Absence Of Contextual Information Research Articles

Interdisciplinary methodology for the characterisation of archaeological metal grave goods from the Museum of Patagonia by PIXE, DRX, and SEM/EDS

AbstractWe present a study of a selection of metal ornaments belonging to archaeological funerary goods from Patagonic Indigenous groups. They are part of the ‘Andrés Giai’ Collection, under the guard of the Museum of Patagonia (Nahuel Huapi National Park [PNNH]; National Parks Administration [APN]), Argentina. The absence of contextual information and its current conservation status motivated the design of an interdisciplinary methodology to develop an Integral Conservation Plan that considered the selection of analytical techniques. Here, we implemented complementary nondestructive characterisation techniques such as particle induced X‐ray emission (PIXE), X‐ray diffraction (XRD) and scanning electron microscopy coupled with energy dispersive X‐ray spectroscopy (SEM/EDS). We developed a methodology enabling us to characterise each piece with respect to its metallic composition and degradation products, and in certain cases, their manufacturing process. These findings have contributed with essential information for the tailored conservation treatment proposal. Moreover, they provided key information in regard to the reconstruction of contextual data for each piece. In addition, the methodology proposed for the Integral Conservation Plan takes into account an optimisation of the techniques to be used in order to minimise unnecessary handling of goods whilst ensuring an appropriate use of technological and economic resources whilst minimising time on potentially unconclusive measurements and results.

Zero-shot stance detection via multi-perspective contrastive learning with unlabeled data

Stance detection is to distinguish whether the text’s author supports, opposes, or maintains a neutral stance towards a given target. In most real-world scenarios, stance detection needs to work in a zero-shot manner, i.e., predicting stances for unseen targets without labeled data. One critical challenge of zero-shot stance detection is the absence of contextual information on the targets. Current works mostly concentrate on introducing external knowledge to supplement information about targets, but the noisy schema-linking process hinders their performance in practice. To combat this issue, we argue that previous studies have ignored the extensive target-related information inhabited in the unlabeled data during the training phase, and propose a simple yet efficient Multi-Perspective Contrastive Learning Framework for zero-shot stance detection. Our framework is capable of leveraging information not only from labeled data but also from extensive unlabeled data. To this end, we design target-oriented contrastive learning and label-oriented contrastive learning to capture more comprehensive target representation and more distinguishable stance features. We conduct extensive experiments on three widely adopted datasets (from 4870 to 33,090 instances), namely SemEval-2016, WT-WT, and VAST. Our framework achieves 53.6%, 77.1%, and 72.4% macro-average F1 scores on these three datasets, showing 2.71% and 0.25% improvements over state-of-the-art baselines on the SemEval-2016 and WT-WT datasets and comparable results on the more challenging VAST dataset.

Deep Bidirectional LSTM Network Learning-Based Sentiment Analysis for Arabic Text

Abstract Sentiment analysis aims to predict sentiment polarities (positive, negative or neutral) of a given piece of text. It lies at the intersection of many fields such as Natural Language Processing (NLP), Computational Linguistics, and Data Mining. Sentiments can be expressed explicitly or implicitly. Arabic Sentiment Analysis presents a challenge undertaking due to its complexity, ambiguity, various dialects, the scarcity of resources, the morphological richness of the language, the absence of contextual information, and the absence of explicit sentiment words in an implicit piece of text. Recently, deep learning has obviously shown a great success in the field of sentiment analysis and is considered as the state-of-the-art model in Arabic Sentiment Analysis. However, the state-of-the-art accuracy for Arabic sentiment analysis still needs improvements regarding contextual information and implicit sentiment expressed in different real cases. In this paper, an efficient Bidirectional LSTM Network (BiLSTM) is investigated to enhance Arabic Sentiment Analysis, by applying Forward-Backward encapsulate contextual information from Arabic feature sequences. The experimental results on six benchmark sentiment analysis datasets demonstrate that our model achieves significant improvements over the state-of-art deep learning models and the baseline traditional machine learning methods.

An error-tuned model for sensorimotor learning.

Current models of sensorimotor control posit that motor commands are generated by combining multiple modules which may consist of internal models, motor primitives or motor synergies. The mechanisms which select modules based on task requirements and modify their output during learning are therefore critical to our understanding of sensorimotor control. Here we develop a novel modular architecture for multi-dimensional tasks in which a set of fixed primitives are each able to compensate for errors in a single direction in the task space. The contribution of the primitives to the motor output is determined by both top-down contextual information and bottom-up error information. We implement this model for a task in which subjects learn to manipulate a dynamic object whose orientation can vary. In the model, visual information regarding the context (the orientation of the object) allows the appropriate primitives to be engaged. This top-down module selection is implemented by a Gaussian function tuned for the visual orientation of the object. Second, each module's contribution adapts across trials in proportion to its ability to decrease the current kinematic error. Specifically, adaptation is implemented by cosine tuning of primitives to the current direction of the error, which we show to be theoretically optimal for reducing error. This error-tuned model makes two novel predictions. First, interference should occur between alternating dynamics only when the kinematic errors associated with each oppose one another. In contrast, dynamics which lead to orthogonal errors should not interfere. Second, kinematic errors alone should be sufficient to engage the appropriate modules, even in the absence of contextual information normally provided by vision. We confirm both these predictions experimentally and show that the model can also account for data from previous experiments. Our results suggest that two interacting processes account for module selection during sensorimotor control and learning.

Méthodologie et construction des bases Minotaure-ARNO des Archives nationales : quels éléments pour un glossaire des typologies d’actes ?

The Minutier central des notaires de Paris and the École nationale des chartes are currently working on a typology of notarial acts produced in Paris in the nineteenth century. Their aim is to construct a glossary that can be used as a reference tool by archivists and as a finding aid by researchers, historians as well as genealogists. It was obvious from the start that ARNO 1851, an exhaustive database for the year 1851 compiled by theMinutier central, could be used to identify the different types of acts and to select the ones that should be included in the glossary. As a first step, it was essential to understand how this and earlier databases available at the Archives Nationales had been designed and developed by their various authors and supervisors. This article presents the history of these databases and the methodologies used to create them, as well as exploring such limitations as the unreliability of data and the absence of contextual information.

Grasping intentions: from thought experiments to empirical evidence

Skepticism has been expressed concerning the possibility to understand others' intentions by simply observing their movements: since a number of different intentions may have produced a particular action, motor information—it has been argued—might be sufficient to understand what an agent is doing, but not her remote goal in performing that action. Here we challenge this conclusion by showing that in the absence of contextual information, intentions can be inferred from body movement. Based on recent empirical findings, we shall contend that: (1) intentions translate into differential kinematic patterns; (2) observers are especially attuned to kinematic information and can use early differences in visual kinematics to anticipate the intention of an agent in performing a given action; (3) during interacting activities, predictions about the future course of others' actions tune online action planning; (4) motor activation during action observation subtends a complementary understanding of what the other is doing. These findings demonstrate that intention understanding is deeply rooted in social interaction: by simply observing others' movements, we might know what they have in mind to do and how we should act in response.

Predicting the presuppositions of soft triggers

The central idea behind this paper is that presuppositions of soft triggers arise from the way our attention structures the informational content of a sentence. Some aspects of the information conveyed are such that we pay attention to them by default, even in the absence of contextual information. On the other hand, contextual cues or conversational goals can divert attention to types of information that we would not pay attention to by default. Either way, whatever we do not pay attention to, be it by default, or in context, is what ends up presupposed by soft triggers. This paper attempts to predict what information in the sentence is likely to end up being the main point (i.e. what we pay attention to) and what information is independent from this, and therefore likely presupposed. It is proposed that this can be calculated by making reference to event times. The notion of aboutness used to calculate independence is based on that of Demolombe and Fariñas del Cerro (In: Holdobler S (ed) Intellectics and computational logic: papers in honor of Wolfgang Bibel, 2000).

Detecting sarcasm from paralinguistic cues: Anatomic and cognitive correlates in neurodegenerative disease

While sarcasm can be conveyed solely through contextual cues such as counterfactual or echoic statements, face-to-face sarcastic speech may be characterized by specific paralinguistic features that alert the listener to interpret the utterance as ironic or critical, even in the absence of contextual information. We investigated the neuroanatomy underlying failure to understand sarcasm from dynamic vocal and facial paralinguistic cues. Ninety subjects (20 frontotemporal dementia, 11 semantic dementia [SemD], 4 progressive non-fluent aphasia, 27 Alzheimer's disease, 6 corticobasal degeneration, 9 progressive supranuclear palsy, 13 healthy older controls) were tested using the Social Inference — Minimal subtest of The Awareness of Social Inference Test (TASIT). Subjects watched brief videos depicting sincere or sarcastic communication and answered yes–no questions about the speaker's intended meaning. All groups interpreted Sincere (SIN) items normally, and only the SemD group was impaired on the Simple Sarcasm (SSR) condition. Patients failing the SSR performed more poorly on dynamic emotion recognition tasks and had more neuropsychiatric disturbances, but had better verbal and visuospatial working memory than patients who comprehended sarcasm. Voxel-based morphometry analysis of SSR scores in SPM5 demonstrated that poorer sarcasm comprehension was predicted by smaller volume in bilateral posterior parahippocampi (PHc), temporal poles, and R medial frontal pole (pFWE<0.05). This study provides lesion data suggesting that the PHc may be involved in recognizing a paralinguistic speech profile as abnormal, leading to interpretive processing by the temporal poles and right medial frontal pole that identifies the social context as sarcastic, and recognizes the speaker's paradoxical intentions.

Food-associated Calls of Tufted Capuchin Monkeys (Cebus Apella Nigritus) Are Functionally Referential Signals

In this paper I explore the possibility that tufted capuchin monkeys ( Cebus apella nigritus ) have food-associated calls, vocalizations that are functionally referential and may provide information about the presence of food to other individuals in the group. Functionally referential signals are those that meet two criteria: (1) they are context specific and (2) they elicit a response that is context independent. The study was conducted on a wild group of capuchins in a subtropical rain-forest in NE Argentina. To evaluate the degree of context specificity of the vocalizations I obtained focal animal sound recordings of the vocalizations emitted by individually recognized animals and indicated the socio-ecological context of call emission. I performed playback experiments to see if animals can respond to the food-associated calls in the absence of contextual information. Two vocalizations, grgrs and whistle series, were considered putative food-associated calls, because previous observations suggested an association of these vocalizations with the presence of food. Grgrs and whistle series were given at a higher rate when the focal animal was feeding on fruit at a highly productive source than in other socioecological contexts. Whistle series were also produced, although at a lower rate, in contexts other than feeding but whistle series given when feeding belong to an acoustically distinct type. Animals responded to the playback of food-associated calls with a rapid and direct movement to the speaker in almost 50% of the trials. Capuchins did not show this response to the playback of control stimuli. Food-associated calls in tufted capuchins can thus be considered functionally referential signals.

Classification of Remotely Sensed Images using Artificial Neural Networks

Neural networks are growing in popularity today as a tool for classification of remotely sensed images. One of the major stumbling blocks for neural networks to be accepted for operational use in remote sensing has been the long computational times involved. This is particularly relevant in the case of the well-known back-propagation (BP) algorithm trained multilayer perceptron (MLP) classifier. The long time involved in training the network to realize the relationship between the training data and their assigned classes is due to lack of a sound theory to set the initial network parameters. Errors in classification are partly due to mixed pixels and absence of contextual information, which is almost always used by human interpreters while analyzing images. An approach is suggested here to take advantage of global optimization techniques to assist in proper training of the MLP classifier, and use of relaxation labelling algorithms to refine the MLP output based on the contextual information present within small local neighbourhoods of pixels. The results are illustrated using Indian Remote Sensing (IRS) images.

The facial expression of anger in seven-month-old infants.

This study concerned whether anger can be observed reliably in facial expressions as early as 7 months of age in a sample of 30 infants. It also assessed the influence of several variables on anger responses: infant's familiarity with the frustrator (mother vs. stranger), repetition of trials, and sex of the child. Correlations were obtained between the expression of anger and cognitive developmental level, maternal perceptions of irascibility (temperament), time since eating or sleeping, and facial flushing. Dependent variables included facial expression components as well as ratings of facial flushing. We found that the capacity to express anger is well developed by 7 months of age: facial patterning was detected reliably in the absence of contextual information, and repeated frustrations increased the amount of anger shown. No significant relationships were found, however, between facial expression of anger and temperament, drive states, or cognitive developmental scores.

The components of population change in nineteenth-century South-east Asia: Village data from the Philippines

Most analysis of contemporary demographic patterns in developing countries suffers from the lack of any useful basis for historical comparison- from the absence of contextual information regarding the movements of the same variables at earlier points in time. And since modern analyses of fertility trends in developing countries almost always describe a period late in the process of rapid economic change, relative to the encroachment of the global economic system on indigenous economies (which in many instances began as early as the nineteenth century), we are often without true baseline information on indigenous demographic processes. The importance of pushing time series of demographic observation backward into the past has been demonstrated amply by the work of the last several decades in European historical demography. The simple concept of the demographic transition has been revised, enriched, and finally transformed into useful behavioural models by painstaking historical reconstruction of individual histories at the local level.1 But despite these advances, the range of cultures and subsistence systems on which our theories of demographic change rest remains extremely narrow outside of the rich body of European and Japanese aggregative and reconstitution studies. There is a real need for historical demographic reconstruction at both aggregate and micro-levels in additional non-western settings. This paper is derived from a continuing research programme in Philippine historical demography that has three long-term goals: to establish a comparative basis for studies of contemporary demographic changes in the Philippines; to answer certain questions of particular interest in the setting of colonial and post-colonial South-east Asia; and to diversify the empirical base of demographic transition theory. Our focus is on the interpretation of aggregate patterns and trends for one rural Philippine locality during the nineteenth century - the pueblo of Nagcarlan. Data from Nagcarlan and similar data for the province and colony surrounding it are juxtaposed, as is limited information from elsewhere in the South-east Asian region. This allows us to sketch the prevailing demography of the region and the place of Nagcarlan as a community-level microcosm of that demographic regime. Only aggregate results are presented in this paper; our micro-level findings will be presented separately. Since a community-level reconstruction of population change has never been attempted with the data explored here, we are concerned equally with the substance of the demographic regime during the nineteenth century and with the adequacy of the data base for describing it. At several points in the analysis more than one method of estimation is used in order to establish the plausibility and consistency of the results. * Peter C. Smith is a Research Associate at the East-West Population Institute, Honolulu, Hawaii. Shui-Meng

Facial Patterning and Infant Emotional Expression: Happiness, Surprise, and Fear

Although recent studies have convincingly demonstrated that emotional expressions can be judged reliably from actor-posed facial displays, there exists little evidence that facial expressions in lifelike settings are similar to actor-posed displays, are reliable across situations designed to elicit the same emotion, or provide sufficient information to mediate consistent emotion judgments by raters. The present study therefore investigated these issues as they related to the emotions of happiness, surprise, and fear. 27 infants between 10 and 12 months of age (when emotion masking is not likely to confound results) were tested in 2 situations designed to elicit hapiness (peek-a-boo game and a collapsing toy), 2 to elicit surprise (a toy-switch and a vanishing-object task), and 2 to elicit fear (the visual cliff and the approach of a stranger. Dependent variables included changes in 28 facial response components taken from previous work using actor poses, as well as judgments of the presence of 6 discrete emotions. In addition, instrumental behaviors were used to verify with other than facial expression responses whether the predicted emotion was elicited. In contrast to previous conclusions on the subject, we found that judges were able to make all facial expression judgments reliably, even in the absence of contextual information. Support was also obtained for at least some degree of specificity of facial component response patterns, especially for happiness and surprise. Emotion judgments by raters were found to be a function of the presence of discrete facial components predicted to be linked to those emotions. Finally, almost all situations elicited blends, rather than discrete emotions.