Miracle-dz/UniFAR-FTUs huggingface dataset:
Topological Indoor Localization &amp; Navigation for Autonomous Industrial Mobile Manipulator

Autonomous Industrial Mobile Manipulators (AIMMs) combine the advantages of both mobile robots and industrial manipulators, therefore they have great mobility, flexibility and functionality. However, great challenges arise when AIMMs are expected to perform various tasks in unstructured or semi-structured environments. Since AIMMs are typically configured in the indoor environments, indoor localization & navigation is one of these challenges. A novel topological indoor localization & navigation method is proposed in this paper. Based on the depth information provided by a popular Kinect sensor, a progressive Bayesian classifier is developed to realize direct corridor type identification. Instead of extracting features from single observation, information from multi-observations are fused to achieve a more robust performance. With the ability of directly determining the corridor types, a topological map generation and loop closing method is proposed to build the environment map through autonomous exploration. By using the Markov Localization and trajectory planning method, the robot can localize itself and navigating freely in the indoor environment. Experiments are performed on a recently built AIMM system, and the results verify the effectiveness of the proposed methodology.
Sample Size Determination for Achieving Stability of Double Multivariate Exponentially Weighted Moving Average Controller

Many semiconductor manufacturing processes have by nature multiple-input and multiple-output (MIMO) variables. For the first-order MIMO process with a linear drift, the double multivariate exponentially weighted moving average (dMEWMA) controller is a popular run-to-run (R2R) controller for adjusting the process mean to a desired target. The long-term stability of this closed-loop MIMO system has not yet been thoroughly investigated and is the focus of our present study. The stability of this MIMO system using a controller with estimated process parameters depends on whether an initial input–output (I–O) predicted model can be obtained successfully in advance (i.e., offline) to accurately and precisely estimate these process parameters. However, the predicted model is typically constructed during an offline DOE/RSM stage, based on a random sample from the I–O variables, and thus the sample size and the strength of the linear relationship between I–O variables play major roles in determining the stability of the process. In this article we first obtain the stability conditions for the MIMO process. Obviously, these conditions depend on the estimated controller, and, consequently, one of the conditions is expressed in terms of a probability. We then derive a formula for the adequate sample size required to achieve stability for the closed-loop MIMO system with a guaranteed probability. We also describe how the offline DOE/RSM is conducted to obtain process parameter estimates. We give two practical MIMO examples to illustrate the proposed procedure. Finally, we describe a study demonstrating the impact of the covariance structure of I–O variables on the required sample size.
Semantic Classification of Nouns in UMLS Using Google Web 1 T 5-gram

In the tasks of information extraction and text mining from biomedical text, automatic classification of term sense is one of the important topics. It is expected that most of terms in a text can be correctly classified by matching them with glossaries extracted from databases or large-scale dictionaries such as UMLS [1]. However, since new terms always appear in the field of the biology and medical science, it is needed to classify the sense of a term not found in any dictionaries. Fan et al. developed a method of semantic classification of terms in UMLS [2]. Each term of UMLS has concept ID, and it is related to semantic type tree number. For instance, the term “DHLA” has concept ID “C0030956”, and it is related to the semantic type tree number “A1.4. 1.2. 1.9. 2”. Semantic type tree number represents a hierarchical categorization of semantics by “A” or “B” as level 0 followed by at most 7 numbers corresponding to level 1-7 (hereinafter called semantic level). In [2], Fan et al. regrouped UMLS concepts into eight broad semantic classes, and using them as class labels, performed classification based on two kinds of feature sets: contextual features extracted from MEDLINE [3] and lexical features extracted from UMLS. However, when we need to classify a novel term, we cannot utilize lexical features since it does not appear in UMLS, and contextual features since it rarely appears in MEDLINE. To solve this problem, this work performed semantic classification of nouns in UMLS using Web 1T 5-gram, the large-scale words co-occurrence data provided by Google [4]. Due to the co-occurrence information richer than above features, the classification accuracy is expected to be improved. Furthermore, in this work, we measured the classification accuracy in each semantic level.
Convergence of Ser/Thr and Two-component Signaling to Coordinate Expression of the Dormancy Regulon in Mycobacterium tuberculosis*

Signal transduction in Mycobacterium tuberculosis is mediated primarily by the Ser/Thr protein kinases and the two-component systems. The Ser/Thr kinase PknH has been shown to regulate growth of M. tuberculosis in a mouse model and in response to NO stress in vitro. Comparison of a pknH deletion mutant (ΔpknH) with its parental M. tuberculosis H37Rv strain using iTRAQ enabled us to quantify >700 mycobacterial proteins. Among these, members of the hypoxia- and NO-inducible dormancy (DosR) regulon were disregulated in the ΔpknH mutant. Using kinase assays, protein-protein interactions, and mass spectrometry analysis, we demonstrated that the two-component response regulator DosR is a substrate of PknH. PknH phosphorylation of DosR mapped to Thr198 and Thr205 on the key regulatory helix α10 involved in activation and dimerization of DosR. PknH Thr phosphorylation and DosS Asp phosphorylation of DosR cooperatively enhanced DosR binding to cognate DNA sequences. Transcriptional analysis comparing ΔpknH and parental M. tuberculosis revealed that induction of the DosR regulon was subdued in the ΔpknH mutant in response to NO. Together, these results indicate that PknH phosphorylation of DosR is required for full induction of the DosR regulon and demonstrate convergence of the two major signal transduction systems for the first time in M. tuberculosis.
RMP neural network based dissolved gas analyzer for fault diagnostic of oil-filled electrical equipment

Dissolved gas analysis (DGA) method is broadly used to diagnose incipient faults in oil-filled electrical equipment in service. This paper presents a reduced multivariate polynomial (RMP)-based neural network (NN) for the interpretation of DGA. RMP NN can be used as a pattern classifier and its parameters can be determined easily. Six inputs to the RMP NN with three-layer structures are made up of five gases. The effect of the order of RMP NN on diagnosis accuracy is analyzed in this study. The fault cases published have been used as training and testing patterns. The test results show that RMP NN has good diagnosis accuracy.
Activation of beta-chemokines and CCR5 in persons infected with human immunodeficiency virus type 1 and tuberculosis.

Tuberculosis (TB) in human immunodeficiency virus type 1 (HIV-1)-infected persons is associated with progression of HIV-1 disease. The expression of macrophage inflammatory protein (MIP)-1alpha and CCR5 was assessed in HIV-1-infected patients with pulmonary TB (HIV-1/PTB) and without PTB (HIV-1/C), PTB patients not infected with HIV-1 (PTB), and control subjects. Mycobacterium tuberculosis (MTB)-induced MIP-1alpha production was lower in peripheral blood mononuclear cells (PBMC) of HIV-1/PTB patients than in those of PTB patients (P< .05) and was lower in PBMC of HIV-1/C patients than in those of control subjects (P< .005). However, MIP-1alpha production was higher in PBMC of HIV/PTB patients than in those of HIV-1/C patients (P< .01). The pattern of MTB-induced RANTES production was similar to that of MIP-1alpha. However, MTB induced greater expression of mRNA for CCR5 in PBMC of HIV-1/PTB patients than in those of HIV-1/C patients (P< .04). Furthermore, the MTB-induced HIV p24 antigen level in PBMC of HIV-1/PTB patients with a CD4 cell count <500 cells/microL was higher (P< .05) than that in HIV-1/C patients. Thus, perturbations in chemokine pathways in HIV-1/PTB patients may accelerate HIV-1 disease.
Liver fibrosis: non‐invasive assessment with MR elastography

The aim of this study was to assess the feasibility of using non‐invasive MR elastography for determining the stage of liver fibrosis. Twenty‐five consecutive patients who had liver biopsy for suspicion of chronic liver disease were included in the study. The stage of fibrosis on the biopsies was assessed according to the METAVIR scoring system from F0, no fibrosis, to F4, cirrhosis. MR elastography was performed by transmitting low‐frequency (65 Hz) mechanical waves into the liver with a transducer placed at the back of the patients. The MR pulse sequence was a motion‐sensitized spin‐echo sequence, phase‐locked to the mechanical excitation. The phase maps were processed to obtain shear elasticity and shear viscosity maps. The mean hepatic shear elasticity increased with increasing stage of fibrosis. The mean elasticity was 2.24 ± 0.23 kPa in the 11 patients without substantial fibrosis (F0–F1 grades), 2.56 ± 0.24 kPa in the four patients with substantial fibrosis (F2–F3) and 4.68 ± 1.61 kPa in the 10 patients with cirrhosis (F4). The differences between groups were statistically significant (p ≤ 0.05). The mean shear viscosity was significantly higher in the patients with cirrhosis (5.19 ± 1.85 Pa · s) than in the patients without cirrhosis (2.39 ± 0.86 Pa · s in F0–F1 and 2.27 ± 0.38 Pa · s in F2–F3 patients). It is concluded that non‐invasive MR elastography is a feasible method to assess the stage of liver fibrosis. Copyright © 2006 John Wiley & Sons, Ltd.
Sampling Evolving Ego-Networks with forgetting Factor

Dynamically evolving networks get humongous in no time. Usually, sampling techniques are used to create representative specimens of such large scale socio-centric temporal networks. Likewise, the size of ego networks gets larger over a period of evolution. Which is why, there is a need to sample ego-centric networks while maintaining the importance and efficiency of the ego. In this paper, we present a novel method to sample ego networks as they evolve, while maintaining the freshness of the ego network, with the latest ties and most stronger relationships from past, based on an attenuation factor. We made use of an exhaustive list of node level and graph level metrics to evaluate and compare the samples with the original network. Our experiments show that the proposed method maintains most active and recent nodes. It also preserves the strength of ties between them. We find that our method decreases the redundancy while maintaining the efficiency of network. We also analysed the evolution of an ego network over a period of 31 days.
Robust Human-Computer Interaction System Guiding a User by Providing Feedback

We introduce a human-computer interaction system which collaborates with a user by providing feed-back during user activities. The goal of the system is to help a user complete a high-level activity that has been represented hierarchically. While a user is performing the high-level activity, our system analyzes what sub-events a user has already completed and what sub-events are needed next in order for the user to finish the activity. The representations of human activities are constructed using a previously developed context-free grammar based representation scheme. We focus on a game named 'pentagram game' to illustrate our system. In the experiments, our system showsthe ability to guide the user to complete the 'pentagram game' by providing explicit feedback. The feedback not only contains atomic level instructions but also describes higher-level long-term goals of the composite activities.
From Ordinary Differential Equations to Structural Causal Models: the deterministic case

We show how, and under which conditions, the equilibrium states of a first-order Ordinary Differential Equation (ODE) system can be described with a deterministic Structural Causal Model (SCM). Our exposition sheds more light on the concept of causality as expressed within the framework of Structural Causal Models, especially for cyclic models.
Detection of Major ASL Sign Types in Continuous Signing For ASL Recognition

In American Sign Language (ASL) as well as other signed languages, different classes of signs (e.g., lexical signs, fingerspelled signs, and classifier constructions) have different internal structural properties. Continuous sign recognition accuracy can be improved through use of distinct recognition strategies, as well as different training datasets, for each class of signs. For these strategies to be applied, continuous signing video needs to be segmented into parts corresponding to particular classes of signs. In this paper we present a multiple instance learning-based segmentation system that accurately labels 91.27% of the video frames of 500 continuous utterances (including 7 different subjects) from the publicly accessible NCSLGR corpus (Neidle and Vogler, 2012). The system uses novel feature descriptors derived from both motion and shape statistics of the regions of high local motion. The system does not require a hand tracker.
Polarization reconfigurable omni-directional antenna combining monopole and loop radiators

A novel polarization reconfigurable omni-directional antenna is proposed in this paper. By adopting a coaxial probe which acts as the monopole and printed spoke-like metal strips fabricated on two substrates which act as the loop, the omni-directional circularly polarized (CP) wave can be generated in the azimuthal plane. To make the antenna polarization reconfigurable, 48 PIN diodes are placed on the two substrates to alter the current direction of the loop. An additional DC bias network is used to bias the diodes. The polarization status can be switched between RHCP and LHCP. The measured -10 dB impedance bandwidth is 25% and 26% and the average axial ratio (AR) is 2.33 dB and 2.45 dB for RHCP and LHCP in the azimuthal plane.
Diffusion‐weighted magnetic resonance imaging in patients with partial status epilepticus

Purpose: Diffusion‐weighted magnetic resonance imaging (DWI) is used to detect changes in the distribution of water molecules in regions affected by various pathologies. Like other conditions, ictal epileptic activity, such as status epilepticus (SE), can cause regional vasogenic/cytotoxic edema that reflects hemodynamic and metabolic changes. This study describes the electroclinical and neuroimaging findings in 10 patients with partial SE whose DWI evaluation disclosed periictal changes related to sustained epileptic activity.
Rarest-first and coding are not enough

Network coding has been applied successfully in peer-to-peer (P2P) systems to shorten the distribution time. Pieces of data, i.e. blocks, are combined, i.e. encoded, by the sending peers before forwarding to other peers. Even though requiring all peers to encode might achieve shortest distribution time, it is not necessarily optimal in terms of computational resource consumption. Short finish time, in many cases, can be achieved with just a subset of carefully chosen peers. P2P systems, in addition, tend to be heterogeneous in which some peers, such as hand-held devices, would not have the required capacity to encode. We therefore envision a P2P system where some peers encode to improve distribution time and other peers, due to limited computational capacity or due to some system-wide optimization, do not encode. Such a system gives rise to a block-selection problem which has never happened in both pure non-coding and full network coding-enabled P2P systems. We identify the problem and fix the current block-selection algorithm to address it. Simulation evaluation confirms the effectiveness of our proposed algorithm without which the system performance degrades considerably.
Electric‐Field‐Assisted Growth of Highly Uniform and Oriented Gold Nanotriangles on Conducting Glass Substrates

A method for the growth of highly aligned gold nanotriangles (NTs) on conducting glass surfaces is described. This may be described as 'potential-assisted seed mediated growth'. Atomic force microscopy confirms that all the triangles observed are equilateral and are uniformly stacked. The NT-coated glass exhibits intense near-infrared absorption and strong surface-enhanced Raman activity.
Antimicrobial/Antimold Polymer-Grafted Starches for Recycled Cellulose Fibers

In this work, an antimicrobial guanidine polymer (PHGH) was grafted onto starch as a carrier to form branched or grafted chains along the starch backbone. This grafting improved the antimicrobial properties and the adsorption of the starch on recycled cellulose fibers. Similar work was also conducted on bleached sulfite fibers for comparison. The results showed that the starch, grafted with 12 wt% PHGH, adsorbed more on recycled fibers than on sulfite fibers. By applying the antimicrobial-modified starch to recycled or sulfite pulps up to 20 mg/g, both antimicrobial and antimold performances of the papers were improved substantially. Additionally, the PHGH-modified starch increased the tensile index of papers, but decreased the tear index slightly. Scanning electron microscopy (SEM) and atomic force microscopy (AFM) were employed to investigate the morphologic changes of Escherichia coli bacteria and Chaetomium globosum fungi upon exposure to the PHGH-modified starch, thus demonstrating that the antimicrobial mechanism is based on the damage of bacterial membrane.
The exposure of cancer cells to hyperthermia, iron oxide nanoparticles, and mitomycin C influences membrane multidrug resistance protein expression levels

Purpose The presence of multidrug resistance-associated protein (MRP) in cancer cells is known to be responsible for many therapeutic failures in current oncological treatments. Here, we show that the combination of different effectors like hyperthermia, iron oxide nanoparticles, and chemotherapeutics influences expression of MRP 1 and 3 in an adenocarcinoma cell line. Methods BT-474 cells were treated with magnetic nanoparticles (MNP; 1.5 to 150 μg Fe/cm2) or mitomycin C (up to 1.5 μg/cm2, 24 hours) in the presence or absence of hyperthermia (43°C, 15 to 120 minutes). Moreover, cells were also sequentially exposed to these effectors (MNP, hyperthermia, and mitomycin C). After cell harvesting, mRNA was extracted and analyzed via reverse transcription polymerase chain reaction. Additionally, membrane protein was isolated and analyzed via sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and immunoblotting. Results When cells were exposed to the effectors alone or to combinations thereof, no effects on MRP 1 and 3 mRNA expression were observed. In contrast, membrane protein expression was influenced in a selective manner. The effects on MRP 3 expression were less pronounced compared with MRP 1. Treatment with mitomycin C decreased MRP expression at high concentrations and hyperthermia intensified these effects. In contrast, the presence of MNP only increased MRP 1 and 3 expression, and hyperthermia reversed these effects. When combining hyperthermia, magnetic nanoparticles, and mitomycin C, no further suppression of MRP expression was observed in comparison with the respective dual treatment modalities. Discussion The different MRP 1 and 3 expression levels are not associated with de novo mRNA expression, but rather with an altered translocation of MRP 1 and 3 to the cell membrane as a result of reactive oxygen species production, and with shifting of intracellular MRP storage pools, changes in membrane fluidity, etc, at the protein level. Our results could be used to develop new treatment strategies by repressing mechanisms that actively export drugs from the target cell, thereby improving the therapeutic outcome in oncology.
Noise Analysis and Simulation of Chopper Amplifier

Conventional SPICE-like simulators are not adequate for the noise simulation of the chopper amplifier, which typically has no DC operating point. This paper discusses the noise properties of the chopper amplifier in both time domain and frequency domain and presents a method of simulating chopper amplifier noise behavior with the RF simulator-SpectreRF. The simulation results for a designed circuit are given. A comparison between the simulation and the calculation results shows effectiveness and efficiency of this method in dealing with chopper amplifier noise simulation
Nocturnal water loss in mature subalpine Eucalyptus delegatensis tall open forests and adjacent E. pauciflora woodlands

We measured sap flux (S) and environmental variables in four monospecific stands of alpine ash (Eucalyptus delegatensis R. Baker, AA) and snowgum (E. pauciflora Sieb. ex Spreng., SG) in Australia's Victorian Alps. Nocturnal S was 11.8 ± 0.8% of diel totals. We separated transpiration (E) and refilling components of S using a novel modeling approach based on refilling time constants. The nocturnal fraction of diel water loss (fn) averaged 8.6 ± 0.6% for AA and 9.8 ± 1.7% for SG; fn differed among sites but not species. Evaporative demand (D) was the strongest driver of nocturnal E (En). The ratio En/D (Gn) was positively correlated to soil moisture in most cases, whereas correlations between wind speed and Gn varied widely in sign and strength. Our results suggest (1) the large, mature trees at our subalpine sites have greater fn than the few Australian native tree species that have been studied at lower elevations, (2) AA and SG exhibit similar fn despite very different size and life history, and (3) fn may differ substantially among sites, so future work should be replicated across differing sites. Our novel approach to quantifying fn can be applied to S measurements obtained by any method.
Flexible Voltage Support Control for Three-Phase Distributed Generation Inverters Under Grid Fault

Ancillary services for distributed generation (DG) systems become a challenging issue to smartly integrate renewable-energy sources into the grid. Voltage control is one of these ancillary services which can ride through and support the voltage under grid faults. Grid codes from the transmission system operators describe the behavior of the energy source, regulating voltage limits and reactive power injection to remain connected and support the grid under fault. On the basis that different kinds of voltage sags require different voltage support strategies, a flexible control scheme for three-phase grid-connected inverters is proposed. In three-phase balanced voltage sags, the inverter should inject reactive power in order to raise the voltage in all phases. In one- or two-phase faults, the main concern of the DG inverter is to equalize voltages by reducing the negative symmetric sequence and clear the phase jump. Due to system limitations, a balance between these two extreme policies is mandatory. Thus, over- and undervoltage can be avoided, and the proposed control scheme prevents disconnection while achieving the desired voltage support service. The main contribution of this work is the introduction of a control algorithm for reference current generation that provides flexible voltage support under grid faults. Two different voltage sags have been experimentally tested to illustrate the behavior of the proposed voltage support control scheme.