Plastic analysis of beam - columns

The results of an analytical study of the inelastic deformation of a wide-flange steel beam-column are presented. Emphasis has been placed on the influence of axial thrust on the pinned-end beam-column subjected to equal end moments with opposite direction. For this type of beam-column behavior, the relationship between the applied moment, axial load, and resultant curvature for the region in the plastic range has been studied in this investigation --Abstract, page ii

Generation of charged droplets by field ionization of liquid helium

Positively charged helium droplets were produced by ionization of liquid helium in an electrostatic spraying experiment, in which fluid emerging from a thin glass capillary was ionized by applying a high voltage to a needle inside the capillary. At 2.2 K, fine droplets (<10 mu m in diameter) were produced in pulsed sprays or showers with total currents as high as 0.4 mu A at relatively low voltages (2-4 kV). Ionization was accompanied by a visible glow at the needle and glass tips. Droplet formation was suppressed at 3.5 K. In contrast, liquid nitrogen formed a well-defined Taylor cone with droplets having diameters comparable to the jet (approximate to 100 mu m) at much lower currents (3 nA) and higher voltages (9 kV), in agreement with previous results. The mechanism for charging in these liquids was proposed to be field ionization, identical to the processes leading to conduction in cryogenic insulating liquids observed by Gomer. The high currents resulting from field ionization in helium, together with the intrinsically low surface tension of helium I, led to charge densities that greatly exceeded the Rayleigh limit, thus preventing formation of a Taylor cone and resulting in Coulomb explosion of the liquid

Generation of energetic He atom beams by a pulsed positive corona discharge

Time-of-flight measurements were made of neutral helium atom beams extracted from a repetitive, pulsed, positive-point corona discharge. Two strong neutral peaks, one fast and one slow, were observed, accompanied by a prompt photon peak and a fast ion peak. All peaks were correlated with the pulsing of the discharge. The two types of atoms appear to be formed by different mechanisms at different stages of the corona discharge. The fast atoms had energies of 190 eV and were formed at the onset of the pulsing, approximately 0.7 µs before the maximum of the photon peak. The slow peak, composed of electronically metastable He atoms, originated 30–50 µs after the photon pulse, and possessed a nearly thermal velocity distribution. The velocity distribution was typical of an undisturbed supersonic expansion with a stagnation temperature of 131 K and a speed ratio of 3.6. Peak intensities and velocities were measured as a function of source voltage, stagnation pressure, and skimmer voltage

The International Decision-Making and Travel Behavior of Graduates Participating in Working Holiday

After graduation, most graduates find themselves at a significant stage in their life as they have to decide between “further study” and “working.” When faced with this confusion and uncertainty, a “working holiday” combining travel and work has coincidentally becomes a third option. This study employed a qualitative approach through literature review, in-depth interviews, and semi-structured interviews. The research revealed that graduates are influenced by “internal personal thinking” and “external driving forces” when they embark on a working holiday. The former includes negative obstructions and positive stimulus. The latter factor’s stimulus includes attraction of natural landscapes, history and culture, learning foreign languages, safety concerns, difficulties in visa application, and the opportunity to obtain a salaried job. The process of embarking on a working holiday was complex and unpredictable. The traveling behavior of working holiday destinations included short-distance leisure behavior and long-distance traveling behavior. In terms of the influences of short-distance leisure behavior, graduates preferred being employed by service industries that had less working hours, flexible work arrangements and included the purchase of preferential price tickets. Graduates’ long-distance traveling behavior was affected by the work they performed. The travel time was different between various industries

The Emerging Epigenetic Landscape in Melanoma

Melanoma is the deadliest form of skin cancer. The disease is driven by molecular alterations in oncogenic signaling pathways, such as mitogen‐activated protein kinase (MAPK) and phosphatidylinositol 3‐kinase (PI3K). Activating mutations in oncogenes, such as BRAF and NRAS, and inactivating mutations in tumor suppressors genes, such as PTEN, promote this disease by altering cellular processes involved in growth, survival, and migration. Therapies targeting critical nodes in these pathways have demonstrated efficacy in clinical trials, but their therapeutic potential has been limited by the rapid onset of drug resistance. Durable therapeutic responses have also been observed in patients receiving immunotherapy. However, this activity appears to be confined to a subset of patients, and combinations with targeted therapies have raised safety concerns. Accumulating evidence strongly suggests that the pathogenesis of melanoma is also shaped by the aberrant activity of epigenetic factors that regulate gene expression through the modification of DNA and chromatin. This chapter provides a comprehensive review of the epigenetic alterations in melanoma and highlights the roles played by specific chromatin regulators during disease progression. We also discuss the clinical utility of both first and second generation epigenetic therapies in the melanoma setting, placing emphasis on the potential to overcome resistance to targeted therapies and to serve as priming agents for immunotherapies

Semiautomated optical coherence tomography-guided robotic surgery for&nbsp;porcine lens removal.

PurposeTo evaluate semiautomated surgical lens extraction procedures using the optical coherence tomography (OCT)-integrated Intraocular Robotic Interventional Surgical System.SettingStein Eye Institute and Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, USA.DesignExperimental study.MethodsSemiautomated lens extraction was performed on postmortem pig eyes using a robotic platform integrated with an OCT imaging system. Lens extraction was performed using a series of automated steps including robot-to-eye alignment, irrigation/aspiration (I/A) handpiece insertion, anatomic modeling, surgical path planning, and I/A handpiece navigation. Intraoperative surgical supervision and human intervention were enabled by real-time OCT image feedback to the surgeon via a graphical user interface. Manual preparation of the pig-eye models, including the corneal incision and capsulorhexis, was performed by a trained cataract surgeon before the semiautomated lens extraction procedures. A scoring system was used to assess surgical complications in a postoperative evaluation.ResultsComplete lens extraction was achieved in 25 of 30 eyes. In the remaining 5 eyes, small lens pieces (≤1.0&nbsp;mm3) were detected near the lens equator, where transpupillary OCT could not image. No posterior capsule rupture or corneal leakage occurred. The mean surgical duration was 277&nbsp;seconds&nbsp;±&nbsp;42 (SD). Based on a 3-point scale (0&nbsp;=&nbsp;no damage), damage to the iris was 0.33&nbsp;±&nbsp;0.20, damage to the cornea was 1.47&nbsp;±&nbsp;0.20 (due to tissue dehydration), and stress at the incision was 0.97&nbsp;±&nbsp;0.11.ConclusionsNo posterior capsule rupture was reported. Complete lens removal was achieved in 25 trials without significant surgical complications. Refinements to the procedures are required before fully automated lens extraction can be realized

PKE-RRT: Efficient Multi-Goal Path Finding Algorithm Driven by Multi-Task Learning Model

Multi-goal path finding (MGPF) aims to find a closed and collision-free path to visit a sequence of goals orderly. As a physical travelling salesman problem, an undirected complete graph with accurate weights is crucial for determining the visiting order. Lack of prior knowledge of local paths between vertices poses challenges in meeting the optimality and efficiency requirements of algorithms. In this study, a multi-task learning model designated Prior Knowledge Extraction (PKE), is designed to estimate the local path length between pairwise vertices as the weights of the graph. Simultaneously, a promising region and a guideline are predicted as heuristics for the path-finding process. Utilizing the outputs of the PKE model, a variant of Rapidly-exploring Random Tree (RRT) is proposed known as PKE-RRT. It effectively tackles the MGPF problem by a local planner incorporating a prioritized visiting order, which is obtained from the complete graph. Furthermore, the predicted region and guideline facilitate efficient exploration of the tree structure, enabling the algorithm to rapidly provide a sub-optimal solution. Extensive numerical experiments demonstrate the outstanding performance of the PKE-RRT for the MGPF problem with a different number of goals, in terms of calculation time, path cost, sample number, and success rate.Comment: 9 pages, 12 figure

Neural-Network-Driven Method for Optimal Path Planning via High-Accuracy Region Prediction

Sampling-based path planning algorithms suffer from heavy reliance on uniform sampling, which accounts for unreliable and time-consuming performance, especially in complex environments. Recently, neural-network-driven methods predict regions as sampling domains to realize a non-uniform sampling and reduce calculation time. However, the accuracy of region prediction hinders further improvement. We propose a sampling-based algorithm, abbreviated to Region Prediction Neural Network RRT* (RPNN-RRT*), to rapidly obtain the optimal path based on a high-accuracy region prediction. First, we implement a region prediction neural network (RPNN), to predict accurate regions for the RPNN-RRT*. A full-layer channel-wise attention module is employed to enhance the feature fusion in the concatenation between the encoder and decoder. Moreover, a three-level hierarchy loss is designed to learn the pixel-wise, map-wise, and patch-wise features. A dataset, named Complex Environment Motion Planning, is established to test the performance in complex environments. Ablation studies and test results show that a high accuracy of 89.13% is achieved by the RPNN for region prediction, compared with other region prediction models. In addition, the RPNN-RRT* performs in different complex scenarios, demonstrating significant and reliable superiority in terms of the calculation time, sampling efficiency, and success rate for optimal path planning.Comment: 9 pages, 8 figure