Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanism underlying histamine-induced intracellular Ca2+ movement in PC3 human prostate cancer cells.

The effect of histamine on intracellular free Ca2+ levels ([Ca2+]i) in PC3 human prostate cancer cells and the underlying mechanism were evaluated using fura-2 as a Ca2+ dye. Histamine at concentrations between 0.1 and 50 microM increased [Ca2+]i in a concentration-dependent manner with an EC50 value of 1 microM. The [Ca2+]i response comprised an initial rise and a slow decay, which returned to baseline within 3 min. Extracellular Ca2+ removal inhibited 50% of the [Ca2+]i signal. In the absence of extracellular Ca2+, after cells were treated with 1 microM thapsigargin (an endoplasmic reticulum Ca2+ pump inhibitor), 10 microM histamine did not increase [Ca2+]i. After pretreatment with 10 microM histamine in a Ca2+-free medium for several minutes, addition of 3 mM Ca2+ induced [Ca2+]i increases. Histamine (10 microM)-induced intracellular Ca2+ release was abolished by inhibiting phospholipase C with 2 microM 1-(6-((17 beta-3- methoxyestra-1,3,5(10)-trien-17-yl)amino)hexyl)-1H-pyrrole-2,5-dione (U73122), and by 10 microM pyrilamine but was not altered by 50 microM cimetidine. Collectively, the present study shows that histamine induced [Ca2+]i transients in PC3 human prostate cancer cells by stimulating H1 histamine receptors leading to Ca2+ release from the endoplasmic reticulum in an inositol 1,4,5-trisphosphate-dependent manner, and by inducing Ca2+ entry.
Isolation and characterization of a Drosophila gene essential for early embryonic development and formation of cortical cleavage furrows

We have isolated a new female sterile mutant from Drosophila melanogaster, which arrests the embryonic development during the transition from syncytial to cellular blastoderm. Cytological analysis of the mutant embryos indicates that pseudocleavage furrows in the syncytial blastoderm are abnormal but not completely disrupted. However, cleavage furrows during cellularization are totally disorganized, and no embryos can develop beyond this stage. Consistent with this observation, the expression of this gene peaks around the cellular blastoderm and not in any later developmental stages. Based on immunofluorescence experiments, the protein product of this gene is localized in both pseudocleavage furrows at the syncytial blastoderm and in the cleavage furrows during the cellularization stage. Sequence homology analysis demonstrates a modest, but statistically significant, similarity of this protein with the carboxyl-terminal domains of dystrophin and a family of proteins collectively known as apodystrophins. It is possible that this protein may play an essential role in organizing and maintaining a specialized cytoskeletal structure, a function also suggested for dystrophin and apodystrophins.
Briefing: Water content determinations of peaty soils using the oven-drying method

In order to prevent possible charring, oxidation and (or) vaporization of substances other than the pore water, many researchers have adopted oven drying temperature (t) values in the range of 60–90°C for water content determinations on peat and other highly organic soils. This paper investigates the oven drying characteristics of six very different highly-decomposed peaty soils retrieved from south-west China for t values of 65°C, 85°C and 105°C. Based on the presented experimental data, it is concluded that the standardised t value of 105°C used for testing of inorganic soil is also appropriate (and preferable than using lower t values) for routine water content determinations on these soils, which is in line with the growing consensus formed by other researchers on this topic. Further, we recommend a wet specimen mass of approximately 50 g and a 24-h oven-drying period in performing the oven drying tests for t = 105°C. The paper also describes an existing approach for comparing and standardising water .
The Number of MCMC Draws Needed to Compute Bayesian Credible Bounds

ABSTRACT In the past 20 years, there has been a staggering increase in the use of Bayesian statistical inference, based on Markov chain Monte Carlo (MCMC) methods, to estimate model parameters and other quantities of interest. This trend exists in virtually all areas of engineering and science. In a typical application, researchers will report estimates of parametric functions (e.g., quantiles, probabilities, or predictions of future outcomes) and corresponding intervals from MCMC methods. One difficulty with the use of inferential methods based on Monte Carlo (MC) is that reported results may be inaccurate due to MC error. MC error, however, can be made arbitrarily small by increasing the number of MC draws. Most users of MCMC methods seem to use indirect diagnostics, trial-and-error, or guess-work to decide how long to run a MCMC algorithm and accuracy of MCMC output results is rarely reported. Unless careful analysis is done, reported numerical results may contain digits that are completely meaningless. In this article, we describe an algorithm to provide direct guidance on the number of MCMC draws needed to achieve a desired amount of precision (i.e., a specified number of accurate significant digits) for Bayesian credible interval endpoints.
Sequence Matching and Learning in Anomaly Detection for Computer Security

Two problems of importance in computer security are to 1) detect the presence of an intruder masquerading as the valid user and 2) detect the perpetration of abusive actions on the part of an otherwise innocuous user. We have developed an approach to these problems that examines sequences of user actions (UNIX commands) to classify behavior as normal or anomalous. In this paper we explore the matching function needed to compare a current behavioral sequence to a historical profile. We discuss the difficulties of performing matching in human-generated data and show that exact string matching is insufficient to this domain. We demonstrate a number of partial matching functions and examine their behavior on user command data. In particular, we explore two methods for weighting scores by adjacency of matches as well as two growth functions (polynomial and exponential) for scoring similarities. We find, empirically, that the optimal similarity measure is user dependant but that measures based on the assumption of causal linkage between user commands are superior for this domain.
Accelerated Invisalign treatment.

T two most important aspects of orthodontic treatment to patients are probably esthetics and speed. Lingual brackets and clear brackets have helped with the esthetic demands, but some patients want even less visible treatment modali­ ties. And while new wire and bracket technolo­ gies have reduced treatment times, many patients would like to have treatment be faster yet. During the past few years, two techniques have been introduced that promise to address both these concerns. This article will report on a treatment approach combining the two.
Orally administered fatty acids enhance anorectic potential but do not activate central fatty acid sensing in Senegalese sole post-larvae

ABSTRACT Studies in fish have reported the presence and function of fatty acid (FA)-sensing systems comparable in many aspects to those known in mammals. Such studies were carried out in juvenile and adult fish, but the presence of FA-sensing systems and control of food intake have never been evaluated in early life stages, despite the importance of establishing when appetite regulation becomes functional in larval fish. In this study, we aimed to elucidate the possible effects of different specific FAs on neural FA-sensing systems and neuropeptides involved in the control of food intake in Senegalese sole post-larvae. To achieve this, we orally administered post-larvae with different solutions containing pure FA – oleate (OA), linoleate (LA), α-linolenate (ALA) or eicosapentaenoate (EPA) – and evaluated changes in mRNA abundance of neuropeptides involved in the control of food intake and of transcripts related to putative FA-sensing systems, 3 and 6 h post-administration. The changes in neuropeptide gene expression were relatively consistent with the activation of anorectic pathways (enhanced cart4 and pomcb) and a decrease in orexigenic factors (npy) following intake of FA. Even though there were a few differences depending on the nature of the FA, the observed changes appear to suggest the existence of a putative anorectic response in post-larvae fish to the ingestion of all four tested FAs. However, changes in neuropeptides cannot be explained by the integration of metabolic information regarding FAs in circulation through FA-sensing mechanisms in the brain. Only the reduction in mRNA levels of the FA metabolism gene acc in OA-treated (6 h), ALA-treated (3 h) and EPA-treated (3 and 6 h) post-larvae could be indicative of the presence of a FA-sensing system, but most genes either were not significantly regulated (fat/cd36-lmp2, acly, kir6.x, srebp1c) or were affected in a way that was inconsistent with FA-sensing mechanisms (fat/cd36-pg4l, fas, cpt1.1, cpt1.2, cpt1.3, sur, pparα and lxrα). Summary: Different fatty acids induced changes in the expression of neuropeptides implicated in the control of food intake through a mechanism not involving central fatty acid-sensing systems.
Clustering by Low-Rank Doubly Stochastic Matrix Decomposition

Clustering analysis by nonnegative low-rank approximations has achieved remarkable progress in the past decade. However, most approximation approaches in this direction are still restricted to matrix factorization. We propose a new low-rank learning method to improve the clustering performance, which is beyond matrix factorization. The approximation is based on a two-step bipartite random walk through virtual cluster nodes, where the approximation is formed by only cluster assigning probabilities. Minimizing the approximation error measured by Kullback-Leibler divergence is equivalent to maximizing the likelihood of a discriminative model, which endows our method with a solid probabilistic interpretation. The optimization is implemented by a relaxed Majorization-Minimization algorithm that is advantageous in finding good local minima. Furthermore, we point out that the regularized algorithm with Dirichlet prior only serves as initialization. Experimental results show that the new method has strong performance in clustering purity for various datasets, especially for large-scale manifold data.
vPatcher: VMI-Based Transparent Data Patching to Secure Software in the Cloud

Quick defense against the spread of software exploits is an important problem, and hot patching is an attractive approach to solve this problem. However, these approaches cannot adapt to cloud well, which brings new challenges to the protection of software. Among these challenges, transparency and rapid deployment are two respective requirements for protection. In this paper, we propose vPatcher, a transparent data patching technique based on Virtual Machine Introspection. Vpatcher uses hypervisor to monitor the network connections of vulnerable programs in protected guest systems, deployed outside the Virtual Machines, without disturbing the target guest systems. Given the vulnerability signatures, vPatcher intercepts network packets, scans these packets for vulnerable processes by reconstructing fine-grained system semantics that include process states as well as corresponding network connections, detects them with their vulnerability signatures, and finally filters exploits. We adopted several realistic vulnerable programs used broadly to evaluate the effectiveness of the technique, and experimental results showed its efficacy and that the overhead is acceptable. In addition, the experiments also show that it could be transparent to guest systems, and suitable for rapid deployment in cloud platforms.
Multiple-Valued Signed-Digit Adder Using Negative Differential-Resistance Devices

The paper describes a signed digit full adder (SDFA) circuit consisting of resonant tunneling diodes (RTDs) and metal oxide semiconductor field effect transistors (MOSFETs). The design is primarily based on a multiple valued logic literal circuit that utilizes the folded back I-V (or negative differential resistance, NDR) characteristics of RTDs to compactly implement its gated transfer function. MOS transistors are configured in current mode logic, where addition of two or more digits is achieved by superimposing the signals of individual wires being physically connected at the summing nodes. The proposed SDFA design uses redundant arithmetic representation and therefore, the circuit can perform addition of two arbitrary size binary numbers in constant time without the need for either carry propagation or carry look-ahead. The SDFA cell design has been verified through simulation by an augmented SPICE simulator that includes new homotopy based convergence routines to tackle the nonlinear device characteristics of quantum devices. From the simulation result, the SDFA cell has been found to perform addition operation in 3.5 nanoseconds, which is somewhat superior to other multivalued redundant arithmetic circuits reported in the literature. The SDFA cell requires only 13 MOS transistors and one RTD, as opposed to the state of the art CMOS redundant binary adder requiring 56 transistors, and to the conventional multivalued current mode adder consisting of 34 MOS transistors. In order to verify the simulation result, a prototype SDFA cell has been fabricated using MOSIS 2-micron CMOS process and GaAs based RTDs connected externally to the MOSFET circuit.
Identification and Antifungal Susceptibility of Penicillium-Like Fungi from Clinical Samples in the United States

ABSTRACT Penicillium species are some of the most common fungi observed worldwide and have an important economic impact as well as being occasional agents of human and animal mycoses. A total of 118 isolates thought to belong to the genus Penicillium based on morphological features were obtained from the Fungus Testing Laboratory at the University of Texas Health Science Center in San Antonio (United States). The isolates were studied phenotypically using standard growth conditions. Molecular identification was made using two genetic markers, the internal transcribed spacer (ITS) and a fragment of the β-tubulin gene. In order to assess phylogenetic relationships, maximum likelihood and Bayesian inference assessments were used. Antifungal susceptibility testing was performed according to CLSI document M38-A2 for nine antifungal drugs. The isolates were identified within three genera, i.e., Penicillium, Talaromyces, and Rasamsonia. The most frequent species in our study were Penicillium rubens, P. citrinum, and Talaromyces amestolkiae. The potent in vitro activity of amphotericin B (AMB) and terbinafine (TRB) and of the echinocandins against Penicillium and Talaromyces species might offer a good therapeutic alternative for the treatment of infections caused by these fungi.
A fast pseudo-Boolean constraint solver

Linear Pseudo-Boolean (LPB) constraints denote inequalities between arithmetic sums of weighted Boolean functions and provide a significant extension of the modeling power of purely propositional constraints. They can be used to compactly describe many discrete EDA problems with constraints in linearly combined, parameterized weights, yet also offer efficient search strategies for proving or disproving whether a satisfying solution exists. Furthermore, corresponding decision procedures can easily be extended for minimizing or maximizing an LPB objective function, thus providing a core optimization method for many problems in logic and physical synthesis. In this paper, we review how recent advances in satisfiability (SAT) search can be extended for pseudo-Boolean constraints and describe a new LPB solver that is based on generalized constraint propagation and conflict-based learning.
An application of LOTEM around salt dome near Houston, Texas

A salt dome is an important large geologic structure for hydrocarbon exploration. It may seal a porous reservoir of rocks that form petroleum reservoirs. Several techniques such as seismic, gravity, and electromagnetic including magnetotelluric have successfully yielded salt dome interpretation. Seismic has difficulties seeing through the salt because the seismic energy gets trapped by the salt due to its high velocity. Gravity and electromagnetics are more ideal methods. Long Offset Transient Electromagnetic (LOTEM) and Focused Source Electromagnetic (FSEM) were tested over a salt dome near Houston, Texas. LOTEM data were recorded at several stations with varying offset, and the FSEM tests were also made at some receiver locations near a suspected salt overhang. The data were processed using KMS’s processing software: First, for assurance, including calibration and header checking; then transmitter and receiver data are merged and microseismic data is separated; Finally, data analysis and processing foll.
Improving Quality of Email Categorization with Tournament Methods

The tournament text classification methods are proposed in this article to perform the task of email categorization, in which the essence is to break down the multi-class categorization process into a set of binary classification tasks. We implement the methods of elimination and Round Robin tournament to classify emails within 15 folders. Substantial experiments are conducted to compare the effectiveness and robustness of the tournament methods against the n-way classification method and the voting method. The experimental results show that the tournament methods outperform the n-way method by 11.7% and the voting method by 4.1% regarding precision, and the Round Robin performs slightly better than the Elimination tournament on average.
Seeking grace: a new object-oriented language for novices

Grace is a new object-oriented language that supports a variety of approaches to teaching programming. It integrates accepted new ideas in programming languages into a simple language that allows students and teachers to focus on the essential complexities of programming rather than the accidental complexities of the language. We motivate Grace, review its design, and evaluate it against Kolling's criteria.
Transaction Costs and Shadow Prices in Discrete Time

For portfolio choice problems with proportional transaction costs, we discuss whether or not there exists a shadow price, i.e., a least favorable frictionless market extension leading to the same optimal strategy and utility. By means of an explicit counter-example, we show that shadow prices may fail to exist even in seemingly perfectly benign situations, i.e., for a log-investor trading in an arbitrage-free market with bounded prices and arbitrarily small transaction costs. We also clarify the connection between shadow prices and duality theory. Whereas dual minimizers need not lead to shadow prices in the above "global" sense, we show that they always correspond to a "local" version.
Content free clustering for search engine query log

Web query clustering is widely used by web information systems. In this paper we present a new content free method for web query log clustering. Query clustering has many applications including page ranking in web search, personalizing search result and web query expansion. In our approach, we first construct a bipartite graph for queries and visited URLs of a query log. Most of the clusters of queries are connected together with noisy users selections. So some huge connected components are produced. To eliminate such noisy links all queries and related URLs are projected in reduced dimensional space by applying singular value decomposition. Finally, a clustering algorithm will be applied in each pruned connected component, in new space. The method has been evaluated using a real world data set and by comparing it to existing approaches, the results show promising improvements.
Extracting Opinions from Topic-Based Events in the Blogosphere

With the rapid development of information technologies in recent years, people can now easily publish their opinions on the Internet. On the other hand, people can also obtain various opinions from others in a few seconds even though they do not know each other. A typical approach to obtain required information is to use a search engine with some relevant keywords. Nevertheless, it is a time-consuming process when looking for opinions of other individuals. Usually, the retrieved opinions are not the latest and single-sided. On the other hand, it is noted that people can have their own blog sites as a platform to publish personal thoughts, ideas or comments easily. We thus take the blogosphere as our major data source and aim at discovering opinions efficiently and effectively in this work. Moreover, two crucial issues are carefully addressed in this work. First, the opinion diversity is addressed by providing various opinions from multiple aspects. Second, we conduct sentiment analysis on opinions against some topic-based events in different time spans to address the opinion dynamics. Empirical studies show that the proposed scheme can help users to obtain opinions of some topic-based events in both an efficient and an effective way.
Collaborative filtering using probabilistic matrix factorization and a Bayesian nonparametric model

In recent times, numerous web-based systems that offer various kinds of services ranging from e-commerce to video and audio streaming are overwhelmed with influx of data. These systems have been introducing various recommender algorithms into their platforms to filter information from their voluminous databases. These recommendation engines help users to save time by providing them with results that suite their taste. Researchers and software engineers have developed numerous algorithms to recommend items more accurately however, very little research have been done on the scope of music recommendation using social data. Orthodox methods of recommendation utilized ratings supplied by users to each item as the basis of recommendation. The accuracy of prediction is significantly affected when ratings are not provided for some items or when the user is new to the platform and has not rated any item yet. It is also difficult to recommend new items that have not yet being rated yet. This problem is termed “cold start”. In order to eliminate this problem we propose the Collaborative Filtering (CF) using Probabilistic Matrix Factorization (PMF) and a Bayesian Nonparametric Model (BNM). A comprehensive experiment on music and social datasets from different source indicates a higher accuracy of prediction and performance.
Discovering and Browsing of Power Users by Social Relationship Analysis in Large-Scale Online Communities

Community Web sites on specific topics are very popular on the Web. Some active Web communities are so huge and diverse that it becomes a challenging issue to efficiently mine meaningful knowledge from the Web communities. In this paper, we develop schemes to discover and browse power users by their activities in online communities. The novelties of this work are two-fold. 1) We define new features to describe user's social activities: statistical features to summarize userspsila activities and relationship-based features to describe interactions between individual users. And, through extensive user study and experiments to compare the performances of the ranking models based on various features, it is shown that the cross reference (CR) feature plays an unique and effective role in discovering power users in post-dominant online communities. 2) Thereafter, we develop a novel interface for effective exploration of power users based on the CR rank. Two schemes are proposed to incrementally navigate a large number of candidate power users with higher CR values: threshold-based navigation and traversal-based one. Experimental results shows that the proposed CR rank can be used for effective browsing of power users: about 70% precision is maintained while retrieving all the power users, which means that we can discover all the power users with relatively small number of false alarms.