Three-dimensional (3D) bioprinting promises to be essential in tissue engineering for solving the rising demand for organs and tissues. Some bioprinters are commercially available, but their impact on the field of TE is still limited due to their cost or difficulty to tune. Herein, we present a low-cost easy-to-build printhead for microextrusion-based bioprinting (MEBB) that can be installed in many desktop 3D printers to transform them into 3D bioprinters. We can extrude bioinks with precise control of print temperature between 2 - 60 ºC. We validated the versatility of the printhead, by assembling it in three low-cost open-source desktop 3D printers. Multiple units of the printhead can also be easily put together in a single printer carriage for building a multi-material 3D bioprinter. Print resolution was evaluated by creating representative calibration models at different temperatures using natural hydrogels such as gelatin and alginate, and synthetic ones like poloxamer. Using one of the three modified low-cost 3D printers, we successfully printed cell-laden lattice constructs with cell viabilities higher than 90% after 24h post printing. Controlling temperature and pressure according to the rheological properties of the bioinks was essential in achieving optimal printability and great cell viability. The cost per unit of our device, which can be used with syringes of different volume, is less expensive than any other commercially available product. These data demonstrate an affordable open-source printhead with the potential to become a reliable alternative to commercial bioprinters for any laboratory.

Large datasets that enable researchers to perform investigations with unprecedented rigor are growing increasingly common in neuroimaging. Due to the simultaneous increasing popularity of open science, these state-of-the-art datasets are more accessible than ever to researchers around the world. While analysis of these samples has pushed the field forward, they pose a new set of challenges that might cause difficulties for novice users. Here, we offer practical tips for working with large datasets from the end-user’s perspective. We cover all aspects of the data life cycle: from what to consider when downloading and storing the data, to tips on how to become acquainted with a dataset one did not collect, to what to share when communicating results. This manuscript serves as a practical guide one can use when working with large neuroimaging datasets, thus dissolving barriers to scientific discovery.

In this work the general problem of the characterization of the topological phase of an open quantum system is addressed. In particular, we study the topological properties of Kitaev chains and ladders under the perturbing effect of a current flux injected into the system using an external normal lead and derived from it via a superconducting electrode. After discussing the topological phase diagram of the isolated systems, using a scattering technique within the Bogoliubov-de Gennes formulation, we analyze the differential conductance properties of these topological devices as a function of all relevant model parameters. The relevant problem of implementing local spectroscopic measurements to characterize topological systems is also addressed by studying the system electrical response as a function of the position and the distance of the normal electrode (tip). The results show how the signatures of topological order affect the electrical response of the analyzed systems, a subset of such signatures being robust also against the effects of a moderate amount of disorder. The analysis of the internal modes of the nanodevices demonstrates that topological protection can be lost when quantum states of an initially isolated topological system are hybridized with those of the external reservoirs. The conclusions of this work could be useful in understanding the topological phases of nanowire-based mesoscopic devices.

The goal of the paper is to investigate the expected participation and mentality of smart citizens in smart cities. The key question is the role of the human factor in smart environments globally studied through a research corpus of the mainstream summaries, trend reports, white papers and visions of business – governmental – university research co- operations. Foremost, a short review of the changing scholarly trends is presented as a theoretical framework. Concerning its key ideas, the corpus based findings are recapped and analysed by content networks and the most referred city strategies. Besides, a critical approach reveal further required factors and risks to investigate. The ultimate goal is to understand how the smart city landscape is shaped by citizen-based strategies, open data, empowerment and responsibility. Accordingly, the paper closes with theoretical, practical and metaphor-based recommendations to support the business and political decision making, and also, the emerging scholarly trends in the context of upcoming technological-structural changes.

Recent advances in open data initiatives allow us to free access to a vast amount of open LiDAR data in many cities. However, most of these open LiDAR data over cities are acquired by airborne scanning, where the points on façades are sparse or even completely missing due to the viewpoint and object occlusions in the urban environment. Integrating other sources of data, such as ground images, to complete the missing parts is an effective and practical solution. This paper presents an approach for improving open LiDAR data coverage on building façades by using point cloud generated from ground images. A coarse-to-fine strategy is proposed to fuse these two different sources of data. Firstly, the façade point cloud generated from terrestrial images is initially geolocated by matching the SFM camera positions to their GPS meta-information. Next, an improved Coherent Point Drift algorithm with normal consistency is proposed to accurately align building façades to open LiDAR data. The significance of the work resides in the use of 2D overlapping points on the outline of buildings instead of limited 3D overlap between the two point clouds and the achievement to a reliable and precise registration under possible incomplete coverage and ambiguous correspondence. Experiments show that the proposed approach can significantly improve the façades details of buildings in open LiDAR data and improving registration accuracy from up to 10 meters to less than half a meter compared to classic registration methods.

Gigantic particle accelerators, incredibly complex detectors, an antimatter factory and the discovery of the Higgs boson – this is part of what makes CERN famous. Only a few know that CERN also hosts the world largest Open Access initiative: SCOAP3. The Sponsoring Consortium for Open Access Publishing in Particle Physics (SCOAP3) started operation in 2014 and has since supported the publication of 19,000 Open Access articles in the field of particle physics, at no direct cost, nor burden, for individual authors worldwide. SCOAP3 is made possible by a 3,000-institute strong partnership, where libraries re-direct funds previously used for subscriptions to ’flip’ articles to ’gold Open Access’. With its recent expansion, the initiative now covers about 90% of the journal literature of the field. This article describes the economic principles of SCOAP3, the collaborative approach of the partnership, and finally summarizes financial results after four years of successful operation.

Observing air quality from sensors onboard light rail cars in Salt Lake County, Utah began as a pilot study in 2014 and has now evolved into a five-year state-funded program. This metropolitan region suffers from both elevated ozone levels during summer and high PM2.5 events during winter. Pollution episodes result predominantly from local anthropogenic emissions but are also impacted by regional transport of dust, chemical precursors to ozone, and wildfire smoke as well as being exacerbated by the topographical features surrounding the city. Two electric light-rail train cars from the Utah Transit Authority light-rail Transit Express (“TRAX”) system were outfitted with PM2.5 and ozone sensors to measure air quality at high spatial and temporal resolution in this region. Pollutant concentration data underwent quality control procedures to determine whether the train motion affected the readings and how the sensors compared against regulatory sensors. Quality assurance results from data obtained over the past year show that TRAX Observation Project sensors are reliable, which corroborates earlier preliminary validation work. Two case studies from summer 2019 are presented to illustrate the strength of the finely-resolved air quality observations: 1) an elevated ozone event and 2) elevated particulate pollution resulting from 4th of July fireworks. The mobile observations were able to capture spatial gradients as well as pollutant hotspots during both of these episodes. Sensors have been recently added to a third light rail train car, which travels on a north-south oriented rail line along which we were unable to monitor air quality previously. The TRAX Observation Project is currently being used to provide reliable pollutant data for health studies and inform urban planning efforts. Links to real-time data displays and updated information on the quality-controlled data from this study are available at https://atmos.utah.edu/air_quality/trax/.

Commuting to work by private vehicle is one of the main sources of air pollution in cities, mainly from NO2 and particulate matter (PM2.5 and PM10). With the spread of telework, traffic congestion during peak hours is reduced on certain days of the week, improving air quality. This study an-alyzes the relationship between the improvement of air quality improvement and urban traffic resulting from teleworking activities after the COVID-19 pandemic in Madrid, Spain. The article considers road traffic and teleworking before the COVID-19 pandemic (2018 and 2019), during the pandemic (2020 and 2021) and in the period after (2022 and 2023) in the city center and the in-fluence on certain environmental factors. Daily NO2, PM2.5, PM10, and O3 concentration data were collected at air quality stations in Madrid municipality, traffic data and some meteorological variables such as wind speed, precipitation and temperature were considered. When conducting correlation and regression analysis among the variables it shows a clear association between NO2 and traffic before the pandemic, which is lower for both PM and O3. This correlation was main-tained during the pandemic, except for O3, whose association increased during this period and then decreased in the later period due to various motives. These results seem to indicate the ex-istence of a relevant relationship between urban mobility and air quality and an especially rele-vant relationship with telework, suggesting the need for policies aimed at promoting sustainable mobility in the future.

This study presents a fit-for-purpose evaluation of commercially available portable sensor systems, measuring PM, NO2 and/or BC, through extensive lab- and field benchmarking. The main aim of the study is to identify sensor systems that can be used for mobile monitoring by citizens to assess dynamic exposure in ambient air. After an initial literature study and market search resulting in 39 sensor systems, 10 sensor systems were ultimately purchased and benchmarked in laboratory and real-word conditions. We evaluated comparability to reference analyzers, sensor precision and sensitivity to temperature, humidity and O3. Moreover, we evaluated if accuracy can be improved by the lab and field calibration. Because the targeted application of the sensor systems under evaluation is mobile monitoring, we conducted a mobile field test in an urban environment to evaluate the GPS accuracy and potential impacts from vibrations on the resulting sensor signals. Results of the considered sensor systems indicate that out-of-the-box performance is relatively good for PM and BC, but maturity of the tested NO2 sensors is still low and additional efforts are needed in terms of signal noise and calibration. The horizontal accuracy of the build-in GPS was generally good achieving a <10m horizontal accuracy for all sensor systems. More accurate and dynamic exposure assessments in contemporary urban environments are crucial to study real-world exposure of individuals and exposome impacts on potential health endpoints. A greater availability of mobile monitoring systems capable of quantifying urban pollutant gradients will further boost this line of research.

This study examines the potential of UiO-66 and g-C3N4-based composite catalysts for environmental purification and pesticide degradation. By integrating zirconium-based metal-organic framework UiO-66 with graphitic carbon nitride (g-C3N4), a composite with a Z-type heterojunction structure is created, enhancing photocatalytic pesticide degradation and phosphorus recovery. The optimal composite, UiO-66/g-C3N4(UG6:4), shows high efficiency in degrading organophosphorus pesticides like DDVP under visible light. This catalyst's high surface area and porous nature efficiently adsorb and break down persistent soil pollutants, including DDT and DDVP. Featuring robust stability and effective photocatalytic activity, the UiO-66/g-C3N4 composite holds promise for soil remediation and dealing with organic pollutants. Future research will aim to further refine this material’s structure and properties, ensuring its practical application in environmental cleanup.

Retiring coal power plants can reduce air pollution and health damages. However, the spatial distribution of those impacts remains unclear due to complex power system adjustments and pollution chemistry and transport. Focusing on coal retirements in Pennsylvania (PA), we analyze six counterfactual scenarios for 2019 that differ in retirement targets (e.g., reducing 50% of coal-based installed capacity vs. generation) and priorities (e.g., closing plants with higher cost, closer to Environmental Justice Areas, or with higher CO₂ emissions). Using a power system model of the PJM Interconnection, we find that coal retirements in PA shift power generation across PA and the Rest of PJM region leading to scenario-varying changes in the plant-level release of several air pollutants. Due to air pollution chemistry and transport and socio-demographics, these changes in turn give rise to a reduction of 10 to 182 PM_2.5-attributable deaths in PJM across the six scenarios, with most reductions occurring in PA. Scenarios that reduce more coal power generation yield greater aggregate health benefits due to air quality improvements in PA and adjacent downwind regions. In addition, vulnerable populations—in both PA and Rest of PJM—benefit most in scenarios that prioritize plant closures in PA near Environmental Justice Areas. These results demonstrate the importance of considering cross-regional linkages and socio-demographics in designing equitable retirement strategies.

It is concerning that Cameroon's urban centers are experiencing an alarming rise in air pollution as a result of urbanization, population growth, industrial activity, and transportation emissions. We examined the causes, health impacts, research methodology, case studies, and government measures to address the urgent issue of air pollution in Cameroon's urban regions. We have emphasized how Cameroon's air pollution levels have significantly increased as a result of causes like population expansion, urbanization, industrial emissions, and automobile exhaust A thorough discussion of the negative health impacts of extended exposure to air pollution is included, with special attention to the sensitivity of the old and young. These effects include respiratory disorders, cardiovascular ailments, and early mortality. We emphasized the pressing need for all-encompassing strategies to address air pollution, such as increased public awareness campaigns, stronger emissions regulations, the development of renewable energy sources, and better waste management. The techniques employed in studies on air pollution, like as epidemiological research and air quality monitoring, are also explained to provide light on the unique health dangers that Cameroonian urban dwellers must contend with. We emphasized in our conclusion the significance of joint efforts by legislators, medical professionals, and the general people to reduce air pollution and protect public health in Cameroon in order to create a cleaner and healthier future. In order to protect public health in the future, it is imperative that Cameroon's air pollution be addressed.

The primary sources of particulate matter are linked to human activity. Certain particulate emissions, particularly those of a finer nature, can significantly impact human health, making them one of the most concerning pollutants. Ultrafine particles (UFP), which have a diameter of less than 100 nm, are of particular concern due to their impact on human health and the difficulty in controlling them. The concentration of ultrafine particles (UFP) in the workplace is a growing concern and is classified as an emerging risk. Workers may be exposed to UFP through inhalation, skin absorption, ingestion, or a combination of these routes. This study aims to determine the levels of UFP exposure among workers in environments with varying direct particle emission patterns. Measurements were conducted to compare the results with the levels recommended by the WHO. The study monitored industrial workplaces with direct particulate matter emissions, such as a carpentry and a bakery, as well as social sector sites without or almost without direct particle emissions, such as a school and a health clinic. One conclusion drawn from this study is that all tasks and occupations are susceptible to high levels of UFP, exceeding WHO recommended values in virtually all monitored environments. Therefore, monitoring and controlling UFP is crucial. Further in-depth studies on this subject are also necessary..

Abstract: Recent years demonstrate the increased attention to radon from two scientific directions. After neglecting radon as earthquake precursors in 1990-th it becomes again the subject of earthquake-forecast papers discussions due to growing networks of the radon monitoring in different countries, especially, the technologies of real-time radon measurements where the gamma-spectrometers become the leader of interest as the sources of 222Rn identification. The second fast developing direction is including the radon in the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) models as a source of the boundary layer ionization. And here we encounter with second direction which is not connected with the earthquake forecast problems. It is the role of air ionization by radon as a source of the Global Electric Circuit (GEC) modification. In this publication we try to unite all these problems to present more complex view on radon as important element of our environment.

DNA extraction for downstream molecular diagnostic applications can be an expensive, time-consuming process. We devised a method to quickly extract genomic DNA from environmental samples based on sodium hydroxide lysis of cells with or without capture by magnetic beads, for subsequent PCR or quantitative PCR. The final DNA extraction method using NaOH is extremely low-cost and can be completed in 10 minutes at room temperature. NaOH extraction was effective for Gram-negative and Gram-positive bacteria in samples from air, soil, sewage, food, laboratory surfaces, and chicken cloacal swabs. The NaOH extraction method was comparable to commercial kits for extraction of DNA from pig fecal samples for 16S amplicon sequencing analyses. We demonstrate that an impinger and portable pump can efficiently capture bacteria in poultry facilities for rapid DNA extraction for quantification of total bacteria and for detection of specific species using qPCR. The air sampling and NaOH extraction procedures are well-suited for routine, high throughput screening, and for metagenomic analyses for specific pathogens, even in resource-limited situations.

The air is a fundamental element for the life on Earth. Rapid urbanization and industrialization release large amounts of pollutants (harmful gases, microorganisms, and particulate matter, among others) into the atmosphere, leading to health hazards. Air filtration is still the most used and promising technique for protecting air against pollutants. The quality and efficiency of filtering process are dependent of material used for the filter and other filter’s properties. Several methods can be used for manufacturing filters, one of them uses fibrous membranes obtained through electrospinning from polymeric solutions. Electrospinning is a technique that combines the application of an electrostatic field to a moving fluid which results in the fibers formation. Electrospun membranes are constituted by fibers that the sizes spread on submicro and or nanometric scales. This review focuses on fiber membranes obtained by electrospinning for filtration of particulate matter. It is addressed the effect of solution, processing and ambient parameters on the morphology and dimensional characteristics of fiber membranes. The basic principles of air filtration and test and characterization of filter performance are presented. The research progress on electrospun nanofibers as air filters in recent years is summarized and examined. Finally, conclusion and future perspectives in electrospun fibers for air filtration are provided and discussed.

This research investigates the compatibility of conventional air conditioning with the principles of green building, highlighting the need for systems that enhance indoor comfort while aligning with environmental sustainability. Conventional cooling systems, though proficient in regulating indoor temperatures, encounter several issues when incorporated into green buildings. These include energy waste, high running costs, and a misalignment with eco-friendly practices, which may also lead to detrimental environmental effects and potentially reduce occupant comfort, particularly in retrofit situations. Given the emphasis on sustainability and energy conservation in green buildings, there is a pressing demand for heating, ventilation, and air conditioning (HVAC) solutions that support these goals. This study emphasizes the critical need to reconsider traditional HVAC strategies in the face of green building advances. It advocates for the adoption of innovative HVAC technologies designed for eco-efficiency and enhanced comfort. These technologies should integrate seamlessly with sustainable construction, use greener refrigerants, and uphold environmental integrity, driving progress towards a sustainable and occupant-friendly built environment.

A study was conducted on the power system of a forklift equipped with PEM fuel cells. A fuel cell assembly relies on several components for proper functioning, and among these, the air compressor holds paramount importance due to its significant energy consumption when compared to other Balance of Plant components. The air supply system, in turn, plays a critical role in ensuring the stable and efficient operation of the entire fuel cell system. To enhance system efficiency, we delved into the impact of varying the stoichiometric ratio of air and air pressure on the validated and optimized power module model. This investigation was carried out under real loading conditions, replicating the conditions experienced by the power module when fuel cells are in use within a forklift. The air compressor, being a pivotal component of a PEM fuel cell system, can be oper-ated at different excess air and pressure ratios, which in turn influence both the fuel cell's performance and the overall efficiency of the power module system. Our research focused on assessing the performance of polymer electrolyte membrane (PEM) fuel cells under different load cycles, adhering to the VDI60 requirements for forklift applications. This comprehensive examination encompassed the system's minimum and maximum load scenarios, with the primary goal of optimizing excess air and pressure ratio parameters, especially under dynamic load conditions. The results revealed that higher air pressures and lower excess air ratios were con-ducive to increasing system efficiency, shedding light on potential avenues for enhancing the performance of PEM fuel cell systems in forklift applications.

In Bangkok, the capital city of Thailand, air pollution is a significant problem, and efforts are needed to define organisms that may be used as bioindicators of air pollution. Epiphytic subaerial algae, which grow on the surface of trees, may have a potential as bioindicators of urban air quality. Algae were collected from randomly selected tree trunks in five parks in Bangkok, and the air pollutants CO, NO2, O3, SO2, PM2.5, and PM10 were measured. Analysis of the subaerial algal communities was performed by metagenomics. Diversity indexes were determined for the algal taxa detected, which were separated into groups corresponding to different collection sites by cluster analysis. Relationships between taxa and air pollutants were analyzed by PCA and the Pearson correlation coefficient (r). The results showed a high diversity of epiphytic subaerial al-gae. We recorded 101 taxa belonging to the Cyanophyta (70 taxa), Chlorophyta (21 taxa), Char-ophyta (5 taxa), Bacillariophyta (3 taxa), and Eustigmatophyta (2 taxa). The most abundant taxon was Chroococcidiopsis sp. 1, for which up to 13,254 individuals/cm2 were recorded. The Shan-non–Weaver index ranged between 1.37 and 2.51, the Margalef index between 3.84 and 4.75, and the Pielou index between 0.30 and 0.54. The similarity index was between 8.00% and 64.82% ac-cording to the cluster analysis results for three groups. The PCA indicated that all air pollutants affected the diversity and abundance of the epiphytic subaerial algae. Cyanothece sp. 2 is consid-ered a potential bioindicator of air pollution. It was negatively related to O3 and positively related to NO2 and CO

Numerical simulations and experiments on evaporative condensers in air conditioning systems using R744 were performed. Two configurations were given to study the feasibility of operating the subcritical R744 cycle. It indicated the capable of evaporative cooling condensing R744 to liquify by analyzing the outlet temperature at the end of the condenser reached from 28.7oC to 30.3oC with the operating pressure from 72.6 bar to 68.5 bar. The mass flow rate in the study increases from 14.34 kg/h to 46.08 kg/h, the pressure drop also increases from 0.23 bar to 0.47 bar for the simulation and 0.4 bar to 0.5 bar for the experiment, respectively. This study indicates that a 5-layers of copper tubes configuration causes a higher pressure drop and lower COP when compared to an 8-layers of copper tubes that split into 2 sets for smaller pressure drop. In this study, the evaporative condensers using mini tubes that are flooded in the cooling water tank are suitable for the subcritical R744 air conditioning system. The results obtained from the experimental data are in good agreement with those obtained from the numerical results, with the deviation less than 5%.

During the second half of August 2022, a dust intrusion event occurred, when dust that originated from the dry regions of Kalmyk steppe and the Precaspian plain was transported over the eastern region of Romania. The dry soil in these regions was the result of the severe drought over a long period of time, accentuated by early heat waves in May and June 2022. The dust event was captured by MODIS images. Smoke trains originating from fires in the north of the Azov were also detected, but these did not reach Romania. Optical parametres from AERONET was used to confirm the dust event. To determine the trajectory of the particles, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used in this paper. The Ensemble median model was used to highlight the presence and concentration of dust in eastern part of Romania. Aerosols were detected between 0 and 4 km, according to radar and ceilometer data of the REXDAN cloud remote sensing facility in Galați, Romania. This dust intrusion event was the result of the dominant easterly cir-culation caused by the extension of East European High to the northeast of the continent, which transported the dust towards eastern part of Romania for more than 2 days. Moreover, the tor-rential rains between August 22nd and 24th did not clear the atmosphere of dust, since the intense easterly circulation kept carrying the dust into the Moldavian area.

The close proximity of different buildings heights can cause disturbances in the working of the smoke and ventilation ducts of lower buildings, threatening the health and even the lives of residents. To define the influence of high-rise building on the work of the ducts of the neighbouring double-storied building, experimental investigations in the wind tunnel were conducted. On this basis, empirical equations and graphs were developed leading to determining the aerodynamic coefficients considering different wind directions and the height of ducts. The direction of the wind reveals a greater influence than the height of the ducts. Properly using deflectors or increasing the height of the duct ensures maintaining static rarefaction in the area of smoke and ventilation ducts. The creation of rarefaction ensures the reliability of the natural ventilation system and the safety of the health of residents.

PM2.5 levels affect human health. However, its relationship with other health vulnerability determinants has not been sufficiently explored. Furthermore, public access to PM2.5 datasets, linkable to health statistics, is not available. We built a georeferenced database and map of annual mean PM2.5 emissions and air concentrations values in Argentina in 2010 and explored their correlations with other health vulnerability determinants. We obtained data for montlhy PM2.5 values emissions and air concentrations in Argentina from public sources. We evaluated health vulnerability by the “Sanitary Vulnerability Index (SVI)”. Non-parametric correlations between variables below 0.22, corresponding to a R2=5%, were deemed meaningless. PM2.5 emissions concentrated in urban and intensive agricultural areas of Argentina. PM2.5 air concentrations were acceptable (≤10 microg/m3) in only 15% of the Argentinean territory, respectively. The correlation between air concentration of PM2.5 and human emission was meaningless. Emissions, but not air concentrations correlated >0.22 with indicators of human activity. SVI correlated meaninglessly with PM2.5 air concentration. In conclusion, PM2.5 levels were above acceptable levels in 85% of the Argentinian territory in 2010. The lack of meaningful correlations between PM2.5 and SVI suggest that these coefficients might be used in combination to assess health vulnerability. Further research is warranted.

The cornea is an avascular tissue which has attracted much attention by the uniqueness of its anatomical characteristics, it has, in proportion, an enormous size, in relation to the number of vessels, because on average few cells in the organism are away more than 30 microns of a blood vessel. However, the cornea, with a diameter of between 11 and 12 mm, is a unique example. It has been tried to explain the notable absence of blood vessels in the cornea, arguing that corneal tissues are able to take oxygen directly from the air. In this article we are explaining that based on the physicochemical characteristics of molecular oxygen and the cell membrane, cytoplasm, water, and cellular metabolism, it is not possible that epithelial corneal cells directly take oxygen from the air, instead, corneal cells have molecules that can dissociate the water molecules thereby these cells, like any other eukaryotic cells, take the oxygen from the intracell water, like plants.

Aerosol Optical Thickness (AOT) is one of the critical factors for global atmospheric conditions, climate change, and air pollution. AOT has been exposed as a major component of air pollution in Bangladesh. This paper aims to map the seasonal distribution of AOT from 2002-2022 and to explore the internal relationship between AOT and ten air pollutants using remote sensing and machine learning tools. These ten air pollutants are Particulate matter (PM2.5), Methane (CH4), Carbon monoxide (CO), Nitrogen dioxide (NO2), Formaldehyde (HCHO), Ozone (O3), Sulfur dioxide (SO2), Aerosol Particulate Radius (APR), Nitrogen oxide (NOx) and Black carbon (BC). The results show that the concentrations of AOT were higher in December-January-February (mean value 0.50) and March-April-May (mean value 0.50) seasons, mostly in the central, western, and southern parts of Dhaka, Narayanganj, and Munshiganj districts. AOT was a bit less in June-July-August (mean value 0.33) and September-October-November (mean value 0.37). This paper also revealed that the AOT was correlated positively with PM2.5 (0.60), CH4 (0.80), NO (0.76), and BC (0.83) while correlated negatively with CO (-0.66), HCHO (-0.16), SO2 (-0.41), APR (-0.48), and NOx (-0.20). From the machine learning, the Rational quadratic GPR (RME-0.0024, MAE-0.0015, R2-0.96), Matern 5/2 GPR (RMSE-0.0023, MAE-0.0015, R2-0.96), and Squared Exponential GPR (RMSE-0.0015, MAE-0.0015, R2-0.96) were found good classifiers to predict AOT. UN agencies, government line departments, and local and regional development councils for air pollution mitigation and long-term protective measures may use the paper's key results.

Cigarette smoking and air pollution (particulate matter) are recognized as two major etiological factors for lung cancer. Of all the risk factors, cigarette smoking is significantly associated with lung carcinogenesis. The main mechanism lies in the metabolically activated carcinogens (majorly polycyclic aromatic hydrocarbons and nitrosamines), which could covalently bind with DNA molecules and lead to irreversible mutations in pivotal cancer genes, such as TP53 and KRAS. Another major etiological factor for lung cancer is air pollution, which is with complex compositions and ubiquitous in daily life, especially in developing countries as China and India. The latest literatures on lung cancer epidemiology and etiology have been briefly summarized and reviewed in this work.

Chronic obstructive pulmonary disease (COPD) is a multifactorial lung inflammatory disease affecting 174 million people worldwide, with a recently reported increased incidence in female patients. Patients with COPD are especially vulnerable to the detrimental effects of environmental exposures, especially from air particulate and gaseous pollutants. Exposure to air pollution severely influences COPD outcomes, resulting in acute exacerbations, hospitalizations, and death. In the current study, we conducted a review of the literature addressing air pollution induced acute exacerbations of COPD (AECOPD) in order to determine whether air pollution affects COPD patients in a sex-specific manner. We found that while the majority of studies enrolled both male and female patients, only a few reported results disaggregated by sex. Most studies had a higher enrollment of male patients, only four compared AECOPD outcomes between sexes, and only one study identified sex differences in AECOPD, with females displaying higher rates. Overall, our analysis of the literature confirmed that air pollution exposure is a trigger for AECOPD hospitalizations and revealed a significant gap in our knowledge of sex-specific effects of air pollutants on COPD outcomes, highlighting the need for more studies considering sex as a biological variable.

Background: Exposure in utero to particulate matter (PM2.5 and PM10) is associated with maladaptive health outcomes. Although exposure to prenatal PM2.5 and PM10 have cord blood DNA methylation signatures at birth, signature persistence into childhood and saliva cross-tissue applicability has not been tested. Methods: In the Fragile Families and Child Wellbeing Study, a United States 20-city birth cohort, average residential PM2.5 and PM10 during pregnancy was estimated using air quality monitors with inverse distance weighting. Saliva DNA methylation at ages 9 (n=749) and 15 (n=793) was measured using the Illumina HumanMethylation 450k BeadArray. Cumulative DNA methylation scores for particulate matter were estimated by weighting participant DNA methylation at each site by meta-analysis effect estimates from Gruzieva et al. 2019 and standardizing the sums. Using mixed effects regression analysis, we tested the associations between cumulative DNA methylation scores at ages 9 and 15 and PM exposure during pregnancy, adjusted for child sex, age, race/ethnicity, maternal income to needs ratio, nonmartial birth status, and saliva cell type proportions. Results: Our study sample was 50.5% male, 56.3% non-Hispanic Black, and 19.8% Hispanic, with median income to needs ratio of 1.4. In the third trimester, mean PM2.5 exposure levels were 27.9 ug/m3/day (standard deviation: 7.0, 23.7% of observations exceeded safety standards) and PM10 were 15.0 ug/m3/day (standard deviation: 3.1). An interquartile range increase in PM2.5 exposure (10.73 g/m3/day) was associated with -0.0287 standard deviation lower cumulative DNA methylation score for PM2.5 (95% CI: -0.0732, 0.0158, p=0.20) across all participants. An interquartile range increase in PM10 exposure (3.20 g/m3/day) was associated with -0.1472 standard deviation lower cumulative DNA methylation score for PM10 (95% CI: -0.3038, 0.0095, p=0.06) across all participants. The PM10 findings were driven by the age 15 subset where an interquartile range increase in PM10 exposure was associated with -0.024 standard deviation lower cumulative DNA methylation score for PM10 (95% CI: -0.043, -0.005, p=0.012). Findings were robust to adjustment for PM exposure at ages 1 and 3. Conclusion: In utero PM10 associated DNA methylation differences persist until age 15 and can be detected in saliva. Benchmarking the persistence and cell type generalizability is critical for epigenetic exposure biomarker assessment.

After the arrival of a new airborne virus to the world, science is aiming to develop solutions to withstand the spread and contagion of the SARS-CoV-2 coronavirus. The most severe among the adopted measures is to remain in home isolation for a significant number of hours per day, in order to avoid the spreading of the infection in an uncontrolled way through public spaces. Recent literature showed that the major route of transmission is via aerosols produced especially in poorly ventilated inner spaces. With regard to contagion rates, accumulated incidence or number of hospitalizations due to COVID-19, Spain has reached very high levels, therefore this article develops a quantitative and qualitative analysis of the requirements established in Spain with respect to the European framework in reference to ventilation parameters indoors. For this, a case study has been analyzed, representing a common residence in current Spanish residential developments. Results show that the criteria established in the applicable regulations are not sufficient to ensure health as well as to avoid contagion by aerosols indoors.

Three genera of very large volant birds existed for most of the Pliocene: the Pelagornithidae seabirds; the large North American Teratornithidae and the stork Leptoptilos falconeri in Africa and Asia. All became extinct around 3 Ma. The reasons for their demise are puzzling, as the Pelagornithidae had a world-wide evolutionary history of more than 50 Ma, smaller teratorns were still extant in the Holocene and smaller stork species are still globally extant. Extant large birds have a common critical takeoff airspeed suggesting a biomechanical limit in terms of power, risk and launch speed, and simulations of the flight of these extinct species suggest that at 1 bar they would have exceeded this value. Estimates for the Late Pliocene atmospheric density are derived from marine and terrestrial isotopes as well as resin chemistry, both approaches suggesting a value of about 1.2 bar, which drops to present levels during the period 3.3 to 2.6 Ma, thus a loss in atmospheric density may have caused biomechanical and ecological stress contributing to their extinction and/or development of smaller forms. This hypothesis is examined in terms of a possible mechanism of atmospheric mass loss and how this would be seen in the geological record. At 1.2 bar all the extinct species present takeoff airspeeds similar to large extant volant birds and which match the expected power and kinetic energy levels.

Concerns about China’s air quality, and its impact on the important tourism industry have been on the debate in recent years. This article aims to investigate the potential effect of air pollution on direct economic impact of tourism, using the case of Beijing and Shanghai. The results indicate that air pollution negatively affects China's inbound tourism, resulting in huge loss of tourist arrivals and receipts, and Beijing suffers a greater loss in comparison with Shanghai, its loss in tourist number amounts to 1569,700 persons, equal to CNY 10264.268 million in tourism receipts, and the GDP losses ranges from CNY 20528.536 to 41057.072 across major source countries. This study provides a quantification of the impact helpful to generate a social awareness of air pollution detrimental impacts on inbound tourism and hence the economy.

In this study, we test the performance of a compact gas chromatograph with photoionization detector (GC-PID) and optimize the configuration to detect ambient (sub-ppb) levels of benzene, toluene, ethylbenzene, and xylene isomers (BTEX). The GC-PID system was designed to serve as a relatively inexpensive (~$10k) and field-deployable air toxic screening tool alternative to conventional benchtop GCs. The instrument uses ambient air as a carrier gas, and consists of a Tenax-GR trap preconcentrator, a gas sample valve, two capillary columns, and a photoionization detector (PID) with a small footprint and low power requirement. The performance of the GC-PID has been evaluated in terms of system linearity and sensitivity in field conditions. The BTEX-GC system demonstrated the capacity to detect BTEX at levels as high as 500 ppb with a linear calibration range of 0-100 ppb. A detection limit lower than 1 ppb was found for all BTEX compounds with a sampling volume of 1 L. No significant drift in the instrument was observed. A time-varying calibration technique was established that requires minimal equipment for field operations and optimizes the sampling procedure for field measurements. With an analysis time of less than 15 minutes, the compact GC-PID is ideal for field deployment of background and polluted atmospheres for near-real time measurements of BTEX. The results highlight the application of the compact and portable GC-PID for community monitoring and screening of air toxics.

In the past two decades, acoustic metamaterials have garnered much attention owing to their unique functional characteristics, which is difficult to be found in naturally available materials. The acoustic metamaterials have demonstrated to exhibit excellent acoustical characteristics that paved a new pathway for researchers to develop effective solutions for a wide variety of multifunctional applications such as low-frequency sound attenuation, sound wave manipulation, energy harvesting, acoustic focusing, acoustic cloaking, biomedical acoustics, and topological acoustics. This review provides an update on the acoustic metamaterials' recent progress for simultaneous sound attenuation and air ventilation performances. Several variants of acoustic metamaterials, such as locally resonant structures, space-coiling, holey and labyrinthine metamaterials, and Fano resonant materials, are discussed briefly. Finally, the current challenges and future outlook in this emerging field is discussed as well.

The literature, aimed at understanding the income-price elasticity of air passenger demand, bases its analysis on airport movement. The diversity of studies regarding the casualty between air transportation and economic growth are examples. Some studies covering this link, estimate the income-price relationship with the demand considering international traffic. Considering a domestic setting, where this traffic is significant in Brazil, studies related to remote regions are scarce, and the existing ones focus on governmental policies and subsidies. In addition, empirical studies on the theme consenter themselves in developed regions, such as Europe, North America, and Australia. For Brazil, where we find the Amazon region, there are no empirical researches. This paper analyses the price-income elasticity of the demand regarding domestic passengers in air links from remote cities of the Brazilian Amazon. This study uses panel data regression analysis method on a database of domestic scheduled flights of Brazil´s National Civil Aviation Agency. The results show that air passengers involving remote region flights present a lower sensitiveness regarding local income and airline´s price variations than those in flights among capitals. The higher difference is in income-elasticity of the remote city of origin, which is lower than that of the air traffic among capitals.

Population concentration in cities brings new risks as an increase in pollution, which causes urban health problems. In order to address this problem, traffic reduction measures are being implemented, as pedestrianization areas and the definition of Low Emissions Zones (LEZ). When the effectiveness of these types of measures is in doubt, smart city tools provide data that can be used to scientifically asses their impact. This article analyzes the situation of Madrid Central (Spain), a LEZ subject to controversy. We apply statistical and regression analyses to evaluate the effectiveness of this measure to reduce air pollution and outdoor noise. According to the results, this LEZ was able to significantly reduce NO$_2$, PM$_{2.5}$, and PM$_{10}$ concentration locally, having the same positive impact in the rest of the city. In terms of noise, this measure is able to mitigate background noise levels generated by the road traffic.

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.

Two isotropic pitches were prepared by air blowing and nitrogen distillation method using ethylene tar (ET) as a raw material. And correspondent carbon fibers were obtained through conventional melt spinning, stabilization and carbonization. The structures and properties of resultant pitches and fibers were characterized and their differences were discussed in this work. The results showed that introduction of the oxygen by air blowing method could quickly increase the yield and softening point of pitch. Moreover, the air blown pitch (ABP) composed of linear methylene chains of aromatic molecules while the nitrogen distilled pitch (NDP) mainly contained polycondensed aromatic rings, which was due to the oxygen containing functional groups existed in ABP could impede order stack of pitch molecules and form methylene bridge structure, instead of aromatic condensed structure like NDP. Meanwhile, the spinnability of ABP was not decreased even containing 2.31 wt% oxygen. In contrast, ABP had narrower molecular weight distribution, which contributed to better stabilization properties and higher tensile strength of carbon fiber. The tensile strength of carbon fibers from ABP was reached to 860 MPa with fiber diameter of about 10 μm, which was higher than that of NDP-derived carbon fibers of 640 MPa.

Ultraviolet (UV) light with a wavelength of 254 nm has proven to be effective at inactivating microorganisms, and thus has been increasingly employed as a method of disinfection for indoor environments. Solar UV wavelengths (300 to 400 nm) are known to initiate the formation of secondary organic aerosol (SOA) particles from photo-oxidation of volatile organic compounds in the atmosphere, but germicidal wavelengths have not been extensively studied for indoor environments. In this work, toluene was exposed to 254 nm UV light in a laboratory photoreactor, with varying conditions of the air, the duration of UV exposure, and the duration of post-UV time. The number of particles formed in the fine particulate matter (PM2.5) size range was measured, and significant levels of particle formation were observed for UV exposure periods of as short as 5 minutes. The particle formation ranged from 2.4x10⁶ particles/m³ for 5 minutes of UV exposure, to 1449.8x10⁶ particles/m³ for 15 minutes of UV exposure. Particle formation was found to increase with increasing concentrations of gas phase toluene, and at relative humidity of approximately 20% and higher. Variations in the initial number of particles present did not appear to have a significant effect on the particle formation, suggesting that nucleation was not a controlling factor. However, tests in a commercial environment showed no significant detectable PM2.5 formation, indicating that SOA formation during the intermittent use of germicidal UV may not significantly affect indoor air quality.

A D-grade type coal was burned under simulated domestic practices in a controlled laboratory set-up, in order to characterize emissions of volatile organic compounds (VOCs); viz. benzene, toluene, ethylbenzene and xylenes (BTEX). Near-field concentrations were collected in a shack-like structure constructed using corrugated iron, simulating a traditional house found in informal settlements in South Africa. Measurements were carried out using the Synspec Spectras GC955 real-time monitor over a three-hour burn cycle. The 3-hour average concentrations (in µg/m³) of benzene, toluene, ethylbenzene, p-xylene and o-xylene were 919 ± 44, 2051 ± 91, 3838 ±19, 4245 41 and 3576 ± 49, respectively. The cancer risk for adult males and females in a typical SA household exposure scenario, was found to be 1.1 -1.2 and 110-120 folds higher than the US EPA designated risk severity indicator (1E^-6), respectively. All four TEX compounds recorded the Hazard Quotient (HQ) of less than 1, indicating a low risk of developing related non-carcinogenic health effects. The HQ for TEX ranged from 0.001– 0.05, with toluene concentrations being the lowest and ethylbenzene the highest. This study has demonstrated that domestic coal burning may be a significant source of BTEX emission exposure.

Nowadays a recognized need for accurate observations of atmospheric aerosols (AEs) and reactive gases (RGs) exists in the framework of regional, national and global near-surface networks based on permanent or mobile measurement stations. In this context, a paramount and not-trivial issue is related to the correct execution of continuous sampling of ambient air and its subsequent distribution to measurement analyzers hosted inside the stations. Sampling artifacts must be minimized for obtaining reliable pictures of ambient air composition. To respond to this need, a suite of novel “smart” and relatively low-cost systems for the continuous sampling of ambient air was developed in the framework of the Project I-AMICA (2012 – 2015, www.i-amica.eu). These systems were designed to execute AE and RG measurements according with WMO/GAW and ACTRIS recommendations and standard operation procedures. A particular attention was dedicated to the stabilization and control of the sampling flow rates and temperatures. The analysis of one full year of operations at the WMO/GAW regional station of Capo Granitola (GAW ID: CGR, Italy), allowed to conclude that these systems are effective in meeting the technical requirements for correct execution of AE and RG measurements

Introduction: Ambient air pollution is major global health problem and commercial drivers are particularly exposed to it. No systematic assessment of the health risks associated with occupational exposure to ambient air pollution in this population has been carried out. Methods: We conducted a systematic review using a protocol-driven strategy. Papers published from inception to 20th April 2018 in MEDLINE, EMBASE, CINAHL, African journals online, Cochrane library, ISRCTN and WHO ICTRP databases were screened for inclusion by two independent reviewers. Original articles with at least an available abstract in English or French were included. Results: The initial search retrieved 1454 published articles of which 20 articles were included. 3 Studies reported a significant difference in white blood cells (106/L) among commercial motorcyclists compared to rural inhabitants (5.041±1.209 vs 5.900±1.213,p=0.001), an increased risk of lung cancer (RR=1.6, 95%CI 1.5-1.8) in bus drivers and an increased standardized mortality ratio (SMR) in bus drivers from Hodgkin’s lymphoma (SMR 2.17, 95%CI 1.19-3.87) compared to white collar workers. Other studies also found that drivers had more oxidative DNA damage and chromosome breaks. 4 papers failed to demonstrate that the drivers were more exposed to air pollution than the controls. 3 other studies also reported no significant difference in lung function parameters and respiratory symptoms. The genetic polymorphisms of detoxifying enzymes were not also homogeneously distributed compared to the controls. Conclusion: There is some evidence that occupational exposure to ambient air pollution among commercial drivers is associated with adverse health outcomes but the existing literature is limited with few studies of small sample size, methodological weaknesses and contradictory findings. Further research is recommended.

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.

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.

Ethylene Oxide (EtO) is a colorless, flammable gas at room temperature, produced by the catalytic oxidation of ethylene. EtO is widely used by medical sterilization facilities to clean medical supplies and equipment. Recent epidemiological studies showed that EtO is a more potent carcinogen than previously documented, leading the Environmental Protection Agency (EPA) to update, in December 2016, the inhalation unit risk estimate for EtO. This resulted in the identification of EtO as a potential health concern in several areas across the US, including the state of Utah. The geography surrounding Salt Lake Valley creates a bowl; ideal for collecting air pollution emissions. The region often experiences inversion episodes which inhibit vertical mixing and cause an accumulation of air pollutants, leading to unhealthy pollution levels. Using the EPA's dispersion modeling software, AERMOD, this study estimated EtO concentrations through facility stack and fugitive emissions modeling results. These values were compared with those of canister-based concentrations from ambient air samples taken near a medical device sterilization facility in the Salt Lake Valley. Stainless steel, whole-air passivated canisters were used to collect 24-hour ambient concentration samples of EtO. Eight locations surrounding a Salt Lake Valley medical device sterilization facility and four background sites were chosen to measure the ambient concentrations. Accounting for potential atmospheric impacts on EtO, measurements were sampled in winter 2022 (January-March) and summer 2022 (July-September). The modeled EtO concentrations were adjusted to account for background values associated with the winter or summer data. Then the two methodologies were compared using a Wilcoxon Sign-ranked, paired test. The statistical analysis resulted in six of the eight sample locations surrounding the sterilization facility being significantly different when comparing canister-based measurements of ambient EtO to modeled estimates. Canister-based measurements taken at sites one, three, and four were statistically greater than the modeled estimates, while sites two, five, and seven were statistically less than the modeled estimates. Also, the summer background value calculated was almost 2.5 times greater than the winter. The results do not suggest whether one method is more or less conservative than the other. In conclusion, the five of the closest sites and site seven were statistically different when comparing measured and modeled ambient concentrations of EtO. The comparison results do not clearly indicate if a correction factor could be derived for future human exposure to cancer risk assessment modeling. However, it is reasonable that the closer to the sterilization facility, the more total EtO exposure will be realized.

The aim of the study was to assess the intensity of the impact of the Křoví mining facility on the environment. The impact of the exploitation of rock deposits in Křoví on the atmosphere, lithosphere, biosphere, hydrosphere and anthroposphere was presented. Vulnerability to natural hazards was also assessed. The multi-criteria Analytic Hierarchy Process (AHP) method and the Leopold matrix were used to assess the impact. The assessment of the impact of raw material extraction in the quarry was carried out by competent experts. It has been found that the lithosphere and biosphere are under the greatest pressure due to land use and surface transformation (including deforestation). The increased susceptibility of the area to natural hazards was noted due to vibrations caused by increased truck traffic (transportation of excavated material). The total value of the matrix indicates the average intensity of the mining facility's impact on the environment. The location of the deposit above the water table of the Bílý potok river means that the extraction of the mineral has a minor impact on the water conditions in the area. Changes in topography and vegetation, and soil degradation are temporary and reversible. Once the mining operations have ceased, the site should be reclaimed and the program of reforestation and habitat restoration implemented to help mitigate adverse impacts on the biosphere.

Open Educational Resources (OER), educational materials permit unrestricted use and adaption, have proven beneficial for cost savings and curriculum flexibility. However, OER are not frequently used in college courses. An OER initiative was designed to understand the factors contribute to increasing access to STEM course materials. This study employed a survey to investigate faculty awareness and usage of OER and explore support needed to increase the use of OER in STEM. Results indicated that one-sixth of the respondents were unaware of OER, and 53% had never used OER. The motivating factors for OER usage included cost-free licenses, day-one availability to students, and increased access. The support strategies for new OER creation included OER workshops, grants, and recognition for OER authoring. In conclusion, the current study fills a gap in the existing literature by documenting motivating factors for faculty to integrate OER into STEM for the first time.

Sustainable development has become the aspiration of many developing countries, including Ecuador. The introduction of Bachelor of Tourism studies at the Technical University of Manabí aligns with this interest, implying a challenge for teachers regarding the application of integrative and innovative teaching methods that promote the training of professionals with high scientific rigor, both in technical and professional senses. To achieve this, the pedagogical group started from three fundamental principles based on the application of teaching work methods and pro-cedures, as well as the determination of interactions between the various factors that directly and indirectly influence the training process of professionals in the tourism sector. The results of comprehensive evaluation processes considering both the academic performance of the teachers and the level of satisfaction of students taking the course support the application of these teaching–learning methods, as well as highlighting the convenience of extending the experiences and re-search results of the pedagogical team to other vocational training centers for tourism activities.

The intricate relationship between Gray-Level Co-occurrence Matrix (GLCM) metrics and machine learning model performance underscores the need for rigorous dataset evaluation and selection protocols to ensure the reliability and generalizability of classification outcomes. This study involved a thorough examination of selected publicly available plant diseases datasets, with an emphasis on how well they performed as measured by GLCM metrics. After first classifying the datasets according to their GLCM metrics, dataset_2 (D2) and dataset_5 (D5) were found, respectively, to be the best-performing dataset in all GLCM analyses. The same datasets were then used to train deep learning models, and their classification performances were assessed. A noteworthy association was observed between the results of training deep learning models and the performance ratings derived from GLCM studies. More specifically, dataset_2 (D2) performed best in both GLCM analysis and deep learning model performance, indicating a strong correlation between the accuracy of classification and the textural qualities that GLCM captured. In the context of plant disease identification, in particular, these results highlight the significance of clearly defined dataset selection criteria in deep learning applications. Scholars can improve the accuracy and dependability of deep learning models for diagnosing plant diseases by giving preference to datasets with favorable GLCM metrics. The research also emphasizes the importance of texture features being taken into account in addition to conventional image features, highlighting the necessity of transparency and rigor in dataset selection procedures.

Green open spaces (GOS) are well known to be vital to enhancing the standard of living conditions in urban environments. The World Health Organization (WHO) says it is important to have at least nine square meters per citizen. The European Environment Agency (EEA) stipulates that 5000 square meters of green space will be reachable within 300 meters to residents. GOS pattern in Kyrenia Region is not adequate or successful in that regard. The process of urban planning has been neglected in the Kyrenia region and these areas have lost their significance and value. This research evaluates the level of accessibility of green spaces in Kyrenia Region. Three urban areas, Kyrenia, Karavas and Agios Epiktitos have been analyzed within this framework. In order to do that, GOS areas and their pattern are researched by deploying geographical information analysis. Accessibility to these areas is measured by using Euclidean and network distance analysis based on 300, 800 and 5000 meters. Mainly, Euclidean distance and network distance methods are measured from building units and results showing accessibility values are constructed. According to the results, network accessibility is very low within the study region. Additionally, Kyrenia, Karavas and Agios Epiktitos have shortage in GOS per capita. To offer effective strategies for urban planning, the factors influencing the accessibility and also the usage of GOS are addressed.

Human language is a prime example of a complex system characterized by multiple scales of description. Understanding its origins and distinctiveness has sparked investigations with very different approaches, ranging from the Universal Grammar to statistical analyses of word usage, all of which highlight, from different angles, the potential existence of universal patterns shared by all languages. Yet, a cohesive perspective remains elusive. In this paper we address this challenge. First, we provide a basic structure of universality, and define recursion as a special case thereof. We cast generative grammars of formal languages, the Universal Grammar and the Greenberg Universals in our basic structure of universality, and compare their mathematical properties. We then define universality for writing systems and show that only those using the rebus principle are universal. Finally, we examine Zipf's law for the statistics of word usage, explain its role as a complexity attractor, and explore its relation to universal writing systems as well as its similarities with universal Turing machines. Overall, we find that there are two main kinds of universality, termed {\it mechanistic} and {\it emergent}, and unveil some connections between them.

Background: The aim of this study was to analyze the relationship between breastfeeding duration and adenoid size, snoring and acute otitis media (AOM). Methods: We analyzed the medical history, reported symptoms, ear, nose and throat (ENT) examination, and flexible nasopharyngoscopy examination of 145 children aged 3-5 years. Results: Breastfeeding duration of 3 and 6 months or more had a significant effect on the reduction of snoring (p = 0.021; p = 0.039). However, it had no effect on the adenoid size, mucus coverage and sleeping with an open mouth. Snoring was correlated with open mouth sleeping (p < 0.001), adenoid size with a 75% A/C ratio or more (p < 0.001), and adenoid mucus coverage in the Mucus of Adenoid Scale by Nasopharyngoscopy Assessment - MASNA scale (p = 0.009). Children who were breastfed for less than 3 months had more than a 4-fold greater risk of snoring. There was a statistically significant correlation between AOM and gender (p = 0.033), breastfeeding duration in groups fed 1, 3 or 6 months or more (p = 0.018; p = 0.004; p = 0.004) and those fed with mother’s breast milk 3 or 6 months or more (p = 0.009; p = 0.010). Moreover, a correlation was found between adenoid size and mucus coverage, tympanogram, and open-mouth sleeping (p < 0.001). Independent factors of snoring in 3- to 5-year-old children were breastfeeding duration of less than 3 months (p = 0.032), adenoid size with an A/C ratio of 75% or more (p = 0.023) and open mouth sleeping (p = 0.001). Conclusion: Children breastfed for 3 and 6 months or more exhibited reduced rates of snoring. There was no effect of breastfeeding duration on adenoid size in children aged 3 to 5 years, suggesting that the link between breastfeeding duration and snoring is primarily associated with craniofacial development and muscle tone stimulation. A breastfeeding duration of 1 month or more plays a key role in reducing the rate of AOM. The mother’s milk plays a protective role against AOM. The presence of mucus might be responsible for snoring in preschool children. A medical history of breastfeeding should be taken into consideration when snoring children are suspected of adenoid hypertrophy.

Static and dynamic analysis of website security risks is generally used for website security meas-urements. The website security measurements method recently proposed includes similarity hash-based website security risk analysis and machine learning-based website security risk anal-ysis. In this study, a method that can be performed through information disclosed on the Internet was proposed to measure the risk of a website. DNS information, IP information, and website history information are required to measure the risk of a website. In addition, global traffic rank-ing, malicious code distribution history, and HTTP access status can be checked in the website history information. In this study, information related to the security risk of websites in a total of 2,000 domains was collected and analyzed in 1,000 normal and malicious domains. Through the experiment results, 11 open information collection items were selected to measure the security risk of the website. This study presented the possibility of using public information collection to measure website security risk.

Electroencephalography (EEG) is a crucial tool in cognitive neuroscience, enabling the study of neurophysiological function by measuring the brain's electrical activity. Its applications are included perception, learning, memory, language, decision-making and neural network mapping. Recently, interest has surged in extending EEG measurements to domestic environments. However, the high costs associated with traditional laboratory EEG systems have hindered accessibility for many individuals and researchers in education, research, and medicine. To tackle this, a mobile-EEG device named "DreamMachine” was developed. A more affordable alternative to both lab-based EEG systems and existing mobile-EEG devices. This system boasts 24-channels, 24-bit resolution, up to 6 hours of battery life, portability and a low price. Our open-source and open-hardware approach empowers cognitive neuroscience, especially in education, learning, and research, opening doors to more accessibility. This paper introduces the DreamMachine's design and compares it with the lab-based EEG system "asalabTM" in an eyes-open and eyes-closed experiment. The Alpha band exhibited higher power in the power spectrum during eyes-closed conditions, whereas the eyes-open condition showed increased power specifically within the Delta frequency range. Our analysis confirms that the DreamMachine accurately records brain activity, meeting the necessary standards when compared to the asalabTM system.

We consider open non-twist Hamiltonian systems represented by an area-preserving two-dimensional map describing incompressible planar flows in the reference frame of a propagating wave, and possessing exits through which map orbits can escape. The corresponding escape basins have a fractal nature that can be revealed by the so-called basin entropy, a novel concept developed to quantify final-state uncertainty in dynamical systems. Since the map considered violates locally the twist condition, there is a shearless barrier that prevents global chaotic transport. In this paper we show that it is possible to determine the shearless barrier breakup by considering the variation of the escape basin entropy with a tunable parameter.

Machine learning has seen enormous growth in the last decade, with healthcare being a prime application for advanced diagnostics and improved patient care. The application of machine learning for healthcare is particularly pertinent in Africa, where many countries are resource-scarce. However, it is unclear how much research on this topic is arising from African institutes themselves, which is a crucial aspect for applications of machine learning to unique contexts and challenges on the continent. Here, we conduct a bibliometric study of African contributions to research publications related to machine learning for healthcare, as indexed in Scopus, between 1993 and 2022. We identified 3,772 research outputs, with most of these published since 2020. North African countries currently lead the way with 64.5% of publications for the reported period, yet Sub-Saharan Africa is rapidly increasing its output. We found that international support in the form of funding and collaborations is correlated with research output generally for the continent, with local support garnering less attention. Understanding African research contributions to machine learning for healthcare is a crucial first step in surveying the broader academic landscape, forming stronger research communities, and providing advanced and contextually aware biomedical access to Africa.

This study proposes a structure for companies to use when implementing human resource practices in open innovation. Despite the fact that open innovation has received a lot of attention in the innovation management field as companies open their doors to information exchange in an effort to spur creative thinking, there are very few empirical articles that connect this trend to the human resource management literature. Our findings are the result of an extensive qualitative investigation into Julphar Gulf Pharmaceutical Industries Manufacturers in the United Arab Emirates (UAE) and its open innovation program. Internal, external, and combined are the three primary pillars of human resource management. We also demonstrate how the evolution of the open innovation initiative is linked to the state of the art in HRM and open innovation literature. The framework identifies HRM practices for both internal and external participants in the open innovation effort. Much of this HRM is done off the books, in a setting separate from the host company. By providing actual evidence of how firms use HRM to manage open innovation projects, our research adds to the scant and mostly theoretical literature linking open innovation and HRM.

Background: The human mind is multimodal. Yet most behavioral studies rely on century-old measures such as task accuracy and latency. To create a better understanding of human behavior and brain functionality, we should introduce other measures and analyze behavior from various aspects. However, it is technically complex and costly to design and implement the experiments that record multiple measures. To address this issue, a platform that allows synchronizing multiple measures from human behavior is needed. Method: This paper introduces an opensource platform named OpenSync, which can be used to synchronize multiple measures in neuroscience experiments. This platform helps to automatically integrate, synchronize and record physiological measures (e.g., electroencephalogram (EEG), galvanic skin response (GSR), eye-tracking, body motion, etc.), user input response (e.g., from mouse, keyboard, joystick, etc.), and task-related information (stimulus markers). In this paper, we explain the structure and details of OpenSync, provide two case studies in PsychoPy and Unity. Comparison with existing tools: Unlike proprietary systems (e.g., iMotions), OpenSync is free and it can be used inside any opensource experiment design software (e.g., PsychoPy, OpenSesame, Unity, etc., https://pypi.org/project/OpenSync/ and https://github.com/moeinrazavi/OpenSync_Unity). Results: Our experimental results show that the OpenSync platform is able to synchronize multiple measures with microsecond resolution.

We explore gaps in Wikipedia's coverage of the visual arts by comparing the representation of 100 artists and 100 artworks from the Western canon against corresponding sets of notable artists and artworks from non-Western cultures. We measure the coverage of these two sets of topics across Wikipedia as a whole and for its individual language versions. We also compare the coverage for Wikimedia Commons and Wikidata, sister-projects of Wikipedia that host digital media and structured data. We show that all these platforms strongly favour the Western canon, giving many times more coverage to Western art. We highlight specific examples of differing coverage of visual art inside and outside the Western canon. We find that European language versions of Wikipedia are generally more "Western" in their coverage and Asian languages more "global", with interesting exceptions. We suggest how both Wikipedia and the wider cultural sector can address this gap in content and thus give Wikipedia a truly global perspective on the visual arts.

Preprints are regularly cited in peer reviewed journal articles, books and conference paper. Are preprint citations somehow less important than citations to peer reviewed research papers? This study investigates citation patterns between 2017 and 2020 for preprints published in three preprint servers, one specializing in biology (bioRxiv), one in chemistry (ChemRxiv), and another hosting preprints in all disciplines (Research Square). As evaluation of scholarship continues to largely rely on citation-based metrics, this analysis and its outcomes will be useful to inform new research-based education in today’s scholarly communication.

Machine learning applications often need large amounts of training data to perform well. Whereas unlabeled data can be easily gathered, the labeling process is difficult, time-consuming, or expensive in most applications. Active learning can help solve this problem by querying labels for those data points that will improve the performance the most. Thereby, the goal is that the learning algorithm performs sufficiently well with fewer labels. We provide a library called scikit-activeml that covers the most relevant query strategies and implements tools to work with partially labeled data. It is programmed in Python and builds on top of scikit-learn.

As 180-degree meanders are observed in abundance in nature, a meandering channel with two consecutive 180-degree bends was designed and constructed to investigate bed topography variations. These two 180-degree mild bends are located between two upstream and downstream straight paths. In this study, different mean velocity to critical velocity ratios have been tested at the upstream straight path to determine the meander's incipient motion. To this end, bed topography variations along the meander and the downstream straight path were addressed for different mean velocity to critical velocity ratios. In addition, the upstream bend's effect on the downstream bend has been investigated. Results indicated that the maximum scour depth at the downstream bend has increased as a result of changing the mean velocity to critical velocity ratio from 0.8 to 0.84, 0.86, 0.89, 0.92, 0.95, and 0.98 by respectively 1.5, 2.5, 5, 10, 12, and 26 times. Moreover, increasing the ratio increased the maximum sedimentary height by 3, 10, 23, 48, 49, and 56 times. The upstream bend's incipient motion was observed for the mean velocity to critical velocity ratio of 0.89, while the downstream bend was equal to 0.78.

Student retention is one indicator of accountability in the implementation of educational programs. Achievement of student retention rates indicates the performance of the quality objectives of an institution or college. To get an accurate picture of the factors related to retention, we need to do modeling. The retention variable is the time response variable measured in semester units. One of the statistical analyzes that can be used to analyze response data in time is survival analysis. The selection of an accurate analytical method in modeling will produce valid conclusions and impact making policies that are right and on target. This paper presents alternative modeling of student retention in distance education using survival analysis. The method used is a literature review. This paper also briefly describes distance education, open and distance education, distance education students' characteristics, distance education student retention, and survival models for modeling student retention in distance education.

The ability to replicate scientific experiments is a cornerstone of the scientific method. Sharing ideas, workflows, data, and protocols facilitates testing the generalizability of results, increases the speed that science progresses, and enhances quality control of published work. Fields of science such as medicine, the social sciences, and the physical sciences have embraced practices designed to increase replicability. Granting agencies, for example, may require data management plans and journals may require data and code availability statements along with the deposition of data and code in publicly available repositories. While many tools commonly used in replicable workflows such as distributed version control systems (e.g. “git”) or scripted programming languages for data cleaning and analysis may have a steep learning curve, their adoption can increase individual efficiency and facilitate collaborations both within entomology and across disciplines. The open science movement is developing within the discipline of entomology, but practitioners of these concepts or those desiring to work more collaboratively across disciplines may be unsure where or how to embrace these initiatives. This article is meant to introduce some of the tools entomologists can incorporate into their workflows to increase the replicability and openness of their work. We describe these tools and others, recommend additional resources for learning more about these tools, and discuss the benefits to both individuals and the scientific community and potential drawbacks associated with implementing a replicable workflow.

We present a generic and open-source framework for the numerical modeling of the expected transport and storage mechanisms in unconventional gas reservoirs. These unconventional reservoirs typically contain natural fractures at multiple scales. Considering the importance of these fractures in shale gas production, we perform a rigorous study on the accuracy of different fracture models. The framework is validated against an industrial simulator and is used to perform a history-matching study on the Barnett shale. This work presents an open-source code that leverages cutting-edge numerical modeling capabilities like automatic differentiation, stochastic fracture modeling, multi-continuum modeling and other explicit and discrete fracture models. We modified the conventional mass balance equation to account for the physical mechanisms that are unique to organic-rich source rocks. Some of these include the use of an adsorption isotherm, a dynamic permeability-correction function, and an embedded discrete fracture model (EDFM) with fracture-well connectivity. We explore the accuracy of the EDFM for modeling hydraulically-fractured shale-gas wells, which could be connected to natural fractures of finite or infinite conductivity, and could deform during production. Simulation results indicates that although the EDFM provides a computationally efficient model for describing flow in natural and hydraulic fractures, it could be inaccurate under these three conditions: 1. when the fracture conductivity is very low. 2. when the fractures are not orthogonal to the underlying Cartesian grid blocks, and 3. when sharp pressure drops occur in large grid blocks with insufficient mesh refinement. Each of these results are very significant considering that most of the fluids in these ultra-low matrix permeability reservoirs get produced through the interconnected natural fractures, which are expected to have very low fracture conductivities. We also expect sharp pressure drops near the fractures in these shale gas reservoirs, and it is very unrealistic to expect the hydraulic fractures or complex fracture networks to be orthogonal to any structured grid. In conclusion, this paper presents an open-source numerical framework to facilitate the modeling of the expected physical mechanisms in shale-gas reservoirs. The code was validated against published results and a commercial simulator. We also performed a history-matching study on a naturally-fractured Barnett shale-gas well considering adsorption, gas slippage & diffusion and fracture closure as well as proppant embedment, using the framework presented. This work provides the first open-source code that can be used to facilitate the modeling and optimization of fractured shale-gas reservoirs. To provide the numerical flexibility to accurately model stochastic natural fractures that are connected to hydraulically-fractured wells, it is built atop other related open-source codes. We also present the first rigorous study on the accuracy of using EDFM to model both hydraulic fractures and natural fractures that may or may not be interconnected.

Thermal-based actuators are known for generating large force and displacement strokes at mesoscale (millimeter) regime. In particular, two-phase thermal actuators are found to benefit from the scaling laws of physics at mesoscale to offer large force and displacement strokes; but they have low thermal efficiencies. As an alternative, a combustion-based thermal actuator is proposed and its performance is studied in both open and closed cycle operations. Through a physics-based lumped-parameter model, we investigate the behavior and performance of the actuator using a spring-mass-damper analogy and taking an air standard cycle approach. Three observations are reported: (1) the mesoscale actuator can generate peak forces of up to 400 N and displacement strokes of about 16 cm suitable for practical applications; (2) an increase in heat input to the actuator results in increasing the thermal efficiency of the actuator for both open and closed cycles; and (3) for a specific heat input, both the open and closed cycle operations respond differently \textemdash different stroke lengths, peak pressures, and thermal efficiencies.

Changes brought about by the Internet to Scholarly Communication and the spread of Open Access movement, have made it possible to increase the number of potential readers of published research dramatically. This two-phase study aims, at first, to assert the satisfaction of the potential for increased open access to articles published by authors at the University of Coimbra, in a context when there was no stimulus for the openness of published science other than an institutional mandate set by the University policy on Open Access (“Acesso Livre”). The satisfaction of the access openness was measured by observing the actual archiving behavior of researchers (either directly or through their agents). We started by selecting the top journal titles used to publish the STEM research of the University of Coimbra (2004-2013) by using Thomson Reuters’ Science Citation Index (SCI). These titles were available at the University libraries or through online subscriptions, some of them in open access (21%). By checking the journals' policy at the time regarding self-archiving at the SHERPA/RoMEO service, we found that the percentage of articles in Open Access (OA) could rise to 80% if deposited at Estudo Geral, the Institutional Repository of the University of Coimbra, as prescribed by the Open Access Policy of the University. As we concluded by verifying the deposit status of every single paper of researchers of the University that published in those journals, this potential was far from being fulfilled, despite the existence of the institutional mandate and favorable editorial conditions. We concluded, therefore, that an institutional mandate was not sufficient by itself to fully implement an open access policy and to close the gap between publication and access. The second phase of the study, to follow, will rescan the status of published papers in a context where the Portuguese public funding agency, the Fundação para a Ciência e a Tecnologia, introduced in 2014 a new significant stimulus for open access in science. The FCT Open Access Policy stipulates that publicly funded published research must be available as soon as possible in a repository of the Portuguese network of scientific repositories, RCAAP, which integrates the Estudo Geral.

The authors introduce the GRASS GIS add-on module g.citation as an initial implementation of a fine-grained software citation concept. The module extends the existing citation capabilities of GRASS GIS, which until now only provide for automated citation of the software project as a whole, authored by the GRASS Development Team, without reference to individual persons. The functionalities of the new module enable individual code citation for each of the over 500 implemented functionalities, including add-on modules. Three different classes of citation output are provided in a variety human- and machine-readable formats. The implications of this reference implementation of scientific software citation for both for the GRASS GIS project and the OSGeo foundation are outlined.

Much of the debate on Plan S seems to concentrate on how to make toll access journals open access, taking for granted that existing open access journals are Plan S compliant. We suspected this was not so, and set out to explore this using DOAJ's journal metadata. We conclude that an overwhelmingly large majority of open access journals are not Plan S compliant, and that it is small HSS publishers not charging APCs that are least compliant and will face major challenges with becoming compliant. Plan S need to give special considerations to smaller publishers and/or non-APC-based journals.

Energy system models have become indispensable to shape future energy systems by providing insights into different trajectories. However, sustainable systems with high shares of renewable energy are characterized by growing cross-sectoral interdependencies and decentralized structures. To capture important properties of increasingly complex energy systems, sophisticated and flexible modelling tools are needed. At the same time open science becomes increasingly important in energy system modelling. This paper presents the Open Energy Modelling Framework (oemof) as a novel approach in energy system modelling, representation and analysis. The framework forms a toolbox to construct comprehensive energy system models and has been published open source under a free license. With a collaborative development based on open processes the framework seeks for a maximum level of participation and transparency to facilitate open science principles in energy system modelling. Based on a generic graph based description of energy systems it is well suited to flexibly model complex cross-sectoral systems and incorporate various modelling approaches. This makes the framework a multi-purpose modelling environment for modelling and analyzing different systems ranging from an urban to a transnational scale.

Given a stream of depth images with a known cuboid reference object present in the scene, we propose a novel approach for accurate camera tracking and volumetric surface reconstruction in real-time. Our contribution in this paper is threefold: (a) utilizing a priori knowledge of the cuboid reference object, we keep drift-free camera tracking without explicit global optimization; (b) we improve the fineness of the volumetric surface representation by proposing a prediction-corrected data fusion strategy rather than simple moving average, which enables accurate reconstruction of high-frequency details such as sharp edges of objects and geometries of high curvature; (c) we introduce a benchmark dataset CU3D containing both synthetic and real-world scanning sequences with ground-truth camera trajectories and surface models for quantitative evaluation of 3D reconstruction algorithms. We test our algorithm on our dataset and demonstrate its accuracy compared with other state-of-the-art algorithms. We release both our dataset and code as opensource1 for other researchers to reproduce and verify our results.

UV-A (ca. 365 nm wavelength, a.k.a. 'black light') photocatalysis has been investigated to comprehensively mitigate odor and selected air pollutants in the livestock environment. This study was conducted to confirm the performance of UV-A photocatalysis on the swine farm. The objectives of this research were to (1) scale-up of the UV-A photocatalysis treatment, (2) evaluate the mitigation of odorous gases from swine slurry pit, and (3) test different UV sources, (4) evaluate the effect of suspended particulate matter (PM), and (5) conduct preliminary economic analyses. We tested UV-A photocatalysis at a mobile laboratory-scale capable of treating ~0.2 - 0.8 m3·s-1 of barn exhaust air. The targeted gaseous emissions of barn exhaust air were significantly mitigated (p < 0.05) up to 40% reduction of measured odor; 63%, 44%, 32%, 40%, 66%, and 49% reduction of dimethyl disulfide, isobutyric acid, butanoic acid, p-cresol, indole, and skatole, respectively; 40% reduction of H2S; 100% reduction of O3; and 13% reduction of N2O. The PM mitigation effect was not significant. Formaldehyde levels did not change, and a 21% generation of CO2 was observed. The percent reduction of targeted gases decreased as the airborne PM increased. Simultaneous chemical and sensory analysis confirmed that UV-A treatment changed the overall nuisance odor character of swine barn emissions into weaker manure odor with 'toothpaste and 'mint' notes. The smell of benzoic acid generated in UV-A treatment was likely one of the compounds responsible for the less-offensive overall odor character of the UV-treated emissions. Results are needed to inform the design of a farm-scale trial, where the interior barn walls can be treated with the photocatalyst, and foul air will be passively treated as it moves through the barn.

(1) Aim of the study was to investigate the spatial and temporal characteristics of the airflow created by two commercially available non-contact tonometers, the CorvisST and the Ocular Re-sponse Analyser. (2) The airflow pressure was measured using a MEMS pressure sensor to inves-tigate the spatial and temporal distribution. The airflow from the CorvisST and Ocular Response Analyser were mapped to a 600µm and a 1mm resolution grid, respectively. (3) Central airflow pressure of the CorvisST (96.4 ± 1.4)mmHg was higher than the Ocular Response Analyser (91.7 ± 0.7)mmHg. The duration of the air-puffs also differed, with the CorvisST showing a shorter du-ration (21.483 ± 0.2881)ms than the ORA (23.061 ± 0.1872)ms. The rising edge of the CorvisST airflow pressure profile demonstrated a lower gradient (+8.94mmHg/ms) compared to the Oc-ular Response Analyser (+11.00mmHg/ms). Both had similar decay response edges; CorvisST -11.18mmHg/ms, Ocular Response Analyser -11.65mmHg/ms. (4) The study presents a valid method to investigate physical dimensions of the airflow pressure of non-contact tonometers. Novel findings relating to the magnitude, duration and spatial characteristics of the respective airflow pressures are reported. It is anticipated that this information will better inform clinical studies and theoretical models relating to ocular biomechanics.

Environmental impact associated with odor and gaseous emissions from animal manure is one of the challenges for communities, farmers, and regulatory agencies. Microbe-based manure additives treatments are marketed and used by farmers for mitigation of emissions. However, their performance is difficult to assess objectively. Thus, comprehensive, practical, and low-cost treatments are still in demand. We have been advancing such treatments based on physicochemical principles. The objective of this research was to test the effect of the surficial application of a thin layer (¼"; 6.3 mm) of biochar on the mitigation of gaseous emissions (as the percent reduction, % R) from swine manure. Two types of biochar were tested: highly alkaline and porous (HAP) biochar made from corn stover and red oak (RO), both with different pH and morphology. Three 30-day trials were conducted with a layer of HAP and RO (2.0 & 1.65 kg∙m^-2, respectively) applied on manure surface, and emissions of ammonia (NH₃), hydrogen sulfide (H₂S), greenhouse gases (GHG), and odorous volatile organic compounds (VOCs) were measured. The manure and biochar type and properties had an impact on the mitigation effect and its duration. RO significantly reduced NH₃ (19-39%) and p-cresol (66-78%). H₂S was mitigated (16~23%), but not significantly for all trials. Significant (66~78%) reductions for p-cresol were observed for all trials. The phenolic VOCs had relatively high % R in most trials but not significantly for all trials. HAP reduced NH₃ (4~21%) and H₂S (2~22%), but not significantly for all trials. Significant % R for p-cresol (91~97%) and skatole (74~95%) were observed for all trials. The % R for phenol and indole ranged from (60~99%) & (29~94%) but was not significant for all trials. The impact on GHGs, isobutyric acid, and the odor was mixed with some mitigation and generation effects. However, larger-scale experiments are needed to understand how biochar properties and the dose and frequency of application can be optimized to mitigate odor and gaseous emissions from swine manure. The lessons learned can also be applicable to surficial biochar treatment of gaseous emissions from other waste and area sources.

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.

Accurate prediction of mercury content emitted from fossil-fueled power stations is of utmost importance for environmental pollution assessment and hazard mitigation. In this paper, mercury content in the output gas of power stations’ boilers was predicted using an adaptive neuro-fuzzy inference system (ANFIS) method integrated with particle swarm optimization (PSO). The input parameters of the model include coal characteristics and the operational parameters of the boilers. The dataset has been collected from 82 power plants and employed to educate and examine the proposed model. To evaluate the performance of the proposed hybrid model of ANFIS-PSO model, the statistical meter of MARE% was implemented, which resulted in 0.003266 and 0.013272 for training and testing, respectively. Furthermore, relative errors between acquired data and predicted values were between -0.25% and 0.1%, which confirm the accuracy of the model to deal nonlinearity and representing the dependency of flue gas mercury content into the specifications of coal and the boiler type.

Abstract: In order to accelerate deployment of distributed recycling by providing low-cost feed stocks of granulated post-consumer waste plastic, this study analyzes an open source waste plastic granulator system. It is designed, built and tested for its ability to convert post-consumer waste, 3-D printed products and waste into polymer feedstock for recyclebots of fused particle/granule printers. The technical specifications of the device are quantified in terms of power consumption (380 to 404W for PET and PLA, respectively) and particle size distribution. The open source device can be fabricated for less than USD$2000 in materials. The experimentally-measured power use is only a minor contribution to the overall embodied energy of distributed recycling of waste plastic. The resultant plastic particle size distributions were found to be appropriate for use in both recyclebots and direct material extrusion 3-D printers. Simple retrofits are shown to reduce sound levels during operation by 4dB-5dB for the vacuum. These results indicate that the open source waste plastic granulator is an appropriate technology for community, library, makespace, fab lab or small business-based distributed recycling.

Both, in developed and developing countries, atmospheric pollution with particulate matter (PM) remains an important issue. Despite the health effects of poor air quality, studies on air pollution are often limited by the high costs of continuous monitoring and the need of extensive sampling. Furthermore, these particles are often enriched in potentially toxic trace elements and organics pollutants. This study evaluates both, the composition of atmospheric dust accumulated during a certain time-span on leaves of Hedera helix and Senecio cineraria, as well as the potential to use them as bio-monitors. The test plants were positioned nearby automatic air quality monitoring stations at four different sites with respectively high, moderate and low traffic intensity. Gravimetric deposition of PM10 and PM2.5 on leaves was consistent with data recorded by the monitoring stations and related to the weather conditions reported by Argentina´s National Meteorological service. To determine the presence of trace elements enriching the PM deposited on leaves, two analytical techniques were applied, XRF (not destructive) and ICP (destructive). The results indicated that only in the unpaved street location (site 2), PM10 and PM2.5 concentrations in the air exceeded WHO guidelines. However, several trace elements were found enriching PM deposited on leaves from all sites. Predominantly, increased concentrations of Cd, Cu, Ti, Mn, Zn and Fe were found, which were associated to construction, traffic and unpaved street sources. Furthermore, based on its high capability to sequester PM and trace elements Senecio cineraria can be take into consideration to be adopted as a bio-monitor or even for PM mitigation.

This study focuses on the use of gamification, specifically the UrbanGame activity, to enhance heritage education related to the Spanish Civil War bombings in Alicante. The research aims to evaluate the effectiveness of active methodologies in raising cultural heritage awareness among university students. By employing a combination of collaborative work, meaningful learning, problem-based learning, discovery learning, concentration, and motivational strategies, the study involved 122 students from primary and secondary education programs. The methods included the design and implementation of the UrbanGame, followed by surveys to collect quantitative and qualitative data on students' perceptions, satisfaction, and learning outcomes. The results indicated that while collaborative work did not have a significant impact on content comprehension, skill acquisition, or value acquisition, meaningful learning showed a positive trend towards content comprehension. Problem-based learning had a weak but notable relationship with content comprehension, while motivation and concentration significantly influenced learning outcomes. Additionally, the UrbanGame activity promoted memory and cultural heritage by emotionally connecting students with local history. The findings suggest that an integrated approach that combines various active methodologies is essential for maximizing educational effectiveness and cultural promotion.

Criteria air pollutant exposure has always been a major factor that negatively impacts human health through different pathways. One of the critical concerns is adverse birth outcomes associated with criteria air pollutant exposure such as low birth weight, preterm births, neonatal mortality, etc. Recent studies show that criteria air pollutant exposures are strongly associated with the elevated risk of preterm births defined as any birth occurring before 37 weeks of gestation. Bangladesh is one of the most polluted and has the highest preterm birth rate compared to other countries of the world. Although numerous global and regional studies investigate the impacts of criteria air pollutant exposure on preterm births, limited studies are available that investigated the impacts of the major criteria air pollutants on preterm births in recent years for Bangladesh. In this study, we employ the criteria air pollution data from the MERRA-2 model and satellite-sensed data regionally scaled for Bangladesh from NASA Giovanni (version 4.38) coupled with exposure-response modeling to quantify the impacts of CO, O₃, PM_2.5, SO₂, and NO₂ exposure on preterm births in Bangladesh during the 2015-2019 period. Based on the air quality analysis, the highest CO, O₃, PM_2.5, SO₂, and NO₂ exposures were observed in 2018 up to 272.8 /m³, 88.2 ppbv, 62.9 /m³, 20.5 /m³, and 11.6 ppbv respectively. This elevated amount of criteria air pollutant exposure has had direct implications for the increased rate of preterm births in Bangladesh. During 2015-2019, CO, O₃, PM_2.5, SO₂, and NO₂ exposures from all natural and anthropogenic emissions combinedly caused from 0.18 million [95% confidence interval (95CI): 0.08 – 0.29 million] up to 0.20 million [95CI: 0.08 – 0.32 million] preterm births among 4.3 million annual total live births each year which indicated a 4.4-4.9% preterm birth rate exclusively attributable to criteria air pollutant exposure in Bangladesh. Our study is critical for the overall wellbeing of the under-represented women and children in Bangladesh as it facilitates the quantitative evidence of preterm births caused by major air pollutant exposure and advocates the reduction of countrywide air pollution and establishment of well-aware community by facilitating low-cost air quality monitoring system in each household, necessary reformation of pollution prevention policies & regulations in national level and strict as well as vigilant law enforcement on human activities that causes air pollution.

In the last decades, numerous studies indicated the substantial role semiconductors could play in photocatalytic processes for environmental applications. Materials that contain a semi-conductor as a photo-catalyst have a semi-permanent capacity for removing harmful gases from the ambient air. In the present work, the focus is on TiO2. Heterogeneous photo-catalysis using TiO2 leads to the degradation of NO/NO2, benzene, toluene, and other priority air pollutants once in contact with the semiconductor surface. Preliminary evidence indicates that TiO2 containing construction materials and paints efficiently destroy the ozone precursors NO and NO2 up to 80% and 30%, respectively. Therefore, the development of innovative coatings containing TiO2 as a photo-catalyst was in the foreground of research activities with the aim to be used as building and construction materials mainly outdoors, e.g. on building facades in high traffic roads for the degradation of priority air pollutants (NOx and volatile organic compounds) in the polluted urban atmosphere. Though the advantages connected with the application of TiO2 due to its band gap of 3.2 eV are limited. TiO2 is effective only in the UV-region (ca. 5%) of the solar spectrum with wavelengths λ

(1)Background：To date, no studies have epidemiologically examined whether the concentration of particulate matter (PM) 2.5 and its ionic components is related to the prevalence of skin symptoms. Therefore, this study aimed to clarify this association in patients with allergic diseases. (2)Methods: From February 1 to May 31, 2020, we evaluated the daily prevalence of skin symptoms in outpatients with allergic diseases being treated at Fukuoka Hospital, Fukuoka, Japan, and measured the concentration of PM2.5 and its ionic components. （3）Results: Univariate analysis showed a statistically significant association between skin symptoms and the concentration of PM2.5 and the ionic components SO42-, NH4+, K+, and Mg2+, and multivariate analysis showed a statistically significant association between the daily prevalence of skin symptoms and the concentration of the ionic components SO42- or Mg2+. (4)Conclusions: Our findings indicate that the concentration of some PM2.5 ionic components may affect skin symptoms in patients with allergic diseases.

Spray penetration into citrus canopies is critical for adequate coverage and deposition to ensure effective pest control. However, mismatch of air assistance to target canopy characteristics can lead to unintended spray loss through over penetration. To evaluate the effect of air assistance on on-target deposition, two sprayers (surrogates for airflow rates) were used to apply a fluorescent tracer dye solution @ target concentration of 300 ppm to 16 medium foliage density tree blocks in a commercial mandarin orchard. The complete factorial experiment in three replications comprised two ground speeds (1.6 and 4.8 km/h), two disc-core nozzles (TeeJet® D3-25 and D6-45), and either one or two nozzle rows to obtain a wide range of application rates (496 to 9,719 L/ha). Dye deposition significantly decreased with canopy depth (p=&lt;0.001) by nearly 7 times across the 3.4-m-wide canopies but was not significant over 1.2 to 2.2 m sampling height (p=0.867). Deposition obtained with the low airflow rate sprayer was significantly greater (p=&lt;0.001) than that obtained with the high airflow rate sprayer over the dose range likely due to too much air pushing out spray droplets. This study underscores the importance of matching the air assistance of orchard sprayers to the target canopy.

Ethiopian Airlines is a leading airline in the world. Its supply chain management is one of the most critical aspects in achieving its sustainability objectives. The present study aims to assess the sustainability practices and strategies of Ethiopian Airways in its supply chain, identifying areas for improvement and recommending strategies for enhancing sustainability. The study concentrates on pertinent sustainability concerns within the aviation sector while examining antecedent research on the sustainability of Ethiopian Airlines’ supply chain management strategies. The findings of the study reveal that there are several areas in need of improvement, including the implementation of waste reduction measures, the establishment of a recycling program, and the reduction of single-use plastic usage. It is suggested that promoting responsible tourism embodying sustainable practices is imperative, particularly within the airline context.

In this paper we present a city-scale (possibly global) air pollution network made of low-cost sensors for particulate matter concentration in the air. The components of presented system are based on our research and experience from previous studies focused on air quality instruments and sensors for addressing urban air pollution. Sensor nodes are produced locally and distributed over a city of Sarajevo, Bosnia and Herzegovina. The system collects, calibrates and displays particulate metal concentrations in real-time. In comparison to the available measurements from governmental institutions, our system demonstrated good agreement of measured parameters, with several advantages including: higher resolution in space and time, lower costs, both horizontal and vertical measurements and many more. One of the capabilities of the system is the real-time air pollution city map with animations. By installing multiple sensor nodes over a slope (cable car), we receive vertical measurements of temperature, humidity and particulate matter concentration in real time, which gives a valuable insight into the dynamics of temperature inversion episodes and air pollution below the inversion layer.

Air pollution is a situation that negatively affects the health of humans and all living things in nature and causes financial damage to the environment. In the case of air pollution, harmful and foreign substances in the air reach an amount and density above normal values. Air pollution also causes climate change, which affects global warming. Particulate matter is a harmful substance that harms the health of humans and other living things, causes air pollution, increases radiation, and negatively affects cloud formation. Particulate matter is extremely small solid particles and liquid droplets suspended in the air. PM10, which is less than 10 microns in diameter, is defined as small particles that can remain in the air for a long time and settle in the respiratory tract, damaging the lungs. Many criteria affect PM10 density and changes in density. The main criteria are vehicle traffic and fuel consumption, industrialization, coal, fuel oil and wood-burning heaters, greenhouse gas impact, and unregulated urbanization. It is important to identify the underlying causes of air pollution caused by PM10. In this context, these criteria need to be evaluated to minimize the negative effects of PM10. In the study, monthly average PM10 data between 2019 and 2023 obtained from the Air Monitoring Station in Kocaeli, Türkiye are used. After determining the criteria affecting PM10, the criteria are prioritized with the Intuitionistic Fuzzy AHP (IF-AHP) method by taking expert decision-maker opinions. The proposed decision-making model aims to guide obtaining the important causes of PM10 emission in terms of danger and focusing on these causes. Additionally, PM10 data is analyzed in the context of Covid-19 and a statistical analysis is made. One-way ANOVA is used to evaluate whether there is a significant difference in the average monthly data over the years. Games-Howell test, one of the post-hoc tests, is used for differences between groups (years). The study is important in that it provides a focus on the criteria affecting PM10 with an intuitive fuzzy perspective, along with statistical analysis.

In 2011, commercial aviation contributed approximately 3.5% of global anthropogenic climate change through the emission of greenhouse gases during flight and operational non-CO2 climate effects. Over the last few years, numerous aviation-related organisations have set goals to reduce aviation’s climate impact. These goals, however, lack alignment, are poorly or ambiguously defined, or are internally inconsistent. This increases uncertainty about what aviation should work towards, how various stakeholders can contribute, and introduces problems with respect to accountability. In order to address this issue, this paper presents a comprehensive definition of a climate neutral air transport system as an “air transport system of which the climate effects of all its greenhouse gases and non-carbon dioxide effects throughout the entire life-cycle of each element of the system is balanced”. The proposed definition spans relevant system and encompasses all life cycle phases. To achieve a climate neutral air transport system by 2050, all life-cycle greenhouse gas emissions and non-CO2 climate effects remaining after in-sector reduction should be neutralised, as should all remaining non-CO2 climate forcing from emissions prior to 2050. Clarity on governance is furthermore needed, as the goal and associated targets proposed should be adopted globally.

Inhaled particulate matter (PM) is a key player in the millions of yearly deaths worldwide related to air pollution. The oxidative potential of PM provides an indication of its ability to promote an oxidative environment. When the human lungs are exposed to PM, the reactive oxygen species (ROS) generated in such oxidative environment, if excessive, may lead to cell damage via oxidative stress. Inflammation, endoplasmic reticulum stress, airway remodeling, and many different cell death modes (apoptosis, ferroptosis, pyroptosis, among others) can be triggered by oxidative stress via complex molecular pathways, which also involve the adaptive cellular response. But ROS can also directly interact with macromolecules such as proteins and lipids, as well as nucleic acids, having been reported to induce DNA damage and epigenetic modifications, which jeopardizes homeostasis. These facts have been extensively studied in in vitro models and confirmed in in vivo models.In this review, we delve beyond conventional assessments of airborne particles, discussing their oxidative potential and the PM-induced ROS-mediated cellular damage observed in in vitro models. The close link between oxidative stress and inflammation, and the manifestation of different cell death modes is highlighted by reviewing the latest literature. The effects of ROS on the balance of DNA damage and repair, carcinogenicity and epigenetics interplay are then analyzed. Finally, we expand on the latest reports on the antioxidants’ potential to counteract the deleterious effects of ROS, and disclose future perspectives for the topic.

As the demand for fossil fuels continues to rise and their availability becomes increasingly limited, it is crucial to explore innovative approaches to optimize fuel combustion in existing systems. Among various engines, diesel engines are heavily reliant on fluid motion within the engine cylinder, which plays a critical role in fuel-air mixing. This abstract focuses on the potential of dynamic mathematical model simulation for multi-compartment rotor compressed combustion engines, aiming to revolutionize power generation by enhancing fuel burning efficiency. By leveraging advanced simulation techniques, this research seeks to unlock new insights into fluid dynamics and optimize fuel-air mixing, leading to more efficient and sustainable energy utilization. Through this exploration, we aim to pave the way for groundbreaking advancements in the field of combustion engines, ultimately contributing to a greener and more sustainable future. In the realm of internal combustion engines, the fluid dynamics within the engine cylinder greatly influence the combustion processes and heat transfer. For compression ignition (C.I) engines, both the bulk gas motion and turbulence characteristics play vital roles in engine performance. This study focuses on enhancing the combustibility of the fuel-air mixture in C.I engines by modifying the engine design to induce turbulence through squish and tumble flows. The modification involves creating multiple compartments on the rotor crown, comprising three small chambers spaced 120º apart. By implementing this design, the aim is to optimize the fuel-air mixing and improve the overall combustion efficiency. Through comprehensive analysis and experimentation, we seek to revolutionize C.I engine technology and pave the way for more efficient and environmentally-friendly power generation. In this study, the performance of a compression ignition (C.I) engine with a multiple compartment rotor has been analyzed under motoring conditions using computational fluid dynamics (CFD) simulations with FLUENT software. The obtained results have been compared with those of a base C.I engine. The analysis focused on the effects of the modified engine design on the tumble ratio and squish velocity, which are important parameters for fuel-air mixing and combustion efficiency. The results indicated a significant improvement with the modified engine, with a 35% increase in tumble ratio and a 31% increase in squish velocity compared to the base engine. These findings suggest that the modified engine design has the potential to enhance fuel-air mixing and combustion performance, leading to improved overall engine efficiency. This research presents promising insights into the optimization of C.I engine design and contributes to the development of more efficient and environmentally-friendly power generation technologies..

Highly transparent, conductive nanosheets are extremely attractive for advanced optoelectronic applications. Previously, we have demonstrated that transparent, conductive Au nanosheets can be prepared by UV irradiation of Au nanoparticle (AuNP) monolayers spread on water, which serves as the subphase. In this study, we show that this UV irradiation technique can easily be extended as a nanosheet modification method by using subphases containing metal ions. That is, aqueous solutions containing Au and Ag ions are effective in modifying Au nanosheets. HAuCl4 solutions increased Au nanosheet thickness, which improved conductivity, but reduced transparency. On the other hand, use of aqueous AgNO3 and CH3COOAg solutions yielded Au-Ag hybrid nanosheets; however, their morphologies depended on the electrolytes used. Homogeneous Au-Ag nanosheets from AgNO3 and AuNPs covered with an Ag nanosheet from CH3COOAg were also produced. Further, these Au-Ag hybrid nanosheets had high conductivity without reduced transparency. Therefore, this UV irradiation method, modified by adding metal ions is quite effective at improving and diversifying properties of Au nanosheets.

Over the last few decades, there is a remarkable increase in air traffic worldwide; however, despite of rapid technological development and improved airport infrastructure, there is still an increasing number of aviation accidents and fatalities. In order to meet safety demands of Air Traffic Control (ATC), Machine Learning (ML) based aircraft conflict detection techniques are focused to predict events before they come to reality. This research presents a systematic literature review (SLR) about the applications of ML techniques in safety prediction of ATC system. Initially, the existing aircraft conflict prediction models are classified into three broad categories; logical, geometric and probabilistic. A formal process of SLR is then conducted which is initiated with preprocessing and effective searching. A series of filtering called title, abstract and objective-based are then applied to extract the most relevant articles. Detailed and critical reviews of selected articles are performed to identify challenges which are segregated into dataset, model and evaluation techniques, furthermore, the optimal solutions for each are proposed. Finally the matrices to map the identified challenged with their proposed solutions are constructed. This research serves as a foundation for future research and towards integration of ML based safety prediction techniques into modern ATC system.

The paper presents the relationship between the efficiency of the process of skin onion peeling and its effect in the form of waste. The research was carried out on a pilot test stand for onion peeling. The process variables were compressed air with a pressure of (p) and valve controlling opening time of flow (t). The experiment took into account the influence of the onion diameter (d0) and its hardness (H). The obtained results were subjected to statistical analysis. Standard deviations were of the percentage loss of onion mass in the form of the skin removed of onion peeling in the process in relation to obtained aver-age values. Tukey's multiple comparison test was performed in order to identify the importance of individual process variables on the final effect of onion peeling. This was the basis for the development of a predictive model in the form of a nonlinear regression Mp=f(p,t,d0,H), which is a mathematical description of the peeling onion skin process . Finally, the response surface area of relationship between analyzed variables was determined. The results of research showed the peeling efficiency of the onion and waste of skin mass depend on the compressed air pressure. Extending the onion blowing time does not improve the process efficiency, while the hardness and size of the onion are irrelevant to the process.

The protection of all environmental compartments (water, soil, air) is of great interest for the normal functioning of life on Earth. Namely, the environment is systematically polluted with different concentrations of physical, biological and chemical pollutants. For the purpose of environmental protection, numerous in situ and ex situ biological, chemical and physical remediation techniques have been developed. Most techniques have limitations such as high costs, processing time and environmental feasibility. In general, biological techniques have proven to be the most environmentally friendly compared to chemical and physical techniques. Furthermore, remediation is an extremely complex procedure due to the complexity of the pollutant composition. Therefore, the implementation of individual physical, biological or chemical remediation techniques is often not sufficient for adequate remediation of the polluted environment. Accordingly, for more economical and efficient environmental remediation, it is recommended to use a combination of techniques that should meet the requirements of efficiency and treatment duration. Ultimately, this short review presents a concise overview of the recent application of physical, biological and chemical remediation techniques to all compartments of the polluted environment (water, air, soil). A critical review of existing knowledge on environmental remediation through a search of relevant literature helped to assess the basic challenges and limitations that arise in the issue of environmental remediation, as well as providing recommendations and guidelines for future research.

Background: Fungi are ubiquitous microorganisms that are easily dispersed through the air. In healthcare environments, indoor air can favor the spread of healthcare-associated fungal infections, compromising mainly immunocompromised hospitalized individuals. Thus, this study aimed to evaluate the indoor air contamination in healthcare environments, investigating mainly the presence of potentially pathogenic yeasts. Methods: Indoor air samples were collected from twelve healthcare environments (hospital and medical clinics). After the growth, isolation, and purification of the yeast colonies, the isolates were identified by polymerase chain reaction using species-specific primers for yeasts of the genus Candida and sequencing of D1/D2 domains of the large ribosomal subunit (LSU rRNA). Results: Fourteen yeast species were identified, including emerging pathogens. Species of clinical importance such as Candida parapsilosis, Candida orthopsilosis, Candida glabrata, Rhodotorula mucilaginosa, and Trichosporon mucoides were present. C. Parapsilosis was the most prevalent species, followed by Rodothorula mucilaginosa. Conclusions: The present study shows that potentially fungal pathogens were present in air samples from healthcare environments, proving the role of indoor air in spreading infections. Thus, monitoring air quality in healthcare environments is a fundamental approach in developing infection control measures, especially those related to invasive fungal infections.

The increase and diversity of low-cost Air Quality (AQ) sensors, as well as their flexibility and low power consumption, offers us the opportunity to integrate them into a broad AQ wireless sensor networks with the aim of enabling real-time monitoring and higher spatial sampling density of pollution in all parts of the cities. Considering that the vast majority of the population lives in these cities and the increase in respiratory/allergic problems in a large part of the population, it is of great interest to offer services and applications to improve their quality of life. In the ECO4RUPA project we focus on this kind of service, proposing an inclusive and intelligent routing ecosystem carried out by using a network of low-cost AQ sensors with the support of 5G communications along with official AQ monitoring stations, assisted with artificial intelligence to improve the AQ monitoring data and by spatial interpolation techniques to enhance its spatial resolution. The goal of this service is to calculate healthy walking and/or cycling routes according to the particular citizen’s profile and needs. We provide and analyse the results of the proposed route planner under different scenarios (different time tables, congestion road traffic and routes) and different user’s profiles, with special interest on citizens with asthma and pregnant women, since both require special needs. In summary, our approach can lead to an approximately average reduction in pollution exposure of 17.82%, while experiencing an approximately average increase in distance travelled of 9.8 %.

Reinforcement learning is used for air combat problems in recent years, and the idea of curriculum learning is often used for reinforcement learning, but traditional curriculum learning suffers from the problem of plasticity loss in neural networks. Plasticity loss is the difficulty of learning new knowledge after the network has converged. To this end, we propose a motivational curriculum learning distributed proximal policy optimization (MCLDPPO) algorithm, through which agents trained can significantly outperform the predictive game tree and mainstream reinforcement learning methods. The motivational curriculum learning is to help the agent gradually improve their combat ability by observing the agent's unsatisfactory performance and providing corresponding rewards as a guide. Additionally, a complete tactical maneuver is encapsulated based on existing air combat knowledge, and through the flexible use of these maneuvers, some tactics beyond human knowledge can be realized. In addition, we designed an interruption mechanism for the agent to increase the frequency of decision-making when the agent faces an emergency. When the number of threats the agent receives changes, the current action will be interrupted to reacquire observations and make decisions again. Using the interruption mechanism can significantly improve the ability of the agent. To simulate actual air combat better, we built an air combat environment based on digital twin technology to create an air combat engine core such as missiles and radars. Based on this environment, we develop a distributed intelligent training system that employs Redis as the cache and obtains the data generated in the distributed environment through a multi-threaded TCP/IP protocol, which significantly increases the training data throughput and helps the agent accelerates convergence. The experimental results demonstrate that the agent can fully exploit the situational information to make reasonable decisions and affords air combat tactical adaption, verifying the effectiveness of the algorithmic framework proposed in this paper.

Modern commercial air travel connects disparate human populations with the global airline industry transporting up to 4.5 billion passengers annually in the years leading up to the COVID-19 pandemic. While such connections are convenient for commerce and tourism, air travel networks can also be efficient distributors of infectious diseases such as influenza, SARS-CoV-1, hemorrhagic fevers, and more recently SARS-CoV-2 and monkeypox. During the COVID-19 pandemic, public health agencies used multi-layered control strategies including pre-departure testing and vaccination requirements, masking, post-arrival testing, and quarantine to manage the risk of COVID-19 transmission associated with air travel. Simultaneously, the surveillance of aircraft wastewater emerged as a promising new data source to screen for SARS-CoV-2 infections, including newly emergent lineages, among international air travelers. Herein, we review the potential of aircraft wastewater for public health surveillance. The known contributing population and flight itinerary combined with the highly concentrated waste stream and convenient sampling during routine lavatory servicing make aircraft wastewater a strategic opportunity for unintrusive surveillance of the global fluxes of human pathogens. We estimate for the cases of fecal- or urine-shed pathogens, sampling from 3,500 and 1,250 flights per week, respectively, would be required to survey 10% of all global long-haul flight passengers. In the case of the United States, achieving 10% coverage of all international arrivals would require sampling from 925 and 322 flights per week, respectively. Aircraft wastewater surveillance could also be integrated with network and infectious disease models to better inform traditional public health control measures during emerging epidemics. Given the tremendous potential for public good and the massive economic costs of epidemics, governments should consider international collaboration to create a global aircraft wastewater surveillance system.

Substantial reductions of the human and economic activities like road traffic for several months in 2020 were one of the consequences of the Coronavirus disease. This unprecedented change in urban metabolism also affected temperature and air pollutants. This study investigates the effects of the first COVID-19 lockdown over 43 cities in Europe. It determines the influence of anthropogenic activities on nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5) as well as on land surface temperature (LST), and the surface urban heat island intensity (SUHII), using satellite, modelled, and mobility data. Our findings show that there are great temporal and spatial differences and distinct patterns between the cities regarding the magnitude of change of the variables under study. In general, the results indicate a significant decrease in NO2 concentrations in most of the studied cities compared to the reference period 2015-2019. However, reductions could not be attributed to mobility changes like less traffic at transit stations, contrary to the results of previous studies. O3 levels increased during the first lockdown mainly influenced by the decreasing NO2 concentrations. The PM pattern was inconsistent over time and space. Similar as the NO2 results, no relation to the altered mobility behavior was found. No clear signal could be detected for LST and the SUHII, likely due to dominating meteorological influences. Therefore, single city case studies may be misleading.

Keywords:

Accurate estimation of vehicle emissions is essential and can be helpful in the decision-making process. Thanks to calculation methods, it is possible to accurately estimate the emissions that result from driving a car and to determine their impact on, for example, the health of pedestrians who are on the pavement near an arterial road. Recent years have seen an increase in the use and importance of emission models, as well as vehicle traffic simulation models. Increasingly, emission models are being combined with traffic simulation models, as it is not practical to actually measure the on-road emissions of an entire fleet of vehicles over a given stretch of road. This paper provides an overview of the selected work on the topic of emission modelling and vehicle traffic simulation models. The models are distinguished according to their respective scales of accuracy, i.e., micro, meso, and macro. Selected work combining emission and traffic simulation models is also presented, as well as development trends in the field. In particular, the paper also highlights the fact of proper calibration of vehicle traffic simulation models in order to obtain the most reliable vehicle emissions results from computational models. The review of the works carried out may be helpful for future projects concerning the use of simulation tools for transport and environmental decision-makers in the area of arterial roads.

The research aims to improve some of the physical and hydro-physical properties of some Vertisols in the southern region (part of the eastern Houran Plateau) in Sweda Governorate at the south of Syria. Using different quantities of volcanic ash, soil samples were collected from the Al-Thahallah village from a depth of (0-30) cm, The experiment was designed according to the complete random design with one factor that represents the ash quantity (1.25, 2.5, 5) %, with three replicates for each treatment in addition to the control treatment a0. The experiment was carried out within the plastic pots during agricultural season 2018/2019, in which the wheat of the Sham variety 3 were cultivated as a cover plant. The results showed that the addition of volcanic ash at the quantity of 5% led to a significant increase in the infiltration rate by (328.60) %,%, where the filtration rate increased from 0.42 cm/hr -1 to 1.80 cm.h-1, as well as for each of the air porosity by (89) % and the volume of infiltrate water by (40) %, compared with the control. The above-mentioned addition also resulted in a decrease in both dry bulk density, total soil porosity and volumetric swelling coefficient by (18.60, 5.80, 314) % Respectively, compared to the control. The addition also contributed to the reduce in the weighted moisture content when saturation and the field capacity, at the level of significance of 5%. The research recommends adding volcanic ash to the soil at a quantity of 5%, and adding enhancements with volcanic ash at various levels such as organic waste.