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 band gap research in graphene is still a very important topic for materials application. Here, we report a band gap opening and p-type semiconducting property of the graphene by using an electrochemical doping on graphene surface. The manganese-oxide nanopar-ticles adsorbed on the graphene were used as the dopants in an electrolyte, which induce the band gap opening and the change of electronic structure. In addition, the fabricated graphene FET shows the p-type semiconductor behaviors. The temperature dependent conductivity of the p-type doped graphene at applied potential of 1.5 V during electro-chemical doping shows the formation of band gap of 0.23 eV, which is obtained from the fitting of conductivity equation. The semiconducting properties of manganese-oxide doped graphene is attributed to the formation of manganese-oxide nanoparticle on the surface of graphene.

Heavy metal accumulation in soils used for agricultural purposes is a major issue as it can affect the growth of plants and contain health risks as plants containing heavy metals are taken as food. This study provided the potential of three Bacillus pumilus strains (C-2PMW-8, C-1 SSK-8, and C-1PWK-7) for mitigation of the health factors related to heavy metals on lettuce (Lactuca sativa) grown in chromium contaminated soil from activities related to mining. Lettuce seeds inoculated with B. pumilus strains were grown in pots with garden soil amended with varying amount of chromite mine soil (2.27%, 4.65%, 7.14%). Growth indicators like days to germination, percentage of germination, leaf weight, leaf area and rate of survival decreased with incremental soil chromium levels but improved highly with inoculation of B. pumilus compared to uninoculated controls. When B. pumilus strains were provided, there was also a decreased level in the buildup of chromium in soil as well as lettuce shoots. The results explains that plant growth-promoting B. pumilus strains may be able to lower down the detrimental effects of chromium on lettuce development, hence increment in the effectiveness of phytoremediation.

Hydrogen is considered as an ideal substitute to the traditional fossil fuels because of its widespread sources, high calorific value of combustion, and zero carbon emissions. The electrocatalytic water-splitting to produce hydrogen is also deemed to be the best approach, however, it is a challenge to make high-efficient and low-cost electrocatalysts. Single-atom catalysts (SACs) are considered the most promising candidate to replace the traditional noble-metal catalysts. Compared with SACs, the dual-atom catalysts (DACs) are of greater attraction including higher metal loading, more versatile active sites, and excellent catalytic activity. In the review, several general synthetic strategies and structural characterization methods of DACs are introduced, and the mechanisms of hydrogen evolution reaction (HER) and oxygen evolution reactions (OER) are discussed. The authors hope that the review has given some insights and inspiration to the researchers about DACs in electrocatalytic water-splitting.

This investigation mainly focused on the microstructural analysis of Al based hybrid metal matrix composites. Aluminium as base metal and reinforced with 2% B4 C, ZrO2 (2%,4%,6%), SiC (4%,8%,12%). Specimens were manufactured by using conventional stir casting technique. Hybrid metal matrix composites were examined by using Scanning electron microscope. This research explained XRD, EDS and Fractography analysis. This investigation shows the reinforced material has given better results in all aspects than pure Al6061 alloy and homogeneous dispersion of particles inside the matrix. Porosity, delamination, cracks, particle distributions were observed through microstructural analysis. Additionally determined the crystal size of pure Aluminium 6061 alloy and hybrid composites.

Recent developments in the field of room temperature ferromagnetic metal oxide semiconductors (RTFMOS) have shown promising potential for improved photocatalytic performance. This review focuses on the combined study of photocatalytic and ferromagnetic properties at room temperature, with a particular emphasis on metal oxides, such as TiO2, which have emerged as a key area of interest in the domains of magnetism and environmental remediation. Despite extensive research over the years, the precise mechanism behind the interplay of ferromagnetism and photocatalysis in these materials remains incompletely understood. Several critical factors contributing to magnetism have been hinted at, including oxygen vacancies and various metal doping. Numerous reports have demonstrated that these factors play a primary role in room temperature ferromagnetism and photocatalysis in wide-band-gap metal oxides. However, establishing a direct correlation between magnetism, oxygen vacancies, dopant concentration, and photocatalysis has proven challenging. This review aims to provide a comprehensive overview of the recent progress in understanding the magnetism and photocatalytic behaviour of metal oxides. By examining the latest findings, this study sheds light on the potential of RTFMOS as effective photocatalysts, thereby contributing to advancements in environmental remediation and related applications.

To address the challenges associated with the difficult electromagnetic (EM) scattering computations of anisotropic dielectric-coated metallic composite targets, we proposed an efficient hybrid algorithm for simulating the EM scattering of complex targets with anisotropic dielectric coatings. This method, based on Impedance Boundary Condition (IBC), utilizes surface impedance vectors to describe the EM properties of the dielectric. It fully leverages the respective advantages of the low-frequency Method of Moments (MoM) and the high-frequency Physical Optics (PO) to achieve high-precision and rapid EM simulation of anisotropic dielectric-coated metallic composite targets. Employing boundary conditions and equivalent principles, we equivalently transform the EM scattering problem of targets with thin dielectric coatings into the radiation problem of equivalent EM current on impedance surfaces. This enables the high-precision and rapid calculation of Radar Cross Sections (RCS) for complex targets with anisotropic dielectric coatings. Using examples such as a square plate structure, a simplified aircraft, and a complex satellite model, the simulation results exhibit a high degree of agreement with full-wave numerical solutions and demonstrate a significant advantage in computational resources. This research convincingly demonstrates the accuracy and effectiveness of the proposed method.

We report a simple and high-performance flexible strain sensor based on liquid metal nanoparticles (LMNPs) on polyimide substrate by laser induced deposition. The LMNPs were prepared by ultrasonic method, and then the femtosecond laser direct writing technology was used to induce the assembly and deposition of the LMNPs to form liquid metal microwires. Laser local sintering enhances the connection between particles, and a wearable strain sensor was fabricated with the high sensitivity as high as 76.18, the good linearity (a correlation coefficient of 0.999) in a wide sensing rage, the fast response/recovery time of 159 ms/120 ms. Attributed to these extraordinary strain sensing performances, the sensor can sense various dynamic strains in real time, monitor both subtle physiological activities and large human motions. It can be adhered to human skin, and well reflect the change of facial expression and realize real-time monitoring of facial expression. And the vocal cord vibration can be detected for speech recognition while the sensor attached to the outside of the throat.

Hip replacement has significantly improved the quality of life of patients with symptomatic hip osteoarthritis. Metal-on-metal (MoM) bearings have been used with conventional total hip re-placement (THR) for several decades with promising results from early applications. Wear and corrosion of these implants may lead to a release of metal products into surrounding tissue and body fluids. From the 1980s onwards, the search for increasingly better coupling materials with low levels of wear led to the rise of hard-on-hard couplings such as ceramic-on-ceramic (CoC). The latter is currently the coupling with the longest known duration and with a wear rate close to zero. MoM coupling has been for a long time the most significative alternative, but systemic and local complications linked to the release of chromium and cobalt ions, determine the withdrawn from the market. One other alternative proposed over the time has been Ceramic-on-Metal (CoM) bearing. Preliminary results have been described as favourable, but due to the failures of metal on metal it has been withdrawn from the market, without causing significant clinical complications. In this narrative review, we analysed risks and benefits associated with the implantation of hybrid hard-on-hard bearings, such as CoM.

New complexes of manganese(II) hexafluoroacetylacetonate [Mn(hfac)2] with 2-(1-R-3-pyrazol-4-yl)-4,4,5,5-tetramethyl-2-imidazoline-3-oxide-1-oxyl (R = CHF2, CH2CH2F, CH2CHF2 or CH2CF3) were synthesised and characterised structurally and magnetically. All complexes were prepared under similar conditions. Nonetheless, their crystal structures were considerably different. Depending on the structure of fluorinated alkyl substituent R, the complexation reaction led to complexes of three types: chain-polymeric complexes with the head-to-head or head-to-tail motif and complexes of molecular structure. All complexes show strong antiferromagnetic behaviour in a high-temperature region (150−300 K) and weak ferro- or antiferromagnetic exchange interactions at low temperatures. The stronger antiferromagnetic exchange, –101.7 ± 1.5 or –136 ± 10 cm–1, –82.3 ± 1.3 cm–1 and –87.4 ± 1.3 cm–1, was attributed to the magnetic interaction in three- or two-spin clusters: {>N∸O–Mn2+–O∸N<} or {>N∸O–Mn2+}, respectively. The weaker antiferromagnetic interaction, –0.005, between three-spin clusters or ferromagnetic interactions, 0.18–0.81 cm–1, between two-spin clusters are realised through the pyrazole ring or intermolecular contacts.

The interactions of metal ions with fulvic acids resulted in changes in the particle size and charge. Particle size distribution was trimodal for fulvic acids, bimodal for fulvic complexes with calcium and magnesium, and copper-fulvic complexes had only one size fraction. The compensation of negative charge of carboxylic and phenolic functional groups by positive charged metal ions resulted in the increase in zeta potential which was getting closer to zero in the case of copper-fulvic complexes. However, all metal humic complexes behaved as colloidally unstable which resulted in visually observable sedimentation. Calorimetric measurements provided positive values of changes in enthalpy which indicated endothermic processes. In contrast quantum chemical calculations as well as experiments with model compounds provided negative values indicated exothermic processes. Changes in Gibbs energy were determined as negative and changes in entropy as positive which meant spontaneous processes.

Metal Additive Manufacturing (MAM) has emerged as a promising technology in the aerospace industry, enabling the production of complex components with enhanced design flexibility and reduced lead times. Concurrently, Industry 4.0 has gained significant attention for its potential to revolutionize aerospace manufacturing processes. The paper aims to cluster and review the literature on MAM in the aerospace industry, specifically focusing on its relevance to Industry 4.0 and its applicability throughout the various stages of the product life cycle for the chief purpose of matching supply with demand. Identified gaps and challenges are analyzed, highlighting the need for further research and outlining research agenda aimed at advancing the integration of MAM for Industry 4.0 in the aerospace sector. By addressing these research areas, the aerospace industry can unlock the value of MAM within an Industry 4.0 framework, leading to improved efficiency, productivity, and competitiveness.

Aptamers are synthetic single stranded oligonucleotides that exhibit selective binding properties to specific targets, thereby providing as powerful basis for the development of selective and sensitive (bio)chemical assays, such as biosensors. Electrochemical biosensors, utilizing aptamers as biological recognition elements, namely aptasensors, are at the forefront of current research. They exploit the combination of the unique properties of aptamers with the advantages of electrochemical detection with the view to fabricate inexpensive and portable analytical platforms for rapid detection in point-of-care (POC) applications or on-site monitoring. The immobilization of aptamers on suitable substrates is of paramount importance with the aim to retain their functionality and optimize the sensors’ sensitivity. This work describes different immobilization strategies for aptamers on the surface of semiconductor-based working electrodes, including metal oxides, conductive polymers and carbon allotropes. These are presented as platforms with tunable band gaps and different surface morphologies for the preparation of low cost, highly versatile aptasensor devices in analytical chemistry. A survey of the current literature is provided, discussing each analytical method. Future trends envisage for aptamer-based biosensing using semiconductors are also outlined.

Lomefloxacin (F1) and pefloxacin (F2) have a broad spectrum of antimicrobial activities against Gram-positive and Gram-negative bacteria. In this study, we investigated the complexation mode, morphological and biological properties of four metal-based complexes of F1 and F2 molecules with Mg(II), Ca(II), Zn(II), and Fe(III) metal ions. These complexes were prepared at ~60–70°C in a neutral medium using a 5% NH3 solution at pH ~7-8 with a 1:1 ratio. Multiple physicochemical methods were employed to characterize the binding mode between F1 and F2 with the metal ions under investigation. The results of these methods suggested that the gross formula of the complexes obtained with the metal ions were [MgF1(H2O)Cl]2H2O, [CaF1(H2O)Cl]3H2O, [ZnF1(H2O)Cl], [FeF1(H2O)2Cl2]Cl2H2O, [MgF2(H2O)Cl]2H2O, [CaF2(H2O)Cl]3H2O, [ZnF2(H2O)Cl], and [FeF2(H2O)2Cl2]Cl2H2O. The microscopic characterizations indicated that the Ca(II)-F1 complex had an interesting surface topography. Its particles had a homogenous, short, rod-like shaped structure that clustered together to form a tree shape. Using the Kirby-Bauer disc diffusion protocol, the synthesized metal-based complexes were screened in vitro against different Gram-positive and Gram-negative bacterial and fungal species. The antimicrobial profile of the Fe(III)-F1 complex indicated that it had remarkable inhibitory activity against all the tested bacterial and fungal species with potency equal to that of the standard drugs (streptomycin and ketoconazole).

A mild, efficient, and photocatalytic synthesis of 6-phosphorylated phenanthridines via tandem radical addition/cyclization/aromatization of 2-isocyanobiphenyls with diarylphosphine oxides is reported. The method features operational simplicity, metal-free conditions, using low-cost rose Bengal as catalyst and sustainable air as terminal oxidant at room temperature, and providing the desired products in moderate to good yields.

The presence of metal ions, in high concentrations, in the effluents results from industrial metal coating is a well-known fact. Most of time, such metal ions, once they reach the environment, contribute significantly to its degradation. Therefore, it is essential that before such effluents are discharged into the environment, the concentration of metal ions is reduced (as much as possible), to minimize the negative impact on the quality of ecosystems. Among all methods that can be used to reduce the concentration of metal ions, sorption is one of the most viable options, due to its high efficiency and low cost. Moreover, due to the fact that many of the industrial wastes have sorbent properties, this method is in accordance with the principles of circular economy. Based on these considerations, in this study, mustard waste biomass (resulting after oil extraction) was functionalized with an industrial polymeric thiocarbamate (METALSORB), and used as an sorbent to removal Cu(II), Zn(II) and Co(II) ions from aqueous media. The best conditions for the functionalization of mustard waste biomass were found to be: mixing ratio biomass : METASORB = 1g : 1.0 mL and temperature of 30 C. The experimental sorption capacities of functionalized sorbent (MET-MWB) were 0.42 mmol/g for Cu(II), 0.29 mmol/g for Zn(II) and 0.47 mmol/g for Co(II), and were obtained in the following conditions: pH of 5.0, 5.0 g sorbent/L and temperature of 21 C. Modeling of isotherms and kinetic curves, but also the analysis of the results obtained from desorption processes, demonstrates the usefulness of this sorbent in the treatment of effluents contaminated with metal ions. In addition, tests on real wastewater samples highlight the potential of MET-MWB for large-scale applications.

The use of tungsten fiber-reinforced tungsten composites (Wf/W) has been demonstrated to significantly enhance the mechanical properties of tungsten (W) by incorporating W-fibers into the W-matrix. However, prior research has been restricted by the usage of single fiber-based textile fabrics, consisting of 150 µm warp and 50 µm weft filaments, with limited homogeneity, reproducibility, and mechanical properties in bulk structures due to the rigidity of the 150 µm fibers. To overcome this limitation, two novel textile preforms were developed utilizing radial braided yarns with 7 core- and 16 sleeve filaments (R.B. 16+7) as the warp material. In this study, bulk composites of two different fabric types were produced via a layer-by-layer CVD-process, utilizing single 50 µm filaments (type 1) and R.B. 16+7 yarns (type 2) as weft materials. The produced composites were sectioned into KLST-type specimen based on DIN EN ISO 179-1:2000 using electrical discharge machining (EDM), and subjected to three-point bending tests. Both composites demonstrated enhanced mechanical properties with pseudo-ductile behavior at room temperature and endured over 10,000 load cycles between 50-90 % of their respective maximum load without sample fracture. Composites based on fabric type 1 demonstrated superior manufacturing performance and mechanical properties, a high relative average density (>97 %), and high fiber volume fraction (14-17 %). Furthermore, a novel approach to predict the fatigue behavior of the material under cyclic loading was developed based on the high reproducibility of the mechanical properties of type 1, providing a new benchmark for upscaling endeavors.

China is a large agricultural country that produces a large amount of crop straw every year. Thus, the development of cost-effective and economic application of invasive plants is warranted. Biochars derived from crop straw has been proven to be promising for adsorbent materials. However, less studies have focused on biochar derived from different types of crop straw as adsorbent under the same conditions to compare their adsorption performance. Here, we characterized the five biochars in the same system (600 ℃). In results, GBC has higher ash content, pH, CEC, specific surface area, mineral composition and oxygen-containing functional groups. The adsorption kinetics can be explained adequately by pseudo-second-order model and Langmuir model, indicating that the adsorption behavior of the biochar is both physical adsorption and chemical adsorption, the adsorption process includes complexation reaction, cationic π bond, ion precipitation and electrostatic adsorption. In conclusion, GBC exhibited higher metal equilibrium adsorption capacities (125 mg·g-1 for Pb2+, 29 mg·g-1 for Cd2+). The solution pH, biochar dosing, pyrolysis temperature and the properties of these heavy metals were responsible for adsorption capacity, thus showing stronger affinity and better adsorption effect. Our results are important for the selection and utilization of plant-based biochar for different heavy metals.

Bismuth oxides are well-known electro-catalysts in fuel cells systems; they are usually used as anodic materials for the oxidation of low molecular weight alcohols. The utilization of BiO₂ and MnO₂ as catalysts in the pharmaceutical analysis is analytical method for the determination of heavy metal antibacterial agents in Pharmaceutical Dosage form is developed. The method is based on the voltammetric determination of heavy metal using Bidified platinum electrode by Bismuth oxide. The two components are oxidized at the Bidified electrode surface with the development of current that is linearly proportional to their concentrations in the range of 7.04*10^-7- 1*10^-3 M heavy metal. The oxidation reaction of the two components is pH-dependent, in which the buffer used is Britton-Robinson at pH = 7.00 where maximum peak current and maximum peak separation is obtained. The regression factors obtained from the calibration curves are 0.9812. The method of analysis was validated, where the limit of detection (LOD) and the limit of quantitation (LOQ) were calculated to be 1.44*10^-4 M, 4.36*10^-4 M and 1.27*10^-4 M, 3.84*10^-4 M respectively, the percentage recovery of both components was also calculated to 77 % for heavy metal.

The electrochemical CO2 reduction reaction can lead to high value-added molecules production while helping decrease anthropogenic CO2 emissions. Copper can reduce CO2 to more than thirty different hydrocarbons and oxygenates, but it lacks the required selectivity. We present a computational investigation of the role of nano-structuring and alloying in Cu-based catalysts on the activity and selectivity of CO2 reduction to one-carbon products: carbon monoxide, formic acid, formaldehyde, methanol, and methane. The adsorption, activation, and conversion of CO2 were computed on monometallic and bimetallic (decorated and core-shell) 55-atom Cu-based clusters. The dopant metals considered were Ag, Cd, Pd, Pt, and Zn, located at different coordination sites. The relative binding strength of the intermediates at different applied potentials were used to identify the optimal catalyst for the selective CO2 conversion to one carbon products. It was discovered that single atom doping with Cd and Zn is optimal for the CO2 to carbon monoxide conversion. The core-shell models with Ag, Pd, and Pt provided higher selectivity for formic acid and formaldehyde. The Cu-Pt and Cu-Pd showed lowest overpotential for methane formation.

The wide interest in developing green energy technologies stimulates the scientific community to seek, for devices, new substitute material platforms with low environmental impact, ease of production and processing and long-term stability. The synthesis of metal oxide (MO) semiconductors fulfils these requirements and efforts are addressed at optimizing their functional properties, through improvement of charge mobility or energy level alignment. Two MOs have rising perspectives for application in light harvesting devices, mainly for the role of charge selective layers but also as light absorbers, namely MoO3 (an electron blocking layer) and Co3O4 (a small band gap semiconductor). The need to achieve better charge transport has prompted us to attempt doping strategies with vanadium (V) ions that, when combined with oxygen in V2O5, produce a high work function MO. We report on subcritical hydrothermal synthesis of V-doped mesostructures of MoO3 and of Co3O4, in which a tight control of the doping is exerted by tuning the relative amounts of reactants. We accomplished a full analytical characterization of these V-doped MOs that unambiguously demonstrates incorporation of the vanadium ions in the MO crystal lattice, as well as effects on the optical properties and work function. We foresee a promising future use of these materials as charge selective materials in energy devices based on multilayer structures.

The effect of rare earth Pr6O11 on the microstructure and mechanical properties of high-strength steel weld metal was investigated by optical microscopy, scanning electron microscopy and mechanical testing. Three different contents of Pr6O11 were added to the flux-cored wires. The results showed that the addition of 1% Pr6O11 can promote the refinement and spheroidization of inclusions, refine the grains, form acicular ferrites, and significantly improve the toughness of weld metal. The addition of Pr6O11 promoted the formation of rare earth composite inclusions and acicular ferrites in the weld metal, refined the lath microstructure, inhibited the formation of martensite and bainite. The crack formation mode changed from the boundary cracking of the bainite clusters caused by the surface shear stress to the surface shear stress-induced decohesion of inclusion. However, excessive addition of Pr6O11 will reduce the number of inclusion nucleation and deteriorate the mechanical properties. The wire No.2 with 1% Pr6O11 had the good comprehensive mechanical properties, and the corresponding values were 835MPa of tensile strength and 72 J of impact toughness. These findings suggest that the control of Pr6O11 can be an effective way to improve the impact toughness of weld metal.

The effect of Pr6O11 on the microstructure and mechanical properties of high-strength steel weld metal was investigated by optical microscopy, scanning electron microscopy and mechanical testing. Three different contents of Pr6O11 were added to the flux-cored wires. The results demonstrate that the addition of 1% Pr6O11 can promote the refinement and spheroidization of inclusions, refine the grains, form acicular ferrites in the weld metal, and significantly improve the toughness. The addition of Pr6O11 promoted the formation of rare earth composite inclusions and acicular ferrites in the weld metal, refined the lath microstructure, inhibited the formation of martensite and bainite. The crack formation mode changed from the boundary cracking of the bainite clusters caused by the surface shear stress to the surface shear stress-induced decohesion of inclusion. Excessive addition of Pr6O11 will reduce the number of inclusion nucleation and deteriorate the mechanical properties. The wire No.2 with 1% Pr6O11 had the good comprehensive mechanical properties.

Certain studies have reported various insulin resistance responses to ambient heavy metal pollution, but few have reported such responses to occupational heavy metal pollution. Even fewer have demonstrated a relationship between mixture effects of heavy metals and insulin resistance in welding workers. Overall, we recruited 53 welders and 48 administrative staff from a shipyard located in northern Taiwan. Personal exposure to heavy metals was monitored for PM2.5 and urine. Blood samples from each participant were collected from the antecubital vein after fasting. Urine samples from each participant were collected in the same period as blood samples. The geometric mean levels for chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), and cadmium (Cd) in the PM2.5 of the personal breathing zone and urinary Mn of welders were significantly higher than those in administrative staffs. Ambient Cr, Co, Ni, and Cu levels in the PM2.5 and urinary Cd were positively related to HOMA2-IR after adjusting for personal covariates (PM2.5-Cr: β=0.036, 95%C.I.: 0.002 to 0.070; PM2.5-Co: β=0.040, 95%C.I.: 0.002 to 0.077; PM2.5-Ni: β=0.054, 95%C.I.: 0.013 to 0.094; PM2.5-Cu: β=0.049, 95%C.I.: 0.010 to 0.088; U-Cd: β=0.209, 95%C.I.: 0.052 to 0.366, respectively). Our findings indicated the PM2.5 metal components and urinary metals were associated with increased insulin resistance in shipyard welders.

This review summarizes experimental and theoretical studies of transition metal complexes with two types of novel metal-carbon bonds. One type features complexes with carbones CL2 as ligands, where the carbon(0) atom has two electron lone pairs which engage in double (σ and π) donation to the metal atom [M] CL2. The second part of this review reports complexes which have a neutral carbon atom C as ligand. Carbido complexes with naked carbon atoms may be considered as endpoint of the series [M]-CR3 → [M]-CR2 → [M]-CR → [M]-C.

Metal foams are widely studied as possible tools for the enhancement of heat transfer from hot bodies. The basic idea is that a metal foam tends to increase significantly the heat exchange area between the hot solid body and the external cooling fluid. For this reason, this class of porous materials are considered as good candidates for an alternative to finned surfaces, with different pros and cons. Among the pros, we mention the generally wider area of contact between solid and fluid. Among the cons is the difficulty of producing different specimens with the same inner structure, with the consequence that their performance may be significantly variable. This paper will offer a survey of the literature with a focus on the main heat transfer characteristics of the metal foams. Then, a numerical simulation of the heat transfer at the pore scale level for an artificial foam with a spatially periodic structure will be discussed. Finally, these numerical results will be employed to assess the macroscopic modelling of the flow and heat transfer in a metal foam.

AMR and drug void have caused huge panic today with few thousand death per year. MDR Typhoid was a serious old disease and caused serious health hazard in humen and animals demanding an update on molecular biology of the status on transferable genetic elements. R-plasmids combined in F’-plasmid and the new MDR conjugative plasmids were shown abundant in Sanmonella ranging 70-440kb with similarities. BlaTEM, blaCTX-M, blaOXA, blaNDM mdr genes were abundant in >50 plasmids analyzed and metal resistant gene clusters are predominant in most large plasmids. Among the acetyltransferase all catA1, aacA1 and aac-1b-cr genes were located. Abundant streptomycin phosphotransferases (StrAB) and rarely colistin resistant Mcr-5/9 phosphoethanolamine–lipid A transferase were detected. Altered isomeric dihydropterote synthases (Sul1/2/3) were present giving sulfamethoxazole resistance and dhfr gene frequently associated giving trimethoprim resistance. Metal resistant gene clusters like SilABC (CusABC), PcoAB, RcnA, terABC, and merABCXT etc were found in many Salmonella enterica plasmids. Toxin genes like HipA and virulence genes like spvABD were located in few plasmids increasing virulence and pathogenesis. Drug efflux genes tetA or tetB and OqxB, floR, CmlA were frequent where as QepA and EamA genes were rarely seen. Thus, Salmonella metal resistant genes combined with antibiotic resistant genes has tried to overcome the both toxic antibiotics and metalions causing Typhoid AMR. Such acquisition spreads salmoniasis in the live stocks (pig, cow, chicken) where toxic soil and water dominate increasing chance of MDR typhoid in human.

Legacy mining industry has left a large number of tailings ponds exposed to water and wind erosion that causes serious environmental and health problems. Prior to rehabilitation actions a deep sampling of the materials infilling the pond used to be necessary. Thus, the primary objective of this study is to demonstrate the usefulness of the Electrical Resistivity Tomography (ERT) method as a non-invasive tool to determine the physicochemical composition of mine tailings ponds, enabling more efficient and low-cost surveys. To achieve this objective, three ERT profiles and three boreholes in each profile were carried out, from each borehole three waste samples from differents depths were collected and a geochemical characterization of the samples was carried. In order to estimate the composition of the infilling wastes in tailing ponds from electrical resistivity measures, several regression models were calculated for different physicochemical properties and metal concentrations. As a result, a high resistivity area was depicted in profiles G2 and G3 while a non-resistive area (profile G1) was also found. Relationships among low resistivity values and high salinity, clay content and high metal concentrations and mobility were established. Specifically, calibrated models were obtained for electrical conductivity, particles sizes of 0.02-50 µm and 50-2000 µm, total Zn and Cd concentration, and bioavailable Ni, Cd and Fe. Therefore, the ERT technique could be considered as a useful tool for mine tailings ponds characterization, and it can be used to estmate some physicochemical properties and metal concentrations of this mine waste.

Gas sensor arrays, also known as electronic noses, leverage a diverse set of materials to identify the components of complex gas mixtures. Metal-organic frameworks (MOFs) have emerged as promising materials for electronic noses due to their high-surface areas and chemical as well as structural tunability. Using our recently reported genetic algorithm design approach, we examined a set of 50 MOFs and searched through the over 1.125x1015 unique array combinations to identify optimal arrays for the detection of CO₂ in air. We found that despite individual MOFs having lower selectivity for O2 or N2 relative to CO₂, intelligently selecting the right combinations of MOFs enabled accurate prediction of the concentrations of all components in the mixture (i.e. CO₂, O₂, N₂). We also analyzed the physical properties of the elements in the arrays to develop an intuition for improving array design. Notably, we find that diversity among the surface areas in the MOFs leads to improved sensing. Consistent with the observation, we found that, as one might expect, the best arrays consistently had more structural diversity than the worst arrays.

This research paper presents a new application of electroactive polyimide doped with gold nanoparticles (PI/AuNPs) as a chemiresistor sensor for detecting hydrogen sulfide gas. The synthesis of PI/AuNPs was done in a simple 3-step process of polymerization using the as prepared amine-capped aniline trimer (ACAT), followed by imidization, and doping. Spectral analyses via FTIR, LC-MS and ¹H-NMR confirmed the formation of amine-capped aniline trimer with a MW of 288 g mol^-1. Comparison of ACAT, BSAA, and PI FTIR spectra showed successful polymerization of the last, while XRD validated the incorporation of metal nanoparticles onto the polymer matrix showing characteristic diffraction peaks corresponding to gold. Furthermore, TEM, and FE-SEM revealed the presence of well-dispersed Au nanoparticles with an average diameter of about 60nm. The electroactive PI/AuNPs-based sensor showed a sensitivity of 0.29% ppm^-1 H₂S at a linear concentration range of 50 to 300 ppm H₂S (r = 0.9777). The theoretical limit of detection was found at 0.142 ppm or 142 ppb H₂S gas. The sensor provided a stable response reading at an average response time of 43±5 seconds, which was easily recovered after an average time of 99±5 seconds. The sensor response was highly repeatable and reversible with RSD values of 8.88%, and 8.60%, respectively. Compared with the performance of the conventional conducting polyaniline also doped with gold nanoparticles (PANI/AuNPs), the fabricated electroactive PI/AuNPs exhibited improved sensing performance making it a potential candidate in monitoring H₂S in the environment and for work-related safety.

A simple and rapid positive–negative colorimetric approach to determine the presence of antimony ions based on the use of gold nanoparticles conjugated with oligonucleotide (poly-A sequence) is developed. Colorimetric measurements reveal that the aggregates of modified gold nanoparticles were afforded after adding antimony ions, thus changing the solution color from pink to blue. The results of aptamer’s interaction on the gold nanoparticle surface with target analyte can be detected either by photometry or by the naked eye. The realized assay provides rapid (2 min), sensitive (detection limit 10 ng/mL), specific, and precise (variation coefficient less than 3.8%) detection of antimony (III) in drinking water

We use a random gap model to describe a metal-insulator transition in three-dimensional semiconductors due to doping and find a conventional phase transition, where the effective scattering rate is the order parameter. Spontaneous symmetry breaking results in metallic behavior, whereas the insulating regime is characterized by the absence of spontaneous symmetry breaking. The transition is continuous for the average conductivity with critical exponent equal to 1. Away from the critical point the exponent is roughly 0.6, which may explain experimental observations of a crossover of the exponent from 1 to 0.5 by going away from the critical point.

Volatile organic compounds (VOCs) are among the most abundant air pollutants. Their high concentrations can adversely affect the human body and therefore, early detection of VOCs is of outmost importance. Among the different VOCs, in this review paper, we have focused our attention on the monitoring of acetaldehyde by chemiresistive gas sensors using nanostructured semiconducting metal oxides. These sensors not only can provide a high sensing signal for detection of acetaldehyde, but also high thermal and mechanical stability and low price. This review paper is divided into three major sections. First, we will introduce acetaldehyde as the target gas and the importance of its detection. Then, the fundamentals of chemiresistive gas sensors will be briefly presented and, in the last section, a survey of literature on acetaldehyde gas sensors will be discussed. Acetaldehyde sensors working mechanism, their structures and configurations are reviewed. Finally, the future development outlook and potential applications are discussed, giving a complete panoramic view for researcher working and interested in acetaldehyde detection for different purposes in many fundamentals and applicative fields.

Magnesium is one of the lightest structural metal used in different industrial sector and many works are present in literature about the study of its reinforcement by fillers addition. Basalt fibres are natural fillers with good mechanical properties, excellent resistance to high temperature and lower cost than carbon fibres. For these aspects, in the last years they are increasingly used in the production of composite materials with polymeric matrices. However, very few information are presents in literature about the use of basalt fibres as reinforcement in metal matrix composite materials. It is well known that the impregnation of fibres reinforcement affects the mechanical behavior of composites materials. The aim of this study is to investigate the impregnation and the behavior of basalt fibres in a magnesium alloy composite material manufactured by a centrifugal casting technique.

The beginning of industrialization human being has observed a variety of environmental troubles in the world. This industrialization has not only brought growth and affluence but ultimately troubled the ecosystem. One of the crashes is visible, in form of water contamination. Here the current study heavy metal contamination of water body has been discussed. Effluents from a great number of industries viz., tannery, textile, pigment & dyes, paint, wood processing, petroleum refining, electroplating, leather etc., have a major amount of heavy metals in their wastewater. The conventional technique of handling heavy metal pollution includes chemical oxidation, chemical precipitation, ion exchange, reverse osmosis, membrane separation, electrodialysis etc. These processes are expensive, energy intensive and frequently related with generation of poisonous by-product. Therefore, the adsorption has been examined as a cost-efficient technique of elimination of heavy metals from wastewater. In the current study different low-cost adsorbent has been a review as an abatement of heavy metal contamination from wastewater. These adsorbent comprise materials of natural origin like peat moss, zeolites, clay, and chitin are found to be an effective agent for removal of deadly heavy metals like Pb, Cd, Zn, Cu, Ni, Hg, Cr etc. Separately from these, a variety of agricultural wastes like rice husk, waste tea, neem bark, black gram; Turkish coffee, walnut shell etc. were also known as a powerful adsorbent for heavy metal removal. at the side of that low-cost industrial byproduct like fly ash, lignin, iron (III) hydroxide and red mud, coffee husks, Areca waste, tea factory waste, sugar beet pulp, battery industry waste, blast furnace sludge, waste slurry, sea nodule remains and grape stalk wastes have been discovered for their technical possibility to eliminate toxic heavy metals from impure water.

We report the electrical characterization and the field emission properties of CVD-grown MoS₂ bilayers deposited on SiO₂/Si substrate. Current-voltage characteristics are measured in the back-gate transistor configuration, with Ti contacts patterned by electron beam lithography. We confirm the n-type character of as-grown MoS₂ and we report normally-on field effect transistors. Local characterization of field emission is performed inside a scanning electron microscope chamber with piezo-controlled tungsten tips working as the anode and the cathode. We demonstrate that an electric field of ~200 V/μm is able to extract current from the flat part of MoS₂ bilayers, which therefore can be conveniently exploited for field emission applications even in low field-enhancement configurations. We show that a Fowler-Nordheim model, modified to account for electron confinement in 2D materials, fully describes the emission process.

In this work, we proposed a novel design of microfluidic mixer utilizing the amplified Marangoni chaotic advection induced by AC continuous electrowetting of a metal droplet situated in electrolyte solution, due to the linear and quadratic voltage-dependence of flow velocity at small or large voltages, respectively. Unlike previous researchers exploiting the unidirectional surface stress with DC bias at droplet/medium interface for pumping of electrolyte where the resulting flow rate is linearly proportional to the field intensity, dominance of another kind of dipolar flow pattern caused by local Marangoni stress at the drop surface in sufficiently intense AC electric field is demonstrated by both theoretical analysis and experimental observation, which exhibits a quadratic growth trend as a function of the applied voltage. The dipolar shear stress merely appears at larger voltages and greatly enhances the mixing performance by inducing chaotic advection between the neighboring laminar flow. The mixer design developed herein, on the basis of amplified Marangoni chaotic advection around a liquid metal droplet at larger AC voltages, has great potential for chemical reaction and MEMS actuator applications, because of generating high-throughput and excellent mixing performance at the same time.

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.

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 %.

Background and Objectives: The aim of this study is to investigate the diagnostic-therapeutic prob-lem of pelvic recurrence of rectum cancer, highlighting current surgical standards and the possi-ble role of the minimally invasive approach. This retrospective analysis of our surgical case study wishes to enter this debate while suggesting a possible line of action, based on the site of recur-rence. Materials and Methods: We examined, retrospectively, all the patients diagnosed, between 2008 and 2018, with cancer of the rectum at the "Pietro Valdoni" Department of Surgery and monitored their follow-up for 5 years. The sample consisted of 368 patients with rectal neoplasm, 136 females and 232 males, with an average age of 65.8 (ranging from 37 to 86). In 103 of the cases, the neo-plasm was located in the upper rectum (28%), in 119 cases in the middle rectum (32.3%), in 102 cases in the lower rectum (27.7%), in 31 cases (8.4%) at the level of the right/sigma junction and in 13 cases it was not possible to define the site with certainty (3.5%). Results: We examined all patients diagnosed with cancer of the rectum between 2008 and 2018 at the "Pietro Valdoni" Department of Surgery retrospectively and monitored their follow-up for 5 years. The sample consists of 368 patients with rectal neoplasm, 136 females and 232 males. Conclusions: The discussion remains open as to which approach is best at surgical level, whether laparoscopic, robotic or open-air. Our experience informs us that the most dangerous site remains on the anastomotic site.

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.

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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.

Several studies have identified a relationship between air pollution and depression, particularly in relation to fine particulate matter (PM2.5) exposure. However, the strength of this association appears to be moderated by variables such as age, gender, genetic vulnerability, physical activity and climatic conditions, and has not been assessed at a cross-national level to date. The current study examines the association between the prevalence of depression in each country, based on the most recent Global Burden of Disease Study data, and the average national level of PM2.5 based on the World Health Organization’s database. The observed associations were adjusted for age, gender, level of physical activity, income, education, population density, climate, and type of depression. It was observed that there was a modest but significant positive correlation between PM2.5 level and the prevalence of depression even after adjusting for the above confounders. This association was more marked above a certain threshold and applied chiefly to major depressive episodes. These findings are of significant public health importance in terms of preventive strategies aimed at reducing the population-level burden of depression.

Ion Transport Membrane (ITM) is a well-developed technology for producing O₂ by separating air in its membrane. To decrease energy loss in air separation unit and to increase the overall efficiency of a power generation unit ITM is added with the gasification unit in this model. Ceramic materials are generally used to make ion transport membrane that produces oxygen by conducting oxygen ions at specified temperature. Potential advantages can be gained by integrating ITM technology with power generation units as 99% pure oxygen is produced from ITM. A salient comparison between ITM air separator combined with IGCC and cryogenic air separator combined with IGCC is done in this paper where the total power generation cycle remains same for both cases excluding the air separation units (ITM and cryogenic). Using ITM air separator is more beneficial compared to cryogenic air separation as ITM technology helps to improve IGCC overall efficiency and also reduces plant auxiliaries than that of power generation systems integrated with cryogenic.

Chronic obstructive pulmonary disease (COPD) is strongly associated with tobacco smoking and it is the increasing cause of morbidity and mortality worldwide. The prevalence of COPD among never smokers varies widely across regions, areas, and nations. COPD in smokers has been extensively explored worldwide, however, COPD in non-smokers is under-explored and there is limited data available on non-smoking COPD. We determined the role of environmental pollution and biomass fuel exposure in COPD patients who were non-smokers. We evaluated the clinical profile of non-smokers with COPD in a retrospective observational study. 180 non-smoker COPD patients were selected from the year 2016-to 2018. We found that many patients with COPD are non-smokers and the incidence is higher among the rural population, suggesting that non-smoking COPD is evolving rapidly due to biomass smoke and other environmental pollutant exposures.

Road vehicles are a large contributor to Nitrogen Oxides (NOx) pollution. The routine road-side monitoring stations, however, may underrepresent the severity of personal exposure in urban areas, because long-term average readings cannot capture the effects of momentary, high peaks of air pollution. While numerical modelling tools historically have been used to propose an improved distribution of monitoring stations, ultra-high resolution Computational Fluid Dynamics models can further assist the relevant stakeholders in understanding the important details of pollutant dispersion and exposure at local level. This study deploys a 10 cm-resolution CFD model to evaluate actual high peaks of personal exposure to NOx from traffic, by tracking the gases emitted from the tailpipe of moving vehicles being dispersed towards the roadside. The investigation shows that a set of four Euro 5-rated diesel vehicles travelling at constant speed may generate momentary road-side concentrations of NOx as high as 1.25 mg/m3, with 25% expected increase for doubling the number of vehicles and approximately 50% reduction when considering Euro 6-rated vehicles. The paper demonstrates how the numerical tool can be used to identify the impact of measures to reduce personal exposure, such as protective urban furniture, as traffic patterns and environmental conditions change.

Aircraft emissions represent a relevant amount of human induced CO2. Globally, up to 2.5 per cent of such emissions stem from the aviation industry. In order to investigate the effects within the atmosphere, realistic flight profiles are necessary to provide quantitatively tangible values of emissions. The flight profiles and the according fuel consumption can be calculated by using waypoints from flight plans and Base of Aircraft Data (BADA). This paper presents an approach to refine the fuel consumption by integrating the passenger load into the calculation. Since effects of emissions have to be assessed on a greater scale, such as on the European air traffic network, the presented approach provides cost functions for CO2 emissions for different aircraft types and load factors. The cost functions were derived by means of regression analyses of BADA based calculated flight profiles with a step size of one second. The calculations are based on real historic traffic scenarios of several days. The derived aircraft specific fuel burn coefficients enable a simple and efficient integration of CO2 estimations depending on the flight distance, load factor and aircraft type. This can be applied to large traffic scenarios to also study different set-ups such as travel restrictions, other disruptions or an alteration in the traffic system as a whole. In order to enable the assessment of further aspects of such changes to the European air traffic system at large and to foster reproducibility and comparability of related studies, we provide further general-purpose cost estimation functions for several important key characteristics. Besides fuel consumption, we develop cost estimations for air navigation fees and maintenance for conventional aircraft. Those functions are also provided for the design concept of a short-range all-electric aircraft. This propeller aircraft features game-changing technologies such as active laminar flow control, active load alleviation and advanced materials and structure concepts. The approaches discussed in this paper will focus on the generic aspects of aircraft related costs, which can be derived from general available data. For the sake of reproducibility, the results will be made publicly available.

Research have been conducted in many countries around the world to assess air quality during COVID-19 pandemic, especially during lockdown period, some of these studies found an increase or decrease in some pollutants. This paper investigates the impact of COVID-19 on seven air pollutants (i.e., PM_2.5, PM₁₀, NO₂, O₃, SO₂, H₂S, CO) from the period January 2020 to December 2020 in the State of Kuwait. Kuwait is a desert country located in the north-eastern part of the Arabian Peninsula, and the northeast of the Arabian Gulf (Persian as it is sometimes called). Several analytical methods were conducted, such as spatial analysis (spatial interpolation) to study the distribution of the studied variables. The data was also statistically analysed (time series analysis - Kernel density) to study the temporal changes. The analysis also included applying air quality index to the data. We found that concentrations for the pollutants decreased during the pandemic due to the decrease of anthropogenic sources including such as traffic and petroleum activities, but the concentration for PM_2.5 increased, mostly because of the transported dust coming with the northwest winds prevailing in Kuwait from the Arabian deserts and Iraq.

The vehicular technology has integrated many features in the system, which enhances the safety and comfort of the user. Among these features, heating, ventilation, and air conditioning (HVAC) is the only feature that maintains the set cabin air temperature (CAT). The user’s command drives the set CAT, and the thermostat provides feedback to the HVAC to maintain the set CAT. The CAT is increased by extracting the heat from the engine surface produced by the fuel combustion, whereas the CAT is reduced by the known processes of the air conditioning system (ACS). Therefore, the CAT driven by the user’s command may not be optimal, and estimating the optimal CAT is still unsolved. In this work, the user was allowed to input a range for CAT instead of a single value. Optimal HVAC criteria were defined, and the CAT was estimated by performing iterative analysis in the user-selected range satisfying the criteria. The HVAC criteria were defined based on two measurable parameters: air conditioning refrigerant fluid pressure (ACRFP) and engine surface temperature (EST) empirically defined as the vector CATOP. In this article, a NARX DL model by mapping the vehicle-level vectors (VLV) to predict the CATOP in real-time using field data obtained from a 2020 Cadillac CT5 test vehicle. Utilising the DL model, CATOP for future time steps were predicted by varying the CAT in the definite range and applying HVAC criteria. Thus, an optimal set CAT was estimated, corresponding to the optimal CATOP defined by the HVAC criteria. We performed the validation of the DL model for multiple datasets using traditional statistical techniques, namely, signal-to-noise ratio (SNR) values, first-order derivatives (FOD), and root-mean-square error (RMSE).

Background: this RCT assesses the 18 months clinical outcomes after regenerative therapy of periimplantitis lesions using either an electrolytic method (EC) to remove biofilms or a combination of powder spray and electrolytic method (PEC). Materials and Methods: Twenty-four patients (24 implants) suffering from periimplantitis were randomly treated by EC or PEC followed by augmentation and submerged healing. Probing pocket depth (PPD), Bleeding on Probing (BoP), suppuration and standardized radiographs were assessed before surgery (T0), 6 months after augmentation (T1), 6 (T2) and 12 (T3) months after replacement of the restoration. Results: Mean of PPD changed from 5.8 ± 1.6 mm (T0) to 3.1 ± 1.4 mm (T3). While BoP and suppuration at T0 was 100 % BoP decreased at T2 to 36.8 % and at T3 to 35.3 %. Suppuration could be found 10.6% at T2 and 11.8% at T3. Radiologic bone level measured from the implant shoulder to the first visible bone to implant contact was 4.9 ± 1.9 mm at me-sial and 4.4 ± 2.2 mm at distal sites (T0) and 1.7 ± 1.7 mm and 1.5 ± 17 mm at T3. Conclusions: Significant radiographic bone fill and improvement of clinical parameters were demonstrated 18 months after therapy.

TRPOMI instrument aboard Sentinel-5P is a relatively new, high-resolution source of information about atmosphere composition. One of the primary atmospheric trace gases that we can observe through it is nitrogen dioxide. By now, we were using the chemical weather model (GEM-AQ) as a mean for estimating nitrogen dioxide concentration on a regional scale. Although well established in atmospheric science, the GEM-AQ simulations were always based on emission data, which in the case of the energy sector were reported by stack owners. In this paper, we attempted to compare the TROPOMI and GEM-AQ derived VCDs over Poland with a particular focus on large point emitters. We also checked how cloudy conditions influence TROPOMI results. Finally, we tried to link the NO2 column number densities with surface concentration using boundary layer height as an additional explanatory variable

The concept of this prototype is to create a cold air film layer, in indoor side of the window. The function of this extra cold air layer is to increase the amount of window resistance and decrease its U-Value. It provide air film layer by using the same concept of desert cooler or wind catcher. They both bring the hot air from outside then let it go throw straw miost with cold water. After hot air move through straw, it would become cold, thus increase the window resistance and decrease the haet gian, therefore, decrease the cooling load. So, this window model works by heating the air in air room by sun radiation, then after a while, air pressure will rise and its volume will increase then it will impulse to wet hay, and become cold. Then there is fins to guide air flow to its correct direction, thus inner side of window will become cold, not like other type of window which when temperature rise, the inner side of window become hot. So, this window prevents heat transition and creare regenereted trubouland air flim in the inner side of the window. Using calculation to find air film characteristics and WINDOW7.7 software to calculate heat gain through window, shows that it is expected from this prototype to reduce heat gain by 6.85 % for double glazed clear window.

Today, air quality is one of the global concerns that governments are facing. One of the main air pollutants is the particulate matter (PM) that affects human health. This article presents the modeling of a purification system by means of negative air ions (NAIs) for air pollutant removal, using computational intelligence methods. The system uses a high voltage booster output to ionize air molecules from stainless steel electrodes; its particle-capturing efficiency reaches up to 97%. With two devices (5 x 2 x 2.5 cm), 2 trillion negative ions are produced per second, and the particulate matter (PM 2.5) can be reduced from 999 to 0 mg / m3 in a period of approximately 5 to 7 minutes (in a 40 x 40 x 40 cm acrylic chamber). This negative ion generator is a viable and sustainable alternative to reduce polluting emissions, with beneficial effects on human health.

Understanding the relationships between land cover/urban structure patterns and air pollutants is key to sustainable urban planning and development. In this study, we employ a mobile monitoring method to collect PM_2.5 and BC data in the city of Philadelphia, PA during the summer of 2019 and apply the Structure of Urban Landscapes (STURLA) methodology to examine relationships between urban structure and atmospheric pollution. We find that, while PM_2.5 and BC vary by STURLA class, many of the differences in pollutant concentrations between classes are not significant. However, we also find that the proportions in which STURLA components are present throughout the urban landscape can be used to predict urban air pollution. Among frequently sampled STURLA classes, gpl hosted the highest PM_2.5 concentrations on average (16.60 _± 4.29 µg/m³), while tgbwp hosted the highest BC concentrations (2.31 _± 1.94 µg/m³). Furthermore, STURLA combined with machine learning modeling was able to correlate PM_2.5 (R²= 0.68, RMSE 2.82 µg/m³) and BC (R² = 0.64, RMSE 0.75 µg/m³) concentrations with the urban landscape and spatially interpolate concentrations where sampling did not take place. These results demonstrate the efficacy of the STURLA methodology in modeling relationships between air pollution and land cover/urban structure patterns.

Air pollution contributes to a critical environmental problem in various towns and cities. With the emergence of the smart cities concept, appropriate methods to curb associated with exposure to pollutants must have been a portion of appropriate urban development policy. This study presents a technologically driven air quality solution in smart cities to advertise energy-efficient and cleaner sequestration in these areas. It aims to address the issue of how to integrate the data-based strategies and artificial intelligence into efficient public sector pollution management in smart cities as a core part of the smart city definition. Exploratory research has been used in 152 smart cities, and environmental experts contributed to this study. It further addresses the technical criteria for implementing such a framework that the public administration uses to prepare the renovation of public buildings, minimize energy use and costs, and link these smart police stations to monitor air pollution as a part of integrated cities. Such a digital transition in resource management will increase public governance's energy performance, a higher standard of operation, and a healthier environment.

Recently, we have witnessed a booming development of composites and multi-dopant metal oxides to be employed as novel photocatalysts. Yet the practical application of photocatalysis for environmental purposes is still elusive. Concerns about the unknown fate and toxicity of nanoparticles, unsatisfactory performance in real conditions, mass transfer limitations and durability issues have so far discouraged investments in full-scale applications of photocatalysis. Herein, we provide a critical overview of the main challenges that are limiting large-scale application of photocatalysis in air and water/wastewater purification. We then discuss the main approaches reported in the literature to tackle these shortcomings, such as the design of photocatalytic reactors that retain the photocatalyst, the study of degradation of micropollutants in different water matrices, and the development of gas-phase reactors with optimized contact time and irradiation. Furthermore, we provide a critical analysis of research-practice gaps such as treatment of real water and air samples, degradation of pollutants with actual environmental concentrations, photocatalyst deactivation, and cost and environmental life-cycle assessment.

: During the period of COVID-19, the Chinese government implemented a series of actions to prevent the spread of the virus. It is noticed that these preventive actions have generated positive effects on air pollution in Wuhan and Beijing. And, due to the differences in city functions, geographic locations, meteorological conditions, and preventive action details between the two cities, noticeable difference is observed on how they reduced air pollution. This unfortunate incident has become a social sample for studying the industrial and livelihood activities impact on air pollution, otherwise would be highly impossible. This paper starts from observing data from NASA's real-time fine particulate matter (PM2.5) and NO2, and comparing the air pollution in this special time domain with previous years. It is discovered that both PM2.5 and NO2 have been reduced in Wuhan, while only NO2 has significant reduction in Beijing, during the COVID-19 responses. This suggests that the human activity suppression by the COVID-19 control yields different effects on different pollutants and in different cities. Possible reasons for such effects are analysed by considering the public health control levels as well as the pollutant migration, industrial activities, and the weather conditions.

As air traffic demand grows, robust, data-driven anomaly detection methods are required to ensure that aviation systems become safer and more efficient. The terminal airspace is identified as the most critical airspace for both individual flight-level and system-level safety and efficiency. As such, developing data-driven anomaly detection methods to analyze terminal airspace operations is paramount. With the expansion of ADS-B technology, open-source flight tracking data has become more readily available to enable larger-scale analyses of aircraft operations. This paper makes a distinction between spatial metrics in ADS-B trajectory data and energy metrics derived from ADS-B trajectory data. Motivated by the limited number of approaches that simultaneously consider both spatial and energy metrics, this paper introduces the concepts of spatial anomalies and energy anomalies. In particular, it proposes a novel, unified framework for detection of spatial and energy anomalies in ADS-B trajectory data (and associated derived metrics). The framework consists of three main parts - a data processing procedure, a spatial anomaly detection method, and an energy anomaly detection method. The framework is demonstrated utilizing four months of ADS-B trajectory data associated with arrivals at San Francisco International Airport, and the relationship between the spatial and energy anomalies in this terminal airspace is explored. The results that stem from the implementation of this framework indicate that if an aircraft is spatially not conforming to an identified set of air traffic flows representing standard spatial operations, then this aircraft is more likely to experience non-conformance to standard operations in its energy metrics. Aviation operators, such as air traffic controllers, may benefit from this observation, as it may factor into decision-making in instances where there is the potential to instruct an aircraft to spatially deviate from standard operations. Additionally, this research revealed underlying differences between trajectories that are spatially nominal yet energy-anomalous and those trajectories that are spatially anomalous and energy-anomalous. Focusing solely on energy anomaly detection does not provide insight into potential spatial-related decisions that may have been made to result in off-nominal energy behavior.

Air conditioning system of electric vehicles has new change as the internal combustion engine is being replaced with electrified AC motor. With large amount of batteries installed at the bottom of frame, the conventional compressor which is belt-driven can be removed and another AC motor can play the role for air conditioning in electric vehicles. From this change, the system efficiency would be improved since it is possible to control the electrified compressor independently from traction system in contrast with the belt-driven compressor. As a result, by applying the electrified compressor for air conditioning system, the whole system can achieve better efficiency and longer driving distance, which is most important in electric vehicles. In this paper, 3-phase interior permanent magnet synchronous motor (IPMSM) was designed using lumped-parameter model and finite element method.

Air pollution has become the world’s single biggest environmental health risk of the past decade, causing about 7 million yearly deaths worldwide. One of the dominant air pollutants is fine particulate matter (PM2.5), a product of combustion. Exposure to PM2.5 has been associated with decreased lung function, impaired immunity, and exacerbations of lung disease. Accumulating evidence suggests that many of the adverse health effects of PM2.5 exposure are associated with lung inflammation and oxidative stress. While the physical structure and surface chemistry of PM2.5 are surrogate measures of particle oxidative potential, little is known about their contributions to negative health effects. In this study, we used functionalized carbon black particles as surrogates for atmospherically aged combustion formed soot to assess the effects of PM2.5 surface chemistry in lung cells. We exposed the BEAS-2B lung epithelial cell line to different soot at a range of concentrations, and assessed cell viability, inflammation, and oxidative stress. Our results indicate that exposure to soot with varying particle surface composition results in differential cell viability rates, expression of pro-inflammatory and oxidative stress genes, and protein carbonylation. We conclude that particle surface chemistry, specifically oxygen content, in soot modulates lung cell inflammatory and oxidative stress responses.

The present study investigates the relationship between the transmission of COVID-19 infections and climate indicators in Dhaka City, Bangladesh, using coronavirus infections data available from the Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh. The Spearman-ranked correlation test was carried out to study the association of seven climate indicators, including humidity, air quality, minimum temperature, precipitation, maximum temperature, mean temperature and wind speed with the COVID-19 outbreak in Dhaka City, Bangladesh. The study found that, among the seven indicators, only three indicators (air quality, minimum temperature and average temperature) have a significant relationship with new COVID-19 cases. The results of this paper will give health regulators and policymakers valuable information to lessen the COVID-19 infection in Dhaka and other countries around the world.

A new coronavirus (SARS-CoV-2) have determined a pneumonia outbreak in China (Wuhan and Hubei) on December 2019. While pharmaceutical and non-pharmaceutical intervention strategies are strengthened worldwide, the scientific community has been studying the risk factors associated with SARS-Cov-2, to enrich epidemiological information. For a long time, before the industrialized era, air pollution has been a real and big health concern and it is today a very serious environmental risk for many diseases and anticipated deaths in the world. It has long been known that air pollutants increasing the invasiveness of pathogens for humans by acting as a carrier and making people more sensitive to pathogens through a negative influence on the immune system. Based on scientific evidences, the hypothesis that air pollution, resulting from a combination of factors such as meteorological data, level of industrialization as well as regional topography, can acts both as an infection carrier as a harmful factor of the health outcomes of COVID-19 disease has been raised recently. This hypothesis is turning in scientific evidence, thanks to the numerous studies that have been launched all over the world. With this review, we want to provide a first unique view of all the first epidemiological studies relating the association between air pollution and SARS-CoV-2. Major findings are consistent, highlighting the important contribution of air pollution on the COVID-19 spread and with a less extent also PM₁₀.

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

In the present paper, a measure of the influence of irregularities of the underlying surface (for instance, the real terrain profile) on the dynamics of air flow is estimated. It is shown that these irregularities significantly perturbing the pressure, density, velocity and temperature of air flow; for perturbed pressure, density, velocity and temperature of air flow the closed formulas in the Fourier integral form are obtained. In addition, in the present paper, it is proved that due to these perturbations, at a certain altitude of the atmosphere some surface of the "sturdy wall" form appears, on which the vertical and horizontal components of the air flow velocity become infinitesimal and infinitely large, respectively.

This retrospective study evaluates the effect of a telemedicine program developed in the central Catalan region in lowering the environmental footprint by reducing the emission of atmospheric pollutants thanks to a reduction in the number of hospital visits involving journeys by road. Between January 2018 and June 2019 a total of 12,322 referrals were made to telemedicine services in the primary care centers, avoiding a total of 9,034 face-to-face visits. In total, the distance saved was 192,682 km, with a total travel time savings of 3,779 hours and a total fuel reduction of 11,754 liters with an associated cost of €15,664. This represents an average reduction of 3,248.3 g of carbon dioxide, 4.05 g of carbon monoxide, 4.86 g of nitric oxide and 3.2 g of sulphur dioxide. This study confirms that telemedicine reduces the environmental impact of atmospheric pollutants emitted by vehicles, reducing the number of journeys made for face-to-face visits and can contribute to environmental sustainability.

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

The purpose of this study is to assess the concentration-response relations between conjunctivitis and exposure to ambient ozone. This retrospective study includes emergency department (ED) visits for conjunctivitis in Edmonton, Canada, for the period April 1992–March 2002. Daily average levels of ozone (range: 1.2–50.9, ppb), of temperature, and of relative humidity were estimated and used for the period of the study. For each of the considered exposure lags, (from 0 to 9 days), six different models were fitted to estimate the concentration-response function. The goodness of fit was assessed using the Akaike information criterion. During the period of the study, 17,211 ED visits for conjunctivitis were recorded and used. For all subjects together, a positive statistically significant association was obtained for the exposure lagged by 5 days. For female subjects, lags 1, 3, and 9 had positive statistically significant associations (lag 2 had negative associations). For male subjects, only lag 5 had a positive statistically significant association. The estimated non-linear concentration-response functions for the considered groups (all, males, females) and lags, revealed the associations along the exposure levels. The fitted shapes are described by algebraic functions and may have various forms. The estimated functions are useful to determine the risk associated with exposure to ground-level ozone.

Air quality has been a major concern throughout the world, Nigeria inclusive. The monitoring of air quality involves indoor and outdoor air quality. In this study, our concern was on indoor air quality. The aim of this study was to assess the air quality of residential homes (17), classrooms (3), hospitals (2), offices (5), Shops (2), and laboratories (5) in Akure, Nigeria in terms of formaldehyde (HCHO), total volatile organic compound (TVOC), Particulate matter (PM_1.0; PM_2.5, and PM₁₀). A Multifunction Air Detector was used for the assessment using the manufacturers’ procedures and the locations were identified using a Mini GPS. The results revealed as follows: HCHO (0.001-0.030 mg/m³), TVOC (0.003-362 mg/m³), PM_1.0 (004-014 µg/m³), PM_2.5 (006-020 µg/m³), and PM₁₀ (006-022 µg/m³). The results obtained were below the 24 h pollution recommended standards (0.1 mg/m³- HCHO; TVOC; 10-20 μ/m³ PM) of EPA and WHO. Statistically, there were correlations within the pollutants and weather. The Indoor air quality (IAQ) depicted the areas as ‘good,’ and toxicity potential (TP) were below unity. Although the locations looked safe, it is recommended that constant monitoring of the indoors should be ensured and proper ventilation should be provided.

Rapid urbanization, increasing population and increased industrialization to cater to demands of the growing population has imposed upon us a huge environmental cost. The significantly deteriorated air quality across the globe is associated with a direct and indirect impact on public health. While associated disorders such as chronic obstructive pulmonary diseases, heart failures are well documented, less is known about the biological basis of the process. We hypothesize that the worsening air quality may likely impact common systemic inflammatory processes, thus driving communicable and non-communicable diseases alike.Receptor mediated entry of particulate matter (PM2.5) results in activation of signaling cascades which culminate in production of inflammatory chemokine and cytokine responses, traversing through the blood mediating impacting not only on other organs but also dysbiosis of microflora. For the purpose of the review we choose tuberculosis (TB) as a model for communicable infectious disease and type 2 diabetes mellitus (T2DM) as a marker for non-communicable disorder. The increasing prevalence of these co-morbidities and the burdening of public health systems justifies this example. However the hypothesis may be applicable to other inflammation driven disorders also.

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

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

The integration of modern technologies like intramedullary fixators and advanced biometallic alloys has revolutionized traumatology and orthopedics. While these innovations have improved treatment, the exploration of new materials for implants persists. Tantalum and niobium, both non-toxic with similar properties, are preferred for titanium-based biomedical alloys due to their exceptional biocompatibility and corrosion resistance. Acting as stabilizers in titanium alloys, they form passive oxide layers resisting corrosion and remain compatible with biological systems. The novel Ti21Nb6Ta (TNT) alloy promises enhanced osteosynthesis outcomes. Our in vivo research on experimental animals evaluated the biocompatibility and osteoinduction of TNT compared to Ti-6Al-4V (BT-6) alloy (control group). The study comprised three experiments across different animal species, assessing acute toxicity, irritant effects, and long-term biocompatibility and osteoinduction through simulated osteosynthesis. Results indicated that aqueous extracts from both alloys were non-toxic and non-irritating. Furthermore, both demonstrated high biocompatibility and active osteoinduction potential after three months of implantation.

Zinc (Zn) is the second most abundant metal in the human body, and is essential for the function of 10% of all proteins. As metals cannot be synthesized or degraded, they must be assimilated from diet by specialized transport proteins, which unfortunately also provide an entry route for the toxic metal pollutant cadmium (Cd). The intestinal absorption of Zn depends on the composition of food that is consumed, firstly the amount of Zn itself, and then the quantity of other food constituents such as phytate, protein and calcium (Ca). In cells, Zn is involved in regulation of intermediary metabolism, gene expression, cell growth, differentiation, apoptosis, and antioxidant defense mechanisms. Cellular influx, efflux, subcellular compartmentalization, and trafficking of Zn are coordinated by transporter proteins, the Solute-Linked Carrier 30A and 39A (SLC30A and SLC39A), known as the ZnT and the Zrt-/Irt-like protein (ZIP). Because of its chemical similarity with Zn and Ca, Cd disrupts the physiological functions of both. The concurrent induction of a Zn efflux transporter ZnT1 (SLC30A1) and metallothionein by Cd disrupts the homeostasis and reduces the bioavailability of Zn. The present review highlights the increased mortality and the severity of various diseases, including those induced by COVID-19 infections, among Cd-exposed persons and the roles of Zn and other transport proteins in the manifestation of Cd cytotoxicity. Special emphasis is given to the potential protective effects of Zn against bone, lung and heart diseases associated with Cd exposure. The difficult challenge of determining a permissible intake level of Cd is discussed in relation to the recommended dietary Zn intake levels.