MXenes are one of the most important classes of materials discussed worldwide by many researchers of diverse fields for diverse applications in recent years. It is a nanomaterial with a wide range of applications due to its multiple forms and structures with fascinating properties, for example, high surface area and porosity, biocompatibility, ease of fictionalizing with various active chemical moieties, benefit of high metallic conductivity, activated metallic hydroxide sites, and sensitivity to moisture. MXenes have great chances for potential applications in environmental issues, water purification, biological applications, and energy storage devices and sensors. MXenes show great selectivity towards the absorption of heavy metals and a good capability to reduce chemical and biological pollutants present in the water. The present review article critically analyzed advancements in water purification using the adsorption and reduction abilities of MXenes and their composites. The mechanism of various procedures, important challenges, and associated problems using MXene and their composites are discussed in detail. The future research directions can be extracted from this article efficiently and comprehensively. The energy storage issues of rechargeable lithium-ion batteries, batteries other than lithium-ion batteries, and electrochemical capacitors are also discussed in detail.

The chemical reinforcement of sandy soils is usually carried out to improve their properties and meet specific engineering requirements. Nevertheless, conventional reinforcement agents are often expensive; the process is energy-intensive and causes serious environmental issues. Therefore, developing a cost-effective, room-temperature-based method that uses recyclable chemicals is necessary. In the current study, poly (styrene-co-methyl methacrylate) (PS-PMMA) is used as a stabilizer to reinforce sandy soil. The copolymer-reinforced sand samples were prepared using the one-step bulk polymerization method at room temperature. The mechanical strength of the copolymer-reinforced sand samples depends on the ratio of the PS-PMMA copolymer to the sand. The higher the copolymer-to-sand ratio, the higher the sample’s compressive strength. The sand (70 wt.%)-PS-PMMA (30 wt.%) sample exhibited the highest compressive strength of 1900 psi. The copolymer matrix enwraps the sand particles to form a stable structure with high compressive strengths.

Urban mobility in Grand Lomé is affected by several negative externalities, including road congestion, insecurity and environmental pollution. Traffic jams cause considerable economic losses, estimated at more than 13,000 CFA francs per month for some public officials, and represent a financial drain of several million CFA francs per day on the Togolese economy. These challenges are accentuated by rapid urbanization and a dizzying increase in the number of vehicles, especially motorcycle taxis. These factors not only cause economic losses, but also to the deterioration of the quality of life of the inhabitants. On average, motorists lose up to 49.5 min per day in traffic jams, with fuel and time costs estimated at hundreds of thousands of CFA francs per year for each user of the main boulevards. Through an in-depth analysis of the impacts of these negative externalities on mobility and sustainable development, this study reveals that traffic congestion, combined with the lack of road infrastructure, generates considerable economic and environmental costs. These traffic jams also worsen air pollution, making the transport sector responsible for 80% of greenhouse gas emissions. These proposed solutions include: 1) The modernization of road infrastructure, culminating in the construction of new lanes entirely dedicated to public and non-motorized transport. 2) The regulation of motorcycle taxis, inspired by regional examples, to improve safety and efficiency. 3) The introduction of rapid transit systems, such as Bus Rapid Transit (BRT), to make travel more fluid. 4) The implementation of strict environmental standards and regular technical controls to reduce greenhouse gas emissions. These proposals aim to reduce social and economic costs, while promoting sustainable mobility and a better quality of life for residents.

A precise risk assessment in a production line constitutes a significant item to identify susceptible areas where there is a possibility of product quality degradation. This also applies to the precast concrete production line in Indonesia that has a spun pile product. Based on a risk assessment activity conducted in this study, it is proposed to build a traceability model in order to maintain and even improve the spun pile product quality in Indonesia. The approach used was the Neural Network of the perceptron model for weighing and will result in a defined traceability path in the context of reducing defects and even failed spun pile products. The simulation result showed that the model has been able to detect risky path possibilities to reduce product quality. The accumulation result of high-risk and medium-risk paths in this study showed that closer to product finalization, the risk will be higher. It is evident that when assessing Indicators, the order from the highest accumulation value first is Curing & Demolding and Stressing & Spinning at 29% each, Casting at 14%, Forming & Setting at 14%, and lastly Cutting & Heading at 14%. Regarding the risk assessment for activities, the first position is Curing & Demolding and Stressing & Spinning with 30% each, the second is Casting and Forming & Setting with 15% each, and the third is Cutting & Heading with 10%.

In the last several decades, cardiovascular diseases (CVDs) have emerged as a major hazard to human life and health. Conventional formulations for the treatment of CVD are available, but they are far from ideal because of poor water solubility, limited biological activity, non-targeting, and drug resistance. With the advancement of nanotechnology, a novel drug delivery approach for the treatment of CVDs has emerged: nano-drug delivery systems (NDDSs). NDDSs have shown significant advantages in tackling the difficulties listed above. Cytotoxicity is a difficulty with the use of non-destructive DNA sequences. NDDS categories and targeted tactics were outlined, as well as current research advancements in the diagnosis and treatment of CVDs. It’s possible that gene therapy might be included into nano-carriers in the delivery of cardiovascular medications in the future. In addition, the evaluation addressed the drug’s safety.

Catastrophes, like earthquakes, bring sudden and severe damage, causing fatalities, injuries, and property loss. This often triggers a rapid increase in insurance claims. These claims can encompass various types, such as life insurance claims for deaths, health insurance claims for injuries, and general insurance claims for property damage. For insurers offering multiple types of coverage, this surge in claims can pose a risk of financial losses or bankruptcy. One option for insurers is to transfer some of these risks to reinsurance companies. Reinsurance companies will assess the potential losses due to a catastrophe event, then issue catastrophe reinsurance contracts to insurance companies. This study aims to construct a valuation model for catastrophe reinsurance contracts that can cover claim losses arising from two types of insurance products. Valuation in this study is done using the Fundamental Theorem of Asset Pricing, which is the expected present value of the number of claims that occur during the reinsurance coverage period. The number of catastrophe events during the reinsurance coverage period is assumed to follow a Poisson process. Each impact of a catastrophe event, such as the number of fatalities and injuries that cause claims, is represented as random variables, and modeled using Peaks Over Threshold (POT). This study uses Clayton, Gumbel, and Frank copulas to describe various dependence characteristics between random variables. The parameters of the POT model and copula are estimated using Inference Functions for Margins method. After estimating the model parameters, Monte Carlo simulations are performed to obtain numerical solutions for the expected value of catastrophe reinsurance based on the Fundamental Theorem of Asset Pricing. The expected reinsurance value based on Monte Carlo simulations using Indonesian earthquake data from 1979–2021 is Rp 10,296,819,838.