Meta-heuristic approach for high-demand facility locations considering traffic congestion and greenhouse gas emission

Large facilities in urban areas, such as storage facilities, distribution centers, schools, department stores, or public service centers, typically generate high volumes of accessing traffic, causing congestion and becoming major sources of greenhouse gas (GHG) emission. In conventional facility-location models, only facility construction costs and fixed transportation costs connecting customers and facilities are included, without consideration of traffic congestion and the subsequent GHG emission costs. This study proposes methods to find high-demand facility locations with incorporation of the traffic congestion and GHG emission costs incurred by both existing roadway traffic and facility users into the total cost. Tabu search and memetic algorithms were developed and tested with a conventional genetic algorithm in a variety of networks to solve the proposed mathematical model. A case study to determine the total number and locations of community service centers under multiple scenarios in Incheon City is then presented. The results demonstrate that the proposed approach can significantly reduce both the transportation and GHG emission costs compared to the conventional facility-location model. This effort will be useful for decision makers and transportation planners in the analysis of network-wise impacts of traffic congestion and vehicle emission when deciding the locations of high demand facilities in urban areas

Microspinning: Local Surface Mixing via Rotation of Magnetic Microparticles for Efficient Small-Volume Bioassays

The need for high-throughput screening has led to the miniaturization of the reaction volume of the chamber in bioassays. As the reactor gets smaller, surface tension dominates the gravitational or inertial force, and mixing efficiency decreases in small-scale reactions. Because passive mixing by simple diffusion in tens of microliter-scale volumes takes a long time, active mixing is needed. Here, we report an efficient micromixing method using magnetically rotating microparticles with patterned magnetization induced by magnetic nanoparticle chains. Because the microparticles have magnetization patterning due to fabrication with magnetic nanoparticle chains, the microparticles can rotate along the external rotating magnetic field, causing micromixing. We validated the reaction efficiency by comparing this micromixing method with other mixing methods such as simple diffusion and the use of a rocking shaker at various working volumes. This method has the potential to be widely utilized in suspension assay technology as an efficient mixing strategy

User Equilibrium-Based Location Model of Rapid Charging Stations for Electric Vehicles with Batteries That Have Different States of Charge

A model was developed for the location of rapid charging stations for electric vehicles (EVs) in urban areas, taking into account the batteries' state of charge and users' charging and traveling behaviors. EVs are one means of preparing for the energy crisis and of reducing greenhouse gas emissions. To help relieve range anxiety, an adequate number of EV charging stations must be constructed. Rapid charging stations are needed in urban areas because there is inadequate space for slow-charging equipment. The objective function of the model is to minimize EVs' travel fail distance and the total travel time of the entire network when the link flow is determined by a user equilibrium assignment. The remaining fuel range (RFR) at the origin node is assumed to follow a probabilistic distribution to reflect users' charging behavior or technical development. The results indicate that the model described in this paper can identify locations for charging stations by using a probabilistic distribution function for the RFR. The location model, which was developed on the basis of user equilibrium assigmnent, is likely to consider the congested traffic conditions of urban areas, to avoid locating charging stations where they could cause additional traffic congestion. The proposed model can assist decision makers in developing policies that encourage the use of EVs, and it will be useful in developing an appropriate budget for implementing the plan.OAIID:oai:osos.snu.ac.kr:snu2014-01/102/0000002383/3SEQ:3PERF_CD:SNU2014-01EVAL_ITEM_CD:102USER_ID:0000002383ADJUST_YN:YEMP_ID:A075708DEPT_CD:457CITE_RATE:.556FILENAME:lee et al(2014) ue based location model.pdfDEPT_NM:건설환경공학부SCOPUS_YN:YCONFIRM:

One-Step Generation of a Drug-Releasing Hydrogel Microarray-On-A-Chip for Large-Scale Sequential Drug Combination Screening

Large-scale screening of sequential drug combinations, wherein the dynamic rewiring of intracellular pathways leads to promising therapeutic effects and improvements in quality of life, is essential for personalized medicine to ensure realistic cost and time requirements and less sample consumption. However, the large-scale screening requires expensive and complicated liquid handling systems for automation and therefore lowers the accessibility to clinicians or biologists, limiting the full potential of sequential drug combinations in clinical applications and academic investigations. Here, a miniaturized platform for high-throughput combinatorial drug screening that is "pipetting-free" and scalable for the screening of sequential drug combinations is presented. The platform uses parallel and bottom-up formation of a heterogeneous drug-releasing hydrogel microarray by self-assembly of drug-laden hydrogel microparticles. This approach eliminates the need for liquid handling systems and time-consuming operation in high-throughput large-scale screening. In addition, the serial replacement of the drug-releasing microarray-on-a-chip facilitates different drug exchange in each and every microwell in a simple and highly parallel manner, supporting scalable implementation of multistep combinatorial screening. The proposed strategy can be applied to various forms of combinatorial drug screening with limited amounts of samples and resources, which will broaden the use of the large-scale screening for precision medicine

Altered exocytosis of inhibitory synaptic vesicles at single presynaptic terminals of cultured striatal neurons in a knock-in mouse model of Huntington’s disease

Huntington’s disease (HD) is a progressive dominantly inherited neurodegenerative disease caused by the expansion of a cytosine-adenine-guanine (CAG) trinucleotide repeat in the huntingtin gene, which encodes the mutant huntingtin protein containing an expanded polyglutamine tract. One of neuropathologic hallmarks of HD is selective degeneration in the striatum. Mechanisms underlying selective neurodegeneration in the striatum of HD remain elusive. Neurodegeneration is suggested to be preceded by abnormal synaptic transmission at the early stage of HD. However, how mutant huntingtin protein affects synaptic vesicle exocytosis at single presynaptic terminals of HD striatal neurons is poorly understood. Here, we measured synaptic vesicle exocytosis at single presynaptic terminals of cultured striatal neurons (mainly inhibitory neurons) in a knock-in mouse model of HD (zQ175) during electrical field stimulation using real-time imaging of FM 1-43 (a lipophilic dye). We found a significant decrease in bouton density and exocytosis of synaptic vesicles at single presynaptic terminals in cultured striatal neurons. Real-time imaging of VGAT-CypHer5E (a pH sensitive dye conjugated to an antibody against vesicular GABA transporter (VGAT)) for inhibitory synaptic vesicles revealed a reduction in bouton density and exocytosis of inhibitory synaptic vesicles at single presynaptic terminals of HD striatal neurons. Thus, our results suggest that the mutant huntingtin protein decreases bouton density and exocytosis of inhibitory synaptic vesicles at single presynaptic terminals of striatal neurons, causing impaired inhibitory synaptic transmission, eventually leading to the neurodegeneration in the striatum of HD

A novel modified-indirect ELISA based on spherical body protein 4 for detecting antibody during acute and long-term infections with diverse Babesia bovis strains

Cattle sera positive by the RAP-1-based cELISA but negative by the SBP4-based MI-ELISA and IFA had negative results by Western blot analysis, suggesting possible false positive results in the cELISA. A. Molecular weight marker (48 to 180 Kd), B. K42-#21, C. W31-#Y-3, D. W31-#Y-11, E. W31-#0-3, F. W31-#Y-9, G. W31-#0-9, H. W31-#Y-10, I. W31-#Y-15, J. P21-#224, K. positive control serum with a band at 75kd representing B. bovis RAP-1 protein, J. negative control serum. Figure S2. Technical difference between the modified indirect ELISA and conventional indirect ELISA using rGST-SBP4 was illustrated in this figure. (DOCX 645 kb

Direct 2D-to-3D transformation of pen drawings

Pen drawing is a method that allows simple, inexpensive, and intuitive two-dimensional (2D) fabrication. To integrate such advantages of pen drawing in fabricating 3D objects, we developed a 3D fabrication technology that can directly transform pen-drawn 2D precursors into 3D geometries. 2D-to-3D transformation of pen drawings is facilitated by surface tension-driven capillary peeling and floating of dried ink film when the drawing is dipped into an aqueous monomer solution. Selective control of the floating and anchoring parts of a 2D precursor allowed the 2D drawing to transform into the designed 3D structure. The transformed 3D geometry can then be fixed by structural reinforcement using surface-initiated polymerization. By transforming simple pen-drawn 2D structures into complex 3D structures, our approach enables freestyle rapid prototyping via pen drawing, as well as mass production of 3D objects via roll-to-roll processing

Exploring consumer preference for taxis against ridesourcing services: an integrated choice and latent variable approach in Seoul, Korea

With the emergence of ride-sourcing services based on the development of smart mobile devices, many countries are considering introducing this type of service. From the government's point of view, improving consumers' preference for taxis against ride-sourcing services is essential to introduce the new service, considering the serious collapse of the taxi industry by introducing the service in the United States. For a comprehensive understanding of consumers’ preference for taxis, we consider several types of variables, including not only level-of-service variables and socio-demographic characteristics but also travel experience using taxis, mobile usage pattern, trip purpose, and consumers’ latent attitudes into a model based on the integrated choice and latent variable structure. The results indicate that the model performs well. We identified how consumers’ preference for a taxi can be improved in Seoul, Korea. First, taxis show the highest elasticity for waiting time. The shorter waiting time would significantly improve consumers’ preference. As consumers become more familiar with use of the smartphone, their preference for a taxi is lower. Thus, it is necessary to introduce various taxi services linked to smartphones, such as e-hailing. The experience of being denied taxi service dramatically decreases consumers’ preference for taxis. Such illegal actions should be prohibited. Among the several latent aspects, consumers’ negative perception of service in vehicles is the most important factor in reducing their preference for taxis. Thus, taxi service must be improved if taxis are to survive