Miracle-dz/UniFAR-FTUs huggingface dataset:
Linear expected-time algorithms for connectivity problems (Extended Abstract)

Researchers in recent years have developed many graph algorithms that are fast in the worst case, but little work has been done on graph algorithms that are fast on the average. (Exceptions include the work of Angluin and Valiant [1], Karp [7], and Schnorr [9].) In this paper we analyze the expected running time of four algorithms for solving graph connectivity problems. Our goal is to exhibit algorithms whose expected time is within a constant factor of optimum and to shed light on the properties of random graphs. In Section 2 we develop and analyze a simple algorithm that finds the connected components of an undirected graph with n vertices in O(n) expected time. In Sections 3 and 4 we describe algorithms for finding the strong components of a directed graph and the blocks of an undirected graph in O(n) expected time. The time required for these three problems is Ω(m) in the worst case, where m is the number of edges in the graph, since all edges must be examined; but our results show that only O(n) edges must be examined on the average. *@@@@ In Section 5 we present an algorithm for finding a minimum weight spanning forest in an undirected graph with edge weights in O(m) expected time.
Interactive simulation of surgical cuts

Presents a framework for the interactive simulation of surgical cuts, such as those practiced in surgical treatment. Unlike most existing methods, our framework is based on tetrahedral volume meshes providing more topological flexibility. In order to keep the representation consistent, we apply adaptive subdivision schemes dynamically during the simulation. The detection of collisions between the surgical tool and the tissue is accomplished by using an axis-aligned bounding-box hierarchy which was adapted for deformable objects. For haptic rendering and feedback, we devised a mechanical scalpel model which accounts for the most important interaction forces between the scalpel and the tissue. The relaxation is computed using a localized, semi-implicit ODE (ordinary differential equation) solver. The achieved quality and performance of the presented framework is demonstrated using a human soft-tissue model.
The ELAV RNA-stability factor HuR binds the 5′-untranslated region of the human IGF-IR transcript and differentially represses cap-dependent and IRES-mediated translation

The type I insulin-like growth factor receptor (IGF-IR) is an integral component in the control of cell proliferation, differentiation and apoptosis. The IGF-IR mRNA contains an extraordinarily long (1038 nt) 5′-untranslated region (5′-UTR), and we have characterized a diverse series of proteins interacting with this RNA sequence which may provide for intricate regulation of IGF-IR gene expression at the translational level. Here, we report the purification and identification of one of these IGF-IR 5′-UTR-binding proteins as HuR, using a novel RNA crosslinking/RNase elution strategy. Because HuR has been predominantly characterized as a 3′-UTR-binding protein, enhancing mRNA stability and generally increasing gene expression, we sought to determine whether HuR might serve a different function in the context of its binding the IGF-IR 5′-UTR. We found that HuR consistently repressed translation initiation through the IGF-IR 5′-UTR. The inhibition of translation by HuR was concentration dependent, and could be reversed in trans by addition of a fragment of the IGF-IR 5′-UTR containing the HuR binding sites as a specific competitor, or abrogated by deletion of the third RNA recognition motif of HuR. We determined that HuR repressed translation initiation through the IGF-IR 5′-UTR in cells as well, and that siRNA knockdown of HuR markedly increased IGF-IR protein levels. Interestingly, we also found that HuR potently inhibited IGF-IR translation mediated through internal ribosome entry. Kinetic assays were performed to investigate the mechanism of translation repression by HuR and the dynamic interplay between HuR and the translation apparatus. We found that HuR, occupying a cap-distal position, significantly delayed translation initiation mediated by cap-dependent scanning, but was eventually displaced from its binding site, directly or indirectly, as a consequence of ribosomal scanning. However, HuR perpetually blocked the activity of the IGF-IR IRES, apparently arresting the IRES-associated translation pre-initiation complex in an inactive state. This function of HuR as a 5′-UTR-binding protein and dual-purpose translation repressor may be critical for the precise regulation of IGF-IR expression essential to normal cellular homeostasis.
Recent Advances in Optical Biosensors for Environmental Monitoring and Early Warning

The growing number of pollutants requires the development of innovative analytical devices that are precise, sensitive, specific, rapid, and easy-to-use to meet the increasing demand for legislative actions on environmental pollution control and early warning. Optical biosensors, as a powerful alternative to conventional analytical techniques, enable the highly sensitive, real-time, and high-frequency monitoring of pollutants without extensive sample preparation. This article reviews important advances in functional biorecognition materials (e.g., enzymes, aptamers, DNAzymes, antibodies and whole cells) that facilitate the increasing application of optical biosensors. This work further examines the significant improvements in optical biosensor instrumentation and their environmental applications. Innovative developments of optical biosensors for environmental pollution control and early warning are also discussed.
Automatic discovery of word semantic relations using paraphrase alignment and distributional lexical semantics analysis

Abstract Thesauri, which list the most salient semantic relations between words, have mostly been compiled manually. Therefore, the inclusion of an entry depends on the subjective decision of the lexicographer. As a consequence, those resources are usually incomplete. In this paper, we propose an unsupervised methodology to automatically discover pairs of semantically related words by highlighting their local environment and evaluating their semantic similarity in local and global semantic spaces. This proposal differs from all other research presented so far as it tries to take the best of two different methodologies, i.e. semantic space models and information extraction models. In particular, it can be applied to extract close semantic relations, it limits the search space to few, highly probable options and it is unsupervised.
The provenance and internal structure of the Cycladic Blueschist Unit revealed by detrital zircon geochronology, Western Cyclades, Greece

This study presents detrital zircon U‐Pb analyses of 23 samples of the Cycladic Blueschist Unit (CBU) from Kea, Kythnos, and Serifos islands, as well as the Lavrion Peninsula of SE Attica. The maximum depositional ages (MDA) and age distributions of detrital zircon U‐Pb dates are used to correlate metasediments between the islands considered herein and infer their provenance. Two distinct detrital zircon U‐Pb age distributions are found in CBU metasediments: “Proterozoic,” comprised of >40% Neoproterozoic zircons with Triassic‐Early Jurassic maximum depositional ages and “Paleozoic,” containing >30% Paleozoic zircons and yielding Late Jurassic‐Cretaceous MDAs. Proterozoic affinity metasediments are rift margin deposits derived from the northern Gondwanan margin. Paleozoic metasediments are flysch sediments most probably sourced from the Internal Hellenides. This metamorphosed flysch forms a distinct marker horizon found in a similar structural position in Lavrion, Kythnos, and Serifos. Based on lithologic correlation, sediment provenance, and MDA estimates, the CBU of Kythnos is correlative to the Lavrion Schists of Attica. On the islands of Serifos and Kythnos and within the Lavrion Schists only young‐on‐old relationships exist between rocks based on MDA estimates.
Detection of lines using hierarchical region based representation

This paper suggests an hierarchical region based representation to implement detection of shapes in gray-scale images. The max-tree structure has been demonstrated to be useful for this purpose, offering a semantic objects vision of the image, thereby reducing the number of elements to process in relation to the pixel based representation. In this way, particular thresholding information, associated with a specific shape analysis, can be used to determine the segmentation or filtering of regions of interest with less computational effort. To demonstrate this technique, a generic application of detection of lines is proposed using the distance transform approach on each connected component from the depth searching in the mentioned tree.
A multiprocessor real-time process scheduling method

Multimedia systems like video-on-demand systems require a good scheduling method to improve their services because of their real-time requirements. If such systems consist of multiple processors, then the scheduling problem becomes much important. Scheduling is an important problem for both computer science and operation research. It is proved that the complexity for scheduling problems is NP-complete and sometimes NP-hard depending on the constraints of the problems, implying the difficulties for finding a good scheduling approach. We propose a method for multiprocessor real-time scheduling algorithm applicable for both computer science and operation research. Our method is general enough to solve different scheduling problems such as wafer lot dispatching and scheduling for behaviors of a robot soccer player. There are scheduling problems exist in multimedia systems with real-time constraints, although the scheduling problems for multimedia systems have some unique characteristics differ from process scheduling, we believe the generality nature of our method facilitates the possibility of our scheduling method to be helpful for multimedia systems to solve scheduling problems after some minor modifications.
A mammalian expression vector for the expression of GAL4 fusion proteins with an epitope tag and histidine tail.

Expression of newly cloned cDNAs in mammalian cell lines is an essential tool for the functional analysis of the proteins encoded by these cDNAs. In many instances, however, evaluation of the protein is difficult because of the difficulty in purification of the expressed protein and/or the lack of specific antibodies which react with the proteins on Western blots or for immunocytochemistry or immunoprecipitation. A number of gene fusion systems have been employed in which a known peptide is fused to the expression product of interest and the fusion protein is purified using affinity chromatography and identified in extracts or by immunocytochemistry using antibodies directed against the affinity handle peptide. The DNA-binding domain of the yeast transcription factor GAL4 is widely used to construct fusion proteins with putative transcription factors to evaluate potential trans-acting domains. Because of the lack of commercially available anti-GAL4 antibodies, the further biochemical characterization of these fusion proteins has remained difficult. We describe the construction of two mammalian expression vectors, pMFH/GAL4 and pMFH2/GAL4 (where pMFH stands for pM2, Flag, Histidine tail), which encode the DNA-binding domain of the yeast transcription factor GAL4 with a Flag peptide (consisting of the 11-amino-acid leader peptide of the gene 10 product from bacteriophage T7) at the NH2-terminus and a tail of six histidines at the COOH-terminus. Unique restriction sites allow both the construction of fusion proteins with the GAL4 DNA-binding domain and the replacement of the GAL4 fragment with another insert. (ABSTRACT TRUNCATED AT 250 WORDS)
The Canada-France Redshift Survey XII: Nature of emission-line field galaxy population up to z = 0.3

We present a spectroscopic study of the 138 field galaxies to a redshift z = 0.3 from the I-selected Canada-France Redshift Survey. 117 (85%) spectra exhibit at least H� in emission, the remaining 21 (15%) are purely absorption-line spectra. We focus our analysis on spectra with Hand Hin emission, accounting for about half of this low- z sample, which we classify using emission-line ratio diagrams. Using photoionization models, we determine the extreme boundaries of H II galaxies in these diagnostic dia- grams, and demonstrate that the emission-line ratios of a significant fraction of galaxies require harder photoionization sources than massive O stars. We find that about 17% of the field galaxies have emission-line ratios consistent with active galaxies, e.g. Seyfert 2 or LINERs. After correcting for stellar absorption under the Balmer lines, we conclude that the fraction of such galaxies is at least 8% of the field galaxy population at z � 0.3.
Reduction in Pathogenic Biofilms by the Photoactive Composite of Bacterial Cellulose and Nanochitosan Dots under Blue and Green Light

In this study, nanochitosan dots (ChiDs) were synthesized using gamma rays and encapsulated in bacterial cellulose (BC) polymer matrix for antibiofilm potential in photodynamic therapy. The composites were analyzed for structural changes using SEM, AFM, FTIR, XRD, EPR, and porosity measurements. Additionally, ChiD release was assessed. The results showed that the chemical composition remained unaltered, but ChiD agglomerates embedded in BC changed shape (1.5–2.5 µm). Bacterial cellulose fibers became deformed and interconnected, with increased surface roughness and porosity and decreased crystallinity. No singlet oxygen formation was observed, and the total amount of released ChiD was up to 16.10%. Antibiofilm activity was higher under green light, with reductions ranging from 48 to 57% under blue light and 78 to 85% under green light. Methicillin-resistant Staphylococcus aureus was the most sensitive strain. The new photoactive composite hydrogels show promising potential for combating biofilm-related infections.
Error-correcting output hashing in fast similarity search

Fast similarity search is one of the key techniques in many large scale learning and data mining applications. Recently, hashing-based methods, which create compact and efficient codes that preserve data distribution, have received considerable attention due to their promising theoretical and empirical results. An ideal hashing method 1) can naturally have out-of-sample extension; 2) has very low computational complexity; and 3) has significant improvement over linear search in the original space in terms of accuracy. However, most existing hashing methods failed to satisfy all the above three requirements. In this paper, we propose a new method called Error-correcting Output Hashing (ECOH) which meets all the above three requirements. ECOH first groups all the samples into clusters using a conventional clustering algorithm. Each cluster is assigned an Error-Correcting Output Code (ECOC) and the linear mappings from the sample vectors to the ECOC are then learned using linear regression models. In this way, ECOH learns both the binary code for each sample and the function which links the input vector and the output code. Experimental results on real world data sets demonstrate the effectiveness and efficiency of the proposed approach.
Exploring the Role of First-Person Singular Pronouns in Detecting Suicidal Ideation: A Machine Learning Analysis of Clinical Transcripts

Linguistic features, particularly the use of first-person singular pronouns (FPSPs), have been identified as potential indicators of suicidal ideation. Machine learning (ML) and natural language processing (NLP) have shown potential in suicide detection, but their clinical applicability remains underexplored. This study aimed to identify linguistic features associated with suicidal ideation and develop ML models for detection. NLP techniques were applied to clinical interview transcripts (n = 319) to extract relevant features, including four cases of FPSP (subjective, objective, dative, and possessive cases) and first-person plural pronouns (FPPPs). Logistic regression analyses were conducted for each linguistic feature, controlling for age, gender, and depression. Gradient boosting, support vector machine, random forest, decision tree, and logistic regression were trained and evaluated. Results indicated that all four cases of FPSPs were associated with depression (p < 0.05) but only the use of objective FPSPs was significantly associated with suicidal ideation (p = 0.02). Logistic regression and support vector machine models successfully detected suicidal ideation, achieving an area under the curve (AUC) of 0.57 (p < 0.05). In conclusion, FPSPs identified during clinical interviews might be a promising indicator of suicidal ideation in Chinese patients. ML algorithms might have the potential to aid clinicians in improving the detection of suicidal ideation in clinical settings.
Geometrical face recognition after plastic surgery

Plastic surgeries alter the original facial features thereby posing a great challenge for face recognition algorithms. To address this problem, a geometrical face recognition after plastic surgery GFRPS system is proposed in this paper. The recognition process is performed in three steps; localising the regions of interest ROIs of the 'After' image, measuring the geometrical distances between the ROIs centres to determine the post-geometrical features vector, and using a minimum distance classifier to compare the post-features vector with the pre-features vectors database to find the perfect matching. The main advantage of the proposed system is its simplicity besides its high performance. The experimental results reveal that the proposed technique achieves much higher face identification rate than the best known results in the literature beside its high robustness under different types of plastic surgery procedures. The proposed technique provides average identification rate of 78.5% for local plastic surgery and 76.1% for global surgery.
Peer-to-peer simulation for improving the system of serving multimedia on the web

P2P networks are scalable in serving multimedia files over Internet which is in contrast to the centralized client-server system in which the server provides all the resources to the clients. In this research, we have designed and implemented a Peer-to-Peer network simulator to efficiently serve multimedia on the Internet considering that P2P streaming applications scale very superior even in large crowd scenarios. Simulated data was used to conduct experiment from current popular multimedia serving websites such as YouTube. We have then simulated user traffic by using the P2P system to compare the performance result with the traditional Client-Server system.
Stein's Method of Exchangeable Pairs with Application to the Curie-Weiss Model

Let (W,W ′) be an exchangeable pair. Assume that E(W − W ′|W ) = g(W ) + r(W ), where g(W ) is a dominated term while r(W ) is negligible. Let G(t) = ∫ t 0 g(s)ds and define p(t) = c1e −c0G(t), where c0 is a properly chosen constant and c1 = 1/ ∫∞ −∞ p(t)dt . Let Y be a random variable with the probability density function p. In this talk we shall proved that W converges to Y in distribution under certain regular conditions. A Berry-Esseen type bound is also given. An application to the Curie-Weiss model will be discussed. The talk is based on a joint work with Sourav Chatterjee.
An upper limit for slow earthquakes zone: self-oscillatory behavior through the Hopf bifurcation mechanism from a model of spring-block under lubricated surfaces

The complex oscillatory behavior of a springblock model is analyzed via the Hopf bifurcation mechanism. The mathematical springblock model is generated by considering the Dieterich–Ruinas's friction law and the Stribeck's effect. The existence of self-sustained oscillations in the transition zone – where slow earthquakes are generated within the frictionally unstable region – is determined. An upper limit for this region is proposed as a function of seismic parameters and frictional coefficients which are concerned with presence of fluids in the system. The importance of the characteristic length scale L , the implications of fluids, and the effects of external perturbations in the complex dynamic oscillatory behavior as well as in the stationary solution, are take into consideration.
Using the R Commander: A Point-and-Click Interface for R

The R Commander (Rcmdr, Fox 2005) is a graphical user interface (GUI) front end for R (R Core Team 2016). The aims of the R Commander are to provide a cross-platform GUI front end to R that is easy to use. The range of commands available are appropriate for a basic statistics course and some intermediate subjects, e.g., generalized linear models, are covered. Currently most of the resources for the R Commander are online tutorials (Karp 2010) and short online articles (Fox and Bouchet-Valat 2015). There are some books, that dedicate a chapter to this topic (Larson-Hall 2015), but Using the R Commander: A Point-and-Click Interface for R is the first book in English,1 that I am aware of, which is dedicated specifically to the R Commander. This book, part of The R Series by Chapman & Hall/CRC Press, is written by John Fox, the R Commander software developer. Fox explains his motivation in the preface, “I felt that R’s command line was an obstacle. I expected that eventually someone would introduce a graphical interface to R, but none materialized. ” So he started on the project himself. Chapter 1: The book starts with a quick explanation of R and the R Commander, including a historical context and an explanation of the book’s overall structure. The next chapter gives detailed instructions to downloading and installing the R Commander on Windows, Mac and Linux systems. This includes troubleshooting advice and running tips for each system. These tips are useful, however this is the kind of information that will soon be out of date. Chapter 3 gives A Quick Tour of the R Commander. This chapter introduces the GUI menu system to new users. The book kicks off in earnest with the importing of data in delimited text format. There follows a worked example including data manipulation, summary statistics and graphics. A key feature of the R Commander is that all of the point-and-click commands generate R code. The resulting R commands and output can be saved and edited and re-run later and can be used as a stepping stone to learning R commands. At the end of the chapter
Data Fusion Estimation of Inertial Sensors Based on Multiscale Stochastic Dynamic Models

In the paper, combing with discrete wavelet transform, dynamic system theory and stochastic process theory establish multiscale stochastic dynamic models considering scale as variable and present multiscale fusion estimation algorithm in order to realize the optimum estimation of the state. The algorithm may be a method used in no state model. Using the algorithm for gyro signals processing and fusing the observation at different scales, the accuracy is improved obviously. Simulation and test all prove that the algorithm is available.
Analysis of JavaScript Web Applications Using SAFE 2.0

JavaScript has been the language for web applications, and the growing prevalence of web environments in various devices makes JavaScript web applications even more ubiquitous. However, because JavaScript and web environments are extremely dynamic, JavaScript web applications are often vulnerable to type-related errors and security attacks. To lessen the problem, researchers have developed various analysis techniques in different analyzers, but such analyzers are not especially aimed for ease of use by analysis developers. In this paper, we present SAFE 2.0, a scalable analysis framework for ECMAScript especially designed as a playground for advanced research in JavaScript web applications. SAFE 2.0 is light-weight, which supports pluggability, extensibility, and debuggability. Demo video: https://youtu.be/ZI_emiRMoxQ.