Miracle-dz/UniFAR-FTUs huggingface dataset:
Mesenchymal Stem Cells Obtained from Synovial Fluid Mesenchymal Stem Cell-Derived Induced Pluripotent Stem Cells on a Matrigel Coating Exhibited Enhanced Proliferation and Differentiation Potential

Induced pluripotent stem cell-derived mesenchymal stem cells (iPSC-MSCs) serve as a promising source for cell-based therapies in regenerative medicine. However, optimal methods for transforming iPSCs into MSCs and the characteristics of iPSC-MSCs obtained from different methods remain poorly understood. In this study, we developed a one-step method for obtaining iPSC-MSCs (CD146+STRO-1+ MSCs) from human synovial fluid MSC-derived induced iPSCs (SFMSC-iPSCs). CD146-STRO-1-SFMSCs were reprogrammed into iPSCs by transduction with lentivirus-mediated Sox2, Oct-3/4, klf4, and c-Myc. SFMSC-iPSCs were maintained with mTeSR1 medium in Matrigel-coated culture plates. Single dissociated cells were obtained by digesting the SFMSC-iPSCs with trypsin. The dissociated cells were then plated into Matrigel-coated culture plate with alpha minimum essential medium supplemented with 10% fetal bovine serum, 1× Glutamax, and the ROCK inhibitor Y-27632. Cells were then passaged in standard cell culture plates with alpha minimum essential medium supplemented with 10% fetal bovine serum and 1× Glutamax. After passaging in vitro, the cells showed a homogenous spindle-shape similar to their ancestor cells (SFMSCs), but with more robust proliferative activity. Flow cytometric analysis revealed typical MSC surface markers, including expression of CD73, CD90, CD105, and CD44 and lack of CD45, CD34, CD11b, CD19, and HLA-DR. However, these cells were positive for CD146 and stro-1, which the ancestor cells were not. Moreover, the cells could also be induced to differentiate in osteogenic, chondrogenic, and adipogenic lineages in vitro. The differentiation potential was improved compared with the ancestor cells in vitro. The cells were not found to exhibit oncogenicity in vivo. Therefore, the method presented herein facilitated the generation of STRO-1+CD146+ MSCs from SFMSC-iPSCs exhibiting enhanced proliferation and differentiation potential.
Learning intrinsic excitability in medium spiny neurons

We present an unsupervised, local activation-dependent learning rule for intrinsic plasticity (IP) which affects the composition of ion channel conductances for single neurons in a use-dependent way. We use a single-compartment conductance-based model for medium spiny striatal neurons in order to show the effects of parameterization of individual ion channels on the neuronal membrane potential-curent relationship (activation function). We show that parameter changes within the physiological ranges are sufficient to create an ensemble of neurons with significantly different activation functions. We emphasize that the effects of intrinsic neuronal modulation on spiking behavior require a distributed mode of synaptic input and can be eliminated by strongly correlated input. We show how modulation and adaptivity in ion channel conductances can be utilized to store patterns without an additional contribution by synaptic plasticity (SP). The adaptation of the spike response may result in either "positive" or "negative" pattern learning. However, read-out of stored information depends on a distributed pattern of synaptic activity to let intrinsic modulation determine spike response. We briefly discuss the implications of this conditional memory on learning and addiction.
Varied Persistent Life Cycles of Borna Disease Virus in a Human Oligodendroglioma Cell Line

ABSTRACT Borna disease virus (BDV) establishes a persistent infection in the central nervous system of vertebrate animal species as well as in tissue cultures. In an attempt to characterize the life cycle of BDV in persistently infected cultured cells, we developed 30 clones by single-cell cloning from a human oligodendroglioma (OL) cell line after infection with BDV. According to the percentage of cells expressing the BDV major proteins, p40 (nucleoprotein) and p24 (phosphoprotein), the clones were classified into two types: type I (>20%) and type II (<20%). mRNAs corresponding to both proteins were detected by in situ hybridization (ISH) in a percentage of cells consistent with that for the protein expression in the two types. Surprisingly, ISH for the detection of the genomic RNA, mainly in type II, revealed a significantly larger cell population harboring the genomic RNA than that with the protein as well as the mRNA expression. By recloning from type II primary cell clones, the same phenotype was confirmed in the secondary cell clones obtained: i.e., low percentage of protein-positive cells and higher percentage of cells harboring the genomic RNA. After nerve growth factor treatment, the two types of clones showed increases in the percentage of cells expressing BDV-specific proteins that reached 80% in type II clones, in addition to increased expression levels per cell. Such enhancement might have been mediated by the activation of the mitogen-activated protein kinase in the clones as revealed by the detection of activated ERK1/2. Thus, our findings show that BDV may have established a persistent infection at low levels of viral expression in OL cells with the possibility of a latent infection.
Evaluation of feature extraction techniques in emotional state recognition

We present in this paper a study of three EEG signals feature extraction techniques. These techniques have been widely employed in researches of emotional states recognition: statistical characteristics, features based on PSD (Power Spectral Density) and features based on HOC (High Order Crossings). The validation was performed via classification of emotional states of calm and stress using the K-NN based classifier in off-line mode using EEG signals from available DEAP database. The best results achieved were 70.1%, using the PSD based technique, and 69.59% using the HOC based technique.
Timed uniform consensus resilient to crash and timing faults

/spl Delta/-timed uniform consensus is a stronger variant of the traditional consensus and it satisfies the following additional property: The correct process terminates its execution within a constant time /spl Delta/ (/spl Delta/-timeliness), and no two processes decide differently (uniformity). In this paper, we consider the /spl Delta/-timed uniform consensus problem in presence of f/sub t/ crash processes and f/sub c/ timing-faulty processes. This paper proposes a /spl Delta/-timed uniform consensus algorithms. The proposed algorithm is adaptive in the following sense: It solves the /spl Delta/-timed uniform consensus when at least f/sub t/ + 1 correct processes exist in the system. If the system has less than f/sub t/ + 1 correct processes, the algorithm cannot solve the /spl Delta/-timed uniform consensus. However, as long as f/sub t/ + 1 processes are non-crashed, the algorithm solves (non-timed) uniform consensus. We also investigate the maximum number of faulty processes that can be tolerated. We show that any /spl Delta/-timed uniform consensus algorithm tolerating up to f/sub t/ timing-faulty processes requires that the system has at least f/sub t/ + 1 correct processes. This impossibility result implies that the proposed algorithm attains the maximal resilience about the number of faulty processes. We also show that any /spl Delta/-timed uniform consensus algorithm tolerating up to f/sub t/ timing-faulty processes cannot solve the (non-timed) uniform consensus when the system has less than f/sub t/ + 1 non-crashed processes. This impossibility result implies that our algorithm attains the maximum adaptiveness.
Location aided broadcast in wireless ad hoc networks

Building efficient ad hoc networks for wireless communications is challenging due to the dynamic nature of the hosts. Broadcast service in ad hoc networks is critical in supporting various applications and protocols. However, excessive redundant retransmissions of traditional broadcast protocols in mobile wireless ad hoc networks have caused the infamous "broadcast storm problem. " Various broadcast protocols have been proposed to alleviate the broadcast storm problem. We identify two primary design issues, namely defer time generation and redundant message classification, for all these protocols. We propose a distance-based defer time scheme for the first issue and an angle-based scheme for the second issue. The two schemes together result in a broadcast protocol that enjoys flooding's high reachability and non-flooding schemes' bandwidth efficiency.
Confusability of Phonemes Grouped According to their Viseme Classes in Noisy Environments

Using visual information, such as lip shapes and movements, as the secondary source of speech information has been shown to make speech recognition systems more robust to problems associated with environmental noise, training/testing mismatch and channel and speech style variations. Research into utilising visual information for speech recognition has been ongoing for 20 years, however over this period, a study into which visual information is the most useful or pertinent to improving speech recognition systems has yet to be performed. This paper presents a study to determine the confusability of the phonemes grouped into their viseme classes over various levels of noise in the audio domain. The rationale behind this approach is that by establishing the interclass confusion for a group of phonemes in their viseme class, a better understanding can be obtained on the complementary nature of the separate audio and visual information sources and this can be subsequently applied in the fusion stage of an audio-visual speech processing (AVSP) system. The experiments performed show high interclass confusion variability at the 0dB and -6dB SNR levels. Further analysis found that this was mainly due to a phonetic imbalance in the dataset. Due to this result, it was suggested that it would be appropriate for an AVSP system used for digit recognition applications heavily weight the visual modality for the phonemes that are most prevalent such as the phoneme N.
An asynchronous time-based image sensor

In this paper we propose a fully asynchronous, time- based image sensor, which is characterized by high temporal resolution, low data rate (near complete temporal redundancy suppression), high dynamic range, and low power consumption. Autonomous pixels asynchronously communicate the detection of relative changes in light intensity, and the time from change detection to the threshold crossing of a photocurrent integrator, so encoding the instantaneous pixel illumination shortly after the time of a detected change. The chip is being implemented in a standard 0.18 mum CMOS process and measures less than 10times8 mm2 at 304times240 pixel resolution.
The Optimization of Direct Digital Frequency Synthesizer Performance by New Approximation Technique

In this study, an optimized Direct Digital Frequency Synthesizer (DDFS) utilizing Piecewise Linear Approximation is introduced. The proposed technique allows successive read access to memory cells per one clock cycle using time sharing. The output values will be temporarily stored and read at a later time. The output of this system is a reconstructed signal that is a good approximation of the desired waveform. As a result, the DDFS only needs to store fewer coefficients and the hardware complexity is significantly reduced. The proposed DDFS has been analyzed using MATLAB. The SFDR of synthesized achieved is 84.2 dBc. To prove the better performance of proposed DDS architecture it is compared favorably with several existing DDS architectures. In future it can also be used to improve the performance of Hybrid DDS-PLL Synthesizers.
Detection of Leptospira DNA in Patients with Aseptic Meningitis by PCR

ABSTRACT Samples of cerebrospinal fluid from 103 patients with aseptic meningitis were tested by PCR for detection of leptospires, and the results were compared with those of the microscopic agglutination test (MAT) and an enzyme-linked immunosorbent assay for detection of immunoglobulin M (ELISA-IgM). Of these samples, 39.80% were positive by PCR and 8.74 and 3.88% were positive by MAT and ELISA-IgM, respectively.
Towards Dynamic Random Testing for Web Services

In recent years, Service Oriented Architecture (SOA) has been increasingly adopted to develop applications in the context of Internet. To develop reliable SOA-based applications, an important issue is how to ensure the quality of Web services. In this paper, we propose a dynamic random testing (DRT) technique for Web services which is an improvement of the widely practiced random testing. We examine key issues when adapting DRT to the context of SOA and develop a prototype for such an adaptation. Empirical studies are reported where DRT is used to test two real-life Web services and mutation analysis is employed to measure the effectiveness. The experimental results show that DRT can save up to 24% test cases in terms of detecting the first seeded fault, and up to 21% test cases in terms of detecting all seeded faults, both with the cases of uniformed mutation analysis and distribution-aware mutation analysis, which refer to faults being seeded in an even or clustered way, respectively. The proposed DRT and the prototype provide an effective approach to testing Web Services.
Fatty acylation promotes fusion of transport vesicles with Golgi cisternae

Two different methods, stimulation of transport by fatty acyl-coenzyme A (CoA) and inhibition of transport by a nonhydrolyzable analogue of palmitoyl-CoA, reveal that fatty acylation is required to promote fusion of transport vesicles with Golgi cisternae. Specifically, fatty acyl-CoA is needed after the attachment of coated vesicles and subsequent uncoating of the vesicles, and after the binding of the NEM- sensitive fusion protein (NSF) to the membranes, but before the actual fusion event. We therefore suggest that an acylated transport component participates, directly or indirectly, in membrane fusion.
ORTHOGONAL WAVEFORMS FOR LARGE MIMO SONAR SYSTEMS

MIMO stands for Multiple Inputs Multiple Outputs. Such systems have been developed at first for radar applications. MIMO have recently gained interest in the underwater acoustic community because of certain benefits over traditional systems such as increase resolution or increase in signal to clutter ratio to name a few. The MIMO concept relies on multiple transmitters (Nt) sending unique and orthogonal waveforms through the environment. Several receivers (Nr) then capture environment, targets or clutter echoes. At each receiver point the total signal is filtered to separate each transmitter signal. The stage at which MIMO systems separate from multi-static systems is at the information processing stage (done centrally rather that separately at each receiver node). Accessing the Nt × Nr signals requires the orthogonality of the out-coming pulses. As purely orthogonal waveforms do not exist, different approaches were developed to minimise the waveform cross-correlation. Such methods include TDMA (time division multiple access) where waveforms share the same frequency band, but at different times, FDMA (frequency division multiple access) where waveforms occupy different frequencies at the same time, or CDMA (code division multiple access) where waveforms share the same frequencies at the same time. In this paper we review the three main classes of orthogonal waveforms proposed for radar applications. We examine their implications and restrictions for sonar systems. We finally propose a novel CDMA design: the ICMS which suits large MIMO sonar systems and transducer constraints.
Multifaceted Integration: Memory for Faces Is Subserved by Widespread Connections between Visual, Memory, Auditory, and Social Networks

Our ability to recognize others by their facial features is at the core of human social interaction, yet this ability varies widely within the general population, ranging from developmental prosopagnosia to “super-recognizers”. Previous work has focused mainly on the contribution of neural activity within the well described face network to this variance. However, given the nature of face memory in everyday life, and the social context in which it takes place, we were interested in exploring how the collaboration between different networks outside the face network in humans (measured through resting state connectivity) affects face memory performance. Fifty participants (men and women) were scanned with fMRI. Our data revealed that although the nodes of the face-processing network were tightly coupled at rest, the strength of these connections did not predict face memory performance. Instead, face recognition memory was dependent on multiple connections between these face patches and regions of the medial temporal lobe memory system (including the hippocampus), and the social processing system. Moreover, this network was selective for memory for faces, and did not predict memory for other visual objects (cars). These findings suggest that in the general population, variability in face memory is dependent on how well the face processing system interacts with other processing networks, with interaction among the face patches themselves accounting for little of the variance in memory ability. SIGNIFICANCE STATEMENT Our ability to recognize and remember faces is one of the pillars of human social interaction. Face recognition however is a very complex skill, requiring specialized neural resources in visual cortex, as well as memory, identity, and social processing, all of which are inherent in our real-world experience of faces. Yet in the general population, people vary greatly in their face memory abilities. Here we show that in the neural domain this variability is underpinned by the integration of visual, memory and social circuits, with the strength of the connections between these circuits directly linked to face recognition ability.
Sampling bedrooms

We propose a top down approach for understanding indoor scenes such as bedrooms and living rooms. These environments typically have the Manhattan world property that many surfaces are parallel to three principle ones. Further, the 3D geometry of the room and objects within it can largely be approximated by non overlapping simple structures such as single blocks (e.g. the room boundary), thin blocks (e.g. picture frames), and objects that are well modeled by single blocks (e.g. simple beds). We separately model the 3D geometry, the imaging process (camera parameters), and edge likelihood, to provide a generative statistical model for image data. We fit this model using data driven MCMC sampling. We combine reversible jump Metropolis Hastings samples for discrete changes in the model such as the number of blocks, and stochastic dynamics to estimate continuous parameter values in a particular parameter space that includes block positions, block sizes, and camera parameters. We tested our approach on two datasets using room box pixel orientation. Despite using only bounding box geometry and, in particular, not training on appearance, our method achieves results approaching those of others. We also introduce a new evaluation method for this domain based on ground truth camera parameters, which we found to be more sensitive to the task of understanding scene geometry.
DL-Lite: Tractable Description Logics for Ontologies

We propose a new Description Logic, called DL-Lite, specifically tailored to capture basic ontology languages, while keeping low complexity of reasoning. Reasoning here means not only computing subsumption between concepts, and checking satisfiability of the whole knowledge base, but also answering complex queries (in particular, conjunctive queries) over the set of instances maintained in secondary storage. We show that in DL-Lite the usual DL reasoning tasks are polynomial in the size of the TBox, and query answering is polynomial in the size of the ABox (i.e., in data complexity). To the best of our knowledge, this is the first result of polynomial data complexity for query answering over DL knowledge bases. A notable feature of our logic is to allow for a separation between TBox and ABox reasoning during query evaluation: the part of the process requiring TBox reasoning is independent of the ABox, and the part of the process requiring access to the ABox can be carried out by an SQL engine, thus taking advantage of the query optimization strategies provided by current DBMSs.
Orientation-singularity and nonsingular orientation-workspace analyses of the Stewart-Gough Platform using unit quaternion representation

This paper mainly addresses the orientation-singularity analysis and the nonsingular orientation-workspace computation of the Stewart-Gough Platform. Employing a unit quaternion to represent the orientation of the moving platform, an analytical symbolic expression that represents the orientation-singularity locus of the manipulator at a fixed position is derived. It is shown that for the Stewart-Gough Platform, it must exist a singularity free orientation void in the orientation space around the orientation origin for each position in the position-workspace. Using the orientation representation and applying the inverse kinematics solution of the Stewart-Gough Platform, a discretization method is proposed for the computation of the nonsingular orientation-workspace of the Stewart-Gough Platform. Based on the research on the orientation-singularity and nonsingular orientation-workspace of the manipulator, a new concept of “practical orientation-capability” is introduced as a performance index for the orientation-capability analysis of the Stewart-Gough Platform at a certain position in the position-workspace. Examples of a 6/6-SPS Stewart-Gough Platform are given to demonstrate these theoretical results.
Active Head Tracking Using Integrated Contour and Template Matching in Indoor Cluttered Environment

Due to the fact that existing surveillance systems usually employ fixed or automatically-patrolled cameras, they cannot effectively track invaders in real-time. Therefore, an automatic head tracking system in indoor cluttered environment is proposed. This system consists of two parts, automatic head tracking system and remote monitoring and control system. In the automatic head tracking system, the position of human head on image plane can be determined based on head tracking strategy. According to the position and size of human head on image plane, a suitable fuzzy rule is designed to maintain the position of human head near image center with appropriate size by controlling the active camera via pan, tilt, and zoom. Specifically, the position of the moving object on image plane can be determined using moving object detection method. Then a sizable tracking window to track human head is used to reduce redundant computation. Moreover, color recognition, template matching, and head contour matching methods are integrated for tracking human head robustly. In order to achieve better performance, Kalman filtering is employed to predict the position of human head on image plane. The proposed active head tracking system has been successfully validated in indoor cluttered environment.