Predicting Sentence-Level Factuality of News and Bias of Media Outlets

Predicting the factuality of news reporting and bias of media outlets is surely relevant for automated news credibility and fact-checking. While prior work has focused on the veracity of news, we propose a fine-grained reliability analysis of the entire media. Specifically, we study the prediction of sentence-level factuality of news reporting and bias of media outlets, which may explain more accurately the overall reliability of the entire source. We first manually produced a large sentence-level dataset, titled "FactNews", composed of 6,191 sentences expertly annotated according to factuality and media bias definitions from AllSides. As a result, baseline models for sentence-level factuality prediction were presented by fine-tuning BERT. Finally, due to the severity of fake news and political polarization in Brazil, both dataset and baseline were proposed for Portuguese. However, our approach may be applied to any other language

Nonordered dendritic mesoporous silica nanoparticles as promising platforms for advanced methods of diagnosis and therapies

Dendritic mesoporous silica nanoparticles (DMSNs) are a new generation of porous materials that have gained great attention compared to other mesoporous silicas due to attractive properties, including straightforward synthesis methods, modular surface chemistry, high surface area, tunable pore size, chemical inertness, particle size distribution, excellent biocompatibility, biodegradability, and high pore volume compared with conventional mesoporous materials. The last years have witnessed a blooming growth of the extensive utilization of DMSNs as an efficient platform in a broad spectrum of biomedical and industrial applications, such as catalysis, energy harvesting, biosensing, drug/gene delivery, imaging, theranostics, and tissue engineering. DMSNs are considered great candidates for nanomedicine applications due to their ease of surface functionalization for targeted and controlled therapeutic delivery, high therapeutic loading capacity, minimizing adverse effects, and enhancing biocompatibility. In this review, we will extensively detail state-of-the-art studies on recent advances in synthesis methods, structure, properties, and applications of DMSNs in the biomedical field with an emphasis on the different delivery routes, cargos, and targeting approaches and a wide range of therapeutic, diagnostic, tissue engineering, vaccination applications and challenges and future implications of DMSNs as cuttingedge technology in medicine

Nonordered dendritic mesoporous silica nanoparticles as promising platforms for advanced methods of diagnosis and therapies

Dendritic mesoporous silica nanoparticles (DMSNs) are a new generation of porous materials that have gained great attention compared to other mesoporous silicas due to attractive properties, including straightforward synthesis methods, modular surface chemistry, high surface area, tunable pore size, chemical inertness, particle size distribution, excellent biocompatibility, biodegradability, and high pore volume compared with conventional mesoporous materials. The last years have witnessed a blooming growth of the extensive utilization of DMSNs as an efficient platform in a broad spectrum of biomedical and industrial applications, such as catalysis, energy harvesting, biosensing, drug/gene delivery, imaging, theranostics, and tissue engineering. DMSNs are considered great candidates for nanomedicine applications due to their ease of surface functionalization for targeted and controlled therapeutic delivery, high therapeutic loading capacity, minimizing adverse effects, and enhancing biocompatibility. In this review, we will extensively detail state-of-the-art studies on recent advances in synthesis methods, structure, properties, and applications of DMSNs in the biomedical field with an emphasis on the different delivery routes, cargos, and targeting approaches and a wide range of therapeutic, diagnostic, tissue engineering, vaccination applications and challenges and future implications of DMSNs as cutting-edge technology in medicine

Simultaneous Estimation of Nebivolol Hydrochloride and Valsartan using RP HPLC

In this study, a rapid, precise, accurate, specific and sensitive ion-paired reverse phase liquid chromatographic method has been developed for the simultaneous estimation of nebivolol hydrochloride and valsartan in their capsule formulation. The chromatographic method was standardized using a HIQ sil C18 column (250×4.6 mm i.d., 5 μm particle size) with UV detection at 289 nm and flow rate of 1 ml/min. The mobile phase consisting of methanol:water (80:20 v/v) with addition of 0.1 percent 1-hexanesulfonic acid monohydrate sodium salt as an ion-pairing reagent was selected. The method was validated and produced accurate and precise results for estimation of the two drugs

Stability analysis of network-controlled generator excitation system with interval time-varying delays

This paper deals with the problem of stability analysis of generator excitation system (GES) with interval time-varying delays. Network-controlled GES involves transmitting measured data from the plant site to controller and control signals from the controller to the plant site. Open communication channels impart time-varying nature to the delays. These time-varying delays can vary between intervals which would affect the system stability. The model of a GES is developed with the proportional integral (PI) controller including delay effects. In this paper, a less conservative delay-dependent stability criterion is derived using Lyapunov-Krasvoskii functional (LKF) for GES with interval time-varying delays. The bounding technique for derivative of LKF is developed by using Wirtinger inequality and free-weighting matrices. The relationship between the delay margins of GES and gains of the PI controller are investigated. This delay margin is used to tune the PI controller. The adequacy of the proposed result is confirmed by using simulation studies

Stability analysis of network-controlled DC position servo system with time-delay

This paper presents a stability analysis of network-controlled direct current (DC) position servo system with time-delays (TDs). The usage of communication links and measurement devices in the network-controlled system involves a considerable amount of TDs. Those TDs would degrade the dynamic performance and causes instability to the DC position servo system. A less conservative delay-dependent stability (DDS) criterion is presented by using Lyapunov–Krasvoskii functional and linear matrix inequality techniques. The maximum allowable TD called delay margin (DM) is computed, which can be used to tune a proportional-integral (PI) controller of the DC position servo system. Two cases of TD are considered in this analysis: time-invariant and time-varying delays. The DDS approach is used to study the trade-off between the PI controller gains and the DMs. This approach together with numerical simulation gives the insightful trade-off between DM and dynamic performance of the system. Finally, the stability of the DC position servo system with PI controller is analysed in the presence of TD through the experimental setup

Asymptotic Stability of Fixed-Point State-Space Digital Filters with Saturation Arithmetic and External Disturbance: An IOSS Approach

A criterion for the input/output-to-state stability of interfered state-space digital filters with saturation arithmetic and external interference is presented. The proposed linear matrix inequality-based criterion ensures the reduction in the effect of external interference as well as confirms the asymptotic stability in the absence of external interference. The criterion turns out to be an improvement over a previously reported criterion. A numerical example is given to illustrate the applicability of the proposed criterion

An improved criterion for peak-to-peak realization of direct-form interfered digital filters employing saturation nonlinearities

Purpose - The purpose of this paper is to present a criterion for global asymptotic stability of state-space direct-form digital filters employing saturation arithmetic. Design/methodology/approach - An elegant use of induced l∞ approach (also known as a peak-to-peak approach) is made to develop a criterion for the overflow stability of state-space direct-form digital filters. Findings - The criterion not only guarantees asymptotic stability but also reduces the effect of external interference. The presented method yields better interference attenuation level as compared to a recently reported method. Numerical examples are given to illustrate the effectiveness of the proposed method. Practical implications - Digital filters are important dynamical systems in signal processing which are used for the processing of discrete signals. During the implementation of higher-order digital filter in hardware or software, introduction of external interference is unavoidable. Therefore, stability analysis of digital filters in the presence of external interference is of much practical importance. Originality/value - The main result of the paper is reported for the first time and it is useful to establish the asymptotic stability of digital filters in the presence of external disturbances

A Note on the Induced l∞ Stability of Fixed-Point Digital Filters Without Overflow Oscillations and Instability Due to Finite Wordlength Effects

A recently reported criterion due to Ahn and Lee (Adv Differ Equ 51:1–7, 2012) for the induced l∞ stability of fixed-point digital filters without overflow oscillations and instability due to finite wordlength effects is reviewed. This article points out that there is a technical error in the main result and at the same time presents an approach to correcting the main result. Moreover, a relaxed version of the criterion is made available. Illustrative examples are given to demonstrate the effectiveness of the proposed result