Miracle-dz/UniFAR-FTUs huggingface dataset:
Artificial Intelligence Applied to Colonoscopy: Is It Time to Take a Step Forward?

Simple Summary In recent years, there has been an exponential rise in artificial intelligence-based technology. Artificial intelligence has been applied to several medical disciplines, such as gastroenterology. In the field of endoscopy, a wide variety of applications for artificial intelligence algorithms have been developed or are in a process of improvement. Computer-aided polyp detection and characterization are two of the most studied applications. In addition, there are several reports of other potential applications, such as the assessment of bowel preparation quality, while another future prospect is the prediction of cancer invasion depth. However, certain concerns remain, such as the universal use of this technology in clinical practice, impact on the incidence of interval colorectal cancer, cost-effectiveness, workload and patient burden. Abstract Growing evidence indicates that artificial intelligence (AI) applied to medicine is here to stay. In gastroenterology, AI computer vision applications have been stated as a research priority. The two main AI system categories are computer-aided polyp detection (CADe) and computer-assisted diagnosis (CADx). However, other fields of expansion are those related to colonoscopy quality, such as methods to objectively assess colon cleansing during the colonoscopy, as well as devices to automatically predict and improve bowel cleansing before the examination, predict deep submucosal invasion, obtain a reliable measurement of colorectal polyps and accurately locate colorectal lesions in the colon. Although growing evidence indicates that AI systems could improve some of these quality metrics, there are concerns regarding cost-effectiveness, and large and multicentric randomized studies with strong outcomes, such as post-colonoscopy colorectal cancer incidence and mortality, are lacking. The integration of all these tasks into one quality-improvement device could facilitate the incorporation of AI systems in clinical practice. In this manuscript, the current status of the role of AI in colonoscopy is reviewed, as well as its current applications, drawbacks and areas for improvement.
Parallel implementation of explicit 2 and 3-point block methods for solving system of special second order ODEs directly

In this paper the explicit 2 and 3-point block method for solving large systems of special second order ODEs directly is discussed. Codes based on the methods are executed in sequential and parallel. The numerical results show that parallel execution of the methods is more efficient compared to sequential counterpart for solving the large system of special second order ODEs.
Ki67 proliferation index quantification using silver standard masks

Deep learning (DL) systems obtain high accuracy on digital pathology datasets that are within the same distribution as the training set. When applied to unseen datasets, performance degradation occurs due to differences in acquisition hardware/software and staining protocols/vendors. This issue poses a barrier to translation since developed models cannot be readily deployed at new labs. To overcome this challenge, we present silver standard (SS) annotations as a method to improve the performance of deep learning architectures on unseen Ki67 pathology images. An unsupervised technique referred to as IHCCH was used to generate SS masks for Ki67+ and Ki67− nuclei from the target lab. A previously validated architecture for Ki67, UV-Net, is trained with a combination of the gold standard (GS) and SS masks to enhance performance consistency. It was found that adding SS masks from the unseen center to the training pool improved performance over clinically relevant PI ranges.
Generation of training dataset for deep-learning noise reduction

Deep-learning (DL) is used extensively in the noise reduction of x-ray computed tomography. In DL, the availability of ground-truth images (GTI) is critical. GTI contains all anatomical information of the low-dose dataset at a much-reduced noise level, resembling that of a high-dose scan of the object. Clinical GTI, however, is difficult to obtain because of ethical and practical constraints. Although the use of model-based-iterative-reconstruction (MBIR) has been proposed, resulting DL images inherent undesired noise characteristics of MBIR. We propose an approach to utilize low-dose FBP images to generate GTI. The approach is based on the observation that the noise in a thick-slice image (TSI) is suppressed while good texture is maintained. Unfortunately, anatomical details of TSI are degraded, resulting from z-averaging. The proposed approach takes the subtraction-image (SI) between the original and TSI, and performs iterative noise reduction (guided by the standard deviation of SI) to gradually remove noise in SI. After the processing, only the differential anatomical structure between the original and TSI remains. This structure is then subtracted from TSI to arrive at GTI. The amount of noise reduction can be adjusted by modifying the slice-thickness of TSI (a factor of 2.4 noise reduction is selected for this study). This approach is evaluated extensively with both clinical neural and body images. For robustness evaluation, all parameters were kept unchanged. For better visual inspection, difference images between the original and GTI are evaluated and negligible residual structure can be detected.
A cluster algorithm for graphs

A cluster algorithm for graphs called the \emph{Markov Cluster algorithm} (MCL~algorithm) is introduced. The algorithm provides basically an interface to an algebraic process defined on stochastic matrices, called the MCL~process. The graphs may be both weighted (with nonnegative weight) and directed. Let~$G$~be such a graph. The MCL~algorithm simulates flow in $G$ by first identifying $G$ in a canonical way with a Markov graph $G_1$. Flow is then alternatingly expanded and contracted, leading to a row of Markov Graphs $G_{(i)}$. Flow expansion corresponds with taking the~$k^{th}$~power of a stochastic matrix, where~$k\in\N$. Flow contraction corresponds with a parametrized operator~$\Gamma_r$, $r\geq 0$, which maps the set of (column) stochastic matrices onto itself. The image~$\Gamma_r M$ is obtained by raising each entry in~$M$ to the~$r^{th}$~power and rescaling each column to have sum~$1$ again. The heuristic underlying this approach is the expectation that flow between dense regions which are sparsely connected will evaporate. The invariant limits of the process are easily derived and in practice the process converges very fast to such a limit, the structure of which has a generic interpretation as an overlapping clustering of the graph~$G$. Overlap is limited to cases where the input graph has a symmetric structure inducing it. The contraction and expansion parameters of the MCL~process influence the granularity of the output. The algorithm is space and time efficient and lends itself to drastic scaling. This report describes the MCL~algorithm and process, convergence towards equilibrium states, interpretation of the states as clusterings, and implementation and scalability. The algorithm is introduced by first considering several related proposals towards graph clustering, of both combinatorial and probabilistic nature.
Digital magnetoresistance characteristics of NiFeCo/Cu/Co spin-valve trilayers

Digital magnetoresistance (MR) properties of the sheet and patterned NiFeCo/Cu/Co spin-valve trilayer films were characterized. As reported in our previous publication, NiFeCo/Cu/Co films showed strong in-plane uniaxial magnetic anisotropy on a special template, 4/spl deg/tilt-cut Si(111) wafer with a 50 /spl Aring/ of Cu underlayer, without any externally applied magnetic field during the deposition. In order to demonstrate the industrial applicability of NiFeCo/Cu/Co films on the specific templates for digital MR devices, dynamic and static MR measurements were performed along the easy axis of the films. For dynamic MR measurement, NiFeCo/Cu/Co films were optimized with respect to Cu spacer thickness and patterned into a stripe of high aspect ratio of 1: 200 (height: width) where the easy aids of the film was aligned along the height direction. After patterning, uniaxial magnetic anisotropy was maintained, and MR properties showed no appreciable degradation. Therefore, it was believed that the special template is effective for the uniaxial magnetic anisotropy of NiFeCo/Cu/Co films and useful in the industrial applications. MR properties of sheet and patterned trilayer films suggest that these NiFeCo/Cu/Co spin valves on the specific templates are good candidates for digital MR devices such as magnetoresistive random access memory (MRAM).
Analytical Modeling of Open-Circuit Air-Gap Flux Density in Interior Permanent Magnet Machine

In this article, a general analytical model suitable for the magnetic analysis of the interior permanent magnet (IPM) machine is proposed by coupling the equivalent model and Maxwell’s equation-based 3-D analytical model. In the proposed analytical model, to reduce boundary conditions, the IPM topology is transformed into the surface-mounted permanent magnet (SPM) topology through the equivalent model with universality. Meanwhile, Maxwell’s equation-based 3-D analytical model is established to conduct magnetic analysis and then gives a unified expression of air-gap flux density of the IPM machine. Then, the saliency effect is considered using the saliency coefficient, which is deduced by the magnetomotive force (MMF) and flux-path permeance model. In addition, the slotting effect is considered by conformal mapping. The saliency and slotting effect act on additional functions in the analytical model. Finally, the accuracy of the analytical method is validated by the finite-element method (FEM) in the IPM machine condition.
Performance of a causal anisotropic absorber for the truncation of finite element meshes in time domain electromagnetic unbounded problems

The application of a new causal anisotropic absorber for the truncation of time domain finite element meshes is presented. Numerical results are illustrated in order to show the performance of the absorber. Both homogeneous and stratified absorbers are considered and their performances compared. The computational efficiency of the finite element code implementing this absorber is also proven by comparing its computational cost with that one of a conventional time domain finite element code with boundary conditions given by perfect conductors and no absorber.
XML and Context Structural Features Relevant to Search Tasks

The work presented in this paper is part of a research project that studies and develops an experimental approach to correlate user needs and IR strategies on the use of structural information. Its goal is to investigate the use of structural features for effective information retrieval and to define a model to link search tasks to specific retrieval strategies. In this paper, we define a first classification of search tasks in structured document collections based on two dimensions: the type of information a user is seeking for (informational or resource) and the user familiarity with the structure of the documents (high, some or none). We then classify the INEX 2004 topics into the defined task categories, and analyse the relevance of several structural features regarding each of these tasks for the INEX collection. We investigate the following research questions:
Raman spectroscopy for analysis of thorium compounds

The thorium fuel cycle is an alternative to the uranium fuel cycle in that when 232Th is irradiated with neutrons it is converted to 233U, another fissile isotope. There are several chemical forms of thorium which are used in the Th fuel cycle. Recently, Raman spectroscopy has become a very portable and facile analytical technique useful for many applications, including e.g. determining the chemical composition of different materials such as for thorium compounds. The technique continues to improve with the development of ever-more sensitive instrumentation and better software. Using a laboratory Fourier-transform (FT)-Raman spectrometer with a 785 nm wavelength laser, we were able to obtain Raman spectra from a series of thorium-bearing compounds of unknown origin. These spectra were compared to the spectra of in-stock-laboratory thorium compounds including e.g. ThO2, ThF4, Th(CO3)2 and Th(C2O4)2. The unknown spectra showed very good agreement to the known standards, demonstrating the applicability of Raman spectroscopy for detection and identification of these nuclear materials.
Modeling Managers As EPS Maximizers

Textbook theory assumes that firm managers maximize the net present value of future cash flows. But when you ask them, the people running large public corporations say that they are maximizing something else entirely: earnings per share (EPS). Perhaps this is a mistake. No matter. We take managers at their word and show that EPS maximization provides a single unified explanation for a wide range of corporate policies such as leverage, share issuance and repurchases, M&A payment method, cash accumulation, and capital budgeting.
Statistical properties of polarized radio continuum emission and effects of data processing

Polarized intensity and polarization angles are calculated from Stokes parameters Q and U in a nonlinear way. The statistical properties of polarized emission hold information about the structure of magnetic fields in a large range of scales, but the contributions of different stages of data processing to the statistical properties should first be understood. We use 1.4 GHz polarization data from the Effelsberg 100-m telescope of emission in the Galactic plane, near the plane and far out of the plane. We analyze the probability distribution function and the wavelet spectrum of the original maps in Stokes parameters Q, U and corresponding PI . Then we apply absolute calibration (i.e. adding the large-scale emission to the maps in Q and U ), subtraction of polarized sources and subtraction of the positive bias in PI due to noise (“denoising”). We show how each procedure affects the statistical properties of the data. We find a complex behavior of the statistical properties for the different regions analyzed which depends largely on the intensity level of polarized emission. Absolute calibration changes the morphology of the polarized structures. The statistical properties change in a complex way: Compact sources in the field flatten the wavelet spectrum over a substantial range. Adding large-scale emission does not change the spectral slopes in Q and U at small scales, but changes the PI spectrum in a complex way. “Denoising” significantly changes the p.d. f. of PI and raises the entire spectrum. The final spectra are flat in the Galactic plane due to magnetic structures in the ISM, but steeper at high Galactic latitude and in the anticenter. For a reliable study of the statistical properties of magnetic fields and turbulence in the ISM based on radio polarization observations, absolute calibration and source subtraction are required.
Nonparametric particle filtering and smoothing with quasi-Monte Carlo sampling

Sequential Monte Carlo methods (also known as particle filters and smoothers) are used for filtering and smoothing in general state-space models. These methods are based on importance sampling. In practice, it is often difficult to find a suitable proposal which allows effective importance sampling. This article develops an original particle filter and an original particle smoother which employ nonparametric importance sampling. The basic idea is to use a nonparametric estimate of the marginally optimal proposal. The proposed algorithms provide a better approximation of the filtering and smoothing distributions than standard methods. The methods’ advantage is most distinct in severely nonlinear situations. In contrast to most existing methods, they allow the use of quasi-Monte Carlo (QMC) sampling. In addition, they do not suffer from weight degeneration rendering a resampling step unnecessary. For the estimation of model parameters, an efficient on-line maximum-likelihood (ML) estimation technique is proposed which is also based on nonparametric approximations. All suggested algorithms have almost linear complexity for low-dimensional state-spaces. This is an advantage over standard smoothing and ML procedures. Particularly, all existing sequential Monte Carlo methods that incorporate QMC sampling have quadratic complexity. As an application, stochastic volatility estimation for high-frequency financial data is considered, which is of great importance in practice. The computer code is partly available as supplemental material.
On the presence of Cephalanthera caucasica (Orchidaceae) in Russia: rediscovery of a threatened orchid in the Republic of Dagestan

Cephalanthera caucasica had been reported previously from the Samur Forest in Dagestan (Russia), but that report was considered doubtful: a possible misidentification of supposed hybrids between C. damasonium and C. longifolia as C. caucasica was speculated. Moreover, this species was recently reduced to a synonym of C. kotschyana in the «Plants of the World Online» database. In the present study, we did not confirm the presence of C. caucasica in the Samur Forest, but it was revealed in a few localities in remnants of beech (Fagus orientalis) forests in Kaytagskiy district and Tabasaranskiy district in the Republic of Dagestan, Russia. Living plants were studied in the vicinity of the village Tatil where 40 flowering individuals were counted. A morphological study suggested that these plants belonged to typical C. caucasica, not to any hybrid. The synonymy of this species with C. kotschyana has also been rejected, because it contradicted to the «International Code of Nomenclature for algae, fungi, and plants» and, besides, was not properly reasoned. The lectotype of C. caucasica is designated in the present paper. The description of the species is provided with measurements of the main morphological parameters. Differences of C. caucasica and the related taxa are discussed. A key to the species of the genus Cephalanthera from the North Caucasus is provided. Cephalanthera caucasica is highly threatened in Russia, being estimated as Endangered taxon (EN B1ab(iii)+2ab(iii)), according to the IUCN categories and criteria. It should be included to the next editions of both national and regional Red Data Books.
Reproductive Biology of Male European Hake (Merluccius merluccius) in Central Mediterranean Sea: An Overview from Macroscopic to Molecular Investigation

Simple Summary The vast majority of the world’s commercial fish stocks are considered overfished. Among demersal species, in the Mediterranean Sea, the European hake (Merluccius merluccius) is experiencing high fishing pressure, resulting in a critical overexploitation status. The reproductive pattern of the male sex is poorly investigated. In order to provide scientific advice for its sustainable management, this study gave, for the first time in the Central Mediterranean Sea, an overview of the reproductive biology of male European hakes, by using a multidisciplinary approach. The sex ratio throughout the three-year period and by length class showed that males dominated the population from February to June and up to 24 cm, respectively. The reproduction occurred all year round with a seasonal peak in spring/summer. The macroscopic and histological sizes at first maturity were 18.6 cm and 15.4 cm, respectively. The entire reproductive cycle was unequivocally identified by five histological developmental stages of the testis. Finally, the molecular approach allowed us to investigate endocrine regulation from the onset of puberty to the adult lifecycle. Abstract The improvement of scientific knowledge about overexploited fishery resources allow us to provide scientific advice for their management and stock protection. By using a multidisciplinary approach, the aim of the study was to characterize, for the first time in the Central Mediterranean Sea (GSA 17), the reproductive biology of males of M. merluccius, currently highly exploited. A multi-year sampling from January 2017 to December 2019 was performed to exhaustively evaluate the sex ratio of the stock, while the 2018 annual sampling was selected to investigate the reproductive pattern of males. Individuals in spawning conditions were found every month, proving that M. merluccius is an asynchronous species, reproducing all year round, with a seasonal reproductive peak in spring/summer, as indicated by GSI. Five gonadal development stages were defined to fully describe the reproductive cycle of males. The macroscopic and histological L50, respectively 18.6 cm and 15.4 cm, were both below the Minimum Conservation Reference Size (MCRS). According to the mRNA levels, fsh and lh played a significant role during spermiation, whereas the gnrhr2a was involved at the beginning of sexual maturity. In the testis, fshr and lhr reached maximum expression levels before the spermiation. The hormonal stimuli of 11-ketotestosterone and its receptor were significantly higher when the specimen was in reproductive activity.
Doppler Radar Analysis of a Snake River Plain Convergence Event

Abstract A convergence zone periodically forms in the Snake River plain (SRP) of eastern Idaho as a result of terrain-induced boundary layer flow under synoptic northwesterly flow at low and midlevels. Complex terrain in central and eastern Idaho is critical to the formation of this mesoscale feature, which is characterized by wind shift lines accompanied by cumulus or stratocumulus bands. These cloud bands routinely produce virga or light rain or light snow and, occasionally, result in moderate to heavy precipitation. Doppler weather radar analysis of a convergence event that produced heavy postfrontal snowfall in the lower SRP on 26 November 1995 is presented. This event was selected for study because significant snowfall resulted from a persistent and well-defined boundary layer convergence zone. The high-resolution (40 km) Eta Model data available from the National Centers for Environmental Prediction did not sufficiently resolve the mesoscale processes that initiated this event. The Eta Model indicat.