Miracle-dz/UniFAR-FTUs huggingface dataset:
Pollination ecology and circadian patterns of inflorescence opening of the Madagascan climber Dalechampia aff. bernieri (Euphorbiaceae)

Abstract: Floral morphology often directly influences interactions with pollinators, but less is known about the role of extrafloral structures. We studied the relationship between bract motility, floral structural specialization and pollination in Dalechampia aff. bernieri, an endemic Madagascan species with floral structures indicating specialized buzz-pollination. We measured circadian bract angles in 47 inflorescences from 11 plants of D. aff. bernieri; in addition, we recorded any flower-visiting insects observed. The inflorescences had motile bracts with mean angles varying from ~50° at 00h00 to ~90° at 10h45. They were visited by buzz-pollinating Nomia viridilimbata bees (Halictidae), but also by non-buzz-pollinating Liotrigona bees (Apidae). The temporal pattern of bract motility observed in D. aff. bernieri may represent an extra-floral specialization to reduce visitation by non-pollinating visitors while maximizing visitation by diurnal buzz-pollinating bees.
The RedGOLD Cluster Detection Algorithm and its Cluster Candidate Catalogue for the CFHT-LS W1

We present RedGOLD (Red-sequence Galaxy Overdensity cLuster Detector), a new optical/NIR galaxy cluster detection algorithm, and apply it to the CFHT-LS W1 field. RedGOLD searches for red-sequence galaxy overdensities while minimizing contamination from dusty star-forming galaxies. It imposes an Navarro–Frenk–White profile and calculates cluster detection significance and richness. We optimize these latter two parameters using both simulations and X-ray-detected cluster catalogues, and obtain a catalogue ∼80 per cent pure up to z ∼ 1, and ∼100 per cent (∼70 per cent) complete at z ≤ 0.6 (z ≲ 1) for galaxy clusters with M ≳ 10^(14) M_⊙ at the CFHT-LS Wide depth. In the CFHT-LS W1, we detect 11 cluster candidates per deg^2 out to z ∼ 1.1. When we optimize both completeness and purity, RedGOLD obtains a cluster catalogue with higher completeness and purity than other public catalogues, obtained using CFHT-LS W1 observations, for M ≳ 10^(14) M_⊙. We use X-ray-detected cluster samples to extend the study of the X-ray temperature–optical richness relation to a lower mass threshold, and find a mass scatter at fixed richness of σ_(lnM|λ) = 0.39 ± 0.07 and σ_(lnM|λ) = 0.30 ± 0.13 for the Gozaliasl et al. and Mehrtens et al. samples. When considering similar mass ranges as previous work, we recover a smaller scatter in mass at fixed richness. We recover 93 per cent of the redMaPPer detections, and find that its richness estimates is on average ∼40–50 per cent larger than ours at z > 0.3. RedGOLD recovers X-ray cluster spectroscopic redshifts at better than 5 per cent up to z ∼ 1, and the centres within a few tens of arcseconds.
Hydrolysis of ovomucin by different enzymes.

In the first part of this study the effectiveness of ten different enzymes to hydrolyze ovomucin were compared. In the second part of this study ovomucin samples were hydrolysed by using three different enzymes (Pronase, Proteinase K and Trypsin) in various enzyme concentrations. Average yields and degree of hydrolysis (DH %) of different ovomucin hydrolysates were measured, and their peptide profiles were analysed by using gel filtration chromatography. It was found that not only by using different enzymes but also by changing the hydrolysis conditions it was possible to produce hydrolysates very different in peptide composition. This can be useful when peptides having different kind of bioactive properties are produced from ovomucin.
Geometric Modelling and Deformation for Shape Optimization of Ship Hulls and Appendages

The precise control of geometric models plays an important role in many domains such as Computer Aided geometric Design and numerical simulation. For shape optimisation in Computational Fluid Dynamics, the choice of control parameters and the way to deform a shape are critical. In this paper, we describe a skeleton-based representation of shapes adapted for CFD simulation and automatic shape optimisation. Instead of using the control points of a classical B-spline representation, we control the geometry in terms of architectural parameters. We assure valid shapes with a strong shape consistency control. Deformations of the geometry are performed by solving optimisation problems on the skeleton. Finally, a surface reconstruction method is proposed to evaluate the shape's performances with CFD solvers. We illustrate the approach on two problems: the foil of an AC45 racing sail boat and the bulbous bow of a fishing trawler. For each case, we obtained a set of shape deformations and then we evaluated and analysed the performances of the different shapes with CFD computations.
Fund-of-Funds Construction by Statistical Multiple Testing Methods

Fund-of-funds (FoF) managers face the task of selecting a (relatively) small number of hedge funds from a large universe of candidate funds. We analyse whether such a selection can be successfully achieved by looking at the track records of the available funds alone, using advanced statistical techniques. In particular, at a given point in time, we determine which funds significantly outperform a given benchmark while, crucially, accouting for the fact that a large number of funds are examined at the same time. This is achieved by employing so-called multiple testing methods. Then, the equal-weighted or the global minimum variance portfolio of the outperforming funds is held for one year, after which the selection process is repeated. When backtesting this strategy on two particular hedge fund universes, we find that the resulting FoF portfolios have attractive return properties compared to the 1/N portfolio (that is, simply equal-weighting all the available funds) but also when compared to two investable hedge fund indices.
PHOTOVOLTAIC MODULE-INTEGRATED CONVERTER (MIC) BASED ON SEMI-Z-SOURCE INVERTERS (SZSI): A NEW SLIDING MODE CONTROL SCHEME CONVERTIDORES FOTOVOLTAICOS EN MÓDULOS INTEGRADOS BASADOS EN INVERSORES DE FUENTE-SEMI-CUASI –Z: UN NUEVO ESQUEMA DE CONTROL POR MODOS DESLIZANTES PhD(c)

A control scheme for power conditioning in a photovoltaic (PV) system based on semi-quasi-z-source inverters (SqZSI) is proposed. The adopted inverter topology allows the independent control of each leg current, enabling the tracking of the maximum power point (MPP). The scheme is an implementation of a hysteretic current mode controller that controls quasi-z-source single-phase inverter. The good agreement between the analytical study and simulation results confirms the validity of the proposed control system.
Off-Policy Neural Fitted Actor-Critic

A new off-policy, offline, model-free, actor-critic reinforcement learning algorithm dealing with continuous environments in both states and actions is presented. It addresses discrete time problems where the goal is to maximize the discounted sum of rewards using stationary policies. Our algorithm allows to trade-off between data-efficiency and scalability. The amount of a priori knowledge is kept low by: (1) using neural networks to learn both the critic and the actor, (2) not relying on initial trajectories provided by an expert, and (3) not depending on known goal states. Experimental results compare data-efficiency to 4 state-of-the-art algorithms on three benchmark environments. This article largely reproduces a previous work [34] by adding a higher dimensional environment, improving control architectures and provides batch normalization for others state-of-the-art algorithms.
INFRASTRUCTURE CONSOLIDATION FOR INTERCONNECTED SERVICES IN A SMART CITY USING CLOUD ENVIRONMENT

Sustainability, appropriate use of natural resources and providing a better quality of life for citizens has become a prerequisite to change the traditional concept of a smart city. A smart city needs to use latest generation Information Technologies, IT, and hardware to improve services and data, to offer to create a balanced environment between the ecosystem and inhabitants. This paper analyses the advantages of using a private cloud architecture to share hardware and software resources when it is required. Our case study is Guadalajara, which has seven municipalities and each one monitor’s air quality. Each municipality has a set of servers to process information independently and consists of information systems for the transmission and storage of data with other municipalities. We analysed the behaviour of the carbon footprint during the years 1999-2013 and we observed a pattern in each season. Thus our proposal requires municipalities to use a cloud-based solution that allows managing and consolidating infrastructure to minimize maintenance costs and electricity consumption to reduce carbon footprint generated by the city.
INTERCONNECTED HIERARCHICAL RANK-STRUCTURED METHODS FOR DIRECTLY SOLVING AND PRECONDITIONING THE HELMHOLTZ EQUATION

In this paper, we design interconnected hierarchical rank-structured methods for the fast direct solution and effective preconditioning of the Helmholtz equation. First, for essentially elliptic PDEs, a direct method is proposed to exploit interconnected structures within two hierarchical layers: the hierarchical partitioning of a large problem into sub-problems for smaller subdomains, and the hierarchically semiseparable (HSS) approximation for the sub-problems. Interconnected low-rank structures enable extensive reuse of information among computations associated with different subdomains, which greatly reduces the cost and memory usage for the construction of structured representations as needed in fast structured direct solutions. In contract, previous structured direct solvers usually require expensive structured constructions which contribute to the dominant cost. Our direct method can quickly solve either the low-frequency or the damped Helmholtz equation. The factorization cost can be as low as O(n) in 2D and O(n logn) in 3D, where n is the matrix size. For the high-frequency case, we build a preconditioner by creating artificial damping near the boundary of subdomains. We give the first result on how the magnitude of the damping parameter affects the compressibility of HSS representation of boundary maps. For O(ω2−γ) damping where ω is the angular frequency and γ ∈ [0, 1], the factorization of the preconditioner costs O(ω2+γ) in 2D and O(ω3+3γ) in 3D. For the interior impedance problem, we show that the condition number of the preconditioned system is O(ω1−γ), and prove GMRES convergence for general cases based on the Elman estimates. Comparing with solving the preconditioner problem iteratively, the rank-structured approach gives a robust solution for various choices of damping, and has a predictable tradeoff between cost the and effectiveness.
Short and Long Run Uncertainty Short and Long Run Uncertainty

Uncertainty appears to have both a short-run and a long-run component, which we measure using rm and macro implied volatility data from options of 30 days to 10 years duration. We ask what may be driving uncertainty over these di erent time horizons, nding that oil price volatility is particularly important for short-run uncertainty, policy uncertainty is particularly important for long-run uncertainty, while currency volatility and CEO turnover appear to equally impact shortand long-run uncertainty. Examining a panel of over 4,000 rms from 1996 to 2013 we nd that R&D is relatively more sensitive to long-run uncertainty than investment, and in turn investment is relatively more sensitive to long-run uncertainty than hiring. In a simulation model we investigate the channels underlying this pecking-order response to long-run uncertainty, and show that lower depreciation rates and higher adjustment costs lead R&D and investment to be more sensitive to longer-run uncertainty than hiring. Collectively, these results suggest that recent events that have raised long-run policy uncertainty may be particularly damaging to growth by reducing R&D and investment. Acknowledgments: We thank participants at numerous seminars for helpful comments. We thank the National Science Foundation, Sloan Foundation and SIEPR for providing generous research support. Disclaimer: This paper was written in Ian Wright's individual capacity and is not related to his role at Goldman Sachs. The analysis, content and conclusions set forth in this paper are those of the authors alone and not of Goldman Sachs & Co. or any of its a liate companies. The authors alone are responsible for the content.
Creep deformation behaviour of PC-ABS parts processed by fused deposition additive manufacturing under different extrusion parameters

Fused deposition modeling (FDM) is a complex process for many additive manufacturing practitioners as it involves selection of a large number of intervening process conditions to produce quality products to meet customer needs and achieve competitive advantages. Understanding the effect of operating conditions on the mechanical properties of FDM printed parts is an important task as they influence the functionality of the products. The growing demand for use of Polycarbonate /Acrylonitrile-Butadiene-Styrene (PC-ABS) alloys in the production of automotive components led to the need for understanding the creep deformation performance of processed material and product under various processing parameters. This study investigates the effect of FDM process conditions on creep deformation behaviour. A systematic study through definitive screening design and statistical analysis was carried out in order to correlate the FDM processing parameters with the performance of PCABS alloys. In this study, the regression model was developed for the calculation of the processing parameters in FDM of PC-ABS products and gives technical information for the determination of which process parameters are the best to use for practical purposes.
Acupuncture in lymphoedema management: a feasibility study

Background: Acupuncture in lymphoedema management is controversial, with assumptions it will introduce infection or exacerbate swelling. Aims: This three-step, patient-centred, mixed-methods study assessed acceptability, impact on quality of life, and adverse events of traditional acupuncture as an adjunct to maintenance care for people with lymphoedema secondary to breast and head and neck cancers. Methods: Step 1: focus groups with patients and clinicians assessed acceptability. Step 2: in an observational study, participants chose seven or 13 treatments. Outcome measures included Measure Yourself Medical Outcome Profile (MYMOP) and 36-Item Short Form Health Survey (SF-36). Step 3: focus group participants discussed their perceptions of treatment. Results: Step 1: eight focus groups (n=39) found acupuncture acceptable, providing affected areas were not needled. Step 2: 30/35 participants completed 13 treatments. MYMOP change scores were clinically and statistically significant at all measurement points. SF-36 scores remained significant for bodily pain and vitality four weeks after the end of treatment. Step 3: data from six focus groups (n=23) supported quantitative results. Conclusions: Acupuncture can be used safely to manage the symptom burden for cancer survivors with upper-body lymphoedema and may improve concordance with long-term management. Declaration of interest: None. Beverley de Valois, Teresa Young, Elaine Melsome
An Inexact Regularized Newton Framework with a Worst-Case Iteration Complexity of $\mathcal{O}(\epsilon^{-3/2})$ for Nonconvex Optimization

An algorithm for solving smooth nonconvex optimization problems is proposed that, in the worst-case, takes $\mathcal{O}(\epsilon^{-3/2})$ iterations to drive the norm of the gradient of the objective function below a prescribed positive real number $\epsilon$ and can take $\mathcal{O}(\epsilon^{-3})$ iterations to drive the leftmost eigenvalue of the Hessian of the objective above $-\epsilon$. The proposed algorithm is a general framework that covers a wide range of techniques including quadratically and cubically regularized Newton methods, such as the Adaptive Regularisation using Cubics (ARC) method and the recently proposed Trust-Region Algorithm with Contractions and Expansions (TRACE). The generality of our method is achieved through the introduction of generic conditions that each trial step is required to satisfy, which in particular allow for inexact regularized Newton steps to be used. These conditions center around a new subproblem that can be approximately solved to obtain trial steps that satisfy the conditions. A new instance of the framework, distinct from ARC and TRACE, is described that may be viewed as a hybrid between quadratically and cubically regularized Newton methods. Numerical results demonstrate that our hybrid algorithm outperforms a cublicly regularized Newton method.
Temperature control device for single molecule measurements using the atomic force microscope

The design and implementation of a temperature control device for the atomic force microscope (AFM) are described. This device is based on a thermoelectric module which can be used for both heating and cooling the samples in the AFM liquid chamber within the range of 5–50°C. A thermocouple is inserted in the liquid chamber to measure the sample temperature. A commercial thermoelectric temperature controller is used to keep the temperature constant during a measurement, which can be stabilized within 0.1°C. To dissipate the heat generated by the thermoelectric module during cooling, a water cooled heat sink is used. Using this device, imaging and mechanical unfolding experiments were carried out at different temperatures. The results show that the temperature control device does not significantly reduce the imaging capacities of the AFM, and that the force-induced unfolding of individual protein molecules can be readily observed at different temperatures. Temperature dependent single molecule measurements .
Miniature and Molecularly Specific Optical Screening Technologies for Breast Cancer

Abstract : The goal of this proposal is to harness the power of light to create "miniature and molecularly specific optical technologies" for breast cancer diagnosis and detection. The miniature technologies will leverage on millimeter scale silicon detectors and LEDs to make compact devices that can be used in a practical clinical setting for breast cancer detection. The features that will be exploited for optical detection/diagnosis of breast cancer will include the physiological, structural and molecular alterations that accompany the transformation of a cell from a normal to malignant state. This proposal also focuses on using contrast agents, specifically aminolevulinic acid (ALA) induced protoporphyrin IX (PpIX) and NBDG, for the molecular detection of breast cancer.
Investigation of the SQUBIC phase mask design for depth-invariant widefield microscopy point-spread function engineering

Point-spread function engineering (PSF), achieved by placing a phase mask at the pupil plane of the imaging lens to encode the wavefront emerging from an imaging system, can be employed to reduce the impact of spherical aberration (SA) in 3D microscopy. In a previous study, the effect of SA on a confocal scanning microscope using a squared cubic phase mask (SQUBIC) was investigated using computer simulations. Here the effect of the SQUBIC design parameter on the insensitivity of the engineered PSF to SA is investigated using a metric based on the second-order moment of the axial variability of the PSF. We show that it is possible to find the optimum SQUBIC for the insensitization to SA.
D-OPTIMAL DESIGN FOR MULTIVARIATE POLYNOMIAL REGRESSION VIA THE CHRISTOFFEL FUNCTION AND SEMIDEFINITE RELAXATIONS

We present a new approach to the design of D-optimal experiments with multivariate polynomial regressions on compact semi-algebraic design spaces. We apply the moment-sum-of-squares hierarchy of semidefinite programming problems to solve numerically and approximately the optimal design problem. The geometry of the design is recovered with semidefinite programming duality theory and the Christoffel polynomial.
Grammatical Error Correction

Grammatical error correction (GEC) is the task of automatically correcting grammatical errors in written text. Earlier attempts to grammatical error correction involve rule-based and classiﬁer approaches which are limited to correcting only some particular type of errors in a sentence. As sentences may contain multiple errors of di ﬀ erent types, a practical error correction system should be able to detect and correct all errors. In this report, we investigate GEC as a translation task from incorrect to correct English and explore some machine translation approaches for developing end-to-end GEC systems for all error types. We apply Statistical Machine Translation (SMT) and Neural Machine Translation (NMT) approaches to GEC and show that they can correct multiple errors of di ﬀ erent types in a sentence when compared to the earlier methods which focus on individual errors. We also discuss some of the weakness of machine translation approaches. Finally, we also experiment on a candidate re-ranking technique to re-rank the hypotheses generated by machine translation systems. With regression models, we try to predict a grammaticality score for each candidate hypothesis and re-rank them according to the score.
Modeling of Ebola Control Strategies

In the last two years Ebola has filled news headlines more than ever, it is mainly because of the large outbreak in West Africa in 2014-2015 with thousands of casualties. What are the options for control of this deadly disease? This paper provides an innovative model of Ebola transmission and discusses three control strategies: hospitalization, burial teams, and probability of seeking hospitalization. By varying certain parameters we measure the effectiveness of these interventions and we focus on suggesting solutions.
METABOLIC SYNDROME AND CHRONIC DISEASES IN PATIENTS WITH CHRONIC OBSTRUCTIVE PULMONARY DISEASE

Yöntem: Bu çalışma periyodu sırasında, 66 KOAH ve kontrol grubu olarak da 40 kişi dahil edildi. Solunum fonksiyon testleri (SFT) flow sensitif spirometri ile ATS kriterlerine göre yapıldı. BODE indeksleri hesaplandı. Kronik hastalıklar şiddet indeksi Modifiye kümülatif hastalıklar değerlendirme ölçeği (MKHDÖ) kullanılarak değerlendirildi. MS, National Cholesterol Education Program (NCEP)’a göre tanımlandı. Total metabolik bozukluk skoru da ayrıca hesaplandı.
Simple Shear Flow of Collisional Granular-Fluid Mixtures

This work deals with the simple shear flow of neutrally buoyant, rigid, frictionless spheres immersed in a viscous fluid that exchange momentum through inelastic collisions. It is shown how kinetic theories are able to provide a full analytical description of the flow, once the influence of the viscous fluid is taken into account in a simple way through the dependence of the collisional coefficient of restitution on the Stokes number. This allows the capture of the characteristics of the experiments performed by Bagnold 60 years ago and the interpretation of the macroviscous and inertial regimes described by the same author as the limits for the coefficient of restitution equal to zero and to the value valid in absence of the viscous fluid, respectively. DOI: 10.1061/(ASCE)HY.1943-7900.0000701. © 2013 American Society of Civil Engineers. CE Database subject headings: Shear flow; Kinetics; Rheology; Coefficients. Author keywords: Simple shear flow; Kinetic theory; Granular-fluid mixture; Rheology.