Wheat husk-based sorbent as an economical solution for removal of oil spills from sea water.

Oil spills are a significant threat to the marine ecosystem that requires immediate removal from the oceanic environment. Many technologies have been employed to clean up oil spills. Of these, adsorption has scored a prominent success due to the high efficiency, economic viability, environmental friendship, and ease of application. The utilization of agricultural waste to produce biosorbents have been considered as an ecofriendly and efficient approach for removing oil. Thus, a new low-cost oil adsorbent was prepared via esterification of the wheat straw (Str) with a hydrophobic benzoyl group, the resulting copolymer (Str-co-Benz) was characterized by FTIR, TGA, DSC, and SEM and used at laboratory scale. The oil spill cleanup process was conducted using a crude oil-natural seawater system under different adsorption conditions such as oil concentration, adsorbent dose, agitation time and speed. Equilibrium studies were performed to determine the capacity of the prepared materials for crude oil adsorption. Langmuir and Freundlich adsorption models were used to describe the experimental isotherms. The reliability of the data was examined and evaluated via application of response surface methodology program. The results showed that oil adsorption followed a pseudo-second-order kinetic model and fitted well with Langmuir model with a maximum adsorption capacity of 10.989 and 12.786 g/g for Str and (Str-co-Benz), respectively. Overall, the modified wheat husk is an effective platform for removing oil from marine ecosystems due to low cost, biodegradability, simple synthesis and fast removal. Moreover, the resulted solid can be used as a fuel in some industrial processes such as steam boilers and brick production incinerators.

Secure biometric systems based on bio-signals and DNA encryption of optical spectrograms.

Recently, biometrics has become widely used in applications to verify an individual's identity. To address security issues, biometrics presents an intriguing window of opportunity to enhance the usability and security of the Internet of Things (IoT) and other systems. It can be used to secure a variety of newly emerging IoT devices. However, biometric scenarios need more protection against different hacking attempts. Various solutions are introduced to secure biometrics. Cryptosystems, cancelable biometrics, and hybrid systems are efficient solutions for template protection. The new trend in biometric authentication systems is to use bio-signals. In this paper, two proposed authentication systems are introduced based on bio-signals. One of them is unimodal, while the other is multimodal. Protected templates are obtained depending on encryption. The deoxyribonucleic acid (DNA) encryption is implemented on the obtained optical spectrograms of bio-signals. The authentication process relies on the DNA sensitivity to variations in the initial values. In the multimodal system, the singular value decomposition (SVD) algorithm is implemented to merge bio-signals. Different evaluation metrics are used to assess the performance of the proposed systems. Simulation results prove the high accuracy and efficiency of the proposed systems as the equal error rate (EER) value is close to 0 and the area under the receiver operator characteristic curve (AROC) is close to 1. The false accept rate (FAR), false reject rate (FRR), and decidability (D) are also estimated with acceptable results of 1.6 × 10-8, 9.05 × 10-6, and 29.34, respectively. Simulation results indicate the performance stability of the proposed systems in the presence of different levels of noise.

Cancelable biometric system for IoT applications based on optical double random phase encoding.

The security issue is essential in the Internet-of-Things (IoT) environment. Biometrics play an important role in securing the emerging IoT devices, especially IoT robots. Biometric identification is an interesting candidate to improve IoT usability and security. To access and control sensitive environments like IoT, passwords are not recommended for high security levels. Biometrics can be used instead, but more protection is needed to store original biometrics away from invaders. This paper presents a cancelable multimodal biometric recognition system based on encryption algorithms and watermarking. Both voice-print and facial images are used as individual biometrics. Double Random Phase Encoding (DRPE) and chaotic Baker map are utilized as encryption algorithms. Verification is performed by estimating the correlation between registered and tested models in their cancelable format. Simulation results give Equal Error Rate (EER) values close to zero and Area under the Receiver Operator Characteristic Curve (AROC) equal to one, which indicates the high performance of the proposed system in addition to the difficulty to invert cancelable templates. Moreover, reusability and diversity of biometric templates is guaranteed.

Novel fabricated low-cost hybrid polyacrylonitrile/polyvinylpyrrolidone coated polyurethane foam (PAN/PVP@PUF) membrane for the decolorization of cationic and anionic dyes.

Dyes are recalcitrait organic pollutants threatening the aquatic environment and human health. In the present study, a novel low-cost hybrid membrane was fabricated by coating polyurethane foam (PUF) with polyacrylonitrile/polyvinylpyrrolidone (PAN/PVP) via phase inversion technique from casting solutions consisting of PAN and PVP with Dimethyl formamide (DMF) and applied for removal of cationic (Methylene Blue (MB)) and anionic (Methyl Orange (MO)) dyes from aqueous solutions. The as-prepared membrane was first characterized by Scan Electron Microscope (SEM), Fourier Transform Infrared (FTIR), Energy Dispersive Spectrometry (EDS), etc. Then, batch experiments were conducted to optimize the adsorption conditions, including contact time, adsorbent dose, dyes concentration, and pH. The dye removal results fitted with pseudo first and second-order kinetics; Langmuir, Freundlich, and Temkin isotherms' models. The maximum dye decolorization was approximately 97% and 95% within 60 and 120 min using 0.5 and 1 g of the fabricated composite for MB and MO, respectively. The kinetic studies showed rapid sorption dynamics following a second-order kinetic model. In addition, dye adsorption equilibrium data fitted well to the Freundlich isotherm with monolayer maximum adsorption capacity of 6.356 and 3.321 mg/g for MO and MB dye, respectively. Thus, the novel hybrid membrane is promising as a cheap and efficient adsorbent for the removal of both cationic and anionic dyes from wastewater. The current study demonstrated a new avenue to achieve efficient management of dyes in aquatic environments.

Biogas upgrading and biochemical production from gas fermentation: Impact of microbial community and gas composition.

The present study proposes a novel alternative method of the current biogas upgrading techniques by converting CO2 (in the biogas) into valuable chemicals (e.g., volatile fatty acids) using H2 as energy source and acetogenic mixed culture as biocatalyst. The influence of thermal treatment (90 °C) on the inhibition of the methanogenic archaea and enriching the acetogenic bacteria in different inocula (mesophilic and thermophilic) was initially tested. The most efficient inoculum that achieved the highest performance through the fermentation process was further used to define the optimum H2/CO2 gas ratio that secures maximum production yield of chemicals and maximum biogas upgrading efficiency. In addition, 16S rRNA analysis of the microbial community was conducted at the end of the experimental period to target functional microbes. The maximum biogas content (77% (v/v)) and acetate yield (72%) were achieved for 2H2:1CO2 ratio (v/v), with Moorella sp. 4 as the most dominant thermophilic acetogenic bacterium.

Simultaneous biogas upgrading and biochemicals production using anaerobic bacterial mixed cultures.

A novel biological process to upgrade biogas was developed and optimised during the current study. In this process, CO2 in the biogas and externally provided H2 were fermented under mesophilic conditions to volatile fatty acids (VFAs), which are building blocks of higher-value biofuels. Meanwhile, the biogas was upgraded to biomethane (CH4 >95%), which can be used as a vehicle fuel or injected into the natural gas grid. To establish an efficient fermentative microbial platform, a thermal (at two different temperatures of 70 °C and 90 °C) and a chemical pretreatment method using 2-bromoethanesulfonate were investigated initially to inhibit methanogenesis and enrich the acetogenic bacterial inoculum. Subsequently, the effect of different H2:CO2 ratios on the efficiency of biogas upgrading and production of VFAs were further explored. The composition of the microbial community under different treatment methods and gas ratios has also been unravelled using 16S rRNA analysis. The chemical treatment of the inoculum had successfully blocked the activity of methanogens and enhanced the VFAs production, especially acetate. The chemical treatment led to a significantly better acetate production (291 mg HAc/L) compared to the thermal treatment. Based upon 16S rRNA gene sequencing, it was found that H2-utilizing methanogens were the dominant species in the thermally treated inoculum, while a significantly lower abundance of methanogens was observed in the chemically treated inoculum. The highest biogas content (96% (v/v)) and acetate production were achieved for 2H2:1CO2 ratio (v/v), with Acetoanaerobium noterae, as the dominant homoacetogenic hydrogen scavenger. Results from the present study can pave the way towards more development with respect to microorganisms and conditions for high efficient VFAs production and biogas upgrading.