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Spectroscopic analysis was employed to evaluate the quality of three bell pepper varieties within the 350–1150 nm wavelength range. Quality parameters such as firmness, pH, soluble solids content, titratable acids, vitamin C, total phenols, and anthocyanins were measured. To enhance data reliability, principal component analysis (PCA) was used to identify and remove outliers. Raw spectral data were initially modeled using partial least squares regression (PLSR). To optimize wavelength selection, support vector machines (SVMs) were combined with genetic algorithms (GAs), particle swarm optimization (PSO), ant colony optimization (ACO), and imperial competitive algorithm (ICA). The most effective wavelength selection method was subsequently used for further analysis. Three modeling techniques—PLSR, multiple linear regression (MLR), and artificial neural networks (ANNs)—were applied to the selected wavelengths. PLSR analysis of raw data yielded a maximum R2 value of 0.98 for red pepper pH, while the lowest R2 (0.58) was observed for total phenols in yellow peppers. SVM-PSO was determined to be the optimal wavelength selection algorithm based on ratio of performance to deviation (RPD), root mean square error (RMSE), and correlation values. An average of 15 effective wavelengths were identified using this combined approach. Model performance was evaluated using root mean square error of cross-validation and coefficient of determination (R2). ANN consistently outperformed MLR and PLSR in predicting firmness, pH, soluble solids content, titratable acids, vitamin C, total phenols, and anthocyanins for all three varieties. R2 values for the ANN model ranged from 0.94 to 1.00, demonstrating its superior predictive capability. Based on these results, ANN is recommended as the most suitable method for evaluating the quality parameters of bell peppers using spectroscopic data.

To achieve wheat starch acetylation (AC) with a high degree of substitution (DS), the acetylation process was carried out using various ultrasonication frequencies, including 25 kHz, 40 kHz, and 25 + 40 kHz. In the second step, wheat starch's ultrasound-assisted acetylation (UAA) is simulated using various approaches including the rheology models, non-isothermal reaction kinetics, and flow/acoustic modelling. The computational fluid dynamics (CFD) simulation solves the non-linear acoustic governing equation to determine the flow field and the amount of delivered ultrasound energy. The acetylated starch increased peak and final viscosity, with the highest values observed for the 25 + 40 kHz frequency than other single frequencies (25 kHz and 40 kHz). The viscosity of the starch is specified based on the experimental data using Herschel–Bulkley, power law, and Casson rheology models. According to differential scanning calorimetry (DSC) analysis, the gelatinization parameters and enthalpy of gelatinization (ΔHgel), were found to be lower in acetylated starches at the frequency of 25 + 40 kHz compared to those at frequencies of 25 kHz and 40 kHz, as well as native starches (NS). Moreover, the gelatinization process is examined by implementing the non-isothermal reaction kinetics to obtain the activation energy and reaction order. Based on the results obtained, implementing sonication at 25 kHz reduces the activation energy by 70.3 % compared to native starch. However, the same parameter is obtained to be 69.9 % and 67.1 % for the application of 40 and 25 + 40 kHz transducers, respectively. Additionally, during the sonication treatment, the yield shear stress increases between 24.1 and 31.8 %, based on the applied frequency. Morphology analysis determined by scanning electron microscopy (SEM) revealed that the surfaces and small granules underwent more damage in acetylated starches at frequencies of 25 kHz and 40 kHz. However, in acetylated starches at 25 + 40 kHz, the larger granules were more affected than the smaller ones.

The utilization of gas sensors has the potential to enhance worker safety, mitigate environmental issues, and enable early diagnosis of chronic diseases. However, traditional sensors designed for such applications are often bulky, expensive, difficult to operate, and require large sample volumes. By employing microfluidic technology to miniaturize gas sensors, we can address these challenges and usher in a new era of gas sensors suitable for point-of-care and point-of-use applications. In this review paper, we systematically categorize microfluidic gas sensors according to their applications in safety, biomedical, and environmental contexts. Furthermore, we delve into the integration of various types of gas sensors, such as optical, chemical, and physical sensors, within microfluidic platforms, highlighting the resultant enhancements in performance within these domains.

On a global scale, millions of tons of diverse agricultural residues are generated annually. Most of these wastes are burned or dumped in landfills, which causes environmental pollution. Addressing environmental issues arising from agricultural waste materials, in addition to mitigating heating and cooling expenses in the construction sector, is an interesting challenge for researchers. The utilization of agricultural wastes in different parts of construction is producing positive findings day by day, and investigating research in this field is a curiosity for researchers. This short study reviewed the most recent achievements in using agricultural wastes as a substitute or additive material for construction. Using these wastes as aggregate, ash (as a supplementary for cement), or fibers for foam concrete, insulation materials, etc. has been reviewed. This review has focused on very recent published papers. Several studies have demonstrated the effective influences of agro-waste materials in construction, like retaining the compressive strength (155 MPa) of concrete at standard levels and reducing heat losses in buildings (69% energy savings for brick insulated using wheat straw), as well as sound insulation. The use of agro-waste materials for insulation positively improved thermal conductivity, costs, and energy savings. However, some wastes did not provide a high added value, which shows that more investigations still need be performed to fill this gap in the research. Considering the global scale of agricultural waste generation and the potential benefits to both the environment and construction industry, continued research in this area is essential.

Fat metabolism is an important modifier of aging and longevity in Caenorhabditis elegans. Given the anatomy and hermaphroditic nature of C. elegans, a major challenge is to distinguish fats that serve the energetic needs of the parent from those that are allocated to the progeny. Broadband coherent anti-Stokes Raman scattering (BCARS) microscopy has revealed that the composition and dynamics of lipid particles are heterogeneous both within and between different tissues of this organism. Using BCARS, we have previously succeeded in distinguishing lipid-rich particles that serve as energetic reservoirs of the parent from those that are destined for the progeny. While BCARS microscopy produces high-resolution images with very high information content, it is not yet a widely available platform. Here we report a new approach combining the lipophilic vital dye Nile Red and two-photon fluorescence lifetime imaging microscopy (2p-FLIM) for the in vivo discrimination of lipid particle sub-types. While it is widely accepted that Nile Red staining yields unreliable results for detecting lipid structures in live C. elegans due to strong interference of autofluorescence and non-specific staining signals, our results show that simple FLIM phasor analysis can effectively separate those signals and is capable of differentiating the non-polar lipid-dominant (lipid-storage), polar lipid-dominant (yolk lipoprotein) particles, and the intermediates that have been observed using BCARS microscopy. An advantage of this approach is that images can be acquired using common, commercially available 2p-FLIM systems within about 10% of the time required to generate a BCARS image. Our work provides a novel, broadly accessible approach for analyzing lipid-containing structures in a complex, live whole organism context.

The aim of this study is to use the response surface methodology (RSM) to mathematically model the response parameters and emission of greenhouse gases (GHG) and optimize the drying variables for a carrot dried with the microwave method using various pretreatments. To this end, the influence of the drying parameters (independent), such as microwave power and slice thickness dried by two pretreatments of ultrasonication at 30 °C for 10 min and blanching at 70 ℃ for 2 min, was explored on the dependent (response) parameters including the thermal properties (drying time, effective moisture diffusion coefficient (Deff), specific energy consumption, energy efficiency, quality features (color changes and shrinkage), and GHG emission (including CO2 and NOx). It should be mentioned that the emission of GHG was determined based on the energy consumption of various types of power plants such as the gas turbine steam power turbine, and combined cycle turbines using various fuels such as natural gas, heavy oil, and gas oil. The results indicated that the ultrasonication and blanching pretreatments can decrement the drying time (linearly), energy consumption (linearly or quadratically), shrinkage(quadratically), and color changes(quadratically) and enhance the Deff (linearly) and energy efficiency (linearly or quadratically) in all samples with R2 > 0.86. Moreover, the shortest drying time (42 min), lowest SEC (9.51 MJ/kg), and GHG emission ((4279.74 g CO2 in the combined cycle turbines plant, and 18.16 g NOX in the gas turbine plant) with natural gas for both plants) were recorded for the samples pretreated with blanching while the lowest color changes (13.69) and shrinkage (21.29) were observed in the ultrasonicated samples. Based on the optimization results, a microwave power of 300 W and steam power turbine of 2 mm were the best variables with a desirability of about 80% which resulted in the highest-quality products at the lowest GHG emission.

The aim of this study was the development of mixed matrix membranes (MMMs) based on silica MCM-41 dispersed in polysulfone (PSf) for the separation of carbon dioxide from methane. For this purpose, MCM-41 was synthesized by a hydrothermal method and was modified with 3-aminopropyltrietoxysilane (APTES). SEM, FTIR, BET and XRD analyses were used for characterization of the modified and unmodified particles. Then, various MMMs containing PSf at different weight percents (5, 10, 15 and 20) of modified and unmodified particles were prepared and the morphology and structure of the prepared membranes were studied using SEM and XRD analyses. Regardless of the particle type, the addition of MCM-41 to PSf caused an increase in gas permeability compared to a neat PSf membrane. Adding unmodified particles to PSf matrix resulted in undesirable effects, including particle agglomeration and/or the formation of interfacial voids. The MMMs with modified MCM-41 showed relatively better separation performance compared to MMMs with unmodified MCM-41. As a result, the MMM of PSf with 20 wt. % modified MCM-41 showed a significant increase in selectivity of carbon dioxide/methane and the value of selectivity reached 25.24.

The purpose of this study is to consider and compare applicability of modified chitosan nano fibers with functionalized mesoporous silica in Elecrtrospinning method for Direct Yellow 12 (D.Y.12) removal from aqueous solutions. Provided nano fibers were monitored and detected by TEM, Fe-SEM, XRD, FT-IR devices and Tensile testing. Subsequently, the effect of different operating parameters was achieving optimum condition for performing the adsorption process: such as nano adsorbent types, adsorbent dose, pH, initial dye concentration, contact time. And ultimately, finding suitable isotherms for adsorption of D.Y.12 was performed. Desirable conditions for removing by mesoporous silica chitosan nano fibers with SBA-15-NH2 adsorbent in 40 minutes contact, pH=2, the amount of adsorbent was 0.05 gr with 20 mg/l initial concentration. Also, the results have shown that D.Y.12 removal is following Langmuir and Freundlich isotherm model. The conclusions of this investigation have shown that CTS/SBA-15-NH2 nano fibers adsorb the D.Y.12 effectively and has great potential for purification of infected waste water with dyes.

The challenges of urban administration are growing, as the population, automobiles, and cities rise. Making cities smarter is thus one of the most effective solutions to urban issues. A key feature of the “smart cities” of today is that they use cutting-edge technology in their infrastructure and services. With strategic planning, the smart city utilizes its resources in the most efficient manner. With reduced expenses and enhanced infrastructure, smart cities provide their residents with more and better services. One of these important urban services that can be very helpful in managing cities is structural health monitoring (SHM). By combining leading new technologies like the Internet of Things (IoT) with structural health monitoring, important urban infrastructure can last longer and work better. A thorough examination of recent advances in SHM for infrastructure is thus warranted. Bridges are one of the most important parts of a city’s infrastructure, and their building, development, and proper maintenance are some of the most important aspects of managing a city. The main goal of this study is to look at how artificial intelligence (AI) and some technologies, like drone technology and 3D printers, could be used to improve the current state of the art in SHM systems for bridges, including conceptual frameworks, benefits and problems, and existing methods. An outline of the role AI and other technologies will play in SHM systems of bridges in the future was provided in this study. Some novel technology-aided research opportunities are also highlighted, explained, and discussed.

In this paper the first example of using C-dots (CDs) as sensing nanomaterial for monitoring low concentrations of NO2 in ambient air is reported. In the logic to support a green circular economy, CDs were prepared from a natural low cost precursor consisting in olive solid waste (OSW) by a simple pyrolysis process combined with chemical oxidation. Characterization data showed the formation of spherical CDs with dimensions in the narrow size range from 0.5 to 5 nm and charged with functional groups (COO- (carboxylate), C-O-C (epoxide) and C-OH (hydroxyl) imprinting excellent water colloidal dispersion. The nanomaterial was used to fabricate and test a conductometric gas sensor (CDs-sensor) that was found to exhibit excellent performances in terms of high and selective response to sub-ppm concentration of NO2 at low temperature (150 °C), low limit of detection (LOD) of 50 ppb, good reproducibility and stability over use and aging. To the best of our knowledge, this is the first example reported in the literature of CDs high performances gas sensing material. Results here presented pave the way for a new class of a carbon nanomaterial for gas sensing to be applied in the field of environmental monitoring.

Magnetic Ag–Co and Ag–Ni alloy nanoparticles were prepared through a chemical reduction method using their corresponding [Co(NH3)6]Cl3 and [Ni(C2O4)2]K2 complexes, and AgNO3. In this reaction, hydrazine monohydrate was used as reducing agent. The obtained nanoparticles were characterized by Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), and vibrating sample magnetometer (VSM). Ag–Co and Ag–Ni nanoalloys exhibited excellent catalytic performance in the preparation of 1,8–dioxooctahydroxanthenes from the reaction of 5,5-dimethyl-1,3-cycloheanedione (dimedone) with aromatic aldehydes. Catalysts were separated by an external permanent magnet and reused. Both, Ag–Co and Ag–Ni nanoalloys posess antibacterial and antioxidant properties and have no significant effect on DNA cleavage.

The effects of hot air temperature (40, 50 and 60 oC) and Radiation Intensity (RI) (0.21, 0.31 and 0.41 w/cm2) on the response variables (drying time, Head Parboiled Rice Yield (HPRY), color value and hardness)) of parboiled rice were investigated. The drying was performed using hybrid hot air–infrared drying. The optimization of drying variables and the relationship between response variables and the influence factors were analyzed using response surface methodology (RSM). Based on RSM results, the best mathematical model for prediction of HPRY, hardness and color value and drying time of samples was linear(R2= 0.96), quadratic(R2= 0.99), linear(R2= 0.93) and linear(R2= 0.99) equation, respectively. The HPRY (62.13- 68.13%) and hardness (130.27- 247.3 N) increased with increasing drying temperature and RI, while the color value (19.77- 18.03) and drying time (59.72- 34.41 min) decreased. The optimized parameters of drying were obtained 55 oC drying temperature and 0.41 w/ cm2 RI.

Drying as an effective method for preservation of crop products is affected by various conditions and to obtain optimum drying conditions it is needed to be evaluated using modeling techniques. In this study, an adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), and support vector regression (SVR) was used for modeling the infrared-hot air (IR-HA) drying kinetics of parboiled hull. The ANFIS, ANN, and SVR were fed with 3 inputs of drying time (0–80 min), drying temperature (40, 50, and 60 °C), and two levels of IR power (0.32 and 0.49 W/cm2) for the prediction of moisture ratio (MR). After applying different models, several performance prediction indices, i.e., correlation coefficient (R2), mean square error index (MSE), and mean absolute error (MAE) were examined to select the best prediction and evaluation model. The results disclosed that higher inlet air temperature and IR power reduced the drying time. MSE values for the ANN, ANFIS tests, and SVR training were 0.0059, 0.0036, and 0.0004, respectively. These results indicate the high-performance capacity of machine learning methods and artificial intelligence to predict the MR in the drying process. According to the results obtained from the comparison of the three models, the SVR method showed better performance than the ANN and ANFIS methods due to its higher R2 and lower MSE.

The evaluation of a production system to analyze greenhouse gases is one of the most interesting challenges for researchers. The aim of the present study is to model almond nut production based on inputs by employing artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFIS) procedures. To predict the almond nut yield with respect to the energy inputs, several ANN and ANFIS models were developed, evaluated, and compared. Among the several developed ANNs, a network with an architecture of 8-12-1 and a log-sigmoid, and a linear transfer function in the hidden and output layers, respectively, is found to be the best model. In general, both approaches had a good capability for predicting the nut yield. The comparison results revealed that the ANN procedure could predict the nut yield more precisely than the ANFIS models. Furthermore, greenhouse gas (GHG) emissions in almond orchards are determined where the total GHG emission is estimated to be about 2348.85 kg CO2eq ha−1. Among the inputs, electricity had the largest contribution to GHG emissions, with a share of 72.32%.

Lower limb prostheses offer a solution to restore the ambulation and self-esteem of amputees. One key component is the prosthetic socket that serves as the interface between prosthetic device and amputee stump and thereby has a wide range of impacts on efficient fitting, appropriate load transmission, operational stability, and control. For the design and optimization of a prosthetic socket, an understanding of the actual intra-socket operational conditions becomes therefore necessary. This is however a difficult task due to the inherent complexity and restricted observability of socket operation. In this study, an innovative mechatronics-twin framework that integrates advanced biomechanical models and simulations with physical prototyping and dynamic operation testing for effective exploration of operational behaviors of prosthetic sockets with amputees is proposed. Within this framework, a specific Stewart manipulator is developed to enable dynamic operation testing, in particular for a well-managed generation of dynamic intra-socket loads and behaviors that are otherwise difficult to observe or realize with the real amputees. A combination of deep learning and Bayesian Inference algorithms is then employed for analyzing the intra-socket load conditions and revealing possible anomalous.

Metamaterial photonic integrated circuits with arrays of hybrid graphene–superconductor coupled split-ring resonators (SRR) capable of modulating and slowing down terahertz (THz) light are introduced and proposed. The hybrid device’s optical responses, such as electromagnetic-induced transparency (EIT) and group delay, can be modulated in several ways. First, it is modulated electrically by changing the conductivity and carrier concentrations in graphene. Alternatively, the optical response can be modified by acting on the device temperature sensitivity by switching Nb from a lossy normal phase to a low-loss quantum mechanical phase below the transition temperature (Tc) of Nb. Maximum modulation depths of 57.3% and 97.61% are achieved for EIT and group delay at the THz transmission window, respectively. A comparison is carried out between the Nb-graphene-Nb coupled SRR-based devices with those of Au-graphene-Au SRRs, and significant enhancements of the THz transmission, group delay, and EIT responses are observed when Nb is in the quantum mechanical phase. Such hybrid devices with their reasonably large and tunable slow light bandwidth pave the way for the realization of active optoelectronic modulators, filters, phase shifters, and slow light devices for applications in chip-scale future communication and computation systems.

This study is focused on the influence of convective drying (50, 60, and 70 °C) and infrared (IR) power (250, 500, and 750 W) on the drying kinetics, the specific energy consumption of terebinth drying as well as quality and bioactive compounds upon various pretreatments such as ultrasound (US), blanching (BL), and microwave (MW). Compared to convective drying, IR drying decreased more the drying time and energy consumption (SEC). Application of higher IR powers and air temperatures accelerated the drying process at lower energy consumption (SEC) and higher energy efficiency and moisture diffusion. Terebinth dried by a convective dryer at 60 °C with US pretreatment showed a better color compared to other samples. It also exhibited the polyphenol and flavonoid content of 145.35 mg GAE/g d.m. and 49.24 mg QE/g d.m., respectively, with color variations of 14.25 and a rehydration rate of 3.17. The proposed pretreatment methods significantly reduced the drying time and energy consumption, and from the other side it increased energy efficiency, bioactive compounds, and quality of the dried samples (p < 0.01). Among the different pretreatments used, microwave pretreatment led to the best results in terms of the drying time and SEC, and energy efficiency. US pretreatment showed the best results in terms of preserving the bioactive compounds and the general appearance of the terebinth.

Magnetite-containing sulfonated polyacrylamide was easily prepared through polymerization of the corresponding monomers followed by the reaction with Fe3O4 nanoparticles. The characterization of the obtained catalyst was performed by Fourier transform infrared spectroscopy (FT-IR), thermal gravimetric analysis (TGA), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), and vibrating sample magnetometer (VSM). The acidic SO3H moiety was found to be 1.1 mmol per gram of the obtained polymer. The catalytic activity of the polymer was examined for the synthesis of biscoumarin derivatives by two-component one-pot domino Knoevenagel-type condensation/Michael reaction between aldehydes and 4-hydroxycoumarin. Biscoumarins were obtained in high to excellent yields in short time. The work-up procedure of this reaction was very simple. The catalyst is stable (as a bench top catalyst) with easy-handling and it can be used again.

Composite nanofibers composed of an organic polymer and inorganic nanomaterials have huge potential to be used in different industrial applications. However, the main concern on the use of composite nanofibers is the distribution properties of nanomaterials in the polymeric matrix. The effect of the capillary tip charge on the additive distribution in the electrospun nanofiber has been previously studied and can be found in the literature. In this study, focus is placed on the investigation of TiO2 nanoparticles (TiO2 NPs) distribution in the polysulfone (PSF) nanofiber. X-ray Photoelectron Spectroscopy (XPS) was conducted to measure the percentage of TiO2 on the surface of the prepared PSF/TiO2 composite nanofiber. The results showed that there was no TiO2 NPs on the surface of the nanofiber for up to 10 nm in depth. TiO2 nanoparticles were mainly found in the center of the nanofiber due to the accumulation of the hydrophobic PSF at the surface of the composite nanofiber. The findings of this work can provide better interpretation of the impact of the interfacial tension on the distribution of the inorganic nanomaterials in the electrospun nanofiber.

This work compares the performance of optical lenses made of silica glass or borosilicate glass (BK-7) when submitted to high-flux radiation emitted by a xenon arc lamp or provided by a high-concentration solar tower. Each irradiation test lasted for 60 min, with continuous monitoring of the radiation-flux incident on the lenses and the temperature generated in their vicinity. All silica glass lenses showed a good performance with both irradiation sources, xenon arc lamp and natural solar radiation, contrary to what was observed with the lenses made of borosilicate glass which fractured when irradiated with a xenon arc lamp. The negative behavior observed with the borosilicate lenses is attributed to the fact that the radiation spectrum of a xenon arc lamp contains certain wavelengths, in the near ultraviolet (UV) region, that are not present in the natural solar radiation spectrum at sea level.

The present study examined the effect of ultrasonic pretreatment at three time the levels of 10, 20 and 30 min on some thermodynamic (effective moisture diffusivity coefficient(Deff), drying time, specific energy consumption (SEC), energy efficiency, drying efficiency, and thermal efficiency) and physical (color and shrinkage) properties of kiwifruit under hybrid hot air-infrared(HAI) dryer at different temperatures (50, 60 and 70 °C) and different thicknesses (4, 6 and 8 mm). A total of 11 mathematical models were applied to represent the moisture ratio (MR) during the drying of kiwifruit. The fitting of MR mathematical models to experimental data demonstrated that the logistic model can satisfactorily describe the MR curve of dried kiwifruit with a correlation coefficient (R2) of 0.9997, root mean square error (RMSE) of 0.0177 and chi-square (χ2) of 0.0007. The observed Deff of dried samples ranged from 3.09 × 10−10 to 2.26 × 10−9 m2/s. The lowest SEC, color changes and shrinkage were obtained as 36.57 kWh/kg, 13.29 and 25.25%, respectively. The highest drying efficiency, energy efficiency, and thermal efficiency were determined as 11.09%, 7.69% and 10.58%, respectively. The results revealed that increasing the temperature and ultrasonic pretreatment time and decreasing the sample thickness led to a significant increase (p < 0.05) in drying efficiency, thermal efficiency, and energy efficiency, while drying time, SEC and shrinkage significantly decreased (p < 0.05).

A novel multiwalled carbon nanotube catalyst with –SO3H functional groups was easily prepared from its starting materials and used as an efficient heterogeneous catalyst for one-pot Knoevenagel condensation, Michael addition, and cyclodehydration of 5,5-dimethyl-1,3-cyclohexanedione (dimedone) with various aromatic aldehydes. Using this method 1,8-dioxo-octahydroxanthenes were obtained in excellent yields at room temperature. The present method is superior in terms of reaction temperature, reaction time, easy work-up, high yields, and ease of recovery of catalyst.

Decorating photocatalysts with noble metal nanoparticles (e.g., Pt) often increases the catalysts’ photocatalytic activity and biomedical properties. Here, a simple and inexpensive method has been developed to prepare a Pt-Ag3PO4/CdS/chitosan composite, which was characterized and used for the visible light-induced photocatalytic and antibacterial studies. This synthesized composite showed superior photocatalytic activity for methylene blue degradation as a hazardous pollutant (the maximum dye degradation was observed in 90 min of treatment) and killing of Gram positive bacterial (Staphylococcus aureus and Bacillus cereus) as well as Gram negative bacteria (Klebsiella pneumoniae, Salmonella typhimurium, Escherichia coli, and Pseudomonas aeruginosa) under visible light irradiation. The antibacterial activity of CdS, CdS/Ag3PO4, and Pt-Ag3PO4/CdS/chitosan against E. coli, Pseudomonas aeruginosa, Salmonella typhimurium, Klebsiella pneumoniae, Staphylococcus aureus, and Bacillus cereus showed the zone of inhibition (mm) under visible light and under dark conditions at a concentration of 20 µg mL−1. Furthermore, the cell viability of the CdS/chitosan, Ag3PO4, Ag3PO4/CdS/chitosan, and Pt-Ag3PO4/CdS/chitosan were investigated on the human embryonic kidney 293 cells (HEK-293), Henrietta Lacks (HeLa), human liver cancer cell line (HepG2), and pheochromocytoma (PC12) cell lines. In addition, the results indicated that the photodegradation rate for Pt-Ag3PO4/CdS/chitosan is 3.53 times higher than that of CdS and 1.73 times higher than that of the CdS/Ag3PO4 composite. Moreover, Pt-Ag3PO4/CdS/chitosan with an optimal amount of CdS killed large areas of different bacteria and different cells separately in a shorter time period under visible-light irradiation, which shows significantly higher efficiency than pure CdS and other CdS/Ag3PO4 composites. The superb performances of this composite are attributed to its privileged properties, such as retarded recombination of photoinduced electron/hole pairs and a large specific surface area, making Pt-Ag3PO4/CdS/chitosan a valuable composite that can be deployed for a range of important applications, such as visible light-induced photocatalysis and antibacterial activity.

In this study, the drying time, effective moisture diffusivity (Deff), specific energy consumption (SEC), and quality (color, shrinkage, and rehydration) of the ultrasound-pretreated (US) carrot slices were compared when dried by hot air drying (HD), microwave drying (MWD), infrared drying (INFD), and hybrid methods of MW–HD and INF–HD. Five mathematical models were considered to describe the drying kinetics in the carrots. The results show that US+MW–HD and INFD were the fastest and the slowest drying techniques compared to the HD technique with a 73% and 23% drying time reduction, respectively. The Deff ranged from 7.12 × 10−9 to 2.78 × 10−8 m2/s. The highest and lowest SECs were 297.29 ± 11.21 and 23.75 ± 2.22 MJ/kg which were observed in the HD and US+MWD, respectively. The color variation indices indicated that the best sample in terms of color stability was the one dried by US+MW–HD with the color variation of 11.02 ± 0.27. The lowest and highest shrinkage values were also observed in the samples dried by US+MWD and HD (31.8 ± 1.1% and 62.23 ± 1.77%), respectively. Samples dried by US+MWD and HD possessed the highest and lowest rehydration, respectively. Although the carrot slices dried at a higher pace by US+MW–HD (compared to US+MWD), the shrinkage and SEC of the samples dried by US+MWD were significantly lower than the US+MW–HD (p < 0.05). Therefore, it can be concluded that the application of the US+MWD method can be considered as a proper alternative for drying the carrot slices when compared to the HD, MWD, INFD, and hybrid methods.