Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanisms of noise robust representation of speech in primary auditory cortex

Significance We show that the auditory system maintains a robust representation of speech in noisy and reverberant conditions by preserving the same statistical distribution of responses in all conditions. Reconstructed stimulus from population of cortical neurons resembles more the original clean than the distorted signal. We show that a linear spectrotemporal receptive field model of neurons with a static nonlinearity fails to account for the neural noise reduction. Although replacing static nonlinearity with a dynamic model of synaptic depression can account for the reduction of additive noise, only the combined model with feedback gain normalization is able to predict the effects across both additive and reverberant conditions. Humans and animals can reliably perceive behaviorally relevant sounds in noisy and reverberant environments, yet the neural mechanisms behind this phenomenon are largely unknown. To understand how neural circuits represent degraded auditory stimuli with additive and reverberant distortions, we compared single-neuron responses in ferret primary auditory cortex to speech and vocalizations in four conditions: clean, additive white and pink (1/f) noise, and reverberation. Despite substantial distortion, responses of neurons to the vocalization signal remained stable, maintaining the same statistical distribution in all conditions. Stimulus spectrograms reconstructed from population responses to the distorted stimuli resembled more the original clean than the distorted signals. To explore mechanisms contributing to this robustness, we simulated neural responses using several spectrotemporal receptive field models that incorporated either a static nonlinearity or subtractive synaptic depression and multiplicative gain normalization. The static model failed to suppress the distortions. A dynamic model incorporating feed-forward synaptic depression could account for the reduction of additive noise, but only the combined model with feedback gain normalization was able to predict the effects across both additive and reverberant conditions. Thus, both mechanisms can contribute to the abilities of humans and animals to extract relevant sounds in diverse noisy environments.
Lyric-based Song Sentiment Classification with Sentiment Vector Space Model

Lyric-based song sentiment classification seeks to assign songs appropriate sentiment labels such as light-hearted and heavy-hearted. Four problems render vector space model (VSM)-based text classification approach ineffective: 1) Many words within song lyrics actually contribute little to sentiment; 2) Nouns and verbs used to express sentiment are ambiguous; 3) Negations and modifiers around the sentiment keywords make particular contributions to sentiment; 4) Song lyric is usually very short. To address these problems, the sentiment vector space model (s-VSM) is proposed to represent song lyric document. The preliminary experiments prove that the s-VSM model outperforms the VSM model in the lyric-based song sentiment classification task.
Salience and defaults in utterance processing

The book addresses controversies around the conscious vs automatic processing of contextual information and the distinction between literal and nonliteral meaning. It sheds new light on the relation of the literal/nonliteral distinction to the distinction between the automatic and conscious retrieval of information. The question of literal meaning is inherently interwoven with the question of salience and defaults. This volume addresses these interconnected issues, stressing their mutual interdependence.
A Rossby Wave Bridge from the Tropical Atlantic to West Antarctica

AbstractTropical Atlantic sea surface temperature changes have recently been linked to circulation anomalies around Antarctica during austral winter. Warming in the tropical Atlantic associated with the Atlantic multidecadal oscillation forces a positive response in the southern annular mode, strengthening the Amundsen–Bellingshausen Sea low in particular. In this study, observational and reanalysis datasets and a hierarchy of atmospheric models are used to assess the seasonality and dynamical mechanism of this teleconnection. Both the reanalyses and models reveal a robust link between tropical Atlantic SSTs and the Amundsen–Bellingshausen Sea low in all seasons except austral summer. A Rossby wave mechanism is then shown to both explain the teleconnection and its seasonality. The mechanism involves both changes in the excitation of Rossby wave activity with season and the formation of a Rossby waveguide across the Pacific, which depends critically on the strength and extension of the subtropical jet over.
Clinical Prediction Algorithm (BRAIN) to Determine Risk of Hematoma Growth in Acute Intracerebral Hemorrhage

Background and Purpose— We developed and validated a simple algorithm to predict the risk of hematoma growth in acute spontaneous intracerebral hemorrhage (ICH) to better inform clinicians and researchers in their efforts to improve outcomes for patients. Methods— We analyzed data from the computed tomography substudies of the pilot and main phases of the Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trials (INTERACT1 and 2, respectively). The study group was divided into a derivation cohort (INTERACT2, n=964) and a validation cohort (INTERACT1, n=346). Multivariable logistic regression was used to identify factors associated with clinically significant (≥6 mL) increase in hematoma volume at 24 hours after symptom onset. A parsimonious risk score was developed on the basis of regression coefficients derived from the logistic model. Results— A 24-point BRAIN score was derived from INTERACT2 (C-statistic, 0.73) based on baseline ICH volume (mL per score, ⩽10=0, 10–20=5, >20=7), recurrent ICH (yes=4), anticoagulation with warfarin at symptom onset (yes=6), intraventricular extension (yes=2), and number of hours to baseline computed tomography from symptom onset (⩽1=5, 1–2=4, 2–3=3, 3–4=2, 4–5=1, >5=0) predicted the probability of ICH growth (ranging from 3.4% for 0 point to 85.8% for 24 points) with good discrimination (C-statistic, 0.73) and calibration (Hosmer–Lemeshow P=0.82) in INTERACT1. Conclusions— The simple BRAIN score predicts the probability of hematoma growth in ICH. This could be used to improve risk stratification for research and clinical practice. Clinical Trial Registration— URL: http://www.clinicaltrials. gov. Unique identifier: NCT00226096 and NCT00716079.
Feature-Based Learners for Description Logics

Inductive learning algorithms that have been applied to learning in description logics (DL) have not been as well studied and optimized as the more general class of feature-based learning algorithms. This paper proposes a way to apply feature-based learners to DL learning tasks by presenting a method to compute a feature-vector representation for DL instances. The representation is based on concepts computed by a DL learning algorithm and by a feature generation method that has previously been applied to sequence categorization tasks. We show encouraging empirical test results using the feature-based learning systems Ripper, C5.0, and Naive Bayes.
Neuroendocrine differentiation in carcinoma of the prostate. Diagnostic, prognostic, and therapeutic implications

Endocrine‐paracrine cells of the prostate (also known as APUD or neuroendocrine cells) constitute, in addition to the basal and exocrine secretory cells, a third population of highly specialized epithelial cells in the prostate gland. These endocrine‐paracrine cells contain, and most likely secrete, serotonin and calcitonin, as well as a variety of other peptides. Little is known of the functional role of these cells, but they probably subserve a paracrine or local regulatory role. They may also regulate via endocrine, lumencrine, or neurocrine mechanisms. These endocrine‐paracrine cells probably play a significant role during prostatic growth and differentiation as well as regulating the secretory process of the mature gland. Neuroendocrine differentiation in prostatic carcinoma occurs in the form of the relatively rare small cell carcinoma and carcinoid or carcinoid‐like tumor, but most commonly as focal neuroendocrine differentiation in a conventional prostatic adenocarcinoma that is a very frequent, if not ubiquitous phenomenon, and reflects tumor cell heterogeneity mimicking the normal differentiation process. The world's literature on neuroendocrine differentiation in prostatic carcinoma is reviewed. Neuroendocrine differentiation in all types of prostatic carcinoma appears to correlate with a poor prognosis. This correlation is probably multifactorial and may relate to a positive correlation with grade, a direct resistance to hormonal manipulation, and/or autocrine/paracrine growth factor activity due to the secretion of neuroendocrine products. Neuron‐specific enolase and chromogranin, as well as other neuroendocrine products, may be useful as serum markers in patients with prostatic carcinoma with neuroendocrine differentiation. New therapeutic strategies need to be developed to treat these tumors. This includes the use of specialized protocols that have been effective against neuroendocrine carcinomas arising in other organ systems.
Supplemental Materials for Reflection Removal using Ghosting Cues

To understand how often ghosting occurs “in the wild”, we analyze images returned by Google’s Image Search. We used the keywords “window reflection”, “window photography reflection”, “window photography reflection problem”, and “reflections on/via/in windows”. After removing irrelevant results such as cartoon images and water reflections, we were left with 197 images. These are shown in Figure 1. We observed that around 96 of these images exhibit significant ghosting (49%). Figure 2 shows sampled images with various levels of ghosting. The original links of these images are in urls.txt.
Bifactor analysis and construct validity of the five facet mindfulness questionnaire (FFMQ) in non-clinical Spanish samples

The objective of the present study was to examine the dimensionality, reliability, and construct validity of the Five Facet Mindfulness Questionnaire (FFMQ) in three Spanish samples using structural equation modeling (SEM). Pooling the FFMQ data from 3 Spanish samples (n = 1191), we estimated the fit of two competing models (correlated five-factor vs. bifactor) via confirmatory factor analysis. The factorial invariance of the best fitting model across meditative practice was also addressed. The pattern of relationships between the FFMQ latent dimensions and anxiety, depression, and distress was analyzed using SEM. FFMQ reliability was examined by computing the omega and omega hierarchical coefficients. The bifactor model, which accounted for the covariance among FFMQ items with regard to one general factor (mindfulness) and five orthogonal factors (observing, describing, acting with awareness, non-judgment, and non-reactivity), fit the FFMQ structure better than the correlated five-factor model. The relationships between the latent variables and their manifest indicators were not invariant across the meditative experience. Observing items had significant loadings on the general mindfulness factor, but only in the meditator sub-sample. The SEM analysis revealed significant links between mindfulness and symptoms of depression and stress. When the general factor was partialled out, the acting with awareness facet did not show adequate reliability. The FFMQ shows a robust bifactor structure among Spanish individuals. Nevertheless, the Observing subscale does not seem to be adequate for assessing mindfulness in individuals without meditative experience.
Concerns and Expectations of Bangladeshi Parents as their Children Start School

This study aimed to examine views, concerns and expectations of immigrant Bangladeshi parents and children in Sydney concerning transition to kindergarten (the first year of school). This study builds on the previous work of the Starting School Research Project at the University of Western Sydney by: • deriving data from families and children for whom English is not the first language; and • exploring the transitional experiences of culturally and linguistically diverse (CALD) children from prior-to-school to school settings. Ten parents and four children were interviewed on the topic of transition to school. In particular, parents were asked to indicate their concerns and expectations that would assist schools in meeting the needs of Bangladeshi children and would make transition to school a positive experience for all concerned. The results revealed issues specific to families and children of non-English-speaking background regarding transition to school.
Considerations in the Identification of Endogenous Substrates for Protein L-Isoaspartyl Methyltransferase: The Case of Synuclein

Protein L-isoaspartyl methyltransferase (PIMT) repairs abnormal isoaspartyl peptide bonds in age-damaged proteins. It has been reported that synuclein, a protein implicated in neurodegenerative diseases, is a major target of PIMT in mouse brain. To extend this finding and explore its possible relevance to neurodegenerative diseases, we attempted to determine the stoichiometry of isoaspartate accumulation in synuclein in vivo and in vitro. Brain proteins from PIMT knockout mice were separated by 2D electrophoresis followed by on-blot [3H]-methylation to label isoaspartyl proteins, and by immunoblotting to confirm the coincident presence of synuclein. On-blot 3H-methylation revealed numerous isoaspartyl proteins, but no signal in the position of synuclein. This finding was corroborated by immunoprecipitation of synuclein followed by on-blot 3H-methylation. To assess the propensity of synuclein to form isoaspartyl sites in vitro, samples of recombinant mouse and human α-synucleins were aged for two weeks by incubation at pH 7.5 and 37°C. The stoichiometries of isoaspartate accumulation were extremely low at 0.02 and 0.07 mol of isoaspartate per mol of protein respectively. Using a simple mathematical model based on the first order kinetics of isoaspartyl protein methyl ester hydrolysis, we ascribe the discrepancy between our results and the previous report to methodological limitations of the latter stemming from an inherent, and somewhat counterintuitive, relationship between the propensity of proteins to form isoaspartyl sites and the instability of the 3H-methyl esters used to tag them. The results presented here indicate that synuclein is not a major target of PIMT in vivo, and emphasize the need to minimize methyl ester hydrolysis when using methylation to assess the abundance of isoaspartyl sites in proteins.
On the divergence of line search methods

We discuss the convergence of line search methods for minimization. We explain how Newton's method and the BFGS method can fail even if the restrictions of the objective function to the search lines are strictly convex functions, the level sets of the objective functions are compact, the line searches are exact and the Wolfe conditions are satisfied. This explanation illustrates a new way to combine general mathematical concepts and symbolic computation to analyze the convergence of line search methods. It also illustrate the limitations of the asymptotic analysis of the iterates of nonlinear programming algorithms.
Finding small balanced separators

Let G be an n-vertex graph that has a vertex separator of size k that partitions the graph into connected components of size smaller than α n, for some fixed 2/3 ≤ α < 1. Such a separator is called an α-separator. Finding an α-separator of size at most k is NP-hard. Moreover, under reasonable complexity theoretic assumptions, it is shown that this problem is not polynomially solvable even when k=O(log n). In this paper, we give a randomized algorithm that finds an α-separator of size k in the given graph, unless the graph contains an (α+ε)-separator of size strictly less than k, in which case our algorithm finds one such separator. For fixed ε, the running time of our algorithm is nO(1)2O(k), which is polynomial for k = O(log n). For bounded degree graphs (as well as for the case of finding balanced edge separators), we present a deterministic algorithm with similar running time.Our algorithm involves (among other things) a new concept that we call (ε,k)-samples. This is related to the notion of detection sets for network failures, introduced by Kleinberg [FOCS 2000]. Our proofs adapt and simplify techniques that were introduced by Kleinberg. As a by-product, our proof improves the known bounds on the size of detection sets. We also show applications of (ε,k)-samples to problems in approximation algorithms and rigorous analysis of heuristics.
RSS-Based Ranging by Leveraging Frequency Diversity to Distinguish the Multiple Radio Paths

Among various ranging techniques, Radio Signal Strength (RSS) based approaches attract intensive research interests because of its low cost and wide applicability. RSS-based ranging is prone to be affected by the multipath phenomenon which allows the radio signals to reach the destination through multiple propagation paths. To address this issue, previous works try to profile the environment and refer this profile during run-time. In a practical dynamic environment, however, the profile frequently changes and the painful retraining is needed. Rather than such static ways of profiling the environments, in this paper, we try to accommodate the environmental dynamics automatically in real-time. The key observation is that given a pair of nodes, the RSS at different spectrum channels will be different. This difference carries the valuable phase information of the radio signals. By analyzing these RSS values, we are able to identify the amplitude of signals solely from the Line-of-Sight (LOS) path. This LOS amplitude is a simple function of the path length (the physical distance). We find that the analysis is a typical non-linear curvature fitting problem that has no general routing algorithms. We prove that, this problem format is ill-conditioned which has no stable and trustable solutions. To deal with this issue, we further explore the practical considerations for the problem and modify it to a greatly improved conditioning shape. We solve the problem by numerical iterations and implement these ideas in a real-time indoor tracking system called MuD. MuD employs only three TelosB nodes as anchors. The experiment results show that in a dynamic environment where five people move around, the averaged localization error is about <inline-formula><tex-math notation="LaTeX">$1$</tex-math> <alternatives><inline-graphic xlink:href="zhang-ieq1-2579619.gif"/></alternatives></inline-formula> meter. Compared with the traditional RSS-based approaches in dynamic environments, the accuracy improves up to <inline-formula> <tex-math notation="LaTeX">$10$</tex-math><alternatives><inline-graphic xlink:href="zhang-ieq2-2579619.gif"/> </alternatives></inline-formula> times.
Photonic Millimeter-wave generation and transmission system applicable to the high-frequency radio interferometers

In the field of high-frequency radio interferometer, Atacama Large Millimeter/sub-millimeter Array (ALMA), its highest receiving frequency reaches 950 GHz. To receive such high frequencies, a higher reference frequency is required (as much as over 100 GHz). To maintain signal coherency, this reference signal has to be highly stable. To address these issues, we have developed a new method to generate and transmit a reference signal in the form of frequency difference between two coherent light waves. The two transmitted optical signals require phase stability better than 10−13 (1sec) in white phase noise in the Allan standard deviation.
Enhancing digital cephalic radiography with mixture models and local gamma correction

We present a new algorithm, called the soft-tissue filter, that can make both soft and bone tissue clearly visible in digital cephalic radiographies under a wide range of exposures. It uses a mixture model made up of two Gaussian distributions and one inverted lognormal distribution to analyze the image histogram. The image is clustered in three parts: background, soft tissue, and bone using this model. Improvement in the visibility of both structures is achieved through a local transformation based on gamma correction, stretching, and saturation, which is applied using different parameters for bone and soft-tissue pixels. A processing time of 1 s for 5 Mpixel images allows the filter to operate in real time. Although the default value of the filter parameters is adequate for most images, real-time operation allows adjustment to recover under- and overexposed images or to obtain the best quality subjectively. The filter was extensively clinically tested: quantitative and qualitative results are reported here.
The Psychology of the Internet

From the Publisher: This volume explores the psychological aspects of cyberspace, a virtual world in which people from around the globe are acting and interacting in many new, unusual, and occasionally alarming ways. Drawing on research in the social sciences, communications, business, and other fields, Dr. Wallace examines how the online environment can influence the way we behave, sometimes for the better, sometimes not. Our own online behavior then becomes part of the Internet's psychological environment for others, creating opportunities for shaping the way this new territory for human interaction is unfolding.
Shoulder pain after stroke: a research challenge.

BACKGROUND An evidence-based approach to the management of shoulder pain after stroke is required, but systematic reviews have highlighted the small number of studies suitable for use in developing clinical guidelines. DESIGN This brief overview summarises obstacles to shoulder pain research that systematic reviews have identified, and compares their therapeutic recommendations to the Royal College of Physicians National Clinical Guidelines for Stroke. CONCLUSION Clinicians treating shoulder pain after stroke can refer to guidelines and systematic reviews, but there are differences in their conclusions regarding the use of steroid injections and electrical stimulation. There is unanimous agreement that further efforts are required to examine interventions singly and in combination.
A Micro-Watt Multi-port Register File with Wide Operating Voltage Range

In this paper, a micro-watt multi-port register file with wide operating voltage range for micro-power applications is presented. Multibank architecture for simultaneous access with collision detecting technique is proposed. The architecture has been analyzed under wide operating voltage range between 1V to 0.25V with varies process corner. Negative voltage write scheme ensures successful write in deep sub-threshold region. Also, an improved read buffer footer and controllable pre-charge in read scheme are designed. A 4W/4R 16KB register file is implemented in UMC 90nm CMOS technology. The simulation results show that the maximum active power of multi-port register file can achieve near 22.3-22.9uW at 485 KHz under 0.25V.
Mitigating Starvation in Wireless Sensor Networks

Wireless sensor nodes deployed in hostile network conditions are required to report events such as enemy movements quickly and reliably. Unfortunately, current CSMA-based MAC protocols for wireless sensor networks suffer from varying degrees of starvation. Such starvation could lead to significant portions of the sensed area being invisible to the sink. It has been shown by prior research that such starvation is caused due to spatial bias and CSMA-based channel access. In this experimental work, we study how the use of B-MAC, the default CSMA-based MAC protocol can be the cause of starvation in a 35 node multi-hop wireless sensor testbed. We then show that the use of Z-MAC, a hybrid MAC, can alleviate such starvation, while at the same time giving high channel utilization