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Nanotexturing as a method to reduce dust accumulation on solar panels

Choi et al. | Jan 30, 2025

Nanotexturing as a method to reduce dust accumulation on solar panels

Dust accumulation on solar panels can reduce electricity output by 20–50%, posing a major challenge for solar energy collection. Instead of altering panel design, we explored a simpler approach by modifying surface energy through nanotexturing, predicting that hydrophobic surfaces would repel both water and dust. This study found that treating glass and silicone surfaces with potassium hydroxide (KOH) for 13 and 10 minutes, respectively, created optimal nanotextures (445 nm for glass, 205 nm for silicone), significantly reducing dirt accumulation and improving solar energy capture.

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Vineyard vigilance: Harnessing deep learning for grapevine disease detection

Mandal et al. | Aug 21, 2024

Vineyard vigilance: Harnessing deep learning for grapevine disease detection

Globally, the cultivation of 77.8 million tons of grapes each year underscores their significance in both diets and agriculture. However, grapevines face mounting threats from diseases such as black rot, Esca, and leaf blight. Traditional detection methods often lag, leading to reduced yields and poor fruit quality. To address this, authors used machine learning, specifically deep learning with Convolutional Neural Networks (CNNs), to enhance disease detection.

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The impact of greenhouse gases, regions, and sectors on future temperature anomaly with the FaIR model

Kosaraju et al. | Jul 29, 2024

The impact of greenhouse gases, regions, and sectors on future temperature anomaly with the FaIR model

This study explores how different economic sectors, geographic regions, and greenhouse gas types might affect future global mean surface temperature (GMST) anomalies differently from historical patterns. Using the Finite Amplitude Impulse Response (FaIR) model and four Shared Socioeconomic Pathways (SSPs) — SSP126, SSP245, SSP370, and SSP585 — the research reveals that future contributions to GMST anomalies.

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Effect of Gram-positive bacteria on antibiotic resistance in Gram-negative bacteria

Willem et al. | Mar 12, 2024

Effect of Gram-positive bacteria on antibiotic resistance in Gram-negative bacteria

Antibiotics are one of the most common treatments for bacterial infections, but the emergence of antibiotic resistance is a major threat to the control of infectious diseases. Many factors contribute to the development of antibiotic resistance. One is bacterial conjugation from Gram-positive to Gram-negative bacteria where there is a transfer of resistance genes from Gram-positive to Gram-negative bacteria that could increase antibiotic resistance in the latter. In light of these observations, we decided to test whether Gram-negative bacteria that came into contact with Gram-positive bacteria had a higher resistance to the antimicrobial properties of spices than Gram-negative bacteria that did not come into contact with Gram-positive bacteria.

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