Miracle-dz/UniFAR-FTUs huggingface dataset:
Regional specialization within the human striatum for diverse psychological functions

Significance The subcortical striatum is critical for the planning and execution of motor behavior, and its dysfunction is associated with disorders such as Parkinson’s disease. More recently, the human striatum has also been reported to be involved in heterogeneous nonmotor psychological functions. However, detailed functional mappings of human psychological processes to striatal regions have been bound by theoretical and methodological limitations, including a strong focus on experimental paradigms derived from animal research, and the tendency to infer function from anatomical connectivity, rather than task-related activation. To overcome these limitations, we used a large-scale, unbiased, data-driven approach, and generated a precise, comprehensive functional map, directly associating striatal zones with the broadest range of psychological processes to date. Decades of animal and human neuroimaging research have identified distinct, but overlapping, striatal zones, which are interconnected with separable corticostriatal circuits, and are crucial for the organization of functional systems. Despite continuous efforts to subdivide the human striatum based on anatomical and resting-state functional connectivity, characterizing the different psychological processes related to each zone remains a work in progress. Using an unbiased, data-driven approach, we analyzed large-scale coactivation data from 5,809 human imaging studies. We (i) identified five distinct striatal zones that exhibited discrete patterns of coactivation with cortical brain regions across distinct psychological processes and (ii) identified the different psychological processes associated with each zone. We found that the reported pattern of cortical activation reliably predicted which striatal zone was most strongly activated. Critically, activation in each functional zone could be associated with distinct psychological processes directly, rather than inferred indirectly from psychological functions attributed to associated cortices. Consistent with well-established findings, we found an association of the ventral striatum (VS) with reward processing. Confirming less well-established findings, the VS and adjacent anterior caudate were associated with evaluating the value of rewards and actions, respectively. Furthermore, our results confirmed a sometimes overlooked specialization of the posterior caudate nucleus for executive functions, often considered the exclusive domain of frontoparietal cortical circuits. Our findings provide a precise functional map of regional specialization within the human striatum, both in terms of the differential cortical regions and psychological functions associated with each striatal zone.
TASSER: A temperature-aware statistical soft-error-rate analysis framework for combinational circuits

Soft error has become one of the most critical reliability issues for nano-scaled CMOS designs. Many previous works discovered that the pulse width due to a particle strike on the device increases with temperature, but its system-level effect has not yet been investigated with statistical soft-error-rate (SER). Therefore, in this paper, a combinational circuit (c17 from ISCAS'85) using a 45nm CMOS technology is f rst observed under different temperatures for SER. As a result, a SER increase (2.16X more) is found on c17 as the ambient temperature elevates from 25°C to 125°C. Second, along with growing design complexity, the operational temperatures of gates are distributed in a wide range and much higher than the ambient temperature in reality. Therefore, we are motivated to build a temperature-aware SSER analysis framework that integrates statistical cell modeling to consider the ambient temperature (Ta) and the temperature variation (Tv), simultaneously. Experimental result shows that our SSER analysis framework is highly eff cient (with multiple-order speed-ups) and accurate (with only <;4% errors), when compared with Monte-Carlo SPICE simulation.
A retrieved context model of the emotional modulation of memory

Emotion enhances episodic memory, an effect thought to be an adaptation to prioritise the memories that best serve evolutionary fitness. But viewing this effect largely in terms of prioritising what to encode or consolidate neglects broader rational considerations about what sorts of associations should be formed at encoding, and which should be retrieved later. Although neurobiological investigations have provided many mechanistic clues about how emotional arousal modulates item memory, these effects have not been wholly integrated with the cognitive and computational neuroscience of memory more generally. Here we apply the Context Maintenance and Retrieval Model (CMR, Polyn, Norman & Kahana, 2009) to this problem by extending it to describe the way people may represent and process emotional information. A number of ways to operationalise the effect of emotion were tested. The winning emotional CMR (eCMR) model reconceptualises emotional memory effects as arising from the modulation of a process by which memories become bound to ever-changing temporal and emotional contexts. eCMR provides a good qualitative fit for the emotional list-composition effect and the emotional oddball effect, illuminating how these effects are jointly determined by the interplay of encoding and retrieval processes. eCMR explains the increased advantage of emotional memories in delayed memory tests through the limited ability of retrieval to reinstate the temporal context of encoding. By leveraging the rich tradition of temporal context models, eCMR helps integrate existing effects of emotion and provides a powerful tool to test mechanisms by which emotion affects memory in a broad range of paradigms.
Hybrid Booleans

In this paper, we present a novel method to compute Boolean operations on polygonal meshes. Given a Boolean expression over an arbitrary number of input meshes we reliably and efficiently compute an output mesh which faithfully preserves the existing sharp features and precisely reconstructs the new features appearing along the intersections of the input meshes. The term “hybrid” applies to our method in two ways: First, our algorithm operates on a hybrid data structure which stores the original input polygons (surface data) in an adaptively refined octree (volume data). By this we combine the robustness of volumetric techniques with the accuracy of surface‐oriented techniques. Second, we generate a new triangulation only in a close vicinity around the intersections of the input meshes and thus preserve as much of the original mesh structure as possible (hybrid mesh). Since the actual processing of the Boolean operation is confined to a very small region around the intersections of the input meshes, we can achieve very high adaptive refinement resolutions and hence very high precision. We demonstrate our method on a number of challenging examples.
Algorithms and Architectures for Low Power Spike Sorting

Front-end integrated circuits for signal processing are useful in neuronal recording systems that engage a large number of electrodes. Detection, alignment, and sorting of the spike data at the frontend reduces the data bandwidth and enables wireless communication. Without such data reduction, large data volumes need to be transferred to a host computer and typically heavy cables are required which constrain the patient or test animal. We explore Neuroprocessor electronic chips for portable applications. The Neuroprocessor can be placed next to the recording electrodes and provide for all stages of spike processing, stimulating neuronal tissues and wireless communication to a host computer. It can dissipate only a limited amount of power, due to supply constraints and heat restrictions. We introduce hardware architectures for automatic spike sorting algorithms in Neuroprocessors, designed for low power. Some of the algorithms are based on principal component analysis. Others employ a novel Integral Transform analysis and achieve 98% of the precision of a PCA sorter, while requiring only 2.5% of the computational complexity. The algorithms execute autonomously, but require off-line training and setting of computational parameters. We employ pre-recorded neuronal signals to evaluate the accuracy of the proposed algorithms and architectures: The recorded data are processed by a standard PCA spike sorting software algorithm, as well as by the several hardware algorithms, and the outcomes are compared.
Measuring Online Service Availability Using Twitter

Real-time micro-blogging services such as Twitter are widely recognized for their social dynamics--how they both encapsulate a social graph and propagate information across it. However, the content of this information is equally interesting since it frequently reflects individual experiences with a broad variety of real-time events. Indeed, events of broad interest are commonly revealed in correlated spikes of semantically-related posting activity. In this paper, we explore one such application this of phenomenon: using Twitter data to infer on-line Internet service availability. We show that simple techniques are sufficient to extract key semantic content from "tweets" (i.e., service X is down) and also filter out extraneous noise. We demonstrate the efficacy of this approach at identifying a range of large-scale service outages in 2009 for popular services such as Gmail, Bing and PayPal.
What you see is what you feel: exploiting the dominance of the visual over the haptic domain to simulate force-feedback with cursor displacements

In this paper, we will present an approach to design a more natural user interface without taking resort to special haptic input/output devices. Tactile sensations like stickiness, touch, or mass can be evoked by applying tiny displacements upon cursor movements. Our active cursor method exploits the domination of the visual over the haptic domain. We will show that interactive animations can be used to simulate the functioning of force-feedback devices. A demo is online at http://www.koert. com/work/activecursor (a shockwave plugin is required).
Reconfigurable processor for deep learning in autonomous vehicles

The rapid growth of civilian vehicles has stimulated the development of advanced driver assistance systems (ADASs) to be equipped in-car. Real-time autonomous vision (RTAV) is an essential part of the overall system, and the emergence of deep learning methods has greatly improved the system quality, which also requires the processor to offer a computing speed of tera operations per second (TOPS) and a power consumption of no more than 30 W with programmability. This article gives an overview of the trends of RTAV algorithms and different hardware solutions, and proposes a development route for the reconfigurable RTAV accelerator. We propose our field programmable gate array (FPGA) based system Aristotle, together with an all-stack software-hardware co design workflow including compression, compilation, and customized hardware architecture. Evaluation shows that our FPGA system can realize real-time processing on modern RTAV algorithms with a higher efficiency than peer CPU and GPU platforms. Our outlook based on the ASIC-based system design and the ongoing implementation of next generation memory would target a 100 TOPS performance with around 20 W power.
GRAPHENE-BASED TRANSPARENT CONDUCTIVE FILMS

Graphene is a promising alternative to indium tin oxide for use in transparent conducting electrodes. We review recent progress in production methods of graphene and its applications in optoelectronic devices such as touch panel screens, organic photovoltaic cells, organic light emitting diodes and thin film transistors. In addition, we discuss important criteria such as optical transmittance, electrical conductivity and work function, which are critical considerations in the integration of graphene conductive films with optoelectronic devices.
Persistence of heavy drinking and ensuing consequences at heavy drinking colleges.

OBJECTIVE The purpose of this study was to examine drinking levels, related harms, and secondhand effects of alcohol use at heavy drinking colleges between 1993 and 2005 at colleges with high levels of drinking in 1993. METHOD Students attending 18 colleges with high levels of heavy episodic drinking (50% of students or more) from the 1993 Harvard School of Public Health College Alcohol Study were surveyed in 2005 (n = 4,518). Data collected through mailed and Web-based questionnaires were compared with responses from students at the same schools in 1993, 1997, 1999, and 2001 (N = 13,254) using time trend analyses. RESULTS Overall, levels of alcohol consumption, experience of problems, and levels of secondhand effects remained high among students attending heavy drinking colleges. More than four of five students at these schools drank alcohol (range: 85%-88%), and more than half engaged in heavy episodic drinking (range: 53%-58%). The stability of drinking behavior occurred among subgroups of students as well. The few statistically significant changes occurred mainly between 1993 and 1997. A decline in driving after any drinking between 1997 and 2005 was observed, but no similar decline was found in two other measures of drinking and driving. CONCLUSIONS Heavy drinking and associated problems continue unabated, with few exceptions, at colleges that are most in need of intervention: those with high levels of heavy episodic drinking. Addressing student alcohol use at heavy drinking colleges may require stronger, more consistent, and more comprehensive approaches, with increased emphasis on the alcohol environment.
Influence of Bilirubin on Human Platelets

Extract: Studies were performed which showed that unbound unconjugated bilirubin at low concentration (0.5 mg/100 ml) causes yellow staining and aggregation of washed human platelets, whereas bilirubin bound to albumin and bilirubin altered by exposure to light have little, if any, of these effects on platelets. Less intense aggregation occurred in some but not all samples of platelet-rich plasma incubated with bilirubin and only at bilirubin levels of 10 mg/100 ml or higher. Aggregation of platelets by bilirubin showed an absolute requirement for calcium ions and this response was enhanced by potassium ions. Adenosine diphosphate and adenosine triphosphate were released from platelets with bilirubin.Speculation: In the early accounts of human kernicterus, and in studies of experimental hyperbilirubinemia in animals, hemorrhagic complications were well known but poorly understood. The data presented suggest that bilirubin influences platelet function. It is tempting to speculate that the effect of bilirubin on platelets could play a role in producing intravascular thrombosis or hemorrhage, or both, in severe hyperbilirubinemia.
Ecophenotypic Variation and Developmental Instability in the Late Cretaceous Echinoid Micraster brevis (Irregularia; Spatangoida)

The Late Cretaceous echinoid genus Micraster (irregular echinoids, Spatangoida) is one of the most famous examples of a continuous evolutionary lineage in invertebrate palaeontology. The influence of the environment on the phenotype, however, was not tested so far. This study analyses differences in phenotypical variations within three populations of Micraster (Gibbaster) brevis from the early Coniacian, two from the Münsterland Cretaceous Basin (Germany) and one from the North Cantabrian Basin (Spain). The environments of the Spanish and the German sites differed by their sedimentary characteristics, which are generally a crucial factor for morphological adaptations in echinoids. Most of the major phenotypical variations (position of the ambitus, periproct and development of the subanal fasciole) among the populations can be linked to differences in their host sediments. These phenotypic variations are presumed to be an expression of phenotpic plasticiy, which has not been considered in Micraster in previous studies. Two populations (Erwitte area, Germany; Liencres area, Spain) were tested for stochastic variation (fluctuating asymmetry) due to developmental instability, which was present in all studied traits. However, differences in the amount of fluctuating asymmetry between both populations were recognised only in one trait (amount of pore pairs in the anterior paired petals). The results strengthen previous assumptions on ecophenotypic variations in Micraster.
Examination of worldwide hardwood lumber production, trade, and apparent consumption: 1995-2013

Worldwide hardwood lumber production fluctuated between 1995 and 2013 and changed considerably with respect to regional market shares. Similarly, worldwide hardwood lumber imports and exports have been constantly changing. Understanding these changes is important because collectively, they define the hardwood lumber consumption of a region or country. In 1995, North America accounted for 25% of worldwide hardwood lumber production whereas East Asia and Oceana (EAO) produced 26%. In the current century, a decline in production in the United States and increased production in China and Vietnam resulted in the EAO region accounting for more than 48% of worldwide hardwood lumber production in 2013. Much of the international trade of hardwood lumber is carried out by EAO and European countries and is intraregional among countries within these regions. Hardwood lumber consumption generally has been moderately to poorly correlated with population at the country level since 1995 and uncorrelated with gross domestic product. However, several other factors also appear to affect current consumption including loss or gain of secondary hardwood industries, age of the population, urbanization, and in recent years, slow economic growth in countries with high per capita gross national product.
Robust state feedback control for discrete-time linear systems via LMIs with a scalar parameter

This paper proposes an improved approach to ℋ2 and ℋ∞ robust state feedback control design for discrete-time polytopic time-invariant linear systems based on Linear Matrix Inequalities (LMIs) with a scalar parameter. The synthesis conditions, that depend on a real parameter lying in the interval (-1,1), become LMIs for fixed values of the scalar, reducing to standard conditions in the literature when the scalar is equal to zero. At the price of line searches combined with LMIs, less conservative results for robust state feedback control are obtained. The closed-loop stability and the ℋ2 and ℋ∞ guaranteed costs are certified by means of an affine parameter-dependent Lyapunov function. The validity and the efficiency of the method are illustrated by means of examples and exhaustive numerical comparisons.
Shape Registration with Spherical Cross Correlation

We present a framework for shape alignment that generalizes several existing methods.We assume that the shape is a closed genus zero surface. Our framework requires a diffeomorphic surface mapping to the 2-sphere which preserves rotation. Our similarity measure is a global spherical cross-correlation function of surface-intrinsic scalar attributes, weighted by the cross-correlation of the parameterization distortion. The final similarity measure may be customized according to the surface- intrinsic scalar functions used in the application.
A novel experimental paradigm to evaluate children and adolescents diagnosed with attention-deficit/hyperactivity disorder: Comparison with two standard neuropsychological methods

ABSTRACT Introduction: In this study we evaluated a recently developed test, the Ball Search Field Task (BSFT) as a neuropsychological tool for measuring cognitive and behavioral performance of individuals with disorders such as attention-deficit/hyperactivity disorder (ADHD), which are frequently accompanied by cognitive deficits and a lack of behavioral inhibition. The task provides a complementary method of assessment that attempts ecological validity by drawing on challenges faced in real-world situations. In this task, energetic costs and gross sensorimotor feedback are involved, as participants are required to search for targets in a large open area. Method: We compared performance on the BSFT in a clinical sample of children and adolescents with a diagnosis of ADHD with their scores on two widely used neuropsychological tools, the Tower of London (ToLo) and the Behavior Rating Inventory of Executive Function (BRIEF). Results: We found no correlations between scores on the BRIEF and those on either the BSFT or ToLo. However, we found moderate correlations between rule violations on ToLo and several BSFT variables, suggesting the capacity of these tests to detect common aspects of executive dysfunction. Conclusions: These findings, although modest, encourage further study of tasks like the BSFT, which may help assess cognitive dysfunction found in neurodevelopmental disorders such as ADHD in ecologically valid situations.
Inferring Semantic Information from Natural-Language Software Artifacts

Code-level specifications play an important role in softwar e engineering. In addition to guiding the development process by outlining what/how to reuse, specifications also help in verification process by allowing quality assurance practitioners to test the expected outcome. One of the valua ble source of such specifications are the Natural language API documents. However, sometimes humans often overlook th ese documents and build software systems that are inconsistent with specifications described in those docume nts. While there are tools and frameworks available to assis t humans to build/reuse quality software, these tools are not designed to work on specifications in natural language. To address this issue, this report presents a Natural Langua ge Processing (NLP) framework to automate the task of inferring semantic information from natural language soft ware artifacts to bridge the disconnect between the inputs required by software engineering tools/frameworks and the specifications described in natural language. This report is a part of a larger dissertation goal to improve developer / tester / end-user productivity by aut omatically inferring semantic information from the textual descriptions in soft ware artifacts. Specifically, in this report I present two recent research efforts that I have conducted in developing/apply ing NLP techniques for inferring semantics from natural language software artifacts. Furthermore, I also outline m y dissertation plan along with intermediate deliverables t o achieve my goal.
TGF-β1 Down-Regulation of NKG2D/DAP10 and 2B4/SAP Expression on Human NK Cells Contributes to HBV Persistence

The mechanism underlying persistent hepatitis B virus (HBV) infection remains unclear. We investigated the role of innate immune responses to persistent HBV infection in 154 HBV-infected patients and 95 healthy controls. The expression of NKG2D- and 2B4-activating receptors on NK cells was significantly decreased, and moreover, the expression of DAP10 and SAP, the intracellular adaptor proteins of NKG2D and 2B4 (respectively), were lower, which then impaired NK cell-mediated cytotoxic capacity and interferon-γ production. Higher concentrations of transforming growth factor-beta 1 (TGF-β1) were found in sera from persistently infected HBV patients. TGF-β1 down-regulated the expression of NKG2D and 2B4 on NK cells in our in vitro study, leading to an impairment of their effector functions. Anti-TGF-β1 antibodies could restore the expression of NKG2D and 2B4 on NK cells in vitro. Furthermore, TGF-β1 induced cell-cycle arrest in NK cells by up-regulating the expression of p15 and p21 in NK cells from immunotolerant (IT) patients. We conclude that TGF-β1 may reduce the expression of NKG2D/DAP10 and 2B4/SAP, and those IT patients who are deficient in these double-activating signals have impaired NK cell function, which is correlated with persistent HBV infection.