Use of Genetically Modified Bacteria to Repair Cracks in Concrete

Machine Learning Model Construction and Testing: Anticipating Cancer Incidence and Mortality

In recent years, the escalating environmental challenges have contributed to a rising incidence of cancer. The precise anticipation of cancer incidence and mortality rates has emerged as a pivotal focus in scientific inquiry, exerting a profound impact on the formulation of public health policies. This investigation adopts a pioneering machine learning framework to address this critical issue, utilizing a dataset encompassing 72,591 comprehensive records that include essential variables such as age, case count, population size, race, gender, site, and year of diagnosis. Diverse machine learning algorithms, including decision trees, random forests, logistic regression, support vector machines, and neural networks, were employed in this study. The ensuing analysis revealed testing accuracies of 62.17%, 61.92%, 54.53%, 55.72%, and 62.30% for the respective models. This state-of-the-art model not only enhances our understanding of cancer dynamics but also equips researchers and policymakers with the capability of making meticulous projections concerning forthcoming cancer incidence and mortality rates. Considering sustainability, the application of this advanced machine learning framework emphasizes the importance of judiciously utilizing extensive and intricate databases. By doing so, it facilitates a more sustainable approach to healthcare planning, allowing for informed decision-making that takes into account the long-term ecological and societal impacts of cancer-related policies. This integrative perspective underscores the broader commitment to sustainable practices in both health research and public policy formulation.

Toward Self-Healing Concrete Infrastructure: Review of Experiments and Simulations across Scales

Cement and concrete are vital materials used to construct durable habitats and infrastructure that withstand natural and human-caused disasters. Still, concrete cracking imposes enormous repair costs on societies, and excessive cement consumption for repairs contributes to climate change. Therefore, the need for more durable cementitious materials, such as those with self-healing capabilities, has become more urgent. In this review, we present the functioning mechanisms of five different strategies for implementing self-healing capability into cement based materials: (1) autogenous self-healing from ordinary portland cement and supplementary cementitious materials and geopolymers in which defects and cracks are repaired through intrinsic carbonation and crystallization; (2) autonomous self-healing by (a) biomineralization wherein bacteria within the cement produce carbonates, silicates, or phosphates to heal damage, (b) polymer-cement composites in which autonomous self-healing occurs both within the polymer and at the polymer-cement interface, and (c) fibers that inhibit crack propagation, thus allowing autogenous healing mechanisms to be more effective. In all cases, we discuss the self-healing agent and synthesize the state of knowledge on the self-healing mechanism(s). In this review article, the state of computational modeling across nano- to macroscales developed based on experimental data is presented for each self-healing approach. We conclude the review by noting that, although autogenous reactions help repair small cracks, the most fruitful opportunities lay within design strategies for additional components that can migrate into cracks and initiate chemistries that retard crack propagation and generate repair of the cement matrix.

Bacterial Carbonate Precipitation Using Active Metabolic Pathway to Repair Mortar Cracks

A study was conducted to check the efficacy of microbial pathways for calcite precipitation to heal pre-existing cracks in mortar. In this experiment, realistic cracks of varying widths were induced on a mortar sample. Different repair methods were applied to a total of 22 mortar samples. Twelve cracked mortar samples with average crack widths ranging from 0.29 to 1.08 mm were subjected to biodeposition treatment using calcium lactate as a food source. The remaining ten samples were split into two groups: five cracked mortar samples were exclusively exposed to the bacterial solution, while the remaining five samples were immersed in distilled water. Digital image processing was used to extract the crack characteristics before and after the repair application. During several repair cycles, image processing was used to track healing. Further, these repaired mortar samples underwent examination for water permeability, ultra-sonic examination, and examination for recovered compressive strength. A forensic examination of the healing product in terms of morphology and elemental composition was conducted using RAMAN, XRD, SEM-EDS, and TGA. The water permeability of the repaired mortar sample using biodeposition with Ca-lactate was dramatically reduced, but samples treated with bacterial solution and distilled water did not exhibit any significant reduction. Complete crack healing was observed when using Ca-lactate as a food source for microbial repair. The forensic analysis confirmed the presence of calcite in healing precipitates.

Experimental Study on Sand Stabilization Using Bio-Cementation with Wastepaper Fiber Integration

Recently, green materials and technologies have received considerable attention in geotechnical engineering. One of such techniques is microbially-induced carbonate precipitation (MICP). In the MICP process, CaCO₃ is achieved bio-chemically within the soil, thus enhancing the strength and stiffness. The purpose of this study is to introduce the wastepaper fiber (WPF) onto the MICP (i) to study the mechanical properties of MICP-treated sand with varying WPF content (0–8%) and (ii) to assess the freeze–thaw (FT) durability of the treated samples. Findings revealed that the ductility of the treated samples increases with the increase in WPF addition, while the highest UCS is found with a small fiber addition. The results of CaCO₃ content suggest that the WPF addition enhances the immobilization of the bacteria cells, thus yielding the precipitation content. However, shear wave velocity analysis indicates that a higher addition of WPF results in rapid deterioration of the samples when subjected to freeze–thaw cycles. Microscale analysis illuminates that fiber clusters replace the solid bonding at particle contacts, leading to reduced resistance to freeze–thaw damage. Overall, the study demonstrates that as a waste material, WPF could be sustainably reused in the bio-cementation.

Effects of Different Types of Fibers on the Physical and Mechanical Properties of MICP-Treated Calcareous Sand

Microbial-induced calcite precipitation (MICP) has been a promising method to improve geotechnical engineering properties through the precipitation of calcium carbonate (CaCO₃) on the contact and surface of soil particles in recent years. In the present experiment, water absorption and unconfined compressive strength (UCS) tests were carried out to investigate the effects of three different fiber types (glass fiber, polyester fiber, and hemp fiber) on the physical and mechanical properties of MICP-treated calcareous sand. The fibers used were at 0%, 0.10%, 0.15%, 0.20%, 0.25%, 0.30%, 0.35%, and 0.40% relative to the weight of the sand. The results showed that the failure strain and ductility of the samples could be improved by adding fibers. Compared to biocemented sand (BS), the water absorption of these three fiber-reinforced biocemented sands were, respectively, decreased by 11.60%, 21.18%, and 7.29%. UCS was, respectively, increased by 24.20%, 60.76%, and 6.40%. Polyester fiber produced the best effect, followed by glass fiber and hemp fiber. The optimum contents of glass fiber and polyester fiber were 0.20% and 0.25%, respectively. The optimum content of hemp fiber was within the range of 0.20–0.25%. Light-emitting diode (LED) microscope and scanning electron microscope (SEM) images lead to the conclusion that only a little calcite precipitation had occurred around the hemp fiber, leading to a poor bonding effect compared to the glass and polyester fibers. It was therefore suggested that polyester fiber should be used to improve the properties of biocemented sand.

Challenges and approaches in assessing the interplay between microorganisms and their physical micro-environments

Spatial structure over scales ranging from nanometres to centimetres (and beyond) varies markedly in diverse habitats and the industry-relevant settings that support microbial activity. Developing an understanding of the interplay between a structured environment and the associated microbial processes and ecology is fundamental, but challenging. Several novel approaches have recently been developed and implemented to help address key questions for the field: from the use of imaging tools such as X-ray Computed Tomography to explore microbial growth in soils, to the fabrication of scratched materials to examine microbial-surface interactions, to the design of microfluidic devices to track microbial biofilm formation and the metabolic processes therein. This review discusses new approaches and challenges for incorporating structured elements into the study of microbial processes across different scales. We highlight how such methods can be pivotal for furthering our understanding of microbial interactions with their environments.