Estimation of Q-matrix for DINA Model Using the Constrained Generalized DINA Framework

The research of cognitive diagnostic models (CDMs) is becoming an important field of psychometrics. Instead of assigning one score, CDMs provide attribute profiles to indicate the mastering status of concepts or skills for the examinees. This would make the test result more informative. The implementation of many CDMs relies on the existing item-to-attribute relationship, which means that we need to know the concepts or skills each item requires. The relationships between the items and attributes could be summarized into the Q-matrix. Misspecification of the Q-matrix will lead to incorrect attribute profile. The Q-matrix can be designed by expert judgement, but it is possible that such practice can be subjective. There are previous researches about the Q-matrix estimation. This study proposes an estimation method for one of the most parsimonious CDMs, the DINA model. The method estimates the Q-matrix for DINA model by setting constraints on the generalized DINA model. In the simulation study, the results showed that the estimated Q-matrix fit better the empirical fraction subtraction data than the expert-design Q-matrix. We also show that the proposed method may still be applicable when the constraints were relaxed

Dynamic Dictionary with Subconstant Wasted Bits per Key

Dictionaries have been one of the central questions in data structures. A dictionary data structure maintains a set of key-value pairs under insertions and deletions such that given a query key, the data structure efficiently returns its value. The state-of-the-art dictionaries [Bender, Farach-Colton, Kuszmaul, Kuszmaul, Liu 2022] store $n$ key-value pairs with only $O(n \log^{(k)} n)$ bits of redundancy, and support all operations in $O(k)$ time, for $k \leq \log^* n$. It was recently shown to be optimal [Li, Liang, Yu, Zhou 2023b]. In this paper, we study the regime where the redundant bits is $R=o(n)$, and show that when $R$ is at least $n/\text{poly}\log n$, all operations can be supported in $O(\log^* n + \log (n/R))$ time, matching the lower bound in this regime [Li, Liang, Yu, Zhou 2023b]. We present two data structures based on which range $R$ is in. The data structure for $R<n/\log^{0.1} n$ utilizes a generalization of adapters studied in [Berger, Kuszmaul, Polak, Tidor, Wein 2022] and [Li, Liang, Yu, Zhou 2023a]. The data structure for $R \geq n/\log^{0.1} n$ is based on recursively hashing into buckets with logarithmic sizes.Comment: 46 pages; SODA 202

Dynamic "Succincter"

Augmented B-trees (aB-trees) are a broad class of data structures. The seminal work "succincter" by Patrascu showed that any aB-tree can be stored using only two bits of redundancy, while supporting queries to the tree in time proportional to its depth. It has been a versatile building block for constructing succinct data structures, including rank/select data structures, dictionaries, locally decodable arithmetic coding, storing balanced parenthesis, etc. In this paper, we show how to "dynamize" an aB-tree. Our main result is the design of dynamic aB-trees (daB-trees) with branching factor two using only three bits of redundancy (with the help of lookup tables that are of negligible size in applications), while supporting updates and queries in time polynomial in its depth. As an application, we present a dynamic rank/select data structure for $n$-bit arrays, also known as a dynamic fully indexable dictionary (FID). It supports updates and queries in $O(\log n/\log\log n)$ time, and when the array has $m$ ones, the data structure occupies $$\log\binom{n}{m} + O(n/2^{\log^{0.199}n})$$ bits. Note that the update and query times are optimal even without space constraints due to a lower bound by Fredman and Saks. Prior to our work, no dynamic FID with near-optimal update and query times and redundancy $o(n/\log n)$ was known. We further show that a dynamic sequence supporting insertions, deletions and rank/select queries can be maintained in (optimal) $O(\log n/\log\log n)$ time and with $O(n \cdot \text{poly}\log\log n/\log^2 n)$ bits of redundancy.Comment: 33 pages, 1 figure; in FOCS 202

Tight Cell-Probe Lower Bounds for Dynamic Succinct Dictionaries

A dictionary data structure maintains a set of at most $n$ keys from the universe $[U]$ under key insertions and deletions, such that given a query $x \in [U]$, it returns if $x$ is in the set. Some variants also store values associated to the keys such that given a query $x$, the value associated to $x$ is returned when $x$ is in the set. This fundamental data structure problem has been studied for six decades since the introduction of hash tables in 1953. A hash table occupies $O(n\log U)$ bits of space with constant time per operation in expectation. There has been a vast literature on improving its time and space usage. The state-of-the-art dictionary by Bender, Farach-Colton, Kuszmaul, Kuszmaul and Liu [BFCK+22] has space consumption close to the information-theoretic optimum, using a total of $$\log\binom{U}{n}+O(n\log^{(k)} n)$$ bits, while supporting all operations in $O(k)$ time, for any parameter $k \leq \log^* n$. The term $O(\log^{(k)} n) = O(\underbrace{\log\cdots\log}_k n)$ is referred to as the wasted bits per key. In this paper, we prove a matching cell-probe lower bound: For $U=n^{1+\Theta(1)}$, any dictionary with $O(\log^{(k)} n)$ wasted bits per key must have expected operational time $\Omega(k)$, in the cell-probe model with word-size $w=\Theta(\log U)$. Furthermore, if a dictionary stores values of $\Theta(\log U)$ bits, we show that regardless of the query time, it must have $\Omega(k)$ expected update time. It is worth noting that this is the first cell-probe lower bound on the trade-off between space and update time for general data structures.Comment: 35 page

A Supporting System for Knowledge Creation Process

A knowledge management system, Knowledge Management System for Scientific Research Group (KMSSRG) is designed to facilitate knowledge creation within a scientific research group. Implementation issues of such a system are analyzed and discussed in this paper. The main feature of the KMSSRG is the support of Internal Knowledge Evolution Network (IKEN). We developed the IKEN by (1) using Ikujiro Nonaka’s SECI model to identify core sub-processes and related knowledge that are keys to knowledge creation, and (2) analyzing carefully the knowledge creation process for both individuals and teams. As a result, IKEN is a directed network that maps knowledge (both implicit and explicit knowledge) fragments created by different team members in various research activities. Context reference relationships among these knowledge fragments can also be represented

Seasonality in the cross section of stock returns: Advanced markets versus emerging markets

We extend the studies of stock return seasonality by Heston and Sadka (2008, 2010) to a comprehensive sample of 42 international markets, including 21 advanced markets and 21 emerging markets. The empirical results show a large variation in stock seasonality across markets and suggest that this phenomenon exists primarily in advanced markets. A winner-loser portfolio approach shows that return seasonality is economically significant in advanced markets but not in emerging markets. We conduct statistical, rational and behavioral analyses to explore the potential reasons for the seasonality observed in advanced markets and find that regression bias, the January effect, and the Fama-French-Carhart type risk premium all can partially explain this seasonality difference

MOF Acetylates the Histone Demethylase LSD1 to Suppress Epithelial-to-Mesenchymal Transition.

The histone demethylase LSD1 facilitates epithelial-to-mesenchymal transition (EMT) and tumor progression by repressing epithelial marker expression. However, little is known about how its function may be modulated. Here, we report that LSD1 is acetylated in epithelial but not mesenchymal cells. Acetylation of LSD1 reduces its association with nucleosomes, thus increasing histone H3K4 methylation at its target genes and activating transcription. The MOF acetyltransferase interacts with LSD1 and is responsible for its acetylation. MOF is preferentially expressed in epithelial cells and is downregulated by EMT-inducing signals. Expression of exogenous MOF impedes LSD1 binding to epithelial gene promoters and histone demethylation, thereby suppressing EMT and tumor invasion. Conversely, MOF depletion enhances EMT and tumor metastasis. In human cancer, high MOF expression correlates with epithelial markers and a favorable prognosis. These findings provide insight into the regulation of LSD1 and EMT and identify MOF as a critical suppressor of EMT and tumor progression

MOF Acetylates the Histone Demethylase LSD1 to Suppress Epithelial-to-Mesenchymal Transition

SummaryThe histone demethylase LSD1 facilitates epithelial-to-mesenchymal transition (EMT) and tumor progression by repressing epithelial marker expression. However, little is known about how its function may be modulated. Here, we report that LSD1 is acetylated in epithelial but not mesenchymal cells. Acetylation of LSD1 reduces its association with nucleosomes, thus increasing histone H3K4 methylation at its target genes and activating transcription. The MOF acetyltransferase interacts with LSD1 and is responsible for its acetylation. MOF is preferentially expressed in epithelial cells and is downregulated by EMT-inducing signals. Expression of exogenous MOF impedes LSD1 binding to epithelial gene promoters and histone demethylation, thereby suppressing EMT and tumor invasion. Conversely, MOF depletion enhances EMT and tumor metastasis. In human cancer, high MOF expression correlates with epithelial markers and a favorable prognosis. These findings provide insight into the regulation of LSD1 and EMT and identify MOF as a critical suppressor of EMT and tumor progression

Controllable Synthesis of Na3V2(PO4)3/C Nanofibers as Cathode Material for Sodium-Ion Batteries by Electrostatic Spinning

Na3V2(PO4)3/C nanofibers are prepared by a pre-reduction assisted electrospinning method. In order to maintain the perfect fibrous architecture of the Na3V2(PO4)3/C samples after calcining, a series of heat treatment parameters are studied in detail. It is found that the heat treatment process shows important influence on the morphology and electrochemical performance of Na3V2(PO4)3/C composite nanofibers. Under the calcining conditions of 800°C for 10 h with a heating rate of 2.5°C min−1, the well-crystallized uniform Na3V2(PO4)3/C nanofibers with excellent electrochemical performances are successfully obtained. The initial discharge specific capacities of the nanofibers at 0.05, 1, and 10C are 114.0, 106.0, and 77.9 mAh g−1, respectively. The capacity retention still remains 97.0% after 100 cycles at 0.05C. This smooth, uniform, and continuous Na3V2(PO4)3/C composite nanofibers prepared by simple electrospinning method, is expected to be a superior cathode material for sodium-ion batteries

Cellular Based Small Unmanned Aircraft Systems (sUAS) MIMO Communications

The use of remotely piloted unmanned aircraft systems/vehicles (UAS/UAV or drones) increases dramatically in recent years. This paper discusses the use of multiple-input and multiple-output (MIMO) technologies in cellular (i.e., LTE) based small UAS (sUAS) communications. More specifically, we will first provide background information about this work, followed by a review of state-of-the-art. Then, we will discuss the benefits of MIMO technologies and propose practical MIMO configurations (e.g., the type, size and number of antennas) that are suitable for NASA's sUAS research and operations. Finally, the design tradeoff among multiplexing, diversity, and interference/jamming cancellation will also be discussed