Miracle-dz/UniFAR-FTUs huggingface dataset:
Submerged macrophytes affect the temporal variability of aquatic ecosystems

1. foundation species strongly the structure and functioning of but little the temporal variation timescales of 24 2. Here, we conducted an outdoor experiment in replicated mesocosms (1000 L) where 25 we manipulated the presence and absence of macrophytes to investigate the temporal 26 variability of their ecosystem effects. We measured several parameters (chlorophyll-a, 27 phycocyanin, dissolved organic matter [DOM], and oxygen) with high-resolution 28 sensors (15 min intervals) over several months (94 days from spring to fall), and 29 estimated metabolic rates of each replicate ecosystem in a Bayesian framework. 30 3. Over the entire experiment, macrophytes had a negative effect on phytoplankton 31 biomass, a positive effect on mean DOM concentration, and either a weak or no effect 32 on mean metabolic rates, DOM composition, and conductivity. We also found that 33 macrophytes increased the variance of DOC composition and metabolic rates, and, at 34 some times of the year, increased the variance of phytoplankton biomass and 35 conductivity. The observation that macrophytes decreased the mean but increased the 36 variance of phytoplankton biomass is consistent with a model of competitive 37 interactions between macrophytes and phytoplankton that we implemented here. 38 4. Our high-resolution time series embedded within a manipulative experiment reveal 39 how a foundation species can affect ecosystem properties and processes that have 40 characteristically different timescales of response to environmental variation. 41 Specifically, our results show how macrophytes can affect short-term dynamics of 42 algal biomass, while also affecting the seasonal buildup of DOM and the variance of 43 ecosystem metabolism.
A New Species of Tapeworm in the Genus Stillabothrium (Rhinebothriidea: Escherbothriidae) from a Stingray from Borneo

ABSTRACT: Examination of spiral intestines from Himantura tutul Borsa, Durand, Shen, Arlyza, Solihin, and Berrebi, 2013 (=Himantura uarnak 3 sensu Naylor et al. [2012]), collected from Malaysian Borneo revealed the presence of a new species of tapeworm belonging to the genus Stillabothrium (Rhinebothriidea: Escherbothriidae). Stillabothrium borneoense n. sp. Herzog, Meininger, and Reyda is assigned to the genus based on its possession of a scolex with 4 bothridia divided into a distinct anterior region with facial loculi that are oriented horizontally and a distinct posterior region with facial loculi that are oriented vertically. The new species is distinguished from its congeners by features of the scolex and proglottids, including a vagina that recurves well anterior to the cirrus sac, as well as a unique locular arrangement not previously reported for members of this genus: 4 horizontally oriented loculi in the anterior region of the bothridia and 7 vertically oriented loculi in the posterior region of the bothridia. Stillabothrium borneoense n. sp. expands both known morphological variation and known host associations within the genus.
Poisoning attack of the training dataset for on-line signature authentication using the perceptron

The study of the dependences of the effectiveness of a poisoning attack for the task of on-line signature authentication using a perceptron to make a decision. The dependences on the structure of the neural network, the volume of poisoning sets and the noise of the training sample were studied. Conclusions are drawn on the lack of the ability to detect such attacks by changing the overall accuracy of the system.
Supermassive Black Holes with High Accretion Rates in Active Galactic Nuclei. XII. Reverberation Mapping Results for 15 PG Quasars from a Long-duration High-cadence Campaign

In this work, we present the first results of the long-term high-cadence spectroscopic monitoring of 15 PG quasars with relatively strong Fe ii emission, as a part of a broader reverberation mapping campaign performed using the Calar Alto Observatory’s 2.2 m telescope. The V-band, 5100 Å continuum, and Hβ broad emission line light curves are measured for a set of quasars for periods ranging from dozens to more than a hundred epochs between 2017 May and 2020 July. Accurate time lags between the variations of the Hβ broad-line fluxes and the optical continuum strength are obtained for all 15 quasars, ranging from 17.0−3.2+2.5 to 95.9−23.9+7.1 days in the rest frame. The virial masses of the central supermassive black holes are derived for all 15 quasars, ranging between 0.50−0.19+0.18 and 19.17−2.73+2.98 in units of 107 M ⊙. For 11 of the objects in our sample, this is the first reverberation analysis to be published. Of the rest, two objects have been the subject of previous reverberation studies, but we determine time lags for these that are only half as long as those found in the earlier investigations, which had only been able to sample much more sparsely. The remaining two objects have previously been monitored with high sampling rates. Our results here are consistent with the earlier findings, in the sense that the time lag and the line width vary inversely, consistent with virialization.
Improving Whole-Cell Biocatalysis by Addition of Deep Eutectic Solvents and Natural Deep Eutectic Solvents

Being considered greener alternatives to ionic liquids (IL), deep eutectic solvents (DES) and natural deep eutectic solvents (NADES) have currently attracted broad interests from academics and industry. In this study, the transformation of isoeugenol to vanillin catalyzed by Lysinibacillus fusiformis CGMCC1347 cells was taken as the model reaction to examine the impacts of 24 DESs and 21 NADESs as cosolvents on whole-cell biocatalysis. Both types of cosolvents showed the ability of improving the production yields up to 142% and 132% of the ones obtained in (NA)DES-free aqueous systems, respectively. The data obtained by confocal laser scanning microscopy and flow cytometry tests and measurements of OD260 and OD280 agreed well with the bioconversion data, suggesting that addition of these cosolvents may be beneficial to whole-cell biocatalysis in enhancing the cellular membrane permeability. Interaction of DES with bacterial cell wall was discussed. The cells immobilized in PVA-alginate beads granted an au.
The Husband: Navigating the Relational Challenge Of Her Institutionalization Or His Widowerhood

Marital status is central to one’s identity. Using interview data from US husband caregivers and British widowers, we explore how men’s relational identity as husband is maintained despite challenges as, and after, marriage ends. These data, analyzed using the constant comparative method associated with constructionist grounded theory, corroborate that the work of being married is key to identity maintenance for husbands and that the married relationship and its associated responsibilities affirm a sense of self as a man. Marriage shelters men, providing a secure place for that self-perception as a man. But a wife’s institutionalization in long-term care or widowerhood threatens the ontological security offered through marriage and prompts identity work. We extend the literature in finding that (former) husbands attempt to retain their long-term relational identity and thus remain sheltered by marriage. They reconstruct masculinity-affirming identities through activities that help them harbor their self-presentation as a (former) husband.
Yoga Asana Identification: A Deep Learning Approach

Yoga is a healthy practice that originated from India, to rejuvenate a man in his physical, mental, and spiritual wellness. Moving with the brisk technology advancements, there is a vast opportunity for computational probing in all social domains. But still, the utilization of artificial intelligence and machine learning techniques for applying to an interdisciplinary domain like yoga is quite challenging. In this work, a system that recognizes a yoga posture from an image or a frame of a video has been developed with the help of deep learning techniques like convolutional neural networks (CNN) and transfer learning. We have considered images of 10 different asanas for training the model as well as evaluating the prediction accuracy. The prediction model backed with transfer learning shows promising results with 85% prediction accuracy and this system can be considered as an initial step to build an automated yoga image and video analysis tool.
Sodium salicylate reduced mRNA abundance of hypoxia-associated genes in MAC-T cells

Graphical Abstract Summary: It is likely that transient hypoxia occurs with rapid development of the mammary gland during lactogenesis. Overlapping transcriptional responses to inflammatory stimuli and hypoxia point to potential interactions in regulation of tissue development. In the MAC-T mammary epithelial cell line, hypoxia induced expression of glucose transporter 1 (GLUT1), whereas the anti-inflammatory drug sodium salicylate decreased mRNA abundance of GLUT1 and heterogeneous nuclear ribonucleoprotein D and tended to suppress expression of the paracrine vascular growth factor vascular endothelial growth factor A. Although interactions of hypoxia and salicylate were only detected for GLUT1 abundance, salicylate treatment generally opposed previously reported transcriptional responses to hypoxia.
Fault diagnosis method of rare earth extraction production line based on wavelet packet and alexnet transfer learning

In rare earth production, improving the fault detection of extraction equipment has a key impact on improving extraction efficiency and product quality. The traditional method is based on the observation of the liquid level, the efficiency and accuracy can’t be guaranteed. In this paper, a fault diagnosis and recognition method for rare earth extraction production line based on wavelet packet and alexnet transfer learning is proposed. Taking six fault states of rare earth extraction production line as the research object, the fault signal is extracted by wavelet packet decomposition, and the corresponding target data set of time-frequency diagram is generated. Then, the pre trained alexnet model is trained and fine tuned on the generated target data set, and finally applied to fault diagnosis of rare earth extraction production line. The results show that the proposed method is more accurate than the traditional convolution neural network, which verifies the effectiveness of the method.
Femtosecond laser welding of silica glass fiber for robust Bragg grating sensing in high temperature environment

Femtosecond laser welding was extended to optical silica fiber (SMF-28) by focusing through fused silica substrates and ferrules to form all-glass weld seams. Laser radiation was focused into the fiber cladding to create a welding zone, which drove molten glass to fill as much as a 3 𝜇𝑚 gap around a contact line to form a crack free pseudo-continuous welding seams along the contact line. The strong weld seams up to 30 𝜇𝑚 wide were generated in fiber-to-plate and fiber-to-ferrule geometries without inducing photochemical or thermal degradation of a fiber Bragg grating (FBG) positioned only 62.5 𝜇m from the weld zone. Welding was optimized by real-time monitoring of the FBG thermo-optical shift during laser scanning. Four-point bending tests confirmed a high mechanical strength while thermal annealing showed stable mechanical and FBG responses up to 1000 ˚C. Femtosecond laser writing and welding thus demonstrated a flexible means for photonics fabrication and packaging of FBGs, enabling reliable, high frequency vibration sensing suited for high temperature and strain environments.
Modeling and experimental verification of the impact of noise sources on projection accuracy of MEMS linear micromirrors for raster scanning applications

The architecture used for driving linear micromirrors in raster scanning systems is typically composed of digital circuits, responsible for generating a sawtooth-like reference signal synchronized to the fast axis, and analog circuits responsible of driving the device. Bridging the two domains is the D/A converter, typically clocked in the MHz range, whose noise sources and distortion affect the accuracy of the scan line. With typical refresh rates in the order of 60 Hz, simulating transistor-level implementations requires up to days for a few operating cycles (i.e. 1.7 cycles/day). This drives the need for accurate models of the dominant noise sources and their impact on scan accuracy, able to achieve verification times compatible with typical design flow timelines. The architecture of this work is composed of a sigma-delta based current-steering D/A converter, which is modelled analytically and behaviorally with its white and flicker noise sources and non-idealities. Each current generator is modelled independently to capture time-variant effects. The developed model can accurately predict noise both from Cadence simulations and experimental measurements, while also reducing simulation times by three orders of magnitude (i.e. 5.7 cycles/minute). The model thus allows to optimize the design and quickly verify the possibility to achieve a tilt-angle rms noise within 1 m◦ in open-loop driving conditions. Experimental results also show a significant distortion, which is not predicted by the model: as hypotheses on its root causes are formulated, the model will enable their investigation within reasonable times.
A Robust Deadbeat Predictive Controller With Delay Compensation Based on Composite Sliding-Mode Observer for PMSMs

This article proposes an improved deadbeat predictive controller for permanent-magnet synchronous motor drive systems. It can eliminate the influence of the parameter mismatch of inductance, resistance, and flux linkage. First, the performance of the conventional predictive current method is investigated to analyze sensitivities of the electric parameters. Then, a composite sliding-mode disturbance observer (SMDO) based on the stator current and lumped disturbance is proposed, which can simultaneously estimate the future current value and lumped disturbance caused by the parameter mismatch of inductance, resistance, and flux linkage. Based on the discrete-time SMDO, currents are estimated and used to replace the sampled values to compensate one-step delay caused by the calculation and sampling delay. Both simulation and experimental performances of the proposed method have been validated and compared with the conventional control methods under different conditions. The comparison results show the superiority of the proposed predictive current control method based on the composite SMDO.
Classification of Glaucoma Optical Coherence Tomography (OCT) Images Based on Blood Vessel Identification Using CNN and Firefly Optimization

Received: 17 June 2020 Accepted: 2 January 2021 Glaucoma is a chronic ocular neurodegenerative condition characterised by optic neuropathy and visual disturbance, corresponding to optic disc cupping and degeneration of optic nerve fibres. Globally 76 million people are suffered from glaucoma, it is an aggregate name of a gathering of eye conditions which can cause vision loss and in the end bring about visual deficiency by dynamic basic and useful harm to the optic nerve. It is one of the main reasons for visual deficiency. Early detection of this condition can reduce the progression of the disease and saves many users throughout the world. The detection and identification of glaucoma in an image are important for controlling the loss of the vision. Even there are numerous models for classification of glaucoma disease, the effected rate and prediction rate is less. But accurate identification is a foremost important thing. In order to train CNN, data augmentation and dropout were performed. A classifier was trained to identify the disc fundus images of healthy and glaucomatous eyes using feature vector representation of each input image to integrate the results from each CNN model, removing the second completely linked layer. In this manuscript convolutional neural network (CNN) is proposed with an optimization mechanism for classification of glaucoma OCT images using CNN based firefly optimization model. The proposed firefly based CNN model performs better when compared to the state of art mechanisms.
Whole tissue homogenization preferable to mucosal scraping in determining the temporal profile of segmented filamentous bacteria in the ileum of weanling rats

Segmented filamentous bacteria (SFB) are thought to play a role in small intestine immunological maturation. Studies in weanling mice have shown a positive correlation between ileal SFB abundance and plasma and faecal interleukin 17 (IL-17) and immunoglobulin A (IgA) concentrations. Although the first observation of SFB presence was reported in rats, most studies use mice. The size of the mouse ileum is a limitation whereas the rat could be a suitable alternative for sufficient samples. Changes in SFB abundance over time in rats were hypothesized to follow the pattern reported in mice and infants. We characterized the profile of SFB colonization in the ileum tissue and contents and its correlation with two immune markers of gastrointestinal tract (GIT) maturation. We also compared two published ileum collection techniques to determine which yields data on SFB abundance with least variability. Whole ileal tissue and ileal mucosal scrapings were collected from 20- to 32-day-old Sprague-Dawley rats. SFB abundance was quantified from proximal, middle and distal ileal tissues, contents and faeces by quantitative PCR using SFB-specific primers. Antibody-specific ELISAs were used to determine IL-17 and IgA concentrations. Significant differences in SFB abundance were observed from whole and scraped tissues peaking at day 22. Variability in whole ileum data was less, favouring it as a better collection technique. A similar pattern of SFB abundance was observed in ileum contents and faeces peaking at day 24, suggesting faeces can be a proxy for ileal SFB abundance. SFB abundance at day 26 was higher in females than males across all samples. There were significant differences in IgA concentration between days 20, 30 and 32 and none in IL-17 concentration, which was different from reports in mice and infants.
Default Risk of Listed Companies in the Context of the Threat to Commodity Markets in the Times of COVID-19 Pandemic

: Purpose: The purpose of this study was to identify the threat of default risk among commodity-related companies in European equity markets. Design/Methodology/Approach: Determination of the default risk of companies listed on several stock exchanges followed the Merton model by comparing the probability of bankruptcy in the time intervals from 1 January 2019 to 30 June 2019, and from 1 January 2020 to 30 June 2020. The calculations were based on data from the Wall Street Journal database. The companies selected for the study represent the main indexes of five European stock exchanges. In total, the analysis covers 40 commodity-related companies and 20 companies from the control groups. Findings: It was observed that commodity-related companies stood out against the control group in terms of default risk in the times of Covid-19 pandemic. The growing risk of default among stock market companies from significant European stock exchanges is a threat which if unrecognized - may lead to a new financial crisis that can undermine the foundations of European economy. Practical Implications: The research results can be used by financial institutions in the process of creating a more customized approach to the modeling of credit risk of commodity-related companies. This will enable rationalization of risk management costs. Originality/Value: This study lies in the research area orientated towards exploration of relations between types of risks, which is an original aspect of this paper. More broadly, the research seeks to build risk assessment models that will be more adaptable to actual market situations in the times of Covid-19 pandemic.
A Paleo Perspective of Alabama and Florida (USA) Interstate Streamflow

Seasonal reconstructions of streamflow are valuable because they provide water planners, policy makers, and stakeholders with information on the range and variability of water resources before the observational period. In this study, we used streamflow data from five gages near the Alabama-Florida border and centuries-long tree-ring chronologies to create and analyze seasonal flow reconstructions. Prescreening methods included correlation and temporal stability analysis of predictors to ensure practical and reliable reconstructions. Seasonal correlation analysis revealed that several regional tree-ring chronologies were significantly correlated (p ≤ 0.05) with March–October streamflow, and stepwise linear regression was used to create the reconstructions. Reconstructions spanned 1203–1985, 1652–1983, 1725–1993, 1867–2011, and 1238–1985 for the Choctawhatchee, Conecuh, Escambia, Perdido, and Pascagoula Rivers, respectively, all of which were statistically skillful (R2 ≥ 0.50). The reconstructions were statistically validated using the following parameters: R2 predicted validation, the sign test, the variance inflation factor (VIF), and the Durbin–Watson (D–W) statistic. The long-term streamflow variability was analyzed for the Choctawhatchee, Conecuh, Escambia, and Perdido Rivers, and the recent (2000s) drought was identified as being the most severe in the instrumental record. The 2000s drought was also identified as being one of the most severe droughts throughout the entire reconstructed paleo-record developed for all five rivers. This information is vital for the consideration of present and future conditions within the system.
DESIGN EXPERT SUPPORTED FORMULATION DEVELOPMENT, MATHEMATICAL OPTIMIZATION AND PREDICTABILITY STUDY OF FLOATING TABLETS OF BISOPROLOL FUMARATE

Objective: Focus of the study was to formulate Design expert Software assisted floating tablet of Bisoprolol Fumarate. Bisoprolol Fumarate is a Beta adrenergic blocking agent, used to treat cardiac diseases favorable characters to be formulated as sustained release Gastro retentive floating tablets. Methods: Floating Tablets of Bisoprolol Fumarate were prepared by using polymers such as Polyox N 12 K and Carbapol 940 P. Formulations were prepared by using direct compression method and evaluated for various parameters like Hradness, thickness, weight variations, Floating lag time Total floating time,% drug release and Stability Study etc. Results: FTIR spectroscopic study indicates no drug-excipients interaction in the prepared formulations. Hardness or crushing strength of the tablets of all the formulation was found between 5.8 and 6.5 kg/cm2. Floating lag time of all batches is in range of 1.18±2.0 to 2.43±1.6 (minutes). All other parameters of all batches are within an acceptable range. The polymer Carbopol 940 P had the significant negative effect of on the floating lag times. The In vitro dissolution profiles of optimized A3 Floating formulation of Bisoprolol Fumarate were found to sustain drug release 99.25 % up to 12 h with floating lag time of 1.45 min; Designed formulation was stable after Stability study. Optimization study was carried out by using 32 factorial designs to fabricate formulations. Conclusion: It can be conclude that reproducible results of various parameters in this developed formulation can easily scale up. Furthermore designed formulation will be very effective for controlling blood pressure.