Miracle-dz/UniFAR-FTUs huggingface dataset:
A Post-Resampling Based Particle Filter for Online Bayesian Estimation and Tracking

For state estimation problem, particle filter is generally used to construct the posterior probability density function by a set of particles, which is regarded as a solution to state estimation. Many techniques have been developed to improve performance of particle filter, at the cost of largely increased computational burden for each particle. In this paper, we propose a post-resampling based particle filter. The modified particle filter is capable of accurately representing the posterior probability density function through properly sampling particles. We applied the proposed particle filter to the classic bearings-only tracking problem. Simulation results showed that our modified particle filter had superior performance and reasonably computational cost, compared with the general approaches. It may provide a promising alternative to the existent particle filters
Factor-1 Pathway Macrophages by Up-regulating the Colony-Stimulating Promoting Response in − Mediates the Tumor Growth α Derived Tumor Necrosis Factor-− Colon Cancer Cell

The interplay between malignant and stromal cells is essential in tumorigenesis. We have previously shown that colonystimulating factor (CSF)-1, matrix metalloprotease (MMP)-2, and vascular endothelial growth factor (VEGF)-A production by stromal cells is enhanced by CSF-1–negative SW620 colon cancer cells. In the present study, the mechanisms by which colon cancer cells up-regulate host factors to promote tumorigenesis were investigated. Profiling of tumor cell cytokine expression in SW620 tumor xenografts in nude mice showed increased human tumor necrosis factor (TNF)-A mRNA expression with tumor growth. Incubation of macrophages with small interfering (si) RNAs directed against TNF-A or TNF-A–depleted SW620 cell conditioned medium versus SW620 cell conditioned medium failed to support mouse macrophage proliferation, migration, and expression of CSF-1, VEGF-A, and MMP-2 mRNAs. Consistent with these results, human TNF-A gene silencing decreased mouse macrophage TNF-A, CSF-1, MMP-2, and VEGF-A mRNA expression in macrophages cocultured with human cancer cells. In addition, inhibition of human TNF-A or mouse CSF-1 expression by siRNA reduced tumor growth in SW620 tumor xenografts in mice. These results suggest that colon cancer cell–derived TNF-A stimulates TNF-A and CSF-1 production by macrophages, and that CSF-1, in turn, induces macrophage VEGF-A and MMP-2 in an autocrine manner. Thus, interrupting tumor cell–macrophage communication by targeting TNF-A may provide an alternative therapeutic approach for the treatment of colon cancer. [Cancer Res 2007;67(3):1038–45]
Characterizing device dynamics for haptic manipulation and navigation

In this work we present a method of systematically selecting regions of a haptic workspace to be used for navigation of large virtual environments. Existing navigational techniques require the partitioning of the workspace into a region of manipulation and a separate region for navigation tasks. These techniques, however, have neglected to describe an effective way to implement these concepts in a device specific manner. We propose a two step technique to define these regions based on the mechanical properties of pre-existing devices. In the first step, the kinematic properties of the device are analyzed across the entirety of the physical workspace. A well-behaved region that favours isotropic mapping from the joint actuators to the generalized forces at the end effector is selected. Having ensured high force fidelity within this region, we then perform a second step analyzing the device dynamic properties. We further subdivide the navigational space into a region with suitable inertial properties in which manipulation tasks may be performed. This procedure generates a haptic display with a highly transparent haptic manipulation region within which a user can interact with a virtual environment. This manipulation region is bounded by a well-behaved navigational region that ensures adequate force transmission. To demonstrate this technique, navigation and manipulation spaces are generated and described for the planar and spatial cases.
Transformational leadership, employee turnover intention, and actual voluntary turnover in public organizations

ABSTRACT This research seeks to make contributions to the organization-level analysis of voluntary turnover in public organizations. Structural equation modelling is used to explore how transformational leadership makes a difference on employees’ actual quitting behaviour. Moreover, the research provides empirical evidence on the relationship between turnover intention and actual turnover. The findings suggested that transformational leadership not only directly prevents employees from forming intentions to leave but also indirectly does so by cultivating a collaborative culture. Additionally, we found that higher turnover intention leads to higher actual turnover rate, so turnover intention may be a valid proxy of actual turnover behaviour.
The Generalized Neoclassical Growth Model

We construct and numerically solve a dynamic Hechscher-Ohlin model which, depending on the distribution of production factors in the world and parameter values, allows for worldwide factor price equalization or complete specialization. We explore the dynamics of the model under different parameter values, and relate our theoretical results to the empirical literature that studies the determinants of countries' income per capita growth and levels. In general, the model is capable of generating predictions in accordance with the most important findings in the empirical growth literature. At the same time, it avoids some of the most serious problems of the (autarkic) neoclassical growth model.
Density-functional study of homogeneous bubble nucleation in the stretched Lennard-Jones fluid

Density-functional theory is used to study homogeneous bubble nucleation in the stretched Lennard-Jones liquid. We show that the ratio of density-functional to classical nucleation theory free energy barriers should scale with the quantity Δμ/Δμspin, the difference in chemical potential between the bulk superheated and the saturated liquid divided by the chemical potential difference between the liquid spinodal and the saturated liquid. The critical bubble changes from classical near coexistence (sharp interface, uniform density that decreases with penetration into the coexistence region) to nonclassical beyond Δμ/Δμspin≈0.5 (diffuse interface, increasing density with increasing penetration into the metastable region). The density at the center of the bubble, the mean bubble density, the bubble size, the interfacial thickness, and the free energy cost of forming a critical bubble all scale with Δμ/Δμspin in temperature-independent fashion. This precise measure of the degree of metastability should emerge .
Cancer Cell Fusion: Mechanisms Slowly Unravel

Although molecular mechanisms and signaling pathways driving invasion and metastasis have been studied for many years, the origin of the population of metastatic cells within the primary tumor is still not well understood. About a century ago, Aichel proposed that cancer cell fusion was a mechanism of cancer metastasis. This hypothesis gained some support over the years, and recently became the focus of many studies that revealed increasing evidence pointing to the possibility that cancer cell fusion probably gives rise to the metastatic phenotype by generating widespread genetic and epigenetic diversity, leading to the emergence of critical populations needed to evolve resistance to the treatment and development of metastasis. In this review, we will discuss the clinical relevance of cancer cell fusion, describe emerging mechanisms of cancer cell fusion, address why inhibiting cancer cell fusion could represent a critical line of attack to limit drug resistance and to prevent metastasis, and suggest one new modality for doing so.
Linear-Combined-Code-Based Unambiguous Code Discriminator Design for Multipath Mitigation in GNSS Receivers

Unambiguous tracking and multipath mitigation for Binary Offset Carrier (BOC) signals are two important requirements of modern Global Navigation Satellite Systems (GNSS) receivers. A GNSS discriminator design method based on optimization technique is proposed in this paper to meet these requirements. Firstly, the discriminator structure based on a linear-combined code is given. Then the requirements of ideal discriminator function are converted into the mathematical constraints and the objective function to form a non-linear optimization problem. Finally, the problem is solved and the local code is generated according to the results. The theoretical analysis and simulation results indicate that the proposed method can completely remove the false lock points for BOC signals and provide superior multipath mitigation performance compared with traditional discriminator and high revolution correlator (HRC) technique. Moreover, the proposed discriminator is easy to implement for not increasing the number of correlators.
Comparison of parallel and random approach to a candidate list in the multifeature querying

In the field of the multifeature querying it is possible to use many heuristics to retrieve top k objects to became low number of accesses to the sources. When the sources have many equal values, it is often hard to choose which source should be accessed next. In this paper we compare previous random approach with the parallel approach to the set of actual candidate sources.
Kinematics mapping and similarity evaluation of humanoid motion based on human motion capture

The captured data must be adapted for the humanoid because its kinematics and dynamic differ from those of the human actor. The kinematics constraints such as ground contact conditions are crucial for humanoid locomotion. Furthermore, it is desirable that the humanoid motion have of high similarity with those of the human actor. In this paper, first the similarity function of the humanoid motion is proposed. Then, the kinematics constrains including ground contact conditions are formulated, and the algorithm to derive the humanoid motion with a high similarity and satisfying kinematics constraints is present. Finally, the effectiveness is confirmed by the experiment of Chinese Kungfu "Taiji" using our developed 33 DOF humanoid robot.
Delay and power consumption of fault tolerant data busses in VDSM technology

In Very Deep-submicron (VDSM) systems, the scaling of ULSI ICs has increased the sensitivity of CMOS technology to cause various noise mechanismssuch as power supply noise, crosstalk noise, leakage noise, etc. In VDSM technology distance between the data bus lines is reduced, so coupling capacitance is dominating factor. Unfortunately, in VDSM systems, the coupling capacitance is of magnitude several times larger than the loading capacitance. The coupling capacitance causes logical malfunction, delay faults, and power consumption on long on-chip data buses. An important effect of the coupling capacitance is Cross talk. Crosstalk is mainly dependent on several factors: drive strength, wire length/spacing, edge rate and propagation duration. The crosstalk noise produces from the coupling capacitance. Such faults may affect data on data bus. To avoid this condition and to guarantee signal integrity on the on-chip communication, a fault tolerant bus can be adopted. This could be achieved by implementing error-correcting codes (ECCs), providing on-line correction and do not require data retransmission. The 4,8,16, and 32-bit data bus is implemented in 180nm, 120nm, and 65nm technologies using Bsim4 model. For reliable transmission of the data ECC techniques is placed on the data bus. We employed a Hamming code and Dual rail as ECC for 4,8,16 and 32-bit fault tolerant data bus. This is implemented in 180nm, 120nm and 65nm technology. The simulation results show that Average power varies from 0.737mw to 0.176mw, and Maximum delay varies from 0.143nsec to 0.077nsec, for hamming 4 bit ECC, Average power varies from 2.135mw to 0.365mw and Maximum delay varies from 0.385nsec to 0.192nsec for hamming 8 bit ECC, Average power varies from 2.288mw to 0.377mw and Maximum delay varies from 0.721nsec to 0.353nsec for hamming 16 bit ECC, Average power varies from 3.064mw to 0.437mw and Maximum delay varies from 1.562nsec to 0.796nsec for hamming 32 bit ECC. The simulation results show that Average power varies from 0.206mw to 0.0459mw, and Maximum delay varies from 0.241nsec to 0.133nsec, for dual rail 4 bit ECC, Average power varies from 0.417mw to 0.0768mw and Maximum delay varies from 0.479nsec to 0.262nsec for dual rail 8 bit ECC, Average power varies from 0.726mw to 0.156mw and Maximum delay varies from 1.026nsec to 0.554nsec for dual rail 16 bit ECC, Average power varies from 0.926mw to 0.108mw and Maximum delay varies from 2.129nsec to 1.145nsec for dual rail 32 bit ECC respectively.
Constructing English: pre-service ELA teachers navigating an unwieldy discipline

Purpose The purpose of this paper is to describe a pedagogical innovation – a matrix construction exercise – intended to help pre-service teachers (PTs) navigate the multiple and oftentimes competing discourses that shape the school subject English Language Arts (ELA). Design/methodology/approach To explore the various ways the PTs drew on the discursively constructed paradigms of ELA throughout their teacher preparation program, researchers (themselves teacher educators) conducted an intertextual analysis (Prior, 1995) of PTs’ classroom texts and interview transcripts. Findings The intertextual analysis suggested that PTs possessed knowledge of and investment in a range of discourses, which they used to anchor their own pedagogical and curricular decision-making and to anticipate the leanings and ideologies of other stakeholders in ELA. Although the organizational schema of the matrix proved helpful from an orientation standpoint, it also may have disguised the productive tensions between particular discourses for some PTs. Originality/value Although scholars have long noted the plurality of the school subject English and some studies on innovations in teacher education allude to the difficulties that teachers encounter as they navigate the multiple purposes of ELA, there is little scholarship that considers how pre-service and beginning teachers might best navigate that incoherence and unwieldiness. This study, which contextualizes and explores a pedagogical innovation in an English methods class designed to help PTs navigate the many “Englishes”, attempts to fill this gap. The findings suggest that teacher preparation in ELA would do well to conceive of pedagogical innovations in teacher education that allow teachers to grapple with, rather than solve, the uncertainty and unfinalizability of the discipline.
Reducing Network Traffic Data Sets

In the study of network traffic, the collection and the processing of measurement data sets play a fundamental role. Due to the large size of typical traffic traces, their analysis is often heavy in terms of computational time and resources. In addition, even when the data sets are small, due to the intrinsic redundancy of the data, there is no need to consider the entire data sets in the processing stages. To cope with these issues, we use an entropy-based methodology to reduce network traffic data sets obtained by measurements over real networks. The off-line approach we used is based on the marginal utility concept, and reveals encouraging results when applied to real data captured over real networks, especially when dealing with large amounts of data. To show the applicability of our approach, we present and discuss results obtained in the analysis and characterization, at packet-level, of traffic traces from two popular network games: Counter-Strike and Age of Mythology. Thanks to the differences between the two considered on-line games and their traffic traces we can draw pros and cons in realistic scenarios.
Integrated motion and clasp planning with virtual linking

In this work, we address the problem of simultaneous clasp and motion planning on unknown objects with holes. Clasping an object enables a rich set of activities such as dragging, toting, pulling and hauling which can be applied to both soft and rigid objects. To this end, we define a virtual linking measure which characterizes the spacial relation between the robot hand and object. The measure utilizes a set of closed curves arising from an approximately shortest basis of the object's first homology group. We define task spaces to perform collision-free motion planing with respect to multiple prioritized objectives using a sampling-based planing method. The approach is tested in simulation using different robot hands and various real-world objects.
Item Familiarity Effects in User-Centric Evaluations of Recommender Systems

Laboratory studies are a common way of comparing recommendation approaches with respect to dierent quality dimensions that might be relevant for real users. One typical experimental setup is to rst present the participants with recommendation lists that were created with dierent algorithms and then ask the participants to assess these recommendations individually or to compare two item lists. The cognitive eort required by the participants for the evaluation of item recommendations in such settings depends on whether or not they already know the (features of the) recommended items. Furthermore, lists containing popular and broadly known items are correspondingly easier to evaluate. In this paper we report the results of a user study in which participants recruited on a crowdsourcing platform assessed system-provided recommendations in a between-subjects experimental design. The results surprisingly showed that users found non-personalized recommendations of popular items the best match for their preferences. An analysis revealed a measurable correlation between item familiarity and user acceptance. Overall, the observations indicate that item familiarity can be a potential confounding factor in such studies and should be considered in experimental designs.
A fusion-based approach for user activities recognition on smart phones

In the recent years, several research works have been conducted on collecting context data from various sensors for activity inference. We observe that users perform several actions in their mobile phones: taking photos, performing check-ins, and accessing Wi-Fi networks. These actions generate spatial-temporal data that could be utilized to capture user activities. Spatial-temporal data could indicate that a user stays in a certain location at a particular time for a certain activity. In addition, by referring to social media data, one could also infer user activities. Three types of features are extracted for activity inference: 1) geographical feature, indicating where a user performs activities; 2) temporal feature, indicating when a user performs activities; and 3) semantic feature, showing the semantic concept of a place from location-based social networks. Here, we propose Spatial-Temporal Activity Inference Model (STAIM) to infer user activities from data with those three features. In addition, to determine the weight for each feature, we further propose three methods based on frequency, entropy, and entropy-frequency. Experimental results show that STAIM is able to effectively infer user activities, achieving 75% accuracy on average. Moreover, STAIM could infer user activities even when there is no training data (with some performance loss). Moreover, sensitive analysis of parameters is also conducted to select the most optimal parameter.
SLL, active elements and available elements of uniformly-excited linear thinned arrays

The relationships between the SLL, the number of active elements and the number of available elements for uniformly-excited linear thinned arrays are investigated. These relationships are found to be logarithmic for both the symmetrical and asymmetrical cases. The relevant equations are provided to allow estimation of the SLL and filling factor for a specified number of available elements.
Demo: Opportunistic Mobile Brain Research

The majority of research using brain imaging and EEG techniques is currently limited to clinical environments, restricting experiments to synthetic tasks in controlled conditions. Lifting these limitations brought about by this articial setup would allow us to perform neuropsychological assessments and research in mobile settings or at locations easier accessible to patients, possibly even in remote, hard to access areas. We developed a tablet based mobile framework to present auditory and visual stimuli, capture wireless commercial EEG and screen interaction data, and analyze the recorded data for immediate evaluation, as well as share the data over internet or local opportunistic links. To demonstrate the feasibility of our approach, we successfully replicated the experimental set-up and evaluation pipeline of two existing EEG studies on event-related potentials. This work therefore lays the foundation to further truly mobile brain research and health-care applications.
Identifying interventions to help rural Kenyan mothers cope with food insecurity: results of a focused ethnographic study

Abstract An ethnographic study was conducted in two areas in southern and western Kenya to identify potential interventions to improve the quality, availability and affordability of foods consumed by infants and young children. A cultural–ecological model of determinants of nutrition identified the sectors of information for data collection related to infant and young child (IYC) diet and feeding‐related behaviours, and the focused ethnographic study manual was used to guide the research. The results provide qualitative evidence about facilitators and constraints to IYC nutrition in the two geographical areas and document their inter‐connections. We conclude with suggestions to consider 13 potential nutrition‐sensitive interventions. The studies provide empirical ethnographic support for arguments concerning the importance of combining nutrition‐specific and nutrition‐sensitive interventions through a multi‐sectoral, integrated approach to improve the nutrition of infants and young children in low‐income, resource‐constrained populations. They also document the value of ethnography as a component of landscape analysis in nutrition programme and policy planning. Key messages In addition to constraints on infant and young child diet that originate in environmental and technological conditions in both agro‐ecological zones, other factors that affect feeding practices include features of social organisation, household access to social support, caregivers income‐earning activities and their own health. The results of the ethnographies, which highlight the importance of obtaining the knowledge and perspectives of caregivers of infants and young children, reveal the interactions of the multiple factors that affect child nutrition and the need for simultaneous nutrition‐sensitive interventions to complement nutrition‐specific intervention actions. Most caregivers in both areas not only understood the importance of diet and food quality for child survival, they also regarded it as essential for child growth and development. This indicates that caregivers in these rural Kenyan communities have adopted the basic biomedical interpretation of the importance of child nutrition as an integral part of their ‘knowledge frameworks’.