Miracle-dz/UniFAR-FTUs huggingface dataset:
Complementarity of Two Rice Mapping Approaches: Characterizing Strata Mapped by Hypertemporal MODIS and Rice Paddy Identification Using Multitemporal SAR

Different rice crop information can be derived from different remote sensing sources to provide information for decision making and policies related to agricultural production and food security. The objective of this study is to generate complementary and comprehensive rice crop information from hypertemporal optical and multitemporal high-resolution SAR imagery. We demonstrate the use of MODIS data for rice-based system characterization and X-band SAR data from TerraSAR-X and CosmoSkyMed for the identification and detailed mapping of rice areas and flooding/transplanting dates. MODIS was classified using ISODATA to generate cropping calendar, cropping intensity, cropping pattern and rice ecosystem information. Season and location specific thresholds from field observations were used to generate detailed maps of rice areas and flooding/transplanting dates from the SAR data. Error matrices were used for the accuracy assessment of the MODIS-derived rice characteristics map and the SAR-derived detailed rice area map, while Root Mean Square Error (RMSE) and linear correlation were used to assess the TSX-derived flooding/transplanting dates. Results showed that multitemporal high spatial resolution SAR data is effective for mapping rice areas and flooding/transplanting dates with an overall accuracy of 90% and a kappa of 0.72 and that hypertemporal moderate-resolution optical imagery is effective for the basic characterization of rice areas with an overall accuracy that ranged from 62% to 87% and a kappa of 0.52 to 0.72. This study has also provided the first assessment of the temporal variation in the backscatter of rice from CSK and TSX using large incidence angles covering all rice crop stages from pre-season until harvest. This complementarity in optical and SAR data can be further exploited in the near future with the increased availability of space-borne optical and SAR sensors. This new information can help improve the identification of rice areas.
Micro-Electro-Mechanical System for Measuring Mechanical Properties of Cell Aggregates

This paper presents design and finite element analysis (FEA) modeling of a novel micro-electro-mechanical system for determining mechanical properties of cell aggregates. The main components of this system are the electrostatic actuator array for applying force onto the cell aggregate and piezoresistive sensor for measuring it. A novel actuator array that allows for a set of five predefined displacements up to 100 μm was designed and modeled. FEA modeling of the components was performed to optimize the design and performance. While the device described is specifically designed for on-chip mechanical characterization of cell aggregates in vitro, it could also be translated to other applications. Application of MEMS in biomedical devices has expanded vastly over the last few decades. MEMS devices have been developed to measure different characteristics of cells. The study of cell biomechanics is of growing importance in biology and medical science, as mechanical properties of cells can be related to the cau.
Identifying Emotional Expressions, Intensities and Sentence Level Emotion Tags Using a Supervised Framework

The present work deals with the extraction of emotional expressions and tagging of English blog sentences with Ekman’s six basic emotion tags and any of the three intensities: low, medium and high. Baseline system is developed based on WordNet Affect lists and dependency relations. Support Vector Machine (SVM) based supervised framework is employed by incorporating different word and context level features. The feature analysis is carried out on 358 development sentences followed by Information Gain Based Pruning. Application of admissible tag sequences and a class-splitting technique improves the system’s performance and reduces the label bias problem of SVM. The supervised system outperforms the baseline system and achieves average F-Scores of 82.72%, 76.74% and 89.21% for emotional expressions, sentential emotion tags and intensities respectively on 565 gold standard test sentences. A comparative evaluation shows that sentential emotion tagging based on emotional expressions, intensities and context features bridges the gap of identifying sentential emotion depending only on words.
Identification of Candidate Genes for Dyslexia Susceptibility on Chromosome 18

Background Six independent studies have identified linkage to chromosome 18 for developmental dyslexia or general reading ability. Until now, no candidate genes have been identified to explain this linkage. Here, we set out to identify the gene(s) conferring susceptibility by a two stage strategy of linkage and association analysis. Methodology/Principal Findings Linkage analysis: 264 UK families and 155 US families each containing at least one child diagnosed with dyslexia were genotyped with a dense set of microsatellite markers on chromosome 18. Association analysis: Using a discovery sample of 187 UK families, nearly 3000 SNPs were genotyped across the chromosome 18 dyslexia susceptibility candidate region. Following association analysis, the top ranking SNPs were then genotyped in the remaining samples. The linkage analysis revealed a broad signal that spans approximately 40 Mb from 18p11.2 to 18q12.2. Following the association analysis and subsequent replication attempts, we observed consistent association with the same SNPs in three genes; melanocortin 5 receptor (MC5R), dymeclin (DYM) and neural precursor cell expressed, developmentally down-regulated 4-like (NEDD4L). Conclusions Along with already published biological evidence, MC5R, DYM and NEDD4L make attractive candidates for dyslexia susceptibility genes. However, further replication and functional studies are still required.
Volumetric segmentation of brain images using parallel genetic algorithms

Active model-based segmentation has frequently been used in medical image processing with considerable success. Although the active model-based method was initially viewed as an optimization problem, most researchers implement it as a partial differential equation solution. The advantages and disadvantages of the active model-based method are distinct: speed and stability. To improve its performance, a parallel genetic algorithm-based active model method is proposed and applied to segment the lateral ventricles from magnetic resonance brain images. First, an objective function is defined. Then one instance surface was extracted using the finite-difference method-based active model and used to initialize the first generation of a parallel genetic algorithm. Finally, the parallel genetic algorithm is employed to refine the result. We demonstrate that the method successfully overcomes numerical instability and is capable of generating an accurate and robust anatomic descriptor for complex objects in the human brain, such as the lateral ventricles.
Improvement of Paper Strength using Pretreated Precipitated Calcium Carbonate (PCC)

Increasing ash content of the paper is one of the most effective methods for saving raw materials and steam consumption and improving optical properties and better print quality. However, the increase of filler loading or filler content using a conventional wet end system is limited due to severe loss in strength properties, affecting runnability and product quality. This is because the filler has no ability to make bonding with cellulosic fibers. Therefore, if the technology to give filler the bonding ability is developed, the ash content of the paper can be increased more than ever. This study was carried out to modify PCC by coating its surface with starch contributing to better bonding with fibers. To prepare the modified PCC, cationic starch was selected as a polymer and then pretreatment was done by mixing PCC and cationic starch. Consequently, the pretreated PCC contributed to higher tensile strength, stiffness and opacity than the conventional filler, such as GCC and untreated PCC. However, CIE whiteness and ISO brightness decreased slightly compared to conventional fillers.
A Mouse Variable Gene Fragment Binds to DNA Independently of the BCR Context: A Possible Role for Immature B-Cell Repertoire Establishment

B-cell maturation occurs in several steps and requires constant stimulus for its continuing development. From the emergence of the pre-B-cell receptor, signal transduction stimulates and supports B-cell development. Current viewpoints indicate that both positive selection pressure for autoantigens and tonic signaling constitutively stimulate B-cell maturation. In this work, we tested for the presence of a putative DNA binding site in a variable gene segment in a germline configuration, independently of VDJ recombination. After a survey of the public antibody databases, we chose a single mouse heavy variable gene segment that is highly represented in anti-nucleic acid antibodies and tested it for ssDNA binding. A phage display approach was used to search for intrinsic binding to oligo deoxythymidine. The results revealed that binding to an antigen can be influenced by the use of a specific DNA binding V gene segment. Our data support the idea that some variable genes have intrinsic reactivity towards specific types of endogenous autoantigens, and this property may contribute to the establishment of the immature B-cell repertoire.
Search-Based Optimal Motion Planning for Automated Driving

This paper presents a framework for fast and robust motion planning designed to facilitate automated driving. The framework allows for real-time computation even for horizons of several hundred meters and thus enabling automated driving in urban conditions. This is achieved through several features. Firstly, a convenient geometrical representation of both the search space and driving constraints enables the use of classical path planning approach. Thus, a wide variety of constraints can be tackled simultaneously (other vehicles, traffic lights, etc.). Secondly, an exact cost-to-go map, obtained by solving a relaxed problem, is then used by A*-based algorithm with model predictive flavour in order to compute the optimal motion trajectory. The algorithm takes into account both distance and time horizons. The approach is validated within a simulation study with realistic traffic scenarios. We demonstrate the capability of the algorithm to devise plans both in fast and slow driving conditions, even when full stop is required.
Electrophilic Affibodies Forming Covalent Bonds to Protein Targets*

Antibody affinity limits sensitivity of detection in many areas of biology and medicine. High affinity usually depends on achieving the optimal combination of the natural 20 amino acids in the antibody binding site. Here, we investigate the effect on recognition of protein targets of placing an unnatural electrophile adjacent to the target binding site. We positioned a weak electrophile, acrylamide, near the binding site between an affibody, a non-immunoglobulin binding scaffold, and its protein target. The proximity between cysteine, lysine, or histidine on the target protein drove covalent bond formation to the electrophile on the affibody. Covalent bonds did not form to a non-interacting point mutant of the target, and there was minimal cross-reactivity with serum, cell lysate, or when imaging at the cell surface. Electrophilic affibodies showed more stable protein imaging at the surface of mammalian cells, and the sensitivity of protein detection in an immunoassay improved by two orders of magnitude. Thus electrophilic affibodies combined good specificity with improved detection of protein targets.
Linear matrix inequalities for dissipative constraints in stabilization with relaxed non-monotonic Lyapunov function

The state feedback design with a relaxed non-monotonic Lyapunov function in the discrete-time domain is developed in this work. Linear matrix inequalities are derived from both dissipation-based constraint and dissipation inequality for the closed-loop system. The dissipation-based constraint facilitates the stabilization with ΔVk  0 and decreasing (not necessarily monotoincally), instead of ΔVk < 0 along the trajectory. Time-invariant matrix inequalities are derived for linear time-invariant systems. State-dependent matrix inequalities are employed in the derivation for nonlinear input-affine systems.
Plasticity, Variability and Age in Second Language Acquisition and Bilingualism

Much of what is known about the outcome of second language acquisition and bilingualism can be summarized in terms of inter-individual variability, plasticity and age. The present review looks at variability and plasticity with respect to their underlying sources, and at age as a modulating factor in variability and plasticity. In this context we consider critical period effects vs. bilingualism effects, early and late bilingualism, nativelike and non-nativelike L2 attainment, cognitive aging, individual differences in learning, and linguistic dominance in bilingualism. Non-uniformity is an inherent characteristic of both early and late bilingualism. This review shows how plasticity and age connect with biological and experiential sources of variability, and underscores the value of research that reveals and explains variability. In these ways the review suggests how plasticity, variability and age conspire to frame fundamental research issues in L2 acquisition and bilingualism, and provides points of reference for discussion of the present Frontiers in Psychology Research Topic.
Determinants and Prognostic Significance of Exercise Pulmonary Hypertension in Asymptomatic Severe Aortic Stenosis

Background— Recent studies emphasized the usefulness of exercise stress echocardiography in asymptomatic patients with aortic stenosis. Nevertheless, the additive value of exercise pulmonary hypertension (Ex-PHT) in such patients remains unexplored. We therefore aimed to identify the determinants and to test the impact on outcome of Ex-PHT in asymptomatic patients with severe aortic stenosis. Method and Results— Asymptomatic patients with severe aortic stenosis (n=105; aortic valve area <0.6 cm2/m2; age, 71±9 years; male, 59%) and preserved left ventricular systolic function (ejection fraction ≥55%) were prospectively submitted to exercise stress echocardiography. Resting PHT and Ex-PHT were defined as a systolic pulmonary arterial pressure >50 and >60 mm Hg, respectively. Ex-PHT was more frequent than resting PHT (55% versus 6%; P<0.0001). On multivariable logistic regression, the independent predictors of Ex-PHT were male sex (odds ratio, 4.3; P=0.002), resting systolic pulmonary arterial pressure (odds ratio, 1.16; P=0.002), exercise indexed left ventricular end-diastolic volume (odds ratio, 1.04; P=0.026), exercise e′-wave velocity (odds ratio, 1.35; P=0.047), and exercise-induced changes in indexed left atrial area (odds ratio, 1.36; P=0.006). Ex-PHT was associated with reduced cardiac event-free survival (at 3 years, 22±7% versus 55±9%; P=0.014). In a multivariable Cox proportional hazards model, Ex-PHT was identified as an independent predictor of cardiac events (hazard ratio, 1.8; 95% confidence interval, 1.0–3.3; P=0.047). When exercise-induced changes in mean aortic pressure gradient were added to the multivariable model, Ex-PHT remained independently associated with reduced cardiac event-free survival (hazard ratio, 2.0; 95% confidence interval, 1.1–3.6; P=0.025). Conclusions— In asymptomatic patients with severe aortic stenosis, the main determinants of Ex-PHT are male sex, resting systolic pulmonary arterial pressure, and exercise parameters of diastolic burden. Moreover, Ex-PHT is associated with a 2-fold increased risk of cardiac events. These results strongly support the use of exercise stress echocardiography in asymptomatic aortic stenosis.
Adaptive Multilooking Based on Complex Patch for Multitemporal Interferometry

Multilooking is a key step in interferometric processing, especially in so-called coherent stacking interferometry approaches. In the past, multilooking algorithms were mainly implemented in the spatial domain on single interferometric pairs. With continuous development in repeat pass capabilities, multitemporal coherent synthetic aperture radar (SAR) images are now generally acquired more easily, thus providing the possibility to exploit also the temporal signature for multilooking. In this field, the possibility to carry out adaptive multilooking is fundamental for the improvement of interferometric processing. A basic similarity test has been introduced in the SqueeSAR approach, namely the Kolmogorov–Smirnov test. Furthermore, similarity tests have been discussed in terms of real-valued data vector, so only amplitude information can be utilized: The influence of the phase signal is typically ignored. To fully exploit the complex information acquired by coherent SAR systems, this paper proposes an adaptive multilooking algorithm based on complex patch (AMCP). The complex signal, which is fundamental in interferometric systems, is here exploited for the derivation of a new patch selection method. The AMCP algorithm can be applicable to all multitemporal techniques that need filtering, including the InSAR stacks of single main image and multi main images. Experiments on simulated data and real data validate that the proposed algorithm has the highlighting major advantages in improving measurement precision compared with traditional methods.
Tailor-made Accessible Computers: An Interactive Toolkit for Iterative Co-Design

An increasing number of people with little experience in technology desire to use the Internet and web related services like social networking or online information research. However, the way most computers are designed today does not allow many older people to participate in this key technology due to their lack in computer-literacy compared with younger generations. Age-related impairments and disabilities can further complicate or deny the use of conventional computers. To remove existing barriers, we created a series of tailor-made computers, which met specific needs like improved accessibility or particular aesthetics. To accomplish this, we used a co-design toolkit that we created (a) to provide senior users with early tangible experiences of their future systems and (b) to iteratively convert it into the final implementation. In this paper, we demonstrate both the toolkit and the resulting designs of accessible Internet computers.
Multiple sigma-point Kalman smoothers for high-dimensional state-space models

This article presents a new multiple state-partitioning solution to the Bayesian smoothing problem in nonlinear high-dimensional Gaussian systems. The key idea is to partition the original state into several low-dimensional subspaces, and apply an individual smoother to each of them. The main goal is to reduce the state dimension each filter has to explore, to reduce the curse of dimensionality and eventual loss of accuracy. We provide the theoretical multiple smoothing formulation and a new nested sigma-point approximation to the resulting smoothing solution. The performance of the new approach is shown for the 40-dimensional Lorenz model.
High infiltration of CD68+ macrophages is associated with poor prognoses of head and neck squamous cell carcinoma patients and is influenced by human papillomavirus

Incidence of human papillomavirus (HPV)-related head and neck squamous cell carcinomas (HNSCCs) has increased over the last few decades. The reaction of the host immune system to these tumors remains biologically complex. Here, we investigated CD68+ macrophage numbers, reporting the prognostic value in comparison to other risk factors. We also examined CD68+ macrophage infiltration during disease progression regarding the impact of HPV infection, and we studied the role of HPV16-E6/E7 oncoproteins in CD68+ macrophage recruitment. CD68+ macrophage numbers were evaluated in 10 cases of tumor-free peri-tumoral epithelia, 43 cases of low-grade dysplasia, 45 cases of high-grade dysplasia and 110 cases of carcinoma. Our in vivo model was developed in 80 C3H/HeN mice orthotopically injected with HPV16-E6, -E7 or -E6/E7-transfected SCC-VII cell lines. High CD68+ macrophage numbers in the intra-tumoral compartment were associated with shorter patient survival (recurrence-free survival: p = 0.001; overall survival: p = 0.01). Multivariate analyses reported that CD68+ macrophage infiltration and tumor stage were strong and independent prognostic factors of HNSCC. CD68+ macrophage numbers increased during HNSCC progression both in intra-epithelial (p < 0.001) and stromal compartments (p < 0.001). A higher density of CD68+ macrophages was observed in advanced stages (p = 0.004). Patients with transcriptionally active HPV infections had higher CD68+ macrophage density than did HPV-negative patients (p = 0.003). CD68+ macrophage infiltration was higher in HPV-E7+ and −E6/E7+ mouse tumors than in -E6+ tumors (p = 0.029 and p < 0.001). In conclusion, the extent of CD68+ macrophage infiltration is a significant prognostic factor for HNSCC patients. The recruitment of macrophages increases during disease progression and is influenced by the HPV virus.
Molecular contribution to cleft palate production in cleft lip mice

Cleft palate following cleft lip may include a developmental disorder during palatogenesis. CL/Fr mice fetuses, which develop cleft lip and palate spontaneously, have less capability for in vivo cell proliferation in palatal mesenchyme compared with CL/Fr normal fetuses. In order to know the changes of signaling molecules contributing to cleft palate morphogenesis following cleft lip, the mRNA expression profiles were compared in palatal shelves oriented vertically (before elevation) in CL/Fr fetuses with or without cleft lip. The changes in mRNA profile of cleft palate morphogenesis were presented in a microarray analysis, and genes were restricted to lists contributing to cleft palate development in CL/Fr fetuses with cleft lip. Four candidate genes (Ywhab, Nek2, Tacc1 and Frk) were linked in a gene network that associates with cell proliferation (cell cycle, MAPK, Wnt and Tgf beta pathways). Quantitative real‐time RT‐PCR highlighted the candidate genes that significantly changed in CL/Fr fetuses with cleft lip (Ywhab, Nek2 and Tacc1). The results of these molecular contributions will provide useful information for a better understanding of palatogenesis in cleft palate following cleft lip. Our data indicated the genetic contribution to cleft palate morphogenesis following cleft lip.
Functional characterization and genomic studies of a novel murine submandibular gland epithelial cell line

A better understanding of the normal and diseased biology of salivary glands (SG) has been hampered, in part, due to difficulties in cultivating and maintaining salivary epithelial cells. Towards this end, we have generated a mouse salivary gland epithelial cell (mSGc) culture system that is well-suited for the molecular characterization of SG cells and their differentiation program. We demonstrate that mSGc can be maintained for multiple passages without a loss of proliferation potential, readily form 3D-spheroids and importantly express a panel of well-established salivary gland epithelial cell markers. Moreover, mSGc 3D-spheroids also exhibit functional maturation as evident by robust agonist-induced intracellular calcium signaling. Finally, transcriptomic characterization of mSGc by RNA-seq and hierarchical clustering analysis with adult organ RNA-seq datasets reveal that mSGc retain most of the molecular attributes of adult mouse salivary gland. This well-characterized mouse salivary gland cell line will fill a critical void in the field by offering a valuable resource to examine various mechanistic aspects of mouse salivary gland biology.