Miracle-dz/UniFAR-FTUs huggingface dataset:
Sentence Compression for Automated Subtitling: A Hybrid Approach

In this paper a sentence compression tool is described. We describe how an input sentence gets analysed by using a.o. a tagger, a shallow parser and a subordinate clause detector, and how, based on this analysis, several compressed versions of this sentence are generated, each with an associated estimated probability. These probabilities were estimated from a parallel transcript/subtitle corpus. To avoid ungrammatical sentences, the tool also makes use of a number of rules. The evaluation was done on three different pronunciation speeds, averaging sentence reduction rates of 40% to 17%. The number of reasonable reductions ranges between 32.9% and 51%, depending on the average estimated pro-nunciation speed.
A swarm intelligence technique to enhance network lifetime in WSN

A Wireless Sensor Network (WSN) is a field of interest for researchers due to its monitoring capability and giving the information which helps in predicting the future scenarios like in health care system, monitoring or tracking etc. Sensor nodes are very small and powerful devices which are continuously sense the data and send it to the base station (Sink) which generates the results based on the details received from sensor nodes. Sensor nodes are battery constrained, they use a lot of energy for transmitting the data and die very quickly. To save the energy of sensor node and make WSN more reliable here authors proposed a clustering mechanism. In clustering mechanism large network divided into small clusters. Each cluster has its own cluster head, cluster members communicate with cluster head and cluster head collects all the data from cluster members and send it to the base station. For cluster formation a noble concept is given called adaptive swarm optimization, here authors worked on best previous position and best global position of nodes. Nodes can changes their position as per their best global position from the previous position and based on this lifetime of overall network can be increased. Nodes death rate is decreased as compared with the existing method.
Abiotic Controls on Macroscale Variations of Humid Tropical Forest Height

Spatial variation of tropical forest tree height is a key indicator of ecological processes associated with forest growth and carbon dynamics. Here we examine the macroscale variations of tree height of humid tropical forests across three continents and quantify the climate and edaphic controls on these variations. Forest tree heights are systematically sampled across global humid tropical forests with more than 2.5 million measurements from Geoscience Laser Altimeter System (GLAS) satellite observations (2004–2008). We used top canopy height (TCH) of GLAS footprints to grid the statistical mean and variance and the 90 percentile height of samples at 0.5 degrees to capture the regional variability of average and large trees globally. We used the spatial regression method (spatial eigenvector mapping-SEVM) to evaluate the contributions of climate, soil and topography in explaining and predicting the regional variations of forest height. Statistical models suggest that climate, soil, topography, and spatial contextual information together can explain more than 60% of the observed forest height variation, while climate and soil jointly explain 30% of the height variations. Soil basics, including physical compositions such as clay and sand contents, chemical properties such as PH values and cation-exchange capacity, as well as biological variables such as the depth of organic matter, all present independent but statistically significant relationships to forest height across three continents. We found significant relations between the precipitation and tree height with shorter trees on the average in areas of higher annual water stress, and large trees occurring in areas with low stress and higher annual precipitation but with significant differences across the continents. Our results confirm other landscape and regional studies by showing that soil fertility, topography and climate may jointly control a significant variation of forest height and influencing patterns of aboveground biomass stocks and dynamics. Other factors such as biotic and disturbance regimes, not included in this study, may have less influence on regional variations but strongly mediate landscape and small-scale forest structure and dynamics.
Shallow NLP techniques for noun phrase extraction

The field of Information Retrieval plays an important role in searching on the Internet. Most of the information retrieval systems are limited to the query processing based on keywords. In information retrieval system the matching of the query against a set of text record is the core of the system. Retrieval of the relevant natural language text document is of more challenge. Today's most search engines are based on keyword based (bag of words) techniques, which results in some disadvantages. For text retrieval key phrases can help to narrow the search results or rank retrieved documents. We exploit shallow NLP techniques to support a range of NL queries and snippets over an existing keyword-based search. This paper describes a simple system for choosing noun phrases from a document as key phrases. The noun phrase extractor is made up of three modules: tokenization; part-of-speech tagging; noun phrase identification using Chunking. A preliminary evaluation was conducted to test this technique with the standard IR benchmark collections such as classic test collections and then with the web snippets collection from the search engines results. The experimental results have been encouraging.
COCOLOG: a conditional observer and controller logic for finite machines

The acronym COCOLOG is used to denote the family of first order conditional observer and controller logics for any given input-state-output system. A semantics is supplied for each COCOLOG in terms of interpretation of controlled transitions on a tree of state estimate sets indexed by observation o(k). Extra-logical rules relating members of family logics of a COCOLOG are then presented in the form of meta-level axioms and inference rules. Consistency and completeness of the first order theories in a COCOLOG family are established, and examples of the operation of a COCOLOG logic control system are given. Finally, comparisons of the features of flexibility and complexity issues of logic-based and classical control systems are addressed, and mention is made of mechanical theorem proving in COCOLOG. <<ETX>>
Signalling Elaboration: Combining Gerund Clauses with Lexical Cues

In this paper, we aim at automatically identifying Elaboration. This relation is particularly difﬁcult to spot since it does not have prototypical markers. Our approach focuses on an ambiguous syntactic pattern, the gerund clause, combined with lexical cues. This approach allows us to detect few but accurate cases of inner sentence Elaborations in our corpus, validating the fact that lexical cues are relevant for this task.
Solving Maximum Cut Problem with an Incremental Genetic Algorithm

In this paper, we propose an incremental genetic algorithm applied to solve the maximum cut problem. We test the implementation of the algorithm on benchmark graph instances. We propose several methods to build up the sequence of subproblems, and they are tested through experiments. The performance of a genetic algorithm makes an improvement when the incremental approach is applied with respect to an appropriate sequence of subproblems.
Evaluation of Ventilators for Mouthpiece Ventilation in Neuromuscular Disease

BACKGROUND: Daytime mouthpiece ventilation is a useful adjunct to nocturnal noninvasive ventilation (NIV) in patients with neuromuscular disease. The aims of the study were to analyze the practice of mouthpiece ventilation and to evaluate the performance of ventilators for mouthpiece ventilation. METHODS: Practice of mouthpiece ventilation was assessed by a questionnaire, and the performance of 6 home ventilators with mouthpiece ventilation was assessed in a bench test using 24 different conditions per ventilator: 3 mouthpieces, a child and an adult patient profile, and 4 ventilatory modes. RESULTS: Questionnaires were obtained from 30 subjects (mean age 33 ± 11 y) using NIV for 12 ± 7 y. Fifteen subjects used NIV for > 20 h/day, and 11 were totally ventilator-dependent. The subject-reported benefits of mouthpiece ventilation were a reduction in dyspnea (73%) and fatigue (93%) and an improvement in speech (43%) and eating (27%). The bench study showed that none of the ventilators, even those with mouthpiece ventilation software, were able to deliver mouthpiece ventilation without alarms and/or autotriggering in each condition. Alarms and/or ineffective triggering or autotriggering were observed in 135 of the 198 conditions. The occurrence of alarms was more common with a large mouthpiece without a filter compared to a small mouthpiece with a filter (P < .001), but it was not related to the patient profile, the ventilatory mode, or the type of ventilator. CONCLUSIONS: Subjects are satisfied with mouthpiece ventilation. Alarms are common with home ventilators, although less common in those with mouthpiece ventilation software. Improvements in home ventilators are needed to facilitate the expansion of mouthpiece ventilation.
Risk, Insurance and Wages in General Equilibrium

We estimate the general-equilibrium labor market effects of a large-scale randomized intervention in which we designed and marketed a rainfall index insurance product across three states in India. Marketing agricultural insurance to both cultivators and to agricultural wage laborers allows us to test a general-equilibrium model of wage determination in settings where households supplying labor and households hiring labor face weather risk. Consistent with theoretical predictions, we find that both labor demand and equilibrium wages become more rainfall sensitive when cultivators are offered rainfall insurance, because insurance induces cultivators to switch to riskier, higher-yield production methods. The same insurance contract offered to agricultural laborers smoothes wages across rainfall states by inducing changes in labor supply. Policy simulations based on our estimates suggest that selling insurance only to land-owning cultivators and precluding the landless from the insurance market (which is the current regulatory practice in India and other developing countries), makes wage laborers worse off relative to a situation where insurance does not exist at all. The general-equilibrium analysis reveals that the welfare costs of current regulation are borne by landless laborers, who represent the poorest segment of society and whose risk management options are the most limited.
A Simplified Soft-Output QRD-M MIMO Detector

In this paper, a low-complexity soft-output QRD-M detection algorithm is proposed for high-throughput Multiple-input multiple-output (MIMO) systems. By employing novel expansion on demand and distributed sorting scheme, the proposed algorithm can reduce 70% and 85% foundational operations for 16-QAM and 64-QAM respectively compared to the conventional QRD-M algorithm. Furthermore, the proposed algorithm can yield soft information to improve the bit error rate (BER) performance. Simulation results show that the proposed algorithm can achieve a near-ML detection performance with less foundational operations.
Computer rendering of stochastic models

A recurrent problem in generating realistic pictures by computers is to represent natural irregular objects and phenomena without undue time or space overhead. We develop a new and powerful solution to this computer graphics problem by modeling objects as sample paths of stochastic processes. Of particular interest are those stochastic processes which previously have been found to be useful models of the natural phenomena to be represented. One such model applicable to the representation of terrains, known as “fractional Brownian motion,” has been developed by Mandelbrot. The value of a new approach to object modeling in computer graphics depends largely on the efficiency of the techniques used to implement the model. We introduce a new algorithm that computes a realistic, visually satisfactory approximation to fractional Brownian motion in faster time than with exact calculations. A major advantage of this technique is that it allows us to compute the surface to arbitrary levels of details without increasing the database. Thus objects with complex appearances can be displayed from a very small database. The character of the surface can be controlled by merely modifying a few parameters. A similar change allows complex motion to be created inexpensively.
Ensemble learning for Intrusion Detection in Computer Networks

The security of computer networks plays a strategic role in modern computer systems. In order to enforce high protection levels against threats, a number of software tools are currently developed. Intrusion Detection Systems aim at detecting intruder who eluded the "first line" protection. In this paper, a pattern recognition approach to network intrusion detection based on ensemble learning paradigms is proposed. The potentialities of such an approach for data fusion and some open issues are outlined.
Games networks play a game theoretic approach to networks

Traditional network protocols such as TCP/IP require cooperation between traffic sources to achieve optimal network performance. This approach does not always work, as evident by frequent congestion problems in the Internet. Recent research in protocol design using game theory removes this limitation by modeling traffic sources as competing players and results in efficient and fair distribution of resources. This paper provides theoretical background of the game theoretic approach as applied to networks, describes some previously proposed schemes for minimizing network congestion, elaborates on pricing mechanisms and discusses game-theoretic routing solutions. Pricing provides a feasible solution for congestion control but application of distributed algorithmic mechanism design (DAMD) can be adapted for congestion control.
Entity Linking: Detecting Entities within Text

With unstructured text on the web and social media increasing at a furious pace, it is all the more important to develop techniques that can ease semantic understanding of text data for humans. One of the key tasks in this process is that of entity linking; identifying mentions of entities in text. Consider the line that reads "The Prime Minister came under harsh criticism over the Immigration Act 2014" Without any additional context, it is not obvious to humans as to who is being talked about. An entity linking technique that has the entity database at its disposal, however, can easily figure out that the mention Prime Minister refers to the Prime Minister of UK since the mention of Immigration Act 2014 in the same sentence narrows down the search space from the set of all countries that have Prime Ministers to just UK. Such linking of text documents to entities enables easier understanding for the reader, as well as improved accuracy in automated tasks such as text document clustering, classification and information retrieval.
Single image defogging

Bad weather, such as fog and haze can significantly degrade the visibility of a scene. In order to overcome it, some approaches have been proposed. In this paper, we proposed a novel defogging algorithm just based on a single image. Firstly, we employ the method of dark channel prior as a foundation of our algorithm. After experimental analysis about the dark channel prior haze removal, we find that although dark channel prior behaves well in most situations, it also results in larger saturation values in some specific situations. Then, focusing on these situations, we propose an iterative algorithm to adjust the color distortion effected by higher saturation. Actually, this kind of global or local rectification can achieve a relatively ideal compromise between natural color and image definition. Experiments show that the algorithm proposed in this paper is good at dealing with the similarity-to-atmospheric-light objects defogging problem.
Spectral Intersections for Non-Stationary Signal Separation

We describe a new method for non-stationary noise suppression that is simple to implement yet has performance that rivals far more complex algorithms. Spectral Intersections is a model based MMSE signal separation method that uses a new approximation to the observation likelihood. Furthermore, Spectral Intersections uses an efficient approximation to the expectation integral of the MMSE estimate that could be described as unscented importance sampling. We apply the new method to the task of separating speech mixed with music. We report results on the Google Voice Search task where the new method provides a 7% relative reduction in WER at 10 dB SNR. Interestingly, the new method provides considerably greater reduction in average WER than the Max method and approaches the performance of the more complex Algonquin algorithm.
A Bio-PEPA Model of Endosomal Trafficking of Src Tyrosine Kinase

Src is a protein which has strong links to various cancers, particularly breast cancer. The Src activation process is through an ‘amplification loop’ where Src itself regulates its own activation. Active Src plays a key role in the regulation of FGF signalling pathway which is closely related to cell growth, differentiation and wound repair. The object of this project was to investigate the sufficiency of Bio-PEPA for constructing a model of the spatial nature of the Src pathway, and assess the ways in which pathway models can be combined to study the interaction between biological pathways. The outcome of the project are a Src model, a FGF model and a full model which shows the interaction between them. A series of ‘in silico’ experiments were carried out to examine certain properties of the models. This dissertation describes the work undertaken and the results.
Designing and Implementing the Chuck Programming Language

ChucK re-factors the idea of a computer music language into three orthogonal basis components: unit generator connections that are data-flow only, globally consistent ”first-class” time control, and sample-synchronous concurrency. The syntax, semantic, and usage have been discussed in previous works. The focus and contributions of this paper are (1) to examine the philosophies and decisions in the language design (2) to describe ChucK’s implementation and runtime model, and (3) to outline potential applications enabled by this framework. We present an experiment in designing a computer music language ”from scratch” and show how things work. We hope these ideas may provides an interesting reference for future computer music systems.
An institutional perspective on the employment position of temporary workers in the Netherlands

This article analyzes the complex employment position of temporary workers within organizations and on the labour market. Temporary employment is usually considered secondary to permanent employment. In recent years, the European Union and the Dutch government have attempted to change this situation by formulating several directives and labour laws. In this paper, we use institutional theory to discuss the institutional foundations and influences that shape the employment and labour-market conditions of temporary workers. The analysis shows that the core issues regarding temporary employment conditions include conflicting (legitimate) interests, socially constructed norms that favour permanent workers, and an uneven distribution of power. Our analysis further shows that institutional forces generate a structural justification for the disadvantaged position of temporary workers.
Cyclic Peptide Inhibitors of HIV-1 Capsid-Human Lysyl-tRNA Synthetase Interaction

The human immunodeficiency virus type 1 (HIV-1) capsid protein (CA) plays a critical role in the viral life cycle. The C-terminal domain (CTD) of CA binds to human lysyl-tRNA synthetase (hLysRS), and this interaction facilitates packaging of host cell tRNALys,3, which serves as the primer for reverse transcription. Here, we report the library synthesis, high-throughput screening, and identification of cyclic peptides (CPs) that bind HIV-1 CA. Scrambling or single-residue changes of the selected peptide sequences eliminated binding, suggesting a sequence-specific mode of interaction. Two peptides (CP2 and CP4) subjected to detailed analysis also inhibited hLysRS/CA interaction in vitro. Nuclear magnetic resonance spectroscopy and mutagenesis studies revealed that both CPs bind to a site proximal to helix 4 of the CA-CTD, which is the known site of hLysRS interaction. These results extend the current repertoire of CA-binding molecules to a new class of peptides targeting a novel site with potential for development into novel antiviral agents.
Analysis and modeling of dual-band GSM networks

This paper studies interconnection of DCS1800 and GSM900 dual-band networks. Two types of interconnection configurations for GSM services, non-overlap and overlap, are described. We propose analytic and simulation models to investigate the benefit of the overlap configuration. Our results explain how the radio channel capacities, the inter-system handoff failure rate, the originating call traffic ratio and the offered loads affect the system performance. This study indicates that with appropriate overlap configuration, the GSM dual-band network can significantly improve the quality of cellular service.
Mitochondrial dysfunction and oxidative stress in patients with chronic kidney disease

Mitochondria abnormalities in skeletal muscle may contribute to frailty and sarcopenia, commonly present in patients with chronic kidney disease (CKD). Dysfunctional mitochondria are also a major source of oxidative stress and may contribute to cardiovascular disease in CKD. We tested the hypothesis that mitochondrial structure and function worsens with the severity of CKD. Mitochondrial volume density, mitochondrial DNA (mtDNA) copy number, BNIP3, and PGC1α protein expression were evaluated in skeletal muscle biopsies obtained from 27 subjects (17 controls and 10 with CKD stage 5 on hemodialysis). We also measured mtDNA copy number in peripheral blood mononuclear cells (PBMCs), plasma isofurans, and plasma F2‐isoprostanes in 208 subjects divided into three groups: non‐CKD (eGFR>60 mL/min), CKD stage 3–4 (eGFR 60–15 mL/min), and CKD stage 5 (on hemodialysis). Muscle biopsies from patients with CKD stage 5 revealed lower mitochondrial volume density, lower mtDNA copy number, and higher BNIP3 content than controls. mtDNA copy number in PBMCs was decreased with increasing severity of CKD: non‐CKD (6.48, 95% CI 4.49–8.46), CKD stage 3–4 (3.30, 95% CI 0.85–5.75, P = 0.048 vs. non‐CKD), and CKD stage 5 (1.93, 95% CI 0.27–3.59, P = 0.001 vs. non‐CKD). Isofurans were higher in patients with CKD stage 5 (median 59.21 pg/mL, IQR 41.76–95.36) compared to patients with non‐CKD (median 49.95 pg/mL, IQR 27.88–83.46, P = 0.001), whereas F2‐isoprostanes did not differ among groups. Severity of CKD is associated with mitochondrial dysfunction and markers of oxidative stress. Mitochondrial abnormalities, which are common in skeletal muscle from patients with CKD stage 5, may explain the muscle dysfunction associated with frailty and sarcopenia in CKD. Further studies are required to evaluate mitochondrial function in vivo in patients with different CKD stages.