An Agent Based Market Design Methodology for Combinatorial Auctions

Auction mechanisms have attracted a great deal of interest and have been used in diverse e-marketplaces. In particular, combinatorial auctions have the potential to play an important role in electronic transactions. Therefore, diverse combinatorial auction market types have been proposed to satisfy market needs. These combinatorial auction types have diverse market characteristics, which require an effective market design approach. This study proposes a comprehensive and systematic market design methodology for combinatorial auctions based on three phases: market architecture design, auction rule design, and winner determination design. A market architecture design is for designing market architecture types by Backward Chain Reasoning. Auction rules design is to design transaction rules for auctions. The specific auction process type is identified by the Backward Chain Reasoning process. Winner determination design is about determining the decision model for selecting optimal bids and auctioneers. Optimization models are identified by Forward Chain Reasoning. Also, we propose an agent based combinatorial auction market design system using Backward and Forward Chain Reasoning. Then we illustrate a design process for the general n-bilateral combinatorial auction market. This study serves as a guideline for practical implementation of combinatorial auction markets design.Combinatorial Auction, Market Design Methodology, Market Architecture Design, Auction Rule Design, Winner Determination Design, Agent-Based System

Effect of Ceramic Dust as Partial Replacement of Cement on Lightweight Foamed Concrete

Disposal of waste into the landfill causes a severe impact on the environment. One of the waste products is ceramic waste. Ceramic waste has some excellent properties in its durability, hardness, and highly resistant to biological, chemical, and physical degradation forces. These excellent properties of the ceramic waste may make it suitable to be used in concrete. This study investigates the effect on the compressive strength of lightweight foamed concrete with different percentage of ceramic dust replacement level towards the cement and three different levels of water-cement ratio. 0%, 5%, 15%, and 25% of replacement level with 0.52, 0.56, and 0.60 water-cement ratios respectively for each replacement level was used as the parameter to investigate the fresh properties, and strength performance of lightweight foamed concrete. The stability and consistency of every mix are studied as well. From this study, it was observed that the incorporation of ceramic waste dust partially replaced the cement did not affect on the fresh properties of the foamed concrete. However, the compressive strength of foamed concrete affected by ceramic waste dust partially replaced the cement

Risk factors for pulmonary tuberculosis in patients with chronic obstructive airway disease in Taiwan: a nationwide cohort study

BACKGROUND: An association between chronic obstructive pulmonary disease (COPD) and tuberculosis (TB) has been described, mainly due to smoking and corticosteroid use. Whether inhaled corticosteroid (ICS) therapy is associated with an increased risk of TB remains unclear. METHODS: We selected COPD cases by using six diagnostic scenarios and control subjects from a nationwide health insurance database, and applied time-dependent Cox regression analysis to identify the risk factors for TB. RESULTS: Among 1,000,000 beneficiaries, 23,594 COPD cases and 47,188 non-COPD control subjects were selected. Cox regression analysis revealed that age, male gender, diabetes mellitus, end-stage renal disease, and cirrhosis, as well as COPD (hazard ratio = 2.468 [2.205–2.762]) were independent risk factors for TB. Among the COPD cases, those who developed TB received more oral corticosteroids and oral β-agonists. Time-dependent Cox regression analysis revealed that age, male gender, diabetes mellitus, low income, oral corticosteroid dose, and oral β-agonist dose, but not ICS dose, were independent risk factors for TB. The identified risk factors and their hazard ratios were similar among the COPD cases selected using different scenarios. CONCLUSION: Keeping a high suspicion and regularly monitoring for the development of pulmonary TB in COPD patients are necessary, especially for those receiving higher doses of oral corticosteroids and other COPD medications. Although ICS therapy has been shown to predispose COPD patients to pneumonia in large randomized clinical trials, it does not increase the risk of TB in real world practice

The genetic diversity among strawberry breeding resources based on SSRs

Cultivated strawberry (Fragaria × ananassa Duch.) is a high value horticultural crop. In this study, the genetic diversity of 160 strawberry accessions was determined using five highly polymorphic simple sequence repeat (SSR) markers. Sixty different alleles were identified, with allele frequencies in the range of 0.006 to1. Similarity scores were in the range of 0.034 to 0.963 (average: 0.507). The accessions were categorized into five groups. Group 1 contained two diploid Fragaria vesca species and one unknown accession. Group 2 contained one accession (F x ananassa). Group 3 contained 20 F × ananassa accessions and six unknown accessions. Group 4 contained 48 F. × ananassa accessions, one octaploid Fragaria chiloensis species, and six unknown accessions while Group 5 contained 69 F. × ananassa accessions and six unknown accessions. Accessions within a pedigree were frequently grouped together. A total of 30 novel accessions were categorized alongside existing accessions. These results will allow breeders to develop strategies which incorporate more genetic diversity into new cultivars

Autosomal dominant transmission of complicated hereditary spastic paraplegia due to a dominant negative mutation of KIF1A, SPG30 gene.

KIF1A is a brain-specific anterograde motor protein that transports cargoes towards the plus-ends of microtubules. Many variants of the KIF1A gene have been associated with neurodegenerative diseases and developmental delay. Homozygous mutations of KIF1A have been identified in a recessive subtype of hereditary spastic paraplegia (HSP), SPG30. In addition, KIF1A mutations have been found in pure HSP with autosomal dominant inheritance. Here we report the first case of familial complicated HSP with a KIF1A mutation transmitted in autosomal dominant inheritance. A heterozygous p.T258M mutation in KIF1A was found in a Korean family through targeted exome sequencing. They displayed phenotypes of mild intellectual disability with language delay, epilepsy, optic nerve atrophy, thinning of corpus callosum, periventricular white matter lesion, and microcephaly. A structural modeling revealed that the p.T258M mutation disrupted the binding of KIF1A motor domain to microtubules and its movement along microtubules. Assays of peripheral accumulation and proximal distribution of KIF1A motor indicated that the KIF1A motor domain with p.T258M mutation has reduced motor activity and exerts a dominant negative effect on wild-type KIF1A. These results suggest that the p.T258M mutation suppresses KIF1A motor activity and induces complicated HSP accompanying intellectual disability transmitted in autosomal dominant inheritance. © The Author(s) 20171

Intracellular Membrane Association of the Aplysia cAMP Phosphodiesterase Long and Short Forms via Different Targeting Mechanisms

Phosphodiesterases (PDEs) play key roles in cAMP compartmentalization, which is required for intracellular signaling processes, through specific subcellular targeting. Previously, we showed that the long and short forms of Aplysia PDE4 (ApPDE4), which are localized to the membranes of distinct subcellular organelles, play key roles in 5-hydroxytryptamineinduced synaptic facilitation in Aplysia sensory and motor synapses. However, the molecular mechanism of the isoform-specific distinct membrane targeting was not clear. In this study, we further investigated the molecular mechanism of the membrane targeting of the ApPDE4 long and short forms. We found that the membrane targeting of the long form was mediated by hydrophobic interactions, mainly via 16 amino acids at the N-terminal region, whereas the short form was targeted solely to the plasma membrane, mainly by nonspecific electrostatic interactions between theirNtermini and the negatively charged lipids such as the phosphatidylinositol polyphosphates PI4P and PI(4,5)P<inf>2</inf>, which are embedded in the inner leaflet of the plasma membrane. Moreover, oligomerization of the long or short form by interaction of their respective upstream conserved region domains, UCR1 and UCR2, enhanced their plasma membrane targeting. These results suggest that the long and short forms of ApPDE4 are distinctly targeted to intracellular membranes through their direct association with the membranes via hydrophobic and electrostatic interactions, respectively. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.1

Deep autoencoder-powered pattern identification of sleep disturbance using multi-site cross-sectional survey data

Pattern identification (PI) is a diagnostic method used in Traditional East Asian medicine (TEAM) to select appropriate and personalized acupuncture points and herbal medicines for individual patients. Developing a reproducible PI model using clinical information is important as it would reflect the actual clinical setting and improve the effectiveness of TEAM treatment. In this paper, we suggest a novel deep learning-based PI model with feature extraction using a deep autoencoder and k-means clustering through a cross-sectional study of sleep disturbance patient data. The data were obtained from an anonymous electronic survey in the Republic of Korea Army (ROKA) members from August 16, 2021, to September 20, 2021. The survey instrument consisted of six sections: demographics, medical history, military duty, sleep-related assessments (Pittsburgh sleep quality index (PSQI), Berlin questionnaire, and sleeping environment), diet/nutrition-related assessments [dietary habit survey questionnaire and nutrition quotient (NQ)], and gastrointestinal-related assessments [gastrointestinal symptom rating scale (GSRS) and Bristol stool scale]. Principal component analysis (PCA) and a deep autoencoder were used to extract features, which were then clustered using the k-means clustering method. The Calinski-Harabasz index, silhouette coefficient, and within-cluster sum of squares were used for internal cluster validation and the final PSQI, Berlin questionnaire, GSRS, and NQ scores were used for external cluster validation. One-way analysis of variance followed by the Tukey test and chi-squared test were used for between-cluster comparisons. Among 4,869 survey responders, 2,579 patients with sleep disturbances were obtained after filtering using a PSQI score of >5. When comparing clustering performance using raw data and extracted features by PCA and the deep autoencoder, the best feature extraction method for clustering was the deep autoencoder (16 nodes for the first and third hidden layers, and two nodes for the second hidden layer). Our model could cluster three different PI types because the optimal number of clusters was determined to be three via the elbow method. After external cluster validation, three PI types were differentiated by changes in sleep quality, dietary habits, and concomitant gastrointestinal symptoms. This model may be applied to the development of artificial intelligence-based clinical decision support systems through electronic medical records and clinical trial protocols for evaluating the effectiveness of TEAM treatment

DeepParcellation: A novel deep learning method for robust brain magnetic resonance imaging parcellation in older East Asians

Accurate parcellation of cortical regions is crucial for distinguishing morphometric changes in aged brains, particularly in degenerative brain diseases. Normal aging and neurodegeneration precipitate brain structural changes, leading to distinct tissue contrast and shape in people aged >60 years. Manual parcellation by trained radiologists can yield a highly accurate outline of the brain; however, analyzing large datasets is laborious and expensive. Alternatively, newly-developed computational models can quickly and accurately conduct brain parcellation, although thus far only for the brains of Caucasian individuals. To develop a computational model for the brain parcellation of older East Asians, we trained magnetic resonance images of dimensions 256 × 256 × 256 on 5,035 brains of older East Asians (Gwangju Alzheimer’s and Related Dementia) and 2,535 brains of Caucasians. The novel N-way strategy combining three memory reduction techniques inception blocks, dilated convolutions, and attention gates was adopted for our model to overcome the intrinsic memory requirement problem. Our method proved to be compatible with the commonly used parcellation model for Caucasians and showed higher similarity and robust reliability in older aged and East Asian groups. In addition, several brain regions showing the superiority of the parcellation suggest that DeepParcellation has a great potential for applications in neurodegenerative diseases such as Alzheimer’s disease