Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation and in vitro/in vivo evaluation of a clonidine hydrochloride drug–resin suspension as a sustained-release formulation

Abstract Objective The purpose of the present study was to prepare a clonidine hydrochloride (CH) sustained-release suspension. Methods The processes involved in the drug formulation included drug loading, impregnating, and suspension preparation. Clonidine hydrochloride drug–resin complexes (CH-DRC) were prepared using the bath method and the CH-DRC impregnated before the microencapsulation process. Based on the bottom spray fluidized bed coating method, the CH microencapsulated drug–resin complexes (CH-MC) were also prepared using Surelease® (the suspension of ethyl cellulose aqueous dispersion) as the coating material. The effects of coating (process/formulation) on the in vitro release of coating microcapsule were evaluated via single factor investigation and orthogonal design optimization. The CH-MC with optimized formulation was further dispersed in a suitable medium to obtain a sustained-release suspension. Rats were given commercial CH ordinary tablets and the CH sustained-release suspension via intragastric administration. The plasma concentration–time curve and related pharmacokinetic parameters were investigated using the non-compartment model. Results The T max of the CH sustained-release suspension was delayed from 2 h to 5 h compared with the CH ordinary tablets. Similarly, the C max was reduced from 32.138 µg·mL−1 to 18.150 µg·mL−1 with the concentration–time curve being more gentle compared with the commercially CH ordinary tablets. After oral administration, the relative bioavailability of CH sustained-release suspension (AUC0–24 of 137.703 µg·h·mL−1) to its CH ordinary tablets (AUC0–24 of 123.337 µg·h·mL−1) was 111.65%. Conclusions The findings showed that the CH sustained-release suspension for oral administration was successfully formulated.
Functionalized fluorescent oxide nanoparticles: Artificial toxins for sodium channel targeting and imaging at the single-molecule level

Lanthanide ion-doped oxide nanoparticles were functionalized for use as fluorescent biological labels. These nanoparticles are synthesized directly in water, which facilitates their functionalization, and are remarkably photostable without emission intermittency. Nanoparticles functionalized with guanidinium groups act as artificial toxins and specifically target sodium channels. They are individually detectable in live cardiac myocytes, revealing a heterogeneous distribution of sodium channels. Functionalized oxide nanoparticles appear to be a novel tool that is particularly attractive for long-term single-molecule tracking.
Hsa_circ_0038383-mediated competitive endogenous RNA network in recurrent implantation failure

Background: Inadequate endometrial receptivity contributes to recurrent implantation failure (RIF) during IVF–embryo transfer. Though multiple circRNAs have been confirmed differentially expression in RIF, the potential function of novel circRNAs needed to be detected. Results: The top ten DEcircRNAs were selected as initial candidates. A ceRNA network was conducted on the basis of circRNA–miRNA–mRNA potential interaction, consisting of 10 DEcircRNAs, 28 DEmiRNAs and 59 DEmRNAs. Three down-regulation circRNAs with high degree of connectivity were verified by RT-qPCR, and results suggested that only hsa_circ_0038383 was significantly downregulation in RIF compared with control group. Subsequently, three hub genes (HOXA3, HOXA9 and PBX1) were identified as hub genes. Ultimately, a subnetwork was determined based on one DEcircRNA (hsa_circ_0038383), two DEmiRNAs (has-miR-196b-5p and has-miR-424-5p), and three DEmRNAs (HOXA3, HOXA9 and PBX1). Following verification, hsa_circ_0038383/miR-196b-5p/HOXA9 axis may be a key pathway in affecting RIF. Conclusion: In summary, a hsa_circ_0038383-mediated ceRNA network related to RIF was proposed. This network provided new insight into exploring potential biomarkers for diagnosis and clinical treatment of RIF. Methods: We retrieved the expression profiles of RIF from GEO databases (circRNA, microRNA and mRNA) and constructed a competing endogenous RNAs (ceRNA) network based on predicted circRNA–miRNA and miRNA–mRNA pairs. The expression levels of three hub DEcircRNAs identified by cytoscape were validated by RT-qPCR.
High dislocation density of tin induced by electric current

A dislocation density of as high as 1017 /m2 in a tin strip, as revealed by high resolution transmission electron microscope, was induced by current stressing at 6.5 x 103 A/ cm2. The dislocations exist in terms of dislocation line, dislocation loop, and dislocation aggregates. Electron Backscattered Diffraction images reflect that the high dislocation density induced the formation of low deflection angle subgrains, high deflection angle Widmanstatten grains, and recrystallization. The recrystallization gave rise to grain refining.
Ceramic Printing - Comparative Study of the Flexural Strength of 3D Printed and Milled Zirconia.

PURPOSE To determine and compare the mechanical properties of 3D-printed yttriastabilized zirconia to milled isostatic pressed yttria-stabilized zirconia, with the following hypotheses: (1) The flexural strength of 3D-printed yttria-stabilized zirconia is comparable to milled yttria-stabilized isostatic pressed zirconia; and (2) thermocycling and chewing simulation do not affect the flexural strength of 3D-printed yttria-stabilized zirconia. MATERIALS AND METHODS A total of 30 bars of an experimental 3D-printed 3 mol% yttriastabilized zirconia (LithaCon 3Y 230, Lithoz) and 10 bars of milled isostatic pressed zirconia (Prettau Zirconia, Zirkonzahn) were utilized. The printed zirconia bars were divided into three groups (n = 10 bars per group): (1) untreated (control); (2) thermocycled; and (3) tested after chewing simulation. A flexural strength test was performed on all samples using a three-point bend test in an Instron Universal testing machine. One-way analysis of variance on ranks was used to compare milled to printed zirconia. The effects of thermocycling and load cycling on 3D-printed zirconia were also determined. RESULTS The flexural strength values for milled and printed zirconia were 936.3 ± 255.0 MPa and 855.4 ± 112.6 MPa, respectively. There was no statistically significant difference in flexural strength between the milled and printed zirconia (P = .178). No statistically significant differences were observed between the control 3D-printed zirconia group and the thermocycled (888.4 ± 59.3 MPa) or load-cycled printed zirconia (789.6 ± 133.8 MPa; P = .119). CONCLUSION Printed 3 mol% yttria-stabilized zirconia has comparable flexural strength to milled yttria-stabilized isostatic pressed zirconia. The thermocycling and chewing simulation used in this study did not significantly alter the flexural strength of the printed 3 mol% yttria-stabilized zirconia. These results indicate a promising role for 3D printing in the fabrication of zirconia restorations. Additional studies are needed to explore the full potential of this technology.
Beam-Guided TasNet: An Iterative Speech Separation Framework with Multi-Channel Output

Time-domain audio separation network (TasNet) has achieved remarkable performance in blind source separation (BSS). Classic multi-channel speech processing framework employs signal estimation and beamforming. For example, Beam-TasNet links multi-channel convolutional TasNet (MC-Conv-TasNet) with minimum variance distortionless response (MVDR) beamforming, which leverages the strong modeling ability of data-driven network and boosts the performance of beamforming with an accurate estimation of speech statistics. Such integration can be viewed as a directed acyclic graph by accepting multi-channel input and generating multi-source output. In this paper, we design a"multi-channel input, multi-channel multi-source output"(MIMMO) speech separation system entitled"Beam-Guided TasNet", where MC-Conv-TasNet and MVDR can interact and promote each other more compactly under a directed cyclic flow. Specifically, the first stage uses Beam-TasNet to generate estimated single-speaker signals, which favors the separation in the second stage. The proposed framework facilitates iterative signal refinement with the guide of beamforming and seeks to reach the upper bound of the MVDR-based methods. Experimental results on the spatialized WSJ0-2MIX demonstrate that the Beam-Guided TasNet has achieved an SDR of 21.5 dB, exceeding the baseline Beam-TasNet by 4.1 dB under the same model size and narrowing the gap with the oracle signal-based MVDR to 2 dB.
On Analytical Usefulness of the Recovery Method

Abstract The recovery method—applied increasingly frequently to studying the effectiveness of analytical procedures—is subjected to a detailed critical appraisal. Two versions of this method that have practical applications are presented, as are broad interpretation possibilities. Effects that may occur during the analytical procedure have been classified and the significance of these effects for the reliability of results gained by the recovery method has been defined. The similarities and differences between this method and the standard addition method have been indicated. Theoretical deliberations are supported by results of analysis of blood samples for selenium and arsenic content by the atomic fluorescence spectrometry method. It has been shown that the “surrogate” version of the recovery method, although potentially attractive from the analytical point of view, in practice can be very unreliable and the more complex the laboratory procedures for preparing the sample for measurement, the more risky is its application.
“We are already 1-0 behind”: Perceptions of Dutch Muslims on Islamophobia, securitisation, and de-radicalisation

ABSTRACT This article presents the findings of an explanatory study into the perceptions of Dutch Muslims in The Hague concerning pre-emptive counter-extremism and de-radicalisation policies. Based on 15 in-depth interviews with established Muslim community figures and a theoretical survey of 102 respondents from 8 mosques, it was found that pre-emptive interventions were perceived unfavourably due to their inherent misconceptualization of the Muslim lived experience. Respondents perceived wide-ranging negative labelling, viewing policies as not just ineffectual but also detrimental in a climate of persistent Islamophobia. In reality, these Dutch Muslims were faced with tackling the challenges of radicalisation based on their existing levels of social and cultural capital. Securitisation forces some Dutch Muslims into further retreat at a time of existing issues of social exclusion and political polarisation. This research highlights the need for greater sensitivity to Muslim community norms and values in developing policy in this area.
A new genus and species of fish parasitic cymothoid isopod (Crustacea) from Indian waters, with a key to the branchial-attaching cymothoid genera

ABSTRACT Brucethoa bharata gen. et sp. nov. is described from the host fish Glossanodon macrocephalus Bineesh and Endo, 2019 (Argentinidae), at depths of 300–600 metres from the south-west coast of India. This monotypic genus is characterised by a head weakly immersed in pereonite 1, dorsum strongly vaulted, pereonites 6 and 7 with posterolateral margin expanded and coxae not visible in dorsal view, relatively wide pleon, pleonite ventrolateral margins produced with lateral gaps evident, both antennae slender, with antennula slightly longer than antenna, and large pleopod rami that extend laterally well beyond the pleotelson margins. Ovigerous females were found in the branchial cavity of the hosts and have proximally thickened oostegites with the posterior marsupium partly enclosed by two sub-rectangular fleshy lobes. All life stages of the new species are described [including females (ovigerous and non-ovigerous), male, transitional and larvae (premanca and manca)]. The species is currently known only from the type locality and the type host. A revised key to the marine branchial cymothoid genera of the world is provided. Publication LSID: lsid:http://zoobank.org:pub:85E54167-072A-4513-B527-20FFD0F75CCA
Automatically Detecting Image–Text Mismatch on Instagram with Deep Learning

Abstract Visual social media have emerged as an essential brand communication channel for advertisers and brands. The active use of hashtags has enabled advertisers to identify customers interested in their brands and better understand their consumers. However, some users post brand-incongruent content—for example, posts composed of brand-irrelevant images with brand-relevant hashtags. Such visual information mismatch can be problematic because it hinders other consumers’ information search processes and advertisers’ insight generation from consumer-initiated social media data. This study aims to characterize visually mismatched content in brand-related posts on Instagram and builds a visual information mismatch detection model using computer vision. We propose a machine-learning model based on three cues: image, text, and metadata. Our analysis shows the effectiveness of deep learning and the importance of combining text and image features for mismatch detection. We discuss the advantages of machine-learning methods as a novel research tool for advertising research and conclude with implications of our findings.
Inference on P ( Y < X ) Based on Record Values for Generalized Pareto Distribution

In this article, the estimation of R = P ( Y < X ) is considered when X and Y are two independent generalized Pareto distributions. The maximum likelihood estimators and Bayes estimators of R are obtained based on record values. The Asymptotic distributions are also obtained together with the corresponding confidence interval of R . AMS 2000 subject classification: 90B25
Parameter Estimation in Multiple Dynamic Synaptic Coupling Model Using Bayesian Point Process State-Space Modeling Framework

Abstract It is of great interest to characterize the spiking activity of individual neurons in a cell ensemble. Many different mechanisms, such as synaptic coupling and the spiking activity of itself and its neighbors, drive a cell's firing properties. Though this is a widely studied modeling problem, there is still room to develop modeling solutions by simplifications embedded in previous models. The first shortcut is that synaptic coupling mechanisms in previous models do not replicate the complex dynamics of the synaptic response. The second is that the number of synaptic connections in these models is an order of magnitude smaller than in an actual neuron. In this research, we push this barrier by incorporating a more accurate model of the synapse and propose a system identification solution that can scale to a network incorporating hundreds of synaptic connections. Although a neuron has hundreds of synaptic connections, only a subset of these connections significantly contributes to its spiking activity. As a result, we assume the synaptic connections are sparse, and to characterize these dynamics, we propose a Bayesian point-process state-space model that lets us incorporate the sparsity of synaptic connections within the regularization technique into our framework. We develop an extended expectation-maximization. algorithm to estimate the free parameters of the proposed model and demonstrate the application of this methodology to the problem of estimating the parameters of many dynamic synaptic connections. We then go through a simulation example consisting of the dynamic synapses across a range of parameter values and show that the model parameters can be estimated using our method. We also show the application of the proposed algorithm in the intracellular data that contains 96 presynaptic connections and assess the estimation accuracy of our method using a combination of goodness-of-fit measures.
Three Stream Network Model for Lung Cancer Classification in the CT Images

Lung cancer is considered to be one of the deadly diseases that threaten the survival of human beings. It is a challenging task to identify lung cancer in its early stage from the medical images because of the ambiguity in the lung regions. This paper proposes a new architecture to detect lung cancer obtained from the CT images. The proposed architecture has a three-stream network to extract the manual and automated features from the images. Among these three streams, automated feature extraction as well as the classification is done using residual deep neural network and custom deep neural network. Whereas the manual features are the handcrafted features obtained using high and low-frequency sub-bands in the frequency domain that are classified using a Support Vector Machine Classifier. This makes the architecture robust enough to capture all the important features required to classify lung cancer from the input image. Hence, there is no chance of missing feature information. Finally, all the obtained prediction scores are combined by weighted based fusion. The experimental results show 98.2% classification accuracy which is relatively higher in comparison to other existing methods.
Flow-roughness heterogeneity: critical obliquity and salient parameters

Abstract A uniform distribution of roughness elements of height, $h$, enhances turbulent momentum exchanges in wall flows of thickness, $\delta$. For $\delta/h$ above a nominal threshold, this distribution of elements enhances drag, but does not induce structural response to outer-/inertial-layer turbulence. Large-scale spatial variability in element attributes, however, can induce $\delta$-scale response in the instantaneous and Reynolds-averaged flow. For the case of a large-scale heterogeneity aligned orthogonal and parallel to the primary transport direction, the Reynolds-averaged flow responds with formation of an internal boundary layer (IBL) and counter-rotating secondary cells, respectively. For oblique flow-heterogeneity alignments, Anderson (J. Fluid Mech., vol. 886, 2020, p. A15), showed that IBL formation persists for flow-heterogeneity aligned at a series of oblique angles, before abruptly collapsing and transitioning to counter-rotating secondary cells at a critical obliquity. We define flow-roughness obliquity angle with symbol, $\theta$, where $\theta = 0$ and ${\rm \pi}/2$ corresponds with streamwise and spanwise heterogeneity, respectively, while the critical obliquity angle is denoted by $\theta_c$. We have used large-eddy simulation to perform a comprehensive parametric assessment on the effect of obliquity, element height, and spacing between adjacent ‘rows’ of elements, all of which is intended to identify the aforementioned critical obliquity. We once again report the aforementioned IBL persistence. It is shown that this response is a product of successive element sheltering, which can be recorded via the element frontal area index: as obliquity angle increases, there is a critical obliquity at which downflow elements fall in the sheltering zone of upflow elements; we find that $\theta_c = 22 {\rm \pi}/ 56$.
Global warming: Design of a flow‐through shallow lake mesocosm climate experiment

Shallow lakes are likely to be strongly impacted by climate changes and, in particular, by increased temperatures. To enable realistic experimental studies of the effects of higher temperatures on in‐lake processes and dynamics, technologically advanced systems are required. This paper presents design details, operating characteristics, and background information on a currently operating experimental flow‐through mesocosm system that allows investigation of the interactions between simulated climate warming and eutrophication and their impacts on biological structure and ecosystem processes in shallow lakes. We use 24 mesocosms to combine three temperature scenarios (one unheated and two heated relative to the Intergovernmental Panel on Climate Change climate scenario A2 and A2 + 50%, respectively) and two nutrient levels (enriched and nonenriched). Planktivorous fish (male sticklebacks, Gasterosteus aculeatus) are stocked in accordance with the nutrient level. The water residence time is regulated by the semicontinuous addition of water and is approximately 2.5 mo in each mesocosm. For heating, we use electrically powered heating elements. The heating system has performed well over 16 mo of continuous heating, and seasonal and diurnal temperature variations of the unheated reference mesocosms were paralleled well by the heated mesocosms. The performance of the flow‐through system and the heating technique are discussed with special emphasis on strengths, limitations, and potential improvements of the system. To illustrate the performance of the system and its potential, we present data for selected periods on total phosphorus retention in the mesocosms and system primary production and respiration.
Decision Support System Based on Indoor Location for Personnel Management

A wide variety of business areas organize their work based on the location of their employees because only by taking these locations into account, they can schedule activities properly. However, in a large number of cases, the requirement of immediacy, such as the need to help an injured person in a hospital or to dry up water in a busy hallway to prevent people from slipping, is a major constraint. This work is based on a proof of concept in which we used Bluetooth Low Energy devices to track the location of each employee in an indoor environment. Among other factors, the location of each individual is assigned a large percentage of the weight to assign a task. This proposal is intended to cover some scenarios of great interest, guaranteeing the correctness of measurement and the privacy of staff tracking.
Removal of N‐nitrosodimethylamine by ultraviolet treatment and anodizing TiO2 membrane processes

N‐Nitrosodimethylamine (NDMA) is a disinfectant by‐product shown to be carcinogenic, mutagenic, and teratogenic. The objective of this study is to compare NDMA removal efficiencies in water using conventional technologies (microfiltration, nanofiltration, reverse osmosis, and UV treatment) and innovative hybrid technology, which combines UV treatment with anodizing TiO2 membrane (UV/A‐Ti‐M) technology. In the UV/A‐Ti‐M photoreaction, the affecting factors such as UV intensity, the initial concentration of NDMA, and initial pHs were investigated. Even though membrane processes were ineffective in removing NDMA compounds, UV irradiation used in combination with an anodizing TiO2 membrane were achieved to remove NDMA completely from water. When NDMA was decomposed by UV/A‐Ti‐M process, dimethylamine yield increased and methylamine yield decreased with an increase in initial NDMA concentration. The successful removal of NDMA was specific to acidic conditions (pH 4–6). UV/A‐Ti‐M process is useful and powerful tools to remove NDMA in water. © 2011 American Institute of Chemical Engineers Environ Prog, 2011
Hand Gestures Recognition Using Radar Sensors for Human-Computer-Interaction: A Review

Human–Computer Interfaces (HCI) deals with the study of interface between humans and computers. The use of radar and other RF sensors to develop HCI based on Hand Gesture Recognition (HGR) has gained increasing attention over the past decade. Today, devices have built-in radars for recognizing and categorizing hand movements. In this article, we present the first ever review related to HGR using radar sensors. We review the available techniques for multi-domain hand gestures data representation for different signal processing and deep-learning-based HGR algorithms. We classify the radars used for HGR as pulsed and continuous-wave radars, and both the hardware and the algorithmic details of each category is presented in detail. Quantitative and qualitative analysis of ongoing trends related to radar-based HCI, and available radar hardware and algorithms is also presented. At the end, developed devices and applications based on gesture-recognition through radar are discussed. Limitations, future aspects and research directions related to this field are also discussed.