Miracle-dz/UniFAR-FTUs huggingface dataset:
Age-Dependent Changes in the Inflammatory Nociceptive Behavior of Mice

The processing of pain undergoes several changes in aging that affect sensory nociceptive fibers and the endogenous neuronal inhibitory systems. So far, it is not completely clear whether age-induced modifications are associated with an increase or decrease in pain perception. In this study, we assessed the impact of age on inflammatory nociception in mice and the role of the hormonal inhibitory systems in this context. We investigated the nociceptive behavior of 12-month-old versus 6–8-week-old mice in two behavioral models of inflammatory nociception. Levels of TRP channels, and cortisol as well as cortisol targets, were measured by qPCR, ELISA, and Western blot in the differently aged mice. We observed an age-related reduction in nociceptive behavior during inflammation as well as a higher level of cortisol in the spinal cord of aged mice compared to young mice, while TRP channels were not reduced. Among potential cortisol targets, the NF-κB inhibitor protein alpha (IκBα) was increased, which might contribute to inhibition of NF-κB and a decreased expression and activity of the inducible nitric oxide synthase (iNOS). In conclusion, our results reveal a reduced nociceptive response in aged mice, which might be at least partially mediated by an augmented inflammation-induced increase in the hormonal inhibitory system involving cortisol.
Overexpression of CERKL, a gene responsible for retinitis pigmentosa in humans, protects cells from apoptosis induced by oxidative stress

Purpose Retinitis pigmentosa (RP), a retinal neurodegenerative disorder characterized by apoptosis of photoreceptor cells, is caused by mutations in many different genes. We analyzed the RP gene ceramide kinase-like (CERKL) to determine CERKL function and contribution to pathogenesis. Methods RT–PCR was performed to characterize CERKL expression in many human adult and fetal tissues, including retina. We analyzed the protein subcellular localization by confocal microscopy and further verified it by sucrose gradients. We performed lipid kinase activity assays. And finally, we studied the effects on cell apoptosis after CERKL overexpression in transiently transfected cultured cells by propidium iodide staining and poly-(ADP-ribose)-polymerase (PARP) caspase-dependent cleavage. Results CERKL transcripts underwent alternative splicing. In the human retina, four different CERKL isoforms of 532, 558, 419, and 463 amino acids were expressed. CERKL proteins were mainly localized in the endoplasmic reticulum and Golgi compartments, but they also shifted localization to nuclei and nucleoli. We also found that CERKL prevented cells from entering apoptosis induced by oxidative-stress conditions. Conclusions CERKL remains a unique orphan lipid kinase in that no candidate substrate has been identified after intense research. The dynamic localization of CERKL suggests multiple sites of action. Remarkably, CERKL (but not the RP R257X mutant) exerts a protective role in cells against oxidative stress, consistent with RP mutations impairing the normal protein function in photoreceptors and thus tilting the balance toward apoptosis. These results provide valuable insights into the molecular mechanisms causing retinal degeneration.
The characteristics of coordination process in construction projects

Modern construction projects are no longer confined to a single discipline but are generally multidisciplinary. An independency relationship between a large number of stakeholders required to be managed in construction projects procurement and execution that need continuous coordination. Coordination function is to harmonize the different activities, so that the determined objectives can be reached effectively. However, the study of coordination characteristics are the way to assess the status of coordination in construction projects. Through the literatures, the most important characteristics of coordination process were identified. Quantitative approach was used to investigate them through questionnaire. The data were analyzed by means of statistical analysis and Chi-square test. The analysis showed that, 45.5 % of the respondents mentioned to a moderate level of knowledge about coordination, however 44.6 % were commonly applied coordination culture. Nevertheless, about 60% believed that, ability and willingness are the main obstacle of coordination application. At the same time, 75% considered coordination effect as significantly improve the project performance. In the future, 70 % of the respondents will always apply coordination consideration from their personal motivation. The results of Chi-square show a significant dependent relationship between the position and organization function variables and the eight coordination characteristics.
A sample-time error calibration technique in time-interleaved ADCs with correlation-based detection and voltage-controlled compensation

Sample-time error between channels degrades the resolution of time-interleaved analog-to-digital converters (TIADCs). A calibration method implemented in mixed circuits with low-complexity and fast-convergence is proposed in this paper. The algorithm for detecting sample-time error is based on correlation and widely applied to wide-sense stationary input signals. The detected sample-time error is corrected by a voltage-controlled sampling switch. Experimental result of the 2-channel 200-MS/s 14-bit TIADC shows that the signal-to-noise-and-distortion ratio improves 19.1 dB, and the spurious-free dynamic range improves 34.6 dB for a 70.12-MHz input after calibration. The convergence time of calibration is about 20000 sampling intervals.
Coherent acoustic phonons in nanostructures investigated by asynchronous optical sampling

A new optical pump-probe technique is implemented for the investigation of acoustic phonon dynamics in the GHz to THz frequency range which is based on two asynchronously linked femtosecond lasers. Asynchronous optical sampling (ASOPS) provides the performance of on all-optical oscilloscope and allows us to record optically induced lattice dynamics over nanosecond times with 200 femtoseconds resolution at scan rates of 10 kHz. The generation of coherent acoustic phonons and their propagation and decay dynamics are investigated in semiconductor heterostructures, layered nanoscale materials of relevance for microelectronics, and X-ray mirrors. Changes of the optical properties of tailored semiconductor heterostructures associated with coherent phonon dynamics open the pathway for the modulation of optical signals at up to THz frequencies.
Tetrandrine Suppresses Cancer Angiogenesis and Metastasis in 4T1 Tumor Bearing Mice

Metastasis remains the most deadly aspect of cancer and still evades direct treatment. Thus, there is a great need to develop new treatment regimens to suppress tumor cells that have escaped surgical removal or that may have already disseminated. We have found that tetrandrine (TET) exhibits anticolon cancer activity. Here, we investigate the inhibition effect of TET to breast cancer metastasis, angiogenesis and its molecular basis underlying TET's anticancer activity. We compare TET with chemotherapy drug doxorubicin in 4T1 tumor bearing BALB/c mice model and find that TET exhibits an anticancer metastatic and antiangiogenic activities better than those of doxorubicin. The lung metastatic sites were decreased by TET, which is confirmed by bioluminescence imaging in vivo. On the other hand, laser doppler perfusion imaging (LDI) was used for measuring the blood flow of tumor in 4T1-tumor bearing mice. As a result, the local blood perfusion of tumor was markedly decreased by TET after 3 weeks. Mechanistically, TET treatment leads to a decrease in p-ERK level and an increase in NF-κB levels in HUVECs. TET also regulated metastatic and angiogenic related proteins, including vascular endothelial growth factor, hypoxia-inducible factor-1α, integrin β5, endothelial cell specific molecule-1, and intercellular adhesion molecule-1 in vivo.
Location Management in Cellular Mobile Networks

Increasing traffic generated from users and different QoE requirements has increased the importance of LM recently. This increasing importance has given way to the development of newer and intelligent schemes as well as the modification of the existing ones. In this article, we have discussed various methods proposed for the two important LM functions, LU and paging. The features, relative performances, and inherent disadvantages associated with each of them have been thoroughly dealt with. Studies reveal that the performance of different LU and paging schemes is largely affected by the user mobility pattern and call arrival characteristics. Further, the newly devised schemes are often associated with tremendous implementation complexity as well as large computational overhead, and require smarter MTs/ networks. For a given network, the best design will include a scheme, or a set of schemes, that provides the best compromise between performance and implementation constraints and is often sub-optimum for a different network.
DHT Performance for Peer-to-Peer SIP - A Mobile Phone Perspective

In this paper we investigate the DHT performance for Peer-to-peer SIP. We analyze performance from the mobile phone perspective. This angle brings battery consumption and efficient use of the limited resources of the mobile devices to the focus. We develop an analytical model of Kademlia DHT performance and use it to analyze a number of different strategies to use peer-to-peer SIP with mobile devices. These analyses include studying a model where all devices participate in the DHT and contrasting that with a model where only a subset of devices forms the DHT. Our analysis shows that in a one million user P2PSIP network, at least 30% of the mobile nodes should participate in operating the DHT to remain energy-efficient.
(coarse Coding of Shape Fragments) (retinotopy) Representation of Structure

—The ability to deal with object structure — to determine what is where in a given object, rather than merely to categorize or identify it — has been hitherto considered the prerogative of 'structural description' approaches, which represent shapes as categorical compositions of generic parts taken from a small alphabet. In this note, we propose a simple extension to a theoretically motivated and extensively tested appearance-based model of recognition and categorization, which should make it capable of representing object structure. We describe a pilot implementation of the extended model, survey independent evidence supporting its modus operandi, and outline a research program focused on achieving a range of object processing capabilities, including reasoning about structure, within a uni ed appearance-based framework. Intelligent processing of visual shapes implies the ability to solve the following core problems: ² Recognition — how to deal with novel views of shapes (generalization across viewpoint changes); ² Categorization — how to deal with novel instances of shape categories (generalization across shape changes), and how to treat radically novel inputs which may belong to none of the familiar categories; ² Representation of structure — how to encode and refer to (i) the arrangement of parts in an object, and (ii) the arrangement of objects in a scene. Some theorists claim that the only computational approach to object vision that is in principle capable of addressing all three of these problems is structural decomposition (Biederman, 1987), in which 'atomic' (i.e. perceptually primitive, indivisible) parts entering into categorical spatial relationships to each other are used to describe potentially complex shapes.
Adaptive estimation of latency change in evoked potentials by direct least mean p-norm time-delay estimation

Evoked potentials (EP) have been widely used to quantify neurological system properties. Changes in EP latency may indicate impending neurological injury. Traditional EP analyses are developed under the condition that the background noise in EP analysis are Gaussian distributed. This paper proposes a latency change detection and estimation algorithm under /spl alpha/-stable noise condition, a generalization of Gaussian noise assumption. An analysis shows that the /spl alpha/-stable model fits the noises found in the impact acceleration experiment under study better than the Gaussian model. The robustness of the proposed algorithm is demonstrated through computer simulations and experimental data analysis under both Gaussian and /spl alpha/-stable noise environments.
A novel rejection sampling scheme for posterior probability distributions

Rejection sampling (RS) is a well-known method to draw from arbitrary target probability distributions, which has important applications by itself or as a building block for more sophisticated Monte Carlo techniques. The main limitation to the use of RS is the need to find an adequate upper bound for the ratio of the target probability density function (pdf) over the proposal pdf from which the samples are generated. There are no general methods to analytically find this bound, except in the particular case in which the target pdf is log-concave. In this paper we adopt a Bayesian view of the problem and propose a general RS scheme to draw from the posterior pdf of a signal of interest using its prior density as a proposal function. The method enables the analytical calculation of the bound and can be applied to a large class of target densities. We illustrate its use with a simple numerical example.
DeepMind Control Suite

The DeepMind Control Suite is a set of continuous control tasks with a standardised structure and interpretable rewards, intended to serve as performance benchmarks for reinforcement learning agents. The tasks are written in Python and powered by the MuJoCo physics engine, making them easy to use and modify. We include benchmarks for several learning algorithms. The Control Suite is publicly available at this https URL A video summary of all tasks is available at this http URL .
Creating a Large-Scale Arabic to French Statistical MachineTranslation System

In this work, the creation of a large-scale Arabic to French statistical machine translation system is presented. We introduce all necessary steps from corpus aquisition, preprocessing the data to training and optimizing the system and eventual evaluation. Since no corpora existed previously, we collected large amounts of data from the web. Arabic word segmentation was crucial to reduce the overall number of unknown words. We describe the phrase-based SMT system used for training and generation of the translation hypotheses. Results on the second CESTA evaluation campaign are reported. The setting was inthe medical domain. The prototype reaches a favorable BLEU score of40.8%.
UCD : Diachronic Text Classification with Character, Word, and Syntactic N-grams

We present our submission to SemEval-2015 Task 7: Diachronic Text Evaluation, in which we approach the task of assigning a date to a text as a multi-class classification problem. We extract n-gram features from the text at the letter, word, and syntactic level, and use these to train a classifier on date-labeled training data. We also incorporate date probabilities of syntactic features as estimated from a very large external corpus of books. Our system achieved the highest performance of all systems on subtask 2: identifying texts by specific time language use.
Aladdin: Automating Release of Android Deep Links to In-App Content

Unlike the Web where each web page has a global URL to reach, a specific "content page" inside a mobile app cannot be opened unless the user explores the app with several operations from the landing page. Recently, deep links have been advocated by major companies to enable targeting and opening a specific page of an app externally with an accessible uniform resource identifier (URI). In this paper, we present an empirical study of deep links over 20,000 Android apps, and find that deep links do not get wide adoption among current Android apps, and non-trivial manual efforts are required for app developers to support deep links. To address such an issue, we propose the Aladdin approach and supporting tool to release deep links to access arbitrary locations of existing apps. We evaluate Aladdin with popular apps and demonstrate its effectiveness and performance.
Script Templates: A Practical Approach to Script Training in Aphasia

Purpose: Script training for aphasia involves repeated practice of relevant phrases and sentences that, when mastered, can potentially be used in other communicative situations. Although an increasingly popular approach, script development can be time-consuming. We provide a detailed summary of the evidence supporting this approach. We then describe a method in which scripts at various levels of difficulty are created by systematically manipulating readability and grammatical and semantic components. We assess the appropriateness of using these template-based scripts with persons with aphasia of differing severities. Method: We evaluated the oral reading performance of 8 individuals with chronic nonfluent aphasia on scripts developed from the templates. Scripts were either of high or low difficulty relative to their aphasia severity and personalized by inserting the participant's town and the name of an acquaintance. Oral reading probes were taken on 3 separate days within a week, and performance within and across participants was examined. Results: Regardless of the participant's aphasia severity, scripts in the low-difficulty condition were read with significantly greater accuracy than scripts in the high-difficulty condition. Discussion: These findings support the use of graded script templates to ensure that appropriately challenging scripts are delivered to persons with aphasia for both clinical practice and research.
Combined economic and emission dispatch by ANN with backprop algorithm using variant learning rate & momentum coefficient

Multi-layered feed-forward artificial neural network (ANN) trained by back-propagation algorithm is used to solve the problem of combined economic and emission dispatch in this paper. The system of generation associates thermal generators and emission involves oxides of nitrogen only. Equality constraints on power balance as well as inequality constraints on generation capacity limits of the generators and transmission loss are also considered. The idea is to minimize total fuel cost of the system and control emission. The problem is first optimized by Lagrange multiplier technique and the result is used to train the ANN wherein tuning parameters eta & alpha are altered to check their effect on convergence rate. The trained ANN is then used to generate test data. It is found that the convergence characteristic of the algorithm is excellent and the results achieved by the proposed method are quite accurate and faster in comparison to the conventional method
SnapToGrid: From Statistical to Interpretable Models for Biomedical Information Extraction

We propose an approach for biomedical information extraction that marries the advantages of machine learning models, e.g., learning directly from data, with the benefits of rule-based approaches, e.g., interpretability. Our approach starts by training a feature-based statistical model, then converts this model to a rule-based variant by converting its features to rules, and "snapping to grid" the feature weights to discrete votes. In doing so, our proposal takes advantage of the large body of work in machine learning, but it produces an interpretable model, which can be directly edited by experts. We evaluate our approach on the BioNLP 2009 event extraction task. Our results show that there is a small performance penalty when converting the statistical model to rules, but the gain in interpretability compensates for that: with minimal effort, human experts improve this model to have similar performance to the statistical model that served as starting point.
Temporal segmentation tool for high-quality real-time video editing software

The increasing use of video editing software requires faster and more efficient editing tools. As a first step, these tools perform a temporal segmentation in shots that allows a later building of indexes describing the video content. Here, we propose a novel real-time high-quality shot detection strategy, suitable for the last generation of video editing software requiring both low computational cost and high quality results. While abrupt transitions are detected through a very fast pixel-based analysis, gradual transitions are obtained from an efficient edge-based analysis. Both analyses are reinforced with a motion analysis that helps to detect and discard false detections. This motion analysis is carried out exclusively over a reduced set of candidate transitions, thus maintaining the computational requirements demanded by new applications to fulfill user needs.
Scanning datapaths: a fast and effective partial scan selection technique

Partial scan DFT is a commonly used technique for improving testability of sequential circuits while maintaining overhead as low as possible. In this context, the selection of the partial scan chain is usually performed at gate-level. In this paper, we present a method for quickly selecting the partial Scan Chain (SC) in datapath-like circuits. The so-obtained SC is such that the number of scan FFs is optimized and such that the achievable fault coverage is the same than with full scan approach.
Robust gender-dependent acoustic-phonetic modelling in continuous speech recognition based on a new automatic male/female classification

The authors present a new automatic male/female classification method based on the location in the frequency domain of the first two formants. This classification is based on a new automatic formant extraction which is faster than a peak picking technique. Gender-dependent acoustic-phonetic models stemming from this classification are used in the INRS continuous speech recognition system with the ATIS corpora. An improvement of 14% is obtained with these models in comparison to the baseline speaker-independent system.
Finding Critical Regions and Region-Disjoint Paths in a Network

Due to their importance to society, communication networks should be built and operated to withstand failures. However, cost considerations make network providers less inclined to take robustness measures against failures that are unlikely to manifest, like several failures coinciding simultaneously in different geographic regions of their network. Considering networks embedded in a two-dimensional plane, we study the problem of finding a critical region-a part of the network that can be enclosed by a given elementary figure of predetermined size-whose destruction would lead to the highest network disruption. We determine that only a polynomial, in the input, number of nontrivial positions for such a figure needs to be considered and propose a corresponding polynomial-time algorithm. In addition, we consider region-aware network augmentation to decrease the impact of a regional failure. We subsequently address the region-disjoint paths problem, which asks for two paths with minimum total weight between a source (s) and a destination (d) that cannot both be cut by a single regional failure of diameter D (unless that failure includes s or d). We prove that deciding whether region-disjoint paths exist is NP-hard and propose a heuristic region-disjoint paths algorithm.