Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel Reordering Approaches in Phrase-Based Statistical Machine Translation

This paper presents novel approaches to reordering in phrase-based statistical machine translation. We perform consistent reordering of source sentences in training and estimate a statistical translation model. Using this model, we follow a phrase-based monotonic machine translation approach, for which we develop an efficient and flexible reordering framework that allows to easily introduce different reordering constraints. In translation, we apply source sentence reordering on word level and use a reordering automaton as input. We show how to compute reordering automata on-demand using IBM or ITG constraints, and also introduce two new types of reordering constraints. We further add weights to the reordering automata. We present detailed experimental results and show that reordering significantly improves translation quality.
A modified Marcano method for improving electrical properties of reduced graphene oxide (rGO)

In this paper, a facile and a fast synthesis process of reduced graphene oxide (rGO) is introduced by using a modified Marcano method. A modification of the chemical synthesis method was developed, which uses a small amount of strong acids, a low oxidation temperature and a short stirring process. X-ray diffraction (XRD) pattern and Fourier transform infrared spectrometry (FTIR) spectra confirmed that rGO was successfully synthesized. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images showed rGO in sheet form. Based on energy dispersive x-ray spectrometry (EDX), the surface of the prepared rGO sample was dominated by ~90% of C atoms. Four-point probe measurements showed the electrical conductivity of the prepared rGO sample at 1180 S m−1. Based on the electrochemical impedance spectrometry (EIS) results gives 2.1 Ω charge transfer resistance between the electrode and the electrolyte to the prepared rGO sample. This study provides a new perspective on rGO synthesis using a wet chemical process.
Spindle positioning in human cells relies on proper centriole formation and on the microcephaly proteins CPAP and STIL

Patients with MCPH (autosomal recessive primary microcephaly) exhibit impaired brain development, presumably due to the compromised function of neuronal progenitors. Seven MCPH loci have been identified, including one that encodes centrosome protein 4.1 associated protein (CPAP; also known as centromere protein J, CENPJ). CPAP is a large coiled-coil protein enriched at the centrosome, a structure that comprises two centrioles and surrounding pericentriolar material (PCM). CPAP depletion impairs centriole formation, whereas CPAP overexpression results in overly long centrioles. The mechanisms by which CPAP MCPH patient mutations affect brain development are not clear. Here, we identify CPAP protein domains crucial for its centriolar localization, as well as for the elongation and the formation of centrioles. Furthermore, we demonstrate that conditions that resemble CPAP MCPH patient mutations compromise centriole formation in tissue culture cells. Using adhesive micropatterns, we reveal that such defects correlate with a randomization of spindle position. Moreover, we demonstrate that the MCPH protein SCL/TAL1 interrupting locus (STIL) is also essential for centriole formation and for proper spindle position. Our findings are compatible with the notion that mutations in CPAP and STIL cause MCPH because of aberrant spindle positioning in progenitor cells during brain development.
Pathovar-specific requirement for the Pseudomonas syringae lemA gene in disease lesion formation

The lemA gene is conserved among strains and pathovars of Pseudomonas syringae. In P. syringae pv. syringae B728a, a causal agent of bacterial brown spot disese of bean, the lemA gene is required for lesion formation on leaves and pods. Using lemA-containing DNA as a probe, we determined that 80 P. syringae pv. syringae strains isolated from bean leaves could be grouped into seven classes based on restriction fragment length polymorphism. Marker exchange mutagenesis showed that the lemA gene was required for lesion formation by representative strains from each restriction fragment length polymorphism class. Hybridization to the lemA locus was detected within six different P. syringae pathovars and within Pseudomonas aeruginosa. Interestingly, a lemA homolog was present and functional within the nonpathogenic strain P. syringae Cit7. We cloned a lemA homolog from a genomic library of P. syringae pv. phaseolicola NPS3121, a causal agent of halo blight of bean, that restored lesion formation to a P. syringae pv. syringae lemA mutant. However, a lemA mutant P. syringae pv. phaseolicola strain retained the ability to produce halo blight disease symptoms on bean plants. Therefore, the lemA gene played an essential role in disease lesion formation by P. syringae pv. syringae isolates, but was not required for pathogenicity of a P. syringae pv. phaseolicola strain.
Efficient Algorithms to Solve Bayesian Stackelberg Games for Security Applications

In a class of games known as Stackelberg games, one agent (the leader) must commit to a strategy that can be observed by the other agent (the adversary/follower) before the adversary chooses its own strategy. We consider Bayesian Stackelberg games, in which the leader is uncertain about the type of the adversary it may face. Such games are important in security domains, where, for example, a security agent (leader) must commit to a strategy of patrolling certain areas, and an adversary (follower) can observe this strategy over time before choosing where to attack. We present here two different MIP-formulations, ASAP (providing approximate policies with controlled randomization) and DOBSS (providing optimal policies) for Bayesian Stackelberg games. DOBSS is currently the fastest optimal procedure for Bayesian Stackelberg games and is in use by police at the Los Angeles International Airport(LAX) to schedule their activities.
MPTP-Induced Dopamine Depletion in Basolateral Amygdala via Decrease of D2R Activation Suppresses GABAA Receptors Expression and LTD Induction Leading to Anxiety-Like Behaviors

Anxiety disorders commonly occur in Parkinson’s disease. Using field potential recording and patch-clamp recording, we evaluated influence of MPTP-reduced dopaminergic afferent in basolateral amygdala (BLA), a main region for affective regulation, on excitatory–inhibitory circuits and synaptic plasticity. Field excitatory post-synaptic potential (fEPSP) slopes at external capsule-BLA synapses were increased in MPTP-mice with decreases in paired-pulse facilitation and long-term potentiation amplitude, which were corrected by bath-application of D2R agonist quinpirole or cannabinoid type 1 receptors agonist WIN55,212-2, but not D1R agonist SKF38393. Compared to single waveform fEPSP in control mice, a multi-spike waveform fEPSP was observed in MPTP-mice with prolongation of duration and an increase in paired-pulse inhibition, which were recovered by BLA-injection of quinpirole for 2 days rather than bath-application. Density of GABA-evoked current (IGABA) in BLA principal neurons and GABAAR-α2 subunit expression were reduced in MPTP-mice, which were recovered by administration of quinpirole. Decline of PKC phosphorylation in BLA of MPTP-mice was corrected by bath-application of quinpirole, but not SKF38393. In MPTP-mice, BLA-injection of quinpirole or PKC activator PMA could recover GABAAR expression, which was sensitive to PKC inhibitor GF109203X. The impairment of long-term depression (LTD) in MPTP-mice was rescued by bath-application of GABAAR agonist muscimol or BLA-injection of quinpirole and PMA. Finally, BLA-injection of muscimol, quinpirole or PMA relieved anxiety-like behaviors in MPTP-mice. The results indicate that the MPTP-induced dopamine depletion in BLA principal neurons through reducing D2R-mediated PKC phosphorylation suppresses GABAAR expression and activity, which impairs GABAAR-mediated inhibition and LTD induction leading to anxiety-like behaviors.
Differences in body-composition assumptions across ethnic groups: practical consequences

Body-composition methodologies rely on assumptions that are not constant across ethnic groups. The consequence is that the methods used need to be population specific to guarantee unbiased conclusions. Alternatively, assumption-free methods such as chemical multiple-compartment models or scanning techniques should be used. Adequate and unbiased scientific data on body fat among ethnic population groups are necessary for a better understanding of the aetiology of obesity and its co-morbidities. The World Health Organization cut-off points for underweight, overweight, obesity and fat distribution, now universally defined, may need revision because the relationship between body mass index and body composition, and between indices of fat distribution and the actual amount of visceral fat, differ across ethnic groups. The need for ethnically specific cut-off points for obesity and fat distribution is substantiated, for example, by elevated disease risks at low levels of body mass index in several populations. Properly designed and conducted studies are needed to obtain unbiased information on these topics.
A COMPUTATIONAL FRAMEWORK FOR IMPLEMENTING BAARS’ GLOBAL WORKSPACE THEORY OF CONSCIOUSNESS

We consider Baars’ "Global Workspace" theory of consciousness and discuss its possible representation within a model of intelligent agents. We first review a particular agent implementation that is given by an abstract machine, and then identify the extensions that are required in order to accommodate the main aspects of consciousness. According to Baars’ theory, this amounts to unconscious process coalitions that result in the creation of contexts. These extensions can be formulated within a reified virtual machine encompassing a representation of the original machine as well as an additional introspective component. This computational framework is illustrating throughout using a simple working example.
Augmented Belief Propagation Decoding of Low-Density Parity Check Codes

We propose an augmented belief propagation (BP) decoder for low-density parity check (LDPC) codes which can be utilized on memoryless or intersymbol interference channels. The proposed method is a heuristic algorithm that eliminates a large number of pseudocodewords that can cause nonconvergence in the BP decoder. The augmented decoder is a multistage iterative decoder, where, at each stage, the original channel messages on select symbol nodes are replaced by saturated messages. The key element of the proposed method is the symbol selection process, which is based on the appropriately defined subgraphs of the code graph and/or the reliability of the information received from the channel. We demonstrate by examples that this decoder can be implemented to achieve substantial gains (compared to the standard locally-operating BP decoder) for short LDPC codes decoded on both memoryless and intersymbol interference Gaussian channels. Using the Margulis code example, we also show that the augmented decoder reduces the error floors. Finally, we discuss types of BP decoding errors and relate them to the augmented BP decoder.
Detwinning of preloaded martensite in shape memory alloys and its effect on the cyclic behavior of NiTi cylindrical actuators

A multi-mechanism material model is used to investigate the effect of the degree of martensitic detwinning/reorientation occurring at the end of mechanical preloading, on the performance of shape memory tubular and solid cylindrical actuators. A high-temperature ternary Ni50.3Ti29. 7Hf20 alloy, showing almost complete transformation behavior, and an ordinary binary Ni49.9Ti50. 1 material, depicting incomplete martensitic transformation, are used. The results indicated a clear correlation between the shape memory cyclic actuation behavior and the martensitic deformation character of the selected alloy. More specifically, while the actuation strokes produced by the Ni50.3Ti29. 7Hf20 systems consistently followed a direct pattern for the different geometries and torque magnitudes, the results for the Ni49.9Ti50. 1 cases indicated a behavior that is counterintuitive to what may be expected under pure mechanical loading conditions. In particular, when subjected to the same, high preload torques, Ni49.9Ti50. 1 solid actuator under lesser stresses generated higher twist strokes than a tubular counterpart experiencing higher stresses.
'It is life threatening but I don't mind'. A qualitative study using photo elicitation interviews to explore adolescents' experiences of renal replacement therapies.

BACKGROUND Renal replacement therapy (RRT) transforms the life prospects of young people with established renal failure. However, these treatments can have significant physiological and psychological implications for adolescents as they prepare to transition into adulthood. Health policies increasingly emphasize children and youth's active participation and consultation as users of health services, yet studies infrequently seek their experiences directly. METHODS Adolescents receiving RRT in a large UK teaching hospital took photographs illustrating the impact of their condition and treatment on their lives. Qualitative photo elicitation interviews were conducted to explore the significance of the images and the young person's experiences. Interviews were analysed using descriptive thematic analysis. RESULTS Ten young people aged 13-17 years participated. Themes identified were: (1) understanding and acceptance of treatment; (2) living in a non-functioning body; (3) impact upon daily life; (4) sources of support. Young people found treatments challenging and experienced significant impact on relationships and daily routines. Yet, health was prioritized over body image and participants demonstrated great emotional resilience. Young people valued support from family and friends, although were wary of disclosing their condition in case it resulted in being highlighted as different. Young people reported hospital staff as being caring and professional, but their biggest virtue appeared to be their willingness to treat the young people as 'normal'. CONCLUSIONS Young people engaged readily with the research, and frankly described the impact of RRT on their everyday lives. Service providers must ensure that adolescents' developmental needs are met as traditional tasks of adolescence may lose priority. However, it is also clear that young people's ability to cope with treatments should not be underestimated.
A Novel Near-Infrared Fluorescence Sensor for H2O2 Based on N-Acetyl-L-Cysteine-Capped Gold Nanoparticles

A novel near-infrared fluorescence quenching method has been developed for the determination of hydrogen peroxide based on N-acetyl-L-cysteine-capped gold nanoparticles (NAC-AuNPs) as a fluorescence probe. The prepared gold nanoparticles with the size of about 1.91 nm exhibited strong near-infrared fluorescence emission at 693 nm with excitation wavelength at 450 nm in aqueous solution. The fluorescence intensity of NAC-AuNPs was quenched dramatically by adding hydrogen peroxide. Therefore, it could be used to detect hydrogen peroxide based on the fluorescence quenching intensity was linear with the concentration of hydrogen peroxide. Under the optimal experimental conditions, the linear range and detection limit were 1.0×10-6 –3.0×10-2 mol/L and 1.0×10-7 mol/L, respectively. The possible quenching mechanism was investigated by time-resolved fluorescence spectroscopy. The proposed method was simple, sensitive and showed good repeatability and stability.
Micromanipulation Method using Backflow Effect of Liquid Crystals

We developed a micromanipulation method using backflow effect of liquid crystals. By adjusting the polarity and the frequency of an applied voltage, the net movement of the microparticles dipped into liquid crystals is caused. The micromanipulation methods using the backflow effect are suitable for the micro and precise manipulation of microobjects that are difficult to handle, for instance microlens or micromirrors
MATHEMATICAL ENGINEERING TECHNICAL REPORTS Hierarchical Subspace Models for Contingency Tables

For statistical analysis of multiway contingency tables we propose modeling interaction terms in each maximal compact component of a hierarchical model. By this approach we can search for parsimonious models with smaller degrees of freedom than the usual hierarchical model, while preserving conditional independence structures in the hierarchical model. We discuss estimation and exacts tests of the proposed model and illustrate the advantage of the proposed modeling with some data sets.
Knowledge Sharing in a Community of Practice : a Text-Based Approach in Emergent Domains

The shared use of specialist terminology amongst the members of a community of practice is explored as evidence for the existence of the concept of communal lexicon. A computer-based method of investigating the extent of terminology is described – this method uses both univariate analysis, specifically frequency distribution of single and compound words, and multivariate statistical analysis, particularly factor analysis. The results show that terminology sharing may act as a metric for knowledge sharing and knowledge diffusion among different (sub-) communities. The case study chosen to demonstrate the efficacy of the terminology-sharing method is drawn from cancer care – especially breast cancer care, where texts produced for and by the three main components of the community are examined – namely the experts, the professionals and the patients.
Harmonic mitigation technique for multilevel inverters in power systems

A new procedure to mitigate some harmonics is presented for a 5-level cascaded inverter, varying the modulation index. The two switching angles α1 and α2 are computed by using a procedure based on graphycal analysis by using Chebyshev polynomials and the Waring's formulae. The proposed mitigation technique is applied to reduce a pair of harmonics among third, fifth and seventh in inverter output voltage according to standard code requirements. Experimental results are also extracted by the prototype built at the laboratory. The measured results confirm the quality of the presented procedure.
Intrinsically motivated neuroevolution for vision-based reinforcement learning

Neuroevolution, the artificial evolution of neural networks, has shown great promise on continuous reinforcement learning tasks that require memory. However, it is not yet directly applicable to realistic embedded agents using high-dimensional (e.g. raw video images) inputs, requiring very large networks. In this paper, neuroevolution is combined with an unsupervised sensory pre-processor or compressor that is trained on images generated from the environment by the population of evolving recurrent neural network controllers. The compressor not only reduces the input cardinality of the controllers, but also biases the search toward novel controllers by rewarding those controllers that discover images that it reconstructs poorly. The method is successfully demonstrated on a vision-based version of the well-known mountain car benchmark, where controllers receive only single high-dimensional visual images of the environment, from a third-person perspective, instead of the standard two-dimensional state vector which includes information about velocity.
Characterization of an Extended Multimedia Benchmark on a General Purpose Microprocessor Architecture

Increasing demand for multimedia applications (MMAs) by general-purpose processor (GPP) users leads architects to merge multimedia processing capability into GPPs. To develop a GPP providing high quality multimedia services as well as high performance general computing, thorough understanding of the characteristics of both types of applications is fundamental. This paper presents an comprehensive multimedia benchmark suite with variable input data files, and quantifies the characteristics of the presented benchmark in comparison to SPEC integer and floating-point benchmarks. Various aspects of program behavior are measured using a run-time tracer. We identify several distinctive characteristics of MMAs compiled for a GPP and discuss the corresponding architectural impacts on GPPs.
Improvement of the flame retardancy of plasticized poly(lactic acid) by means of phosphorus‐based flame retardant fillers

The aim of this study is to improve the flame resistance and toughness of poly(lactic acid) (PLA) with the addition of low amount of flame retardant fillers and plasticizer simultaneously. Poly(ethylene glycol) (PEG) was used as plasticizer for PLA. Ammonium polyphosphate, boron phosphate, and tri‐phenyl phosphate (TPP) were used as flame retardant additives. Among these flame retardant additives, boron phosphate was synthesized from its raw materials by using microwave heating technique. Characterization of PLA/PEG‐based flame retardant composites was performed by conducting tensile, impact, differential scanning calorimeter, thermal gravimetric analysis, scanning electron microscope, limiting oxygen index, and UL‐94 vertical burning tests. Mechanical tests showed that the highest tensile strength, impact strength, and elongation at break values were obtained with the addition of ammonium polyphosphate and TPP into PLA/PEG matrix, respectively. Scanning electron microscopy analysis of the composites exhibited that the more homogeneous filler distribution in the matrix was observed for TPP containing composite. The best flame retardancy performance was also provided by TPP when compared with the other flame retardant additives in the plasticized PLA‐based composites.
ON THE BILINEAR COMPLEXITY OF THE MULTIPLICATION IN FINITE FIELDS

The aim of this paper is to introduce the bilinear complexity of the mul- tiplication in finite fields and to give a brief exposition of the recent results obtained in this part of algebraic complexity theory. In particular we present the new results obtained using the Chudnovsky-Chudnovsky algorithm and its generalizations. Resume (Sur la complexite bilineaire de la multiplication dans les corps finis)
Privacy-Preserving Multi-Keyword Ranked Search over Encrypted Cloud Data

With the advent of cloud computing, data owners are motivated to outsource their complex data management systems from local sites to the commercial public cloud for great flexibility and economic savings. But for protecting data privacy, sensitive data have to be encrypted before outsourcing, which obsoletes traditional data utilization based on plaintext keyword search. Thus, enabling an encrypted cloud data search service is of paramount importance. Considering the large number of data users and documents in the cloud, it is necessary to allow multiple keywords in the search request and return documents in the order of their relevance to these keywords. Related works on searchable encryption focus on single keyword search or Boolean keyword search, and rarely sort the search results. In this paper, for the first time, we define and solve the challenging problem of privacy-preserving multi-keyword ranked search over encrypted data in cloud computing (MRSE). We establish a set of strict privacy requirements for such a secure cloud data utilization system. Among various multi-keyword semantics, we choose the efficient similarity measure of "coordinate matching," i.e., as many matches as possible, to capture the relevance of data documents to the search query. We further use "inner product similarity" to quantitatively evaluate such similarity measure. We first propose a basic idea for the MRSE based on secure inner product computation, and then give two significantly improved MRSE schemes to achieve various stringent privacy requirements in two different threat models. To improve search experience of the data search service, we further extend these two schemes to support more search semantics. Thorough analysis investigating privacy and efficiency guarantees of proposed schemes is given. Experiments on the real-world data set further show proposed schemes indeed introduce low overhead on computation and communication.