Omkar2118/datasets huggingface dataset:
Overall-Driving-Behavior-Recognition-By-Smartphone
Full name: Hamid Reza Eftekhari

Monitoring and evaluating of driving behavior is the main goal of this paper that encourage us to develop a new system based on Inertial Measurement Unit (IMU) sensors of smartphones. In this system, a hybrid of Discrete Wavelet Transformation (DWT) and Adaptive Neuro Fuzzy Inference System (ANFIS) is used to recognize overall driving behaviors. The behaviors are classified into the safe, the semi-aggressive, and the aggressive classes that are adopted with Driver Anger Scale (DAS) self-reported questionnaire results. The proposed system extracts four features from IMU sensors in the forms of time series. They are decomposed by DWT in two levels and their energies are sent to six ANFISs. Each ANFIS models the different perception about driving behavior under uncertain knowledge and returns the similarity or dissimilarity between driving behaviors. The results of these six ANFISs are combined by three different decision fusion approaches. Results show that Coiflet-2 is the most suitable mother wavelet for driving behavior analysis. In addition, the proposed system recognizes the overall driving behavior patterns with 92% accuracy without necessity to evaluate the maneuvers one by one. We show that without longitude acceleration data, the driver behavior cannot be recognized successfully while the results do not disturb substantially when the gyroscope is not available.
16s rDNA sequencing of feces from C9orf72 loss of function mice

In one round of sequencing, 5 fecal pellets from 2 pro-inflammatory environments (Harvard BRI/Johns Hopkins) and 2 pro-survival environments (Broad Institute/Jackson Labs) were sequenced at the 16s rDNA locus. In a second round of sequencing, 9 fecal pellets from Harvard BRI, 9 fecal pellets from Broad Institute, 6 fecal pellets from Harvard BRI mice transplanted with Harvard BRI feces, and 6 pellets from Harvard BRI mice transplanted with Broad feces were sequenced at the 16S rDNA locus