Haptic Interactions with Virtual Reality

Many possible systems exist that could benefit from Haptic Interactions, the communication of forces between a user and a system. Robotic assisted rehabilitation, interactive Virtual Reality media, and Telerobotics are some examples. However, due to simplified interactions methods, high costs, and lack of application development tools, Haptic Interaction with Virtual Reality has not reached its full potential. As a solution towards these problems, the team created a development platform Haptic Interaction System, capable of supplying Haptic Interactions between a user and hosted simulated environment and objects, along with the tools to enhance the system and develop applications based on Haptic Interactions

YOLO-LHD: an enhanced lightweight approach for helmet wearing detection in industrial environments

Establishing a lightweight yet high-precision object detection algorithm is paramount for accurately assessing workers’ helmet-wearing status in intricate industrial settings. Helmet detection is inherently challenging due to factors like the diminutive target size, intricate backgrounds, and the need to strike a balance between model compactness and detection accuracy. In this paper, we propose YOLO-LHD (You Only Look Once-Lightweight Helmet Detection), an efficient framework built upon the YOLOv8 object detection model. The proposed approach enhances the model’s ability to detect small targets in complex scenes by incorporating the Coordinate attention mechanism and Focal loss function, which introduce high-resolution features and large-scale detection heads. Additionally, we integrate the improved Ghostv2 module into the backbone feature extraction network to further improve the balance between model accuracy and size. We evaluated our method on MHWD dataset established in this study and compared it with the baseline model YOLOv8n. The proposed YOLO-LHD model achieved a reduction of 66.1% in model size while attaining the best 94.3% mAP50 with only 0.86M parameters. This demonstrates the effectiveness of the proposed approach in achieving lightweight deployment and high-precision helmet detection

Mars Settlement Exhibit Project

This report, prepared for the Mars Foundation, lays out a plan for developing a museum exhibit pertaining to the settlement of Mars called the ”Phobos First Scenario”. Plans for the production of a model Mars rover with accompanying software and game objects are contained herein. Supporting research was done documenting the reaction to the plan and the likely efficacy of such an exhibit. Corollary exhibit materials are also presented. Using the recommendations and materials in this report, it should be possible to build a full museum exhibit fit for children of middle-school age given appropriate funding

Circular RNAs as a potential source of neoepitopes in cancer

Neoepitopes have attracted much attention as targets for immunotherapy against cancer. Therefore, efficient neoepitope screening technology is an essential step in the development of personalized vaccines. Circular RNAs (circRNAs) are generated by back-splicing and have a single-stranded continuous circular structure. So far, various circRNAs have been poorly characterized, though new evidence suggests that a few translated circRNAs may play a role in cancer. In the present study, circRNA was used as a source of neoepitope, a novel strategy as circRNA-derived neoepitopes have never been previously explored. The present study reports CIRC_neo (circRNA-derived neoepitope prediction pipeline), which is a comprehensive and automated bioinformatic pipeline for the prediction of circRNA-derived neoepitopes from RNA sequencing data. The computational prediction from sequencing data requires complex computational workflows to identify circRNAs, derive the resulting peptides, infer the types of human leukocyte antigens (HLA I and HLA II) in patients, and predict the neoepitopes binding to these antigens. The present study proposes a novel source of neoepitopes. The study focused on cancer-specific circRNAs, which have greatly expanded the source pool for neoepitope discovery. The statistical analysis of different features of circRNA-derived neoepitopes revealed that circRNAs could produce long proteins or truncated proteins. Because the peptides were completely foreign to the human body, they could be highly immunogenic. Importantly, circRNA-derived neoepitopes capable of binding to HLA were discovered. In the current study, circRNAs were systematically analyzed, revealing potential targets and novel research clues for cancer diagnosis, treatment, and prospective personalized vaccine research

Measuring charge distribution of molecular cations by atomic Coulomb probe microscope

Imaging the charge distributions and structures of molecules and clusters will promote the understanding of the dynamics of the quantum system. Here, we report a method by using an Ar atom as a tip to probe the charge distributions of benzene (Bz) cations in gas phase. Remarkably, the measured charge distributions of Bz cation (QH =0.204,QC=-0.037)and dication (QH =0.248,QC=0.0853)agree well with the calculated Mulliken distributions,and the structures of Bz dimer is reconstructed by using the measured charge distributions. The structures of two Bz dimer isomers (T-shaped and PD isomers) can be resolved from the measured inter-molecular potential V(R) between two Bz ions, and the structures of Bz dimer agree well with the theoretical predictions.Comment: 7 pages, 3 Figure

Isolation and Characterization of Two New Deoxynivalenol-Degrading Strains, Bacillus sp. HN117 and Bacillus sp. N22

peer reviewedDeoxynivalenol (DON), produced by Fusarium species, is one of the most common trichothecenes detected in cereals pre- and post-harvest, which poses a great threat to the health of livestock and human beings due to its strong toxicity. In this study, we isolated and characterized two DON-degrading bacterial strains, Bacillus sp. HN117 and Bacillus sp. N22. Both strains could degrade DON efficiently in a wide range of temperatures (from 25 °C to 42 °C) and concentrations (from 10 mg/L to 500 mg/L). After optimization of the degradation conditions, 29.0% DON was eliminated by HN117 in 72 h when it was incubated with 1000 mg/L DON; meanwhile, the DON degradation rate of N22 was boosted notably from 7.41% to 21.21% within 120 h at 500 mg/L DON. Degradation products analysis indicated HN117 was able to transform DON into a new isomer M-DOM, the possible structure of which was deduced based on LC-MS and NMR analysis, and N22 could convert DON into potential low-toxic derivatives norDON E and 9-hydroxymethyl DON lactone. These two strains have the potential to be developed as new biodegrading agents to control DON contamination in food and feed industries

Programming Correlated Magnetic States via Gate Controlled Moir\'e Geometry

Understanding quantum many-body systems is at the heart of condensed matter physics. The ability to control the underlying lattice geometry of a system, and thus its many-body interactions, would enable the realization of and transition between emergent quantum ground states. Here, we report in-situ gate switching between honeycomb and triangular lattice geometries of an electron many-body Hamiltonian in R-stacked MoTe2 moir\'e bilayers, resulting in switchable magnetic exchange interactions. At zero electric field, we observe a correlated ferromagnetic insulator near one hole per moir\'e unit cell ({\nu}=-1), i.e., a quarter-filled honeycomb lattice, with a widely tunable Curie temperature up to 14K. Fully polarizing layer pseudospin via electric field switches the system into a half-filled triangular lattice with antiferromagnetic interactions. Further doping this layer-polarized superlattice introduces carriers into the empty layer, tuning the antiferromagnetic exchange interaction back to ferromagnetic. Our work demonstrates R-stacked MoTe2 moir\'es to be a new laboratory for engineering correlated states with nontrivial topology.Comment: 13 pages, 4 figures, plus supplementary materia