Miracle-dz/UniFAR-FTUs huggingface dataset:
A major role for Tau in neuronal DNA and RNA protection in vivo under physiological and hyperthermic conditions

Nucleic acid protection is a substantial challenge for neurons, which are continuously exposed to oxidative stress in the brain. Neurons require powerful mechanisms to protect DNA and RNA integrity and ensure their functionality and longevity. Beside its well known role in microtubule dynamics, we recently discovered that Tau is also a key nuclear player in the protection of neuronal genomic DNA integrity under reactive oxygen species (ROS)-inducing heat stress (HS) conditions in primary neuronal cultures. In this report, we analyzed the capacity of Tau to protect neuronal DNA integrity in vivo in adult mice under physiological and HS conditions. We designed an in vivo mouse model of hyperthermia/HS to induce a transient increase in ROS production in the brain. Comet and Terminal deoxyribonucleotidyltransferase-mediated deoxyuridine triphosphate nick end labeling (TUNEL) assays demonstrated that Tau protected genomic DNA in adult cortical and hippocampal neurons in vivo under physiological conditions in wild-type (WT) and Tau-deficient (KO-Tau) mice. HS increased DNA breaks in KO-Tau neurons. Notably, KO-Tau hippocampal neurons in the CA1 subfield restored DNA integrity after HS more weakly than the dentate gyrus (DG) neurons. The formation of phosphorylated histone H2AX foci, a double-strand break marker, was observed in KO-Tau neurons only after HS, indicating that Tau deletion did not trigger similar DNA damage under physiological or HS conditions. Moreover, genomic DNA and cytoplasmic and nuclear RNA integrity were altered under HS in hippocampal neurons exhibiting Tau deficiency, which suggests that Tau also modulates RNA metabolism. Our results suggest that Tau alterations lead to a loss of its nucleic acid safeguarding functions and participate in the accumulation of DNA and RNA oxidative damage observed in the Alzheimer’s disease (AD) brain.
Crowdsourcing synset relations with Genus-Species-Match

Enabling a domain-specific lexical resource is useful for improving the performance of a natural language processing system. However, such resources may be represented in the form of glossaries-terms provided with their sense definitions. Despite the problem of integrating such domain-specific glossaries into more sophisticated general purpose resources like thesuari being highly topical, it is complicated by ambiguity of the individual terms. This paper presents Genus-Species-Match, a crowdsourcing workflow for matching noisy pairs of synsets representing hyponymic/hypernymic relations. The system demonstrates F1 score of 80% on an experiment conducted on an online labor marketplace using the EMERCOM glossary and the Yet Another RussNet sense inventory.
Attentional Control and Retrieval Induced Forgetting

Retrieval Induced Forgetting (RIF) refers to the fi nding that the retrieval of some items from memory (RP+) impairs the retrieval of related items (RP-). The RIF effect is indicated by a comparison of RP- with unrelated but also to- be-remembered items (NRP). Since RIF appears during intentional memorizing of words, therefore we checked whether it depends on attentional control (AC) involved in goal maintenance, and also if implicit evaluations of to-be-remembered (RP) contents moderate this process (causing e.g. inhibition). In three experiments, each including AC as the independent variable, we found AC to be related to the RIF effect. Only high but not low AC subjects showed the presence of RIF. The results of the affective priming procedure showed that implicit evaluations of NRP items moderate the relationship of high AC and the RIF effect. The explanation why temporarily devaluated NRP could enhance the RIF effect and suggestion concerning future research summarize the article.
M an us cr ip t Multifunctionality in dialogue

This paper studies the multifunctionality of dialogue utterances, i.e. the phenomenon that utterances in dialogue often have more than one communicative function. It is argued that this phenomenon can be explained by analyzing the participation in dialogue as involving the performance of several types of activity in parallel, relating to different dimensions of communication. The multifunctionality of dialogue utterances is studied by (1) redefining the notion of ‘utterance’ in a rigorous manner (calling the revised notion ‘functional segment’), and (2) empirically investigating the multifunctionality of functional segments in a corpus of dialogues, annotated with a rich, multidimensional annotation schema. It is shown that, when communicative functions are assigned to functional segments, thereby eliminating every form of segmentation-related multifunctionality, an average multifunctionality is found between 1.8 and 3.6, depending on what is considered to count as a segment’s communicative function. Moreover, a good understanding of the nature of the relations among the various multiple functions that a segment may have, and how functional segments relate to other units in dialogue segmentation, opens the way for defining a multidimensional computational update semantics for dialogue interpretation.
On the Cramer-Rao Lower Bound for Frequency Correlation Matrices of Doubly Selective Fading Channels for OFDM Systems

The analytic expression of CRLB and the maximum likelihood estimator for the sample frequency correlation matrices in doubly selective fading channels for OFDM systems are reported in this paper. According to the analytical and numerical results, the amount of samples affects the average mean square error dominantly while the SNR and the Doppler spread do negligibly.
Implementing Web Classification for TLDs

On the market there are many commercial web classification services and a few publicly available web directory services. Unfortunately they mostly focus on English-speaking web sites, making them unsuitable for other languages in terms of classification reliability and coverage. This paper covers the design and implementation of a web-based classification tool for TLDs (Top Level Domain). Each domain is classified by analysing the main domain web site, and organised it in categories according to its content. The tool has been successfully validated by classifying all the registered. It Internet domains, whose results are presented in this paper.
Bi-decompositions of multi-valued functions for circuit design and data mining applications

We present efficient algorithms for the bi-decomposition of arbitrary incompletely specified functions in variable-valued logic. Several special cases are discussed. The algorithms are especially applicable for Data Mining applications, because, in contrast to the general multi-valued approaches to function decomposition that decompose to arbitrary tables, we create a network from multi-valued two-input operators that are selected by the user. Such decompositions lead to decision rules that are easier to understand by humans.
Efficient, High-Quality, GPU-Based Visualization of Voxelized Surface Data with Fine and Complicated Structures

This paper proposes a GPU-based method that can visualize voxelized surface data with fine and complicated features, has high rendering quality at interactive frame rates, and provides low memory consumption. The surface data is compressed using run-length encoding (RLE) for each level of detail (LOD). Then, the loop for the rendering process is performed on the GPU for the position of the viewpoint at each time instant. The scene is raycasted in planes, where each plane is perpendicular to the horizontal plane in the world coordinate system and passes through the viewpoint. For each plane, one ray is cast to rasterize all RLE elements intersecting this plane, starting from the viewpoint and ranging up to the maximum view distance. This rasterization process projects each RLE element passing the occlusion test onto the screen at a LOD that decreases with the distance of the RLE element from the viewpoint. Finally, the smoothing of voxels in screen space and full screen anti-aliasing is performed. To provide lighting calculations without storing the normal vector inside the RLE data structure, our algorithm recovers the normal vectors from the rendered scene's depth buffer. After the viewpoint changes, the same process is re-executed for the new viewpoint. Experiments using different scenes have shown that the proposed algorithm is faster than the equivalent CPU implementation and other related methods. Our experiments further prove that this method is memory efficient and achieves high quality results.
Parallel Online Temporal Difference Learning for Motor Control

Temporal difference (TD) learning, a key concept in reinforcement learning, is a popular method for solving simulated control problems. However, in real systems, this method is often avoided in favor of policy search methods because of its long learning time. But policy search suffers from its own drawbacks, such as the necessity of informed policy parameterization and initialization. In this paper, we show that TD learning can work effectively in real robotic systems as well, using parallel model learning and planning. Using locally weighted linear regression and trajectory sampled planning with 14 concurrent threads, we can achieve a speedup of almost two orders of magnitude over regular TD control on simulated control benchmarks. For a real-world pendulum swing-up task and a two-link manipulator movement task, we report a speedup of 20× to 60×, with a real-time learning speed of less than half a minute. The results are competitive with state-of-the-art policy search.
Children of Two Cultures: Immigrant Children from Ethiopia in Israel

The second part of the twentieth century could be rightly labeled as the century of migration. Vast numbers of people are moving from their country of origin to new countries in order to find better living conditions. A rich output of literature treats a variety of problems concerning both the immigrants and the host country. It is a universally accepted assumption that migration creates "social problems for both sides". For the immigrants the separation from their roots, culture, social ties and the taken-for-granted pattern of daily life is a traumatic separation. No less traumatic is the entrance into the new society. The status of 'stranger', of immigrant, is, to say the least, an uncomfortable status. There is a new culture, often a new language, unknown customs and norms, undefined or not well understood demands. The host society is mostly ambivalent toward the strangers. The influx of strangers raises feelings of uneasiness. Even when the immigrants are needed, as was the case with the "guest- workers" in various European countries and in Israel, they were not accepted socially. No society can tolerate large numbers of people who are "outside" the society. They have to be taken in at some level while at the same time they are also excluded from full integration. Integration is usually demanding the adaptation of the immigrant to the new way of life, involvement and interaction in the formal-institutional and on the informal-social level of the society. At the same time exclusionary practices make adaptation difficult and closure of the dominant group jeopardizes the creation of mixed social networks (Bar-Yosef, 1998). Under the impact of a considerable number of immigrants some dormant problems are emerging with more virulence, existing conflicts are intensified, accepted values are questioned and new values are emerging. A society after accepting a considerable number of immigrants is not the same society as it was before the wave of immigrants. It is usually assumed that the migrant is a working age male and much of the literature deals with problems of occupational adaptation. Less interest was shown to other groups such as women who came independently or as wives, elderly parents and children.
Are Forensic Experts Already Biased before Adversarial Legal Parties Hire Them?

This survey of 206 forensic psychologists tested the “filtering” effects of preexisting expert attitudes in adversarial proceedings. Results confirmed the hypothesis that evaluator attitudes toward capital punishment influence willingness to accept capital case referrals from particular adversarial parties. Stronger death penalty opposition was associated with higher willingness to conduct evaluations for the defense and higher likelihood of rejecting referrals from all sources. Conversely, stronger support was associated with higher willingness to be involved in capital cases generally, regardless of referral source. The findings raise the specter of skewed evaluator involvement in capital evaluations, where evaluators willing to do capital casework may have stronger capital punishment support than evaluators who opt out, and evaluators with strong opposition may work selectively for the defense. The results may provide a partial explanation for the “allegiance effect” in adversarial legal settings such that preexisting attitudes may contribute to partisan participation through a self-selection process.
Bilingualism and educational achievements: the impact of the language used at home by Tatar school students in Tatarstan, Russia

ABSTRACT This article empirically studies the impact of bilingualism on educational achievements. This relationship has been thoroughly studied in a number of countries around the world, but not in Russia. We used a sample of 709 ethnic Tatar school students aged 15–16 (in the ninth grade) in the spring of the year 2010. We found a positive significant effect on school grades based on logistic regressions, and controlling for family background characteristics, school characteristics, psychological attributes, health issues, peers, gender, and the impact of the capital city Kazan. Oral bilingual children, who use Tatar language at home, are more likely to obtain the highest grades in literature and chemistry classes, and they have lower probabilities of obtaining the lowest grades in Russian language, literature, geometry, and physics. We did not find negative impacts on school grades due to the use of Tatar at home. Therefore, we found evidence in favour of bilingualism and against the assumption of Russian policymakers that bilingualism threatens the knowledge of Russian.
Adaptive Variable-Length Quantiser for Image Compression

In this paper, a novel adaptive variable-length quantizer design is proposed and its application to predictive image coding is presented. The new quantiser makes advantage of the fact that more than 80% of the prediction error data usually reside near the origin and hence can be coded with small number of bits. The remaining 20% of the prediction error data can be coded with larger number of bits which results in smaller file size and enhanced quality of the reconstructed image. The simulation results showed improvements in the peak signal to noise ratio at the expense of increased computational complexity. The improvements in the quality of the compressed images overweight the computational complexity of the model
Thoracoscopic Video-Assisted Pulmonary Vein Antrum Isolation, Ganglionated Plexus Ablation, and Periprocedural Confirmation of Ablation Lesions: First Results of a Hybrid Surgical-Electrophysiological Approach for Atrial Fibrillation

Background—Thoracoscopic pulmonary vein isolation (PVI) and ganglionated plexus ablation is a novel approach in the treatment of atrial fibrillation (AF). We hypothesize that meticulous electrophysiological confirmation of PVI results in fewer recurrences of AF during follow-up. Methods and Results—Surgery was performed through 3 ports bilaterally. Ganglionated plexi were localized and subsequently ablated. PVI was performed and entry and exit block was confirmed. Additional left atrial ablation lines were created and conduction block verified in patients with nonparoxysmal AF. The left atrial appendage was removed. Freedom of AF was assessed by ECGs and Holter monitoring every 3 months or during symptoms of arrhythmia. Antiarrhythmic drugs were discontinued after 3 months and oral anticoagulants were discontinued according to the guidelines. Thirty-one patients were treated (16 paroxysmal AF, 13 persistent AF, 2 long-standing persistent AF). Thirteen patients with nonparoxysmal received additional left atrial ablation lines. After 1 year, 19 of 22 patients (86%) had no recurrences of AF, atrial flutter, or atrial tachycardia and were not using antiarrhythmic drugs (11/12 paroxysmal, 7/9 persistent, and 1/1 long-standing persistent). Three patients had a sternotomy because of uncontrolled bleeding during thoracoscopic surgery. Four adverse events were 1 hemothorax, 1 pneumothorax, and 2 pneumonia. No thromboembolic complications or mortality occurred. Conclusions—Thoracoscopic surgery with PVI and ganglionated plexus ablation for AF is a safe and successful procedure with a single procedure success rate of 86% at 1 year. Electrophysiological guided thorough PVI and additional left atrial ablation line creation presumably contributes in achieving a high success rate in the surgical treatment of AF.
Applying dynamic reconfiguration in the mobile robotics domain: A case study on computer vision algorithms

Mobile robots are widely used in industrial environments and are expected to be widely available in human environments in the near future, for example, in the area of care and service robots. This article proposes an implementation for a highly customizable color recognition module based on Field Programmable Gate Array (FPGA) hardware to accomplish tasks like real-time frame processing for image streams. In comparison to a pure software solution on a CPU, an attached FPGA-based hardware accelerator enables real-time image processing and significantly reduces the required computing power of the CPU. Instead, the CPU can be used for tasks that cannot be efficiently implemented on FPGAs, for example, because of a large control overhead. We concentrate on a multirobot scenario where a group of robots follows a human team member by keeping a specific formation in order to support the human in exploration and object detection. Additionally, the robots provide a communication infrastructure to maintain a stable multihop communication network between the human and a base station recording all actions and evaluating the captured images and transmitted data. Depending on the current operating conditions, the robot system has to be able to execute a wide variety of different tasks. Since only a small number of tasks have to be executed concurrently, dynamic reconfiguration of the FPGA can be used to avoid the parallel implementation of all tasks on the FPGA. Within this context, this article discusses application fields where dynamic reconfiguration of FPGA-based coprocessors significantly reduces the CPU load and presents examples of how dynamic reconfiguration can be used in exploration.
Low-cost Sensor Glove with Force Feedback for Learning from Demonstrations using Probabilistic Trajectory Representations

Sensor gloves are popular input devices for a large variety of applications including health monitoring, control of music instruments, learning sign language, dexterous computer interfaces, and tele-operating robot hands. Many commercial products as well as low-cost open source projects have been developed. We discuss here how low-cost (approx. 250 EUROs) sensor gloves with force feedback can be build, provide an open source software interface for Matlab and present first results in learning object manipulation skills through imitation learning on the humanoid robot iCub.
Induction of plasminogen activator synthesis by antibodies

We have purified the immunoglobulins (IgG) from rabbit antisera raised against two cell lines--LLC-PK1 derived from pig kidney and from Kirsten sarcoma virus-transformed BALB/3T3--and have studied the effects of IgG on cultures of the respective target cells. The following observations were made with both cell types: (a) The addition of purified IgG produced a rapid change in morphology within 2 h. This consisted of cell rounding, agglutination, and detachment from the surface of the dish. (b) Beginning approximately 2 h after IgG addition there was a progressive rise in plasminogen activator production for 24- -36 h. (c) Both the morphological change and the induction of plasminogen activator (PA) synthesis were reversible and required the continued presence of IgG for their maintenance. The increase in PA production, but not morphological change, depended on genetic transcription and translation, being inhibited by actinomycin and/or cycloheximide. (d). These effects of IgG were specific: they were not observed with preimmune or indifferent IgG and occurred only after interaction between an IgG preparation from antisera and the cells used to generate the particular antiserum. The divalent IgG fragments F(ab')2 retained fully the activities of the native IgG molecules from which they were derived.
Nonsubsampled Contourlet Transform Based Descriptors for Gender Recognition

Gender recognition using facial images plays an important role in biometric technology. A key component of a gender recognition system is feature extraction. Motivated by the success of multiresolution techniques in various applications, we investigated four different feature extraction techniques based on Nonsubsampled Contourlet Transform (NSCT) to identify the best performing technique. We present a gender recognition system that uses SVM, two-stage feature selection and different feature descriptors based on NSCT. Among different NSCT based feature descriptors, the one based on NSCT and Weber Law Descriptor (WLD) gives the best accuracy (99.5±1.05) and it outperforms the state-of-the-art gender recognition systems on FERET database. This research reveals the best feature description technique using NSCT for gender recognition problem.
Knowledge Management and Data Mining: In Demand Estimation Approach for Perfect Revenue Management

Knowledge management and data mining techniques have been widely used in many important applications in both scientific and business domains in recent years. The importance of forecasting has also been exposed in many practical zones. Considering that accurate forecasts are the base for correct decisions in revenue management, the purpose of this paper is to study the role of knowledge management and data mining techniques for a demand estimating process. For this reason this paper deals with neural network structures, which is a data mining technique, for railway passenger demand forecasting. It is advised that information should be made available in specific positions in neural network operations rather than combining all the accessible information at the beginning. The results can be useful for all knowledge based transportation businesses.
Threshold-based 3D Tumor Segmentation using Level Set (TSL)

Three-dimensional segmentation is reliable approach to achieve a proper estimation of tumor volume. Among all possible methods for this purpose, level set can be used as a powerful tool which implicitly extracts the tumor surface. In this paper, we introduce a threshold-based algorithm for 3D tumor segmentation using level set (TSL). This algorithm uses a global threshold to form the level set speed function which is updated iteratively throughout the level set growing process. An important feature of TSL is that no explicit knowledge about the tumor and non-tumor density functions is required. The proposed method can be implemented in the automatic and semi-automatic forms depending on the complexity of the tumor shape. TSL is examined on several clinical MRIs for both visual and quantitative evaluation. Experimental results demonstrate the effectiveness of our approach