Learning market prices in real-time supply chain management

This paper proposes a model for dynamic pricing that combines knowledge of production capacity and existing commitments, reasoning about uncertainty and learning of market conditions in an attempt to optimise expected profits. In particular, the market conditions are represented as a set of probabilities over the success rate of product prices, and those prices are learned online as the market develops. The dynamic pricing model is integrated into a real-time supply chain management agent using the Trading Agent Competition Supply Chain Management game as a test framework. We evaluate the agent experimentally in competition with other supply chain agents, and demonstrate the benefits of incorporating more market data into the dynamic pricing mechanism.     

维吾尔语词首音节元音声学分析

该文利用“维吾尔语语音声学参数数据库”,统计分析和归纳了维吾尔语词首音节元音的共振峰模式及其分布格局。声学元音图有多种画法,该文采用JOOS型声学元音图。这种元音图的特点是以F1为纵坐标,以F2为横坐标。这样绘制成的声学元音图与元音舌位图有很好的对应性。维语标准音词首音节中有[y, i, e, O, u, o, ;, A]等8个元音。舌位前后的分布特点是[u, o, A]为后元音,[y, i, e, O, ;]为前元音;开口度(舌位高低)分布特点是[y, i, u]为高元音,[e, O, o]为次高元音,[;]为次低元音, [A]为低元音.     

Cost-Based Filtering Techniques for Stochastic Inventory Control Under Service Level Constraints

This paper¹ considers a single product and a single stocking location production/inventory control problem given a non-stationary stochastic demand. Under a widely-used control policy for this type of inventory system, the objective is to find the optimal number of replenishments, their timings and their respective order-up-to-levels that meet customer demands to a required service level. We extend a known CP approach for this problem using three cost-based filtering methods. Our approach can solve to optimality instances of realistic size much more efficiently than previous approaches, often with no search effort at all. This work was supported by Science Foundation Ireland under Grant No. 03/CE3/I405 as part of the Centre for Telecommunications Value-Chain-Driven Research (CTVR) and Grant No. 00/PI.1/C075. ¹This paper is an extended version of [19].     

A compact hybrid feature vector for an accurate secondary structure prediction

Amino acid propensity score is one of the earliest successful methods used in protein secondary structure prediction. However, the score performs poorly on small-sized datasets and low-identity protein sequences. Based on current in silico method, secondary structure can be predicted from local folds or local protein structure. In biology, the evolution of secondary structure produces local protein structure with different lengths. To precisely predict secondary structures, we propose a derivative feature vector, DPS that utilizes the optimal length of the local protein structure. DPS is the unification of amino acid propensity score and dihedral angle score. This new feature vector is further normalized to level the edges. Prediction is performed by support vector machines (SVM) over the DPS feature vectors with class labels generated by secondary structure assignment method (SSAM) and secondary structure prediction method (SSPM). All experiments are carried out on RS126 sequences. The results from this proposed method also highlight the overall accuracy of our method compared to other state-of-the-art methods. The performance of our method was acceptable specifically in dealing with low number and low identity sequences.     

A controlled genetic programming approach for the deceptive domain

Traditional genetic programming (GP) randomly combines subtrees by applying crossover. There is a growing interest in methods that can control such recombination operations in order to achieve faster convergence. In this paper, a new approach is presented for guiding the recombination process for genetic programming. The method is based on extracting the global information of the promising solutions that appear during the genetic search. The aim is to use this information to control the crossover operation afterwards. A separate control module is used to process the collected information. This module guides the search process by sending feedback to the genetic engine about the consequences of possible recombination alternatives.     

Modelling and solving English Peg Solitaire

Peg Solitaire is a well known puzzle, which can prove difficult despite its simple rules. Pegs are arranged on a board such that at least one ‘hole’ remains. By making draughts/checkers-like moves, pegs are gradually removed until no further moves are possible or some goal configuration is achieved. This paper considers the English variant, consisting of a board in a cross shape with 33 holes. Modelling Peg Solitaire via constraint or integer programming techniques presents a considerable challenge and is examined in detail. The merits of the resulting models are discussed and they are compared empirically. The sequential nature of the puzzle naturally conforms to a planning problem, hence we also present an experimental comparison with several leading AI planning systems. Other variants of the puzzle, such as ‘Fool's Solitaire’ and ‘Long-hop’ Solitaire are also considered.     

Preparation of dye sensitized titanium oxide nanoparticles for solar cell applications

A new method for synthesis of titanium dioxide (TiO₂)-dye nanoparticles is reported. TiO₂ nanocrystals were obtained at 150 and 200 °C by using chemically bonded TiO₂-sensitizer dye as a precursor. Titanium tetraisopropoxide was first modified with a dye molecule and then precipitated by dropping into acidic water. A strongly colored precipitate was obtained. Hydrothermal growth of a colloidal solution was carried out in a Teflon-lined stainless steel autoclave. Dye sensitized solar cell efficiencies obtained were comparable and fill factor values were close to the analogous cells prepared by the use of conventional TiO₂ paste techniques. This method allows the use of different substrates together with nanocrystalline TiO₂ for many technological applications.     

Dual responsive wool fabric by cellulose nanowhisker reinforced shape memory polyurethane

Shape memory wool fabrics having both temperature and moisture responsiveness were fabricated by a functional nanocomposite treatment comprising of shape memory polyurethane (SMPU) and cellulose nanowhisker (CNW). Water vapor permeability and sweat absorption properties were investigated under different temperature or relative humidity values to test smart comfort capabilities of the treated fabrics. Besides, felting shrinkage and weight loss of the fabrics after repeated washing cycles were investigated for end use performance. It was found out that the wool fabrics functionalized by nanocomposite treatments exhibited dynamic breathability and sweat absorption changing with temperature and relative humidity of body or environment. Moreover, nanocomposite application enhanced rigidity, tear strength, anti-felting and weight loss performances of the wool fabric. 20 wt% CNW concentration can be suggested for thermal comfort, mechanical and end use performance enhancements to obtain smart garments having dynamic responsiveness to both body physiological and environmental changes. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 137, 48674.     

Inflammation in the Human Periodontium Induces Downregulation of the α1- and β1-Subunits of the sGC in Cementoclasts

Nitric oxide (NO) binds to soluble guanylyl cyclase (sGC), activates it in a reduced oxidized heme iron state, and generates cyclic Guanosine Monophosphate (cGMP), which results in vasodilatation and inhibition of osteoclast activity. In inflammation, sGC is oxidized and becomes insensitive to NO. NO- and heme-independent activation of sGC requires protein expression of the α₁- and β₁-subunits. Inflammation of the periodontium induces the resorption of cementum by cementoclasts and the resorption of the alveolar bone by osteoclasts, which can lead to tooth loss. As the presence of sGC in cementoclasts is unknown, we investigated the α₁- and β₁-subunits of sGC in cementoclasts of healthy and inflamed human periodontium using double immunostaining for CD68 and cathepsin K and compared the findings with those of osteoclasts from the same sections. In comparison to cementoclasts in the healthy periodontium, cementoclasts under inflammatory conditions showed a decreased staining intensity for both α₁- and β₁-subunits of sGC, indicating reduced protein expression of these subunits. Therefore, pharmacological activation of sGC in inflamed periodontal tissues in an NO- and heme-independent manner could be considered as a new treatment strategy to inhibit cementum resorption.