Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional Activation and Effective Connectivity Differences in Adolescent Marijuana Users Performing a Simulated Gambling Task

Background. Adolescent marijuana use is associated with structural and functional differences in forebrain regions while performing memory and attention tasks. In the present study, we investigated neural processing in adolescent marijuana users experiencing rewards and losses. Fourteen adolescents with frequent marijuana use (>5 uses per week) and 14 nonuser controls performed a computer task where they were required to guess the outcome of a simulated coin flip while undergoing magnetic resonance imaging. Results. Across all participants, “Wins” and “Losses” were associated with activations including cingulate, middle frontal, superior frontal, and inferior frontal gyri and declive activations. Relative to controls, users had greater activity in the middle and inferior frontal gyri, caudate, and claustrum during “Wins” and greater activity in the anterior and posterior cingulate, middle frontal gyrus, insula, claustrum, and declive during “Losses. ” Effective connectivity analyses revealed similar overall network interactions among these regions for users and controls during both “Wins” and “Losses. ” However, users and controls had significantly different causal interactions for 10 out of 28 individual paths during the “Losses” condition. Conclusions. Collectively, these results indicate adolescent marijuana users have enhanced neural responses to simulated monetary rewards and losses and relatively subtle differences in effective connectivity.
Predicting suicide attempts in adolescents with longitudinal clinical data and machine learning

BACKGROUND Adolescents have high rates of nonfatal suicide attempts, but clinically practical risk prediction remains a challenge. Screening can be time consuming to implement at scale, if it is done at all. Computational algorithms may predict suicide risk using only routinely collected clinical data. We used a machine learning approach validated on longitudinal clinical data in adults to address this challenge in adolescents. METHODS This is a retrospective, longitudinal cohort study. Data were collected from the Vanderbilt Synthetic Derivative from January 1998 to December 2015 and included 974 adolescents with nonfatal suicide attempts and multiple control comparisons: 496 adolescents with other self-injury (OSI), 7,059 adolescents with depressive symptoms, and 25,081 adolescent general hospital controls. Candidate predictors included diagnostic, demographic, medication, and socioeconomic factors. Outcome was determined by multiexpert review of electronic health records. Random forests were validated with optimism adjustment at multiple time points (from 1 week to 2 years). Recalibration was done via isotonic regression. Evaluation metrics included discrimination (AUC, sensitivity/specificity, precision/recall) and calibration (calibration plots, slope/intercept, Brier score). RESULTS Computational models performed well and did not require face-to-face screening. Performance improved as suicide attempts became more imminent. Discrimination was good in comparison with OSI controls (AUC = 0.83 [0.82-0.84] at 720 days; AUC = 0.85 [0.84-0.87] at 7 days) and depressed controls (AUC = 0.87 [95% CI 0.85-0.90] at 720 days; 0.90 [0.85-0.94] at 7 days) and best in comparison with general hospital controls (AUC 0.94 [0.92-0.96] at 720 days; 0.97 [0.95-0.98] at 7 days). Random forests significantly outperformed logistic regression in every comparison. Recalibration improved performance as much as ninefold - clinical recommendations with poorly calibrated predictions can lead to decision errors. CONCLUSIONS Machine learning on longitudinal clinical data may provide a scalable approach to broaden screening for risk of nonfatal suicide attempts in adolescents.
H2O maser and a plasma obscuring torus in the radio galaxy NGC 1052

We present multi-frequency simultaneous VLBA observations at 15, 22 and 43 GHz towards the nucleus of the nearby radio galaxy NGC 1052. These three continuum images reveal a double-sided jet structure, whose relative intensity ratios imply that the jet axis is oriented close to the sky plane. The steeply rising spectra at 15–43 GHz at the inner edges of the jets strongly suggest that synchrotron emission is absorbed by foreground thermal plasma. We detected H2O maser emission in the velocity range of 1550–1850 km s–1, which is redshifted by 50–350 km s–1 with respect to the systemic velocity of NGC 1052. The redshifted maser gas appears projected against both sides of the jet, similar to the H I seen in absorption. The H2O maser gas is located where the free-free absorption opacity is large. This probably implies that the masers in NGC 1052 are associated with a circumnuclear torus or disk as in the nucleus of NGC 4258. Such circumnuclear structure can be the sense of accreting onto the central engine (© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Factors Contributing to Preschoolers' Communicative Participation Outcomes: Findings From a Population-Based Longitudinal Cohort Study in Ontario, Canada.

Purpose The aim of this study was to identify predictors of communicative participation outcomes for a large cohort of preschoolers with speech and language impairments. Method A secondary analysis of longitudinal program evaluation data from Ontario, Canada's Preschool Speech and Language Program was done. Data available for 46,872 children 18-67 months of age (M = 41.76 months, SD = 11.92; 68% boys, 32% girls) were previously used to predict children's communicative participation skill development in 5 levels of function. Demographic and intervention-based variables were added to the models to identify new predictors of growth. Results Three demographic and 3 intervention-based variables were statistically significant predictors of children's communicative participation outcomes. Clinically significant predictors included participation in an early learning environment, receipt of speech-language interventions, and the amount of time spent in intervention. These variables impacted predicted outcomes differently, depending on a child's level of communicative function. Conclusions This population-based study of preschoolers with speech and language impairments identified predictors of growth in communicative participation skills-an outcome important and meaningful to families but not often explored. A broad picture emerged of factors that may influence the development of communicative participation skills and may be used to predict outcomes for preschoolers. Given the large sample size, these robust findings may be used to predict outcomes outside the Preschool Speech and Language Program as well. Supplemental Material https://doi.org/10.23641/asha.6024422.
Auditory Processing under Cross-Modal Visual Load Investigated with Simultaneous EEG-fMRI

Cognitive task demands in one sensory modality (T1) can have beneficial effects on a secondary task (T2) in a different modality, due to reduced top-down control needed to inhibit the secondary task, as well as crossmodal spread of attention. This contrasts findings of cognitive load compromising a secondary modality’s processing. We manipulated cognitive load within one modality (visual) and studied the consequences of cognitive demands on secondary (auditory) processing. 15 healthy participants underwent a simultaneous EEG-fMRI experiment. Data from 8 participants were obtained outside the scanner for validation purposes. The primary task (T1) was to respond to a visual working memory (WM) task with four conditions, while the secondary task (T2) consisted of an auditory oddball stream, which participants were asked to ignore. The fMRI results revealed fronto-parietal WM network activations in response to T1 task manipulation. This was accompanied by significantly higher reaction times and lower hit rates with increasing task difficulty which confirmed successful manipulation of WM load. Amplitudes of auditory evoked potentials, representing fundamental auditory processing showed a continuous augmentation which demonstrated a systematic relation to cross-modal cognitive load. With increasing WM load, primary auditory cortices were increasingly deactivated while psychophysiological interaction results suggested the emergence of auditory cortices connectivity with visual WM regions. These results suggest differential effects of crossmodal attention on fundamental auditory processing. We suggest a continuous allocation of resources to brain regions processing primary tasks when challenging the central executive under high cognitive load.
Spectral classification of emission-line galaxies from the Sloan Digital Sky Survey. I. An improved classification for high redshift galaxies

We study the spectral classification of emission-line galaxies as star-forming galaxies or Active Galactic Nuclei (AGNs). From the Sloan Digital Sky Survey (SDSS) high quality data, we define an improved classification to be used for high redshift galaxies. We classify emission-line galaxies of the SDSS according to the latest standard recipe using [Oiii]5007, [Nii]6584, [Sii]6717+6731, H, and H emission lines. We obtain four classes: star-forming galaxies, Seyfert 2, LINERs, and composites. We then examine where these galaxies fall in the blue diagram used at high redshift (i.e. log([Oiii]5007/H) vs. log([Oii]3726+3729/H). We define new improved boundaries in the blue diagram for star-forming galaxies, Seyfert 2, LINERs, SF/Sy2, and SF-LIN/comp classes. We maximize the success rate to 99.7% for the detection of star-forming galaxies, to 86% for the Seyfert 2 (including the SF/Sy2 region), and to 91% for the LINERs. We also minimize the contamination to 16% in the region of star-forming galaxies. We cannot reliably separate composites from star-forming galaxies and LINERs, but we define a SF/LIN/comp region where most of them fall (64%).
Emotion detection: a technology review

Emotion detection has become one of the most important aspects to consider in any project related to Affective Computing. Due to the almost endless applications of this new discipline, the development of emotion detection technologies has brought up as a quite profitable opportunity in the corporate sector. Many start-up enterprises have emerged in the last years, dedicated almost exclusively to a specific type of emotion detection technology. In this paper, we present a thorough review of current technologies to detect human emotions. To this end, we explore the different sources from which emotions can be read, along with existing technologies developed to recognize them. We also explore some application domains in which this technology has been applied. This survey has let us identify the strengths and shortcomings of current technology for emotion detection. We conclude the survey highlighting the aspects that requires further research and development.
Efficient Reasoning in Multiagent Epistemic Logics

In many applications, agents must reason about what other agents know, whether to coordinate with them or to come out on top in a competitive situation. However in general, reasoning in a multiagent epistemic logic such as Kn has high complexity. In this paper, we look at a restricted class of knowledge bases that are sets of modal literals. We call these proper epistemic knowledge bases (PEKBs). We show that after a PEKB has been put in prime implicate normal form (PINF), an efficient database-like query evaluation procedure can be used to check whether an arbitrary query is entailed by the PEKB. The evaluation procedure is always sound and sometimes complete. We also develop a procedure to convert a PEKB into PINF. As well, we extend our approach to deal with introspection.
Electric shock causes physiological stress responses in shore crabs, consistent with prediction of pain

Animal pain is defined by a series of expectations or criteria, one of which is that there should be a physiological stress response associated with noxious stimuli. While crustacean stress responses have been demonstrated they are typically preceded by escape behaviour and thus the physiological change might be attributed to the behaviour rather than a pain experience. We found higher levels of stress as measured by lactate in shore crabs exposed to brief electric shock than non-shocked controls. However, shocked crabs showed more vigorous behaviour than controls. We then matched crabs with the same level of behaviour and still found that shocked crabs had stronger stress response compared with controls. The finding of the stress response, coupled with previous findings of long-term motivational change and avoidance learning, fulfils the criteria expected of a pain experience.
Fully CMOS Memristor Based Chaotic Circuit Ş

This paper demonstrates the design of a fully CMOS chaotic circuit consisting of only DDCC based memristor and inductance simulator. Our design is composed of these active blocks using CMOS 0.18 μm process technology with symmetric ±1.25 V supply voltages. A new single DDCC+ based topology is used as the inductance simulator. Simulation results verify that the design proposed satisfies both memristor properties and the chaotic behavior of the circuit. Simulations performed illustrate the success of the proposed design for the realization of CMOS based chaotic applications.
Computational inference and experimental validation of the nitrogen assimilation regulatory network in cyanobacterium Synechococcus sp. WH 8102

Deciphering the regulatory networks encoded in the genome of an organism represents one of the most interesting and challenging tasks in the post-genome sequencing era. As an example of this problem, we have predicted a detailed model for the nitrogen assimilation network in cyanobacterium Synechococcus sp. WH 8102 (WH8102) using a computational protocol based on comparative genomics analysis and mining experimental data from related organisms that are relatively well studied. This computational model is in excellent agreement with the microarray gene expression data collected under ammonium-rich versus nitrate-rich growth conditions, suggesting that our computational protocol is capable of predicting biological pathways/networks with high accuracy. We then refined the computational model using the microarray data, and proposed a new model for the nitrogen assimilation network in WH8102. An intriguing discovery from this study is that nitrogen assimilation affects the expression of many genes involved in photosynthesis, suggesting a tight coordination between nitrogen assimilation and photosynthesis processes. Moreover, for some of these genes, this coordination is probably mediated by NtcA through the canonical NtcA promoters in their regulatory regions.
How patch size and refuge availability change interaction strength and population dynamics: a combined individual- and population-based modeling experiment

Knowledge on how functional responses (a measurement of feeding interaction strength) are affected by patch size and habitat complexity (represented by refuge availability) is crucial for understanding food-web stability and subsequently biodiversity. Due to their laborious character, it is almost impossible to carry out systematic empirical experiments on functional responses across wide gradients of patch sizes and refuge availabilities. Here we overcame this issue by using an individual-based model (IBM) to simulate feeding experiments. The model is based on empirically measured traits such as body-mass dependent speed and capture success. We simulated these experiments in patches ranging from sizes of petri dishes to natural patches in the field. Moreover, we varied the refuge availability within the patch independently of patch size, allowing for independent analyses of both variables. The maximum feeding rate (the maximum number of prey a predator can consume in a given time frame) is independent of patch size and refuge availability, as it is the physiological upper limit of feeding rates. Moreover, the results of these simulations revealed that a type III functional response, which is known to have a stabilizing effect on population dynamics, fitted the data best. The half saturation density (the prey density where a predator consumes half of its maximum feeding rate) increased with refuge availability but was only marginally influenced by patch size. Subsequently, we investigated how patch size and refuge availability influenced stability and coexistence of predator-prey systems. Following common practice, we used an allometric scaled Rosenzweig–MacArthur predator-prey model based on results from our in silico IBM experiments. The results suggested that densities of both populations are nearly constant across the range of patch sizes simulated, resulting from the constant interaction strength across the patch sizes. However, constant densities with decreasing patch sizes mean a decrease of absolute number of individuals, consequently leading to extinction of predators in the smallest patches. Moreover, increasing refuge availabilities also allowed predator and prey to coexist by decreased interaction strengths. Our results underline the need for protecting large patches with high habitat complexity to sustain biodiversity.
Towards computer-aided reverse engineering of heavy vehicle parts using laser range imaging techniques

We present an integrated system to automatically generate computer-aided design (CAD) models of existing vehicle parts using laser range imaging techniques. The proposed system integrates data acquisition, model reconstruction, and post processing to generate a set of models from real-world automotive parts. This range image-based, computer-aided reverse engineering (CARE) system has potential for faster model reconstruction over traditional reverse engineering technologies. As part of this system, we also propose a novel crease detection algorithm, which segments the surfaces of reconstructed models along smoothness discontinuities. We present results for both the CARE system and the proposed crease detection algorithm for a set of automotive parts.
Connecting the dots1 : Mental spaces and metaphoric language in discourse

How are metaphors understood in local context? We examine the rise of the expression "connect the dots" as it appears in the speech of counter-terrorism expert Richard Clarke in a radio interview. Although conceptual metaphor theory (Lakoff& Johnson 1980, 1999) provides important insights into the congruence of the connect-the-dots-metaphor with conventional metaphoric mappings between seeing and knowing, it cannot account for novel uses of the metaphor in the expressions used by these discourse participants. These novel metaphors are better described by mental spaces and conceptual integration theory, as involving conceptual structure integrated from multiple mental spaces. We examine how specific aspects of background, contextual, and linguistic knowledge contribute to their meaning in this particular instance. Examining prosodic features in the speech will help us account for the role vocalization plays in the structuring of ongoing discourse. This examination enables researchers to assess the compatibility between mental spaces theory and Wallace Chafe's theory of discourse.
Social-data storage-systems

The amount of social data produced by a wide variety of social platforms grows every day. Storing and querying this huge amount of data in almost real time presents a challenge to storage systems in order to scale up to hundreds or thousands of nodes. Also the graph structure and the diverse and changing structure of every single node in social data has to be handled by these systems. In this paper, we describe five storage system types on the basis of eight current open source storage system solutions in order to analyze their application potential.
Predicting Age of Sexual Initiation: Family-Level Antecedents in Three Ethnic Groups

We investigated how family characteristics and experiences during early adolescence predicted timing of sexual initiation. In addition, we investigated adolescent sex and race/ethnicity as potential moderating factors. As part of the Children of the National Longitudinal Survey of Youth-1979 (CNLSY-79), 799 adolescents aged 12 to 15 years provided data at 2-year intervals between 1994 and 2010 (51.7% male; 24.5% Hispanic, 36.5% African American, 38.9% European American); their mothers also provided data in 1986 and 1994. Analyses indicated that early sexual initiation was primarily attributable to male sex, Black race, early maternal childbearing, father absence, and adolescents’ autonomous decision making during early adolescence. Multigroup path models suggested that few effects were moderated by sex or race/ethnicity. We discuss implications of these findings for future research and prevention/intervention efforts.
Crowdsourcing as a Screening Tool to Detect Clinical Features of Glaucomatous Optic Neuropathy from Digital Photography

Aim Crowdsourcing is the process of simplifying and outsourcing numerous tasks to many untrained individuals. Our aim was to assess the performance and repeatability of crowdsourcing in the classification of normal and glaucomatous discs from optic disc images. Methods Optic disc images (N = 127) with pre-determined disease status were selected by consensus agreement from grading experts from a large cohort study. After reading brief illustrative instructions, we requested that knowledge workers (KWs) from a crowdsourcing platform (Amazon MTurk) classified each image as normal or abnormal. Each image was classified 20 times by different KWs. Two study designs were examined to assess the effect of varying KW experience and both study designs were conducted twice for consistency. Performance was assessed by comparing the sensitivity, specificity and area under the receiver operating characteristic curve (AUC). Results Overall, 2,540 classifications were received in under 24 hours at minimal cost. The sensitivity ranged between 83–88% across both trials and study designs, however the specificity was poor, ranging between 35–43%. In trial 1, the highest AUC (95%CI) was 0.64(0.62–0.66) and in trial 2 it was 0.63(0.61–0.65). There were no significant differences between study design or trials conducted. Conclusions Crowdsourcing represents a cost-effective method of image analysis which demonstrates good repeatability and a high sensitivity. Optimisation of variables such as reward schemes, mode of image presentation, expanded response options and incorporation of training modules should be examined to determine their effect on the accuracy and reliability of this technique in retinal image analysis.
Support Vector Machines as Multivariate Calibration Model for Prediction of Blood Glucose Concentration Using a New Non-invasive Optical Method Named Pulse Glucometry

A novel optical non-invasive in vivo blood glucose concentration (BGL) measurement technique, named "Pulse Glucometry", was combined with a kernel method; support vector machines. The total transmitted radiation intensity (Ilambda) and the cardiac-related pulsatile changes superimposed on Ilambda in human adult fingertips were measured over the wavelength range from 900 to 1700 nm using a very fast spectrophotometer, obtaining a differential optical density (DeltaODlambda) related to the blood component in the finger tissues. Subsequently, a calibration model using paired data of a family of DeltaODlambdas and the corresponding known BGLs was constructed with support vector machines regression instead of using calibration by a conventional partial least squares regression (PLS). Our results show that the calibration model based on the support vector machines can provide a good regression for the 183 paired data, in which the BGLs ranged from 89.0-219 mg/dl (4.94-12.2 mmol/1). The resultant regression was evaluated by the Clarke error grid analysis and all data points fell within the clinically acceptable regions (region A: 93%, region B: 7%).