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Thermoelectric Power Generation: Harnessing Solar Thermal Energy to Power an Air Conditioner

Lew et al. | Jul 06, 2021

Thermoelectric Power Generation: Harnessing Solar Thermal Energy to Power an Air Conditioner

The authors test the feasibility of using thermoelectric modules as a power source and as an air conditioner to decrease reliance on fossil fuels. The results showed that, at its peak, their battery generated 27% more power – in watts per square inch – than a solar panel, and the thermoelectric air conditioner operated despite an unsteady input voltage. The battery has incredible potential, especially if its peak power output can be maintained.

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Significance of Tumor Growth Modeling in the Behavior of Homogeneous Cancer Cell Populations: Are Tumor Growth Models Applicable to Both Heterogeneous and Homogeneous Populations?

Reddy et al. | Jun 10, 2021

Significance of Tumor Growth Modeling in the Behavior of Homogeneous Cancer Cell Populations: Are Tumor Growth Models Applicable to Both Heterogeneous and Homogeneous Populations?

This study follows the process of single-cloning and the growth of a homogeneous cell population in a superficial environment over the course of six weeks with the end goal of showing which of five tumor growth models commonly used to predict heterogeneous cancer cell population growth (Exponential, Logistic, Gompertz, Linear, and Bertalanffy) would also best exemplify that of homogeneous cell populations.

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Determining the Effects of Voice Pitch on Adolescent Perception, Subconscious Bias, and Marketing Success Using Electroencephalography

Guan et al. | Apr 28, 2021

Determining the Effects of Voice Pitch on Adolescent Perception, Subconscious Bias, and Marketing Success Using Electroencephalography

Voice pitch affects perceived authoritativeness, competency, and leadership capacity. In this study, the authors suggest that examining certain measures of brain activity collected using an affordable EEG could predict advertising effectiveness, which may be invaluable in future neuromarketing research. Understanding voice pitch and other factors that cause implicit bias may allow significant advances in marketing, facilitating business success.

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Evaluating the impact of prompting styles on LLM accuracy for AIME math questions

Ganesa et al. | Jul 26, 2026

Evaluating the impact of prompting styles on LLM accuracy for AIME math questions

Large language models are increasingly used to solve math problems, but their ability to handle multi-step reasoning remains uncertain. In this study, students tested whether different prompting styles could improve LLM accuracy on challenging AIME math questions and found that detailed step-by-step solutions did not significantly outperform simpler prompts. These results suggest that improving LLM mathematical reasoning may require deeper model-level advances rather than changes in prompting style alone.

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A 3D printed triboelectric nanogenerator for bridge vibration energy harvesting and sensing

Walavalkar et al. | Jul 19, 2026

A 3D printed triboelectric nanogenerator for bridge vibration energy harvesting and sensing
Image credit: Jakub Żerdzicki

This study strongly illustrates that optimizing 3D printing parameters would enhance a triboelectric nanogenerator's performance. The design improvements substantiate the potential of optimized, 3D-printed TENGs for developing scalable, cost-effective solutions for powering low-energy electronics, particularly in applications such as structural health monitoring.

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Evaluating need for adversarial training data given algorithmic defense methods against adversarial attacks

Yian et al. | Jul 05, 2026

Evaluating need for adversarial training data given algorithmic defense methods against adversarial attacks

The purpose of this study was to determine the necessity of previous non-algorithmic attacks (Adversarial Training) in light of algorithmic defense methods (Gradient Masking and Defensive Distillation) against FGSM attacks. We found a significant increase in image classification accuracy from defense methods with the non-algorithmic defense method compared to ones without. By analyzing the significance with a McNemar test, we determined that the inclusion of non-algorithmic defense methods is still necessary in light of new algorithmic defense methods.

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Innovative fake health news detection: Integrating emotional features into graph neural networks

Wang et al. | Jul 03, 2026

Innovative fake health news detection: Integrating emotional features into graph neural networks
Image credit: Wang and Wang

This manuscript tackles a major social issue in the health news sector, with social media being one of the primary sources of information and a prime spot to propagate fake news. The author proposes X-HND , which is a unique architecture that combines emotional and contextual analysis in a Graph Neural Network to accurately detect fake news. This was a multi-step process which involved the creation of a custom health news dataset (HNDataset), and an emotional variant that uses RoBERTa to extract emotion. These dataset were then used to prove the hypothesis that accuracy increases when the custom dataset is used to train the model and that with the integration of emotion capture, the detection accuracy increases further.

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Differences in online reviews between different communities: An empirical study on Amazon and Goodreads

Choi et al. | May 30, 2026

Differences in online reviews between different communities:  An empirical study on Amazon and Goodreads
Image credit: Choi and Choi

Online review platforms often provide different reviews on the same product, potentially confusing consumers. In this study, we found that the number of raters on Amazon is lower for the same book, while ratings on Amazon were higher than those on Goodreads. Furthermore, these differences in ratings and rater counts were larger for fiction books than for non‑fiction books.

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