Processing Optimal Sequenced Route Queries Using Voronoi Diagrams

The Optimal Sequenced Route (OSR) query strives to find a route of minimum length starting from a given source location and passing through a number of typed locations in a specific sequence imposed on the types of the locations. In this paper, we propose a pre-computation approach to OSR query in both vector and metric spaces. We exploit the geometric properties of the solution space and theoretically prove its relation to additively weighted Voronoi diagrams. Our approach recursively accesses these diagrams to incrementally build the OSR. Introducing the analogous diagrams for the space of road networks, we show that our approach is also efficiently applicable to this metric space. Our experimental results verify that our pre-computation approach outperforms the previous index-based approaches in terms of query response time. This research has been funded in part by NSF grants EEC-9529152 (IMSC ERC), IIS-0238560 (PECASE), IIS-0324955 (ITR), IIS-0534761, and unrestricted cash gifts from Google and Microsoft. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF.

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A Wavelet-ANFIS Hybrid Model for Groundwater Level Forecasting for Different Prediction Periods

Artificial neural network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have an extensive range of applications in water resources management. Wavelet transformation as a preprocessing approach can improve the ability of a forecasting model by capturing useful information on various resolution levels. The objective of this research is to compare several data-driven models for forecasting groundwater level for different prediction periods. In this study, a number of model structures for Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Wavelet-ANN and Wavelet-ANFIS models have been compared to evaluate their performances to forecast groundwater level with 1, 2, 3 and 4 months ahead under two case studies in two sub-basins. It was demonstrated that wavelet transform can improve accuracy of groundwater level forecasting. It has been also shown that the forecasts made by Wavelet-ANFIS models are more accurate than those by ANN, ANFIS and Wavelet-ANN models. This study confirms that the optimum number of neurons in the hidden layer cannot be always determined by using a specific formula but trial-and-error method. The decomposition level in wavelet transform should be determined according to the periodicity and seasonality of data series. The prediction of these models is more accurate for 1 and 2 months ahead (for example RMSE?=?0.12, E?=?0.93 and R ²?=?0.99 for wavelet-ANFIS model for 1 month ahead) than for 3 and 4 months ahead (for example RMSE?=?2.07, E?=?0.63 and R ²?=?0.91 for wavelet-ANFIS model for 4 months ahead).     

Stores clustering using a data mining approach for distributing automotive spare-parts to reduce transportation costs

Clustering of retail stores in a distribution network with specific geographical limits plays an important and effective role in distribution and transportation costs reduction. In this paper, the relevant data and information for an established automotive spare-parts distribution and after-sales services company (ISACO) for a 3-year period have been analyzed. With respect to the diversity and lot size of the available information such as stores location, order, goods, transportation vehicles and road and traffic information, three effecting factors with specific weights have been defined for the similarity function: 1. Euclidean distance, 2. Lot size 3. Order concurrency. Based on these three factors, the similarity function has been examined through 5 steps using the Association Rules principles, where the clustering of the stores is performed using k-means algorithm and similar stores are allocated to the clusters. These steps include: 1. Similarity function based on the Euclidean distances, 2. Similarity function based on the order concurrency, 3. Similarity function based on the combination of the order concurrency and lot size, 4. Similarity function based on the combination of these three factors and 5. Improved similarity function. The above mentioned clustering operation for each 5 cases addressed in data mining have been carried out using R software and the improved combinational function has been chosen as the optimal clustering function. Then, trend of each retail store have been analyzed using the improved combinational function and along with determining the priority of the depot center establishment for every cluster, the appropriate distribution policies have been formulated for every cluster. The obtained results of this study indicate a significant cost reduction (32%) in automotive spare-parts distribution and transportation costs.     

Robust matrix 𝒟U‐stability analysis

In this paper, the problem of robust matrix root‐clustering is addressed. The studied matrices are subject to both polytopic and unstructured uncertainties. An original point is the large choice of clustering regions enabled by the proposed approach since these regions can be unions of possibly disjoint and non‐symmetric subregions of the complex plane. The precise purpose is, considering a specified polytope, to determine the greatest robustness bound on the unstructured uncertainty such that robust matrix root‐clustering is ensured. To reduce conservatism in the derivation of the bound, the reasoning relies on a framework based upon parameter‐dependent Lyapunov functions. The bound value is computed by solving an ?? ?? ? problem. Copyright © 2003 John Wiley & Sons, Ltd.     

Insight into the Impact of Oxidative Stress on the Barrier Properties of Lipid Bilayer Models

As a new field of oxidative stress-based therapy, cold physical plasma is a promising tool for several biomedical applications due to its potential to create a broad diversity of reactive oxygen and nitrogen species (RONS). Although proposed, the impact of plasma-derived RONS on the cell membrane lipids and properties is not fully understood. For this purpose, the changes in the lipid bilayer functionality under oxidative stress generated by an argon plasma jet (kINPen) were investigated by electrochemical techniques. In addition, liquid chromatography-tandem mass spectrometry was employed to analyze the plasma-induced modifications on the model lipids. Various asymmetric bilayers mimicking the structure and properties of the erythrocyte cell membrane were transferred onto a gold electrode surface by Langmuir-Blodgett/Langmuir-Schaefer deposition techniques. A strong impact of cholesterol on membrane permeabilization by plasma-derived species was revealed. Moreover, the maintenance of the barrier properties is influenced by the chemical composition of the head group. Mainly the head group size and its hydrogen bonding capacities are relevant, and phosphatidylcholines are significantly more susceptible than phosphatidylserines and other lipid classes, underlining the high relevance of this lipid class in membrane dynamics and cell physiology.     

Modeling metallurgical responses of coal Tri-Flo separators by a novel BNN:a "Conscious-Lab" development

Tri-flo cyclone,as a dense-medium separation device,is one of the most typical environmentally friendly industrial techniques in the coal washery plants.Surpris...     

Fluid Flow and Mixing in Non-Isothermal Water Model of Continuous Casting Tundish

Fluid flow and mixing of molten steel in a twin-slab-strand continuous casting tundish were investigated using a mixing model under non-isothermal conditions.This model led to a set of ordinary differential equations that were solved with a Runge-Kutta algorithm.Steady state water modeling was carried out under non-isothermal conditions.Experimental data obtained from the water model were used to calibrate the mixing model.Owing to the presence of a mixed convection in the non-isothermal conditions,a channelizing flow would be created in the fluid inside the tundish.A mixing model was designed that was capable of predicting RTD（residence time distribution）curves for different cases in non-isothermal conditions.The relationship between RTD parameters and the Tu（tundish Richardson number）was obtained for various cases under non-isothermal conditions.The results show that the RTD parameters were completely different under isothermal and non-isothermal conditions.The comparison of the RTD curves between the isothermal and non-isothermal conditions presents that the extent of mixing in the tundish in non-isothermal conditions is lower than the mixing extent in isothermal conditions.     

Camelid Single-Domain Antibodies: Promises and Challenges as Lifesaving Treatments

Since the discovery of camelid heavy-chain antibodies in 1993, there has been tremendous excitement for these antibody domains (VHHs/sdAbs/nanobodies) as research tools, diagnostics, and therapeutics. Commercially, several patents were granted to pioneering research groups in Belgium and the Netherlands between 1996–2001. Ablynx was established in 2001 with the aim of exploring the therapeutic applications and development of nanobody drugs. Extensive efforts over two decades at Ablynx led to the first approved nanobody drug, caplacizumab (Cablivi) by the EMA and FDA (2018–2019) for the treatment of rare blood clotting disorders in adults with acquired thrombotic thrombocytopenic purpura (TPP). The relatively long development time between camelid sdAb discovery and their entry into the market reflects the novelty of the approach, together with intellectual property restrictions and freedom-to-operate issues. The approval of the first sdAb drug, together with the expiration of key patents, may open a new horizon for the emergence of camelid sdAbs as mainstream biotherapeutics in the years to come. It remains to be seen if nanobody-based drugs will be cheaper than traditional antibodies. In this review, I provide critical perspectives on camelid sdAbs and present the promises and challenges to their widespread adoption as diagnostic and therapeutic agents.