Miracle-dz/UniFAR-FTUs huggingface dataset:
Motion Retargeting for Humanoid Robots Based on Simultaneous Morphing Parameter Identification and Motion Optimization

This paper presents a novel method for retargeting human motions onto a humanoid robot. The method solves the following three simultaneous problems: the geometric parameter identification that morphs the human model to the robot model, motion planning for a robot, and the inverse kinematics of the human motion-capture data. Simultaneous solutions can imitate the original motion more accurately than conventional approaches, which solve the problems sequentially. The proposed method can reconstruct the human motion within the physical constraints imposed by robot dynamics. A reconstruction step enables quantitative analysis of the retargeting results through direct comparison with the original human motion. The method can also provide the precise morphing function as well as subject-specific models, which can handle the different body dimensions of human subjects. This new framework is suitable for applications that require an accurate generation of human-like motions with quantitative evaluation criteria, such as humanoid robots that evaluate assistive devices. Experimental tests of the proposed method were performed with humanoid robot HRP-4.
Packet-Mode Emulation of Output-Queued Switches

Most common network protocols transmit variable size packets, whereas contemporary switches still operate with fixed- size cells, which are easier to transmit and buffer. This necessitates packet segmentation and reassembly modules, resulting in significant computation and communication overhead that might be too costly as switches become faster and bigger. It is, therefore, imperative to investigate an alternative mode of scheduling in which packets are scheduled contiguously over the switch fabric. This paper investigates the cost of packet-mode scheduling for the combined input-output-queued (CIOQ) switch architecture. We devise frame-based schedulers that allow a packet-mode CIOQ switch with small speedup to mimic an ideal output-queued switch, with bounded relative queuing delay. The schedulers are pipelined and based on matrix decomposition. Our schedulers demonstrate a trade-off between the switch speedup and the relative queuing delay incurred while mimicking an output-queued switch. When the switch is allowed to incur high relative queuing delay, a speedup arbitrarily close to two suffices to mimic an ideal output-queued switch. This implies that packet-mode scheduling does not require higher speedup than a cell-based scheduler. The relative queuing delay can be significantly reduced with just a doubling of the speedup. We further show that it is impossible to achieve zero relative queuing delay (that is, a perfect emulation), regardless of the switch speedup. In addition, simpler algorithms can mimic an output-queued switch with a bounded buffer size, using speedup arbitrarily close to one. Simulations confirm that packet-mode emulation with reasonable relative queuing delay can be achieved with moderate speedup. Furthermore, a simple and practical heuristic is shown by simulations to also provide effective packet-mode emulation.
Rough Set Based Approach to Text Classification

Textual document set has become an important and rapidly growing information source in the web. Text classification is one of the crucial technologies for information organisation and management. Text classification has become more and more important and attracted wide attention of researchers from different research fields. In this paper, many feature selection methods, the implement algorithms and applications of text classification are introduced firstly. However, because there are much noise in the knowledge extracted by current data-mining techniques for text classification, it leads to much uncertainty in the process of text classification which is produced from both the knowledge extraction and knowledge usage, therefore, more innovative techniques and methods are needed to improve the performance of text classification. It has been a critical step with great challenge to further improve the process of knowledge extraction and effectively utilization of the extracted knowledge. Rough Set decision making approach is proposed to use Rough Set decision techniques to more precisely classify the textual documents which are difficult to separate by the classic text classification methods. The purpose of this paper is to give an overview of existing text classification technologies, to demonstrate the Rough Set concepts and the decision making approach based on Rough Set theory for building more reliable and effective text classification framework with higher precision, to set up an innovative evaluation metric named CEI which is very effective for the performance assessment of the similar research, and to propose a promising research direction for addressing the challenging problems in text classification, text mining and other relative fields.
Alethiometer: a framework for assessing trustworthiness and content validity in social media

There are both positive and negative aspects in the use of social media in news and information dissemination. To deal with the negative aspects, such as the spread of rumours and fake news, the flow of information should implicitly be filtered and marked to specific criteria such as credibility, trustworthiness, reputation, popularity, influence, and authenticity. This paper proposes an approach that can enhance trustworthiness and content validity in the presence of information overload. We introduce Alethiometer, a framework for assessing truthfulness in social media that can be used by professional and general news users alike. We present different measures that delve into the detailed analysis of the content, the contributors of the content and the underlying context. We further propose an approach for deriving a single metric that considers, in a unified manner, the quality of a contributor and of the content provided by that contributor. Finally, we present some preliminary statistical results from the examination of a set of 10 million twitter users, that provide useful insights on the characteristics of social media data.
CrFK Feline Kidney Cells Produce an RD114-Like Endogenous Virus That Can Package Murine Leukemia Virus-Based Vectors

ABSTRACT The feline kidney cell line CrFK is used extensively for viral infectivity assays and for study of the biology of various retroviruses and derived vectors. We demonstrate the production of an endogenous, RD114-like, infectious retrovirus from CrFK cells. This virus also is shown to efficiently package Moloney murine leukemia virus vectors.
A Solution to the Simultaneous Localisation and Map Building (SLAM) Problem

—The simultaneous localisation and map building (SLAM) problem asks if it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and then to incrementally build a map of this environment while simultaneously using this map to compute absolute vehicle location. Starting from the estimation-theoretic foundations of this problem developed in [1], [2], [3], this paper proves that a solution to the SLAM problem is indeed possible. The underlying structure of the SLAM problem is ﬁrst elucidated. A proof that the estimated map converges monotonically to a relative map with zero uncertainty is then developed. It is then shown that the absolute accuracy of the map and the vehicle location reach a lower bound de-ﬁned only by the initial vehicle uncertainty. Together, these results show that it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and, using relative observations only, incrementally build a perfect map of the world and to compute simultaneously a bounded estimate of vehicle location. This paper also describes a substantial implementation of the SLAM algorithm on a vehicle operating in an out-door environment using millimeter-wave (MMW) radar to provide relative map observations. This implementation is used to demonstrate how some key issues such as map management and data association can be handled in a practical environment. The results obtained are cross-compared with absolute locations of the map landmarks obtained by sur-veying. In conclusion, this paper discusses a number of key issues raised by the solution to the SLAM problem including sub-optimal map-building algorithms and map management.
Exposure fusion based on sparse coding in pyramid transform domain

Sparse representation theory explores the sparseness of natural signals, and can be used to fuse multi-exposure images. To reduce the presence of artifacts, a "sliding window" technique with a small step size is usually adopted, enabling high-quality images to be obtained. However, this approach is time-consuming, especially when the source image is large (i.e., 1280 × 1024 pixels). The method proposed in this paper reduces the computation time of the image fusion process. We know that the low-frequency component gives a coarse representation of the original image, and inherits certain properties such as the mean intensity and texture information. First, we obtain the low-frequency subimage using Laplacian pyramid decomposition of the source images. These low-frequency components are used to represent the original image, and are fused using the sparse coding fusion framework. Second, we apply saliency matching as a fusion rule for the high-frequency subimage obtained by Laplacian pyramid decomposition. Experiments show that the proposed method produces comparative or even better results than other typical exposure fusion methods, and greatly reduces the computation time.
Reduced Mature MicroRNA Levels in Association with Dicer Loss in Human Temporal Lobe Epilepsy with Hippocampal Sclerosis

Hippocampal sclerosis (HS) is a common pathological finding in patients with temporal lobe epilepsy (TLE) and is associated with altered expression of genes controlling neuronal excitability, glial function, neuroinflammation and cell death. MicroRNAs (miRNAs), a class of small non-coding RNAs, function as post-transcriptional regulators of gene expression and are critical for normal brain development and function. Production of mature miRNAs requires Dicer, an RNAase III, loss of which has been shown to cause neuronal and glial dysfunction, seizures, and neurodegeneration. Here we investigated miRNA biogenesis in hippocampal and neocortical resection specimens from pharmacoresistant TLE patients and autopsy controls. Western blot analysis revealed protein levels of Dicer were significantly lower in certain TLE patients with HS. Dicer levels were also reduced in the hippocampus of mice subject to experimentally-induced epilepsy. To determine if Dicer loss was associated with altered miRNA processing, we profiled levels of 380 mature miRNAs in control and TLE-HS samples. Expression of nearly 200 miRNAs was detected in control human hippocampus. In TLE-HS samples there was a large-scale reduction of miRNA expression, with 51% expressed at lower levels and a further 24% not detectable. Primary transcript (pri-miRNAs) expression levels for several tested miRNAs were not different between control and TLE-HS samples. These findings suggest loss of Dicer and failure of mature miRNA expression may be a feature of the pathophysiology of HS in patients with TLE.
Planning Marketing-Mix Strategies in the Presence of Interaction Effects

Companies spend millions of dollars on advertising to boost a brand's image and simultaneously spend millions of dollars on promotion that many believe calls attention to price and erodes brand equity. We believe this paradoxical situation exists because both advertising and promotion are necessary to compete effectively in dynamic markets. Consequently, brand managers need to account for interactions between marketing activities and interactions among competing brands. By recognizing interaction effects between activities, managers can consider interactivity trade-offs in planning the marketing-mix strategies. On the other hand, by recognizing interactions with competitors, managers can incorporate strategic foresight in their planning, which requires them to look forward and reason backward in making optimal decisions. Looking forward means that each brand manager anticipates how other competing brands are likely to make future decisions, and then by reasoning backward deduces one's own optimal decisions in response to the best decisions to be made by all other brands. The joint consideration of interaction effects and strategic foresight in planning marketing-mix strategies is a challenging and unsolved marketing problem, which motivates this paper. This paper investigates the problem of planning marketing mix in dynamic competitive markets. We extend the Lanchester model by incorporating interaction effects, constructing the marketing-mix algorithm that yields marketing-mix plans with strategic foresight, and developing the continuous-discrete estimation method to calibrate dynamic models of oligopoly using market data. Both the marketing-mix algorithm and the estimation method are general, so they can be applied to any other alternative model specifications for dynamic oligopoly markets. Thus, this dual methodology augments the decision-making toolkit of managers, empowering them to tackle realistic marketing problems in dynamic oligopoly markets. We illustrate the application of this dual methodology by studying the dynamic Lanchester competition across five brands in the detergents market, where each brand uses advertising and promotion to influence its own market share and the shares of competing brands. Empirically, we find that advertising and promotion not only affect the brand shares own and competitors' but also exert interaction effects, i.e., each activity amplifies or attenuates the effectiveness of the other activity. Normatively, we find that large brands underadvertise and overspend on promotion, while small brands underadvertise and underpromote. Finally, comparative statics reveal managerial insights into how a specific brand should respond optimally to the changes in a competing brand's situation; more generally, we find evidence that competitive responsiveness is asymmetric.
Pacific Asia Conference on Information Systems ( PACIS ) 2010 Understanding the Role of Knowledge Co-Production between Users and Developers in ISD Project : An Intellectual Capital Perspective

Information system development (ISD) has long been treated as that process that system developers craft an artifact to support business operation based on their special expertise. However, a significant portion of projects still have failed because the developed outcome cannot fit users’ needs. An emerging internal service concept indicates that, by treating ISD as one type of service, the requirement definition can be viewed as a co-production process in which users and developers integrate their own knowledge. By incorporating this concept into research design and taking intellectual capital perspective into account, this study proposed a model to examine the antecedents and consequences of knowledge co-production between users and developers. Data collected from 267 developers confirmed our hypotheses that knowledge co-production can benefit ISD outcomes, and common knowledge, relational capital and participative decision-making between these two parties increase the effectiveness of knowledge co-production effectively. Lastly, the implications toward academic and practitioner are also provided.
Synchronization views for event-loop actors

The actor model has already proven itself as an interesting concurrency model that avoids issues such as deadlocks and race conditions by construction, and thus facilitates concurrent programming. The tradeoff is that it sacrifices expressiveness and efficiency especially with respect to data parallelism. However, many standard solutions to computationally expensive problems employ data parallel algorithms for better performance on parallel systems. We identified three problems that inhibit the use of data-parallel algorithms within the actor model. Firstly, one of the main properties of the actor model, the fact that no data is shared, is one of the most severe performance bottlenecks. Especially the fact that shared state can not be read truly in parallel. Secondly, the actor model on its own does not provide a mechanism to specify extra synchronization conditions on batches of messages which leads to event-level data-races. And lastly, programmers are forced to write code in a continuation-passing style (CPS) to handle typical request-response situations. However, CPS breaks the sequential flow of the code and is often hard to understand, which increases complexity and lowers maintainability. We proposes synchronization views to solve these three issues without compromising the semantic properties of the actor model. Thus, the resulting concurrency model maintains deadlock-freedom, avoids low-level race conditions, and keeps the semantics of macro-step execution.
Activation of GPR4 by Acidosis Increases Endothelial Cell Adhesion through the cAMP/Epac Pathway

Endothelium-leukocyte interaction is critical for inflammatory responses. Whereas the tissue microenvironments are often acidic at inflammatory sites, the mechanisms by which cells respond to acidosis are not well understood. Using molecular, cellular and biochemical approaches, we demonstrate that activation of GPR4, a proton-sensing G protein-coupled receptor, by isocapnic acidosis increases the adhesiveness of human umbilical vein endothelial cells (HUVECs) that express GPR4 endogenously. Acidosis in combination with GPR4 overexpression further augments HUVEC adhesion with U937 monocytes. In contrast, overexpression of a G protein signaling-defective DRY motif mutant (R115A) of GPR4 does not elicit any increase of HUVEC adhesion, indicating the requirement of G protein signaling. Downregulation of GPR4 expression by RNA interference reduces the acidosis-induced HUVEC adhesion. To delineate downstream pathways, we show that inhibition of adenylate cyclase by inhibitors, 2′,5′-dideoxyadenosine (DDA) or SQ 22536, attenuates acidosis/GPR4-induced HUVEC adhesion. Consistently, treatment with a cAMP analog or a Gi signaling inhibitor increases HUVEC adhesiveness, suggesting a role of the Gs/cAMP signaling in this process. We further show that the cAMP downstream effector Epac is important for acidosis/GPR4-induced cell adhesion. Moreover, activation of GPR4 by acidosis increases the expression of vascular adhesion molecules E-selectin, VCAM-1 and ICAM-1, which are functionally involved in acidosis/GPR4-mediated HUVEC adhesion. Similarly, hypercapnic acidosis can also activate GPR4 to stimulate HUVEC adhesion molecule expression and adhesiveness. These results suggest that acidosis/GPR4 signaling regulates endothelial cell adhesion mainly through the Gs/cAMP/Epac pathway and may play a role in the inflammatory response of vascular endothelial cells.
Audio-based affect detection in web videos

We present a new technique for detecting audio concepts in web content as well outline the technique's applications to video sequence parsing. Our focus is primarily on affective concepts and in order to study them we have collected a new dataset, consisting of videos where a speaker is persuading a crowd, called “Rallying a Crowd”. We develop new classifiers for graded levels of arousal in speech as well as crowd noise and music and demonstrate their effectiveness on web content. These techniques achieve high detection accuracy (58.2%) for affective concepts on this new dataset and outperform (36.8%) state-of-the-art techniques (33.1%) for semantic concepts on a previously collected dataset. We also develop a new audio sequence segmentation technique which enables us to rapidly classify subsections of test sequence audio into the aforementioned audio classes. We are thus able to robustly address the detection of affective concepts in highly variable web content as well as the computational challenge of quick classification so as to enable web scale processing.
Rapid Detection of Hepatitis B Virus Surface Antigen by an Agglutination Assay Mediated by a Bispecific Diabody against Both Human Erythrocytes and Hepatitis B Virus Surface Antigen

ABSTRACT Bispecific antibodies have immense potential for use in clinical applications. In the present study, a bispecific diabody against human red blood cells (RBCs) and hepatitis B virus surface antigen (HBsAg) was used to detect HBsAg in blood specimens. The bispecific diabody was constructed by crossing over the variable region of the heavy chains and the light chains of anti-RBC and anti-HBsAg antibodies with a short linker, SRGGGS. In enzyme-linked immunosorbent assays, this bispecific diabody showed specific binding to both RBCs and HBsAg. When this bispecific diabody was mixed with human blood specimens in the presence of HBsAg, the dual binding sites of the diabody caused agglutination of human RBCs. This diabody-mediated agglutination assay was then used to test 712 clinical blood specimens and showed 97.7% sensitivity and 100% specificity when the results were compared with those of the conventional immunoassay, which was used as a reference. This autologous RBC agglutination assay provides a simple approach for rapid screening for HBsAg in blood specimens.
A multiple-layer radome for reducing the RCS of a microstrip patch

A specific multiple-layer radome geometry for reducing the RCS (radar cross section) of a microstrip patch antenna is presented. The radome consists of a stacked set of lossless dielectric layers whose permittivities alternate between low and high values of in /sub r/. Choosing the layer thicknesses properly makes it possible to achieve significant RCS reduction. However, the radiation efficiency is also reduced along with the RCS, so that a tradeoff occurs. <<ETX>>
Risk contribution of sexual behavior and cigarette smoking to cervical neoplasia

Infection with high-risk human papillomavirus (HPV) is considered a “necessary cause” for cervical cancer (CC); however, only some HPV-infected women develop CC. We report on the differential risk contribution of sexual behavior and cigarette smoking to cervical neoplasia in the US and Venezuela. A total of 142 patients and 158 matched-controls were recruited from both countries using the same recruitment protocol, the same pathologists for case verification, and the same experimental procedures for analysis. HPV infection was significantly associated with CC for both populations as expected, but the Venezuelan controls were twice as likely to be infected with HPV as the US controls. Having >2 lifetime sexual partners (OR = 4.7, 95% CI = 1.7-13.1) and initiation of sexual activities before the age of 18 (OR = 4.7, 95% CI = 1.6-13.7) were significant risk factors in a multivariate model for CC in Venezuela. In contrast, current cigarette smoking was a significant risk factor only in the US (OR = 3.6, 95% CI = 1.7-7.7). The observed differences in risk factors support the need for additional studies in different geographic regions and the information can be used to develop country-specific CC prevention programs.