Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Long-Term Coding of LSF Parameters Trajectories for Large-Delay/Very- to Ultra-Low Bit-Rate Speech Coding

This paper presents a model-based method for coding the LSF parameters of LPC speech coders on a "long-term" basis, that is, beyond the usual 20–30 ms frame duration. The objective is to provide efficient LSF quantization for a speech coder with large delay but very- to ultra-low bit-rate (i.e., below 1 kb/s). To do this, speech is first segmented into voiced/unvoiced segments. A Discrete Cosine model of the time trajectory of the LSF vectors is then applied to each segment to capture the LSF interframe correlation over the whole segment. Bi-directional transformation from the model coefficients to a reduced set of LSF vectors enables both efficient "sparse" coding (using here multistage vector quantizers) and the generation of interpolated LSF vectors at the decoder. The proposed method provides up to 50% gain in bit-rate over frame-by-frame quantization while preserving signal quality and competes favorably with 2D-transform coding for the lower range of tested bit rates. Moreover, the implicit time-interpolation nature of the long-term coding process provides this technique a high potential for use in speech synthesis systems.
Moulded pulp products manufacturing with thermoforming

Over the past years, eco‐friendly packaging solutions such as moulded pulp have resonated with a growing number of consumers. Among all of them, the thermoformed products make use of the most recent manufacturing approach that produces high‐quality, thin‐walled items. However, it remains an underresearched area, and the development of an efficient and precise manufacturing process is fundamental in order to increase the implementation of sustainable packaging.
The homeobox gene DLX4 regulates erythro-megakaryocytic differentiation by stimulating IL-1β and NF-κB signaling

ABSTRACT Megakaryocyte and erythroid development are tightly controlled by a repertoire of cytokines, but it is not clear how cytokine-activated signaling pathways are controlled during development of these two lineages. Here, we identify that expression of DLX4, a transcription factor encoded by a homeobox gene, increases during megakaryopoiesis but decreases during erythropoiesis. Enforced expression of DLX4 in CD34+ stem and progenitor cells and in bipotent K562 cells induced lineage markers and morphologic features of megakaryocytes and repressed erythroid marker expression and hemoglobin levels. Converse results were obtained when DLX4 was knocked down. Gene Ontology and Gene Set Enrichment Analyses of genome-wide changes in gene expression revealed that DLX4 induces a megakaryocytic transcriptional program and inhibits an erythroid transcriptional program. DLX4 also induced gene signatures that are associated with nuclear factor κB (NF-κB) signaling. The ability of DLX4 to promote megakaryocyte development at the expense of erythroid generation was diminished by blocking NF-κB activity or by repressing IL1B, a transcriptional target of DLX4. Collectively, our findings indicate that DLX4 exerts opposing effects on the megakaryocytic and erythroid lineages in part by inducing IL-1β and NF-κB signaling. Summary: The homeobox gene DLX4 promotes megakaryocyte development at the expense of erythroid generation by inducing IL-1 and NF-κB signaling.
Contributions to Lane Marking Based Localization for Intelligent Vehicles. (Contribution à la localisation de véhicules intelligents à partir de marquage routier)

Autonomous Vehicles (AV) applications and Advanced Driving Assistance Systems (ADAS) relay in scene understanding processes allowing high level systems to carry out decision marking. For such systems, the localization of a vehicle evolving in a structured dynamic environment constitutes a complex problem of crucial importance. Our research addresses scene structure detection, localization and error modeling. Taking into account the large functional spectrum of vision systems, the accessibility of Open Geographical Information Systems (GIS) and the widely presence of Global Positioning Systems (GPS) onboard vehicles, we study the performance and the reliability of a vehicle localization method combining such information sources. Monocular vision–based lane marking detection provides key information about the scene structure. Using an enhanced multi-kernel framework with hierarchical weights, the proposed parametric method performs, in real time, the detection and tracking of the ego-lane marking. A self-assessment indicator quantifies the confidence of this information source. We conduct our investigations in a localization system which tightly couples GPS, GIS and lane makings in the probabilistic framework of Particle Filter (PF). To this end, it is proposed the use of lane markings not only during the map-matching process but also to model the expected ego-vehicle motion. The reliability of the localization system, in presence of unusual errors from the different information sources, is enhanced by taking into account different confidence indicators. Such a mechanism is later employed to identify error sources. This research concludes with an experimental validation in real driving situations of the proposed methods. They were tested and its performance was quantified using an experimental vehicle and publicly available datasets.
The Anti-Adhesive Effect of Curcumin on Candida albicans Biofilms on Denture Materials

The use of natural compounds as an alternative source of antimicrobials has become a necessity given the growing concern over global antimicrobial resistance. Polyphenols, found in various edible plants, offers one potential solution to this. We aimed to investigate the possibility of using curcumin within the context of oral health as a way of inhibiting and preventing the harmful development of Candida albicans biofilms. We undertook a series of adsorption experiments with varying concentrations of curcumin, showing that 50 μg/ml could prevent adhesion. This effect could be further synergized by the curcumin pre-treatment of yeast cells to obtain significantly greater inhibition (>90%, p < 0.001). Investigation of the biological impact of curcumin showed that it preferentially affected immature morphological forms (yeast and germlings), and actively promoted aggregation of the cells. Transcriptional analyses showed that key adhesins were down-regulated (ALS1 and ALS3), whereas aggregation related genes (ALS5 and AAF1) were up-regulated. Collectively, these data demonstrated that curcumin elicits anti-adhesive effects and that induces transcription of genes integrally involved in the processes related to biofilm formation. Curcumin and associated polyphenols therefore have the capacity to be developed for use in oral healthcare to augment existing preventative strategies for candidal biofilms on the denture surface.
Characterization of the Mechanical Integrity of Cu Nanowire-Based Transparent Conducting Electrode

Smooth Cu nanowires were synthesized in a dual surfactant hydrothermal process using oleylamine and oleic acid. The Cu nanowires have a mean diameter of 82.3 nm and lengths >300 μm. Cu nanowire based transparent conducting electrodes were successfully fabricated with a decreased sheet resistance of 3.479 to 1.04 kΩ/sq in an increasing nanowire density with a transmittance from 94-80 %. The fabricated transparent electrode exhibits good mechanical stability with high flexibility even after 50 bending cycles. This indicates strong adhesion of the Cu nanowires on the substrate.
Searchable encryption with decryption in the standard model

A searchable public key encryption (PEKS) scheme allows to generate, for any given message W , a trapdoor TW , such that TW allows to check whether a given ciphertext is an encryption ofW or not. Of course, TW should not reveal any additional information about the plaintext. PEKS schemes have interesting applications: for instance, consider an email gateway that wants to prioritize or filter encrypted emails based on keywords contained in the message text. The email recipient can then enable the gateway to do so by releasing the trapdoors for the corresponding keywords. This way, the gateway can check emails for these keywords, but it learns nothing more about the email contents. PEKS schemes have first been formalized and constructed by Boneh et al. But with one exception, no known construction of a PEKS scheme supports the decryption of ciphertexts. That is, known constructions allow to test for a certain message, but they do not allow to retrieve the message, even when having the full secret key. Besides being somewhat unnatural for an encryption scheme, this “no-decryption”-property also limits the applicability of a PEKS scheme. The one exception, a PEKS scheme with decryption due to Fuhr and Paillier, is formulated in the random oracle model, and inherently relies on the statistical properties of the random oracle. In fact, Fuhr and Paillier leave it as an open problem to construct a PEKS scheme with decryption in the standard model. In this paper, we construct the first PEKS scheme with decryption (PEKSD scheme) in the standard model. Our sole assumption is an anonymous IBE scheme. We explain the technical difficulties that arise with previous attempts to build a PEKS scheme with decryption and how we overcome these difficulties. Technically, we isolate a vital additional property of IBE schemes (a property we call well-addressedness and which states that a ciphertext is tied to an identity and will be rejected when trying to decrypt with respect to any other identity) and show how to generically achieve it. Our construction of a PEKSD scheme from an anonymous IBE scheme provides a natural example of a non-shielding construction (in which the decryption algorithm queries the encryption algorithm). Gertner et al. have shown that an IND-CCA secure public key encryption scheme cannot be constructed and proven from an IND-CPA secure scheme in a black-box and shielding way. However, our results give evidence that encryption queries in the decryption algorithm may well prove useful in a security reduction. ∗CWI, Amsterdam, The Netherlands. E-mail: Dennis.Hofheinz@cwi.nl †CWI, Amsterdam, The Netherlands. E-mail: e.n. weinreb@cwi.nl
Integration Techniques for Micro/Nanostructure-Based Large-Area Electronics

Advanced nanostructured materials such as organic and inorganic micro/nanostructures are excellent building blocks for electronics, optoelectronics, sensing, and photovoltaics because of their high-crystallinity, long aspect-ratio, high surface-to-volume ratio, and low dimensionality. However, their assembly over large areas and integration in functional circuits are a matter of intensive investigation. This Element provides detailed description of various technologies to realize micro/nanostructures based large-area electronics (LAE) devices on rigid or flexible/stretchable substrates. The first section of this Element provides an introduction to the state-of-the-art integration techniques used to fabricate LAE devices based on different kind of micro/nanostructures. The second section describes inorganic and organic micro/nanostructures, including most common and promising synthesis procedures. In the third section,different techniques are explained that have great potential for integration of micro/nanostructures over large areas. Finally, the fourth section summarizes important remarks about LAE devices based on micro/nanostructures, and future directions.
GreenGlue: Power Optimization for Data Centers through Resource-Guaranteed VM Placement

In a data center, virtual machines (VMs) not only require the server resource (e.g., CPU, memory) but also might generate a lot of network traffic among themselves. Existing research works on VMs placement are focusing on (1) how to place VMs to minimize server energy consumption without considering consumption of network resources, or (2) how to minimize inter-VM network traffic without considering energy consumption. In this work, we tackle the power saving issue of data centers from the point of view of VM placement as well, but, our idea is to address VM placement problem by joint consideration of both server and network energy consumption for minimizing total power consumption of a data center. First, we validate that the network power consumption plays an important part on the total power consumption of a data center by analyzing the data center architectures and the power benchmark of IT equipments. Next, we propose an energy-aware VM placement algorithm, called GreenGlue, which jointly optimizes the power consumed by servers and switches. GreenGlue is able to address initial VM placement issue, in which VM requests are given and no running VM exists in a data center. Furthermore, an optimal VM placement model is derived via the mixed integer linear programming. Finally, we present a comprehensive performance study via simulation with different scenarios generated by synthetic and real traffic traces. The results show that GreenGlue can perform better than existing VM placement schemes in terms of the power saving and the rate of finding feasible placement.
Latchup in bulk FinFET technology

Latchup (LU) had been considered to be less important in advanced CMOS technologies. However, I/O interface and analog applications can still operate at high voltage (e.g., 1.8V or 3.3V) in sub-20nm bulk FinFET technologies. LU threats are never eliminated and the sensitivity towards LU is increased in bulk FinFET technology.
Enhanced BRET Technology for the Monitoring of Agonist-Induced and Agonist-Independent Interactions between GPCRs and β-Arrestins

The bioluminescence resonance energy transfer (BRET) technique has become extremely valuable for the real-time monitoring of protein–protein interactions in live cells. This method is highly amenable to the detection of G protein-coupled receptor (GPCR) interactions with proteins critical for regulating their function, such as β-arrestins. Of particular interest to endocrinologists is the ability to monitor interactions involving endocrine receptors, such as orexin receptor 2 or vasopressin type II receptor. The BRET method utilizes heterologous co-expression of fusion proteins linking one protein of interest (GPCR) to a bioluminescent donor enzyme, a variant of Renilla luciferase, and a second protein of interest (β-arrestin) to an acceptor fluorophore. If in close proximity, energy resulting from oxidation of the coelenterazine substrate by the donor will transfer to the acceptor, which in turn fluoresces. Using novel luciferase constructs, we were able to monitor interactions not detectable using less sensitive BRET combinations in the same configuration. In particular, we were able to show receptor/β-arrestin interactions in an agonist-independent manner using Rluc8-tagged mutant receptors, in contrast to when using Rluc. Therefore, the enhanced BRET methodology has not only enabled live cell compound screening as we have recently published, it now provides a new level of sensitivity for monitoring specific transient, weak or hardly detectable protein–protein complexes, including agonist-independent GPCR/β-arrestin interactions. This has important implications for the use of BRET technologies in endocrine drug discovery programs as well as academic research.
Face Sketch Synthesis using E-HMM and Selective Ensemble

In this manuscript, we propose an automatic sketch synthesis algorithm based on embedded hidden Markov model (E-HMM) and selective ensemble strategy. The E-HMM is used to model the nonlinear relationship between a photo-sketch pair firstly, and then a series of pseudo-sketches, which are generated based on several learned models for a given photo, are integrated together with selective ensemble strategy to synthesize a finer face pseudo-sketch. The experimental results illustrate that the proposed algorithm achieves satisfactory effect of sketch synthesis.
Using Lexical Acquisition to Enrich a Predicate Argument Reusable Database

The work described in this paper aims to enrich the noun classifications of an existing database of lexical resources (de Matos and Ribeiro, 2004) adding missing information such as semantic relations. Relations are extracted from an annotated and manually corrected corpus. Semantic relations added to the database are retrieved from noun-appositive relations found in the corpus. The method uses clustering to generate labeled sets of words with hypernym relations between set label and set elements.
Muscles and their myokines

Summary In the past, the role of physical activity as a life-style modulating factor has been considered as that of a tool to balance energy intake. Although it is important to avoid obesity, physical inactivity should be discussed in a much broader context. There is accumulating epidemiological evidence that a physically active life plays an independent role in the protection against type 2 diabetes, cardiovascular diseases, cancer, dementia and even depression. For most of the last century, researchers sought a link between muscle contraction and humoral changes in the form of an ‘exercise factor’, which could be released from skeletal muscle during contraction and mediate some of the exercise-induced metabolic changes in other organs such as the liver and the adipose tissue. We have suggested that cytokines or other peptides that are produced, expressed and released by muscle fibres and exert autocrine, paracrine or endocrine effects should be classified as ‘myokines’. Given that skeletal muscle is the largest organ in the human body, our discovery that contracting skeletal muscle secretes proteins sets a novel paradigm: skeletal muscle is an endocrine organ producing and releasing myokines, which work in a hormone-like fashion, exerting specific endocrine effects on other organs. Other myokines work via paracrine mechanisms, exerting local effects on signalling pathways involved in muscle metabolism. It has been suggested that myokines may contribute to exercise-induced protection against several chronic diseases.
A steganographic approach to mitigate password attacks

With the advancement in cyber security, attacks on passwords are also becoming advanced and industrial espionage poses one of the greatest danger to business these days. Critical corporate information gets on stake with the password of system falling into wrong hands. With many tools and tables available to break preliminary security levels, stress is laid on multilayered security for storage and communication of enterprise's delicate information. In this paper, we analyse two popular password attacks based on the time needed to crack them. We then propose a solution which uses steganography (text and image) to store the password and user account information which adds additional layers of security.
On a new generation of torque controlled light-weight robots

The paper describes the recent design and development efforts in DLR Robotics Lab towards the second generation of light-weight robots. The design of the light weight mechanics, integrated sensors and electronics is outlined. The fully sensory joint, with motor and link position sensors as well as joint torque sensors enables the implementation of effective vibration damping and advanced control strategies for compliant manipulation. The mechatronic approach incorporates a tight collaboration between mechanics, electronics and controller design. The authors hope that important steps towards a new generation of service and personal robots have been achieved.
Semi-tied covariance matrices

A standard problem in many classification tasks is how to model feature vectors whose elements are highly correlated. If multi-variate Gaussian distributions are used to model the data then they must have full covariance matrices to accurately do so. This requires a large number of parameters per distribution which restricts the number of distributions that may be robustly estimated, particularly when high dimensional feature vectors are required. This paper describes an alternative to full covariance matrices in these situations. An approximate full covariance matrix is used. The covariance matrix is now split into two elements, one full and one diagonal, which may be tied at completely separate levels. Typically, the full elements are extensively tied, resulting in only a small increase in the number of parameters compared to the diagonal case. Thus dramatically increasing the number of distributions that may be robustly estimated. Simple iterative re-estimation formulae for all the parameters within the standard EM framework are presented. On a large vocabulary speech recognition task a 10% reduction in word error rate over a standard system was achieved.
Bundle adjustment from sonar images and SLAM application for seafloor mapping

This paper reports on two-view bundle adjustment using sonar images, specifically focusing on feature detection and a sensor measurement model for imaging sonar. To overcome limited sensor information for underwater navigation, we use Dual frequency IDentification SONar (DIDSON) in the imaging mode to provide spatial constraints when a scene is revisited. Unlike terrestrial images, sonar images are usually low resolution with highly speckled noise. We found that exploiting features from nonlinear scale space improves feature detection. In this paper, we adopt KAZE features and use random sample consensus (RANSAC) to refine correspondences. Using these correspondences, we propose point-based relative pose estimation via bundle adjustment. The target application that this work focuses on is underwater seafloor mapping, and the proposed model assumes a fixed elevation. Through this work, we present (i) validation of nonlinear scale space features for sonar images and (ii) proposal of a sonar sensor measurement model for underwater simultaneous localization and mapping (SLAM). The proposed method will be validated through both synthetic data sets and a tank test for seafloor mapping.
Annealing-Based Electrical Tuning of Cobalt-Carbon Deposits Grown by Focused-Electron-Beam-Induced Deposition.

An effective postgrowth electrical tuning, via an oxygen releasing method, to enhance the content of non-noble metals in deposits directly written with gas-assisted focused-electron-beam-induced deposition (FEBID) is presented. It represents a novel and reproducible method for improving the electrical transport properties of Co-C deposits. The metal content and electrical properties of Co-C-O nanodeposits obtained by electron-induced dissociation of volatile Co2(CO)8 precursor adsorbate molecules were reproducibly tuned by applying postgrowth annealing processes at 100 °C, 200 °C, and 300 °C under high-vacuum for 10 min. Advanced thin film EDX analysis showed that during the annealing process predominantly oxygen is released from the Co-C-O deposits, yielding an atomic ratio of Co:C:O = 100:16:1 (85:14:1) with respect to the atomic composition of as-written Co:C:O = 100:21:28 (67:14:19). In-depth Raman analysis suggests that the amorphous carbon contained in the as-written deposit turns into graphite nanocrystals with size of about 22.4 nm with annealing temperature. Remarkably, these microstructural changes allow for tuning of the electrical resistivity of the deposits over 3 orders of magnitude from 26 mΩ cm down to 26 μΩ cm, achieving a residual resistivity of ρ2K/ρ300 K = 0.56, close to the value of 0.53 for pure Co films with similar dimensions, making it especially interesting and advantageous over the numerous works already published for applications such as advanced scanning-probe systems, magnetic memory, storage, and ferroelectric tunnel junction memristors, as the graphitic matrix protects the cobalt from being oxidized under an ambient atmosphere.