The combination of ecologically acceptable polysaccharide and graphene oxide (GO) nanoparticles was used (Chitosan)
producing the fuel cell membrane for alkaline straight ethanol (DAEFC).
Due to its great power efficiency and minimal influence on the environment, this kind of fuel cell has a lot of potential uses.
Recently, the performance of polymer-based DAEFC was significantly improved by the use of graphene. Since the roughness plays an important role in the charge transfer, Herein we present our study of the change in the roughness of GO blended Chitosan using different preparation methods and different concentrations of GO.

An electronic nose (e-nose) is an electronic device composed of one or more odor sensors, a microcontroller, electronic components, and software that acquire and analyze a gas or volatile organic compound (VOC) present in an environment. E-noses attempt to identify the gas or VOC based on their chemical composition, sending electronic data about the detected odor signature to a computer, akin to an animal nose identifying odors and sending electro-chemical signals to an animal brain. Then the computer will attempt to identify the perceived odor. E-noses have been used in human-computer interaction in specialized computing applications containing a user interface (UI) with a purpose, supporting its user to identify an odor and its properties, and communicating information about the odor on the UI.
E-nose information can be communicated to the user in different information presentation modalities using practically all the human sensory channels. In the context of HCI, a modality is considered as a single independent input/output sensory channel between a human and a computer. Odor fingerprint results generated by the e-nose can be presented visually, and aurally, playing sound through a buzzer. Other sensory modalities could be used, such as representing odor information through haptics that can be perceived with the sense of touch.
Recent advances in the development of e-noses have been extensive, as the literature of recent years can testify. This work describes some of the current e-noses development projects impacting people through HCI.

Humans have undergone a technology innovation in daily personal lives as a result of the invention of the computer but, afterward, the web, as well as we carry on living in a technologically advanced world. Artificial intelligence (AI) is a term that we always keep hearing among computer scientists because we're all aware that it is a fast-expanding discipline in a multitude of areas. Numerous problems, including dynamic, unpredictable behaviors, and intricacy, are present in the architecture of research and production tools and procedures. Several research and engineering experts' working methods have recently changed as a result of the development of larger datasets, fast processing speed, cloud technology, and artificial intelligence procedures. For researchers and producers, such techniques provide exhilarating, cutting-edge solutions to difficult problems. In contrast, artificial intelligence (AI) is a broad field. The availability of a wide range of concepts, strategies, and techniques makes it difficult to select the best AI approach for the correct technical or production industry and settings. Our examination of the works on numerous Automatic industrial claims and production through using suggested classification provided valuable understanding. Additionally, we identified plans for potential AI application investigation in the fields of engineering besides production.

One of the main sources of global warming is greenhouse gasses, most importantly carbon dioxide. Reducing CO₂ emissions, as well as its utilization or storage, is a global challenge to tackle climate change. In this work, the operating conditions of the pilot CO₂ capture unit are studied using the ASPEN PLUS® software. This study describes the methodology of the simulations and main results. The unit consists of one scrubber and one stripper. For carbon dioxide absorption from gas streams, aqueous solvents K₂CO₃ is used. The effect on absorption of CO₂ and regeneration of carbon dioxide and potassium carbonate were studied by varying parameters of pressure, temperature and concentration of solvent. For each parameter, three values were evaluated with the following ranges: pressure 0.3-1bar; temperature 80-100 ^oC; concentration of potassium carbonate 15-25wt%. The optimum operating conditions of the pilot unit are pressure 0.3bar; stripper temperature 100^oC and solvent concentration 15wt%. Under these conditions, 99.91% CO₂ capture and 85.46% CO₂ regeneration were achieved. The present research aims to find the optimal operating parameters of the pilot plant, to validate the model with the experimental data. In this way, the model parameterization can be used for the design of large-scale CO₂ capture units.

Zinc oxide (ZnO) is an n-type II-VI semiconductor material that has gained prominence in recent decades due to the possibility of applications in the most diverse scientific areas, such as photonics, optoelectronics, magnetism, and biological systems. In this context, the scientific community seeks alternative synthetic methodologies to those already established in the literature, emphasizing the use of organic solvents, which are increasingly efficient, low-cost, and easy to reproduce. Thus, the present work proposed a method of colloidal aqueous synthesis, using different precursors of zinc and cobalt salts in a molar fraction according to the expression, Zn_1-xCo_xO (x = 0.05, 0.075, 0.10), mercaptosuccinic acid (MSA) as a stabilizing agent, in a stoichiometric ratio of 1:4 of Zn:MSA, and NaOH as a precipitating agent at pH = 11. The colloidal suspension obtained after 90 min of synthesis was frozen, remaining stable after the thawing of the suspension. A mixture of isopropyl alcohol and acetone was used to force the precipitation process. The precipitates obtained were washed with water and ethyl alcohol for subsequent heat treatment for one hour in an oven at 120 ºC and annealed at 300 ºC for two hours. The results confirmed the formation of pure and cobalt-doped ZnO nanoparticles from X-ray diffractometry characterization. To evaluate their properties, studies of compositional analysis and size distribution of ZnO nanoparticles using characterization techniques such as inductively coupled plasma spectroscopy (ICP) and transmission electron microscopy (TEM) are being carried out to obtain even more promising results in this field.

This paper studied, the structural, microstructural, thermal, electrical, and dielectric properties of ZnS nanoparticles synthesized using the co-precipitation technique. The precipitate was characterized by X-ray diffraction (XRD) which confirmed the formation of a single-phase cubic nanocrystalline structure; crystalline size was obtained with different three models.

Information regarding thermal transition such as melting, oxidation, and crystallization was revealed using Differential scanning calorimetry and thermogravimetry (DTG/TG).

Transmission electron microscopy (TEM) images were performed to explore the stability, morphology, and other properties of ZnS nanoparticles. An EDX analysis was applied to confirm the constituents and an element estimation. For the importance of the crystallite size of the prepared ZnS different techniques were utilized to estimate the crystallite size, and the calculations confirmed the formation of ZnS in nanocrystal form. The electrical and dielectric properties of the synthesized nanocrystals were measured at different temperatures over a wide range of frequencies from about 50 Hz up to 5 MHz. Regarding the frequency dependence of both the AC conductivity and dielectric constant, the conduction mechanism and the source of the relaxation were revealed.

at different temperatures over the completely studied range of frequency, The real part of electric modulus (M') and imaginary part of electric modulus (M'') components were calculated and (M'') showed an asymmetrical peak approximately centered in the dispersion region of M"(ω). The Activation energy (E_a) was found to decrease with increasing frequency.

The Leaf Area Index (LAI) is an important algorithm for studying the health status of vegetation. In the study, the impact of hydrocarbon micro-seepage on vegetation in Ugwueme, South-Eastern Nigeria was investigated using the LAI image classification approach. Landsat TM 1996, ETM+ 2006, and OLI 2016, satellite images which were downloaded from the United States Geological Survey (USGS) portal, were used to classify various LAI maps as low, moderate, and high classes. The spatial-temporal analysis revealed that the low, moderate, and high LAI density classification changed from 41.24 km² (50.43%), 33.98 km² (41.54%), and 6.56 km² (8.02%) in 1996 to 23.70 km² (28.98%), 29.48 km² (36.04%), and 28.60 km² (34.97%) in 2006, and to 38.23 km² (46.74%), 27.54 km² (33.68%), and 16.01 km² (19.58%) in 2016. The stimulation analysis shows that by 2030 (the 14-year planning period), the low, moderate, and high LAI density classifications will be 8.86 km² (10.82%), 24.28 km² (29.70%), and 48.63 km² (59.46%). The study shows that LAI is an important algorithm that can effectively be used to study the health status of vegetation in an ecosystem.

According to European Union data, on average 173 kg per person of total food waste (organic waste) are produced annually, of which 92 kg per person come from households (organic waste). Food waste is defined the waste from household, restaurants, canteens, food industries as well as markets. The importance of food waste stretches from environmental pressures to economic and social impacts. An Environmental technology for the biodegradation of food waste is Anaerobic digestion. Is a very attractive technique and combines waste treatment and renewable energy recovery. This study investigates the characteristics of food waste leachates from composting buckets and their valorization as substrate for anaerobic digestion process.
A complete characterization of different food waste leachates was conducted (pH, COD, VFAs, heavy metals etc.). Food waste leachates proved to be an ideal feedstock for Anaerobic digestion. In this direction, batch tests were performed to evaluate the methane yield of food waste leachates under different operating conditions. Three different SIR ratios were tested (0,5, 1,0 and 1,5) A SIR equal to 0.5 proved to be the as the higher methane yield was achieved. The removal of COD under all operating conditions was higher than 70% with the higher removal (85,18%) for an SIR equal to 1.5.

Periodontitis is an infectious inflammatory disease that damages the tissues supporting the tooth, causing tooth loss due to bone resorption and lack of bone stability. Periodontal regeneration remains a challenge due to the complex and well-arranged structure of the periodontium, which comprises the cementum, alveolar bone and periodontal ligament. Current clinical techniques yield variable and unpredictable outcomes and cannot regenerate all the periodontal tissues, including hard tissues (cementum and alveolar bone) and soft tissues (periodontal ligament). Hydrogels are highly hydrophilic polymeric networks that can simulate the native microenvironment of cells. Thus, hydrogels are suitable candidates for periodontal regeneration due to their capacity to interact with both soft and hard tissues, as well as to conform to the 3D defect through minimal invasion procedures.

Cell-derived decellularized extracellular matrix (dECM) has been reported as a promising biomaterial for Tissue Engineering and Regenerative Medicine applications, since dECM derived from cells can recreate cellular niches and model cellular functions, mimicking the composition and structure of the native microenvironment. In this work, collagen hydrogels were developed by incorporating lyophilized cell-derived dECM and their effects on the proliferation and osteogenic/periodontal differentiation of dental stem cells were evaluated. Overall, our results confirmed the beneficial effect of dECM-derived hydrogels in proliferation and periodontal differentiation of dental stem cells. These results suggest that the novel dECM technology might represent a potential approach to achieve complete periodontal regeneration.

Adverse health effects caused by lead (Pb) exposure have been extensively documented. Lead in residential soils has long been recognized as a principal source of excess Pb absorption in young children. Weathering, chipping, scraping, sanding, and sandblasting of structures bearing Pb-based paints result in Pb becoming entrained in soils that are continuously tracked inside the house in the form of dust, which remains the primary route of chronic human exposure driving the health risk.

The hazard imposed by Pb within soils is dependent on soil properties and the geochemical forms of Pb in soils. Soil properties such as pH, soil organic matter, clay and carbonate contents can affect the geochemical form of Pb and consequently, Pb bioaccessibility and human bioavailabity. Therefore, this study was performed to assess varying geochemical forms of Pb and hence its availability in Pb contaminated residential soils with different physio-chemical properties. An extensive field survey and subsequent collection of soils from 10 residential sites in San Antonio, TX (with alkaline pH) as well as 10 residential sites with acidic pH from Baltimore, were conducted. Soils were analyzed for texture, pH, salinity (EC), Cation Exchange Capacity (CEC), total iron, aluminum, Pb, extractable iron, aluminum, Pb, total and extractable calcium and magnesium, total and extractable P, Soil Organic Matter (SOM), total carbon. Results showed that soils collected from San Antonio were alkaline (pH ranging from 7.43 to 7.87), whereas those from Baltimore were acidic (pH ranging from 5.16 to 6.25). Generally, San Antonio samples had relatively high salinity (EC ranging from 217-1051 µS/cm), high clay content (7.33% - 65.22%), moderate to high SOM (5.23% - 12.89%), and high total Pb concentration, with the highest being 7768 mg/Kg. Baltimore samples were characterized by low salinity (EC ranging from 97-715 µS/cm), low clay content (2.1% - 5.2%), low SOM (0.64% - 2.27%), and the highest total Pb concentration of 5373 mg/Kg). Studies to identify the various geochemical forms of lead in San Antonio and Baltimore soils are currently in progress.