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Mosquito-borne diseases are a major issue across the world, and the objective for this project was to determine the characteristics that make some communities more susceptible to these diseases than others. The authors identified and studied characteristics that make communities susceptible to mosquito-borne diseases, including water in square miles, average temperature, population, population density, and poverty rates per county. They found that the population of a county is the best indicator of the prevalence of mosquito-borne diseases.

Many common respiratory illnesses like bronchitis, asthma, and chronic obstructive pulmonary disease (COPD) lead to bronchial inflammation and, subsequently, a blockage. However, there are many difficulties in measuring the severity of the blockage. A numeric metric to determine the degree of the blockage severity is necessary. To tackle this demand, we aimed to develop a novel human respiratory model and design a deep-learning program that can constantly monitor and report bronchial blockage by recording breath sounds in a non-intrusive way.

Salmonella is a genus of bacteria responsible for over 90 million cases of intestinal illnesses yearly. Like many bacteria, Salmonella can create a biofilm matrix, which confers stronger resistance against antibiotics. However, there has been relatively little research on the inhibition of Salmonella biofilm formation, which is a crucial factor in its widespread growth. In this study, Lee and Kim quantitatively measure the effectiveness of several common probiotics in inhibiting Salmonella bacterial growth. They found concentration-dependent antibacterial effects varied among the probiotics tested, indicating the possibility of probiotic species-specific mechanisms of Salmonella growth inhibition.

The number of bacterial infections in humans is rising, and a major contributor is foodborne illnesses, which affect a large portion of the population and result in many hospitalizations and deaths. Common household cleaners are an effective strategy to combat foodborne illness, but they are often costly and contain harmful chemicals. Thus, the authors sought to test the antimicrobial effectiveness of spices (clove, nutmeg, astragalus, cinnamon, turmeric, and garlic) on microbes cultured from refrigerator handles and cutting boards. Results from this study demonstrate long-lasting, antimicrobial effects of multiple spices that support their use as alternatives to common household cleaners.

Droughts have a wide range of effects, from ecosystems failing and crops dying, to increased illness and decreased water quality. Drought prediction is important because it can help communities, businesses, and governments plan and prepare for these detrimental effects. This study predicts drought conditions by using predictable weather patterns in machine learning models.

Long hospital stays can be stressful for the patient for many reasons. We hypothesized that age would be the greatest predictor of hospital stay among patients who underwent orthopedic surgery. Through our models, we found that severity of illness was indeed the highest factor that contributed to determining patient length of stay. The other two factors that followed were the facility that the patient was staying in and the type of procedure that they underwent.

Bacterial infection is resurging as one of the most dangerous challenges facing the medical establishment. Americans spend about 55 to 70 billion dollars per year on antibiotics, yet these antibiotics are becoming increasingly ineffective as illness-causing bacteria gain resistance to the prescribed drugs. We tested if 11 commonly-used spices could inhibit growth of the gram-negative bacteria, E. coli, the main takeaway from these experiments is that certain spices and herbs have antibacterial effects that inhibit growth of E.coli , and these spices could show similarly promising activity towards other bacteria.

Almost all urban areas face the challenge of urban heat islands, areas with substantially hotter land surface temperatures than the surrounding rural areas. These areas are associated with worse air and water
quality, increased power outages, and increased heat-related illnesses. To learn more about these areas, Ustin et al. analyze satellite images of Cleveland neighborhoods to find out if there is a correlation between surface area development and surface temperature.

Zoos offer educational and scientific advantages but face high maintenance costs and challenges in animal care due to diverse species' habits. Challenges include tracking animals, detecting illnesses, and creating suitable habitats. We developed a deep learning framework called SmartZoo to address these issues and enable efficient animal monitoring, condition alerts, and data aggregation. We discovered that the data generated by our model is closer to real data than random data, and we were able to demonstrate that the model excels at generating data that resembles real-world data.

In this report, Bhardwaj and Sharma tested whether placing specific plants indoors can reduce levels of indoor air pollution that can lead to lung-related illnesses. Using machine learning, they show that plants improved overall indoor air quality and reduced levels of particulate matter. They suggest that plant-based interventions coupled with sensors may be a useful long-term solution to reducing and maintaining indoor air pollution.