Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-Layer Scheduler for DVB-S2/S2X with Time Slicing

This paper deals with forward link scheduling at a terrestrial Gateway (GW) for a geostationary satellite system based on the DVB-S2/S2X standard. We consider the case of Time-Slicing (TS) that deserves particular attention for the current market of high-throughput low-cost user terminals. Two QoS traffic classes and related requirements have been envisaged that is real-time and non-real-time services. In this paper, a novel multi-stage GW scheduler architecture is investigated in order to support the TS option of DVB-S2/S2X. This scheduler takes several aspects into account, such as IP class of service, PHY-layer conditions, BBframe generation, and TS structure. Many scheduling schemes are compared for both real-time and non-real-time services in terms of different performance indexes related to the traffic management at the terrestrial GW. A simulator has been built modifying the SNS3 simulator developed in another project.
Analysing Shortcomings of Statistical Parametric Speech Synthesis

Output from statistical parametric speech synthesis (SPSS) remains noticeably worse than natural speech recordings in terms of quality, naturalness, speaker similarity, and intelligibility in noise. There are many hypotheses regarding the origins of these shortcomings, but these hypotheses are often kept vague and presented without empirical evidence that could confirm and quantify how a specific shortcoming contributes to imperfections in the synthesised speech. Throughout speech synthesis literature, surprisingly little work is dedicated towards identifying the perceptually most important problems in speech synthesis, even though such knowledge would be of great value for creating better SPSS systems. In this book chapter, we analyse some of the shortcomings of SPSS. In particular, we discuss issues with vocoding and present a general methodology for quantifying the effect of any of the many assumptions and design choices that hold SPSS back. The methodology is accompanied by an example that carefully measures and compares the severity of perceptual limitations imposed by vocoding as well as other factors such as the statistical model and its use.
Synergistic Activity of Colistin-Containing Combinations against Colistin-Resistant Enterobacteriaceae

Resistance to colistin, a polypeptide drug used as an agent of last resort for the treatment of infections caused by multidrug-resistant (MDR) and extensively drug-resistant (XDR) Gram-negative bacteria, including carbapenem-resistant Enterobacteriaceae (CRE), severely limits treatment options and may even transform an XDR organism into one that is pan-resistant. We investigated the synergistic activity of colistin in combination with 19 antibiotics against a collection of 20 colistin-resistant Enterobacteriaceae isolates, 15 of which were also CRE. ABSTRACT Resistance to colistin, a polypeptide drug used as an agent of last resort for the treatment of infections caused by multidrug-resistant (MDR) and extensively drug-resistant (XDR) Gram-negative bacteria, including carbapenem-resistant Enterobacteriaceae (CRE), severely limits treatment options and may even transform an XDR organism into one that is pan-resistant. We investigated the synergistic activity of colistin in combination with 19 antibiotics against a collection of 20 colistin-resistant Enterobacteriaceae isolates, 15 of which were also CRE. All combinations were tested against all strains using an inkjet printer-assisted digital dispensing checkerboard array, and the activities of those that demonstrated synergy by this method were evaluated against a single isolate in a time-kill synergy study. Eighteen of 19 combinations demonstrated synergy against two or more isolates, and the 4 most highly synergistic combinations (colistin combined with linezolid, rifampin, azithromycin, and fusidic acid) were synergistic against ≥90% of strains. Sixteen of 18 combinations (88.9%) that were synergistic in the checkerboard array were also synergistic in a time-kill study. Our findings demonstrate that colistin in combination with a range of antibiotics, particularly protein and RNA synthesis inhibitors, exhibits synergy against colistin-resistant strains, suggesting that colistin may exert a subinhibitory permeabilizing effect on the Gram-negative bacterial outer membrane even in isolates that are resistant to it. These findings suggest that colistin combination therapy may have promise as a treatment approach for patients infected with colistin-resistant XDR Gram-negative pathogens.
Learning to Control the Specificity in Neural Response Generation

In conversation, a general response (e.g., “I don’t know”) could correspond to a large variety of input utterances. Previous generative conversational models usually employ a single model to learn the relationship between different utterance-response pairs, thus tend to favor general and trivial responses which appear frequently. To address this problem, we propose a novel controlled response generation mechanism to handle different utterance-response relationships in terms of specificity. Specifically, we introduce an explicit specificity control variable into a sequence-to-sequence model, which interacts with the usage representation of words through a Gaussian Kernel layer, to guide the model to generate responses at different specificity levels. We describe two ways to acquire distant labels for the specificity control variable in learning. Empirical studies show that our model can significantly outperform the state-of-the-art response generation models under both automatic and human evaluations.
Time-Variant Cluster-Based Channel Modeling for V2V Communications

With the advent of vehicle-to-vehicle (V2V) communication, the research on the propagation channel modeling between vehicles becomes a vital topic. In this paper, measurements of V2V radio channel are conducted in a suburban scenario. The measurements are performed at the center frequency of 5.9 GHz with a bandwidth of 50 MHz. A single omnidirectional antenna is placed at the transmitter (Tx) vehicle, and a 16 dual-polarized cylindrical antenna array is adopted at the receiver (Rx) vehicle. The multipath components (MPCs) are extracted based on the Space- Alternating Generalized Expectation-maximization (SAGE) algorithm, and we also apply an automatic clustering and tracking algorithm to cluster the MPCs and track the time-variant clusters for our measured V2V channel. Under such a scheme, a time- variant cluster-based channel modeling approach is proposed. The model parameters include a number of inter-cluster parameters and some intra-cluster parameters, which are provided with detailed analysis. The proposed model is useful for characterizing the time-variant V2V channel with high accuracy and low complexity.
A aprendizagem das crianças na cultura digital

O estudo analisa como as criancas incorporam e usam as Tecnologias Digitais de Informacao e Comunicacao (TDIC) em seus processos de aprendizagem, no contexto escolar e extra escolar, considerando que estas tecnologias fazem parte do cotidiano destas criancas e influenciam diretamente em seu desenvolvimento cognitivo. A pesquisa, enquanto metodo misto e configurada como Estudo de Caso, se fundamentou nos estudos historico-culturais, a partir de Vygotsky e na analise emergente do aprendizado em rede, de Siemens e Downes. As criancas participantes da pesquisa fazem parte da cultura digital e apresentam especificidades e singularidades no aprender com e sobre as TDIC. No aporte teorico, destacam-se alguns conceitos relevantes para esta investigacao: cultura digital, Zona de Desenvolvimento Proximal (ZDP), estrategia cognitiva e Conectivismo. O processo de aprendizagem de 57 criancas do 5o ano do Ensino Fundamental foi acompanhado entre os meses de maio a agosto de 2014, a partir da observacao em suas praticas no laboratorio de informatica de uma escola da rede privada de ensino de Maceio, como tambem nos momentos de intervalo de aulas (recreio), em conjunto com os instrumentos: questionario; entrevista semi-estruturada; planos de aula das professoras da serie. Para compreender as respostas dos participantes nas tecnicas utilizadas, foi incorporado um olhar comparativo para estabelecer relacoes entre o contexto escolar e o contexto extra escolar, utilizando apropriacao tecnologica, uso das TDIC como estrategias de aprendizagem e compartilhamento, criacao, inovacao e colaboracao em rede como categorias de analise. Os dados da pesquisa mostraram que as criancas estao inseridas na cultura digital e utilizam as TDIC como estrategia de aprendizagem de forma mais espontânea e inovadora nos ambientes externos a escola. O estudo, evidenciou que as TDIC por si mesmas, nao dao conta do processo aprendizagem e que as interacoes, mesmo de forma limitada por meio das TDIC, sao necessarias e potencializadoras do aprendizado.
Implementing Hitchcock - the Role of Focalization and Viewpoint

Focalization and viewpoint are important aspects of narrative movie-making that need to be taken into account by cinematography and editing. In this paper, we argue that viewpoint can be determined from the first principles of focalization in the screenplay and adherence to a slightly modified version of Hitchcock's rule in cinematography and editing. With minor changes to previous work in automatic cinematography and editing, we show that this strategy makes it possible to easily control the viewpoint in the movie by rewriting and annotating the screenplay. We illustrate our claim with four versions of a moderately complex movie scene obtained by focalizing on its four main characters, with dramatically different camera choices.
Doppler Effect Reduction in an OFDM System Thanks to Massive MIMO

Among many challenges, 5G should improve the quality of service for moving users. In such a mobility context, the Doppler effect creates interference which can severely damage the performance of the systems. The effect of very large number of uncorrelated receive antennas on the Doppler effect is studied in this paper with a simple maximum ratio combining receiver and the orthogonal frequency division multiplexing modulation. This paper relies on an analytical analysis of the signal-to-interference ratio (SIR) and on a statistical analysis of the propagation channel. Therefore, the contribution of this paper is twofold. First, the asymptotic SIR is analytically expressed when the number of receive antennas tends toward infinity. Second, the decrease of the impact of the Doppler effect with the increase of the number of receive antennas is demonstrated, proving that a massive multiple-input multiple-output system with a low-complexity maximum ratio combining receiver can be used to improve the quality of service in mobility scenarios. Finally, the simulation results highlight the impact of such a massive multiple-input multiple-output system in practice.
Food Security of Adolescents in Selected Khat- and Coffee-Growing Areas in the Sidama Zone, Southern Ethiopia

Whilst pervasive food insecurity exists among adolescents in Ethiopia, the available information is scant and inconsistent. Therefore, the main objective of this cross-sectional study was to contribute to these gaps by assessing the food security of adolescents in the selected khat- and coffee-growing areas. We selected 234 (117 girls and 117 boys) adolescents aged 12–18 years via stratified random sampling. We measured the height and weight of the adolescents and asked about their food insecurity experiences. We assessed the prevalence of stunting and thinness using the WHO 2007 growth reference standards. Out of the total, 17 (7.3%) and 30 (12.8%) adolescents were stunted and thin, respectively. In addition, 89 (38.0%) adolescents reported food insecurity experiences and nine (3.8%) were overweight. A regression analyses showed that the stunting was associated with the age of the adolescents and maternal education. Thinness was associated with area, gender, and the number of meals. Food insecurity experiences were associated with health problems in the past 30 days. In general, adolescents from the khat-growing area have better food security than those from the coffee-growing area, and the same is true, gender-wise, for girls compared to boys. We recommend possible interventions primarily for adolescents in coffee-growing areas.
Addressing Noise in Multidialectal Word Embeddings

Word embeddings are crucial to many natural language processing tasks. The quality of embeddings relies on large non-noisy corpora. Arabic dialects lack large corpora and are noisy, being linguistically disparate with no standardized spelling. We make three contributions to address this noise. First, we describe simple but effective adaptations to word embedding tools to maximize the informative content leveraged in each training sentence. Second, we analyze methods for representing disparate dialects in one embedding space, either by mapping individual dialects into a shared space or learning a joint model of all dialects. Finally, we evaluate via dictionary induction, showing that two metrics not typically reported in the task enable us to analyze our contributions’ effects on low and high frequency words. In addition to boosting performance between 2-53%, we specifically improve on noisy, low frequency forms without compromising accuracy on high frequency forms.
Attention-based Semantic Priming for Slot-filling

The problem of sequence labelling in language understanding would benefit from approaches inspired by semantic priming phenomena. We propose that an attention-based RNN architecture can be used to simulate semantic priming for sequence labelling. Specifically, we employ pre-trained word embeddings to characterize the semantic relationship between utterances and labels. We validate the approach using varying sizes of the ATIS and MEDIA datasets, and show up to 1.4-1.9% improvement in F1 score. The developed framework can enable more explainable and generalizable spoken language understanding systems.
On Collusion and Coercion: Agent Interconnectedness and In-Group Behaviour

The interconnectedness of actors is an antecedent for collective corruption, which in turn can lead to endemic corruption in a society. As a testbed for studying the effects of social interconnectedness on corrupt behaviours, we examine the domain of maritime customs. We add to our existing agent-based simulation a nuanced model of actor relatedness, consisting of clan, in-group (sect), and place of origin, and encode associated behavioural norms. We examine in simulation the effects of social interconnectedness on domain performance metrics such as container outcomes, delay, revenue, collusion, and coercive demands. Results confirm that, when corruption is widespread, localized punitive- or incentive-based policies are weakened, and that the effect of process re-engineering is frustrated when interconnectedness increases beyond a critical point, for two out of three forms of homophily connections.
Local Restricted Convolutional Neural Network for Change Detection in Polarimetric SAR Images

To detect changed areas in multitemporal polarimetric synthetic aperture radar (SAR) images, this paper presents a novel version of convolutional neural network (CNN), which is named local restricted CNN (LRCNN). CNN with only convolutional layers is employed for change detection first, and then LRCNN is formed by imposing a spatial constraint called local restriction on the output layer of CNN. In the training of CNN/LRCNN, the polarimetric property of SAR image is fully used instead of manual labeled pixels. As a preparation, a similarity measure for polarimetric SAR data is proposed, and several layered difference images (LDIs) of polarimetric SAR images are produced. Next, the LDIs are transformed into discriminative enhanced LDIs (DELDIs). CNN/LRCNN is trained to model these DELDIs by a regression pretraining, and then a classification fine-tuning is conducted with some pseudolabeled pixels obtained from DELDIs. Finally, the change detection result showing changed areas is directly generated from the output of the trained CNN/LRCNN. The relation of LRCNN to the traditional way for change detection is also discussed to illustrate our method from an overall point of view. Tested on one simulated data set and two real data sets, the effectiveness of LRCNN is certified and it outperforms various traditional algorithms. In fact, the experimental results demonstrate that the proposed LRCNN for change detection not only recognizes different types of changed/unchanged data, but also ensures noise insensitivity without losing details in changed areas.
Fundamental Limits of Caching: Improved Rate-Memory Tradeoff with Coded Prefetching

We consider a cache network in which a single server is connected to multiple users via a shared error free link. The server has access to a database with 𝒩 files of equal length $F$, and serves $K$ users each with a cache memory of $MF$ bits. A novel centralized coded caching scheme is proposed for cenarios with more users than files $N\leq K$ and cache capacities satisfying $\frac{1}{K}\leq M\leq\frac{N}{K}$. The proposed scheme outperforms the best rate-memory region known in the literature if $N\leq K\leq\frac{N^{2}+1}{2}$.
Pathological Response and Survival in Triple-Negative Breast Cancer Following Neoadjuvant Carboplatin plus Docetaxel

Purpose: Prognostic value of pathologic complete response (pCR) and extent of pathologic response attained with anthracycline-free platinum plus taxane neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) is unknown. We report recurrence-free survival (RFS) and overall survival (OS) according to degree of pathologic response in patients treated with carboplatin plus docetaxel NAC. Patients and Methods: One-hundred and ninety patients with stage I–III TNBC were treated with neoadjuvant carboplatin (AUC6) plus docetaxel (75 mg/m2) every 21 days × 6 cycles. pCR (no evidence of invasive tumor in breast and axilla) and Residual cancer burden (RCB) were evaluated. Patients were followed for recurrence and survival. Extent of pathologic response was associated with RFS and OS using the Kaplan–Meier method. Results: Median age was 51 years, and 52% were node-positive. pCR and RCB I rates were 55% and 13%, respectively. Five percent of pCR patients, 0% of RCB I patients, and 58% of RCB II/III patients received adjuvant anthracyclines. Three-year RFS and OS were 79% and 87%, respectively. Three-year RFS was 90% in patients with pCR and 66% in those without pCR [HR = 0.30; 95% confidence interval (CI), 0.14–0.62; P = 0.0001]. Three-year OS was 94% in patients with pCR and 79% in those without pCR (HR = 0.25; 95% CI, 0.10–0.63; P = 0.001). Patients with RCB I demonstrated 3-year RFS (93%) and OS (100%) similar to those with pCR. On multivariable analysis, higher tumor stage, node positivity, and RCB II/III were associated with worse RFS. Conclusions: Neoadjuvant carboplatin plus docetaxel yields encouraging efficacy in TNBC. Patients achieving pCR or RCB I with this regimen demonstrate excellent 3-year RFS and OS without adjuvant anthracycline.
Physics-Based Features for Anomaly Detection in Power Grids with Micro-PMUs

The expansion of monitoring systems for power grids from the traditional transmission lines to include the distribution grid - closer to the end-user - is largely due to the advance in electrical monitoring devices and their increasing affordability. This paradigm-shift benefits from new algorithms that can be implemented at the grid edge (as opposed to the transmission grid) to detect anomalies faster, more efficiently, and in real-time. Micro-PMUs are phasor measurement units that can be placed on the distribution lines to provide real-time data about the state of the grid and can detect fast transients. In this paper, we use data from micro-PMUs to engineer physics-based features for a novel anomaly detection algorithm that detects anomalies based on the transient properties of the power grid. This allows for a more capable, agile, and reliable anomaly scoring system that can learn normal behavior patterns and detect anomalous behavior efficiently. We show that by combining the classical data-based approaches with physics-based features in the anomaly detection algorithm, the machine learning algorithm proposed is capable of detecting different classes of anomalies (such as edge devices on-off attacks, single line-to-ground (SLG) faults, etc.). Simulation results on IEEE 34-node test feeder show that we can achieve better detection performance than traditional techniques for a broader class of anomalies.
Spacing of cue-approach training leads to better maintenance of behavioral change

The maintenance of behavioral change over the long term is essential to achieve public health goals such as combatting obesity and drug use. Previous work by our group has demonstrated a reliable shift in preferences for appetitive foods following a novel non-reinforced training paradigm. In the current studies, we tested whether distributing training trials over two consecutive days would affect preferences immediately after training as well as over time at a one-month follow-up. In four studies, three different designs and an additional pre-registered replication of one sample, we found that spacing of cue-approach training induced a shift in food choice preferences over one month. The spacing and massing schedule employed governed the long-term changes in choice behavior. Applying spacing strategies to training paradigms that target automatic processes could prove a useful tool for the long-term maintenance of health improvement goals with the development of real-world behavioral change paradigms that incorporate distributed practice principles.
Gut Microbial β-Glucuronidase Inhibition via Catalytic Cycle Interception

Microbial β-glucuronidases (GUSs) cause severe gut toxicities that limit the efficacy of cancer drugs and other therapeutics. Selective inhibitors of bacterial GUS have been shown to alleviate these side effects. Using structural and chemical biology, mass spectrometry, and cell-based assays, we establish that piperazine-containing GUS inhibitors intercept the glycosyl-enzyme catalytic intermediate of these retaining glycosyl hydrolases. We demonstrate that piperazine-based compounds are substrate-dependent GUS inhibitors that bind to the GUS–GlcA catalytic intermediate as a piperazine-linked glucuronide (GlcA, glucuronic acid). We confirm the GUS-dependent formation of inhibitor–glucuronide conjugates by LC–MS and show that methylated piperazine analogs display significantly reduced potencies. We further demonstrate that a range of approved piperazine- and piperidine-containing drugs from many classes, including those for the treatment of depression, infection, and cancer, function by the same mechanism, and we confirm through gene editing that these compounds selectively inhibit GUS in living bacterial cells. Together, these data reveal a unique mechanism of GUS inhibition and show that a range of therapeutics may impact GUS activities in the human gut.
Contribution of Host Defence Proteins and Peptides to Host-Microbiota Interactions in Chronic Inflammatory Lung Diseases

The respiratory tract harbours a variety of microorganisms, collectively called the respiratory microbiota. Over the past few years, alterations in respiratory and gut microbiota composition have been associated with chronic inflammatory diseases of the lungs. How these changes influence disease development and progression is an active field of investigation. Identifying and understanding host-microbiota interactions and factors contributing to these interactions could promote the development of novel therapeutic strategies aimed at restoring host-microbiota homeostasis. In this review, we discuss recent literature on host-microbiota interactions in the respiratory tract, with a specific focus on the influence of endogenous host defence peptides and proteins (HDPs) on the composition of microbiota populations in vivo and explore possible HDPs-related therapeutic approaches targeting microbiota dysbiosis in chronic inflammatory lung diseases.