the ecosystem.serving as a vector for transport. In this study, a review of the literature has been conducted with the following objectives: (1) to summarise the concentrations of toxic chemicals such heavy metals and hydrophobic organic contaminants sorped on microplastics; (2) to evaluate their spatial distribution regarding adsorbed contaminant (3) to discuss plausible mechanism by which microplastics adsorp or desorp toxic chemicals in the environment; (4) to discuss implications of their occurrence in air, water and soil media; and (5) to discuss the impact of ingested microplastics to human health. Microplastics are ubiquitous environmental contaminant. Concentrations of sorped toxic chemical varied with location which represents a local problem; industrialized areas (especially areas experiencing crude oil related activities or have history of crude oil pollution) have higher concentrations than less industrialized areas. Ingestion of microplastics has been demonstrated in a range of marine and soil organisms as well as edible plants, thus possible contaminating the base of the food-web. Potential health effect to human is by particle localization, chemical toxicity and microbal toxins. We conclude by highlighting the gap in knowledge and suggesting key future areas of research for scientists and policymakers.

Determination of time-weighted average (TWA) concentrations of volatile organic compounds (VOCs) in air using solid-phase microextraction (SPME) is advantageous over other sampling techniques, but is often characterized by insufficient accuracies, particularly at longer sampling times. Experimental investigation of this issue and disclosing the origin of the problem is problematic and often not practically feasible due to high uncertainties. This research is aimed at developing the model of TWA extraction process and optimization of TWA air sampling by SPME using finite element analysis software (COMSOL Multiphysics). It was established that sampling by porous SPME coatings with high affinity to analytes is affected by slow diffusion of analytes inside the coating, an increase of analytes concentrations in the air near the fiber tip due to equilibration, and eventual lower sampling rate. The increase of a fiber retraction depth (Z) resulted in better recoveries. Sampling of studied VOCs using 23-ga Car/PDMS assembly at maximum possible Z (40 mm) was proven to provide more accurate results. Alternative sampling configuration based on 78.5 x 0.75 mm i.d. SPME liner was proven to provide similar accuracy at improved detection limits. Its modification with the decreased internal diameter from the sampling side should provide even better recoveries. The developed model offers new insight into optimization of air and gas sampling using SPME.

The development effect of water flooding in ultra-low permeability reservoir was poor due to its poor physical property and high shale content, the experimental study of air flooding which help to complement producing energy was carried out. Based on the Accelerating Rate Calorimeter experimental results, the crude oil of N block in L oilfield can produce low-temperature oxidation reaction, which was the basic condition of air flooding. Three groups of experiment natural cylinder core were designed for oil displacement, water flooding and air flooding were used respectively, and the relationship of differential pressure, oil recovery, injection capacity with injection volume was investigated. It has been showed on the result that the recovery efficiency improved sharply than water flooding, the effect of depressurization and augmented injection was obvious, and the air displacement was validation.

The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques.

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

The SARS-CoV-2 virus that causes the COVID-19 disease has wreaked havoc on the world community in terms of every imaginable parameter. The research output on COVID-19 has been nothing short of phenomenal, especially in the medical and biomedical sciences, where the search for a potential vaccine is being conducted in earnest. Much of the advanced research has been distributed in the leading medical journals, including the Journal of the American Medical Association (JAMA), where the latest research is distributed on a daily basis. The purpose of this paper is to provide some perspectives on 44 interesting and highly topical research papers that have been published in JAMA, at the time of writing, within the past two weeks. The diverse topics include public health, general medicine, internal medicine, oncology, paediatrics, geriatrics, and biostatistics.

Primate vision is an active process that constructs a stable internal representation of the 3D world based on 2D sensory inputs that are inherently unstable due to incessant eye movements. We present here a mathematical framework for processing visual information for a biologically-mediated active vision stereo system with asymmetric conformal cameras. This model utilizes the geometric analysis on the Riemann sphere developed in the group-theoretic framework of the conformal camera, thus far only applicable in modeling monocular vision. The asymmetric conformal camera model constructed here includes the fovea’s asymmetric displacement on the retina and the eye’s natural crystalline lens tilt and decentration, as observed in ophthalmological diagnostics. We extend the group-theoretic framework underlying the conformal camera to the stereo system with asymmetric conformal cameras. Our numerical simulation shows that the 1 theoretical horopter curves in this stereo system are conics that well approximate the empirical longitudinal horopters of the primate vision system.

Marine cold air outbreaks (MCAOs) are large-scale events in which cold air masses are advected over open ocean. It is well-known that these events are linked to the formation of polar lows and other mesoscale phenomena associated with high wind speeds, and that they therefore in some cases represent a hazard to maritime activities. However, it is still unknown whether MCAOs are generally conducive to higher wind speeds than normal. Here this is investigated by comparing ocean near-surface wind speeds during MCAOs in atmospheric reanalysis products with different horizontal grid spacings, along with two case studies using a convection-permitting numerical weather prediction model. The study regions are the Labrador Sea and the Greenland–Iceland–Norwegian (GIN) Seas, where MCAOs have been shown to be important for air–sea interaction and deep water formation. One of the main findings is that wind speeds during the strongest MCAO events are higher than normal and higher than wind speeds during less severe events. Limited evidence from the case studies suggests that reanalyses with grid spacings of more than 50 km underestimate winds driven by the large ocean–atmosphere energy fluxes during MCAOs. The peak times of MCAO usually occur when baroclinic waves pass over the regions. Therefore, the strong wind episodes during MCAOs generally last for just a few days. However, MCAOs can persist for 50 days or more.

The study of the concentrations and effects of fine particulate matter in urban areas have been of great interest to researchers in recent times. This is due to the acknowledgment of the far-reaching impacts of fine particulate matter on public health. Remote sensing data have been used to monitor the trend of concentrations of particulate matter by deriving aerosol optical depth (AOD) from satellite images. The Center for International Earth Science Information Network (CIESIN) has released the second version of its global PM_2.5 data with improvement in spatial resolution. This paper revisits the study of spatial and temporal variations in particulate matter in Saudi Arabia by exploring the cluster analysis of the new data. Cluster analysis of the PM_2.5 values of Saudi cities is performed by using Anselin local Moran’s I statistic. Also, the analysis is carried out at the regional level by using self-organizing map (SOM). The results show an increasing trend in the concentrations of particulate matter in Saudi Arabia, especially in some selected urban areas. The eastern and south-western parts of the Kingdom have significantly clustering high values. Some of the PM2.5 values have passed the threshold indicated by the World Health Organization (WHO) standard and targets posing health risks to Saudi urban population.

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

In the paper, the authors establish two identities to express the generating function of the Chebyshev polynomials of the second kind and its higher order derivatives in terms of the generating function and its derivatives each other, deduce an explicit formula and an identities for the Chebyshev polynomials of the second kind, derive the inverse of an integer, unit, and lower triangular matrix, present several identities of the Catalan numbers, and give some remarks on the closely related results including connections of the Catalan numbers respectively with the Chebyshev polynomials, the central Delannoy numbers, and the Fibonacci polynomials.

Air pollution has created a lot of problems in the developed and developing countries. To avoid or reduce these problems, constant monitoring of the air should be ensured. The conventional techniques is costly because it requires a lot of money and time consuming. Biomonitoring has been the alternative method. Moss, lichens and plants are biomonitors available to entrap air pollutants. The aim of this paper is to discuss one of the ways of monitoring air pollution – Moss bag technique. To do this, types, choice, preparation, handling of bags after preparation of moss were discussed. From the literatures consulted, it was discovered that there were differences in the techniques used by the researchers. In all, the use of mosses with emphasis on the employment of moss bag have proved to be a powerful tool in airborne particulate and toxic elements. To conclude, developing countries should focus more on this technique because it will reduce cost of air monitoring.

We consider the financial planning problem of a retiree wishing to enter a retirement village at a future uncertain date. The date of entry is determined by the retiree's utility and bequest maximisation problem within the context of uncertain future health states. In addition, the retiree must choose optimal consumption, investment, bequest and purchase of insurance products prior to her full annuitisation on entry to the retirement village. A hyperbolic absolute risk-aversion (HARA) utility function is used to allow necessary consumption for basic living and medical costs. The retirement village will typically require an initial deposit upon entry. This threshold wealth requirement leads to exercising the replication of an American put option at the uncertain stopping time. From our numerical results, active insurance and annuity markets are shown to be a critical aspect in retirement planning.

The main foundations of the standard $\Lambda $CDM model of cosmology are that: 1) The redshifts of the galaxies are due to the expansion of the Universe plus peculiar motions; 2) The cosmic microwave background radiation and its anisotropies derive from the high energy primordial Universe when matter and radiation became decoupled; 3) The abundance pattern of the light elements is explained in terms of primordial nucleosynthesis; and 4) The formation and evolution of galaxies can be explained only in terms of gravitation within a inflation+dark matter+dark energy scenario. Numerous tests have been carried out on these ideas and, although the standard model works pretty well in fitting many observations, there are also many data that present apparent caveats to be understood with it. In this paper, I offer a review of these tests and problems, as well as some examples of alternative models.

Traffic congestion is one of the foremost problems confronted by the urban and suburban tenants of today. Traffic congestion increases vehicle emissions and degrades air quality. Urban planners and policy makers have consequently been always investigating choices to alleviate traffic congestion and to enhance air quality. Teleworking is one option that has received significant consideration and has been studied in the recent past. The aim of the study is to explore the relationship between teleworking, air quality and traffic in Switzerland. The analysis relies on panel individual and household level data over the period 2002-2013. We examine five main air pollutants; the sulphur dioxide (SO₂), the ground-level ozone (O₃) the nitrogen dioxide (NO₂), the carbon monoxide (CO) and the particulate matter less than 10 microns (PM₁₀). Based on the fixed effects estimates, teleworking reduces traffic volume by 1.9 per cent. Furthermore, the reduction observed on air pollution is higher for NO₂, CO and PM₁₀ ranging between 3.3-3.7 per cent, followed by O₃ at 2.3 per cent and SO₂ at 2.1 per cent. According to instrumental variable (IV) approach and the two stage least squares (2SLS) method, the effect is higher ranging between 2.6-4.1 per cent. The respective reduction on traffic becomes 2.7 per cent. Overall, the main concluding remark of the study is that teleworking can be a promising tool for urban planning and development, focusing at the traffic volume reduction, and the air quality improvement. Additional policy implications of teleworking and its beneficial effects for the society are further discussed.

By using Modified simple equation method, we study the Cahn Allen equation which arises in many scientific applications such as mathematical biology, quantum mechanics and plasma physics. As a result, the existence of solitary wave solutions of the Cahn Allen equation is obtained. Exact explicit solutions interms of hyperbolic solutions of the associated Cahn Allen equation are characterized with some free parameters. Finally, the variety of structure and graphical representation make the dynamics of the equations visible and provides the mathematical foundation in mathematical biology, quantum mechanics and plasma physics.

Solar green roofs, namely rooftops functionalized with properly selected living vegetation and photovoltaic modules, achieve an ideal symbiotic relationship in which promotion of biodiversity and onsite renewable energy production are both enhanced whereas the roof provides a wide range of environmental, health, aesthetic and economic benefits. This study provides a unified outlook of this eminent sustainable technology at the dawn of its uptake across the world, especially in polluted urban areas.

The present study aimed to analyze novel mechanisms underlying Nrf2-mediated anti-apoptosis in periodontal ligament stem cells (PDLSCs) in the periodontitis oxidative microenvironment. We created an oxidative stress model with H2O2-treated PDLSCs. Herein, we used real-time PCR, western blotting, TUNEL staining, fluorogenic assay and transfer genetics to confirm the degree of oxidative stress and apoptosis as well as the Nrf2 function. Surprisingly, we demonstrated that with up-regulated ROS and MDA levels, the effect of oxidative stress was obvious under H2O2 treatment. Anti-oxidative molecules were changed after the H2O2 exposure, whereby the anti-oxidative signaling of Nrf2 was activated with the increase of its downstream effectors, HO-1, NQO1 and γ-GCS. Additionally, the apoptosis levels gradually increased with oxidative stress and changes in the caspase-9, caspase-3, Bax and c-Fos levels, but not with caspase-8 and down-regulated Bcl-2. The enhanced antioxidant effect could not resist the occurrence of apoptosis. Furthermore, Nrf2 overexpression effectively improved the anti-oxidative levels and increased cell proliferation. At the same time, overexpression effectively restrained TUNEL staining and decreased the molecular levels of caspase-9, caspase-3, et al, but not that of caspase-8. By contrast, silencing the expression Nrf2 levels had the opposite effect. Collectively, Nrf2 alleviates PDLSCs via its effects on anti-oxidative and anti-intrinsic apoptosis by the activation of anti-oxidative enzymes.

Let {$\Gamma(k)$} denote {$(k-1)!$}, and let {$\Gamma_{n}(k)$} denote {$(k-1)!$}, where {$n \in \{3,\ldots,16\}$} and {$k \in \{2\} \cup [2^{\textstyle 2^{n-3}}+1,\infty) \cap \mathbb N$}. For an integer {$n \in \{3,\ldots,16\}$}, let $\Sigma_n$ denote the following statement: if a system of equations {${\mathcal S} \subseteq \{\Gamma_{n}(x_i)=x_k:~i,k \in \{1,\ldots,n\}\} \cup \{x_i \cdot x_j=x_k:~i,j,k \in \{1,\ldots,n\}\}$} with $\Gamma$ instead of $\Gamma_{n}$ has only finitely many solutions in positive integers {$x_1,\ldots,x_n$}, then every tuple {$(x_1,\ldots,x_n) \in (\mathbb N \setminus \{0\})^n$} that solves the original system ${\mathcal S}$ satisfies {$x_1,\ldots,x_n \leqslant 2^{\textstyle 2^{n-2}}$}. Our hypothesis claims that the statements {$\Sigma_{3},\ldots,\Sigma_{16}$} are true. The statement {$\Sigma_6$} proves the following implication: if the equation {$x(x+1)=y!$} has only finitely many solutions in positive integers $x$ and $y$, then each such solution {$(x,y)$} belongs to the set {$\{(1,2),(2,3)\}$}. The statement {$\Sigma_6$} proves the following implication: if the equation {$x!+1=y^2$} has only finitely many solutions in positive integers $x$ and $y$, then each such solution {$(x,y)$} belongs to the set {$\{(4,5),(5,11),(7,71)\}$}. The statement {$\Sigma_9$} implies the infinitude of primes of the form {$n^2+1$}. The statement {$\Sigma_9$} implies that any prime of the form {$n!+1$} with {$n \geqslant 2^{\textstyle 2^{9-3}}$} proves the infinitude of primes of the form {$n!+1$}. The statement {$\Sigma_{14}$} implies the infinitude of twin primes. The statement {$\Sigma_{16}$} implies the infinitude of Sophie Germain primes.

Daily maximum surface air temperature (Tamax) is a crucial factor for understanding complex land surface processes under rapid climate change. Remote detection of Tamax has widely relied on the empirical relationship between air temperature and land surface temperature (LST), a product derived from remote sensing. However, little is known about how such a relationship is affected by the high heterogeneity in landscapes and dynamics in seasonality. This study aims to advance our understanding of the roles of land cover and seasonal variation in the estimation of Tamax using the MODIS (Moderate Resolution Imaging Spectroradiometer) LST product. We developed statistical models to link Tamax and LST in the middle and lower reaches of the Yangtze River in China for five major land-cover types (i.e., forest, shrub, water, impervious surface, cropland, and grassland) and two seasons (i.e., growing season and non-growing season). Results show that the performance of modeling the Tamax-LST relationship was highly dependent on land cover and seasonal variation. Estimating Tamax over grasslands and water bodies achieved superior performance; while uncertainties were high over forested lands that contained extensive heterogeneity in species types, plant structure, and topography. We further found that all the land-cover specific models developed for the plant non-growing season outperformed the corresponding models developed for the growing season. Discrepancies in model performance mainly occurred in the vegetated areas (forest, cropland, and shrub), suggesting an important role of plant phenology in defining the statistical relationship between Tamax and LST. For impervious surfaces, the challenge of capturing the high spatial heterogeneity in urban settings using the low-resolution MODIS data made Tamax estimation a difficult task, which was especially true in the growing season.

Current therapeutic strategies targeting cancer cells within solid tumors have displayed limited success owing to the presence of non-cancer components referred to as the tumor stroma within the tumor microenvironment (TM). These stromal cells, extracellular matrix and blood vessels influence cancer cell response to therapy and play key roles in tumor relapse and resistance. Of the stromal cells present in the TM, a lot of attention has been given to cancer-associated fibroblasts (CAFs) as they are the most abundant and are important in cancer initiation, progression and therapy resistance. In this updated review I emphasize the role of CAFs in the regulation of tumor cell behaviour and reveal how CAF-derived factors and signaling influence tumor cell heterogeneity and development of novel strategies to combat cancer. To investigate the expression of CAF markers in tumor tissues versus normal tissues, transcriptomic data from The Cancer Genome Atlas (TCGA) and the Gene Expression Profiling Interactive Analysis (GEPIA) databases was used. Bioinformatic analysis reveals differential expression of CAF markers in several cancer types, underscoring the need for further multiomics and biochemical studies on CAFs, CAF subsets and markers. Differences in CAF markers’ expression could be due to different cellular origins as well as the effect of cancer-specific tumor microenvironmental effect on CAFs. Lastly, I present recent advances in therapeutic targeting of CAFs and the success of such endeavours or its lack thereof. It is recommended that for patients’ outcomes to improve, cancer treatment be combinatorial in nature, targeting both cancer cells and stromal cells and interactions.

Implementation of the German Climate change Strategy in the Federal State of Saxony-Anhalt is discussed in this paper. It shares the requirement and importance of sustainable development. An overview of strategy, The DAS Indicator System is provided with results of a portion of work being done for the ministry of agriculture by Deutscher Wetterdienst (DWD). Applicability of the indicator system is also shown by evaluation of results for specific indicators from 1961-2015.

Microplastics (of size < 5mm) pollution in our environment is of current concern by researchers, public media and non-governmental organizations. Implications by their presence in aquatic and soil ecosystems have been well studied and documented, but less attention has been paid on airborne microplastics (MPs). Studies concerning airborne microplastics started from 2016 and only a few (n=7) have been published till date. Although, studies may increase in the following years, since air is very important for human survival. Microplastics have been observed in atmospheric fallouts in indoor and outdoor environments using a sampling or vacuum pump, rain sampler and/or particulate fallout collector. Identification and quantification have been carried out by visual, spectroscopic and spectrometric techniques. Factors such as meterological, climatic and anthropogenic influence the distribution and movement of airborne MP. Human exposure may be through inhalation or dermal route with their potential biopersistence and translocation. Ingestion may cause localized inflammation and cancer due to responses by the immune cells, especially in individuals with compromised metabolism and poor clearance mechanisms. Ecological risks involve possible contamination of the ecosystem through a dynamic relationship of MPs in soil, water and air forming a MP contamination cycle. The present review aimed at providing a comprehensive overview of current knowledge or information regarding microplastics in air, identifies gap in knowledge and give suggestions for future research.

This study inscribes itself in the global discussion on the nurturing of pro-environmental behaviors among young people for a sustainable future. Here we focus on students' interest in Ecosystem Services and Sustainability to explain their awareness and optimism about the environmental issues of air pollution, water shortage and green gas emission in 50 countries around the world. To this end, we use the cross-sectional survey data of the OECD's Program for International Student Assessment (PISA) 2015, along with seemingly unrelated bi-variate weighted ordered Probit modeling with country specific effects. The results show that in addition to factors such as age, gender, immigration status, and economic, social and cultural status, interest in the biosphere is a significant determinant of students' environmental awareness and optimism. In fact, a one level increase in students' interest in ecosystem services and sustainability raises on average their awareness level by 15.3% for the issue of air pollution, 15.7% for the issue of water shortage, and 24.6% for the issue of green gas emission. Although students' interest in the biosphere seems to not have a significant effect on their expectations about the issue of green gas emission, it does however raise their level of optimism by 0.8% for the issue of air pollution, and 0.2% for the issue of water shortage. Furthermore, every one level increase in students' environmental awareness leads to 17.3% more optimism about the issue of air pollution, 15.8% more optimism about the issue of water shortage, and 17.4% more optimism about the issue of green gas emission. Therefore, relying on the Theory of Planned Behavior (TPB), our results imply that governments and policy makers can successfully leverage young people interests in the biosphere to effectively achieve their goals for sustainability.

An important aspect of the new sustainable development goals (SDGs) is a greater emphasis on reducing the health impacts of urban ambient air pollution (AAP) in developing countries. Meanwhile, the burden of disease attributable to AAP in sub-Saharan Africa (SSA) is growing, yet estimates of its impact in the region are likely underestimated due to a lack of air quality monitoring, the paucity of epidemiological studies, and important population vulnerabilities in the region. The lack of studies in the SSA region also represents an important global health disparity and environmental justice issue because thousands of air pollution health effects studies have been conducted in Europe and North America rather than in some of the most polluted regions of the world, such as SSA. In this review, we synthesize all of the ambient air pollution epidemiological studies that have been conducted in SSA to date. We highlight the gaps in AAP epidemiological studies conducted in different sub-regions of SSA and provide methodological recommendations for future environmental epidemiology studies addressing AAP in the SSA region.

This paper deals with the environmental characterization of a large and densely populated area, with a poor reputation for contamination, considering the contribution of environmental features (air, soil, soil hydraulic and groundwater) and the potential effects on human health. The use of Geographic Information System (GIS) has made possible a georeferenced inventory and, by overlaying environmental information, an operational synthesis of comprehensive environmental conditions. The cumulative effects on environmental features were evaluated, taking into account superposition effects, by means of the spatial multicriteria decision analysis (S-MCDA). The application of the S-MCDA for converging the combination of heterogeneous factors, related to soil, land and water, deeply studied by heterogeneous groups of experts, constitutes the novelty of the paper. The results confirmed an overall higher potential of exposure to contaminants in the environment and higher mortality rates in the study area for some tumours, but hospital admissions for tumours were generally similar to the regional trend. Besides, mortality data may be strictly dependent on the poor socioeconomic conditions, quality of therapy and a lack of welfare in the area relative to the rest of Italy. Finally, as regards the possible relationship between presence of contaminants in the environment and health conditions of the population no definite conclusions can be drawn, although the present study encourages the use of the new proposed methods, that increase the possibilities for studying the combined effect of more environmental factors.

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

In the paper, by virtue of the Fa`a di Bruno formula, some properties of the Bell polynomials of the second kind, and the inversion formulas of binomial numbers and the Stirling numbers of the first and second kinds, the authors simplify meaningfully and significantly coefficients in two families of ordinary differential equations associated with higher order Frobenius–Euler numbers.

In this paper, a semi-empirical model of air waves induced by falling rock is described. The model is composed of a uniform motion phase (velocity close to 0 m·s^-1) and an acceleration movement phase. The uniform motion phase was determined based on experimentally and the acceleration movement phase was derived by theoretical analysis. A series of experiments were performed to verify the semi-empirical model and elucidated the law of the uniform motion phase. The acceleration movement phase accounted for a larger portion with a greater height of the falling rock. Experimental results of different falling heights of the goaf showed close agreement with theoretical analysis values. The semi-empirical model could accurately and conveniently estimate the velocity of air wave induced by falling rock. Thus, the semi-empirical model can provide a reference and basis for estimating the speed of air waves and designing protective measures in mines.

A case-crossover study examined how PM_2.5 from Asian Dust Storms (ADS) affects the number of emergency room (ER) admissions for cardiovascular diseases (CVDs) and respiratory diseases (RDs). Our data indicated that PM_2.5 concentration from ADS was highly correlated with ER visits for CVDs and RDs. The odds ratios (OR) increased by 2.92 (95% CI: 1.22-5.08) and 1.86 (95% CI: 1.30-2.91) per increase 10 µg/m³ in PM_2.5 levels, for CVDs and RDs, respectively. A 10 µg/m³ increase in PM_2.5 from ADSs was significantly associated with increase in ER visits for CVDs among those 65 years of age and older (an increase of 2.77 in OR) and for females (an increase of 3.09 in OR). In contrast, PM_2.5 levels had a significant impact on RD ER visits among those under 65 years of age (OR=1.77). The risk of ER visits for CVDs increased on the day when the ADS occurred in Taiwan and the day after (lag 0 and lag 1); the corresponding risk increase for RDs only increased on the fifth day after the ADS (lag 5). In Taiwan’s late winter and spring, the severity of ER visits for CVDs and RDs increases. Environmental protection agencies should employ an early warning system for ADS to reduce high-risk groups’ exposure to PM_2.5.

In this paper new upper limits on the parameters of the Continuous Spontaneous Localization (CSL) collapse model are extracted. To this end the X-ray emission data collected by the IGEX collaboration are analyzed and compared with the spectrum of the spontaneous photon emission process predicted by collapse models. This study allows to obtain the most stringent limits within a relevant range of the CSL model parameters, with respect to any other method. The collapse rate $\lambda$ and the correlation length $r_C$ are mapped, thus allowing to exclude a broad range of the parameter space.

In the paper, the authors present unified generalizations for the Bell numbers and polynomials, establish explicit formulas and inversion formulas for these generalizations in terms of the Stirling numbers of the first and second kinds with the help of the Faà di Bruno formula, properties of the Bell polynomials of the second kind, and the inversion theorem connected with the Stirling numbers of the first and second kinds, construct determinantal and product inequalities for these generalizations with aid of properties of the completely monotonic functions, and derive the logarithmic convexity for the sequence of these generalizations.

The Late Bronze Age on the territory of Southern Transurals is represented by two major archeological cultures: Srubnaya and Andronovskaya (Alakul culture and Fyodorovskaya – type). Their interaction of constitutes a special mix of material cultures which preserves common features of two independent, Srubnaya and Andronovskaya cultures, but also creates novel local material features. These cultural groups are also known to have brought to the region the technology of bronze production. This is evidenced, amongst others, by the proximity of the largest copper mining in the region, Kargaly mines Chernykh (2002). New methods to produce ceramics and to work bones were also developed, combining two traditions, coming from Srubnaya and Andronovskaya cultures respectively. Importantly, the features of these cultures are commonly encountered together in a single cultural horizon across the distribution ares. These diffusion processes took place in a vast area (more than 120,000 km²) andwere reflected in archeological micro-district of the Urshak river basin. We present here the most recent results of the scientific examination of the Late Bronze Age settlements in southern Transurals and attempt to address a peculiar cultural co-habitation of two distinct cultural groups in this region. We also discuss their synchronism based on absolute dates and elaborate on this cultural syncretism in the entire territory of the Volga-Ural region.

In the paper, by virtue of the Faà di Bruno formula, some properties of the Bell polynomials of the second kind, and an inversion formula for the Stirling numbers of the first and second kinds, the authors establish meaningfully and significantly two identities which simplify coefficients in a family of ordinary differential equations associated with higher order Bernoulli numbers of the second kind.

Purpose: This study aimed to focus on the design and development of low-cost DIY air purifiers, using a ventilating fan, air pump, water pump, and an ultrasonic generator, with regard to filtration efficacy and also cost-effectiveness that can be used during the COVID-19 pandemic and haze pollution. Methods: Six types of household air purifiers, incorporating a HEPA filter, a HEPA filter & electrostatic fiber, an air pump, an air pump & ultrasonic wave, a water pump, and a water pump & ultrasonic wave, were fabricated. The amount of particulate matter (PM) and CO₂ levels were recorded at 0, 10, 20, 30, and 60 min, then, repeated 3 times. After 10 min of the 3^rd experiment of each study, the last measurement of air pollution would be recorded. Results: At 60 min, the HEPA filter & electrostatic fiber showed the best performance regarding reduction of PM and CO₂ levels. The highest PM reduction rate had occurred at 30 min using an air pump procedure (99.330 to 100%). The CO₂ levels of all experiments had fluctuated at different times. After 10 min of a closed machine, HEPA filter & electrostatic fiber revealed the highest rate of PM elevation, while PM levels of all water-based purifier systems were decreased. A water pump and air pump were the cheapest air cleaners, when taking into account maintenance expenses and electricity charges. Conclusion: An air pump is the optimum method for reducing particulate matter at minimum cost but without the benefit of reduced humidity, while the HEPA filter & electrostatic fiber is the best system to decrease PM levels, but this requires an enclosed structure at the inlet to prevent dust coming back into the room. As filtration efficiency is increased by the use of filters & electrostatic fiber mechanisms, the more expensive the system becomes.

Collision avoidance is an important feature in advanced driver-assistance systems, aiming at providing correct, timely and reliable warnings before an imminent collision (objects, vehicles, pedestrians, etc.). A co-simulation framework is proposed in this paper to address the design and evaluation of collision avoidances in a cyber-physical system. The co-simulation framework is supported on the interaction between SCANeR and Matlab/Simulink. From the best of authors’ knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip LIDAR sensors in a cyber-physical system (CPS) considering traffic scenarios is presented. The CPS is designed and implemented in SCANeR. Secondly, an obstacle recognition library with three specific Artificial Intelligence-based methods is also designed based on sensory information database provided by SCANeR. Three methods for collision avoidance detection are considered, i.e.; a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods for detecting obstacles before different weather conditions is done with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and fog conditions, the support vector machine in rainy and self-organized map in snowy conditions.

The continuous energy transformation processes in heating, ventilation and air conditioning systems of buildings are responsible for 36% of global final energy consumption. Tighter thermal insulation requirements for buildings have significantly reduced heat transfer losses. Unfortunately, this has little effect on energy demand for ventilation. On the basis of the First and the Second Law of Thermodynamics, the concepts of entropy and exergy are applied to the analysis of ventilation air handling unit (AHU) with a heat pump in this paper. This study aims to develop a consistent approach for this purpose, taking into account the variations of reference temperature and temperatures of working fluids. An analytical investigation on entropy generation and exergy analysis are used, when exergy is determined by calculating coenthalpies and evaluating exergy flows and their directions. The results show that each component of the AHU has its individual character of generated entropy, destroyed exergy and exergy efficiency variation. However, the evaporator of heat pump and fans have unabated quantities of exergy destruction. The exergy efficiency of AHU decreases from 45-55% to 12-15% when outdoor air temperature is within the range of –30°C…+10°C, respectively. This helps to determine conditions and components of improving the exergy efficiency of the AHU at variable real-world local climate conditions. The presented methodological approach could be used in the dynamic modelling software and contribute to a wider application of the Second Law of Thermodynamics in practice.

Air corridors are an integral part of the advanced air mobility infrastructure. They are the virtual highways in the sky for transportation of people and cargo in the controlled airspace at an altitude of around 1000 ft. to 2000 ft. above the ground level. This paper presents fundamental insights into the design of air corridors with high operational efficiency as well as zero collisions. It begins with the definitions of air cube, skylane or track, intersection, vertiport, gate, and air corridor. Then, a multi-layered air corridor model is proposed. Traffic at intersections is analyzed in detail with examples of vehicles turning in different directions. The concept of capacity of an air corridor is introduced along with the nature of distribution of locations of vehicles in the air corridor and collision probability inside the corridor are discussed. Finally, the results of simulations of traffic flows are presented.

We have recently presented a unified quantum gravity theory [1]. Here we extend on that work and present an even simpler version of that theory. For about hundred years, modern physics has not been able to build a bridge between quantum mechanics and gravity. However, a solution may be found here; we present our quantum gravity theory, which is rooted in indivisible particles where matter and gravity are related to collisions and can be described by collision space-time. In this paper, we also show that we can formulate a quantum wave equation rooted in collision space-time, which is equivalent to mass and energy.The beauty of our theory is that most of the main equations that currently exist in physics are not changed (in terms of predictions), except at the Planck scale. The Planck scale is directly linked to gravity and gravity is, surprisingly, actually a Lorentz symmetry as well as a form of Heisenberg uncertainty break down at the Planck scale. Our theory gives a dramatic simplification of many physics formulas without altering the output predictions. The relativistic wave equation, the relativistic energy momentum relation, and Minkowski space can all be represented by simpler equations when we understand mass at a deeper level. This not attained at a cost, but rather a reflection of the benefit in having gravity and electromagnetism unified under the same theory.

We present a first formal analysis of specific and complete local integration. Complete local integration was previously proposed as a criterion for detecting entities or wholes in distributed dynamical systems. Such entities in turn were conceived to form the basis of a theory of emergence of agents within dynamical systems. Here, we give a more thorough account of the underlying formal measures. The main contribution is the disintegration theorem which reveals a special role of completely locally integrated patterns (what we call ι-entities) within the trajectories they occur in. Apart from proving this theorem we introduce the disintegration hierarchy and its refinement-free version as a way to structure the patterns in a trajectory. Furthermore we construct the least upper bound and provide a candidate for the greatest lower bound of specific local integration. Finally, we calculate the i-entities in small example systems as a first sanity check and find that ι-entities largely fulfil simple expectations.

Understanding the vulnerability of areas and the likelihood of specific disasters, particularly earthquakes, is one of the most important issues in Iran. One of the major concerns in Iran is the resilience of rural communities. The present study is devoted to spatial analysis of risk in rural areas and the evaluation of preparedness in the rural districts of the city of Abhar. In particular, this study evaluates the resilience to earthquakes. The research was conducted in two parts in which the first part has used the VIKOR Multiple criteria decision making model as well as the employment of this model in the ArcGis. The second part of the study used field studies, in the form of questionnaires, to evaluate the readiness of the local population against the risks of earthquakes. Four indicators, individual, physical, economic abilities and access, were assessed. The population included rural districts, where statistical samples were villagers. Results of the spatial analysis indicated that 15 villages are in the high-risk areas, 24 villages were in the medium-risk areas and all other villages were in low-risk areas. In terms of readiness of the locals, the results indicated a lack of planning with regards to the four mentioned indicators.

Despite extensive investigations of the Depression Anxiety Stress Scales-21 (DASS-21) since its development in 1995, its factor structure and other psychometric properties still need to be firmly established, with several calls for revising its item structure. Employing confirmatory factor analysis (CFA), this study examined the factor structure of the DASS-21 and five shortened versions of the DASS-21 among psychiatric patients (N = 168) and the general public (N = 992) during the COVID-19 confinement period in Saudi Arabia. Multigroup CFA, Mann Whitney W test, Spearman’s correlation, and coefficient alpha were used to examine the shortened versions of the DASS-21 (DASS-13, DASS-12, DASS-9 (two versions), and DASS-8) for invariance across age and gender groups, discriminant validity, predictive validity, item coverage, and internal consistency, respectively. Compared with the DASS-21, all three-factor structures of the shortened versions expressed good fit, with the DASS-8 demonstrating the best fit and highest item loadings on the corresponding factors in both samples (χ2(16, 15) = 16.5, 67.0; p = 0.420, 0.000; CFI= 1.000, 0.998; TLI = 0.999, 0.997; RMSEA = 0.013, 0.059, SRMR = 0.0186, 0.0203). It expressed configural, metric, and scalar invariance across age and gender groups. Its internal consistency was comparable to other versions (α = 0.94). Strong positive correlations of the DASS-8 and its subscales with the DASS-21 and its subscales (r = 0.97 to 0.81) suggest adequate item coverage and good predictive validity of this version. The DASS-8 and its subscales distinguished the clinical sample from the general public at the same level of significance expressed by the DASS-21 and other shortened versions, supporting its discriminant validity. Neither the DASS-21 nor the shortened versions distinguished patients diagnosed with depression and anxiety from other conditions. The DASS-8 represents a valid short version of the DASS-21, which may be useful in research and clinical practice for quick identification of individuals with potential psychopathologies. Diagnosing depression/anxiety disorders may be further confirmed in a next step by clinician-facilitated examinations. Brevity of the DASS-21 would save time and effort used for filling the questionnaire and support comprehensive assessments by allowing the inclusion of more measures on test batteries.

In the paper, the author (1) presents an explicit formula and its inversion formula for higher order derivatives of generating functions of the Bell polynomials, with the help of the Faà di Bruno formula, properties of the Bell polynomials of the second kind, and the inversion theorem for the Stirling numbers of the first and second kinds; (2) recovers an explicit formula and its inversion formula for the Bell polynomials in terms of the Stirling numbers of the first and second kinds, with the aid of the above explicit formula and its inversion formula for higher order derivatives of generating functions of the Bell polynomials; (3) constructs some determinantal and product inequalities and deduces the logarithmic convexity of the Bell polynomials, with the assistance of the complete monotonicity of generating functions of the Bell polynomials. These inequalities are main results of the paper.

Solving environmental odor issues can be confounded by many analytical, technological, and socioeconomic factors. Considerable know-how and technologies can fail to properly identify odorants responsible for the downwind nuisance odor and mitigate it for the affected citizenry. We propose enabling solutions to environmental odor issues by utilizing troubleshooting techniques developed for the food, beverage, and consumer products industries. We showed that the downwind odorant impact-priority ranking process can be definable and relatively simple. The initial challenge is the prioritization of environmental odor character from the perspective of the impacted citizenry downwind. In this research, we aim at summarizing three natural models of the rolling unmasking effect (RUE) and discuss them more systematically in the context of the proposed downwind environmental odor prioritization approach. Regardless of the size and reach of an odor source, a simplification of odor character and composition typically develops with downwind dilution. The extreme odor simplification-upon-dilution was demonstrated for two plant varieties, prairie verbena and Virginia pepperweed. Their downwind odor frontal boundaries were dominated by single, character-defining odorants; p-cresol-dominated ‘barnyard’ odor, and benzyl mercaptan-dominated ‘burnt match’ odor, respectively. The P.T. porcupine downwind odor frontal boundary was dominated by two potent, character-defining odorants: (1) ‘onion’/‘body odor’ odorant #1 and (2) ‘onion’/‘grilled’ odorant #2. In contrast with their downwind boundary simplicities, each odor source presented considerable compositional complexity and composite character difference near the source. The proposed RUE approach’s ultimate significance is the illustration of naturally occurring phenomena that explain why some environmental odors and their sources can be challenging to identify and mitigate using the analytical only approach (focused on compound identities and concentrations). These approaches rarely move beyond comprehensive lists of compounds being emitted by the source.

The ongoing COVID-19 global pandemic is affecting every facet of human lives (e.g., public health, education, economy, transportation, and the environment). This novel pandemic and citywide implemented lockdown measures are affecting virus transmission, people’s travel patterns, and air quality. Many studies have been conducted to predict the COVID-19 diffusion, assess the impacts of the pandemic on human mobility and air quality, and assess the impacts of lockdown measures on viral spread with a range of Machine Learning (ML) techniques. This review study aims to analyze results from past research to understand the interactions among the COVID-19 pandemic, lockdown measures, human mobility, and air quality. The critical review of prior studies indicates that urban form, people's socioeconomic and physical conditions, social cohesion, and social distancing measures significantly affect human mobility and COVID-19 transmission. During the COVID-19 pandemic, many people are inclined to use private transportation for necessary travel purposes to mitigate coronavirus-related health problems. This review study also noticed that COVID-19 related lockdown measures significantly improve air quality by reducing the concentration of air pollutants, which in turn improves the COVID-19 situation by reducing respiratory-related sickness and deaths of the people. It is argued that ML is a powerful, effective, and robust analytic paradigm to handle complex and wicked problems such as a global pandemic. This study also discusses policy implications, which will be helpful for policymakers to take prompt actions to moderate the severity of the pandemic and improve urban environments by adopting data-driven analytic methods.

The importance of predicting the exposure to environmental hazards is highlighted by issues like global climate change, public health problems caused by environment stresses, and property damages and depreciations. Several approaches have been used to assess potential exposure and achieve optimal results under various conditions, for example, for different scales, groups of people, or certain points in time. Micro-simulation tools are becoming increasingly important in human exposure assessment, where each person is simulated individually and continuously. This paper describes an agent-based model (ABM) framework that can dynamically simulate human exposure levels, along with their daily activities, in urban areas that are characterized by environmental stresses such as air pollution and heat stress. Within the framework, decision making processes can be included for each individual based on rule-based behavior to achieve goals under changing environmental conditions. The ideas described in this paper are implemented in a free and open source NetLogo platform. A simplified modeling scenario of the ABM framework in Hamburg, Germany, further demonstrates its utility in various urban environments and individual activity patterns, and portability to other models, programs and frameworks. The prototype model can potentially be extended to support environmental incidence management by exploring the daily routines of different groups of citizens and compare the effectiveness of different strategies. Further research is needed to fully develop an operational version of the model.

Assuming a two component, positive and negative mass, superfluid/supersolid for space (the Winterberg model), we model the Higgs field as a condensate made up of a positive and a negative mass, planckion pair. The connection is shown to be consistent (compatible) with the underlying field equations for each field, and the continuity equation is satisfied for both species of planckions, as well as for the Higgs field. An inherent length scale for space (the vacuum) emerges, which we estimate from previous work to be of the order of,

The investigation by the integrated approach newly introduced for this study indicates that insulin resistance (IR) would develop first preferentially in the muscle tissue with a relatively low cell turnover and then progress in sequence to the subcutaneous adipose tissue, to the visceral adipose tissue, and to the liver with higher cell turnovers. Moreover, metabolic disruptions due to IR vary widely from tissue to tissue, contrary to the conventional notion that IR merely impairs glucose uptake in the whole body. This warrants that IR be divided better into four distinct tissue specific IRs: muscle insulin resistance (MIR), subcutaneous adipose insulin resistance (s-AIR), visceral adipose insulin resistance (v-AIR), and hepatic insulin resistance (HIR). Tissue-specific IRs developing in the order of MIR, s-AIR, v-AIR, and HIR – producing tissue specific metabolic disruptions – would amount to nothing but the whole body insulin resistance (WBIR) evolving in four distinctively insulin resistant stages. The four stage metabolic evolution from rapid weight gain to visceral obesity to rapid weight loss to full blown diabetes not only complies well with the natural development history of diabetes but also resolves most of the controversies regarding obesity or diabetes, including visceral obesity, obesity paradox, and dawn phenomenon that have long remained metabolic puzzles. In addition, the four-stage WBIR evolution model refutes the entrenched notion of the lipid-induced insulin resistance (LIIR) but supports instead the glycation-induced insulin resistance (GIIR) proposed in this study. A speculation is that the glycation reaction activated ever more with WBIR evolving may serve as the common thread connecting each other a cluster of disorders or diseases that are often collectively referred to as the metabolic syndrome, such as obesity, diabetes, cardio/cerebral vasculopathy, nephropathy, neuropathy, and retinopathy.

In the paper, by the Faά di Bruno formula, several identities for the Bell polynomials of the second kind, and an inversion theorem, the authors simplify coefficients of two families of nonlinear ordinary differential equations for the generating function of the Catalan numbers and discover inverses of fifteen closely related lower triangular integer matrices.

With forty years of developments, bio-macromolecule cryo-electron microscopy has met its revolution of resolution and is playing a very important role in structural biology study. According to different specimen states, cryo-electron microscopy (cryo-EM) involves three specific techniques, single particle analysis (SPA), electron tomography and sub-tomogram averaging, and electron diffraction. All these three techniques have not realized their full potentials of solving structures of bio-macromolecules and therefore need to be developed in the future. In this review, the current existing bottlenecks of cryo-EM SPA are discussed with theoretical analysis, which includes air-water interface during specimen cryo-vitrification, bio-macromolecular conformational heterogeneity, focus gradient within thick specimen, and electron radiation damage. Besides, potential solutions of these bottlenecks are proposed and discussed, which are worthy of further investigations in the future.

Phenotype variation is produced through a complex of interactions between genotype and environment. Phenotype, genotype, and environment are addresses the relationship between architecture and identity. The term genotype biology and phenotype have been adopted into architecture in the late twentieth century. Genotypes are abstract relational models that govern the arrangement of space, and the principle of organizing space and phenotypes is the real realization of genotypes in the physical environment. The genotype is a reflection that is not only about the spatial organization but also the nature of social and cultural patterns. Then this study purpose to an understanding of the connectedness variant phenotype from a genotype and environment. The repetition pattern being stable structure in variation phenotype uses as a database to finding an identity in architecture. The method used in this research was Levi Strauss's structuralism and multi-layer of a biological system. This research samples traditional Malay houses in West Borneo, Indonesia. These houses have a unique site and existing environment. The houses can be found mainly along the river. The results found from the phenotype, genotype, and environment have value and meaning as a traditional Malay house rule in West Borneo which was always handed down from generation to generation.

When it comes to air pollution complaints, odours are often the most significant contributor. Sources of odour emissions range from natural to anthropogenic. Mitigation of odour can be challenging, multifaceted, site-specific, and is often confounded by its complexity—defined by existing (or non-existing) environmental laws, public ordinances, and socio-economic considerations. The objective of this paper is to review and summarize odour legislation in selected European countries (France, Germany, Austria, Hungary, United Kingdom, Spain, The Netherlands, Italy, Belgium), North America (USA and Canada), South America (Chile and Colombia), as well as Oceania (Australia and New Zealand) and Asia (Japan, China). Many countries have incorporated odour controls into their legislation. However, odour-related assessment criteria tend to be highly variable between countries, individual states, provinces and even counties and towns. Legislation ranges from (1) no specific mention in environmental legislation that regulates pollutants which are known to have an odour impact to (2) extensive details about odour source testing, odour dispersion modeling, ambient odour monitoring, (3) setback distances, (4) process operations, and (5) odour control technologies and procedures. Agricultural operations are one specific source of odour emissions in rural and suburban areas and a model example of such complexities. Management of agricultural odour emissions is important because of the dense consolidation of animal feeding operations and the advance of housing development into rural areas. Overall, there is a need for continued survey, review, development, and adjustment of odour legislation that considers sustainable development, environmental stewardship, and socio-economic realities, all of which are amenable to a just, site-specific, and sector-specific application.

Cropland area per capita and pressure index on cropland is the important parameters measuring the social vulnerability and sustainability in the perspective of food security in a certain region in China during the historical periods. This study reconstructs the spatial distribution change of cropland area per labor/household and pressure index on cropland during the 17th-20th century by the methods of historical documents, regression analysis, pressure index model and GIS. Then it analyzed the impacting process of climate change and sustainability of cropland use during the different periods. It draws conclusions: (i) the spatial difference of labor/household density was obvious which had the same pattern as cropland distribution during the same periods, which is higher density in three agricultural areas. (ii) Cropland area per capita was relatively higher during the 17th-18th century, which were above 0.4 ha/person in majority counties and distributed homogenously. Till the 19th century and the beginning of 20th century, cropland area per capita in large amount of regions decreased below 0.2 ha/person embodying the increase of social vulnerability and unsustainability at that time. (iii) Pressure index on cropland also showed the similar spatial pattern as cropland area per capita which presented lower threshold than nowadays. During the 17th-18th century there was no pressure on cropland. While, in the 19th century and at the beginning of 20th century, two high value centers of pressure index on cropland appeared in Middle Shandong and the Jiaodong region, pressure on sustainable cropland use increased obviously and a food crisis is probably created. (iv) Higher sustainable extent of cropland use corresponds to cold period, and lower sustainable extent of cropland use corresponds to warm period in Shandong over the past 300 years. The turning point of 1680s from dry to wet attributes to the decrease of sustainable extent of cropland use in Shandong not very distinctively. More and more pressure on sustainability of cropland use finally since the beginning of 20th century would intensify the social conflict and increase the probability of social revolts.

The aim of this research was to investigate the mass, substances and energy flow through two-stroke low speed Diesel engines. For this reason, a zero-dimensional model of the combustion in the engine was developed with a calculated amount and composition of exhaust gases. Due to the large amount of oxygen in the exhaust gases, a ratio of real air consumption and stoichiometric amount of air required for combustion of injected fuel was set. The calculated ratio showed that the engine consumes four times more air than needed for combustion in AFR_stoich. In this work it is called the Air Consumption Factor or Ratio and has not been mentioned in scientific literature before. Air Consumption Ratio is defined as a factor of dry or humid air. To be more comprehensive, a modified diagram of composition of the flow in and out of a two-stroke fuel injection engine and the cylinder was drawn.

Local air quality is a major concern for the population regularly exposed to high levels of air pollution. The airport, mainly due to its aircraft engines activities during taxiing and take off, is often submitted to heterogeneous but important concentrations of NOx and PM. The study suggests an innovative approach to determine the air traffic impact on air quality at the scale of the airport, its runways and terminals, in order to be able to locate the persistent high concentrations spots. The pollutants concentrations at 10 m resolution and 1 s time step are calculated in order to identify the most affected areas of an airport platform. A real day of air traffic on a regional airport is simulated, using real data as aircraft trajectories (from radar streams). In order to estimate the aircraft emissions, the Air Transport Systems Evaluation Infrastructure (IESTA) is used. Regarding local air quality, IESTA relies on the non-hydrostatic meso-scale atmospheric model Meso-NH using grid-nesting capabilities with 3 domains, for this study. The detailed cartography of the airport distinguishes between grassland, parking and terminals, allowing to compute exchanges of heat, water and momentum between the different types of surfaces and the atmosphere as well as the interactions with the building using a drag force. The dynamic parameters like wind, temperature, turbulent kinetic energy and pollutants concentration are computed at 10 m resolution over the 2 × 4 km airport domain. The pollutants are considered in this preliminary study as passive tracers, without chemical reactions. This preliminary study aims at proving the feasibility of high scale modelling over an airport with state of the art physical models.

In the paper, the author introduces the notions "multi-order logarithmic numbers" and "multi-order logarithmic polynomials", establishes an explicit formula, an identity, and two recurrence relations by virtue of the Faa di Bruno formula and two identities of the Bell polynomials of the second kind in terms of the Stirling numbers of the first and second kinds, and constructs some determinantal inequalities, product inequalities, logarithmic convexity for multi-order logarithmic numbers and polynomials by virtue of some properties of completely monotonic functions.

According to the current understanding, the recently observed accelerated expansion of the universe is caused by the dark or the vacuum energy. Attempts to calculate the magnitude of this energy using the standard model of particle physics led to values which are 59 – 120 orders of magnitude larger than the experimentally estimated one. Even though the expanding space has positive internal energy, in a flat universe it is completely balanced by the negative energy of gravitational field making the net energy equal to zero. However, the current physical theories may breakdown for times less than or on the order of Planck time and one cannot assume that the above assertion concerning the balance of two energies is valid also in this time scale. In this note it is assumed that this balance of the two energies during the creation of new space as the universe expands takes place only for times larger than the Planck time. If this assumption is correct, the net energy of the newly created space remains positive for times on the order of Planck time and the positive vacuum energy has to be burrowed from empty space before it is being balanced by gravity. This can happen only within the restrictions of the time-energy uncertainty principle. In this note it is shown that such considerations lead to a vacuum energy density of about 0.3 Nanojoules per cubic meter which has to be compared with the measured value of 0.6 Nanojoules per cubic meter.

Epiphytic lichens are well-known indicators of air contamination. The chemical composition of lichens is affected by the concentration of pollutants in the environment. Usually, researchers assess long-term variations in trace elements or other pollutants in the study area or identify the spatial features of air contamination. The aim of this study is to create a database of trace element concentrations in the samples of the epiphytic lichen Hypogymnia physodes growing in the Kaliningrad region. The database can be used as a ‘reference point’ for monitoring studies. Another objective is to identify the spatial patterns of iron, manganese, nickel, cadmium, silver, lead, strontium, rubidium, and calcium in the Kaliningrad region. The samples of wild lichens were collected from pine and birch trees 1.2-1.8 m from the bases of the threes, using a regular grid, in August 2010. One-two-year-old thalli were used in the chemical analysis. The metals Ag, Cd, Cu, Pb, Ni, Fe, Mn, and Zn were determined by AAS (Mn, Fe by flame AAS and the others by ETA-AAS) and the elements Sr, Rb, and Ca by X-ray fluorescence. The concentration of metals in the western coastal area (the Sambian or Kaliningrad Peninsula) is higher than it is in the central and eastern parts of the region. Principal component factor analysis was carried out to detect and characterise different pollution sources and to identify the most polluted areas. The factors of metal emission were described. The authors examined the features of the spatial distribution of trace elements. Prevailing winds are form south-west. Therefore, the highest concentrations of trace elements were found on the Sambian peninsula and on the coasts of the Vistula and Curonian Lagoons. The high concentrations of trace elements in the samples of the lichen H.physodes, which were observed in the coastal part of the region, are associated with human impact and subsequent pollution. The chemical composition of lichens on the Sambian peninsula may have developed under the impact of both local pollution sources – vehicles, thermal energy facilities, and ports – and such factors as transboundary traffic and sea spray.

In the summertime, convections occur frequently over the Tibetan Plateau (TP) because of the large dynamic and thermal effects of the landmass. Measurements of vertical air velocity in convective cloud are useful for advancing our understanding of the dynamic and microphysical mechanisms of clouds and can be used to improve the parameterization of current numerical models. This paper presents a technique for retrieving high-resolution vertical air velocity from convective cloud over the TP, by using Doppler spectra from a vertically pointing Ka-band cloud radar. The method is based on the development of a “small-particle-traced” idea and the necessary data processing and uses three modes of radar. Spectral broadening corrections, uncertainty estimations, and result merging are used to ensure accurate results. Qualitative analysis of two typical convective cases shows that the retrievals are reliable and agree with the expectant results inferred from other radar measurements. A quantitative retrieval of vertical air motion from a ground-based optical disdrometer is used to preliminarily validate our radar-derived results. The comparison illustrates that while the data trends from the two methods of retrieval are similar, with the updrafts and downdrafts coinciding, cloud radar has a much higher resolution and can reveal the small-scale variation of vertical air motion.