Proposal for the Restoration of Fire-Damaged Soil Using Water-Soluble Aromatic Compounds Derived from Soil Actinomycetes
The following issues associated with soil affected by wildfires were identified: First, there was a significant decline in the populations of anaerobic and aerobic soil bacteria, which play a critical role in the decomposition and cycling of organic matter. This decline resulted in reduced water retention capacity and porosity of the soil, leading to poor moisture retention and increased evaporation compared to unaffected soil. Moreover, the organic matter content in the soil was significantly depleted, inhibiting plant growth. Additionally, there was a notable proliferation of methane-producing bacteria, which contribute to the greenhouse effect. It was further observed that fire-damaged soils exhibit limited natural recovery, even over prolonged periods. .An investigation into the underlying causes of these problems revealed that actinomycetes, the primary microorganisms responsible for producing watersoluble aromatic compounds in soil, are particularly sensitive to heat compared to other bacterial species. Research demonstrated that the population and diversity of actinomycetes are significantly diminished in soils exposed to wildfires. To mitigate these issues, water-soluble aromatic compounds produced by actinomycetes were extracted and introduced into wildfire-affected soil. This intervention promoted the restoration of actinomycetes populations, enabling their normal growth in the affected soil. Consequently, various wildfire-induced soil problems were effectively resolved. These outcomes were confirmed through the study...Key Words: Actinomycetes, anaerobic and aerobic soil bacteria, methane-producing bacteria, wildfires, water-soluble aromatic compounds.
Modal frequencies in a nonlinear beam-magnet coupled oscillator system
In this paper, I investigated the motion of a nonlinear coupled oscillator system consisting of two leaf springs secured to a non-magnetic base with magnets attached to the upper ends such they repel and are free to move. My results showed that the system exhibits the beats phenomenon, and interestingly that the frequencies show a dependence on initial conditions. I hence hypothesized this sensitivity is due to two sources of nonlinearities: geometric nonlinearity during large deflections of the leaf springs and the nonlinearity in the magnetic force. To test this hypothesis, a nonlinear mathematical model was developed, accounting for nonlinear beam effects up to third order and fully solving the nonlinear magnetic force using a current cylinder model, accounting for the tilting of the magnets. An approximate linear model was also developed for comparison. The theoretical models were validated experimentally by investigating the dynamic motion of the springs through time, as well as how the modal frequencies in the system depend on the initial displacement, the length of the spring, and the distance between the springs. The more accurate nonlinear model I derived shows good agreement with experimental results while the linear theory does not, highlighting the importance of nonlinearities in this system. An improved understanding of these nonlinear systems could lead to advancements in design and efficiency, and safety in various applications such as energy harvesting.
DSUP: New Research On The Implementation Of Radioresistance In Cellular Systems
In radiation treatments and manned interplanetary space travel, radiation is one of the biggest problems. The radiotolerance of cancer cells makes it necessary to apply high doses to surrounding healthy tissues by subjecting the cells to heavy stress. With regard to space travel (which involves a minimum travel time of 6 months) (1,2) the danger concerns cosmic radiation which is capable of inducing genetic mutations that, in turn, can evolve into very serious pathologies, such as cancer, damage to dendrites consequently compromising synapses. The project is aimed at developing a technology that can address these issues and aims to make human DNA radioresistant. This study involves a nucleosome-binding protein called DSUP (Damage Suppressor Protein) unique to the tardigrade Ramazzottius Varieornatus and the subject of its radioresistance. It can theoretically safeguard genetic material damaged by radiation. *Internship theme at the Pino Torinese Astronomical Observatory and the DISIT-UPO Environmental Molecular Toxicology Laboratory. The study molecule: Numerous tests have been carried out through the "in silico" approach geared toward mathematical modeling of its protein structure and complex mechanisms of action simulated through artificial intelligence systems, followed by direct laboratory analysis involving biosynthesis of DSUP by genetically modified bacteria and related tests. Both approaches, applied synergistically, aim to make it accessible and useful for the protection of human health.
Decoding Climate Resilience: Functional Profiling of Protein Phosphatase 2C Family Genes for Abiotic Stress Tolerance in Rice
Problem • Rice is the primary cereal crop consumed by nearly half the population worldwide • By 2050, there will be a 50% increase in demand for rice • The world’s poor populations depend more on rice, both for income and consumption, than any other food. Rice is the single-largest source of employment and income for rural people • Worldwide, 51–82% of agricultural crop yield is lost annually due to abiotic stress due to climate change • Climate change causes extreme temperatures, erratic rainfall, dangerous droughts, and increased salinity from rising sea levels Solution • To adapt to abiotic stress, rice has intricate signaling pathways, particularly those mediated by the phytohormone abscisic acid (ABA), that cause an increase in stress tolerance • Clade A genes of the Protein Phosphatase 2C (PP2C) gene family are known to be negative regulators of the ABA signaling pathway. • “Deleting” these genes activates the ABA pathway and increases stress tolerance in rice without inducing stress CRISPR gene editing technology is the ideal solution Research Goal • While the role of PP2C genes in stress response is recognized, there is a gap in understanding the specific genes within this family that contribute significantly to stress signaling. Furthermore, there is a need for a detailed investigation into the effects of targeted CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) genome editing on rice stress response pathways.
BeeMind AI: Development of an AI-Based System to Assess Honeybee Health, Behavior, and Nutrient Effects on Learning and Memory
Due to their pollination services, honeybees are one of the most ecologically vital animals, being singlehandedly responsible for nearly 80% of global agricultural pollination [1]. However, in recent years, they have experienced large declines in populations, and as a survey reported roughly 50% of beekeepers in the US lost their honeybee colonies [2]. These losses are experienced globally due to a combination of many factors, including but not limited to habitat loss, pesticides, climate change, and other invasive species [3, 4]. One of the biggest factors attributed to the decline of honeybee colonies is the usage of pesticides, specifically neonicotinoids [3-6]. Neonicotinoid compounds have been used globally since their introduction in the early 1990s [4]. Studies have shown that neonicotinoids can have both sublethal and lethal effects on honeybees, depending on the dosages that they are exposed to, as neonicotinoids bind to nervous system receptors of honeybees [7]. These effects can range from behavior changes to altered motor functions [7-9]. Among the reported effects, one of the more significant ones is the effect of neonicotinoids on honeybee learning and memory [10, 11]. Additionally, there is a lack of availability for methods of monitoring of honeybee hives, essentially meaning that the only methods to track honeybee health are through obtrusive physical methods of inspection. This paper aims to develop a novel AI-based honeybee health assessment system, able to monitor beehives using the following functions: continuous temperature and humidity monitoring both inside and outside the hive, as well as video and audio recording to assess honeybee health as well as population. In addition, this system can be used for honeybee-related studies such as nutrition effects and evaluation on health, learning, and memory. To do this, four types of nutrition have been studied and their effects have been analyzed by a deep learning approach.