Miracle-dz/UniFAR-FTUs huggingface dataset:
Particle Filtering for Multiple Object Tracking in Molecular Cell Biology

Motion analysis of subcellular structures in living cells is currently a major topic in molecular cell biology, for which computerized methods are desperately needed. In this paper we adopt and tailor particle filtering techniques for this purpose and present the results of robust and accurate tracking of multiple objects in real fluorescence microscopy image data acquired for specific biological studies. Experimental results demonstrate that the automated method produces results comparable to manual tracking but using only a fraction of the manual tracking time.
A Handheld High-Sensitivity Micro-NMR CMOS Platform With B-Field Stabilization for Multi-Type Biological/Chemical Assays

We report a micro-nuclear magnetic resonance (NMR) system compatible with multi-type biological/chemical lab-on-a-chip assays. Unified in a handheld scale (dimension: 14 × 6 × 11 cm3, weight: 1.4 kg), the system is capable to detect <;100 pM of Enterococcusfaecalis derived DNA from a 2.5 μL sample. The key components are a portable magnet (0.46 T, 1.25 kg) for nucleus magnetization, a system PCB for I/O interface, an FPGA for system control, a current driver for trimming the magnetic (B) field, and a silicon chip fabricated in 0.18 μm CMOS. The latter, integrated with a current-mode vertical Hall sensor and a low-noise readout circuit, facilitates closed-loop B-field stabilization (2 mT → 0.15 mT), which otherwise fluctuates with temperature or sample displacement. Together with a dynamic-B-field transceiver with a planar coil for micro-NMR assay and thermal control, the system demonstrates: 1) selective biological target pinpointing; 2) protein state analysis; and 3) solvent-polymer dynamics, suitable for healthcare, food and colloidal applications, respectively. Compared to a commercial NMR-assay product (Bruker mq-20), this platform greatly reduces the sample consumption (120×), hardware volume (175×), and weight (96×).
A trainable trajectory formation model TD-HMM parameterized for the LIPS 2008 challenge

We describe here the trainable trajectory formation model that will be used for the LIPS'2008 challenge organized at InterSpeech'2008. It predicts articulatory trajectories of a talking face from phonetic input. It basically uses HMM-based synthesis but asynchrony between acoustic and gestural boundaries - taking for example into account non audible anticipatory gestures - is handled by a phasing model that predicts the delays between the acoustic boundaries of allophones to be synthesized and the gestural boundaries of HMM triphones. The HMM triphones and the phasing model are trained simultaneously using an iterative analysissynthesis loop. Convergence is obtained within a few iterations. Using different motion capture data, we demonstrate here that the phasing model improves significantly the prediction error and captures subtle ontextdependent anticipatory phenomena
The Use of Melodic and Rhythmic Mnemonics To Improve Memory and Recall in Elementary Students in the Content Areas

5 INTRODUCTION 6 STATEMENT OF PROBLEM 7 PURPOSE STATEMENT 7 RESEARCH QUESTIONS 8 THEORETICAL RATIONALE 9 ASSUMPTIONS 10 BACKGROUND AND NEED 11 REVIEW OF THE LITERATURE 13 REVIEW OF THE PREVIOUS RESEARCH 13 HISTORICAL CONTEXT 13 RESEARCH FROM THE MEDICAL PERSPECTIVE 13 RESEARCH FROM THE CLASSROOM AND LEARNING ENVIRONMENT 15 SUMMARY OF MAJOR THEMES 18 HOW PRESENT STUDY WILL EXTEND LITERATURE 19 DISCUSSION 20 SUMMARY OF MAJOR FINDINGS 20 LIMITATIONS/GAPS IN THE LITERATURE 20 IMPLICATIONS FOR FUTURE RESEARCH 21 OVERALL SIGNIFICANCE OF THE LITERATURE 21 BACKGROUND INFORMATION 22 ALTERNATIVE VIEWPOINTS 22 INSTRUCTIONAL APPLICATION 23
Interior layered deposits within a perched basin, southern Coprates Chasma, Mars: Evidence for their formation, alteration, and erosion

A basinA¢Â�Â�like area containing three interior layer deposits (ILDs) on the southern margin of Coprates Chasma was studied. We interpret the area as an ancestral basin and demonstrate that ILD deposition postdates the formation of the current wall rock slopes. The geometry of the ILD and the wall rock spurs form a catchment area between each ILD and the plateau to the south. Erosional remnants of extensive ash or dust layers deposited on the plateau south of Valles Marineris also crop out on the southern plateau of Coprates Chasma. A mass balance calculation suggests that the volume of each ILD is compatible with the volume of the ash or dust that would have been deposited within each catchment area. We propose that the ILDs likely formed by episodically washing such aerially deposited material down from chasma walls. Rifting of the IusA¢Â�Â�MelasA¢Â�Â�Coprates graben opened the enclosed basin and removed any standing water. Faults within the ILDs are compatible with this chasm opening. Sulfates are associated with the ILDs and lightA¢Â�Â�toned material on the basin floor. We suggest that they result from water alteration of preexisting deposits, though the timing of that alteration may predate or postdate the breaching of the basin. Scours within one ILD are similar to terrestrial glacial scours. During a period of high obliquity ice would accumulate in this region; hence we argue the scours are Martian glacial scours. A late deposited layer marks the end of the active local geological history between 100 My and 1 Gy.
Vagueness , Tolerance and Non-Transitive

Vagueness is standardly opposed to precision. Just as gradable adjectives like ‘tall’ and a quantity modifier like ‘a lot’ are prototypically vague expressions, mathematical adjectives like ‘rectangular’, and measure phrases like ‘1.80 meters’ are prototypically precise. But what does it mean for these latter expressions to be precise? On first thought it just means that they have an exact mathematical definition. However, if we want to use these terms to talk about observable objects, it is clear that these mathematical definitions would be useless: if they exist at all, we cannot possibly determine what are the existing (non-mathematical) rectangular objects in the precise geometrical sense, or objects that are exactly 1.80 meters long. For this reason, one allows for a margin of measurement error, or a threshold, in physics, psychophysics and other sciences. The assumption that the predicates we use are observational predicates gives rise to another consequence as well. If statements like ‘the length of stick S is 1.45 meters’ come with a large enough margin of error, the circumstances in which this statement is appropriate (or true, if you don’t want the notion of truth to be empty) might overlap with the appropriate circumstances for uttering statements like ‘the length of stick S is 1.50 meters’. Thus, although the predicates ‘being a stick of 1.45 meters’ and ‘being a stick of 1.50 meters’ are inconsistent under a precise interpretation, the predicates might well be applicable to the same object when a margin of error is taken into account, i.e., when the predicates are interpreted tolerantly.2 Thus, although the standard, i.e. precise, semantic meanings of two predicates might be incompatible, when one or both of these observational predicates are more realistically interpreted in a tolerant way, they might well be compatible.
EMG Signal Classification for Myoelectric Teleoperating a Dexterous Robot Hand

This paper details a strategy of discriminating finger motions using surface electromyography (EMG) signals, which could be applied to teleoperating a dexterous robot hand or controlling the advanced multi-fingered myoelectric prosthesis for hand amputees. Finger motions discrimination is the key problem in this study. Thus the emphasis is put on myoelectric signal processing approaches in this paper. The EMG signal classification system was established based on the surface EMG signals from the subject's forearm. Four pairs of electrodes were attached on the subjects to acquire the signals during six types of finger motions, i.e. thumb extension, thumb flexion, index finger extension, index finger flexion, middle finger extension, and middle finger flexion. In order to distinguish these finger motions. A combination of autoregressive (AR) model and an artificial neural network (ANN) was used in the system. The discrimination procedure consists of two steps. Firstly, the AR model is used to preprocess the surface EMG signals to reduce the scale of the data. These data will be imported into the myoelectric pattern classifier. Secondly the coefficients of AR model are imported into the ANN to identify the finger motions. The experimental results show that the discrimination system works with satisfaction
Segmentation of unorganized point cloud from terrestrial laser scanner in urban region

Segmentation of unorganized point cloud is the key procedure of 3D model construction. And also the problem of management of massive point clouds can be manipulated with segmentation techniques. Global segmentation parameters and metrics are the most essential and difficulty parts of segmentation algorithm, especially in urban region. An optimization solution for segmentation of unorganized point cloud is presented, which is based on several estimated geometry properties, using fuzzy clustering algorithms, and extracts geometry features and semantic features in urban area. The proposal segmentation method is tested in terms of its validity, applicability with two unorganized point clouds from terrestrial laser scanner.
Iron in Micronutrient Powder Promotes an Unfavorable Gut Microbiota in Kenyan Infants

Iron supplementation may have adverse health effects in infants, probably through manipulation of the gut microbiome. Previous research in low-resource settings have focused primarily on anemic infants. This was a double blind, randomized, controlled trial of home fortification comparing multiple micronutrient powder (MNP) with and without iron. Six-month-old, non- or mildly anemic, predominantly-breastfed Kenyan infants in a rural malaria-endemic area were randomized to consume: (1) MNP containing 12.5 mg iron (MNP+Fe, n = 13); (2) MNP containing no iron (MNP−Fe, n = 13); or (3) Placebo (CONTROL, n = 7), from 6–9 months of age. Fecal microbiota were profiled by high-throughput bacterial 16S rRNA gene sequencing. Markers of inflammation in serum and stool samples were also measured. At baseline, the most abundant phylum was Proteobacteria (37.6% of rRNA sequences). The proteobacterial genus Escherichia was the most abundant genus across all phyla (30.1% of sequences). At the end of the intervention, the relative abundance of Escherichia significantly decreased in MNP−Fe (−16.05 ± 6.9%, p = 0.05) and CONTROL (−19.75 ± 4.5%, p = 0.01), but not in the MNP+Fe group (−6.23 ± 9%, p = 0.41). The second most abundant genus at baseline was Bifidobacterium (17.3%), the relative abundance of which significantly decreased in MNP+Fe (−6.38 ± 2.5%, p = 0.02) and CONTROL (−8.05 ± 1.46%, p = 0.01), but not in MNP-Fe (−4.27 ± 5%, p = 0.4445). Clostridium increased in MNP-Fe only (1.9 ± 0.5%, p = 0.02). No significant differences were observed in inflammation markers, except for IL-8, which decreased in CONTROL. MNP fortification over three months in non- or mildly anemic Kenyan infants can potentially alter the gut microbiome. Consistent with previous research, addition of iron to the MNP may adversely affect the colonization of potential beneficial microbes and attenuate the decrease of potential pathogens.
Two new species of the land-locked freshwater shrimps genus, Neocaridina Kubo, 1938 (Decapoda : Caridea : Atyidae), from Taiwan, with notes on speciation on the island

Two new species of land-locked shrimp, Neocandina saccam and N. ketagalan (Decapoda: Caridea: Atyidae), are described from Tainan, southwestern Taiwan, and Taipei, northern Taiwan, respectively. Based on morphological and molecular (mitochondrial 16S rRNA and cytochrome oxidase I genes) evidence, both can be distinguished from their congeners. A speciation model for this genus on the island of Taiwan is also proposed based on geological events and molecular clock estimates.
Recent Advances in Biosensing With Photonic Crystal Surfaces: A Review

Photonic crystal surfaces that are designed to function as wavelength-selective optical resonators have become a widely adopted platform for label-free biosensing, and for enhancement of the output of photon emitting tags used throughout life science research and in vitro diagnostics. While some applications, such as analysis of drug-protein interactions, require extremely high resolution and the ability to accurately correct for measurement artifacts, others require sensitivity that is high enough for detection of disease biomarkers in serum with concentrations ~1 pg/ml. As the analysis of cells becomes increasingly important for studying the behavior of stem cells, cancer cells, and biofilms under a variety of conditions, approaches that enable high-resolution imaging of live cells without cytotoxic stains or photobleachable fluorescent dyes are providing new tools to biologists who seek to observe individual cells over extended time periods. This paper will review several recent advances in photonic crystal biosensor detection instrumentation and device structures that are being applied toward direct detection of small molecules in the context of high-throughput drug screening, photonic crystal fluorescence enhancement as utilized for high sensitivity multiplexed cancer biomarker detection, and label-free high-resolution imaging of cells and individual nanoparticles as a new tool for life science research and single-molecule diagnostics.
Mitogenic Response of Murine B Lymphocytes to Salmonella typhimurium Lipopolysaccharide Requires Protein Kinase C-Dependent Late Tyrosine Phosphorylations

ABSTRACT Unlike the cross-linking of membrane immunoglobulins, the activation of B cells by lipopolysaccharide (LPS) does not involve the phosphoinositol turnover and the initial activation of tyrosine kinases. However, LPS-induced B-cell proliferation was inhibited by the tyrosine kinase inhibitors genistein and herbimycin A even when added 48 h after the beginning of the culture. Tyrosyl-phosphorylated proteins were detected by Western blotting after 24 h of culture with LPS, reaching a maximum concentration after 72 h. Late tyrosine phosphorylations were also detected in B cells activated for 72 h with anti-immunoglobulin M antibody and were abrogated by the protein synthesis inhibitor cycloheximide, the tyrosine kinase inhibitors genistein and herbimycin A, and the protein kinase C inhibitor chelerythrine. The role of protein kinase C in late tyrosine kinase activation is independent of Ca2+mobilization and was confirmed by detection of a comparable but restricted pattern of tyrosine-phosphorylated substrates in B cells treated with phorbol myristate acetate alone or in association with ionomycin. Tyrosine kinase activation was dependent on de novo protein synthesis. However, culture supernatants of LPS-activated B cells were devoid of mitogenic activity and induced a phosphorylation pattern more restricted than that achieved by LPS. Altogether these data indicate that proliferation signals induced by LPS or by the cross-linking of membrane immunoglobulins are controlled by late tyrosine phosphorylations occurring throughout the first 3 days of culture, controlled in part by protein kinase C activation, and dependent on the synthesis of an intermediate protein(s) either not secreted in the culture supernatant or present but biologically inactive in naive B cells.
Permutation Entropy: New Ideas and Challenges

Over recent years, some new variants of Permutation entropy have been introduced and applied to EEG analysis, including a conditional variant and variants using some additional metric information or being based on entropies that are different from the Shannon entropy. In some situations, it is not completely clear what kind of information the new measures and their algorithmic implementations provide. We discuss the new developments and illustrate them for EEG data.
The Current State and Future of Search Based Software Engineering

This paper describes work on the application of optimization techniques in software engineering. These optimization techniques come from the operations research and metaheuristic computation research communities. The paper briefly reviews widely used optimization techniques and the key ingredients required for their successful application to software engineering, providing an overview of existing results in eight software engineering application domains. The paper also describes the benefits that are likely to accrue from the growing body of work in this area and provides a set of open problems, challenges and areas for future work.
Criteria of Stabilizability for Switching-Control Systems with Solvable Linear Approximations

We study the stability and stabilizability of a continuous-time switched control system that consists of the time-invariant $n$-dimensional subsystems \dot{x}=A_ix+B_i(x)u\quad (x\in\mathbb{R}^n, t\in\mathbb{R}_+ \textrm{and} u\in\mathbb{R}^{m_i}),\qquad \textrm{where} i\in{1,. ,N} and a switching signal $\sigma(\bcdot)\colon\mathbb{R}_+\rightarrow{1,. ,N}$ which orchestrates switching between these subsystems above, where $A_i\in\mathbb{R}^{n\times n}, n\ge1, N\ge2, m_i\ge1$, and where $B_i(\bcdot)\colon\mathbb{R}^n\rightarrow\mathbb{R}^{n\times m_i}$ satisfies the condition $\|B_i(x)\|\le\bbbeta\|x\|\;\forall x\in\mathbb{R}^n$. We show that, if ${A_1,. ,A_N}$ generates a solvable Lie algebra over the field $\mathbbm{C}$ of complex numbers and there exists an element $\bbA$ in the convex hull $\mathrm{co}{A_1,. ,A_N}$ in $\mathbb{R}^{n\times n}$ such that the affine system $\dot{x}=\bbA x$ is exponentially stable, then there is a constant $\bbdelta>0$ for which one can design "sufficiently many" piecewise-constant switching signals $\sigma(t)$ so that the switching-control systems \dot{x}(t)=A_{\sigma(t)}x(t)+B_{\sigma(t)}(x(t))u(t),\quad x(0)\in\mathbb{R}^n\textrm{and} t\in\mathbb{R}_+ are globally exponentially stable, for any measurable external inputs $u(t)\in\mathbb{R}^{m_{\sigma(t)}}$ with $|u(t)|\le\bbdelta$.
Object Tracking Based on Genetic Algorithm and Kalman Filter

Robust object tracking is quite important in computer vision. In this paper, a novel tracking approach for single object which combines genetic algorithm and Kalman filter is proposed. Genetic algorithm is introduced and reasonably applied to find the tracked object in a search area. A further step called multi-blocks voting is exploited for obtaining more accurate object localization. Kalman filter is exploited to both estimate the position of object center and cope with temporary occlusion. Results on real sequences and comparisons with other standard techniques demonstrate the effectiveness of the proposed algorithm.
UW-ISL document image analysis toolbox: an experimental environment

A document image analysis toolbox including a collection of data structures and algorithms to support a variety of applications, is described in this paper. An experimental environment is built to allow developers to develop, test and optimize their algorithms and systems. Appropriate and quantitative performance metrics for each kind of information a document analysis technique infers have been developed. The performance of each algorithm has been evaluated based on these metrics and the UW-III document image database which contains a total of 1600 English document images randomly selected from scientific and technical journals.
Threshold Saturation for Spatially Coupled LDPC and LDGM Codes on BMS Channels

Spatially-coupled low-density parity-check (LDPC) codes, which were first introduced as LDPC convolutional codes, have been shown to exhibit excellent performance under low-complexity belief-propagation decoding. This phenomenon is now termed threshold saturation via spatial coupling. Spatially-coupled codes have been successfully applied in numerous areas. In particular, it was proven that spatially-coupled regular LDPC codes universally achieve capacity over the class of binary memoryless symmetric (BMS) channels under belief-propagation decoding. Recently, potential functions have been used to simplify threshold saturation proofs for scalar and vector recursions. In this paper, potential functions are used to prove threshold saturation for irregular LDPC and low-density generator-matrix codes on BMS channels, extending the simplified proof technique to BMS channels. The corresponding potential functions are closely related to the average Bethe free entropy of the ensembles in the large-system limit. These functions also appear in statistical physics when the replica method is used to analyze optimal decoding.
Ankylosing Spondylitis Patients with HLA-B*2704 have More Uveitis than Patients with HLA-B*2705 in a North Chinese Population

ABSTRACT Purpose: To investigate the correlation between clinical features of ankylosing spondylitis (AS) and different human leukocyte antigen (HLA)-B27 subtypes. Methods: We conducted a cross-sectional study of 216 patients with AS. HLA-B27 and its subtypes were detected by polymerase chain reaction with sequence specific primer (PCR-SSP). Clinical features were compared between the different HLA-B27 subtypes. A meta-analysis on uveitis frequencies in AS patients with HLA-B*2705 vs 2704 was performed. Results: The most prevalent subtypes of HLA-B27 were HLA-B*2704 (66.1%) and HLA-B*2705 (32.2%). There were 57 HLA-B27-positive AS patients with the history of uveitis; 45 were B*2704 and 12 were B*2705. Patients with B*2704 had more uveitis than B*2705 (p = 0.021). After meta-analysis, there was no significant difference in the presence of uveitis between HLA-B*2704 and HLA-B*2705. Conclusions: AS patients with B*2704 have a higher risk of uveitis than AS with B*2705 in a north Chinese people.
FactorBase: SQL for Learning A Multi-Relational Graphical Model

We describe FactorBase, a new SQL-based framework that leverages a relational database management system to support multi-relational model discovery. A multi-relational statistical model provides an integrated analysis of the heterogeneous and interdependent data resources in the database. We adopt the BayesStore design philosophy: statistical models are stored and managed as first-class citizens inside a database. Whereas previous systems like BayesStore support multi-relational inference, FactorBase supports multi-relational learning. A case study on six benchmark databases evaluates how our system supports a challenging machine learning application, namely learning a first-order Bayesian network model for an entire database. Model learning in this setting has to examine a large number of potential statistical associations across data tables. Our implementation shows how the SQL constructs in FactorBase facilitate the fast, modular, and reliable development of highly scalable model learning systems.