Miracle-dz/UniFAR-FTUs huggingface dataset:
Vitamin E levels in soybean (Glycine max (L.) Merr.) expressing a p-hydroxyphenylpyruvate gene from oat (Avena sativa L.).

The enzyme p-hydroxyphenylpyruvate dioxygenase (HPPD) is ubiquitous in plants and functions in the tyrosine catabolic pathway, resulting in the formation of homogentisate. Homogentisate is the aromatic precursor of all plastoquinones and tocochromanols, including tocopherols and tocotrienols. Soybean (Glycine max (L.) Merr. ) has been genetically modified to express the gene avhppd-03 that encodes the protein AvHPPD-03 derived from oat (Avena sativa L.). The AvHPPD-03 isozyme has an inherent reduced binding affinity for mesotrione, a herbicide that inhibits the wild-type soybean HPPD enzyme. Expression of avhppd-03 in soybean plants confers a mesotrione-tolerant phenotype. Seeds from three different avhppd-03-expressing soybean events were quantitatively assessed for content of eight vitamin E isoforms. Although increased levels of two tocopherol isoforms were identified for each of the three soybean events, they were within, or not substantially different from, the ranges of these isoforms found in nontransgenic soybean varieties. The increases of these tocopherols in the avhppd-03-expressing soybean events may have a slight benefit with regard to vitamin E nutrition but, given the commercial processing of soybeans, are unlikely to have a material impact on human nutrition with regard to vitamin E concentrations in soybean oil.
Faceted Search over Ontology-Enhanced RDF Data

An increasing number of applications rely on RDF, OWL 2, and SPARQL for storing and querying data. SPARQL, however, is not targeted towards end-users, and suitable query interfaces are needed. Faceted search is a prominent approach for end-user data access, and several RDF-based faceted search systems have been developed. There is, however, a lack of rigorous theoretical underpinning for faceted search in the context of RDF and OWL 2. In this paper, we provide such solid foundations. We formalise faceted interfaces for this context, identify a fragment of first-order logic capturing the underlying queries, and study the complexity of answering such queries for RDF and OWL 2 profiles. We then study interface generation and update, and devise efficiently implementable algorithms. Finally, we have implemented and tested our faceted search algorithms for scalability, with encouraging results.
Stability of persistence spaces of vector-valued continuous functions

Multidimensional persistence modules do not admit a concise representation analogous to that provided by persistence diagrams for real-valued functions. However, there is no obstruction for multidimensional persistent Betti numbers to admit one. Therefore, it is reasonable to look for a generalization of persistence diagrams concerning those properties that are related only to persistent Betti numbers. In this paper, the persistence space of a vector-valued continuous function is introduced to generalize the concept of persistence diagram in this sense. The main result is its stability under function perturbations: any change in vector-valued functions implies a not greater change in the Hausdorff distance between their persistence spaces.
Mcm10: A Dynamic Scaffold at Eukaryotic Replication Forks

To complete the duplication of large genomes efficiently, mechanisms have evolved that coordinate DNA unwinding with DNA synthesis and provide quality control measures prior to cell division. Minichromosome maintenance protein 10 (Mcm10) is a conserved component of the eukaryotic replisome that contributes to this process in multiple ways. Mcm10 promotes the initiation of DNA replication through direct interactions with the cell division cycle 45 (Cdc45)-minichromosome maintenance complex proteins 2-7 (Mcm2-7)-go-ichi-ni-san GINS complex proteins, as well as single- and double-stranded DNA. After origin firing, Mcm10 controls replication fork stability to support elongation, primarily facilitating Okazaki fragment synthesis through recruitment of DNA polymerase-α and proliferating cell nuclear antigen. Based on its multivalent properties, Mcm10 serves as an essential scaffold to promote DNA replication and guard against replication stress. Under pathological conditions, Mcm10 is often dysregulated. Genetic amplification and/or overexpression of MCM10 are common in cancer, and can serve as a strong prognostic marker of poor survival. These findings are compatible with a heightened requirement for Mcm10 in transformed cells to overcome limitations for DNA replication dictated by altered cell cycle control. In this review, we highlight advances in our understanding of when, where and how Mcm10 functions within the replisome to protect against barriers that cause incomplete replication.
Performances comparison of linear and sliding mode attitude controllers for flexible spacecraft with reaction wheels

In this study, two control algorithms for the three axes stabilized geosynchronous communication satellite Intelsat V are given. The spacecraft is assumed to be controlled via reaction wheels. First, linear control method is used to design an attitude feedback control algorithm for a rigid satellite with attitude angles. Linearized form of the spacecraft dynamics are given in attitude angles representation. Second, sliding mode control method is used for the attitude controller with equivalent control term for flexible satellite. The performances and disadvantages are discussed on design example for both cases. Modeling and simulation are done by using MATLAB-Simulink programming. The results show that using attitude linear controller may cause the mission cost to be high and decrease the maneuver performances for a geosynchronous satellite mission. Also linear attitude controller does not include neglected nonlinear effects, flexibility effects, etc. That is why the linear attitude controller has a very long settling time. On the other hand, attitude sliding mode controller for geosynchronous satellite with flexible solar arrays uses energy optimally with a great performance and relative small settling time. Moreover, attitude sliding mode controller includes all effects of nonlinear dynamics which is robust to bounded external disturbances and unmodelled dynamics
Collaboration signatures reveal scientific impact

Collaboration is an integral element of the scientific process that often leads to findings with significant impact. While extensive efforts have been devoted to quantifying and predicting research impact, the question of how collaborative behavior influences scientific impact remains unaddressed. In this work, we study the interplay between scientists' collaboration signatures and their scientific impact. As the basis of our study, we employ an ArnetMiner dataset with more than 1.7 million authors and 2 million papers spanning over 60 years. We formally define a scientist's collaboration signature as the distribution of collaboration strengths with each collaborator in his or her academic ego network, which is quantified by four measures: sociability, dependence, diversity, and self-collaboration. We then demonstrate that the collaboration signature allows us to effectively distinguish between researchers with dissimilar levels of scientific impact. We also discover that, even from the early stages of one's researcher career, a scientist's collaboration signature can help to reveal his or her future scientific impact. Finally, we find that as a representative group of outstanding computer scientists, Turing Award winners collectively produce distinctive collaboration signatures throughout the entirety of their careers. Our conclusions on the relationship between collaboration signatures and scientific impact give rise to important implications for researchers who wish to expand their scientific impact and more effectively stand on the shoulders of "collaborators. ".
ML Theory Lecture 3

– Briefly we’ll show in Theorem 1.2 (sketched last time) that the representation question is essential — sometimes, by choosing the wrong function class, you can get a bad error, even though there are simple predictors that get 0 error. – Continuous fit I: box approximations; namely, we’ll show that a variety of functions can approximate continuous functions by showing they approximate piecewise constant functions. – Continuous fit II: polynomial approximations; we’ll show refined results for other functions by showing that they in turn can be related to polynomials. – Succinct representations; recall that approximating continuous functions was “giving up”. In this subsection we’ll show that neural networks can efficiently approximate a variety of interesting functions. – GANs: lastly we’ll discuss the ability of neural networks to approximate probability distributions.
Wearable Electroencephalography

The electroencephalogram (EEG) is a classic noninvasive method for measuring a person's brainwaves and is used in a large number of fields: from epilepsy and sleep disorder diagnosis to brain-computer interfaces (BCIs). Electrodes are placed on the scalp to detect the microvolt-sized signals that result from synchronized neuronal activity within the brain. Current long-term EEG monitoring is generally either carried out as an inpatient in combination with video recording and long cables to an amplifier and recording unit or is ambulatory. In the latter, the EEG recorder is portable but bulky, and in principle, the subject can go about their normal daily life during the recording. In practice, however, this is rarely the case. It is quite common for people undergoing ambulatory EEG monitoring to take time off work and stay at home rather than be seen in public with such a device. Wearable EEG is envisioned as the evolution of ambulatory EEG units from the bulky, limited lifetime devices available today to small devices present only on the head that can record EEG for days, weeks, or months at a time [see Figure 1(a) and (b)]. Such miniaturized units could enable prolonged monitoring of chronic conditions such as epilepsy and greatly improve the end-user acceptance of BCI systems. In this article, we aim to provide a review and overview of wearable EEG technology, answering the questions: What is it, why is it needed, and what does it entail? We first investigate the requirements of portable EEG systems and then link these to the core applications of wearable EEG technology: epilepsy diagnosis, sleep disorder diagnosis, and BCIs. As a part of our review, we asked 21 neurologists (as a key user group) for their views on wearable EEG. This group highlighted that wearable EEG will be an essential future tool. Our descriptions here will focus mainly on epilepsyand the medical applications of wearable EEG, as this is the historical background of the EEG, our area of expertise, and a core motivating area in itself, but we will also discuss the other application areas. We continue by considering the forthcoming research challenges, principally new electrode technology and lower power electronics, and we outline our approach for dealing with the electronic power issues. We believe that the optimal approach to realizing wearable EEG technology is not to optimize any one part but to find the best set of tradeoffs at both the system and implementation level. In this article, we discuss two of these tradeoffs in detail: investigating the online compression of EEG data to reduce the system power consumption and the optimal method for providing this data compression.
CONTRAST ECHOCARDIOGRAPHY

The last decade has seen a revolution in the technique of contrast echocardiography, with detailed understanding of the interaction between microscopic air bubbles and ultrasound leading to rapid development in both contrast and imaging technology. Several transpulmonary contrast agents have been developed, capable of crossing the pulmonary vascular bed and hence achieving left heart opacification following intravenous injection. Combined with major developments in cardiac ultrasound equipment, left heart contrast echocardiography has moved from research into mainstream clinical echocardiography and we stand on the threshold of myocardial contrast echocardiography as a tool for routine clinical use in the assessment of the patient with ischaemic heart disease. Optimal use of these techniques requires detailed understanding of the agents used, mode of administration, and optimum machine settings. Basic knowledge of the physics of ultrasound is now crucial if the potential for contrast echocardiography is to be realised in clinical practice.
On Initial Trust Building for E-Commerce: Revisiting from the Perspective of Signal Theory and Trust Transference

Trust building for consumers has been a main stream of research in e-commerce. However, little research pays attention to how consumers treat the revealed information about warranty, privacy statement, assurance, and related statements. Although this information is provided in real-world settings, their effectiveness has not been fully understood. This study attempts to look into this issue by employing signal theory and perspective of trust transference. Empirical results gathered from lab experiment show that warranty perception, rather than the assurance itself, is the critical antecedent of initial trust building. Once consumers discredit the revealed information in a web site, the signals will fail to induce consumers’ trust. Information from a trusted third party may be an efficient way to build consumer trust. However, it should be noted that information from trusted third party will not be effective if consumers fail to notice them, or misunderstand their meanings. Hence, e-tailers should devote to build initial trust by applying assurance and quality signals from independent institutions.
Requirement of Tyrosine- and Serine/Threonine Kinases in the Transcriptional Activation of the Mammalian grp78/BiP Promoter by Thapsigargin (*)

Depletion of endoplasmic reticulum (ER) Ca store by thapsigargin (Tg) in mammalian cells induces a set of ER protein genes known as the glucose-regulated proteins. Recently, IRE1p, a transmembrane protein postulated to have a serine/threonine kinase activity, has been identified as required for the induction of ER resident proteins genes in Saccharomyces cerevisiae. To investigate whether IRE1p can stimulate mammalian grp transcription, a stable Chinese hamster ovary cell line containing amplified copies of IRE1p has been created. The IRE1p expressing transfectants exhibited a modest (2-fold) enhancement of both the basal and Tg induced level of grp78 and grp94, two coordinately regulated grp genes. Using okadaic acid as a specific inhibitor for the endogenous serine/threonine protein phosphatase activities, a mild (2-fold) stimulative effect was observed for Tg induction of grp78 transcription. The okadaic acid potentiating effect requires a 50-base pair region in the vicinity of the grp78 TATA element. In contrast, the transcriptional activation of grp78 by Tg is almost totally eliminated by genistein, a tyrosine kinase inhibitor. The grp core, the C3 and C1 elements which are major Tg response elements of the rat grp78 promoter, are also major targets of the inhibitive effects of genistein.
The MC-CDMA System Using LS Codes and Nonorthogonal Subcarriers

In this paper, the integration of large-area-synchronized code division multiple access (LAS-CDMA) technology and multicarrier technology is studied. Single cell LAS-CDMA system takes LS codes as its spread spectrum code which have good correlation property, so that the inter-symbol interference (ISI) and multiple access interference (MAI) can be eliminated by finely designing the LS codes. The system model is given in this paper. The received signal especially the interference is well analyzed. Simulational performance and their comparison are given. By integrating multicarrier technology into LAS-CDMA system, much better capacity or performance than that of ordinary multicarrier code division multiple access (MC-CDMA) system can be achieved. In addition, nonorthogonal subcarriers are possible to be applied to LAS-CDMA system as long as most of the interference is removed. As a result, the frequency space between two neighbor subcarriers decreases and the spectrum efficiency of such kind of LAS-CDMA system increases greatly
Re-Ranking Recommendations Based on Predicted Short-Term Interests - A Protocol and First Experiment

The recommendation of additional shopping items that are potentially interesting for the customer has become a standard feature of modern online stores. In academia, research on recommender systems (RS) is mostly centered around approaches that rely on explicit item ratings and long-term user profiles. In practical environments, however, such rating information is often very sparse and for a large fraction of the users very little is known about their preferences. Furthermore, in particular when the shop offers products from a variety of categories, the decision of what should be recommended can strongly depend on the user's current short-term interests and the navigational context. In this paper, we report the results of an initial experimental analysis evaluating the predictive accuracy of different contextualized and non-contextualized recommendation strategies and discuss the question of appropriate experimental designs for such types of evaluations. To that purpose, we introduce a parameterizable protocol that supports session-specific accuracy measurements. Our analysis, which was based on log data obtained from a large online retailer for clothing and lifestyle products, shows that even a comparably simple contextual post-processing approach based on product features can leverage short-term user interests to increase the accuracy of the recommendations.
BioProber: Software System for Biomedical Relation Discovery from PubMed

The numbers of articles and journals that are published are increasing at a considerable rate, and the published information is growing continuously and fast. Because of this, researches to acquire knowledge automatically have been carried out in the areas of information retrieval, information extraction and text mining. Information retrieval approaches are good for specific topics that the number of related articles is small. But, if the number is bigger, searching skill and knowledge acquisition ability are useless. Though many efforts have been made to extract information from literature, many approaches have concentrated on specific entities, such as proteins, genes and their interactions, and much information is still remained in unstructured text. So, we have developed a system that discovers relations between various categories of biomedical entities. Our system collects abstracts from PubMed by queries representing a topic and visualizes relationship from the collection by automatic information extraction
Generating security tests in addition to functional tests

This paper is about generating security tests, in addition to functional tests previously generated by a model-based testing approach. The method that we present re-uses the functional model and the adaptation layer developed for the functional testing, and relies on an additional security model. We propose to compute the tests by using some test purposes as guides for the tests to be extracted from the models. We see a test purpose as the combination of a security property and a test need issued from the know-how of a security engineer. We propose a language based on regular expressions for the expression of such test purposes. We illustrate our approach with experiments on IAS.
Detecting leaf water content using intensity data from terrestrial laser scanner

Leaf water content (LWC) plays an important role in agriculture and forestry management. It can be used to assess drought conditions and wildfire susceptibility [1]. Recent studies have also shown the potential of using terrestrial laser scanner (TLS) radiometric information (backscatter intensity) for estimating LWC. The usefulness of backscatter intensity data has been limited by leaf surface characteristics, and incidence angle effects.
Distributed Consensus Algorithms in Sensor Networks With Imperfect Communication: Link Failures and Channel Noise

The paper studies average consensus with random topologies (intermittent links) and noisy channels. Consensus with noise in the network links leads to the bias-variance dilemma-running consensus for long reduces the bias of the final average estimate but increases its variance. We present two different compromises to this tradeoff: the A-ND algorithm modifies conventional consensus by forcing the weights to satisfy a persistence condition (slowly decaying to zero;) and the A-NC algorithm where the weights are constant but consensus is run for a fixed number of iterations [^(iota)], then it is restarted and rerun for a total of [^(p)] runs, and at the end averages the final states of the [^(p)] runs (Monte Carlo averaging). We use controlled Markov processes and stochastic approximation arguments to prove almost sure convergence of A-ND to a finite consensus limit and compute explicitly the mean square error (mse) (variance) of the consensus limit. We show that A-ND represents the best of both worlds-zero bias and low variance-at the cost of a slow convergence rate; rescaling the weights balances the variance versus the rate of bias reduction (convergence rate). In contrast, A-NC, because of its constant weights, converges fast but presents a different bias-variance tradeoff. For the same number of iterations [^(iota)][^(p)] , shorter runs (smaller [^(iota)] ) lead to high bias but smaller variance (larger number [^(p)] of runs to average over. ) For a static nonrandom network with Gaussian noise, we compute the optimal gain for A-NC to reach in the shortest number of iterations [^(iota)][^(p)] , with high probability (1-delta), (epsiv, delta)-consensus (epsiv residual bias). Our results hold under fairly general assumptions on the random link failures and communication noise.
Defining metrics for software components

As component oriented programming becomes more popular, the need emerges for the definition of a suitable set of metrics to describe the internal attributes of components. This paper presents a set of component metrics based on the Chidamber and Kemerer metrics suite (1994). The metrics is validated with the properties based approach by (Briand et al., 1996). An example of usage of this metrics is presented, with reference to the Java 2 Swing package.
Game-Theoretic Learning Using the Imprecise Dirichlet Model

We discuss two approaches for choosing a strategy in a two-player game. We suppose that the game is played a large number of rounds, which allows the players to use observations of past play to guide them in choosing a strategy. Central in these approaches is the way the opponent's next strategy is assessed; both a precise and an imprecise Dirichlet model are used. The observations of the opponent's past strategies can then be used to update the model and obtain new assessments. To some extent, the imprecise probability approach allows us to avoid making arbitrary initial assessments. To be able to choose a strategy, the assessment of the opponent's strategy is combined with rules for selecting an optimal response to it: a so-called best response or a maximin strategy. Together with the updating procedure, this allows us to choose strategies for all the rounds of the game. The resulting playing sequence can then be analysed to investigate if the strategy choices can converge to equilibria.