Toward improved mechanical, tribological, corrosion and in-vitro bioactivity properties of mixed oxide nanotubes on Ti–6Al–7Nb implant using multi-objective PSO

Bioremediation of hexavalent chromium from wastewater using bacteria-a green technology

Hexavalent chromium has high toxic effect on the ecological system. The aim of the present study is to isolate and characterize the bacteria that can reduce the toxicity of hexavalent chromium from liquid effluent. The bacterial isolate was identified as Bacillus sp. ltds1 after 16 S rRNA gene sequencing, and annotation has been submitted in National Center for Biotechnology Information (NCBI) GenBank. The bacterial strain was found able to grow in Luria Broth medium at 100 mg/L Cr⁶⁺ concentration. A maximum Cr⁶⁺ bioremediation (95.24 ± 2.08 %) could be achieved using the said isolate at 40 mg/L, pH 7, and inoculum concentration 4 % at 24 h. The residual chromium was found in the form of less toxic trivalent chromium (Cr³⁺), which confirms that the bacterial isolate can transform toxic Cr⁶⁺ to non-toxic Cr³⁺. Fourier Transform Infra-Red (FTIR) study was performed to analyze the functional groups and overall nature of chemical bonds involved in the remediation process, whereas, Energy-Dispersive Spectroscopy (EDS) studies of native and treated cells showed the changes in elemental composition in response to metal stress. Artificial Neural Network (ANN) based prediction model is developed based on experimental points. The developed model was found to predict the bioremediation of Cr⁶⁺ at various operating conditions. Particle Swarm Optimization (PSO) is used to optimize the variables like the initial concentration of metal, pH, temperature, and inoculum concentration for the said bacterial strain. The results showed that the isolate could be applied as a potential bioremediation agent for Cr⁶⁺ removal.

Mixed oxide nanotubes in nanomedicine: A dead-end or a bridge to the future?

Nanomedicine has seen a significant rise in the development of new research tools and clinically functional devices. In this regard, significant advances and new commercial applications are expected in the pharmaceutical and orthopedic industries. For advanced orthopedic implant technologies, appropriate nanoscale surface modifications are highly effective strategies and are widely studied in the literature for improving implant performance. It is well-established that implants with nanotubular surfaces show a drastic improvement in new bone creation and gene expression compared to implants without nanotopography. Nevertheless, the scientific and clinical understanding of mixed oxide nanotubes (MONs) and their potential applications, especially in biomedical applications are still in the early stages of development. This review aims to establish a credible platform for the current and future roles of MONs in nanomedicine, particularly in advanced orthopedic implants. We first introduce the concept of MONs and then discuss the preparation strategies. This is followed by a review of the recent advancement of MONs in biomedical applications, including mineralization abilities, biocompatibility, antibacterial activity, cell culture, and animal testing, as well as clinical possibilities. To conclude, we propose that the combination of nanotubular surface modification with incorporating sensor allows clinicians to precisely record patient data as a critical contributor to evidence-based medicine.

A new solar power output prediction based on hybrid forecast engine and decomposition model

Regarding to the growing trend of photovoltaic (PV) energy as a clean energy source in electrical networks and its uncertain nature, PV energy prediction has been proposed by researchers in recent decades. This problem is directly effects on operation in power network while, due to high volatility of this signal, an accurate prediction model is demanded. A new prediction model based on Hilbert Huang transform (HHT) and integration of improved empirical mode decomposition (IEMD) with feature selection and forecast engine is presented in this paper. The proposed approach is divided into three main sections. In the first section, the signal is decomposed by the proposed IEMD as an accurate decomposition tool. To increase the accuracy of the proposed method, a new interpolation method has been used instead of cubic spline curve (CSC) fitting in EMD. Then the obtained output is entered into the new feature selection procedure to choose the best candidate inputs. Finally, the signal is predicted by a hybrid forecast engine composed of support vector regression (SVR) based on an intelligent algorithm. The effectiveness of the proposed approach has been verified over a number of real-world engineering test cases in comparison with other well-known models. The obtained results prove the validity of the proposed method.

Understanding and augmenting the stability of therapeutic nanotubes on anodized titanium implants

Titanium is an ideal material choice for orthopaedic and dental implants, and hence a significant amount of research has been focused towards augmenting the therapeutic efficacy of titanium surfaces. More recently the focus has shifted to nano-engineered implants fabricated via anodization to generate self-ordered nanotubular structures composed of titania (TiO₂). These structures (titania nanotubes/TNTs) enable local drug delivery and tailorable cellular modulation towards achieving desirable effects like enhanced osseointegration and antibacterial action. However, the mechanical stability of such modifications is often ignored and remains underexplored, and any delamination or breakage in the TNTs modification can initiate toxicity and lead to severe immuno-inflammatory reactions. This review details and critically evaluates the progress made in relation to this aspect of TNT based implants, with a focus on understanding the interface between TNTs and the implant surface, treatments aimed at augmenting mechanical stability and strategies for advanced mechanical testing within the bone micro-environment ex vivo and in vivo. This review article extends the existing knowledge in this domain of TNTs implant technology and will enable improved understanding of the underlying parameters that contribute towards mechanically robust nano-engineered implants that can withstand the forces associated with implant surgical placement and the load bearing experienced at the bone/implant interface.