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Investigating the functionality of an Eco-Cooler made of plastic bottles

Tong et al. | Jul 22, 2026

Investigating the functionality of an Eco-Cooler made of plastic bottles
Image credit: Tong, Tong, and Migenes

In the study, the authors looked at an environmentally friendly alternative to A/C systems/cooling. They wanted to test the effectiveness of this cooling system called the Eco-Cooler as well as see if they could improve it. They found that the Eco-Cooler had minimal cooling, while their altered Eco-Cooler system had some cooling. This results shows the use of water helps cool the environment a lot more.

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Assessing Spanish interpretation in community healthcare: a study of patient satisfaction

Yon et al. | Jun 22, 2026

Assessing Spanish interpretation in community healthcare: a study of patient satisfaction
Image credit: Yon and Jones

This manuscript explores the use of Spanish language translators in an outpatient clinic in New Jersey. The authors surveyed patients before and after in person, video, and telephone appointments to determine which modality was most acceptable to the patients. The authors found that the three modalities did not differ in patient satisfaction, but that patients were grateful for translations services and that patient trust may be expanded by the use of these services and by focuses of translator soft skills.

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Development of selective RAC1/KLRN inhibitors

Kubrat Neczaj-Hruzewicz et al. | Nov 04, 2024

Development of selective RAC1/KLRN inhibitors

Kalirin is a guanine nucleotide exchange factor (GEF) for the GTPase RAC1, linked to schizophrenia and Alzheimer’s Disease. It plays a crucial role in synaptic plasticity by regulating dendritic spine formation and actin cytoskeleton remodeling, which are essential for creating new synapses. Authors developed two novel compounds targeting kalirin, confirming that predictive modeling can indicate biological activity.

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The Role of a Mask - Understanding the Performance of Deep Neural Networks to Detect, Segment, and Extract Cellular Nuclei from Microscopy Images

Dasgupta et al. | Jul 06, 2021

The Role of a Mask - Understanding the Performance of Deep Neural Networks to Detect, Segment, and Extract Cellular Nuclei from Microscopy Images

Cell segmentation is the task of identifying cell nuclei instances in fluorescence microscopy images. The goal of this paper is to benchmark the performance of representative deep learning techniques for cell nuclei segmentation using standard datasets and common evaluation criteria. This research establishes an important baseline for cell nuclei segmentation, enabling researchers to continually refine and deploy neural models for real-world clinical applications.

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