Miracle-dz/UniFAR-FTUs huggingface dataset:
Supplemental Information

Supplementary Methods and Materials Psychophysiological Interaction Analysis The connectivity analysis was designed to assess whether the lateral frontal regions identified in the main analysis were influencing attention to the faces as reflected in visual sensory association cortex activity (1). This was achieved using psychophysiological interaction (PPI) analyses (2) to examine the pattern of correlation between activity in the lateral PFC (lPFC) clusters and face selective visual sensory cortex (see below for description of the localizer analysis used to identify face selective cortex). Separate analyses were used for the right and left lPFC clusters. In both of these analyses three regressors were included: the timeseries of the peak voxel from the lateral frontal cluster of the participant’s fMRI data (the “physiological” regressor), a regressor coding for whether each block of 20 trials was attended or unattended (the “psychological” regressor) and a final regressor reflecting the interaction of the two (the “interaction” regressor). The interaction regressor provides a measure of how the correlation between activity in the lPFC and sensory cortex differs when attention is directed towards or away from the faces. The mean value of this interaction regressor was extracted from each participant’s left and right fusiform masks, for both PPI analyses, resulting in four data points per participant.
Converting 3D furniture models to fabricatable parts and connectors

Although there is an abundance of 3D models available, most of them exist only in virtual simulation and are not immediately usable as physical objects in the real world. We solve the problem of taking as input a 3D model of a man-made object, and automatically generating the parts and connectors needed to build the corresponding physical object. We focus on furniture models, and we define formal grammars for IKEA cabinets and tables. We perform lexical analysis to identify the primitive parts of the 3D model. Structural analysis then gives structural information to these parts, and generates the connectors (i.e. nails, screws) needed to attach the parts together. We demonstrate our approach with arbitrary 3D models of cabinets and tables available online.
Low Temperature Plasma Causes Double-Strand Break DNA Damage in Primary Epithelial Cells Cultured From a Human Prostate Tumor

Research in the new field of plasma medicine continues to demonstrate the efficacy of low temperature plasmas (LTPs) for numerous biomedical applications. Responses such as reduction in cell viability and cell death for cancer therapy, cell proliferation for wound healing, and bacterial inactivation have been observed as a result of plasma treatment. In this paper, we applied LTP to prostate cancer primary cells derived from patient tumour tissue to inflict irreparable DNA damage.
Detecting environmental disasters in digital news archives

Automatically extracting events from large, unstructured/semi-structured textual data requires a mechanism for identifying the event, abstracting it from the text, validating the event's occurrence against some known values, and sharing the event with users effectively. Inherent in the challenge of Big Data is that it often exceeds a scale at which humans can effectively operate. In this paper, we focus on the domain of archived newspaper articles, and describe a system that generates a collection of event summaries from unstructured text, extracts a geographic marker for the event, and stores both in an on-line database that can be searched and/or visualized using an interactive map. The system relies on text mining techniques to filter out a dataset of news stories from a digital news archive source and extracts 1-2 sentences from each event to be stored in the database. We illustrate this approach using a flood database case study, automatically extracting descriptions of past flooding events occurring in Nova Scotia, Canada from a 20-year archive of regional newspaper articles. We validate our event extraction in two dimensions (identification of articles mentioning flood events; identification of accurate geographic markers from articles about flood events) using Amazon's Mechanical Turk (MTurk) to obtain human assessments at scale.
The benefits of event: driven energy accounting in power-sensitive systems

A prerequisite of energy-aware scheduling is precise knowledge of any activity inside the computer system. Embedded hardware monitors (e.g., processor performance counters) have proved to offer valuable information in the field of performance analysis. The same approach can be applied to investigate the energy usage patterns of individual threads. We use information about active hardware units (e.g., integer/floating-point unit, cache/memory interface) gathered by event counters to establish a thread-specific energy accounting. The evaluation shows that the correlation of events and energy values provides the necessary information for energy-aware scheduling policies.Our approach to OS-directed power management adds the energy usage pattern to the runtime context of a thread. Depending on the field of application we present two scenarios that benefit from applying energy usage patterns: Workstations with passive cooling on the one hand and battery-powered mobile systems on the other hand.Energy-aware scheduling evaluates the energy usage of each thread and throttles the system activity so that the scheduling goal is achieved. In workstations we throttle the system if the average energy use exceeds a predefined power-dissipation capacity. This makes a compact, noiseless and affordable system design possible that meets sporadic yet high demands in computing power. Nowadays, more and more mobile systems offer the features of reducible clock speed and dynamic voltage scaling. Energy-aware scheduling can employ these features to yield a longer battery life by slowing down low-priority threads while preserving a certain quality of service.
ℓ1 Adaptive trend filter via fast coordinate descent

Identifying the unknown underlying trend of a given noisy signal is extremely useful for a wide range of applications. The number of potential trends might be exponential, thus their search can be computationally intractable even for short signals. Another challenge is the presence of abrupt changes and outliers at unknown times which impart resourceful information regarding the signal's characteristics. In this paper, we present the ℓ1 Adaptive Trend Filter, which can consistently identify the components in the underlying trend and multiple level-shifts, even in the presence of outliers. Additionally, an enhanced coordinate descent algorithm which exploits the filter design is presented. Some implementation details are discussed and a version in the Julia language is presented along with two distinct applications to illustrate the filter's potential.
Symbolic semantic rules for producing compact STGLAs from value passing process descriptions

Value passing process algebras with infinite data domains need to be equipped with symbolic semantic models in order for their analysis to be possible. This means that appropriate symbolic models and the related verification algorithms must be developed, together with suitable semantic rules mapping the value passing process descriptions to such symbolic models. In this article, we first introduce the model of the symbolic transition graphs with lookahead assignment (STGLAs), a variant of the symbolic transition graphs with assignment (STGAs) of Lin that can undergo to the strong, weak and observational bisimulation equivalence checking algorithms of Li and Chen. We then define a set of symbolic semantic rules that map a useful fragment of value passing CCS to finite STGLAs without making any assumption about the variable names. We demonstrate that the symbolic semantic rules are correct with respect to both the usual concrete semantic rules and the novel issue of the assignment application order. Finally, we prove that, for the considered fragment of value passing CCS, the STGLAs produced by the symbolic semantic rules are optimal with respect to a certain compactness criterion, thus improving on the symbolic models and the semantic rules previously proposed in the literature.
Expression Recognition Based on BP Neural Network

The way computers interact with humans is changing with the continuous development of computer technology in the field of affective computing. A human facial expression is the formation of facial muscle movement. In our previous research, we had proposed a method of identifying facial muscle movement which based on motion templates and Gentle Boost. But the method was not robust enough to recognize human expression. So in this paper, we present an approach to solve the problem. The approach is based on our previous work and BP neural network. Tests in our laboratory have been conducted and the results have proved that the method presented in this paper can solve the problem encountered in our previous research.
Regulation of T‐cell receptor signalling by membrane microdomains

There is now considerable evidence suggesting that the plasma membrane of mammalian cells is compartmentalized by functional lipid raft microdomains. These structures are assemblies of specialized lipids and proteins and have been implicated in diverse biological functions. Analysis of their protein content using proteomics and other methods revealed enrichment of signalling proteins, suggesting a role for these domains in intracellular signalling. In T lymphocytes, structure/function experiments and complementary pharmacological studies have shown that raft microdomains control the localization and function of proteins which are components of signalling pathways regulated by the T‐cell antigen receptor (TCR). Based on these studies, a model for TCR phosphorylation in lipid rafts is presented. However, despite substantial progress in the field, critical questions remain. For example, it is unclear if membrane rafts represent a homogeneous population and if their structure is modified upon TCR stimulation. In the future, proteomics and the parallel development of complementary analytical methods will undoubtedly contribute in further delineating the role of lipid rafts in signal transduction mechanisms.
Integration of GSM technology with IPv 6 Architecture

Consumers are demanding world-wide cellular access to the internet. This requires a global standard and effective means of accessing the internet from wireless devices . Integrating the two successful domains, viz, cellular networks and the Internet, provide anytime, anywhere access in third generation (3G) cellular networks. In this paper a hierarchical architecture for integration of cellular network (GSM) and Mobile IPv6 as mobility management is proposed. GSM is the most widely used cellular network and Mobile IP allows transparent routing of IP datagram in the Internet to the Mobile node irrespective of its physical location. Mobile IP provides an elegant solution for inter-domain, or macro-mobility management, but does not perform well for micro-mobility or intra-domain management. The transition of IPv4 to IPv6 is studied and its improvements are incorporated in the proposed architecture. The proposed hierarchical architecture improves the performance of Mobile IP in GSM networks in terms of fast intra-domain hand-offs.
Modeling parameterized geometry in GPU-based Monte Carlo particle transport simulation for radiotherapy

Monte Carlo (MC) particle transport simulation on a graphics-processing unit (GPU) platform has been extensively studied recently due to the efficiency advantage achieved via massive parallelization. Almost all of the existing GPU-based MC packages were developed for voxelized geometry. This limited application scope of these packages. The purpose of this paper is to develop a module to model parametric geometry and integrate it in GPU-based MC simulations. In our module, each continuous region was defined by its bounding surfaces that were parameterized by quadratic functions. Particle navigation functions in this geometry were developed. The module was incorporated to two previously developed GPU-based MC packages and was tested in two example problems: (1) low energy photon transport simulation in a brachytherapy case with a shielded cylinder applicator and (2) MeV coupled photon/electron transport simulation in a phantom containing several inserts of different shapes. In both cases, the calculated dose distributions agreed well with those calculated in the corresponding voxelized geometry. The averaged dose differences were 1.03% and 0.29%, respectively. We also used the developed package to perform simulations of a Varian VS 2000 brachytherapy source and generated a phase-space file. The computation time under the parameterized geometry depended on the memory location storing the geometry data. When the data was stored in GPU’s shared memory, the highest computational speed was achieved. Incorporation of parameterized geometry yielded a computation time that was ~3 times of that in the corresponding voxelized geometry. We also developed a strategy to use an auxiliary index array to reduce frequency of geometry calculations and hence improve efficiency. With this strategy, the computational time ranged in 1.75–2.03 times of the voxelized geometry for coupled photon/electron transport depending on the voxel dimension of the auxiliary index array, and in 0.69–1.23 times for photon only transport.
A 1-V 1-Mb SRAM for portable equipment

Low-power and high-speed circuit techniques are described for 1-V battery operated SRAMs. A design concept is shown that uses two kinds of MOSFETs different in threshold voltages to reduce power dissipation due to the subthreshold leakage current in both standby and active modes. We propose a step-down boosted word-line scheme to reduce power dissipation in the memory array to 57% while accelerating the sensing speed. A novel bidirectional differential internal-bus architecture provides data transmission that is 45% faster than in the conventional architecture, yet without area or power penalty. A charge-recycling I/O buffer incorporating a data transition detector reduces the power dissipation of the I/O buffer by 30%. A 1-Mb SRAM designed using these techniques and 0.5-/spl mu/m CMOS technology demonstrated 4.8-mW power dissipation and a 75-ns address access time with standby power of 1.2-/spl mu/W at a 1-V power supply.
Teacher Perspectives on the Potential for Scaffolding with an Open Learner Model and a Robotic Tutor

This paper considers the potential for scaffolding learning in openended learning environments using a robotic tutor and an open learner model. While we expect this approach to be more broadly applicable, we here illustrate with a map-reading activity in geography and/or environmental sciences. The paper presents issues raised in open-ended teacher interviews, which suggest real possibilities for incorporating a robotic tutor together with an open learner model in the classroom.
Way prediction set-associative data cache for low power digital signal processors

In digital signal processors, set-associative caches achieve low miss rates for typical applications but result in significant power consumption. Set-associative caches decrease access time by probing all the data ways in parallel with the tag lookup, although the output of only the matching way is used. The power spent access the other ways is wasted. Eliminating the power consumption by performing the data lookup following the tag comparison definitely increase cache access time, and is unacceptable for high performance level 1 caches. In this paper we propose a way prediction method to reducing set-associative data cache dynamic power while maintaining high performance. This method predicts the matching way and only probes the predicted way, achieving power savings. We evaluate the effectiveness of this method in reducing level 1 data cache power consumption and the simulation results show that this proposed technique achieves a power reduction of up to 18.97% and 14.70% on average, respectively, with negligible area overheads.
A certifying compiler for Java

This paper presents the initial results of a project to determine ifthe techniques of proof-carrying code and certifying compilers can be applied to programming languages of realistic size and complexity. The experiment shows that: (1) it is possible to implement a certifying native-code compiler for a large subset of the Java programming language; (2) the compiler is freely able to apply many standard local and global optimizations; and (3) the PCC binaries it produces are of reasonable size and can be rapidly checked for type safety by a small proof-checker. This paper also presents further evidence that PCC provides several advantages for compiler development. In particular, generating proofs of the target code helps to identify compiler bugs, many of which would have been difficult to discover by testing.
Restricted Poly-Time SAT-Solvable CNF’s

—This article, from an algorithmic point of view, studies the satisﬁability problem SAT restricted to a CNF fraction MHF whose members consist of a Horn formula and a 2-CNF part. In general SAT is NP-complete for such formulas. We consider various structurally deﬁned subclasses of MHF, for which SAT can be solved in polynomial time. The instances deﬁned here are required to have a linear, or even exact-linear Horn part. Moreover, the 2-CNF part is required to be of speciﬁc graph structure, e.g., disjoint edges or disjoint triangles. Further poly-time classes are presented, for which the Horn part is not forced to be linear.
Perinasal Imaging of Physiological Stress and Its Affective Potential

In this paper, we present a novel framework for quantifying physiological stress at a distance via thermal imaging. The method captures stress-induced neurophysiological responses on the perinasal area that manifest as transient perspiration. We have developed two algorithms to extract the perspiratory signals from the thermophysiological imagery. One is based on morphology and is computationally efficient, while the other is based on spatial isotropic wavelets and is flexible; both require the support of a reliable facial tracker. We validated the two algorithms against the clinical standard in a controlled lab experiment where orienting responses were invoked on n=18 subjects via auditory stimuli. Then, we used the validated algorithms to quantify stress of surgeons (n=24) as they were performing suturing drills during inanimate laparoscopic training. This is a field application where the new methodology shines. It allows nonobtrusive monitoring of individuals who are naturally challenged with a task that is localized in space and requires directional attention. Both algorithms associate high stress levels with novice surgeons, while low stress levels are associated with experienced surgeons, raising the possibility for an affective measure (stress) to assist in efficacy determination. It is a clear indication of the methodology's promise and potential.
Good Practices for Adaptive Clinical Trials in Pharmaceutical Product Development

This article is a summary of good adaptive practices for the planning and implementation of adaptive designs compiled from experiences gained in the pharmaceutical industry. The target audience is anyone involved in the planning and execution of clinical trials. The first step prior to planning an adaptive design is to assess the appropriateness of its use. Hence, strategic points to consider when assessing if an adaptive design is the right choice for a trial are discussed. In addition, strategic points for consideration at the design and implementation stage are included from operational, regulatory, clinical, and statistical perspectives. Good practices for trial simulation, trial documentation, and data monitoring committees are provided.
Linear support vector machines via dual cached loops

Modern computer hardware offers an elaborate hierarchy of storage subsystems with different speeds, capacities, and costs associated with them. Furthermore, processors are now inherently parallel offering the execution of several diverse threads simultaneously. This paper proposes StreamSVM, the first algorithm for training linear Support Vector Machines (SVMs) which takes advantage of these properties by integrating caching with optimization. StreamSVM works by performing updates in the dual, thus obviating the need to rebalance frequently visited examples. Furthermore we trade off file I/O with data expansion on the fly by generating features on demand. This significantly increases throughput. Experiments show that StreamSVM outperforms other linear SVM solvers, including the award winning work of [38], by orders of magnitude and produces more accurate solutions within a shorter amount of time.
Electrophysiological and clinical evaluation of the effects of transcutaneous electrical nerve stimulation on the spasticity in the hemiplegic stroke patients

To investigate whether transcutaneous electrical nerve stimulation (TENS) mitigates the spasticity of hemiplegic stroke patients, as assessed by electrophysiological variables, and the effects, if any, on the clinical appearance of spasticity. [Subjects and Methods] Twenty-seven subjects who had acute hemiplegia and 24 healthy people as the control group, were enrolled in this study. Some of the acute cerebrovascular disease patients could walk. Subjects who did not have spasticity, who were taking antispasticity medicine, or had a previous episode of cerebrovascular disease were excluded. The walking speed of the patients was recorded before and after TENS. EMG examinations were performed on the healthy controls and in the affected side of the patients. A 30-minute single session of TENS was applied to lower extremity. At 10 minutes after TENS, the EMG examinations were repeated. [Results] A statistically significant decrease in the spasticity variables, and increased walking speed were found post-TENS. The lower M amplitude and higher H reflex amplitude, H/M maximum amplitude ratio, H slope, and H slope/M slope ratio on the spastic side were found to be statistically significant. [Conclusion] TENS application for hemiplegic patients with spastic lower extremities due to cerebrovascular disease resulted in marked improvement in clinical scales of spasticity and significant changes in the electrophysiological variables.
Multi-image Semantic Matching by Mining Consistent Features

This work proposes a multi-image matching method to estimate semantic correspondences across multiple images. In contrast to the previous methods that optimize all pairwise correspondences, the proposed method identifies and matches only a sparse set of reliable features in the image collection. In this way, the proposed method is able to prune nonrepeatable features and also highly scalable to handle thousands of images. We additionally propose a low-rank constraint to ensure the geometric consistency of feature correspondences over the whole image collection. Besides the competitive performance on multi-graph matching and semantic flow benchmarks, we also demonstrate the applicability of the proposed method for reconstructing object-class models and discovering object-class landmarks from images without using any annotation.