Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of URI Nuclear Interaction with RPB5 and Components of the R2TP/Prefoldin-Like Complex

Unconventional prefoldin RPB5 Interactor (URI) was identified as a transcriptional repressor that binds RNA polymerase II (pol II) through interaction with the RPB5/POLR2E subunit. Despite the fact that many other proteins involved in transcription regulation have been shown to interact with URI, its nuclear function still remains elusive. Previous mass spectrometry analyses reported that URI is part of a novel protein complex called R2TP/prefoldin-like complex responsible for the cytoplasmic assembly of RNA polymerase II. We performed a mass spectrometry (MS)-based proteomic analysis to identify nuclear proteins interacting with URI in prostate cells. We identified all the components of the R2TP/prefoldin-like complex as nuclear URI interactors and we showed that URI binds and regulates RPB5 protein stability and transcription. Moreover, we validated the interaction of URI to the P53 and DNA damage-Regulated Gene 1 (PDRG1) and show that PDRG1 protein is also stabilized by URI binding. We present data demonstrating that URI nuclear/cytoplasmic shuttling is affected by compounds that stall pol II on the DNA (α-amanitin and actinomycin-D) and by leptomycin B, an inhibitor of the CRM1 exportin that mediates the nuclear export of pol II subunits. These data suggest that URI, and probably the entire R2TP/prefoldin-like complex is exported from the nucleus through CRM1. Finally we identified putative URI sites of phosphorylation and acetylation and confirmed URI sites of post-transcriptional modification identified in previous large-scale analyses the importance of which is largely unknown. However URI post-transcriptional modification was shown to be essential for URI function and therefore characterization of novel sites of URI modification will be important to the understanding of URI function.
Vector-space topic models for detecting Alzheimer’s disease

Semantic deﬁcit is a symptom of language impairment in Alzheimer’s disease (AD). We present a generalizable method for automatic generation of information content units (ICUs) for a picture used in a standard clinical task, achieving high recall, 96.8%, of human-supplied ICUs. We use the automatically generated topic model to extract semantic features, and train a random forest classiﬁer to achieve an F-score of 0.74 in binary classiﬁcation of controls versus people with AD using a set of only 12 features. This is comparable to re-sults (0.72 F-score) with a set of 85 manual features. Adding semantic information to a set of standard lexicosyntactic and acoustic features improves F-score to 0.80. While control and dementia subjects discuss the same topics in the same contexts, controls are more informative per second of speech.
Bean yellow mosaic virus infecting broad bean in the green belt of Córdoba, Argentina

Broad bean (Vicia faba L) is the fourth most important pulse crop in the world. In Argentina, broad bean production was of 1,841 hectares and 16,500 tons during the 2017 growing season. Broad bean is commonly used in rotations; especially by farmers located in “green belts” that are peri-urban areas surrounding large cities that include horticultural family farms. Plants showing marked foliar mosaic symptoms, typical of viral infection, were collected during the 2015 growing season in the green belt of Córdoba city, Argentina. Preparations of symptomatic tissues were mechanically inoculated onto healthy broad bean plants in the greenhouse, which developed symptoms similar to those observed in the field. In addition, symptomatic samples were positive when tested by indirect ELISA with the anti-potyvirus group monoclonal antibody. Further, flexuous filamentous particles typical of potyviruses were observed under the electronic microscope on dip preparations. Lastly, total RNA was extracted from a symptomatic leaf and high-throughput sequenced, which allowed the assembly of a single virus sequence corresponding to a new highly divergent strain of Bean yellow mosaic virus (BYMV). Phylogenetic insights clustered this Argentinean broad bean isolate (BYMV-ARGbb) within group IX of BYMV. Given the economical importance of this virus and its associated disease, the results presented here are a pivotal first step oriented to explore the eventual incidence and epidemiological parameters of BYMV in broad bean in Argentina.
Development and psychometric properties of the Geriatric Mistreatment Scale

Aim: Elder mistreatment is a phenomenon that has increased proportionally to the increase in the number of older adults in different populations of the world. So far, in Mexico there is no instrument measuring and assessing this phenomenon. The objective of the present study was to develop and to know some psychometric properties of the Geriatric Mistreatment Scale (GMS).
An introduction to silanes and their clinical applications in dentistry.

PURPOSE This overview presents a description of organofunctional trialkoxysilane coupling agents (silanes), their chemistry, properties, use, and some of the main clinical experiences in dentistry. MATERIALS AND METHODS The main emphasis was on major dental journals that have been reviewed from 1958 up to the latest research news from 2002. A MEDLINE search with the key words "dental silanes" was used. Special silane literature and journals outside dentistry were also cited. RESULTS The main emphasis is on the use of silanes in prosthetic and restorative dentistry. Clinical relevance was based mainly on either short- or long-term tests. The interpretation of various results is not given, mainly because of controversial observations that may be very difficult to explain. Nevertheless, the majority of the clinical results pointed to silanes playing a significant role in the adhesion process. Silane reaction mechanisms were not entirely understood, and there exist several theories for bonding mechanisms for silanes and substrates. CONCLUSION Dental materials offer a continuously challenging forum for silanes, and silanes will play an essential role in material development.
Building adaptive defense against cybercrimes using real-time data mining

In today's fast changing world, cybercrimes are growing at perturbing pace. At the very definition of it, cybercrimes get engendered by capitalizing on threats and exploitation of vulnerabilities. However, recent history reveals that such crimes often come with surprises and seldom follow the trends. This puts the defense systems behind in the race, because of their inability to identify new patters of cybercrime and to ameliorate to the required levels of security. This paper visualizes the empowerment of security systems through real-time data mining by the virtue of which these systems will be able to dynamically identify patterns of cybercrimes. This will help those security systems stepping up their defense capabilities, while adapting to the required levels posed by newly germinating patterns. In order to confine within scope of this paper, the application of this approach is being discussed in the context of selected scenarios ofcybercrime.
Eurographics/ Acm Siggraph Symposium on Computer Animation (2006) Fast Arbitrary Splitting of Deforming Objects

We present a novel algorithm for efficiently splitting deformable solids along arbitrary piecewise linear crack surfaces in cutting and fracture simulations. We propose the use of a meshless discretization of the deformation field, and a novel visibility graph for fast update of shape functions in meshless discretizations. We decompose the splitting operation into a first step where we synthesize crack surfaces as triangle meshes, and a second step where we use the newly synthesized surfaces to update the visibility graph, and thus the meshless discretization of the deformation field. The separation of the splitting operation into two steps, along with our novel visibility graph, enables high flexibility and control over the splitting trajectories, provides fast dynamic update of the meshless discretization, and facilitates an easy implementation, making our algorithm scalable, versatile, and suitable for a large range of applications, from computer animation to interactive medical simulation.
Effect of Cerium addition on microstructure and mechanical properties of 4004 aluminum alloy

The effects of Cerium addition on the microstructure and mechanical properties of 4004 aluminum alloy were investigated. The results showed that Cerium(Ce) addition can improve mechanical properties and microstructure of 4004 aluminum alloy when the percentage of Ce is below 2.0%. The best tensile properties, in which ultimate tensile strength was 220MPa and elongation was 5.6%, were obtained when the addition of Cerium were 2.0%. Meanwhile, tensile fracture slightly reveals ductile fracture. However, tensile strength and elongation decreases when Cerium content was above 2.0%.
Hypoglycemic Activity of Tilia americana, Borago officinalis, Chenopodium nuttalliae, and Piper sanctum on Wistar Rats

Diabetes mellitus (DM) is considered the epidemic of the 21st century. Traditional medicine uses plants to treat DM; many of these have hypoglycemic effects in both animal models and diabetic patients. Our objective was to evaluate the hypoglycemic activity of Tilia americana, Borago officinalis, Chenopodium nuttalliae, and Piper sanctum on diabetic rats. The methanolic extracts of the plants under study were obtained by Soxhlet extraction. Toxicity was evaluated on Artemia salina; the antioxidant potential was evaluated using the DPPH technique. Hypoglycemic capacity at doses of 250 and 500 mg/kg was tested on Wistar rats with diabetes induced by alloxan (120 mg/kg). The toxicity on A. salina was null for the extracts of B. officinalis and P. sanctum, moderate for T. americana, and highly toxic for C. nuttalliae. The relevant extract of T. americana var. mexicana showed antioxidant activity. Three plants of the studied plants showed hypoglycemic activity: Tilia Americana (p = 0.0142), Borago officinalis (p = 0.0112), and Piper sanctum (p = 0.0078); P. sanctum was the one that showed the greatest reduction in glucose levels at a lower dose.
Direct triangle extraction by a randomized Hough technique

The macro features, such as triangle, quadrilateral, polygon, play a very important role in many computer vision applications such as matching, visual inspection, object tracking. However, effective ways to extract such macro features from images are still not available in the literature up to now. Worse, there are few reports on the matter. The paper proposes a randomized Hough technique to directly extract general triangles (i.e., with unknown size and orientation) from images. Extensive simulations as well as experiments with real images show that the results are satisfactory.
APPLICATION COMMUNICATION EMULATION FOR PERFORMANCE MANAGEMENT OF NOW CLUSTERS

Performance management of clusters and grids poses many challenges. The sharing of a large distributed set of resources can provide efficiencies, but it also introduces complexity in terms of providing and maintaining adequate performance. Current application requirements focus on the amount of resources needed without explicitly characterizing the performance required from those resources. In clusters and Grids, inconsistent or highly variable run-time of applications is an indication of systemic inconsistency and is an issue with implications for those running the application as well as those managing the resources. We are focusing on the contribution of the interconnection network to application run-time variability. This work presents experimental results characterizing parallel application run-time sensitivity to communication performance variability using an Application Communication Emulator (ACE).
Communication Patterns Within a Group of Shelter Dogs and Implications for Their Welfare

Keeping shelter dogs in groups provides them with a more socially and physically enriched environment, but eventually it may cause them stress. Understanding dogs' communication could help shelter staff recognize and prevent undesirable communicative patterns and encourage desirable ones. Therefore, the objective of this study was to determine communication patterns in a group of dogs in a shelter. The observed dogs were engaged in different classes of dyadic and group interactions. Certain dogs were frequently initiators of dyadic interactions, and different dogs were the recipients. The predominant form of dyadic interactions was a neutral one, and aggressive behavior was rarely observed. The tendency of certain dogs to interact continuously may represent a nuisance for less social individuals. All of the dogs participated in 3 defined classes of group interactions. At the group level, the dogs frequently interact vocally or olfactorily. A major welfare problem may be very vocal dogs because their vocalizations are noisy and broadcast far-reaching signals. The frequency of some group interactions was reduced by the amount of time the dogs had in the shelter.
Smart Grid Wireless Network Security Requirements Analysis

Power grids are being enhanced by integrating the Information and Communication Technology (ICT) to make them more reliable, economic, efficient, and environmentally friendly. The integration of power grids with ICT to build Smart Grids (SGs) has reduced costs and improved their performances. But, on the other hand, this has also brought the cyber security threats as well. In traditional ICT systems, the end devices are the powerful systems which have high computation power and memory capacity to perform the intense computations to avoid cyber security threats, whereas most of the end devices in SG lack these capabilities. Incorporating the security in the early stages of SG development through systems security requirements engineering can reduce the potential cyber security threats. This paper presents the results of applying Security Requirements Engineering Process (SREP) on the SG wireless network, and proposes the potential solutions that can be implemented such as using Global System for Mobile Communication (GSM)-enabled Intelligent Electronic Devices (IEDs) with Global Positioning System (GPS) support.
WiFace: a secure geosocial networking system using WiFi-based multi-hop MANET

A number of mobile online social networking (OSN) services appear in the market. Majority of mobile systems can strongly benefit from services offered by cloud. However, centralized servers and communication infrastructures may not always be available. Further their location-based services are not offered to low-end mobile devices without GPS modules. To build a system that can take advantage of cloud, and also can address these potential problems that could hinder OSN usage, we design and construct a multi-hop networking system named MoNet based on WiFi, and on top of which we design and implement WiFace, a privacy-aware geosocial networking service. For the situation without any infrastructure, we design a distributed content sharing protocol which can significantly shorten the relay path, reduce conflicts and improve data persistence and availability. A role strategy is designed to encourage users to collaborate in the network. Furthermore, a key management and an authorization mechanism are developed to prevent some attacks and protect privacy. We conduct comprehensive experiments to evaluate the performance of our mobile platform MoNet and application WiFace. The results show that MoNet is more than sufficient to support social networking, and even audio and video applications.
Variations of Sex Hormones across the Menstrual Cycle: Correlations to Depressive Symptoms, Hostility, Lipidemic and Haemostatic Factors

Background: Exogenous sex hormones affect lipid metabolism and haemostasis, as well as psychological aspects of the personality but the information on the interrelationships regarding the endogenous hormones is limited.Objective: In the present study we examined the association between sex hormones, lipidemic profile, haemostatic activity, and symptoms of hostility and depression at 3 phases of the menstrual cycle in 59 healthy young women (22.95 ± 2.83 mean age ± SD). Methods: Blood was drawn at follicular (FL), mid luteal (ML) and late luteal (LL) phase. At each visit, students completed the Zung Depression Scale and the Hostility and Direction of Hostility, and following variables were measured: a) Estradiol (E2), Testosterone (T), Free Testosterone (FT), Δ4–Androstenedione (Δ4 -A), b) Total cholesterol, LDL-cholesterol, HDL-cholesterol, triglycerides c) PT and APTT, AT III, Proteins C and S, Plasminogen and Fibrinogen. Pearson´s and Spearmans rank correlation were used to determine the relation between variables. P<0.05 was considered significant.Results: Aspects of hostility were mostly positively correlated with androgens especially in FL and ML phase. Ratio T/E2 positively correlated with depression scores and the direction of hostility, in the ML and LL phase, respectively. FT positively correlated with triglycerides across the cycle while the ratios T/E2, FT/E2 and Δ4A/E2 appear to influence fibrinogen and protein C levels but not premenstrually. E2 levels do not seem to essentially modulate lipid levels and haemostatic factors across the menstrual cycle. Conclusion: The relations between sex hormones and the tested psychological and biological factors in the young female population generally appear to differ markedly across the cycle, while the effect of endogenous hormones on these factors may be different comparatively to exogenous ones. Therefore, in order to evaluate them, the menstrual cycle effect should be taken into consideration.
Environmental sensor networks

The developments in wireless network technology and miniaturization makes it possible to realistically monitor the natural environment. Within the field of environmental sensor networks, domain knowledge is an essential fourth component. Before designing and installing any system, it is necessary to understand its physical environment and deployment in detail. Sensor networks are designed to transmit data from an array of sensors to a server data repository. They do not necessarily use a simple one way data stream over a communication network rather elements of the system decide what data to pass on, using local area summaries and filtering to minimize power use while maximizing the information content. The Envisense Glacs Web project is developing a monitoring system for a glacial environment. Monitoring the ice caps and glaciers provides valuable information about the global warming and climate change.
Survey of Learning Analytics based on Purpose and Techniques for Improving Student Performance

Learning Analytics is a process to analyze the learners which improves the educational performance. Learning Analytics also helps the higher educational institutions to improve the educational practices and techniques. This paper provides a detailed survey of the current research activities conducted in the education system. The review of Learning Analytics is based on some of existing Learning Analytics applications, purpose of the Learning Analytics in the education system and the type of students. The review based on various tools, techniques and data collection methods used to implement the Learning analytics is discussed in this paper. KeywordsAnalytics, tools, techniques
Speaker Normalization Through Feature Shifting of Linearly Transformed i-Vector

In this paper, we propose a simple speaker normalization for deep neural network (DNN) using i-vectors, the state-of-the-art technique for speaker recognition, for automatic speech recognition. There have been already many techniques using ivectors for speaker adaptation or speaker variability reduction of DNN acoustic models. However, in order to add the speaker information into the acoustic feature, most of those techniques have to train a large number of parameters while dimensionality of the i-vector is quite small. We tried to apply a componentwise shift to the acoustic features by linearly transformed ivector, and then achieved the better performance than typical approaches. On top of that, we propose to modify this structure to adapt each frame of the features, reducing the number of parameters. Experiments were conducted on the TED-LIUM release-1 corpus, and the proposed method showed some performance gains.
Self-Diagnosis for Detecting System Failures in Large-Scale Wireless Sensor Networks

Existing approaches to diagnosing sensor networks are generally sink based, which rely on actively pulling state information from sensor nodes so as to conduct centralized analysis. First, sink-based tools incur huge communication overhead to the traffic-sensitive sensor networks. Second, due to the unreliable wireless communications, sink often obtains incomplete and suspicious information, leading to inaccurate judgments. Even worse, it is always more difficult to obtain state information from problematic or critical regions. To address the given issues, we present a novel self-diagnosis approach, which encourages each single sensor to join the fault decision process. We design a series of fault detectors through which multiple nodes can cooperate with each other in a diagnosis task. Fault detectors encode the diagnosis process to state transitions. Each sensor can participate in the diagnosis by transiting the detector's current state to a new state based on local evidences and then passing the detector to other nodes. Having sufficient evidences, the fault detector achieves the Accept state and outputs a final diagnosis report. We examine the performance of our self-diagnosis tool called TinyD2 on a 100-node indoor testbed and conduct field studies in the GreenOrbs system, which is an operational sensor network with 330 nodes outdoor.
A Fast Parallel Stochastic Gradient Method for Matrix Factorization in Shared Memory Systems

Matrix factorization is known to be an effective method for recommender systems that are given only the ratings from users to items. Currently, stochastic gradient (SG) method is one of the most popular algorithms for matrix factorization. However, as a sequential approach, SG is difficult to be parallelized for handling web-scale problems. In this article, we develop a fast parallel SG method, FPSG, for shared memory systems. By dramatically reducing the cache-miss rate and carefully addressing the load balance of threads, FPSG is more efficient than state-of-the-art parallel algorithms for matrix factorization.