Miracle-dz/UniFAR-FTUs huggingface dataset:
Motion graphs++

This paper introduces a new generative statistical model that allows for human motion analysis and synthesis at both semantic and kinematic levels. Our key idea is to decouple complex variations of human movements into finite structural variations and continuous style variations and encode them with a concatenation of morphable functional models. This allows us to model not only a rich repertoire of behaviors but also an infinite number of style variations within the same action. Our models are appealing for motion analysis and synthesis because they are highly structured, contact aware, and semantic embedding. We have constructed a compact generative motion model from a huge and heterogeneous motion database (about two hours mocap data and more than 15 different actions). We have demonstrated the power and effectiveness of our models by exploring a wide variety of applications, ranging from automatic motion segmentation, recognition, and annotation, and online/offline motion synthesis at both kinematics and behavior levels to semantic motion editing. We show the superiority of our model by comparing it with alternative methods.
Moderating Effects of Cortisol on Neural-Cognitive Association in Cognitively Normal Elderly Subjects

Cortisol homeostasis is important for healthy brain and cognitive aging. The aim of the current study is to investigate the role of serum cortisol levels in the relationship between regional brain volumes and cognitive processing speed in a group of cognitively normal elderly subjects. Forty-one healthy elderly participants were from a parallel longitudinal study. The reported data in this study reflects baseline measurements. Whole-brain anatomical scanning was performed using a 3.0 Tesla Philips Medical Systems Achieva scanner. Cognitive processing speed was assessed by the digit-symbol and symbol search tests, from the Chinese version of the Wechsler Adult Intelligence Scale—third edition (WAIS-III). Serum cortisol levels (sampled in the late morning) were measured by ELISA kits. Whole-brain regression analysis revealed that serum cortisol levels positively predicted the white matter volumes (WMV) of the right thalamus, the gray matter volumes (GMV) of the left thalamus and right cerebellar tonsil, and negatively predicted the WMV and GMV of the left middle temporal gyrus (MTG) in 41 healthy elderly participants. Furthermore, serum cortisol significantly moderated the relationship between the GMV of the left MTG and processing speed, as well as the GMV of the left thalamus and processing speed. This study provided the first piece of evidence supporting serum cortisol levels in moderating the relationship between regional brain volumes and processing speed in healthy elderly subjects. This observation enriches our understanding of the role of cortisol in brain morphology and cognitive functioning.
High precision touch screen interaction

Bare hand pointing on touch screens both benefits and suffers from the nature of direct input. This work explores techniques to overcome its limitations. Our goal is to design interaction tools allowing pixel level pointing in a fast and efficient manner. Based on several cycles of iterative design and testing, we propose two techniques: Cross-Keys that uses discrete taps on virtual keys integrated with a crosshair cursor, and an analog Precision-Handle that uses a leverage (gain) effect to amplify movement precision from the user's finger tip to the end cursor. We conducted a formal experiment with these two techniques, in addition to the previously known Zoom-Pointing and Take-Off as baseline anchors. Both subjective and performance measurements indicate that Precision-Handle and Cross-Keys complement existing techniques for touch screen interaction.
Training deep neural-networks based on unreliable labels

In this study we address the problem of training a neural network based on data with unreliable labels. We introduce an extra noise layer by assuming that the observed labels were created from the true labels by passing through a noisy channel whose parameters are unknown. We propose a method that simultaneously learns both the neural network parameters and the noise distribution. The proposed method is compared to standard back-propagation neural-network training that ignores the existence of wrong labels. The improved classification performance of the method is illustrated on several standard classification tasks. In particular we show that in some cases our approach can be beneficial even when the labels are set manually and assumed to be error-free.
Role of the Toll-like Receptor 4/NF-&kgr;B Pathway in Saturated Fatty Acid–Induced Inflammatory Changes in the Interaction Between Adipocytes and Macrophages

Objective—Previous studies demonstrated that obese adipose tissue is characterized by increased infiltration of macrophages, suggesting that they might represent an important source of inflammation. Using an in vitro coculture system composed of 3T3-L1 adipocytes and RAW264 macrophages, we previously demonstrated that saturated fatty acids (FAs) and tumor necrosis factor (TNF)-α derived from adipocytes and macrophages, respectively, play a major role in the coculture-induced inflammatory changes. Methods and Results—Coculture of adipocytes and macrophages resulted in the activation of nuclear factor-&kgr;B (NF-&kgr;B), a primary regulator of inflammatory responses, in both cell types. Pharmacological inhibition of NF-&kgr;B markedly suppressed the coculture-induced production of proinflammatory cytokines and adipocyte lipolysis. Peritoneal macrophages obtained from Toll-like receptor 4 (TLR4) mutant mice exhibited marked attenuation of TNFα production in response to saturated FAs. Notably, coculture of hypertrophied adipocytes and TLR4-mutant macrophages resulted in marked inhibition of proinflammatory cytokine production and adipocyte lipolysis. We also observed that endogenous FAs, which are released from adipocytes via the β3-adrenergic stimulation, resulted in the activation of the TLR4/NF-&kgr;B pathway. Conclusion—These findings suggest that saturated FAs, which are released in large quantities from hypertrophied adipocytes via the macrophage-induced adipocyte lipolysis, serve as a naturally occurring ligand for TLR4, thereby inducing the inflammatory changes in both adipocytes and macrophages through NF-&kgr;B activation.
Assessing Physician Competency: An Update on the Joint Commission Requirement for Ongoing and Focused Professional Practice Evaluation

In 2008, the Joint Commission created 2 new hospital standards that revolve around competency assessment of credentialed and privileged healthcare practitioners. These are called Ongoing Professional Practice Evaluation (OPPE) and Focused Professional Practice Evaluation (FPPE). As many pathologists work as members of a hospital medical staff, either through primary employment or contract relationships, pathology departments and groups need to have OPPE and FPPE policies in place and should be using them to evaluate physicians for competency as part of a regular cycle. There are many subtleties in the standards, and careful attention to the details of the policies will be essential. Furthermore, as credentialing and privileging decisions may be made based upon the assessments that are carried out in OPPE and FPPE, it is quite important to follow internal policies consistently. This review describes OPPE and FPPE in detail, with an analysis of the Standards and the Elements of Performance. It also provides scenarios to illustrate the concepts and charts that can be used to create OPPE and FPPE documents for a practice.
Interpolating Conditional Density Trees

Joint distributions over many variables are frequently modeled by decomposing them into products of simpler, lower-dimensional conditional distributions, such as in sparsely connected Bayesian networks. However, automatically learning such models can be very computationally expensive when there are many datapoints and many continuous variables with complex nonlinear relationships, particularly when no good ways of decomposing the joint distribution are known a priori. In such situations, previous research has generally focused on the use of discretization techniques in which each continuous variable has a single discretization that is used throughout the entire network. \ In this paper, we present and compare a wide variety of tree-based algorithms for learning and evaluating conditional density estimates over continuous variables. These trees can be thought of as discretizations that vary according to the particular interactions being modeled; however, the density within a given leaf of the tree need not be assumed constant, and we show that such nonuniform leaf densities lead to more accurate density estimation. We have developed Bayesian network structure-learning algorithms that employ these tree-based conditional density representations, and we show that they can be used to practically learn complex joint probability models over dozens of continuous variables from thousands of datapoints. We focus on finding models that are simultaneously accurate, fast to learn, and fast to evaluate once they are learned.
Die Entwicklung und Validierung eines evidenzbasierten Kompetenzmodells effektiver Führung (LEaD: Leadership Effectiveness and Development)

Die Entwicklung von Fuhrungskraften und die dazu erforderliche Diagnostik von Fuhrungskompetenzen stellen zentrale Inhalte jeder HR-Strategie dar. Viele Unternehmen greifen dabei insbesondere in der Diagnostik auf selbst entwickelte Instrumente zuruck, ohne die Vielfalt praxisrelevanter Erkenntnisse der Fuhrungsforschung zu berucksichtigen. Mit dem LEaD-Kompetenzmodell wurde im deutschen Raum einer der ersten Versuche unternommen, den Ansatz des evidenzbasierten Managements auf die Entwicklung eines praxisrelevanten Kompetenzmodells fur Fuhrungsaufgaben anzuwenden. Dieser Beitrag beschreibt den Prozess der theoretischen Herleitung und inhaltlichen iterativen Konzeption, skizziert die Inhalte des Kompetenzmodells und berichtet zentrale Ergebnisse der empirischen Studien (Interviewstudie, Prototypizitatsstudie, Pretest und Validierungsstudie). Die Ergebnisse der Validierungsstudie (N = 720) zur Konstrukt- und Kriteriumsvalidierung und inkrementellen Validitat zeigen, dass das theoriebasierte Kompetenzmodell.
Youth perceptions of suicide and help-seeking: ‘They'd think I was weak or “mental”’

Youth suicide is an issue of international concern and the college population may have a considerably higher rate of suicidal behaviour than the general population, yet seeking help for suicidality is uncommon. This research sought to understand college students' knowledge of suicidal behaviour and attitudes to help-seeking, in a New Zealand university. A mixed-method approach comprising a survey and interviews was utilised. Approximately one-fifth of participants had been suicidal, were aware of another student's suicide and/or had supported a suicidal student. Some participants expressed willingness to seek help for another, but far fewer were willing to seek help for themselves. Key reasons for the latter include stigma and a perceived need for self-reliance. Participants expressed greater willingness to seek help for another if they were not a close friend.
Planning and Moving in Dynamic Environments A Statistical Machine Learning Approach

In this chapter, we develop a new view on problems of movement control and planning from a Machine Learning perspective. In this view, decision making, control, and planning are all considered as an inference or (alternately) an information processing problem, i.e., a problem of computing a posterior distribution over unknown variables conditioned on the available information (targets, goals, constraints). Further, problems of adaptation and learning are formulated as statistical learning problems to model the dependencies between variables. This approach naturally extends to cases when information is missing, e.g., when the context or load needs to be inferred from interaction; or to the case of apprentice learning where, crucially, latent properties of the observed behavior are learnt rather than the motion copied directly. With this account, we hope to address the long-standing problem of designing adaptive control and planning systems that can flexibly be coupled to multiple sources of information (be they of purely sensory nature or higher-level modulations such as task and constraint information) and equally formulated on any level of abstraction (motor control variables or symbolic representations). Recent advances in Machine Learning provide a coherent framework for these problems.
One-loop QCD corrections to top quark decay into a neutralino and light stop squark.

We calculate the one-loop QCD corrections to {ital t}{r_arrow}{ital {tilde t}}{sub 1}{tilde {chi}}{sup 0}{sub {ital j}} using the dimensional reduction scheme, including QCD and supersymmetric QCD corrections. The analytic expressions for the corrections to the decay width are given, which can easily be extended to {ital t}{r_arrow}{tilde {chi}}{sup +}{sub {ital j}}{ital {tilde b}}{sub {ital i}}. The numerical results show that the correction amounts to more than a 10{percent} reduction in the partial width relative to the tree level result. We also compare the corrections in the no-mixing top squark case with those in the mixing top squark case. {copyright} {ital 1996 The American Physical Society. }
THE CORE PROBLEM WITHIN A LINEAR APPROXIMATION PROBLEM AX ≈ B WITH MULTIPLE RIGHT-HAND SIDES∗

This paper focuses on total least squares (TLS) problems AX ≈ B with multiple right-hand sides. Existence and uniqueness of a TLS solution for such problems was analyzed in the paper [I. Hnětynková, M. Plešinger, D. M. Sima, Z. Strakoš, and S. Van Huffel (2011)]. For TLS problems with single right-hand sides the paper [C. C. Paige and Z. Strakoš (2006)] showed how necessary and sufficient information for solving Ax ≈ b can be revealed from the original data through the so-called core problem concept. In this paper we present a theoretical study extending this concept to problems with multiple right-hand sides. The data reduction we present here is based on the singular value decomposition of the system matrix A. We show minimality of the reduced problem; in this sense the situation is analogous to the single right-hand side case. Some other properties of the core problem, however, can not be extended to the case of multiple right-hand sides.
Linguistic Diversities of Demographic Groups in Twitter

The massive popularity of online social media provides a unique opportunity for researchers to study the linguistic characteristics and patterns of user's interactions. In this paper, we provide an in-depth characterization of language usage across demographic groups in Twitter. In particular, we extract the gender and race of Twitter users located in the U.S. using advanced image processing algorithms from Face++. Then, we investigate how demographic groups (i.e. male/female, Asian/Black/White) differ in terms of linguistic styles and also their interests. We extract linguistic features from 6 categories (affective attributes, cognitive attributes, lexical density and awareness, temporal references, social and personal concerns, and interpersonal focus), in order to identify the similarities and differences in particular writing set of attributes. In addition, we extract the absolute ranking difference of top phrases between demographic groups. As a dimension of diversity, we also use the topics of interest that we retrieve from each user. Our analysis unveils clear differences in the writing styles (and the topics of interest) of different demographic groups, with variation seen across both gender and race lines. We hope our effort can stimulate the development of new studies related to demographic information in the online space.
Seawall: Performance Isolation for Cloud Datacenter Networks

While today's virtual datacenters have hypervisor based mechanisms to partition compute resources between the tenants co-located on an end host, they provide little control over how tenants shore the network. This opens cloud applications to interference from other tenants, resulting in unpredictable performance and exposure to denial of service attacks. This paper explores the design space for achieving performance isolation between tenants. We find that existing schemes for enterprise datacenters suffer from at least one of these problems: they cannot keep up with the numbers of tenants and the VM churn observed in cloud datacenters; they impose static bandwidth limits to obtain isolation at the cost of network utilization; they require switch and/or NIC modifications; they cannot tolerate malicious tenants and compromised hypervisors. We propose Seawall, an edge-based solution, that achieves max-min fairness across tenant VMs by sending traffic through congestion-controlled, hypervisor-to-hypervisor tunnels.
Written language disorders: speech-language pathologists' training, knowledge, and confidence.

PURPOSE This study examined speech-language pathologists' (SLPs') perceptions of their (a) educational and clinical training in evaluating and treating written language disorders, (b) knowledge bases in this area, (c) sources of knowledge about written language disorders, (d) confidence levels, and (e) predictors of confidence in working with written language disorders. METHOD A 6-part survey was developed and was mailed to 1,000 school-based SLPs. RESULTS SLPs (n = 599) practicing in 47 states responded to the survey. A majority (60.3%) reported working with a child with a written language disorder either weekly or daily. SLPs described their educational and clinical training as "limited" in the evaluation and treatment of children with written language disorders. The average SLP stated feeling "somewhat confident" to evaluate and treat written language disorders, and 63.8% reported that they received most of their knowledge through "on-the job" training. Confidence was related to four variables: on-the-job training, general knowledge about written language disorders, attendance at conventions, and understanding of collaborative efforts. CONCLUSION Our findings provide information about SLPs' training, knowledge, and confidence about written language beyond anecdotal reports and fill research gaps regarding SLPs' preservice and professional development needs. Predictors of confidence are discussed.
High-performance Dynamic Programming on FPGAs with OpenCL

Field programmable gate arrays (FPGAs) provide reconfigurable computing fabrics that can be tailored to a wide range of time and power sensitive applications. Traditionally, programming FPGAs required an expertise in complex hardware description languages (HDLs) or proprietary high-level synthesis (HLS) tools. Recently, Altera released the worlds first OpenCL conformant SDK for FPGAs. OpenCL is an open, royalty-free standard for cross-platform, parallel programming of heterogeneous systems that together with Altera extensions significantly reduces FPGA development time and costs in high-performance computing environments. In this paper, we demonstrate dynamic programming on FPGAs with OpenCL by implementing the Smith Waterman algorithm for DNA, RNA, or protein sequencing in bioinformatics in a manner readily familiar to both hardware and software developers. Results show that Altera FPGAs significantly outperform leading CPU and GPU parallel implementations by over an order of magnitude in both absolute performance and relative power efficiency.
Graph Structured Semantic Representation and Learning for Financial News

This study links stock prices of publicly traded companies with online financial news to predict direction of stock price change. Previous work shows this to be an extremely challenging problem. We develop a very high-dimensional representation for news about companies that encodes lexical, syntactic and frame semantic information in graphs. Use of a graph kernel to efficiently compare subgraphs for machine learning provides a uniform feature engineering framework that integrates semantic frames in document representation. Evaluated on a news web archive against two benchmarks, only our approach beats the majority class baseline, and with statistically significant results.
Conceptual Combinations: The Role of Similarity

Noun-noun compounds, such as shark lawyer, are claimed to be interpreted via property construction when the noun concepts are similar (Wisniewski, 1996). In Experiment 1, noun-noun compounds with dissimilar constituents were derived from metaphors and were given to participants for interpretation. Property construction interpretations were overwhelmingly preferred, despite the dissimilarity of the constituents. In Experiment 2, noun-noun compounds with dissimilar constituents that satisfied theoretical criteria for metaphorical property attribution (Glucksberg, McGlone, & Manfredi, 1997) were interpreted via property construction. In contrast, compounds with highly similar constituents were interpreted primarily via hybridizational. We consider the implications of these findings for (a) the boundary conditions for the role of similarity in choice of noun-noun compound interpretation and (b) the automaticity of metaphor comprehension.
Experimental performance investigation of cooling or heating coil valves and their impact on temperature controls.

Hysteresis and nonlinearity exist in most valves that are utilized in building HVAC systems, such as in cooling or heating coil valves. The hysteresis mainly comes from the manufacturing clearance in an actuator gearbox and nonlinearity in the variation of the regulated flow with respect to control signal originates from valve design. The combination of valve hysteresis and nonlinearity poses significant difficulties in obtaining satisfactory control performance when utilizing a conventional PI controller. This paper presents experimental testing results for a set of valves in an operating HVAC system serving an office building. The test valves include VAV reheat coil and AHU cooling coil valves provided by two mainstream manufacturers. Open-loop experiments were carried out that are used to analyze valve performance in terms of hysteresis and nonlinearity. Valve closed-loop performance was also investigated and the results showed that valves with significant hysteresis and nonlinear characteristics lead to unsatisfactory supply air or zone air temperature controls with severe temperature oscillations and control chattering.
Acquisition of English Causative Psych Verbs by Chinese Learners

1 This study centers upon, the form-meaning connections of second language (L2) causative psych verbs. More specifically, it attempts to (1) interpret the Chinese learners’ internal representation of knowledge on English causative psych verbs, (2) explain how and to what extent the transfer of the first language (Chinese) motivates similar or different outcomes at different second language (English) proficiency levels, and, consequently, (3) figures out how the Chinese English learners acquire the ability of using second language causative psych verbs’ structure accurately, meaningfully, and appropriately. Based on 90 Chinese English learners and 30 native English speakers, it reveals that Chinese is a crucial factor to influence the acquisition of causative psych verbs in English. Index Terms causative psych verbs, second language acquisition, Chinese, English