Miracle-dz/UniFAR-FTUs huggingface dataset:
Luteolin decreases the UVA-induced autophagy of human skin fibroblasts by scavenging ROS

Luteolin (LUT) is a flavone, which is universally present as a constituent of traditional Chinese herbs, and certain vegetables and spices, and has been demonstrated to exhibit potent radical scavenging and cytoprotective properties. Although LUT has various beneficial effects on health, the effects of LUT on the protection of skin remain to be fully elucidated. The present study investigated whether LUT can protect human skin fibroblasts (HSFs) from ultraviolet (UV) A irradiation. It was found that, following exposure to different doses of UVA irradiation, the HSFs exhibited autophagy, as observed by fluorescence and transmission electron microscopy, and reactive oxygen species (ROS) bursts, analyzed by flow cytometry, to differing degrees. Following incubation with micromolar concentrations of LUT, ROS production decreased and autophagy gradually declined. In addition, the expression of hypoxia-inducible factor-1α and the classical autophagy-associated proteins, LC3 and Beclin 1 were observed by western blotting. Western blot analysis showed that the expression levels of HIF-1α, LC3-II and Beclin 1 gradually decreased in the UVA-irradiated HSFs following treatment with LUT. These data indicated that UVA-induced autophagy was mediated by ROS, suggesting the possibility of resistance against UV by certain natural antioxidants, including LUT.
TOCCF: Time-Aware One-Class Collaborative Filtering

One-class collaborative filtering (OCCF), or recommendation with one-class feedback such as shopping records, has recently gained more attention from researchers and practitioners in the community. The main reason is that one-class feedback in the form of (user, item) pairs are often more abundant than numerical ratings in the form of (user, item, rating) triples as exploited by traditional collaborative filtering algorithms. However, most of the previous work on OCCF do not consider the temporal context, which is known of great importance to users’ preferences and behaviors. In this paper, we first formally define a new problem called time-aware OCCF (TOCCF), and then design a novel timeaware similarity learning (TSL) model accordingly. Our TSL is based on a novel time-aware weighting scheme and a seminal work on similarity learning, and is able to learn the item similarities more accurately. Empirical studies on two large real-world datasets show that our TSL model can integrate the temporal information effectively, and perform significantly better than several state-of-the-art recommendation algorithms.
An Efficient Outlier Mining Algorithm for Large Dataset

Since an outlier often contains useful information, outlier detection is becoming a hot issue in data mining. Thus, an efficient outlier mining algorithm based on KNN is proposed in this paper. It can find outlier more accurately through defining a correlation matrix considering the importance and correlation between attributes. In addition, a data structure R-tree is used in the algorithm and it utilizes pruning scheme to drastically reduce the time consuming of computing. Experimental results show that our algorithm is more efficient than the traditional KNN algorithm. It will provide an effective solution for outlier mining in large dataset.
Optimality of routing on the wiretap network with simple network topology

In this paper, we study the performance of routing in the Level-I/II (n1, n2) wiretap networks, consisting of a source node, a destination node, and an intermediate node. The intermediate node connects the source and the destination nodes via a set of noiseless parallel channels, with sizes n1 and n2, respectively. The information in the network may be eavesdropped by a wiretapper, who can access at most one set of channels, called a wiretap set. All the possible wiretap sets which may be accessed by the wiretapper form a wiretap pattern. A random key K is used to protect the message M. We define two decoding levels: in Level-I, only M is decoded and in Level-II, both M and K are decoded. The objective is to minimize H(K)/H(M) under perfect secrecy constraint. Our concern is whether routing is optimal in this simple network. By harnessing the power of Shannon-type inequalities, we enumerate all the wiretap patterns in the Level-I/II (3, 3) networks, and find out that gaps exist between the bounds by routing and the bounds by Shannon-type inequalities for a small fraction of all the wiretap patterns. Furthermore, we show that for some wiretap patterns, the Shannon bounds can be achieved by a linear code; i.e, routing is not optimal even in the (3, 3) case. Some subtle issues on the network models are discussed and interesting open problems are introduced.
What Do New Views of Knowledge and Thinking Have to Say About Research on Teacher Learning?

The education and research communities are abuzz with new (or at least re-discovered) ideas about the nature of cognition and learning. Terms like "situated cognition," "distributed cognition," and "communities of practice" fill the air. Recent dialogue in Educational Researcher (Anderson, Reder, & Simon, 1996,1997; Greeno, 1997) typifies this discussion. Some have argued that the shifts in world view that these discussions represent are even more fundamental than the now-historical shift from behaviorist to cognitive views of learning (Shuell, 1986). These new ideas about the nature of knowledge, thinking, and learning—which are becoming known as the "situative perspective" (Greeno, 1997; Greeno, Collins, & Resnick, 1996)—are interacting with, and sometimes fueling, current reform movements in education. Most discussions of these ideas and their implications for educational practice have been cast primarily in terms of students. Scholars and policymakers have considered, for example, how to help students develop deep understandings of subject matter, situate students' learning in meaningful contexts, and create learning communities in which teachers and students engage in rich discourse about important ideas (e.g., National Council of Teachers of Mathematics, 1989; National Education Goals Panel, 1991; National Research Council, 1993).
Role of molecular charge in glomerular permeability. Tracer studies with cationized ferritins

Mouse kidneys were perfused with Krebs-Ringer bicarbonate buffer (KRB) containing native, anionic horse spleen ferritin or various cationized derivatives, and the glomerular localization of the probe molecules determined by electron microscopy. Ferritins cationic with respect to the medium (KRB, pH 7.45) accumulated in the subendothelial layers of the glomerular basement membrane (GBM) in amounts far exceeding those observed with anionic ferritins, the degree being greater for the more cationized derivatives. Strongly cationized ferritins, in addition permeated the full thickness of the GBM in considerable amounts, but appeared to be retarded from entry into the urinary spaces at the level of the filtration slits. Very strongly cationized derivatives adhered to glomerular endothelium and GBM and formed aggregates in the outer layers of the latter. The results suggest that intrinsic negative charges are present in the GBM and endothelium, and that the barrier function of the glomerular capillary wall may be ascribed in part to its electrophysical properties.
Phage Therapy Is Effective against Infection by Mycobacterium ulcerans in a Murine Footpad Model

Background Buruli Ulcer (BU) is a neglected, necrotizing skin disease caused by Mycobacterium ulcerans. Currently, there is no vaccine against M. ulcerans infection. Although the World Health Organization recommends a combination of rifampicin and streptomycin for the treatment of BU, clinical management of advanced stages is still based on the surgical resection of infected skin. The use of bacteriophages for the control of bacterial infections has been considered as an alternative or to be used in association with antibiotherapy. Additionally, the mycobacteriophage D29 has previously been shown to display lytic activity against M. ulcerans isolates. Methodology/Principal findings We used the mouse footpad model of M. ulcerans infection to evaluate the therapeutic efficacy of treatment with mycobacteriophage D29. Analyses of macroscopic lesions, bacterial burdens, histology and cytokine production were performed in both M. ulcerans-infected footpads and draining lymph nodes (DLN). We have demonstrated that a single subcutaneous injection of the mycobacteriophage D29, administered 33 days after bacterial challenge, was sufficient to decrease pathology and to prevent ulceration. This protection resulted in a significant reduction of M. ulcerans numbers accompanied by an increase of cytokine levels (including IFN-γ), both in footpads and DLN. Additionally, mycobacteriophage D29 treatment induced a cellular infiltrate of a lymphocytic/macrophagic profile. Conclusions/Significance Our observations demonstrate the potential of phage therapy against M. ulcerans infection, paving the way for future studies aiming at the development of novel phage-related therapeutic approaches against BU.
Unveiling combinatorial regulation through the combination of ChIP information and in silico cis-regulatory module detection

Computationally retrieving biologically relevant cis-regulatory modules (CRMs) is not straightforward. Because of the large number of candidates and the imperfection of the screening methods, many spurious CRMs are detected that are as high scoring as the biologically true ones. Using ChIP-information allows not only to reduce the regions in which the binding sites of the assayed transcription factor (TF) should be located, but also allows restricting the valid CRMs to those that contain the assayed TF (here referred to as applying CRM detection in a query-based mode). In this study, we show that exploiting ChIP-information in a query-based way makes in silico CRM detection a much more feasible endeavor. To be able to handle the large datasets, the query-based setting and other specificities proper to CRM detection on ChIP-Seq based data, we developed a novel powerful CRM detection method ‘CPModule’. By applying it on a well-studied ChIP-Seq data set involved in self-renewal of mouse embryonic stem cells, we demonstrate how our tool can recover combinatorial regulation of five known TFs that are key in the self-renewal of mouse embryonic stem cells. Additionally, we make a number of new predictions on combinatorial regulation of these five key TFs with other TFs documented in TRANSFAC.
Kernel Principle Component Analysis in Face Recognition System: A Survey

Face recognition is a dynamic topic in the fields of biometrics. Many achievements have been obtained in face recognition. Principal Components Analysis (PCA) and kernel principal components Analysis (KPCA) is a elementary technique broadly used in face feature extraction and recognition. This research paper presents nitty-gritty of KPCA and an up to date review of techniques KPCA. Papers also notify benefits of KPCA over PCA. Finally, it finds that it is appropriate technique in face recognition system. Therefore, it will be a possibility to seek a good system using this approach.
Identifying Auto-Generated Code by Using Machine Learning Techniques

Recently, many researchers have conducted mining source code repositories to retrieve useful information about software development. Source code repositories often include auto-generated code, and auto-generated code is usually removed in a preprocessing phase because the presence of auto-generated code is harmful to source code analysis. A usual way to remove auto-generated code is searching particular comments which exist among auto-generated code. However, we cannot identify auto-generated code automatically with such a way if comments have disappeared. In addition, it takes too much time to identify auto-generated code manually. Therefore, we propose a technique to identify auto-generated code automatically by using machine learning techniques. In our proposed technique, we can identify whether source code is auto-generated code or not by utilizing syntactic information of source code. In order to evaluate the proposed technique, we conducted experiments on source code generated by four kinds of code generators. As a result, we confirmed that the proposed technique was able to identify auto-generated code with high accuracy.
First wavila challenge: several considerations on the security of a feature-based synchronisation scheme for digital image watermarking

This paper presents a study on the security of feature-points based synchronisation watermarking methods. The studied scheme, based on the Harris detector, is presented. An analysis of the feature point de- tector enables then to draw two different attacks. The first attack called the competition attack is performed to lure the detector by increasing the response of neighbouring feature points. The ranking attack affects the final ranking which is used to extract the most robust feature points. Examples are given on toy images and the security of feature-based wa- termarking scheme is afterward discussed.
Adaptive Minimum Symbol Error Rate Beamforming Assisted Receiver for Quadrature Amplitude Modulated Systems

An adaptive beamforming assisted receiver is proposed for multiple antenna aided multiuser systems that employ bandwidth efficient quadrature amplitude modulation (QAM). A novel minimum symbol error rate (MSER) design is proposed for the beamforming assisted receiver, where the system's symbol error rate is directly optimized. Hence the MSER approach provides a significant symbol error ratio performance enhancement over the classic minimum mean square error design. A sample-by-sample adaptive algorithm, referred to as the least symbol error rate (LBER) technique, is derived for allowing the adaptive implementation of the system to arrive from its initial beamforming weight solution to MSER beamforming solution
The Conditional Diagnosability of Twisted Cubes under the Comparison Model

In evaluating the fault tolerance of an network structure, it is essential to estimate the order of a maximal connected component of this network provided the faulty vertices may break its connectedness, and it is crucial to local and to replace the faulty processors to maintain system’s high reliability. The fault diagnosis is the process of identifying fault processors in a system through testing. The conditional diagnosis requires that for each processor v in a system, all the processors that are directly connected to v do not fail at the same time. In this paper, the conditional diagnosability of the twisted cubes TQn under the comparison diagnosis model is 3n-5 when n≫6. Hence the conditional diagnosability of TQn is three times larger than its classical diagnosability.
Can Triticum urartu (Poaceae) be identified by pollen analysis? Implications for detecting the ancestor of the extinct two-grained einkorn-like wheat

The domestication of the one-grained einkorn (Triticum monococcum) in the Near East is relatively well known. However, an independent two-grained einkorn-like domestication has been archaeobotanically detected and scarce information is available. Triticum urartu, a wild wheat, was not fully described until the 1970s because the phenology does not allow it to be distinguished easily from wild einkorn (Triticum boeoticum subsp. thaoudar), although a genetic separation exists. Both species are mostly two grained and could potentially be the relatives of the extinct two-grained form. Pollen grains of several genetically well-identified wheat species, including T. urartu and T. boeoticum subsp. thaoudar, were studied by measuring the grain diameter and examining the exine sculpturing with phase-contrast microscopy and scanning electron microscopy to gain an insight into differences enabling taxonomic identification. This work showed that, although T. urartu pollen is smaller on average, grain diameter is not sufficient because of the size overlap between the species, but T. urartu presents a different exine sculpturing (scabrate) from other Triticum spp. (aerolate). This outcome is useful for taxonomists and archaeobotanists. First, it will allow a simple re-classification of herbarium materials. Second, further research could establish whether T. urartu was cultivated. © 2015 The Linnean Society of London, Botanical Journal of the Linnean Society, 2015, 177, 278–289.
Universal biometric evaluation system: Framework for testing evaluation and comparison of biometric methods

Biometric recognition significantly evolved during the last decade and today is used on daily basis. Despite active research in this area it is very hard for scientists to compare their results with others mainly because of different implementations and environment conditions. In this paper, we present modular biometric system based on universal schema of biometric recognition process. Modular architecture keeps execution process separated from specific method, preprocessing and implementation of these methods.
The Impact of Linked Documents and Graph Analysis on Information Retrieval Methods for Book Recommendation

A new combination of multiple Information Retrieval approaches are proposed for book recommendation based on complex users' queries. We used different theoretical retrieval models: probabilistic as InL2 (Divergence From Randomness model) and language models and tested their interpolated combination. We considered the application of a graph based algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD) a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of CLEF Labs precisely Social Book Search track. We established a specific strategy for queries searching after separating query set into two genres Analogue and Non-Analogue after analyzing users' needs. Series of reranking experiments demonstrate that combining retrieval models and exploiting linked documents for retrieving yield significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments.
Dual allosteric activation mechanisms in monomeric human glucokinase

Significance Glucokinase (GCK), the body’s primary glucose sensor, displays a unique sigmoidal kinetic response that is a hallmark of allostery. Allostery in GCK is different from textbook models, because the enzyme is monomeric and contains only one glucose binding site. Previously, synthetic activators and activating disease mutations were thought to share a common mechanism of allosteric activation in which GCK is shifted toward a glucose-bound–like state. Using mutagenesis and genetic selection, we identify an activated variant that utilizes a different mechanism. Limited proteolysis and NMR reveal that activation is achieved by modulating the dynamic properties of an active-site loop without perturbing the ensemble structure. This previously undescribed activation mechanism is shown to operate in naturally occurring, hyperinsulinemia-associated disease variants. Cooperativity in human glucokinase (GCK), the body’s primary glucose sensor and a major determinant of glucose homeostatic diseases, is fundamentally different from textbook models of allostery because GCK is monomeric and contains only one glucose-binding site. Prior work has demonstrated that millisecond timescale order-disorder transitions within the enzyme’s small domain govern cooperativity. Here, using limited proteolysis, we map the site of disorder in unliganded GCK to a 30-residue active-site loop that closes upon glucose binding. Positional randomization of the loop, coupled with genetic selection in a glucokinase-deficient bacterium, uncovers a hyperactive GCK variant with substantially reduced cooperativity. Biochemical and structural analysis of this loop variant and GCK variants associated with hyperinsulinemic hypoglycemia reveal two distinct mechanisms of enzyme activation. In α-type activation, glucose affinity is increased, the proteolytic susceptibility of the active site loop is suppressed and the 1H-13C heteronuclear multiple quantum coherence (HMQC) spectrum of 13C-Ile–labeled enzyme resembles the glucose-bound state. In β-type activation, glucose affinity is largely unchanged, proteolytic susceptibility of the loop is enhanced, and the 1H-13C HMQC spectrum reveals no perturbation in ensemble structure. Leveraging both activation mechanisms, we engineer a fully noncooperative GCK variant, whose functional properties are indistinguishable from other hexokinase isozymes, and which displays a 100-fold increase in catalytic efficiency over wild-type GCK. This work elucidates specific structural features responsible for generating allostery in a monomeric enzyme and suggests a general strategy for engineering cooperativity into proteins that lack the structural framework typical of traditional allosteric systems.
Recovery Block with Backup Voting: A New Pattern with Extended Representation for Safety Critical Embedded Systems

The concept of design patterns has been widely used in the software and hardware domain. Several fault tolerance patterns have been proposed to document widely used fault tolerance methods. In this paper, we propose a new software fault tolerance pattern, which is called recovery block with backup voting pattern. This pattern can be used to improve the software reliability of the classical recovery block pattern in applications in which the construction of an effective acceptance test can not be guaranteed. In order to represent the new pattern, we use a pattern representation that focuses on the nonfunctional consequences of the design patterns on safety critical embedded systems. These nonfunctional consequences contain: safety, reliability, modifiability, cost, and execution time. Among other side effects, the implications part of the new pattern shows that it is resulting in higher reliability than the classical recovery block with relatively low additional hardware cost.
Women Engineering Students’ Self Efficacy Beliefs – The Longitudinal Picture

Many sources and historical data have shown the consistently low representation of women in undergraduate engineering curricula and in the engineering workforce. Specifically, women comprise approximately only 20% of undergraduate engineering school enrollment nationwide and only about 8.5 % of the United State’s engineers 1 . Establishing WIE programs at approximately 50 colleges and universities around the United States has been one response to this situation 2 . WIE programs serve many functions, but their primary responsibilities focus on recruitment of women into engineering undergraduate programs and then retention and development of those same women within their programs of study. Initially, this may sound well defined, but the ways in which WIE programs work to accomplish these outcomes vary tremendously. For WIE programs to be maximally effective, they must have access to validated assessment instruments for measuring the effectiveness of their recruitment and retention activities for WIE studies. Such assessment results can provide the basis for the development and revamping of effective activities designed to meet program objectives and missions.