Miracle-dz/UniFAR-FTUs huggingface dataset:
Targeting and Proportionality during the NATO Bombing Campaign against Yugoslavia

The 1999 NATO bombing campaign against the Federal Republic of Yugoslavia relied upon modern precision weaponry and purported to pay due regard to contemporary legal standards, in particular to the requirement to limit incidental civilian casualties. There are no such things as error-free wars or casualty-free wars. It appears, however, that NATO classified a wider range of objects as military objectives than has traditionally been the case, in particular the RTS broadcasting station headquarters in Belgrade. It also appears that some earlier bombing campaigns (the 1972 'Linebacker 2' campaign against North Vietnam which was conducted at the dawn of the era of precision weapons is an example) were conducted paying equal regard to the requirement to limit incidental civilian casualties.
Research on 2nd harmonic impedance measurement based active islanding detection method

A new active islanding detection method based on 2nd harmonic impedance measurement is studied. With this method, the inverter current reference is slightly modified by an injected signal which affecting the in-grid current in a negligible way. When the grid becomes unavailable, the value of grid impedance moves outside of a preset threshold value, and the 2nd harmonic voltage of the inverter becomes bigger enough to identify the islanding. Influence on the in-grid current and Non-Detection-Zones (NDZ) by the islanding detection method is analyzed in detail. This method is promised smaller disturbance to the grid and almost no NDZ. In addition, the method is highly robust to different grid disturbances and stiffness, and effective for multiple inverters running in parallel. A NDZ map which illustrates the NDZ by quality factor of the loads and 2nd harmonic component of the grid voltage is proposed. The new islanding detection method has been tested on a prototype inverter successfully, and it is verified that the new method meets the standard requirements IEEE 929-2000 well.
Optimal Schwarz Waveform Relaxation for the One Dimensional Wave Equation

We introduce a nonoverlapping variant of the Schwarz waveform relaxation algorithm for wave propagation problems with variable coefficients in one spatial dimension. We derive transmission conditions which lead to convergence of the algorithm in a number of iterations equal to the number of subdomains, independently of the length of the time interval. These optimal transmission conditions are in general nonlocal, but we show that the nonlocality depends on the time interval under consideration, and we introduce time windows to obtain optimal performance of the algorithm with local transmission conditions in the case of piecewise constant wave speed. We show that convergence in two iterations can be achieved independently of the number of subdomains in that case. The algorithm thus scales optimally with the number of subdomains, provided the time windows are chosen appropriately. For continuously varying coefficients we prove convergence of the algorithm with local transmission conditions using energy estimates. We then introduce a finite volume discretization which permits computations on nonmatching grids, and we prove convergence of the fully discrete Schwarz waveform relaxation algorithm. We finally illustrate our analysis with numerical experiments.
Physmism: Re-Introducing Physical Modelling for Electronic Musical Exploration

In this paper we describe the design and implementation of the PHYSMISM: an interface for exploring the possibilities for improving the creative use of physical modelling sound synthesis. Four different physical modelling techniques are implemented, to explore the implications of using and combining different techniques. In order to evaluate the creative use of physical models, a test was performed using 11 experienced musicians as test subjects. Results show that the capability of combining the physical models and the use of a physical interface engaged the musicians in creative exploration of physical models.
Effect of head of the line blocking on session initiation protocol session establishment delays

We have studied the effect of head of the line blocking (HOLB) on session initiation protocol (SIP) session establishment delays. Our results are based on experiments performed in a test bed and on the public Internet. We used the stream control transmission protocol (SCTP) as a transport for SIP because SCTP can be configured to suffer or to avoid HOLB. Our experiments show that the effect of HOLB on session establishment delays generally starts to be significant starting at fairly low packet loss rates. However, there are scenarios where network conditions are good enough to make the effect of HOLB insignificant.
Trends in educational disadvantage in Dutch primary school

The central question in this study is whether the language and math delays of the different socio-economic and ethnic minority groups targeted by Dutch educational disadvantage policy have diminished or not. Data are from the years 1995, 1999, 2003 and 2008. Information from a total of 90,000 pupils in Grades 2 and 8 was selected to represent the start and end points of primary education. The conclusion is that large differences exist between disadvantaged and non-disadvantaged pupils at the start of primary school. Minority target group pupils have a substantial language delay. In the last year of primary school, this delay has diminished somewhat but it is still substantial. In the period 1995–2008 the delays of the minority target group pupils have declined by more than 40%. Part of the non-minority target group pupils also made gains, but these are less than those observed for the minority target group pupils. Moreover, for the period 2003–2008, the relative position of the non-minority target group pupils with regard to their language skills can be seen to deteriorate.
Concurrent phase classification for accelerating MPSoC simulation

To rapidly evaluate performances and power consumption in design space exploration of modern highly complex embedded systems, new simulation tools are needed. The checkpointing technique, which consists in saving system states in order to simulate in detail only a small part of the application, is among the most viable simulation approaches. In this paper, a new method for generating and storing checkpoints for accelerating MPSoC simulation is presented. Experimental results demonstrate that our technic can reduce simulation time and the memory size required to store these checkpoints on a secondary memory. In addition, the necessary time to load checkpoints on the host processor at runtime is optimized. These advantages speedup simulations and allow exploration of a large space of alternative designs in the DSE.
The use of pooled viral load testing to identify antiretroviral treatment failure

Background:To develop less costly methods to virologically monitor patients receiving antiretroviral therapy, we evaluated methods that use pooled blood samples and quantitative information available from viral load assays to monitor a cohort of patients on first-line antiretroviral therapy for virologic failure. Methods:We evaluated 150 blood samples collected after 6 months of therapy from participants enrolled in a San Diego primary infection program between January 1998 and January 2007. Samples were screened for virologic failure with individual viral load testing, 10 × 10 matrix pools and minipools of five samples. For the pooled platforms (matrix and minipools), we used a search and retest algorithm based on the quantitative viral load data to resolve samples that remained ambiguous for virologic failure. Viral load thresholds were more than 500 and more than 1500 copies/ml for the matrix and more than 250 and more than 500 copies/ml for the minipool. Efficiency, accuracy and result turnaround times were evaluated. Results:Twenty-three percent of cohort samples were detectable at more than 50 HIV RNA copies/ml. At an algorithm threshold of more than 500 HIV RNA copies/ml, both minipool and matrix methods used less than half the number of viral load assays to screen the cohort, compared with testing samples individually. Both pooling platforms had negative predictive values of 100% for viral loads of more than 500 HIV RNA copies/ml and at least 94% for viral loads of more than 250 HIV RNA copies/ml. Conclusion:In this cohort, both pooling methods improved the efficiency of virologic monitoring over individual testing with a minimal decrease in accuracy. These methods may allow for the induction and sustainability of the virologic monitoring of patients receiving antiretroviral therapy in resource-limited settings.
Random projections: A remedy for overfitting issues in time series prediction with echo state networks

Modelling time series is quite a difficult task. The last recent years, reservoir computing approaches have been proven very efficient for such problems. Indeed, thanks to recurrence in the connections between neurons, this approach is a powerful tool to catch and model time dependencies between samples. Yet, the prediction quality often depends on the trade-off between the number of neurons in the reservoir and the amount of training data. Supposedly, the larger the number of neurons, the richer the reservoir of dynamics. However, the risk of overfitting problem appears. Conversely, the lower the number of neurons is, the lower the risk of overfitting problem is but also the poorer the reservoir of dynamics is. We consider here the combination of an echo state network with a projection method to benefit from the advantages of the reservoir computing approach without needing to pay attention to overfitting problems due to a lack of training data.
Correlates of Alcohol and Marijuana Use among Junior High School Students

This study analyzes survey data collected from over 400 junior high school students in Grades 7 and 8 in an attempt to determine the relationships between family drug use factors; peer drug use factors; school problems; psychosocial concerns; alcohol, marijuana, and other drug use; and abstinence. Socialization theory is used as the theoretical framework, factor analysis is used to create indexes, and analysis of variance and regression procedures are used for analysis. Based on the findings, implications for policy, prevention, and treatment programs are discussed.
Cross-Lingual Transfer Learning for POS Tagging without Cross-Lingual Resources

Training a POS tagging model with crosslingual transfer learning usually requires linguistic knowledge and resources about the relation between the source language and the target language. In this paper, we introduce a cross-lingual transfer learning model for POS tagging without ancillary resources such as parallel corpora. The proposed cross-lingual model utilizes a common BLSTM that enables knowledge transfer from other languages, and private BLSTMs for language-specific representations. The cross-lingual model is trained with language-adversarial training and bidirectional language modeling as auxiliary objectives to better represent language-general information while not losing the information about a specific target language. Evaluating on POS datasets from 14 languages in the Universal Dependencies corpus, we show that the proposed transfer learning model improves the POS tagging performance of the target languages without exploiting any linguistic knowledge between the source language and the target language.
Cultural differences in the motivation of Generation Y knowledge workers

This article presents our research into cultural differences in the motivation of Generation Y knowledge workers. The goal of our research was to verify whether the motivation of young knowledge workers (members of Generation Y) could be assessed only in relation to the specifics of their generation, or whether it is necessary to take their national cultural background into account as well. The research carried out among two hundred respondents in four countries has confirmed that it is essential to take into account both generation differences and cultural differences.
Perceptual Spatial Audio Recording, Simulation, and Rendering

Developments in immersive audio technologies have been evolving in two directions: physicallymotivated and perceptually-motivated systems. Physically motivated techniques aim to reproduce a physically accurate approximation of desired sound fields by employing a very high equipment load and sophisticated computationally intensive algorithms. Perceptually-motivated techniques, on the other hand, aim to render only the perceptually relevant aspects of the sound scene by means of modest computational and equipment load. This article presents an overview of perceptually motivated techniques, with a focus on multichannel audio recording and reproduction, audio source and reflection culling, and artificial reverberators.
Identity Status and Locus of Control: A Meta-Analysis

This investigation examined the relationship between identity status and locus of control through techniques of meta-analysis. Early research has found an association between identity achievement and an internal locus of control and between identity diffusion and an external locus of control. Findings for the relationship between locus of control and the moratorium and foreclosure statuses, however, have been inconsistent. A total of 565 empirical studies of identity status that were conducted between 1966 and 2005 were identified from PsychINFO, ERIC, Sociological Abstracts, and Dissertation Abstracts International using these search terms: “identity status,” “identity and Marcia,” “identity and Marcia's,” and “ego identity. ” Nineteen of these studies addressed the relationship between locus of control and identity status; only five of the studies (N = 711 participants) provided data with satisfactory information to be included in the meta-analysis. Internal and external locus of control scales were correlated with each identity status, and effect sizes were primarily in predicted directions.
A transgenic mouse line for collecting ribosome-bound mRNA using the tetracycline transactivator system

Acquiring the gene expression profiles of specific neuronal cell-types is important for understanding their molecular identities. Genome-wide gene expression profiles of genetically defined cell-types can be acquired by collecting and sequencing mRNA that is bound to epitope-tagged ribosomes (TRAP; translating ribosome affinity purification). Here, we introduce a transgenic mouse model that combines the TRAP technique with the tetracycline transactivator (tTA) system by expressing EGFP-tagged ribosomal protein L10a (EGFP-L10a) under control of the tetracycline response element (tetO-TRAP). This allows both spatial control of EGFP-L10a expression through cell-type specific tTA expression, as well as temporal regulation by inhibiting transgene expression through the administration of doxycycline. We show that crossing tetO-TRAP mice with transgenic mice expressing tTA under the Camk2a promoter (Camk2a-tTA) results in offspring with cell-type specific expression of EGFP-L10a in CA1 pyramidal neurons and medium spiny neurons in the striatum. Co-immunoprecipitation confirmed that EGFP-L10a integrates into a functional ribosomal complex. In addition, collection of ribosome-bound mRNA from the hippocampus yielded the expected enrichment of genes expressed in CA1 pyramidal neurons, as well as a depletion of genes expressed in other hippocampal cell-types. Finally, we show that crossing tetO-TRAP mice with transgenic Fos-tTA mice enables the expression of EGFP-L10a in CA1 pyramidal neurons that are activated during a fear conditioning trial. The tetO-TRAP mouse can be combined with other tTA mouse lines to enable gene expression profiling of a variety of different cell-types.
Weighted maximum likelihood loss as a convenient shortcut to optimizing the F-measure of maximum entropy classifiers

We link the weighted maximum entropy and the optimization of the expected F measure, by viewing them in the framework of a general common multi-criteria optimization problem. As a result, each solution of the expectedF -measure maximization can be realized as a weighted maximum likelihood solution - a well understood and behaved problem. The specific structure of maximum entropy models allows us to approximate this characterization via the much simpler class-wise weighted maximum likelihood. Our approach reveals any probabilistic learning scheme as a specific trade-off between different objectives and provides the framework to link it to the expectedF -measure.
Semi‐automatic Vortex Flow Classification in 4D PC‐MRI Data of the Aorta

We present an Aortic Vortex Classification (AVOCLA) that allows to classify vortices in the human aorta semi‐automatically. Current medical studies assume a strong relation between cardiovascular diseases and blood flow patterns such as vortices. Such vortices are extracted and manually classified according to specific, unstandardized properties. We employ an agglomerative hierarchical clustering to group vortex‐representing path lines as basis for the subsequent classification. Classes are based on the vortex' size, orientation and shape, its temporal occurrence relative to the cardiac cycle as well as its spatial position relative to the vessel course. The classification results are presented by a 2D and 3D visualization technique. To confirm the usefulness of both approaches, we report on the results of a user study. Moreover, AVOCLA was applied to 15 datasets of healthy volunteers and patients with different cardiovascular diseases. The results of the semi‐automatic classification were qualitatively compared to a manually generated ground truth of two domain experts considering the vortex number and five specific properties.
Variations in Neural Network Topology and OutputAveraging on the Discrimination of Mental Tasks fromSpontaneous

Electroencephalogram, or EEG, signals are an important source of information for the study of underlying brain processes. Such studies now provide a framework for the development of a new modality of human-computer interaction based on EEG. Current research in this area only detects a small number of mental states. In this article, EEG from one subject who performed three mental tasks are classiied by neural networks. Using a sixth-order autoregressive (AR) model of half-second windows of six-channel EEG, a classiication accuracy of 89% on test data is achieved. A cross-validation study of a variety of neural network topologies showed that a network with one hidden layer of 20 units produced the best performance. It was also found that averaging the output of the network over consecutive inputs improved performance. K-means clustering of the resulting neural networks' weights identiied key components of the AR representation.
Stream data clustering based on grid density and attraction

Clustering real-time stream data is an important and challenging problem. Existing algorithms such as CluStream are based on the k-means algorithm. These clustering algorithms have difficulties finding clusters of arbitrary shapes and handling outliers. Further, they require the knowledge of k and user-specified time window. To address these issues, this article proposes D-Stream, a framework for clustering stream data using a density-based approach. Our algorithm uses an online component that maps each input data record into a grid and an offline component that computes the grid density and clusters the grids based on the density. The algorithm adopts a density decaying technique to capture the dynamic changes of a data stream and a attraction-based mechanism to accurately generate cluster boundaries. Exploiting the intricate relationships among the decay factor, attraction, data density, and cluster structure, our algorithm can efficiently and effectively generate and adjust the clusters in real time. Further, a theoretically sound technique is developed to detect and remove sporadic grids mapped by outliers in order to dramatically improve the space and time efficiency of the system. The technique makes high-speed data stream clustering feasible without degrading the clustering quality. The experimental results show that our algorithm has superior quality and efficiency, can find clusters of arbitrary shapes, and can accurately recognize the evolving behaviors of real-time data streams.
Correlating traditional Ayurvedic and modern medical perspectives on cancer: results of a qualitative study.

OBJECTIVE To characterize Ayurvedic perspectives on the etiopathogenesis and supportive treatments for a biomedical diagnosis of cancer. METHODS Hour-long, digitally recorded interviews were conducted with 10 experienced Ayurvedic clinicians, transcribed verbatim, and analyzed using techniques of qualitative thematic analysis. RESULTS Four major themes were identified. The Ayurvedic description of the pathophysiology of cancer uses traditional concepts translated into a modern context. Although the biomedical treatment of cancer is considered valuable, from an Ayurvedic perspective it results in degeneration and depletion. In cases where biomedical treatment of cancer is not feasible, an Ayurvedic approach focusing on strengthening digestion, eliminating toxins, reducing tumor growth, and improving tissue metabolism is useful. An Ayurvedic approach to cancer supportive care focuses on restoring equilibrium, building strength, and rejuvenation. CONCLUSION Ayurvedic medicine offers a unique perspective on the biomedical diagnosis of cancer that emphasizes restoring wholeness, uses natural remedies, includes a focus on emotional health, and emphasizes prevention strategies.
Cell morphogenesis of trichomes in Arabidopsis: differential control of primary and secondary branching by branch initiation regulators and cell growth.

Cell morphogenesis, i.e. the acquisition of a particular cell shape, can be examined genetically in the three-branched trichomes that differentiate from single epidermal cells on the leaves of Arabidopsis thaliana. In normal development, the growing trichome cell undergoes two successive branching events, resulting in a proximal side stem and a distal main stem which subsequently splits in two branches. Using new and previously described trichome mutants, we have analyzed the branching pattern in single and double mutants affecting branch number or cell size in order to determine underlying mechanisms. Our results suggest that primary branching is genetically distinct from subsequent branching events and that the latter, secondary events are initiated in response to positive and negative regulators of branching as well as subject to control by cell growth. We propose a model of how trichome cell morphogenesis is regulated during normal development.
Tonsil volume and allergic rhinitis in children

Tonsil hypertrophy (TH) is very common in children. Previously, it has been reported that an inverse relationship exists between adenoid hypertrophy (AH) and allergic rhinitis (AR). This study aimed to investigate the possible relationship between tonsil volume and AR diagnosis in a group of children complaining of upper airways obstruction. Globally, 171 children (91 boys; mean age, 6.6 years) were studied. Clinical visit, nasal endoscopy, and skin-prick test were performed in all patients. TH and anterior nasal obstruction were graded using the Friedman's classifications. Adenoid volume was graded using the Parikh's classification. Fifty-eight children (33.9%) had relevant TH (grades 3–4); 77 children (44.94%) had AR. There was a strong correlation (gamma = 0.564; p < 0.001) between TH and AH. Tonsil volume was inversely associated with AR diagnosis (odds ratio [OR], 0.314). Risk factors for TH were intense mucosal inflammation (pale mucous membranes) and AH (OR, 3.54 and 2.856, respectively). This study shows that large tonsils are negatively associated with allergy, whereas intense inflammation is a risk factor for TH; AH may be frequently associated with TH.