Debris Flow Risk Assessment and Land-Use Planning – A Case Study of Jhonglun Hot Spring Area

The Jhonglun Scenic Area in Chiayi County, is famous for its hot spring, the region was hit by debris flow with tremendous losses and resulted with dramatic change of the landscape during Typhoon Morakot in 2009. The most effective strategy for reducing natural hazard risks is through land-use planning. Following the concept of Risk=Hazard*Exposure*Vulnerability, this study conducted risk identification through the collection of landslide inventory and history debris flow hazard mapping of Chiayi DF051 potential debris flow torrent. Together with elements at risk information from field investigations, the risk analysis was conducted with several return periods debris flow simulation to recognize the possible economic losses and fatalities by debris flow. The identified high risk areas in Jhonglun Scenic Area were compared to the current special district planning to understand the spatial distribution of high risk areas. The result shows that some of the designated zones were among the areas with high debris flow risks, which further indicates that land-use planning should consider the consequences of natural hazards. The result of this study provides one of the first steps for land use planning restrictions within the potential debris flow region

AMP-activated protein kinase activation mediates CCL3-induced cell migration and matrix metalloproteinase-2 expression in human chondrosarcoma

Chemokine (C-C motif) ligand 3 (CCL3), also known as macrophage inflammatory protein-1α, is a cytokine involved in inflammation and activation of polymorphonuclear leukocytes. CCL3 has been detected in infiltrating cells and tumor cells. Chondrosarcoma is a highly malignant tumor that causes distant metastasis. However, the effect of CCL3 on human chondrosarcoma metastasis is still unknown. Here, we found that CCL3 increased cellular migration and expression of matrix metalloproteinase (MMP)-2 in human chondrosarcoma cells. Pre-treatment of cells with the MMP-2 inhibitor or transfection with MMP-2 specific siRNA abolished CCL3-induced cell migration. CCL3 has been reported to exert its effects through activation of its specific receptor, CC chemokine receptor 5 (CCR5). The CCR5 and AMP-activated protein kinase (AMPK) inhibitor or siRNA also attenuated CCL3-upregulated cell motility and MMP-2 expression. CCL3-induced expression of MMP-2 and migration were also inhibited by specific inhibitors, and inactive mutants of AMPK, p38 mitogen activated protein kinase (p38 or p38-MAPK), and nuclear factor κB (NF-κB) cascades. On the other hand, CCL3 treatment demonstrably activated AMPK, p38, and NF-κB signaling pathways. Furthermore, the expression levels of CCL3, CCR5, and MMP-2 were correlated in human chondrosarcoma specimens. Taken together, our results indicate that CCL3 enhances the migratory ability of human chondrosarcoma cells by increasing MMP-2 expression via the CCR5, AMPK, p38, and NF-κB pathways

Disordered Fe vacancies and superconductivity in potassium-intercalated iron selenide (K2-xFe4+ySe5)

The parent compound of an unconventional superconductor must contain unusual correlated electronic and magnetic properties of its own. In the high-Tc potassium intercalated FeSe, there has been significant debate regarding what the exact parent compound is. Our studies unambiguously show that the Fe-vacancy ordered K2Fe4Se5 is the magnetic, Mott insulating parent compound of the superconducting state. Non-superconducting K2Fe4Se5 becomes a superconductor after high temperature annealing, and the overall picture indicates that superconductivity in K2-xFe4+ySe5 originates from the Fe-vacancy order to disorder transition. Thus, the long pending question whether magnetic and superconducting state are competing or cooperating for cuprate superconductors may also apply to the Fe-chalcogenide superconductors. It is believed that the iron selenides and related compounds will provide essential information to understand the origin of superconductivity in the iron-based superconductors, and possibly to the superconducting cuprates

Knowledge-Enriched Visual Storytelling

Stories are diverse and highly personalized, resulting in a large possible output space for story generation. Existing end-to-end approaches produce monotonous stories because they are limited to the vocabulary and knowledge in a single training dataset. This paper introduces KG-Story, a three-stage framework that allows the story generation model to take advantage of external Knowledge Graphs to produce interesting stories. KG-Story distills a set of representative words from the input prompts, enriches the word set by using external knowledge graphs, and finally generates stories based on the enriched word set. This distill-enrich-generate framework allows the use of external resources not only for the enrichment phase, but also for the distillation and generation phases. In this paper, we show the superiority of KG-Story for visual storytelling, where the input prompt is a sequence of five photos and the output is a short story. Per the human ranking evaluation, stories generated by KG-Story are on average ranked better than that of the state-of-the-art systems. Our code and output stories are available at https://github.com/zychen423/KE-VIST.Comment: AAAI 202

Establishing engineering S-curves to evaluate supervision engineer allocations for highway construction projects

An engineering consultant firm needs to allocate engineers to supervise a highway construction project in each month during the construction phase. Properly assigning the supervision engineers under a cost-plus-fixed-fee contract has been a key factor affecting the profitability of the firm and the quality assurance of the project. Assigning too many engineers will be a waste, while allocating too few engineers may harm the supervision quality. This work proposes a two-stage model to develop engineering S-curves (called ES-curves) for planning and controlling the engineering super­vision schedule. In the planning stage, a predictive ES-curve model is established based on historical ES-curves. In the controlling stage, an ES-curve is built according to the relationships between the engineering progress and construction progress. A cluster analysis and regression analysis are applied to the model development. A case study demonstrates that the produced ES-curves can help management in planning and evaluating when to increase or decrease the number of supervision engineers assigned to a project