The Complexity of SORE-definability Problems

Single occurrence regular expressions (SORE) are a special kind of deterministic regular expressions, which are extensively used in the schema languages DTD and XSD for XML documents. In this paper, with motivations from the simplification of XML schemas, we consider the SORE-definability problem: Given a regular expression, decide whether it has an equivalent SORE. We investigate extensively the complexity of the SORE-definability problem: We consider both (standard) regular expressions and regular expressions with counting, and distinguish between the alphabets of size at least two and unary alphabets. In all cases, we obtain tight complexity bounds. In addition, we consider another variant of this problem, the bounded SORE-definability problem, which is to decide, given a regular expression E and a number M (encoded in unary or binary), whether there is an SORE, which is equivalent to E on the set of words of length at most M. We show that in several cases, there is an exponential decrease in the complexity when switching from the SORE-definability problem to its bounded variant

Comparative Evaluation of the Antioxidant Capacities, Organic Acids, and Volatiles of Papaya Juices Fermented by Lactobacillus acidophilus

Fermentation of foods by lactic acid bacteria is a useful way to improve the nutritional value of foods. In this study, the health-promoting effects of fermented papaya juices by two species, Lactobacillus acidophilus and Lactobacillus plantarum, were determined. Changes in pH, reducing sugar, organic acids, and volatile compounds were determined, and the vitamin C, total phenolic content, and flavonoid and antioxidant capacities during the fermentation process were investigated. Juices fermented by Lactobacillus acidophilus and Lactobacillus plantarum had similar changes in pH and reducing sugar content during the 48 h fermentation period. Large amounts of aroma-associated compounds and organic acids were produced, especially lactic acid, which increased significantly (p<0.05) (543.18 mg/100 mL and 571.29 mg/100 mL, resp.), improving the quality of the beverage. In contrast, the production of four antioxidant capacities in the fermented papaya juices showed different trends after 48 hours’ fermentation by two bacteria. Lactobacillus plantarum generated better antioxidant activities compared to Lactobacillus acidophilus after 48 h of fermentation. These results indicate that fermentation of papaya juice can improve its utilization and nutritional effect

Fresh Multiple Access: A Unified Framework Based on Large Models and Mean-Field Approximations

Information freshness has attracted increasingly attention in the past decade as it plays a critical role in the emerging real-time applications. Age of information (AoI) holds the promise of effectively characterizing the information freshness, hence widely considered as a fundamental performance metric. However, in multiple-device scenarios, most existing works focus on the analysis and optimization of AoI based on queueing systems. The study for a unified approach for general multiple access control scheme in freshness-oriented scenarios remains open. In this paper, we take into consideration the combination of the fundamental freshness metric AoI and multiple access control schemes to achieve efficient cross-layer analysis and optimization in freshness-oriented scenarios, which is referred to as fresh multiple access. To this end, we build a unified framework with a discrete-time tandem queue model for fresh multiple access. The unified framework enables the analysis and optimization for general multiple access protocols in fresh multiple access. To handle the high dimension framework embedded in fresh multiple access, we introduce large model approaches for the Markov chain formulation in AoI oriented scenarios. Two typical AoI-based metric are studied including age of incorrect information (AoII) and peak AoII. Moreover, to address the computational complexity of the large model, we present mean-field approximations which significantly reduces the dimension of the Markov chain model by approximating the integral affect of massive devices in fresh multiple access.Comment: accepted by Journal of Communications and Network

An Algorithm for Cellular Reprogramming

The day we understand the time evolution of subcellular elements at a level of detail comparable to physical systems governed by Newton's laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology, providing data-guided frameworks that allow us to develop better predictions about and methods for control over specific biological processes and system-wide cell behavior. In this paper we describe an approach to optimizing the use of transcription factors in the context of cellular reprogramming. We construct an approximate model for the natural evolution of a synchronized population of fibroblasts, based on data obtained by sampling the expression of some 22,083 genes at several times along the cell cycle. (These data are based on a colony of cells that have been cell cycle synchronized) In order to arrive at a model of moderate complexity, we cluster gene expression based on the division of the genome into topologically associating domains (TADs) and then model the dynamics of the expression levels of the TADs. Based on this dynamical model and known bioinformatics, we develop a methodology for identifying the transcription factors that are the most likely to be effective toward a specific cellular reprogramming task. The approach used is based on a device commonly used in optimal control. From this data-guided methodology, we identify a number of validated transcription factors used in reprogramming and/or natural differentiation. Our findings highlight the immense potential of dynamical models models, mathematics, and data guided methodologies for improving methods for control over biological processes

Additive Manufacturing Of (MgCoNiCuZn)O High-entropy Oxide Using A 3D Extrusion Technique And Oxide Precursors

This report presents an additive manufacturing approach, for the first time, to producing high-entropy oxides (HEOs) using a 3D extrusion-based technique with oxide precursors. The precursors were prepared by a wet chemical method from sulfates. Additives were utilized to optimize the rheological properties of the printing inks with these precursors, and the properties of the printed HEOs were improved by increasing the solid content of the inks. When ink with a solid content of 78 wt% was used for printing, the resulting HEO exhibited a relative density of 92% and a high dielectric constant after undergoing pressure less sintering at 800 °C. Compared to traditional methods of manufacturing HEOs, the 3D extrusion technique is a very promising method for producing HEOs with complex geometries