SIRIS-Lab/unlabelled-sti-corpus huggingface dataset:
Estimating dominant spatial scales in cross-sectional velocity data

Flow velocity measurements in rivers and coastal areas are often collected at cross-sections where velocity is measured at multiple locations and over certain period of time. Subsequent data processing often involves temporal averaging and spatial smoothing of the raw velocity data. This process of spatial smoothing and temporal averaging is motivated by spatial and temporal behavior we expect to be present in the data, such as coherent velocity patterns at the scale of the water depth and temporal coherence at the scale of for instance tides. The process of smoothing and averaging, however, is often arbitrary, and the consequences of averaging windows in space and time on the resulting velocity patterns are often obscure. In this contribution we investigate a method based on spectral analysis to analyze the spatial patterns in a cross-section. This allows to identify the dominant spatial patterns that are present in the velocity data leading to a more grounded choice for spatial smoothing. Furthermore, the choice of basis function allows to include some physically based constraints such as no-slip at the bed and banks. The method consists of computing the components and location of the velocities measured in a cross-section. These locations are transformed to a normalized coordinate system. For each velocity component a set of basis function is selected and higher order function are progressively included and fitted to all the velocity data measured at a cross-section. The process is repeated until there is no spatial structure in the residuals. The method is applied to velocity measurements collected in a sharp bend. The analysis allows to identify dominant spatial patterns present in the data and results in continuous functions that describe the velocity field in detail, and that meet the requirement of no slip at the boundaries. Future work will extend the analysis to include different of basis functions, to include more physical constraints, such as continuity.
Abstract A67: Defining signaling pathways governing metastatic potential in pancreas cancer

Pancreas cancer is an aggressively metastatic disease in which circulating tumor cells (CTC) often colonize distant organs long before diagnosis. Approximately 45% of patients present at diagnosis with metastatic disease, and this increases to 90% at the time of death. Even after surgical resection of the primary tumor, local and distant recurrence develops in approximately two thirds of cases. These sobering statistics highlight the need to define mechanisms and vulnerabilities of metastasis that can be targeted to improve patient outcomes. To better understand the process of pancreatic cancer metastasis, we study the Kras LSL-G12D/+ ; Trp53 LSL-R172H/+ ; Pdx1-Cre ( KPC ) model of autochthonous pancreas cancer. KPC mice spontaneously develop invasive and metastatic disease to numerous sites, including the liver and lungs, at rates similar to those seen in humans. Lineage tracing, performed by selectively expressing fluorescent reporters in pancreatic cells of KPC mice, has revealed a rare population of CTC that may be precursors to these metastatic foci. Building on this model, we show that alteration of TGFβ pathway components significantly affects the metastatic potential of autochthonous tumors, and that the timing and balance of signaling is critical in the metastatic process. These differences in metastatic potential are reflected in the numbers and functional properties of the respective CTC. Our distinct models with drastically different metastatic potentials provide clues to understanding the signaling mechanisms driving metastasis in pancreas cancer. Citation Format: Martin C. Whittle, Markus Carlson, Sunil R. Hingorani. Defining signaling pathways governing metastatic potential in pancreas cancer. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Innovations in Research and Treatment; May 18-21, 2014; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2015;75(13 Suppl):Abstract nr A67.
A MPC approach for optimal generation scheduling in CSP plants

Abstract Thermal energy storage (TES) systems allow concentrated solar power (CSP) producers to participate in a day-ahead market. Therefore, the optimal power scheduling problem can be posed, whose objective is the maximization of profits derived from electricity sales. The daily generation schedule has to be offered in advance, usually the previous day before a certain time, thus an electricity price and weather forecast must be carried out. This paper proposes a model-based predictive control (MPC) approach for optimal scheduling in CSP plants. This approach has a dual purpose: (1) the periodic update of the generation schedule to track the schedule that has been committed to by means of the most recent electricity price and weather forecast and information about the plant state and (2) the generation of the optimal schedule for the next day. As these two tasks are related, they are performed simultaneously. Therefore, the MPC sliding window is composed of a first time interval to track the committed schedule and a second time interval to generate the next schedule for the following hours. This is then offered as the generation schedule for the next day at the appropriate time. The proposed approach is applied, in a simulation context, to a 50 MW parabolic trough collector-based CSP plant with molten-salt-based TES. The chosen criterion to track the committed schedule is the even distribution of the possible generation error within the first interval. A case-study with overestimated initial DNI forecast is undertaken. The results show that the MPC control with short-term DNI forecast significantly improves the above-mentioned objective and allows for a reduction of the deviation from the scheduled generation, when compared with the case without short-term DNI forecast.
Simulation of flocculation in W/O emulsions and experimental study

Abstract The flocculation of aqueous droplets in W/O emulsions has been studied using Langevin dynamics simulation. The range of aqueous phase concentrations and time necessary for the formation of percolation clusters were determined. Percolation clusters are not formed if aqueous phase concentrations in simulated emulsions are less than 0.15. In emulsions with aqueous phase concentrations from 0.15 to 0.3–0.4 the percolation cluster is formed within 2 s, but the rate of the subsequent attaching droplets and small aggregates to this cluster is low. In simulated emulsions with aqueous phase concentrations of above 0.3–0.4, almost all droplets are combined into percolation clusters within a few fractions of a second. Experimental data were compared with the results of computer simulations. In emulsions with aqueous phase concentrations of above 0.15 the droplet flocs form a network structure in the oil phase, and the rate of oil phase release depends on the rate of oil drainage. In less concentrated emulsions, the separation into a more concentrated W/O emulsion and a diluted W/O emulsion containing small flocs of aqueous droplets takes place. The data obtained suggests that the simulation by the Langevin dynamics method makes it possible to predict the stability of W/O emulsions to flocculation and subsequent sedimentation.
Hybrid Gel Electrolytes Derived from Keggin-Type Polyoxometalates and Imidazolium-Based Ionic Liquid with Enhanced Electrochemical Stability and Fast Ionic Conductivity

New hybrid gel electrolytes, derived from synergetic self-assembling of inorganic polyoxometalates (POMs) and organic ionic liquid (IL) components, have been successfully prepared using Keggin-type heteropolyanions such as {PMo11VO40}4– and {PW11MoO40}3– and ionic liquid N-methyl imidazolium-1-(3-sulfonic group) propyl (MIMPS). Powder X-ray diffraction study reveals that these hybrid gels possess lamellar structure and exhibit characteristic thermo-tropic liquid-crystalline behavior. Ionic conductivity (σ) of ∼0.1 S cm–1 under ambient conduction was observed at 93 °C for [MIMPS]4PMo11VO40 (IL-PMo11V) and [MIMPS]3PW11MoO40 (IL-PW11Mo) hybrid gels. The electrochemical stability window (ESW) of IL-PMo11V and IL-PW11Mo seem to be about 2 and 4 V, respectively, at room temperature. The POM-based IL gel electrolytes show super ionic conductivity and high ESW compared to other known IL-based electrolytes, including 1-dodecyl-3-methylimidazolium-bis(pentafluoro-ethylsolfonyl)imide (σ = 0.003 S cm–1 at 94 °C, ESW ...
Enhanced k-means clustering for patient reported outcome

Data Mining has become one of the most exciting and fastest growing fields in Information Technology. This is due to unprecedented growth-rate of data which is being collected, loaded and stored through World Wide Web and accessed electronically in almost all fields of Human Endeavour. But online retrieval or querying of useful information from these very large databases for Medical diagnosis in hospital information systems (HIS), Biomedical, DNA analysis etc is becoming an increasing scientific challenge. As a result there is an urgent need for sophisticated tools and techniques that can handle extremely large multiple databases. Even it is necessary to globalize Knowledge discovery in databases (KDD) to process and extract useful knowledge's using fully automated techniques. In the field of medicine, as human cannot practically deal with such a huge amount of data, a growing attention has been paid for information processing. To resolve these, it is highly expected to enhance clustering techniques. In this paper we enhance K-means algorithm of Clustering technique by Automatic K generation and optimize the cluster.
Interference Aware MAC scheduling for Collision Avoidance using Energy Detection Scan

Advances in MEMS (Micro Electro Mechanical Systems), microprocessor, and wireless technologies, have accelerated deployment of network-capable computing devices attached to various objects over the world. These devices should be small in size and have a characteristic of extremely low power consumption. Therefore, in 2004, IEEE 802.15.4 has been established as a global standard for LR-WPANs. After that, the phenomenal popularity of this standard has also led to indiscreet deployment of other WPANs. Therefore, LR-WPANs can suffer from collision by other WPAN devices. In order to solve collision problem in IEEE 802.15.4, in this paper we introduce a novel channel scheduling scheme which is an adaptive method with fast recovery. The proposed scheme can minimize the possibility of beacon collisions by efficiently managing the multiple available channels in a hybrid manner combining proactive and reactive methods.
Syntaxin 11 is required for NK and CD8<sup>+</sup>T-cell cytotoxicity and neutrophil degranulation

Syntaxin 11 (STX11) controls vesicular trafficking and is a key player in exocytosis. Since Stx11 mutations are causally associated with a familial hemophagocytic lymphohistio-cytosis, we wanted to clarify whether STX11 is functionally important for key immune cell populations. This was studied in primary cells obtained from newly generated Stx11(-/-) mice. Our data revealed that STX11 is not only widely expressed in different immune cells, but also induced upon LPS or IFN-γ treatment. However, Stx11 deficiency does not affect macrophage phagocytic function and cytokine secretion, mast cell activation, or antigen presentation by DCs. Instead, STX11 selectively controls lymphocyte cytotoxicity in NK and activated CD8(+) T cells and degranulation in neutrophils. Stx11(-/-) NK cells and CTLs show impaired degranulation, despite a comparable activation, maturation and expression of the complex-forming partners MUNC18-2 and VTI1B. In addition, Stx11(-/-) CTLs and NK cells produce abnormal levels of IFN-γ. Since functional reconstitution rescues the defective phenotype of Stx11(-/-) CTLs, we suggest a direct, specific and key role of STX11 in controlling lymphocyte cytotoxicity, cytokine production and secretion. Finally, we show that these mice are a very useful tool for dissecting the role of STX11 in vesicular trafficking and secretion.
Image processing apparatus, image capture apparatus, and image processing method

An image processing apparatus and image processing method, which enable suppression of coloring that occurs in image recovery processing for a RAW image are disclosed. Pixel interpolation processing is executed for a predetermined reference color component of the RAW image. For each color component other than the reference color component, a first color difference is obtained using a pixel value of the color component and a corresponding pixel value of the reference color component after the pixel interpolation processing. After applying the image recovery processing to each color component, a second color difference is obtained in a similar manner to the first color difference, and a pixel value is corrected according to the difference between the first and second color differences determined before and after the image recovery processing.
Understanding and modelling the earth system with machine learning

Earth system models are fundamental to understand climate change. Although they have improved significantly, considerable biases and uncertainties in their projections remain. Process parameterisations limit the models’ ability to simulate both global and regional Earth system responses, which are key for assessing climate change and its impacts on ecosystems and society. In recent years, the volume of data from high-resolution models and observations has substantially increased to petabyte scales. Concomitantly, the field of machine learning (ML) has quickly developed, promising breakthroughs in detecting and analysing non-linear relationships and patterns in large multivariate datasets. Yet, traditionally, physical modelling and ML have been often treated as two different worlds with opposite scientific paradigms (theory-driven versus data-driven). Thus, despite its great potential, ML has not yet been widely adopted for addressing the urgent need of improved understanding and modelling of the Earth system. USMILE will combine multi-disciplinary expertise in ML and process-based atmosphere and land modelling to completely rethink model development and evaluation. ML will further allow us to define novel observational constraints on Earth system feedbacks and climate projections. We will (1) develop ML algorithms to enhance Earth observation datasets accounting for spatio-temporal covariations, (2) deploy ML-based parameterisations and sub-models for clouds and land-surface processes that have hindered progress in climate modelling for decades, and (3) detect and understand modes of climate variability, multivariate extremes and uncover dynamical aspects of the Earth system with novel deep learning and causal inference techniques. USMILE will drive a paradigm shift in the current modelling of the Earth system towards a new data-driven physics-aware science and to an unprecedented reduction of uncertainties in projections.
Lyapunov Exponents of Minimizing Measures for Globally Positive Diffeomorphisms in All Dimensions

The globally positive diffeomorphisms of the 2n-dimensional annulus are important because they represent what happens close to a completely elliptic periodic point of a symplectic diffeomorphism where the torsion is positive definite. For these globally positive diffeomorphisms, an Aubry–Mather theory was developed by Garibaldi and Thieullen that provides the existence of some minimizing measures. Using the two Green bundles \({G_-}\) and \({G_+}\) that can be defined along the support of these minimizing measures, we will prove that there is a deep link between: 


the angle between \({G_-}\) and \({G_+}\) along the support of the considered measure \({\mu}\);


the size of the smallest positive Lyapunov exponent of \({\mu}\);


the tangent cone to the support of \({\mu}\).
Construction of two recreational and holiday buildings with the base of the “Sielska settlement”.

The project concerns the construction of two individual recreation houses with an area of up to 35 m² each, including one adapted to the needs of persons with disabilities, purchase of equipment, preparation of parking spaces, including for persons with disabilities, in the village of Rudenka, the municipality of Olszanica, in order to launch a new service – short-term accommodation, in an extended season (guests will be received from 4th to X), in new facilities (two houses) adapted for persons with disabilities, with food taking into account the diet: vegetarian, vegan, gluten-free, inspired by local tradition, with thematic workshops (cullinary, thematic for children and youth on the work of the local poet Maria Czerkawska), sauna, gazebo with grill. The new service will increase the economic attractiveness of the region through the development of activities in the area of broadly understood tourism and its promotion, which will translate into the promotion of 12 Bieszczady municipalities. The project is compatible with the Regional Smart Specialisation of the Voivodeship. Podkarpacki: quality of life.
Streamlining genetic testing by standardizing its report formats and exchange among all stakeholders

Scientific objectives A growing base of genetic testings is now available for clinicians and its results could improve the quality of care and its outcomes. In addition, these testings are also helpful for predictive medicine and early detection of diseases. Genetic testings could further personalize the care processes based on the patient individual genetic makeup. Genetic testing methods are diverse and span from testing for known germline mutations in the context of single-gene disorders, to full sequencing of genes in tumor tissues looking for somatic variations in cancer cells, and on to whole-exome sequencing in cases of predictive medicine or unknown diagnosis. As a consequence of that diversity and the constantly growing number of techniques yielding new result formats less familiar to clinicians, existing report formats attempt to contain rather detailed descriptions of the tests performed, but that approach makes it hard to understand the interpretations of the testing results and given recommendations. Genetic testing reports should be both human readable to its users, and at the same time also be processable to computerized algorithms computing the interpretation of the genetic testing results. Thus, it is equally important to standardize the way genetic testing interpretations are represented [1] as an inherent part of the report structure.
SCANNING DISPLAY WITH INCREASED UNIFORMITY

A light assembly can have an array of light sources forming rows and columns, where the array comprises a plurality of chips, and each chip comprises a subarray of light sources forming the rows and columns. A boundary between chips in the array can be configured to extend diagonally across rows and columns of the array such that, for each column across which the boundary extends, the first row of the plurality rows may not have a light source disposed in the respective column, but a second row of the plurality of rows has a light source disposed in the respective column.
Releasing the full potential of instruct to expand and consolidate infrastructure services for integrated structural life science research

Instruct-Ultra aims to advance the scope and efficiency of implementation of Instruct and consolidate the foundations for long-term sustainability. This will be achieved through specific objectives: expand Instruct membership to new Member States and increase global links; engage new user communities; improve efficiencies in service delivery; improve data capture and management; adjust the scale and reliability of the infrastructure. Instruct-Ultra will deliver these alongside the transition to ERIC legal status and rapid developments in, and increased demand for, integrated structural biology infrastructure. These advances in the scale and speed of delivery will earn further trust within the life science community. One focus will to expand membership to Eastern European states and EFTA countries, integrating their structural biology communities into Instruct and providing new opportunities to support research excellence and raise standards. Opportunities for engaging with industrialised and developing countries outside the ERA will build on existing cooperative work between Instruct and Asian, African and South American countries to establish strong bilateral programmes of benefit to both parties, giving Instruct better engagement in emerging global challenges and positioning Instruct as a trusted global resource for high quality structural biology services. Starting from baseline operations four years ago Instruct has now identified key areas of service which should be expanded, new potential user groups, and opportunities for more reliable, efficient and sometimes remotely used workflows. Instruct-Ultra will therefore test new modes of access and pilot new service methods in high demand areas to accelerate access for more users. Instruct-Ultra will reinforce Instruct operations by updating and expanding the business plan and structural biology roadmap, whilst improving the interface with academia and industry as a strategy to sustainability.
Charge state modulation of nitrogen vacancy centers in diamond by applying a forward voltage across a p–i–n junction

Abstract Charge state control of the nitrogen vacancy center (NV center) in diamond is important to the realization of applications such as magnetometers or quantum information processing, because only negatively charged NV centers have attractive spin properties. We fabricated p–i–n (p-type–intrinsic–n-type) junctions to investigate the charge state properties of the NV centers in an ultrapure i-layer with a low impurity concentration. The photoluminescence of the ensemble of NV centers demonstrated that the charge state can be modulated by external voltage across the p–i–n junction. The charge state of the NV centers was tuned towards NV− by applying a forward bias below the built-in voltage.
NRF2 loss recapitulates heritable impacts of paternal cigarette smoke exposure

Paternal cigarette smoke (CS) exposure is associated with increased risk of behavioral disorders and cancer in offspring, but the mechanism has not been identified. Here we use mouse models to investigate mechanisms and impacts of paternal CS exposure. We demonstrate that CS exposure induces sperm DNAme changes that are partially corrected within 28 days of removal from CS exposure. Additionally, paternal smoking is associated with changes in prefrontal cortex DNAme and gene expression patterns in offspring. Remarkably, the epigenetic and transcriptional effects of CS exposure that we observed in wild type mice are partially recapitulated in Nrf2-/- mice and their offspring, independent of smoking status. Nrf2 is a central regulator of antioxidant gene transcription, and mice lacking Nrf2 consequently display elevated oxidative stress, suggesting that oxidative stress may underlie CS-induced heritable epigenetic changes. Importantly, paternal sperm DNAme changes do not overlap with DNAme changes measured in offspring prefrontal cortex, indicating that the observed DNAme changes in sperm are not directly inherited. Additionally, the changes in sperm DNAme associated with CS exposure were not observed in sperm of unexposed offspring, suggesting the effects are likely not maintained across multiple generations.