Miracle-dz/UniFAR-FTUs huggingface dataset:
Fluorescent-Tagged Antiscalants—The New Materials for Scale Inhibition Mechanism Studies, Antiscalant Traceability and Antiscaling Efficacy Optimization during CaCO3 and CaSO4·2H2O Scale Formation

Equipment scaling leads to reduced production efficiency in a wide range of industrial applications worldwide. Various antiscaling agents are currently commonly used to mitigate this problem. However, irrespective of their long and successful application in water treatment technologies, little is known about the mechanisms of scale inhibition, particularly the localization of scale inhibitors on scale deposits. The lack of such knowledge is a limiting factor in the development of applications for antiscalants. Meanwhile, fluorescent fragments integrated into scale inhibitor molecules have provided a successful solution to the problem. The focus of this study is, therefore, on the synthesis and investigation of a novel fluorescent antiscalant: (2-(6-morpholino-1,3-dioxo-1H-benzo[de]isoquinolin-2(3H)yl)ethylazanediyl)bis(methylenephosphonic acid) (ADMP-F) which is an analog of the commercial antiscalant: aminotris(methylenephosphonic acid) (ATMP). ADMP-F has been found to effectively control the precipitation of CaCO3 and CaSO4 in solution and is a promising tracer for organophosphonate scale inhibitors. ADMP-F was compared with two other fluorescent antiscalants—polyacrylate (PAA-F1) and bisphosphonate (HEDP-F)—and was found to be highly effective: PAA-F1 > ADMP-F >> HEDP-F (CaCO3) and PAA-F1 > ADMP-F > HEDP-F (CaSO4·2H2O). The visualization of the antiscalants on the deposits provides unique information on their location and reveals differences in the “antiscalant-deposit” interactions for scale inhibitors of different natures. For these reasons, a number of important refinements to the mechanisms of scale inhibition are proposed.
A model-based regularized inverse method for ultrasonic B-scan image reconstruction

Ultrasonic B-scan imaging is affected by the acoustic diffraction and electrical effects in nondestructive testing (NDT), resulting in insufficient lateral and temporal resolution for defect characterization. The minimum mean squared error (MMSE) method can improve the resolution by inversing a linear imaging model, which takes the acoustic diffraction and electrical effects into account, and achieve higher resolution than the synthetic aperture focusing technique (SAFT). However, its computation efficiency and resolution improvement are unsatisfactory due to the hypothetical Gaussian distribution of defects. To overcome these problems, a model-based regularized inverse method for ultrasonic B-scan image reconstruction is proposed. Benefitting from the sparse distribution of defects in NDT applications, the proposed method formulates an inverse objective function composed of ℓ1 ? >-norm as well as ℓ2 ? >-norm, and the sparse reconstruction by a separable approximation (SpaRSA) algorithm is adopted to obtain the optimal solution. The performance of the proposed method is evaluated by B-scan imaging of two 0.3 mm steel wires conducted both in simulation and experiment. The results verify that the proposed method improves the lateral and temporal resolution simultaneously with high computation efficiency.
Linear and Quasilinear Parabolic Problems: Volume I: Abstract Linear Theory

Parabolic Evolution Equations and their Applications This book details the mathematical developments in total variation based image restauration. From the reviews: "This book is devoted to PDE's of elliptic and parabolic type associated to functionals having a linear growth in the gradient, with a special emphasis on the applications related to image restoration and nonlinear filters.The book is written with great care, paying also a lot of attention to the bibliographical and historical notes. "-ZENTRALBLATT MATH Critical Parabolic-Type Problems This book is devoted to the qualitative study of solutions of superlinear elliptic and parabolic partial differential equations and systems. This class of problems contains, in particular, a number of reaction-diffusion systems which arise in various mathematical models, especially in chemistry, physics and biology. The first two chapters introduce to the field and enable the reader to get acquainted with the main ideas by studying simple model problems, respectively of elliptic and parabolic type. The subsequent three chapters are devoted to problems with more complex structure; namely, elliptic and parabolic systems, equations with gradient depending nonlinearities, and nonlocal equations. They include many developments which reflect several aspects of current research. Although the techniques introduced in the first two chapters provide efficient tools to attack some aspects of these problems, they often display new phenomena and specifically different behaviors, whose study requires new ideas. Many open problems are mentioned and commented. The book is self-contained and up-to-date, it has a high didactic quality. It is devoted to problems that are intensively studied but have not been treated so far in depth in the book literature. The intended audience includes graduate and postgraduate students and researchers working in the field of partial differential equations and applied mathematics. The first edition of this book has become one of the standard references in the field. This second edition provides a revised text and contains a number of updates reflecting significant recent advances that have appeared in this growing field since the first edition. R-Boundedness, Fourier Multipliers and Problems of Elliptic and Parabolic Type ? MATRIX is Australia’s international and residential mathematical research institute. It facilitates new collaborations and mathematical advances through intensive residential research programs, each 1-4 weeks in duration. This book is a scientific record of the eight programs held at MATRIX in its second year, 2017: Hypergeometric Motives and Calabi–Yau Differential Equations Computational Inverse Problems Integrability in Low-Dimensional Quantum Systems Elliptic
In silico study on inclusion complex of sorafenib and regorafenib with modified cyclodextrins

Sorafenib (SOR) and regorafenib (RG) are oral multikinase inhibitors that effectively hamper the growth and spread of cancer cells by targeting angiogenesis and proliferation. However, both of the drugs have low water solubility. To address this issue, cyclodextrins (CDs), widely used to enhance the solubility and stability of lipophilic drugs by encapsulating them within their molecular structure, were considered in this study. We focused on ? -cyclodextrin (? CD) and its derivatives, including hydroxypropyl-? -cyclodextrin (HP? CD), dimethyl-? -cyclodextrin (DM? CD), sulfobutylether-? -cyclodextrin (SBE? CD), and compared them with ? -cyclodextrin (? CD) for generating inclusion complexes with SOR and RG. The 200-ns molecular dynamics simulations revealed that both drugs could form inclusion complexes with all CDs in two possible orientations: pyridine group insertion (P-form) and chlorobenzotrifluoride group insertion (C-form), primarily driven by van der Waals interactions. Among the four ? CD derivatives studied, SOR and RG exhibited the highest number of atom contacts with SBE? CD and demonstrated the lowest solvent accessibility within the hydrophobic cavity. These findings correlated with the highest binding affinity determined by SIE, MM/GBSA, and MM/PBSA methods. Experimental results further supported our computational predictions, as SOR/SBE? CD exhibited a stability constant of 940 M-1 while the Kc value of RG/SBE? CD was 640 M-1 at 25 ? C, surpassing ? CD's stability constant of 210 M-1 and 240 M-1 respectively. �Taken together, our results suggest that modified CDs, particularly SBE? CD, hold promising potential as an efficient molecular encapsulating agent for both SOR and RG, offering improved solubility and stability for these lipophilic drugs. While trying to analyze ? CD with different methyl substitutions it was observed that 13-M? CD exhibits a distinct conformation characterized by a predominantly circular shape, low likelihood of flipping, and cavity enclosure and could be considered a more suitable host for encapsulating low-water soluble compounds.
Nuevo cangrejo violinista (género Uca, Ocypodidae) en el Plio-Pleistoceno del litoral pacífico de Honduras

Resumen. Se describen los primeros cangrejos fosiles encontrados en Honduras; se trata de representantes del genero Uca Leach, 1814 (Brachyura, Ocypodidae) procedentes del Plio-Pleistoceno del golfo de Fonseca en la costa pacifica de Honduras en la localidad de Cedeno, Departamento de Choluteca. Se conocen cerca de cien especies actuales de Uca, si bien el registro fosil de este genero es muy incompleto ya que hasta la fecha tan solo se conocian cinco fosiles descritos con informacion diagnostica muy escasa. En este trabajo se describe Uca (Uca) marinae sp. nov. basada en un total de catorce individuos. Se trata de una especie de quela mayor plana emparentada con las actuales Ucaornata (Smith, 1870), U. maraconai (Latreille, 1802-1803) y U. insignis (Milne Edwards, 1852). El analisis filogenetico confirma esas relaciones y establece la posicion filogenetica de la nueva especie y de U. antiqua (Mioceno, norte de Brasil) como el plesion mas distal y basal respectivamente de U. ornata. El analisis filogenetico tiene implicaciones biogeograficas, etologicas y de ocupacion de biotopos pues muestra que los ancestros del grupo de especies Uca ornata, U. maraconai y U. insignis y las extinguidas U. marinae y U. antiqua debieron tener una distribucion panamericana en un momento anterior al Mioceno inferior y que debio haber un evento de vicarianza reciente, seguramente tras el cierre del istmo de Panama durante el Plio-Pleistoceno, entre U. insignis y U. maracoani y otro de edad indeterminada en el grupo basal de U. ornata. Abstract. A NEW FIDDLER CRAB (GENUS UCA, OCYPODIDAE,) FROM THE PLIO-PLEISTOCENE FROM THE PACIFIC COAST OF HONDURAS.The first fossils crabs from Honduras assigned to Uca Leach, 1814 (Brachyura, Ocypodidae) taken at Cedeno (Choluteca region) on the Pacific slope around the Gulf of Fonseca are described. Although Uca are common estuarine crustaceans with ~100 extant species across the globe, their fossil record is extremely scarce with only five described taxa. Moreover, these descriptions are based on very fragmentary fossils with poor diagnostic features. On the basis of fourteen silicified specimens, Uca (Uca) marinae sp. nov. is described here. With a large, flattened major cheliped, the new species is most likely related to the extant species Uca ornata, U. maracoani and U. insignis. Farther analysis indicates that the phylogenetic positions of both the new species as well as U. antiqua (Miocene, Northern Brazil) are relatively close to U. ornata. Biogeographic, ethologic, and ecologic interpretations imply that the last common ancestor for the extant forms, Uca ornata, U. maraconai and U. insignis, and the extinct congeners, U. marinae and U. antique, had a Pan-American distribution prior to the early Miocene and experienced at least two vicariance events. The most recent probably occurred after the closing of the trans-Panamanian seaway during the Plio-Pleistocene separating U. insignis and U. maracoani. During an earlier era, another event created a lineage stemming from an ancestor of U. ornata.
Predicting Bulk Soil Electrical Conductivity versus Saturation Paste Extract Electrical Conductivity Calibrations from Soil Properties1

Soil electrical conductivity was calibrated with salinity for 12 soil types, and the calibrations were related to soil properties. The calibration slope was found to be highly correlated with water-holding capacity and saturation percentage, whereas the intercept was highly correlated with clay content. These findings permit the prediction of calibrations for salinity diagnosis applications where direct calibrations are unavailable or unwarranted. Additional Index Words: salinity, electrical resistivity. Rhoades, J. D. 1981. Predicting bulk soil electrical conductivity vs. saturation paste extract electrical conductivity calibrations from calibrations from soil properties. Soil Sci. Soc. Am. J. 45:42-44. 1 Contribution from the U.S. Salinity Laboratory, USDA, Riverside, CA 92501. This research was supported by a grant from the United States-Israel (Binational) Agricultural Research and Development Fund (BARD). Received 20 June 1980. Approved 26 Sept. 1980. 2 Supervisory Soil Scientist. S SALINITY is conventionally determined by measuring (generally in the laboratory) the electrical conductivity of the extract (ECe) of a saturated soil paste. The paste is made using a sieved soil sample taken from the field. For a given soil type, ECe and bulk soil electrical conductivity (ECa) are highly correlated, and the latter can be directly measured in the field (without need for soil sampling and laboratory analysis) using four-electrode and electromagnetic induction methods (Rhoades and Ingvalson, 1971; Rhoades, 1976; Rhoades and van Schilfgaarde, 1976; Sriyotai and Gilmour, 1976; Halvorson et al., 1977; van Hoorn, 1980; Rhoades and Corwin, 1980). Until now, ECe vs. ECa calibrations for soils have been empirically determined using one of three techniques as described in Rhoades and Ingvalson (1971), Rhoades (1976), Rhoades et al. (1977), and Rhoades and Halvorson (1977). Published January, 1981
Observations of Runoff and Sediment and Dissolved Loads from the Greenland Ice Sheet at Kangerlussuaq, West Greenland, 2007 to 2010

Observations from 2007 to 2010 of runoff, sediment and solute delivery from a segment of the Greenland Ice Sheet (GrIS) and the proglacial landscape draining into the fjord at Kangerlussuaq are presented. The observations include at least three jokulhlaups and extreme recordings from 2010. The average runoff from the 9743 km2 catchment was 377 mm (min. 267 mm and max. 565 mm) and the sediment delivery was 744 t km– 2 y–1 with (min. 493 and max. 1221t km– 2 y–1). Solute transport was only 0.4 % of the total load (sediment loaddissolved load). These new values are a factor two higher than values previously published for 2007 and 2008. The average effective erosion from the catchment was 0.28 mm (min. 0.18 and max. 0.45 mm). The erosion is larger than indicated from most other locations along the GrIS, but in the same order of magnitude as erosion in other glaciated areas at the same latitude, e.g. Norway. The sandur in the proglacial area acts as a sediment sink for a lot of the sediments from the GrIS.
An Adaptive Duplex Switching Scheme That Exploits Interference Statistics for Hybrid-Duplex Cellular Networks

The full duplex (FD) technique allows transmission and reception in the same frequency band and at the same time. It can potentially improve the spectral efficiency. However, in a cellular network, FD communication results in increased interference which may diminish the gain. It has been shown that hybrid designs with proper selection between the FD and the half duplex (HD) modes can reach a performance better than that of the pure FD and pure HD systems. The optimal mode selection requires accurate channel information within a cell and between cells which incur a significant amount of signaling overhead and the computation is highly complex. In this paper, we propose a duplex switching method based on only the instantaneous channel information within a cell and the statistics of the other-cell interference to avoid extensive information exchange and complex computation. The other-cell interference depends on the portions of the links in the other cells adopting the FD or HD mode, which again depend on the other-cell interference these links see. Due to this recursion or interaction between cells, the interference statistics are difficult to derive. Using stochastic geometry, we propose an approximation approach to obtain the probability of other cells adopting the FD mode, and use this probability to approximate the other-cell interference which is then exploited for duplex mode switching in a cell. Simulation results show that the proposed design outperforms the pure FD, pure HD, and an existing duplex switching system. Surprisingly, it also outperforms a system with mode selection based on the actual instantaneous other-cell interference.
Prompt Learning for Low-Resource Multi-Domain Fake News Detection

The spread of fake news has caused severe damage to people's lives and society nowadays. Social media is inundated with fake news from multiple domains. Previously, the methods used to detect fake news have tended to be limited to single domains and have performed inadequacy in other or multiple domains. Therefore, the detection of multi-domain fake news has garnered significant interest. However, multi-domain fake news detection approaches rely more on sufficient training samples. In the real world, the low-resource problem has become a significant challenge that restricts the detection of fake news in multi-domain. In that case, prompt learning approaches have significant advantages in low-resource scenarios, but the existing fake news detection approaches based on prompt learning differ greatly in performance across different domains. In addition, the verbalizer in the prompt learning framework is the key module for mapping label words to classification labels, and the performance of existing methods is also limited by simply designed verbalizer modules, which makes the label words coverage small and the label words prediction inaccurate, especially in zero-shot scenarios. In this paper, we propose prompt learning for low-resource multi-domain fake news detection(PLDFEND). We incorporate domain-aware and relational learning into the prompt learning framework to improve the prompting effect. In addition, the verbalizer is optimized to adapt to different scenarios and map the label words to classification labels, thus achieving multi-domain news classification detection. After conducting comprehensive experiments in settings with limited resources and abundant data, we have confirmed the effectiveness of PLDFEND.
Gap‐Filled Multivariate Observations of Global Land–Climate Interactions

The volume of Earth system observations has grown massively in recent decades. However, multivariate or multisource analyses at the interface of atmosphere and land are still hampered by the sparsity of ground measurements and the abundance of missing values in satellite observations. This can hinder robust multivariate analysis and introduce biases in trends. Nevertheless, gap‐filling is often done univariately, which can obscure physical dependencies. Here, we apply the new multivariate gap‐filling framework CLIMate data gapFILL (CLIMFILL). CLIMFILL combines state‐of‐the‐art spatial interpolation with an iterative approach accounting for dependencies across multiple incomplete variables. CLIMFILL is applied to a set of remotely sensed and in situ observations over land that are central to observing land–atmosphere interactions and extreme events. The resulting gridded monthly time series covers 1995–2020 globally with gap‐free maps of nine variables: surface layer soil moisture from European Space Agency (ESA)‐Climate Change Initiative (CCI), land surface temperature and diurnal temperature range from Moderate‐resolution Imaging Spectroradiometer, precipitation from GPM, terrestrial water storage from GRACE, ESA‐CCI burned area, and snow cover fraction as well as 2‐m temperature and precipitation from CRU. Time series of anomalies are reconstructed better compared to state‐of‐the‐art interpolation. The gap‐filled data set shows high correlations with ERA5‐Land, and soil moisture estimates compare favorably to in situ observations from the International Soil Moisture Network. Soil moisture drying trends in ESA‐CCI only agree with the reanalysis product ERA5‐Land trends after gap‐filling. We furthermore showcase that key features of droughts and heatwaves in major fire seasons are well represented. The data set can serve as a step toward the fusion of multivariate multisource observations.
A CNN Hyperparameters Optimization Based on Particle Swarm Optimization for Mammography Breast Cancer Classification

Breast cancer is considered one of the most-common types of cancers among females in the world, with a high mortality rate. Medical imaging is still one of the most-reliable tools to detect breast cancer. Unfortunately, manual image detection takes much time. This paper proposes a new deep learning method based on Convolutional Neural Networks (CNNs). Convolutional Neural Networks are widely used for image classification. However, the determination process for accurate hyperparameters and architectures is still a challenging task. In this work, a highly accurate CNN model to detect breast cancer by mammography was developed. The proposed method is based on the Particle Swarm Optimization (PSO) algorithm in order to look for suitable hyperparameters and the architecture for the CNN model. The CNN model using PSO achieved success rates of 98.23% and 97.98% on the DDSM and MIAS datasets, respectively. The experimental results proved that the proposed CNN model gave the best accuracy values in comparison with other studies in the field. As a result, CNN models for mammography classification can now be created automatically. The proposed method can be considered as a powerful technique for breast cancer prediction.
Chickpea Sprouts as a Potential Dietary Support in Different Prostate Disorders—A Preliminary In Vitro Study

Background: Prostate cancer (PC) and benign prostatic hyperplasia (BPH) are common health problems in the aging male population. Due to the unexplored and unconfirmed impact of food containing isoflavones, like sprouts, on the development of the management of BPH and prostate cancer, we decided to extend the knowledge in this area. Results: We have demonstrated for the first time that chickpea sprouts may play an important role in the chemoprevention of prostate disorders. However, attention should be paid to the isoflavone content in the sprouts, as in our study, chickpea sprouts with a moderate concentration of the compounds, harvested in natural light conditions (CA10L) and blue LED light (CA7B), showed the best scores in terms of their potential towards prostate disorders. Methods: Chickpea seeds were grown in LED chambers. The methanol extracts from sprouts were quantitatively defined using the HPLC system. Experiments such as the determination of PSA, 5-α-reductase, and dihydrotestosterone were performed on PNT2 and LNCaP cells. For anti-inflammatory assays (determination of NO, IL-6, and TNF-alpha release), murine RAW264.7 macrophages were used. Conclusions: The role of legume products as a diet element should be deeply evaluated for the development of future dietary recommendations for prostate cancer and BPH prevention.