Miracle-dz/UniFAR-FTUs huggingface dataset:
Can multiple segmentation methods enhance deep learning networks generalization? A novel hybrid learning paradigm

Deep learning methods are the state-of-the-art for medical imaging segmentation tasks. Still, numerous segmentation algorithms based on heuristic-based methods have been proposed with exceptional results. To validate segmentation algorithms, manual annotations are typically considered as ground truth. However, manual annotations often suffer from inter/intra-operator variability and can also be occasionally inaccurate, especially when considering time-consuming and precise tasks. A sample case is the manual delineation of the lumen-intima (LI) and media-adventitia (MA) borders for intima-media thickness (IMT) measurement in B-mode ultrasound images. In this work, a novel hybrid learning paradigm which combines manual segmentations with the automatic segmentation of a dynamic programming technique for ground truth determination is presented. A profile consensus strategy is proposed to construct the hybrid ground truth. Two open-source datasets (n=2576) were employed for training four deep learning networks using the hybrid learning paradigm and three single source training targets as a comparison. The pipeline was fixed across the four tests and included a Faster R-CNN detection network to locate the carotid artery and then subsequent division into patches which were segmented using a UNet. The validation of the results was performed on an external test set comparing the predictions of the four different models to the annotations of three independent manual operators. The hybrid learning paradigm showed the best overall segmentation results (Dice=0.907±0.037, p<0.001) and demonstrated an exceptional correlation between the mean of three operators and the automatic measure (ICC(2,1)=0.958), demonstrating how the incorporation of heuristic-based segmentation methods within the learning paradigm of a deep neural network can enhance and improve final segmentation performance results.
On the Essence of Generic Sentence and Concept

Generic sentences appear to have universal quantifications. They, nevertheless, tolerate exceptions. This is the main feature of generics and also the most puzzling problem to be solved in the researches about them. This feature indicates that generics express something involving intensionality. Based on intensional semantics, this paper uses a formal method to reveal that generic sentences express the intensions of concepts, and shows that what generics are about. Thus, some puzzling phenomena around generics are explained with satisfaction. This discovery relies on several assumptions: Concepts are functions mapping from a set of possible worlds to the power set of a set of intensions; the intension of a concept is the set of all generic consequences derived from the sense of the term that expresses the concept; etc. However, these assumptions are not in accord with the traditional views. To make the results presented here more conclusive, the fundamental properties from the bottom line of the concepts are discussed and analyzed. They are summarized to be seven basic properties of concepts. The positions proposed in this paper are argued for and enforced by exploring the relation between concept and language, as well as the relation between concept and knowledge. These arguments consist of a new theory of concept.
Music Similarity Estimation based on Feature Extraction and Deep Learning

The field of music information retrieval (MIR) has developed rapidly in recent years, which provides a lot of convenience for people's entertainment life after combining with big data and deep learning. This paper studies music similarity estimation in the field of music information retrieval. To be specific, based on the deep learning of music feature data, the music similarity model (a classifier) is obtained to judge whether the music similarity reaches more than 50% (i.e., random model). According to the experiment, using the Siamese neural network to train the model with chroma features as input can achieve high accuracy. It will make it more convenient for music recommendation, humming recognition and plagiarism identification. In the future, more researches ought to focus on the real value instead of classifier to judge the similarity or at least the clustering model (multiple thresholds instead of two). Anyway, these results shed light on guiding further exploration focusing on similarity extraction of music in the context of the state-of-art deep learning scenarios.
Special points on orthogonal symmetric spaces

The theory of complex multiplication has been a powerful tool for studying various aspects of classical modular forms along with their generalizations. With the recent work of Borcherds there has been an increase in the interest in studying modular forms on orthogonal groups of signature (2,n) as well as the spaces on which they live. In this thesis, we study the special points (or CM-points) that exist on these spaces. We develop cohomological classifications relating the special points, their associated CM-fields and the spaces in which these points can be found. %%%%La theorie de la multiplication complexe nous donnent des outils puissants pour etudier des aspects divers des formes modulaires classiques, ainsi que leurs generalisations. Les travaux recents de Borcherds donne une nouvelle motivation pour etudier les formes modulaires sur des groupes orthogonaux de signature (2,n), ainsi que les espaces sur lesquels elles agissent. Dans cette these, nous etudierons les points speciaux (ou points-CM) qui existent dans ces espaces. Nous developperons des classifications cohomologiques concernant les points speciaux, les corps-CM associes et les espaces dans lesquels ces points peuvent etre trouvees.
Role of Oritavancin in the Treatment of Infective Endocarditis, Catheter- or Device-Related Infections, Bloodstream Infections, and Bone and Prosthetic Joint Infections in Humans: Narrative Review and Possible Developments

Oritavancin is a long-acting lipoglycopeptide with in vitro activity against Gram-positive pathogens, as well as good bactericidal activity and sterilisation ability in biofilm. It has been approved for acute bacterial skin and skin structure infections (ABSSSI), but recent reports have demonstrated possible off-label uses, such as for vancomycin resistant enterococci (VRE), deep-seated infections including those involving prosthetic material and invasive infections. The aim of this work is to review the uses of oritavancin outside of ABSSSI, focusing on its real-life applications on infective endocarditis, catheter- or device-related infections, bloodstream infections, and bone and prosthetic joint infections in humans, as well as possible future applications. We performed a narrative review, collecting the literature published between 1 December 2002 and 1 November 2022 on PubMed and the Cochrane Library using the term ‘oritavancin’. Available studies have shown how effective it is in different settings, suggesting an opportunity for step-down strategies or outpatient management of infections requiring a long duration of antibiotic treatment. So far, evidence is still scarce, and limited to a few studies and case reports, mostly focusing on Staphylococcus aureus as the major isolate. Concerns about fluid intake for dilution and interaction with coagulation markers also need to be taken into account. Further studies are required in order to assess the safety and effectiveness of Oritavancin in vascular, prosthetic, or device-related infections, as well as in resistant Gram-positive bacteria or enterococcal infections.
Sustainable Innovation: Turning Waste into Soil Additives

In recent years, a dynamic increase in environmental pollution with textile waste has been observed. Natural textile waste has great potential for environmental applications. This work identifies potential ways of sustainably managing natural textile waste, which is problematic waste from sheep farming or the cultivation of fibrous plants. On the basis of textile waste, an innovative technology was developed to support water saving and plant vegetation- biodegradable water-absorbing geocomposites (BioWAGs). The major objective of this study was to determine BioWAG effectiveness under field conditions. The paper analyses the effect of BioWAGs on the increments in fresh and dry matter, the development of the root system, and the relative water content (RWC) of selected grass species. The conducted research confirmed the high efficiency of the developed technology. The BioWAGs increased the fresh mass of grass shoots by 230-420% and the root system by 130-200% compared with the control group. The study proved that BioWAGs are a highly effective technology that supports plant vegetation and saves water. Thanks to the reuse of waste materials, the developed technology is compatible with the assumptions of the circular economy and the goals of sustainable development.
Multi-view based computer-aided model with anatomical position prior for architectural distortion detection in digital breast tomosynthesis

Architectural distortion (AD) is one of the important breast abnormal signs in digital breast tomosynthesis (DBT). It is hard to be detected due to its subtle appearance and similar intensity with surrounding tissue. To assist radiologists to detect ADs, a single-view based computer-aided detection model in DBT was developed by us previously. In this study, considering the fact that radiologists always use information from craniocaudal (CC) and mediolateral oblique (MLO) views of DBT simultaneously for better diagnosis of each breast in clinic, we further develop a multi-view based AD detection model in DBT that combines the information from the two views. In this model, AD candidates in each view are detected by our previous AD detection model. Anatomical position priors of AD candidates in the two views are considered through establishing a 3D anatomical coordinate system. A multi-view based classifier is trained to fuse information from the two views and distinguish the true AD candidates. A dataset of 196 CC-MLO DBT pairs were collected with IRB approval, 101 of them contained ADs and the remaining were negative pairs. Ten-fold cross-validation showed that after involving our proposed multi-view method, the sensitivities of AD detection at 1, 2, 3 and 4 false positive predictions per DBT pairs improved from 0.66, 0.73, 0.77 and 0.79 to 0.69, 0.77, 0.78, and 0.83, respectively. The results showed that the multi-view based model achieved better detection performance than single-view based model. This model has potential to assist radiologists in detection of ADs in DBT.
Tripeptide IRW Improves AMPK/eNOS Signaling Pathway via Activating ACE2 in the Aorta of High-Fat-Diet-Fed C57BL/6 Mice

Simple Summary Metabolic syndrome refers to a cluster of various risk factors commonly associated with cardiovascular diseases and diabetes. Upregulation of angiotensin-converting enzyme 2 (ACE2), a key member of the renin–angiotensin system (RAS), is in general protective against cardiovascular diseases and diabetes. Peptide IRW was previously shown to upregulate ACE2 in spontaneously hypertensive rats, but not the skeletal muscle ACE2 in a high-fat-diet (HFD)-induced insulin-resistant mouse model. The study aims to investigate the regulatory role of peptide IRW on aortic ACE2 and its associated signaling pathways in HFD-induced insulin-resistant mice. Our results indicated that upregulation of aortic ACE2 by peptide IRW in HFD-induced insulin-resistant mice is responsible for the activation of the pathways associated with vasodilation of blood vessels, which might play a role in improving insulin resistance and glucose metabolism. Abstract This study aims to investigate the effect of tripeptide IRW on the local renin–angiotensin system (RAS), particularly angiotensin-converting enzyme 2 (ACE2), and their association with signaling pathways in the aorta of a high-fat-diet (HFD)-induced insulin-resistant mouse model. C57BL/6 mice were fed HFD (45% of the total calories) for six weeks, and then IRW was added to the diet (45 mg/kg body weight (BW)) for another eight weeks. ACE2 mRNA expression and protein level(s) were increased (p < 0.05), while angiotensin II receptor (AT1R) and angiotensin-converting enzyme (ACE) protein abundance was significantly reduced (p < 0.05) in the aorta of HFD mice treated by IRW. IRW supplementation also improved glucose transporter 4 (GLUT4) abundance (p < 0.05) alongside AMP-activated protein kinase (AMPK) (p < 0.05), Sirtuin 1 (SIRT1) (p < 0.05), and endothelial nitric oxide synthase (eNOS) (p < 0.05) expression. IRW downregulated the levels of endothelin 1 (ET-1) and p38 mitogen-activated protein kinases (p38 MAPK, p < 0.05). Furthermore, the levels of AMPK and eNOS in vascular smooth muscle cells (VSMCs) were significantly reduced in ACE2 knockdown cells treated with or without IRW (p < 0.01). In conclusion, this study provided new evidence of the regulatory role of IRW on the aortic ACE2 against metabolic syndrome (MetS) in an HFD-induced insulin-resistant model.
Electrosynthesized CuMgAl Layered Double Hydroxides as New Catalysts for the Electrochemical Reduction of CO2

In this study, new nanostructured CuMgAl Layered Double Hydroxide (LDH) based materials are synthesized on a 4 cm2 sized carbonaceous gas diffusion membrane. By means of microscopic and spectroscopic techniques, the catalysts are thoroughly investigated, revealing the presence of several species within the same material. By a one‐step, reproducible potentiodynamic deposition it is possible to obtain a composite with an intimate contact between a ternary CuMgAl LDH and Cu0/Cu2O species. The catalyst compositions are investigated by varying: the molar ratio between the total amount of bivalent cations and Al3+, the amount of loading, and the molar ratios among the three cations in the electrolyte. Each electrocatalyst has been evaluated based on the catalytic performances toward the electrochemical CO2 reduction to CH3COOH at −0.4 V versus reversible hydrogen electrode in liquid phase. The optimized catalyst, that is, CuMgAl 2:1:1 LDH exhibits a productivity of 2.0 mmolCH3COOH gcat−1 h−1. This result shows the beneficial effects of combining a material like the LDHs, alkaline in nature, and thus with a great affinity to CO2, with Cu0/Cu+ species, which couples the increase of carbon sources availability at the electrode with a redox mediator capable to convert CO2 into a C2 product.
New Records of Tardigrades from the Danco and Graham Coasts, the Maritime Antarctic

Abstract. Antarctic is an area with extreme conditions for the survival of living organisms, as well as a specific region for conducting research. For this reason, studies of Antarctic tardigrades are rather fragmentary. Since 1904, when the first tardigrade was described in the Antarctic, up to the present, 76 species of tardigrades have been reported from Antarctic and Subantarctic regions. In this paper, we report seven tardigrade taxa found in different locations of the western coast of the Antarctic Peninsula during the 26th Ukrainian Antarctic Expedition. Diphascon puchalskii and Mesobiotus aradasi are recorded for the first time outside type localities for Danco Coast and the area outside King George Island correspondently.
Dealing with asynchronicity in parallel Gaussian Process based global optimization

During the last decade, Kriging-based sequential algorithms like EGO and its variants have become reference optimization methods in computer experiments. Such algorithms rely on the iterative maximization of a sampling criterion, the expected improvement (EI), which takes advantage of Kriging conditional distributions to make an explicit trade-off between promizing and uncertain search space points. We have recently worked on a multipoints EI criterion meant to simultaneously choose several points, which is useful for instance in synchronous parallel computation. Here we propose extensions of these works to asynchronous parallel optimization and focus on a variant of EI, EEI, for the case where some new evaluation(s) have to be done while the reponses of previously simulations are not all known yet. In particular, different issues regarding EEI's maximization are addressed, and a proxy strategy is proposed.
Analysis and synthesis of robust control system with separable nonlinearities.

The objective of this thesis is to propose a design method for controllers to secure specified robust oscillation amplitude and frequency for separable nonlinear systems exhibiting unavoidable or desirable limit cycles. The design approach of robust limit cycle controllers introduced here can be used for autonomous systems with separable single-input-single-output nonlinearities. The proposed design approach consists of quasi-linearization of the nonlinearity via the Describing Function (DF) method and then shaping the loop to reach desired limit cycle characteristics. As the DF method is used, loop shaping takes place in the Nyquist plot, because the intersection between the loop shaped loci and the DF negative reciprocal loci is related to the limit cycle characteristics of the system. In the problem addressed in this thesis, the original linear subsystem (i.e. without controller) is considered as an uncertain system with unstructured uncertainty. A condition to be satisfied by the shaped loop is given such that the controlled system has limit cycle characteristics as close as possible to the nominal characteristics even though the uncertainty considered. Three requirements are satisfied in the loop shaping step. The first requirement assures the nominal desired limit cycle characteristics in the designed system. The second is related to limit cycle stability, i.e., if a (small) perturbation disturbs the limit cycle of the controlled system, it will return to the earlier limit cycle. The third requirement addresses the robustness question, and the condition mentioned before is used. After the loop is shaped to satisfy the requirements, a controller is computed so that the controlled linear subsystem transfer function is equal the transfer function obtained in the loop shaping. This approach is applicable to systems with linear subsystems that are minimum phase. In some cases it may be necessary to add a high frequency pole in order to obtain a proper controller. Examples are given in order to illustrate the robustness of the controlled system with respect to uncertainty in the linear subsystem model. In the first example the intersection between the loop shaped loci and the DF negative reciprocal loci is on the real axis. In the second example the crossing point is not on the real axis and so, restrictions more generals than the ones used in the first example are used. In the third example the crossing point is on the real axis and output disturbance is considered.
Mycotoxins in fermented foods: A comprehensive review

While the super-swift escalation of antibiotic-resistant pathogenic microbial strains is a great matter of public health concern; however, mycotoxins are not to be forgotten as well. According to the statistical analyses, mycotoxins contaminate up to 25 % of the world’s food supply and contribute to a substantial amount of food spoilage. These toxins, which are secondary metabolites of certain species of pathogenic fungi, are responsible for a variety of adverse health effects that range from acute food poisoning to long-term effects, such as cancer; pregnancy disruption, and immunodeficiency. Although fermented foods have been consumed since time immemorial, in the 21 st century, they are gaining immense popularity owing to their numerous health benefits. However, it should be noted that mycotoxin-infested fermented food is not uncommon, due to the use of poor-quality starter microbial cultures for fermentation and/or other improper practices; thus making this mycotoxin-infested fermented food an important food safety issue. However, due to the recent developments in food processing and the advent of very sophisticated and precise techniques, such as immunoassay and chromatography analysis, which are used to detect these mycotoxins, detecting their presence has become easier. This review aimed to address several aspects pertaining to mycotoxins, including their predominant types and producer fungi; their harmful effects, methods of sampling and extraction from fermented foods, and their detection and analysis techniques, in addition to the methods used to mitigate those.
ON THE INTERNAL STRUCTURE OF SUPER-DENSE STARS

The properties of a condensed-state-plasma phase transition in ultra- compressed matter are discussed and it is concluded that the core of dense white dwarfs may be in a condensed state. From these conclusions it is stated that the rate of nuclear processes is much lower (compared to that in a plasma) and the possible concentration of hydrogen in the matter of white dwarfs may be much higher. (auth)
Application of Sobel Operator in Optical Correlation Target Recognition

In this paper, image edge detection is applied to joint transform correlator, and Sobel operator is used as the detect operator. Power spectrum and correlation peaks of object plane have been simulated by VC++ program in correlation detection. This method improved the ratio of target recognition, got much sharper correlation peaks than original image, and has better effect on detecting low contrast targets.
Zur Parametrisierung radialsymmetrischer Dichtemodelle für die Erde

Even in the frame of a spherical symmetric, non-rotating, linear elastic and isotropic model an independent description of the Earth’s density and elastic properties, as usual in most existing models, has no unique solution and thus leads to an over-parametrisation. Whereas the elastic properties can be verified well with the help of seismic traveltimes, the density remains much less determinate. With this work, an adequate description of a normal density distribution based on a physically meaningful, non-empirical parametrisation and an abstraction to the essential physical properties will be presented. Beside the postulate on homogeneity of the chemical composition and phase inside each shell and an adiabatic gradient of temperature, the main assumption is hydrostatic equilibrium, which must be fulfilled in a global sense for the widest parts of the Earth’s interior. Under these circumstances the WilliamsonAdams-equation holds as a fundamental relation between density and seismic velocities. Deviations from the underlying suppositions can be described, if necessary and appropriate information exists, a priori by the Bullen-Parameter. By the physical relation between density and seismic velocities alone a parametrisation is not given. With the help of a postulate on a pressure-density-relation in historical density laws it is possible to develop a suitable function. A differential equation follows from the Poisson equation for the inner gravitational potential in conjunction with that postulate and the assumption of hydrostatic equilibrium. Its special solutions lead in consistence with seismic data to a parametrisation of the density. Extensive investigations show that only functions in even powers of the radius allow a best and stable fit to the seismic data, while ordinary polynomials most common in use are less eligible for a description of the density. Furthermore, to obtain a stable determination of the density a strict separation of the data-types is unavoidable. From the seismic velocities it is only possible to infer the shape of the density-function within the shells, additional data as the density below the crust-mantle-boundary, the geodetic values for mean mass and mean moment of inertia and the frequencies of the free oscillations are necessary to fix the absolute level in each shell. Under consideration of the aforementioned aspects it is possible to obtain a unique and stable description of a normal density distribution in accordance with seismic and geodetic information. Thus the presented parametrisation can serve as a basis for anomaly analysis in geodesy and geophysics.