Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting conversing groups of chatters: a model, algorithms, and tests

Chatrooms, for example Internet Relay Chat, are generally multi-user, multi-channel and multiserver chat-systems which run over the Internet and provide a protocol for real-time text-based conferencing between users all over the world. While a well-trained human observer is able to understand who is chatting with whom, there are no efficient and accurate automated tools to determine the groups of users conversing with each other. A precursor to analysing evolving cyber-social phenomena is to first determine what the conversations are and which groups of chatters are involved in each conversation. We consider this problem in this paper. We propose an algorithm to discover all groups of users that are engaged in conversation. Our algorithms are based on a statistical model of a chatroom that is founded on our experience with real chatrooms. Our approach does not require any semantic analysis of the conversations, rather it is based purely on the statistical information contained in the sequence of posts. We improve the accuracy by applying some graph algorithms to clean the statistical information. We present some experimental results which indicate that one can automatically determine the conversing groups in a chatroom, purely on the basis of statistical analysis.
Electroacupuncture Zusanli (ST36) on Release of Nitric Oxide in the Gracile Nucleus and Improvement of Sensory Neuropathies in Zucker Diabetic Fatty Rats

The purpose of these studies was to examine the effects of electroacupuncture (EA) Zusanli (ST36) on release of nitric oxide (NO) in the gracile nucleus (GN) and determine if functional neuropathic changes were modified by EA ST36-induced NO in the nucleus in Zucker diabetic fatty (ZDF) rats. The foot withdrawal responses to mechanical, thermal and cold stimuli were measured before and after EA stimulation. A microdialysis probe was implanted in the GN and dialysate samples were collected 20 min before, during and after EA ST36. Total nitrate and nitrite (NOx −) concentrations in the samples were quantified by using chemiluminescence. The baseline dialysate NOx − concentrations in the GN were decreased in ZDF rats compared to lean control (LC) rats (P < .05). In ZDF rats, dialysate NOx − releases in the GN were markedly increased during EA ST36, whereas in LC rats, the releases were moderately enhanced at 20–40 min after EA ST36. The withdrawal latencies to mechanical, cold and thermal stimuli were significantly improved 20 min after EA ST36 both in LC and ZDF rats, but not altered by non-acupoint stimulation. The withdrawal latencies to EA ST36 were further potentiated by 3-morpholinyl-sydnoneimine and inhibited by NG-Propyl-l-arginine infused into the GN in ZDF rats (P < .05). These results show that EA ST36 increases NO release in the GN, and NO in the nucleus modifies withdrawal latencies to mechanical, cold, and thermal nociception stimuli. Data suggest that EA ST36 induces NO release in the GN, which contributes to improvement of sensory neuropathies in rats.
Exotoxin A production in Pseudomonas aeruginosa requires the iron‐regulated pvdS gene encoding an alternative sigma factor

Exotoxin A (ETA) is secreted by Pseudomonas aeruginosa under iron‐limiting growth conditions. The ETA structural gene, toxA, is regulated at the transcriptional level by the gene products of the regAB operon. The expression of both toxA and regAB is repressed under iron‐replete conditions, suggesting a role for the ferric uptake regulator (Fur) in regulation of ETA synthesis; however, the Fur protein does not interact directly with the toxA or the regAB promoters. Evidence is presented that the iron control of ETA synthesis is mediated by a Fur‐regulated alternative sigma factor, PvdS, which had initially been identified as a positive activator for the production of the siderophore pyoverdin. In a ΔpvdS deletion mutant, ETA was produced at low levels of less than 5% compared to wild type, but still in response to iron starvation, and introduction of a functional pvdS gene on a plasmid fully restored wild‐type levels and normal iron regulation of ETA synthesis. Therefore, a functional pvdS locus is essential for ETA production. Neither toxA nor regAB mRNA was detectable in a ΔpvdS mutant. Overexpression of pvdS from the tac promoter on a plasmid resulted in a high‐level and iron‐independent production of ETA in wild‐type PAO1, in the ΔpvdS strain, but not in a ΔregA strain as a host. These findings suggest that PvdS is required for the activation of the regAB promoters. The transcription of regAB and toxA after induction of the Ptac–pvdS gene was monitored in cells grown in high‐iron medium. While both regAB and toxA were highly expressed during all growth phases under microaerobic conditions, toxA transcripts were detected only during the exponential but not the early stationary phase of growth under aerobic conditions. These results suggest that a second regulatory mechanism besides the Fur–PvdS system is involved in iron regulation of ETA production.
Low-Rank Matrix Approximation Using Point-Wise Operators

The problem of extracting low-dimensional structure from high-dimensional data arises in many applications such as machine learning, statistical pattern recognition, wireless sensor networks, and data compression. If the data is restricted to a lower dimensional subspace, then simple algorithms using linear projections can find the subspace and consequently estimate its dimensionality. However, if the data lies on a low-dimensional but nonlinear space (e.g., manifolds), then its structure may be highly nonlinear and, hence, linear methods are doomed to fail. In this paper, we introduce a new technique for dimensionality reduction based on point-wise operators. More precisely, let be a matrix of rank and assume that the matrix is generated by taking the elements of to some real power . In this paper, we show that based on the values of the data matrix , one can estimate the value and, therefore, the underlying low-rank matrix ; i.e., we are reducing the dimensionality of by using point-wise operators. Moreover, the estimation algorithm does not need to know the rank of . We also provide bounds on the quality of the approximation and validate the stability of the proposed algorithm with simulations in noisy environments.
Relevance of Laser Doppler and Laser Speckle Techniques for Assessing Vascular Function: State of the Art and Future Trends

In clinical and research applications, the assessment of vascular function has become of major importance to evaluate and follow the evolution of cardiovascular pathologies, diabetes, hypertension, or foot ulcers. Therefore, the development of engineering methodologies able to monitor noninvasively blood vessel activities-such as endothelial function-is a significant and emerging challenge. Laser-based techniques have been used to respond-as much as possible-to these requirements. Among them, laser Doppler flowmetry (LDF) and laser Doppler imaging (LDI) were proposed a few decades ago. They provide interesting vascular information but possess drawbacks that prevent an easy use in some clinical situations. Recently, the laser speckle contrast imaging (LSCI) technique, a noninvasive camera-based tool, was commercialized and overcomes some of the LDF and LDI weaknesses. Our paper describes how-using engineering methodologies-LDF, LDI, and LSCI can meet the challenging clinician needs in assessing vascular function, with a special focus on the state of the art and future trends.
A View on Despeckling in Ultrasound Imaging

Ultrasound imaging is a widely used and safe medical diagnostic technique, due to its noninvasive nature, low cost and capability of forming real time imaging. However the usefulness of ultrasound imaging is degraded by the presence of signal dependant noise known as speckle. The speckle pattern depends on the structure of the image tissue and various imaging parameters. There are two main purposes for speckle reduction in medical ultrasound imaging (1) to improve the human interpretation of ultrasound images (2) despeckling is the preprocessing step for many ultrasound image processing tasks such as segmentation and registration. A number of methods have been proposed for speckle reduction in ultrasound imaging. While incorporating speckle reduction techniques as an aid for visual diagnosis, it has to keep in mind that certain speckle contains diagnostic information and should be retained. The objective of this paper is to give an overview about types of speckle reduction techniques in ultrasound imaging 1. Importance of ultrasound Imaging ULTRASOUND imaging application in medicine and other fields is enormous. It has several advantages over other medical imaging modalities. The use of ultrasound in diagnosis is well established because of its noninvasive nature, low cost, capability of forming real time imaging and continuing improvement in image quality. It is estimated that one out of every four medical diagnostic image studies in the world involves ultrasonic techniques. US waves are characterized by frequency above 20 KHz which is the upper limit of human hearing. In medical US applications, frequencies are used between 500 KHz and 30 MHz B-mode imaging is the most used modality in medical US. An US transducer which is placed onto the patient's skin over the imaged region sends an US pulse which travels along a beam into the tissue. Due to interfaces some of the US energy is reflected back to the transducer which converts it into echo signals. These signals are then sent into amplifiers and signal processing circuits in the imaging machine's hardware to form a 2-D image. This process of sending pulses launched in different directions is repeated in order to examine the whole region in the body. Thus, US imaging involves signals which are obtained by coherent summation of echo signals from scatterers in the tissue. In many cases volume quantification is important in assessing the progression of diseases and tracking progression of response to treatment. Thus, 3D ultrasound imaging has drawn great attention in recent years. 2. Ultrasound Imaging System
Modeling Transport And Protein Adsorption In Microfluidic Systems

Mass transport limitations and surface interactions are important phenomena in microfluidic devices. The flow of water is laminar at small scales and the absence of turbulent mixing can lead to transport limitations, especially for reactions that take place at surfaces. Microscale devices have a high ratio of surface area to volume, and proteins are known to adsorb preferentially at interfaces. Protein adsorption plays a significant role in biology by mediating critical processes such as the attachment of cells to surfaces, the immune response and the coagulation of blood. Simulation tools that can quantitatively predict transport and protein adsorption will enable the rational design of microfluidic devices for biomedical applications. Two-dimensional random sequential adsorption (RSA) models are widely used to model the adsorption of proteins on surfaces. As Brownian dynamics simulations have become popular for modeling protein adsorption, the interface model has changed from two-dimensional to three-dimensional. Brownian dynamics simulations were used to model the diffusive transport of hard-sphere particles in a liquid and the adsorption of the particles onto a uniform surface. The configuration of the adsorbed particles was analyzed to quantify the chemical potential near the surface, which was used to derive a continuum model of adsorption that incorporates the results from the Brownian dynamics simulations. The equations of the continuum model were discretized and coupled to a conventional computational fluid dynamics (CFD) simulation of diffusive transport to the surface. The kinetics of adsorption
Building a Linguistically Interpreted Corpus of Bulgarian: the BulTreeBank

In the field of Human Language Technology (HLT), the existence of linguistically interpreted real-world texts provides the license necessary for a given language to enter the area of high-tech applications. The significance of BulTreeBank is the granting of an HLT license to a “less processed” language like Bulgarian which, until recently, has been formally modelled and processed mainly on the morphology level. The BulTreeBank project aims at the creation of syntactically annotated data for Bulgarian and the tools for their production, management and automatic processing. It provides not only language resources, but develops an infrastructure of research solutions, production scenarios and services.
Securing Network Content

The goal of the current Internet is to provide content of interest (Web pages, voice, video, etc.) to the users that need it. Access to that content is achieved using a communication model designed in terms of connections between hosts. This conflation of what content you want to access with where (on what host) that content resides extends throughout current network protocols, and determines the context in which they offer network security. Trust in content – that it is the desired content, from the intended source, and unmodified in transit – is determined by where (from what host) and how (over what kind of connection) the content was retrieved. A user believes they are reading the news from the New York Times when they access it via a user-friendly name for the authoritative source of that news – www.nytimes. com; whether guessed, known, or obtained from a trusted directory (Google) in response to a few relevant search terms. Implicitly, they are also trusting that a) the DNS has given them a reliable indicator of where to find a host authorized to “speak for” the name they are interested in, b) they have actually made an HTTP connection to that host or its delegate (such as a content distribution network, or CDN) and c) that the content retrieved over that connection is unaltered by any unauthorized intermediary.1 A user accessing a higher-value resource, say their bank account, may do so with confidence only over a connection further authenticated by a cryptographic protocol such as TLS [10]. This gives them assurance that not only is the data coming from the intended source (as determined by the trust model for evaluating digital certificates built into their software client), and that it has not been tampered with in transit, but additionally that it may be protected from eavesdropping by encryption. This connection-focused approach to security inex-
Iterational retiming with partitioning: Loop scheduling with complete memory latency hiding

The widening gap between processor and memory performance is the main bottleneck for modern computer systems to achieve high processor utilization. To hide memory latency, a variety of techniques have been proposed—from intermediate fast memories (caches) to various prefetching and memory management techniques. In this article, we propose a new loop scheduling with memory management technique, Iterational Retiming with Partitioning (IRP), that can completely hide memory latencies for applications with multidimensional loops on architectures like CELL processor. In IRP, the iteration space is first partitioned carefully. Then a two-part schedule, consisting of processor and memory parts, is produced such that the execution time of the memory part never exceeds the execution time of the processor part. These two parts are executed simultaneously and complete memory latency hiding is reached. In this article, we prove that such optimal two-part schedule can always be achieved given the right partition size and shape. Experiments on DSP benchmarks show that IRP consistently produces optimal solutions as well as significant improvement over previous techniques.
Dialect identification using Gaussian mixture models

Recent results in the area of language identification have shown a significant improvement over previous systems. In this paper, we evaluate the related problem of dialect identification using one of the techniques recently developed for language identification, the Gaussian mixture models with shifted-delta-cepstral features. The system shown is developed using the same methodology followed for the language identification case. Results show that the use of the GMM techniques yields an average of 30% equal error rate for the dialects in the Miami corpus and about 13% equal error rate for the dialects in the CallFriend corpus.
Comparative evolutionary diversity and phylogenetic structure across multiple forest dynamics plots: a mega-phylogeny approach

Forest dynamics plots, which now span longitudes, latitudes, and habitat types across the globe, offer unparalleled insights into the ecological and evolutionary processes that determine how species are assembled into communities. Understanding phylogenetic relationships among species in a community has become an important component of assessing assembly processes. However, the application of evolutionary information to questions in community ecology has been limited in large part by the lack of accurate estimates of phylogenetic relationships among individual species found within communities, and is particularly limiting in comparisons between communities. Therefore, streamlining and maximizing the information content of these community phylogenies is a priority. To test the viability and advantage of a multi-community phylogeny, we constructed a multi-plot mega-phylogeny of 1347 species of trees across 15 forest dynamics plots in the ForestGEO network using DNA barcode sequence data (rbcL, matK, and psbA-trnH) and compared community phylogenies for each individual plot with respect to support for topology and branch lengths, which affect evolutionary inference of community processes. The levels of taxonomic differentiation across the phylogeny were examined by quantifying the frequency of resolved nodes throughout. In addition, three phylogenetic distance (PD) metrics that are commonly used to infer assembly processes were estimated for each plot [PD, Mean Phylogenetic Distance (MPD), and Mean Nearest Taxon Distance (MNTD)]. Lastly, we examine the partitioning of phylogenetic diversity among community plots through quantification of inter-community MPD and MNTD. Overall, evolutionary relationships were highly resolved across the DNA barcode-based mega-phylogeny, and phylogenetic resolution for each community plot was improved when estimated within the context of the mega-phylogeny. Likewise, when compared with phylogenies for individual plots, estimates of phylogenetic diversity in the mega-phylogeny were more consistent, thereby removing a potential source of bias at the plot-level, and demonstrating the value of assessing phylogenetic relationships simultaneously within a mega-phylogeny. An unexpected result of the comparisons among plots based on the mega-phylogeny was that the communities in the ForestGEO plots in general appear to be assemblages of more closely related species than expected by chance, and that differentiation among communities is very low, suggesting deep floristic connections among communities and new avenues for future analyses in community ecology.
FSMA - A Topology-Transparent Scheme for Opportunistic Spectrum Access

With the advent of cognitive radio technology, new paradigms for spectrum access can achieve near-optimal spectrum utilization by letting users sense and utilize available spectrum opportunistically. Recently, graph-coloring models have been used to produce fair, efficient and optimal spectrum allocations for a given network topology. However, topology changes (e.g., due to user mobility) can incur significant signaling traffic to reallocate spectrum, consuming valuable resources. We propose a frequency-spread multiple access (FSMA) scheme that is topology-transparent, and numerical results suggest that it is suited for opportunistic spectrum access in a sparsely-connected, low-density mobile ad-hoc network.
Over-expression of HER-2 is associated with the stage in carcinomas of the urinary bladder

Background The frequency of over-expression of human epidermal growth factor receptor-2 (HER-2) in bladder cancer is one of the highest among all human malignancies. This over-expression is thought to play a role in aberrant proliferation of cancer cells. Studies on HER-2 expression in bladder carcinoma have shown heterogeneous results. Purpose The aim of the study was to evaluate the status of HER-2 protein expression in patients with invasive carcinomas of the urinary bladder as related to tumor grade and stage. Materials and methods Archival samples from 39 patients (6 women, 33 males) with urinary bladder cancer were analyzed for HER-2 over-expression, using immunohistochemistry with the HercepTest. Results HER-2 over-expression was observed in 23/39 tumors (59%) and was more frequent in high-grade than in low-grade carcinomas, but the difference was not statistically significant. A significant correlation was established between HER-2 over-expression and tumor stage (p=0.011). HER-2 expression was more frequent in transitional cell carcinomas (TCC) and adenocarcinomas (AC) as compared with squamous cell carcinoma (SCC). Patients’ age and sex were not related to HER-2 over-expression. Conclusion Over-expression of HER-2 was frequent in carcinomas of the urinary bladder. Knowing the HER-2 status would be helpful in formulating a rational treatment strategy for patients with urinary bladder cancer.
A compression/decompression method for streaming based humanoid animation

In VRML, a modeling language for describing 3D objects on the internet, the specification to realize lifelike movement of a 3D character with a skeletal structure (such as a human) has been standardized as VRML Humanoid Animation Ver.1. 0 (H-Anim Ver.1.0) in the H-Anim WG of the VRML Consortium. To extend this specification, we suggest a method that makes it possible to send/receive motion data in real time on a network with narrow bandwidth such as a telephone line. Moreover, by sending the motion data with streaming data from server to client, the time required before playback can be greatly reduced. This technology uses basic techniques that can be applied widely to webbased 3D applications, broadcasting contents etc.
Real Time Traffic Signboard Detection and Recognition from Street Level Imagery for Smart Vehicle

The text or symbol detection and recognition from traffic panels is a challenging problem. Number of important application areas is dependent on text detection and recognition, including advanced driver assistance systems, road surveying, and autonomous vehicles. In this research project a novel system for the automatic detection and recognition of text and symbol in traffic signs is proposed. Search regions with in the image must be defined. In this particular region locate a large number of candidates, which are then reduced by applying constraints based on temporal and structural information. This problem can be divided in two stages; First stage will be detection of region and second will be character recognition. The detection stage exploits knowledge of the structure of the scene, the size and location of the road in the frame. Once a potential traffic panels has been located, the next stage attempts to recognize text and symbols within the region. For the purpose of text detection MSER is used and for recognition purpose optical Character Recognition method is used. Automatic testing using XML files provide better accuracy.