Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel NLOS mitigation approach for TDOA based on IMU measurements

The location estimation of a mobile station (MS) is becoming more and more important in many applications. By using the time difference of arrival (TDOA) method, the position of a MS can be determined based on the relative time difference measurements. However, the accuracy of the position estimation suffers from Non-line-of-sight (NLOS) errors. In this paper, the influence of the main base station (BS) selection for the position estimation accuracy is discussed. It is shown that the selection of the accurate range differences is more important for position estimation than the detection of the NLOS BSs for TDOA method. A novel accurate range differences selection approach based on IMU measurements is developed. Instead of selecting the BSs under line-of-sight (LOS), the accurate range differences are chosen for calculation. The selection method is combined with Iterative Extended Kalman Filter (IEKF) to effectively mitigate the NLOS measurement errors. The IEKF performance difference, with and without the selection approach, is analyzed. The performance of ultra-wideband/inertial sensor (UWB/INS) tightly coupled approach and Taylor approach are discussed. Among all the approaches, the IEKF with selection approach shows better accuracy both in simulation and real field tests.
In Silico Approaches Applied to the Study of Peptide Analogs of Ile-Pro-Ile in Relation to Their Dipeptidyl Peptidase IV Inhibitory Properties

Inhibition of dipeptidyl peptidase IV (DPP-IV) may be exploited to maintain the incretin effect during the postprandial phase. As a result, glycemic regulation and energy homeostasis may be improved. Food protein-derived peptides have been identified as natural agents capable of inhibiting DPP-IV. Ile-Pro-Ile is the most potent DPP-IV inhibitory peptide identified to date. A minimum analog peptide set approach was used to study peptide analogs of Ile-Pro-Ile. The DPP-IV half maximal inhibitory concentration (IC50) values of the 25 peptides evaluated ranged from 3.9 ± 1.0 µM (Ile-Pro-Ile) to 247.0 ± 32.7 µM (Phe-Pro-Phe). The presence of Pro at position 2 of tripeptides was required to achieve high DPP-IV inhibition. Most peptides behaved as competitive inhibitors of DPP-IV with the exception of peptides with a N-terminal Trp, which were mixed-type inhibitors. While possessing the structure of preferred DPP-IV substrates, most peptides studied were particularly stable during 30 min incubation with DPP-IV. Molecular docking revealed that Ile-Pro-Ile and its peptide analogs interacted in a very similar manner with the active site of DPP-IV. In addition, no correlation was found between the Hydropathic INTeraction score and the DPP-IV IC50 values of the peptides studied. This outcome suggests that free energy may not be directly responsible for enzyme inhibition by the peptides. Finally, novel DPP-IV inhibitory peptides were identified using the strategy employed herein. These results may be relevant for the development of food protein-derived peptides with serum glucose lowering and food intake regulatory properties in humans.
Marginal Policy Gradients for Complex Control

Many complex domains, such as robotics control and real-time strategy (RTS) games, require an agent to learn a continuous control. In the former, an agent learns a policy over R and in the latter, over a discrete set of actions each of which is parametrized by a continuous parameter. Such problems are naturally solved using policy based reinforcement learning (RL) methods, but unfortunately these often suffer from high variance leading to instability and slow convergence. We show that in many cases a substantial portion of the variance in policy gradient estimators is completely unnecessary and can be eliminated without introducing bias. Unnecessary variance is introduced whenever policies over bounded action spaces are modeled using distributions with unbounded support, by applying a transformation T to the sampled action before execution in the environment. Recent works have studied variance reduced policy gradients for actions in bounded intervals, but to date no variance reduced methods exist when the action is a direction – constrained to the unit sphere – something often seen in RTS games. To address these challenges we: (1) introduce a stochastic policy gradient method for directional control; (2) introduce the marginal policy gradient framework, a powerful technique to obtain variance reduced policy gradients for arbitrary T ; (3) show that marginal policy gradients are guaranteed to reduce variance, quantifying that reduction exactly; (4) validate our framework by applying the methods to a popular RTS game and a navigation task, demonstrating improvement over a policy gradient baseline.
Structural priming within and across languages: a corpus-based perspective*

Structural priming is the phenomenon that speakers tend to re-use structures they have recently comprehended or produced themselves. Most studies on this topic are experimental and looked at within-language priming. However, there are now also many observational studies, a development that is inextricably related to new/larger corpora, new statistical methodologies, and new theoretical ideas. Second, there is a growing body of research on cross-linguistic structural priming, though mostly experimental. These developments lead to a new potential research avenue: cross-linguistic priming on the basis of observational data. Here, we will first summarize some fundamental studies of cross-linguistic priming, and then trace the historical development of observational studies of structural priming to showcase how statistical and theoretical developments have shaped research on priming in general and discuss what such observational priming research has offered to within-language priming research. We end with a discussion of how this research can inform cross-linguistic priming.
Data fusion for efficient height calculation of stixels

This paper presents a stereo-based method towards robust identification of obstacle heights using stixels. The aim is to ensure a very low false detection rate for obstacles in video data recorded in vehicles. Basically, frames are segmented into ground manifold and obstacles (approximated by stixels). To robustly estimate the obstacle height, our method leverages the height of stixels by fusing color information, represented by a saliency map, with disparity information, represented by a membership map. Experiments illustrate the accuracy of the proposed method using common benchmark datasets. The proposed method outperforms previously published methods on the used datasets; in particular, (as demonstrated in this brief paper) it performs superior compared to base-line stixel calculation in cases of challenging scene conditions.
Effect of pretreatment regimens of 1-aminobenzotriazole on metabolism and gastric emptying of probe compounds in rat

Abstract 1-Aminobenzotriazole (ABT) is a mechanism-based inactivator of major cytochrome P450 (CYP) enzymes, which is used in multiple mechanistic studies. The purpose was to evaluate the effect of 2 and 16-h pretreatment regimens of ABT on the exposures of triazolam in rat. Another objective was to evaluate the effect of ABT on gastric emptying of acetaminophen. Plasma area under the curve (AUC) of triazolam was increased by 101-fold and 81-fold for the rats pretreated with ABT at 2 and 16 h, respectively, compared to control rats. Time to reach maximum concentration was 0.3, 4.8 and 3.7 h in control, 2 and 16-h pretreatment animals, respectively. In the case of acetaminophen, where Tmax was not delayed, the mean absorption time (MAT) in control, 2 and 16 h ABT pretreatment groups were 0.3, 4.6 and 2.9 h, respectively, suggesting delayed absorption. This hypothesis was further supported by GastroPlusTM simulation. In summary, extent of triazolam absorption was increased to a similar extent with both 2 and 16 h ABT pretreatment regimens, suggesting that either of the regimen can be used to increase parent exposures in rat. With ABT pretreatment, delayed absorption of triazolam and acetaminophen was observed, as suggested by delay in Tmax and MAT, respectively.
13 Creating and using corpora

a. technological progress (e.g., processor speeds as well as hard drive and RAM sizes); b. methodological progress (e.g., the development of software tools, programming languages, and statistical methods); c. a growing desire by many linguists for (more) objective, quantifiable, and replicable findings as an alternative to, or at least as an addition to, intuitive acceptability judgments (see Chapter 3); d. theoretical developments such as the growing interest in cognitively and psycholinguistically motivated approaches to language in which frequency of (co-)occurrence plays an important role for language acquisition, processing, use, and change.
Compact broadband circularly polarized microstrip antenna over artificial ground structure

A compact broadband circularly polarized (CP) antenna over the artificial ground structure (AGS) is investigated. The CP radiation patch is comprised of a truncated corner square patch loaded by an extended strip. The AGS which is comprised of a 4 × 4 slot-loaded square metal patches changes the reflection phase in accordance with the polarization state of the incident wave. Broad bandwidth including impedance bandwidth, 3-dB axial ratio (AR) bandwidth, and gain bandwidth is achieved by properly combining the transmitted wave from the patch antenna and the reflected wave from the AGS. The measured results show that the AR bandwidth of the antenna is 14.0% (2.84–3.26 GHz), while the impedance bandwidth is 41.3% (2.48–3.72 GHz). The antenna gain at boresight is 5.35 dBic at 2.9 GHz. The gain fluctuation is less than 1 dB in the whole operating bandwidth. The overall antenna volume is 0.40 × 0.40 × 0. 048λ0 at 3 GHz.
Game Theoretic Reward Based Adaptive Data Communication in Wireless Sensor Networks

Selfish or non-cooperative behavior of nodes can degrade the performance of a wireless sensor network in many ways. These nodes can cause increased end-to-end delays and unfair energy consumption among the nodes due to higher packet loss ratio and non-utilization of optimal routes. Various nodes’ stimulation techniques have been proposed. Credit-based incentives with game theoretic approaches are said to be more effective in such experiments. This paper introduces a game theoretic reward-based mechanism to balance the work load among network nodes by stimulating them to equally cooperate in data forwarding toward the base station. Various possible parameters associated with a network and its nodes are considered. In addition, a card-based punishment system is introduced, which is rationally applied on the nodes according to their individual importance in the network. A new technique for finding nodes’ individual importance in the network is designed for better manipulation of nodes.
SPC-MAC: A short preamble cognitive MAC protocol for cognitive radio sensor networks

Cognitive radio has been widely recognized as a promising solution to reliable and time-efficient wireless sensor networks. However, cognitive capability requires an extra energy consumption in spectrum sensing and spectrum access, which imposes a rather challenging problem to low cost sensors. This paper proposes a short preamble cognitive medium access control (SPC-MAC) protocol which supports reliable and fast spectrum access while addressing the energy conservation problem in cognitive radio sensor networks (CRSNs). The novelty of SPC-MAC lies in the combination of short preamble sampling (for supporting low duty cycling in CRSNs) and the opportunistic forwarding (for reliable and fast transmission). Because of the self-organizing nature, SPC-MAC does not require a common control channel. Extensive simulations demonstrate the advantage of SPC-MAC over existing works in terms of energy consumption and throughput.
Protective effect of crocin on ultraviolet B-induced dermal fibroblast photoaging

Ultraviolet B (UVB) radiation induces the production of reactive oxygen species (ROS), resulting in the aging of dermal fibroblasts. Crocin, a bioactive constituent of Crocus sativus, possesses anti-oxidation effects. The purpose of the present study was to evaluate the protective effect of crocin on UVB-induced dermal fibroblast photoaging. Human dermal fibroblasts were isolated and cultured with different concentrations of crocin prior to and following exposure to UVB irradiation. The senescent phenotypes of cells were evaluated, including cell proliferation, cell cycle, senescence-associated β-galactosidase (SA-β-gal) expression, intracellular ROS, expression of antioxidant protein glutathione peroxidase 1 (GPX-1) and extracellular matrix protein collagen type 1 (Col-1). Crocin rescued the cell proliferation inhibited by UVB irradiation, prevented cell cycle arrest and markedly decreased the number of SA-β-gal-positive cells. In addition, crocin reduced UVB-induced ROS by increasing GPX-1 expression and other direct neutralization effects. Furthermore, crocin promoted the expression of the extracellular matrix protein Col-1. Crocin could effectively prevent UVB-induced cell damage via the reduction of intracellular ROS; thus, it could potentially be used in the prevention of skin photoaging.
L1 LMS theoretical tap-weight vector update — derivation and simulation results

In this paper, the L1 LMS algorithm is considered as an alternative to conventional cross-correlation processing for generating an estimate of a radar range profile. The update equation for the Li LMS filter tap weight vector is derived to enhance the reader's understanding. Results achieved in simulation using MATLAB® are shown, which illustrate robust performance achieved by an LMS-type algorithm employing a regularization term in the cost function to be minimized when processing simulated radar data for which the transmit noise waveform's spectrum contains multiple notches.
Test structure design for model-based electromigration

As VLSI technology features are pushed to the limit with every generation and with the introduction of new materials and increased current densities to satisfy performance demands, failure risk due to Electromigraton (EM) is ever-increasing. In this paper, we present experimental results using a novel set of test structures to validate a new model-based EM risk assessment approach. In this method, EM risk can be assessed for any interconnect geometry through an exact solution of the fundamental stress equations. This approach eliminates the need for complex look-up tables for different geometries and can be implemented in CAD tools very easily as we demonstrate on real design examples.
Research on automatic summary of Chinese short text based on LSTM and keywords correction

Network platform is an important way for people to exchange information and communicate with each other. In order to ensure users to get the information they want faster, summaries should be generated from these short texts. However, such a large number of summaries have gone far beyond the limit of manual processing, so the automatic summary techniques need to be used to automatically generate the summary. Chinese automatic summary technology starts later, and the summary of short texts generated by the traditional method is not good. In this paper, deep learning method are introduced to generate short text summary automatically, and the keywords of the original text are also used to optimize the results. In the method, an attention-based sequence-to-sequence model with Long-Short Term Memory Network (LSTM) is constructed, which combines the character features and word features as its inputs. The keywords of short texts are used to correct the words of model-generated summary. Experiments show that our method improves the performance of short summaries generation on LCSTS dataset.
Towards Model Checking Android Applications

As feature-rich Android applications (apps for short) are increasingly popularized in security-sensitive scenarios, methods to verify their security properties are highly desirable. Existing approaches on verifying Android apps often have limited effectiveness. For instance, static analysis often suffers from a high false-positive rate, whereas approaches based on dynamic testing are limited in coverage. In this work, we propose an alternative approach, which is to apply the software model checking technique to verify Android apps. We have built a general framework named DroidPF upon Java PathFinder (JPF), towards model checking Android apps. In the framework, we craft an executable mock-up Android OS which enables JPF to dynamically explore the concrete state spaces of the tested apps; we construct programs to generate user interaction and environmental input so as to drive the dynamic execution of the apps; and we introduce Android specific reduction techniques to help alleviate the state space explosion. DroidPF focuses on common security vulnerabilities in Android apps including sensitive data leakage involving a non-trivial flow- and context-sensitive taint-style analysis. DroidPF has been evaluated with 131 apps, which include real-world apps, third-party libraries, malware samples and benchmarks for evaluating app analysis techniques like ours. DroidPF precisely identifies nearly all of the previously known security issues and nine previously unreported vulnerabilities/bugs.
Space-time constrained optimization for deep locomotion controller

Physics-based methods synthesize motion for virtual characters following physics principles in real world. Given the high dimensions and continuity of joint actuation, designing a controller for virtual characters is a challenging task. Existing methods normally construct the controller based on Finite State Machine, which is a manual process and requires expert knowledge. This paper uses deep neural network, as the locomotion controller, to control the motion of virtual characters. The network learning is conducted with the Deep Deterministic Policy Gradient. We propose to integrate space-time constraints, as part of the reward function, during the learning process. The experiment results confirm that the introduction of the space-time constraints avoids the problem of generating awkward gait (as observed in existing methods).
Load balancing video clients in enterprise wireless networks

Given the increasing popularity of real-time video communication over enterprise wireless networks, ensuring good quality of experience is becoming critical. A common problem in such networks is that the clients typically adopt the strategy of associating to the access point with the highest signal strength, which can lead to load imbalance, unfair throughput allocation, and low overall video quality. In this paper, we propose to improve load balancing across video clients by selectively triggering directed roams of chosen clients, while explicitly accounting for the cost of roaming. We formulate the problem of identifying the directed roams to perform as an optimization problem where the objective function reflects both the overall utility of all video clients and the cost due to roaming. We subsequently apply relaxations to the original NP-Hard problem, and propose a three-stage algorithm that efficiently computes an approximate solution. Simulations show that by selectively roaming just 5% of the clients, we increase throughput relative to an initial strongest signal based association by at least 10% for over half of the clients and by at least 20% for over a quarter of the clients. We also increase aggregate throughput, improve fairness and thereby increase the overall video quality.
A high step up boost converter

Based on the addition of conventional boost converter, a new non-isolated step up converter is proposed. It is mainly used in high voltage application where a high conversion is required. The main feature is the possibility of modularity of the structure. The control and implementation is simple. Also the balance across the capacitor is natural. An analysis of the proposed converter with operation principle, static gain and voltage and current stresses in the main components is explained. The working of the proposed converter and simulation results are presented. The output voltage of the integrated boost is much more higher depending on the number of integrated converter than the conventional boost converter.
Reinforcement-learning-aided ML detector for uplink massive MIMO systems with low-precision ADCs

This paper considers an uplink massive multiple-input multiple-output (MIMO) system with low-precision analog-to-digital converters (ADCs). In this system, a robust maximum-likelihood detection (MLD) method is proposed under imperfect channel state information at a receiver (CSIR). Inspired by reinforcement learning theory, the idea of the proposed method is to enhance the accuracy of a likelihood function estimated at the receiver, by exploiting associations between correctly detected data symbols and quantized received signals. The proposed method utilizes these associations as training examples to learn the true likelihood function of the system, which provides a more accurate estimate for the likelihood function that can overcome the effect of imperfect CSIR. Simulation results show that the proposed MLD considerably outperforms the conventional MLD in terms of the detection performance under imperfect CSIR.
RSE et développement durable en PME

Les petites et moyennes entreprises (PME) ont des caractéristiques particulières tant sur le plan macroéconomique que microéconomique qui justifient que la responsabilité sociale des entreprises (RSE) soit adaptée à leur contexte. C’est l’une des principales observations sur laquelle s’appuie chacun des sept chapitres de cet ouvrage collectif. En effet, sur le plan macroéconomique, les PME sont importantes d’un point de vue numérique (95 % des entreprises) comme en termes de création d’emplois et de richesse. Dans ce sens, sans une intégration de la RSE dans une masse critique de PME, le développement durable risque d’être un projet difficilement réalisable. Sur le plan microéconomique, il est reconnu aux PME des modes de fonctionnement et de gestion particuliers. Par conséquent, la transposition dans la PME d’approches théoriques, de méthodes, d’outils de gestion ou même de politiques conçus à l’origine pour la grande entreprise doit se faire avec prudence. Le traitement de problématiques contemporaines telles que la RSE et le développement durable devrait donc faire sienne cette réalité des PME, afin d’apporter des réponses satisfaisantes aux préoccupations de leurs dirigeants. En ce qui concerne la RSE, ces préoccupations sont d’ordre conceptuel, stratégique et opérationnel. Cependant, il semble que jusque dans les années 2011, celles-ci ont fait l’objet de très peu de recherche. Cet ouvrage tente ainsi d’apporter sa contribution à une meilleure compréhension de la RSE et du développement durable en contexte de PME.