Miracle-dz/UniFAR-FTUs huggingface dataset:
Event-Argument Linking in Disaster Domain

Linking event triggers with their respective arguments is an essential component for building an event extraction system. It is challenging to link event triggers with their corresponding argument triggers when the sentence contains multiple event and argument triggers. The task becomes even more challenging in a low-resource setup due to the unavailability of natural language processing resources and tools. In this paper, we study the event-argument linking task based on disaster event ontology in a low resource setup. We use BERT and non-BERT-based deep learning models in both monolingual and cross-lingual event-argument linking tasks. We also perform an ablation study of various features like position embeddings (PE), position indicator (PI), and segment ID (SI) to understand their contribution to performance improvement in non-BERT-based models. Using three different languages viz. Hindi, Bengali, and Marathi, we compare the results with multilingual BERT-based deep neural models in both monolingual and cross-lingual scenarios. We observe that the multilingual BERT-based model outperforms the best performing non-BERT-based model in cross-lingual settings. But in monolingual settings, the performance is similar in Hindi and Bengali datasets and slightly better in Marathi dataset. We choose the disaster domain due to its social implications. Our current experiments can be helpful in mining important information related to disaster events from news articles and building event knowledge graphs in low-resource languages.
A novel model for estimating the endpoint stiffness of a limb

In past years, the muscle activation, collected from a human operator, was used to drive not only the endpoint force and trajectory, but also the impedance of robotic devices. Therefore, different groups proposed algorithms for real-time estimation of endpoint stiffness from muscle activation, but these estimations were based on complex models of the human, which required the control of subject-specific anatomically accurate musculo-skeletal models, or oversimplified models, which reduced the high redundancy of the musculo-skeletal system by collecting the activity of few couples of antagonist muscles. This study describes and tests a novel algorithm which approximates the stiffness exerted by a multi-joint multi-muscle system, from the muscle activation. This algorithm approximates the stiffness of a limb as the component of the muscle activation that do not generates any endpoint force, which is calculated as the projection of the muscle activation vector onto the null space of the mapping between muscle activation and endpoint force. The proposed approximation was verified on an upper limb model made of two joints and six muscles, modeled as the Hill muscle model. This study identifies the null space component of the muscle activation as an acceptable estimation of the major axis of the stiffness ellipse, especially for low muscle activation. The presented model could be directly implemented in myoelectric controlled devices for the real-time estimation of the endpoint forces, or endpoint movement, from the mapping between muscle activation and force, without any more calibrations.
An Economic Evaluation of the Adjuvanted Quadrivalent Influenza Vaccine Compared with Standard-Dose Quadrivalent Influenza Vaccine in the Spanish Older Adult Population

Standard-dose quadrivalent influenza vaccines (QIV) are designed to provide protection against all four influenza strains. Adjuvanted QIV (aQIV), indicated for individuals aged 65+ years, combines MF59® adjuvant (an oil-in-water emulsion of squalene oil) with a standard dose of antigen, and is designed to produce stronger and longer immune response, especially in the elderly where immunosenescence reduces vaccine effectiveness. This study evaluated the cost-effectiveness of aQIV vs. egg-based standard-dose QIV (QIVe) in the elderly population, from the payer and societal perspective in Spain. A dynamic transmission model, which accounts for herd protection, was used to predict the number of medically attended infections in Spain. A decision tree structure was used to forecast influenza-related costs and benefits. Influenza-related probabilities of outpatient visit, hospitalization, work absenteeism, mortality, and associated utilities and costs were extracted from Spanish and European published literature. Relative vaccine effectiveness (rVE) was sourced from two different meta-analyses: the first meta-analysis was informed by laboratory-confirmed influenza studies only, resulting in a rVE = 34.6% (CI95% 2–66%) in favor of aQIV; the second meta-analysis included real world evidence influenza-related medical encounters outcomes, resulting in a rVE = 13.9% (CI95% 4.2–23.5%) in benefit of aQIV. All costs were expressed in 2021 euros. Results indicate that replacing QIVe with aQIV in the Spanish elderly population would prevent on average 43,664 influenza complicated cases, 1111 hospitalizations, and 569 deaths (with a rVE = 34.6%) or 19,104 influenza complicated cases, 486 hospitalizations, and 252 deaths (with a rVE = 13.9%). When the rVE of aQIV vs. QIVe is 34.6%, the incremental cost per quality adjusted life years (QALY) gained was €2240 from the payer; from the societal perspective, aQIV was cost saving compared with QIVe. If the rVE was 13.9%, the incremental cost per QALY was €6694 and €3936 from the payer and societal perspective, respectively. Sensitivity analyses validated the robustness of these findings. Results indicate that replacing QIVe with aQIV in the Spanish elderly population is a cost-effective strategy for the Spanish healthcare system.
Rapid, Sensitive and Selective Optical Glucose Sensing with Stimulated Raman Scattering (SRS)

Optical blood glucose sensing offers pain-free, non-invasive, continuous monitoring with minimum risk of infection since it does not require breaking the skin barrier. Among various optical detection and spectroscopic techniques, only Raman scattering offers both high-accuracy and chemical-specific acquisition along with label-free sensing. However, spontaneous Raman scattering is a feeble process. The integration time is long and high laser intensities are demanded to achieve acceptable sensitivity in detecting physiologically relevant glucose levels. This hinders the inherent advantages of Raman scattering-based technologies as a wearable medical point-of-care device. Therefore, this study applies stimulated Raman scattering (SRS) to glucose sensing, which overcomes the limitations of spontaneous Raman spectroscopy. This is the first study demonstrating the application of SRS in glucose concentration monitoring. Herein, by enhancing the Raman effect using stimulating excitation, we have recorded a linear calibration curve for concentrations below 100 mol/m3 with a theoretical limit of detection (LOD) of 3.5 mol/m3 in a phenomenal 0.6 s integration time merely by employing univariate data analysis. In addition, we have assessed the optimum required averaged laser power and sensing mechanism's feasibility in complete human serum glucose measurement and established a highly selective detection mechanism by solely identifying the characteristic Raman shift peak of glucose around 1130 cm−1.
Mechanical Unloading of the Left Ventricle before Coronary Reperfusion in Preclinical Models of Myocardial Infarction without Cardiogenic Shock: A Meta-Analysis

Aim: to compare a conventional primary reperfusion strategy with a primary unloading approach before reperfusion in preclinical studies. Methods: we performed a meta-analysis of preclinical studies. The primary endpoint was infarct size (IS). Secondary endpoints were left ventricle end-diastolic pressure (LVEDP), mean arterial pressure (MAP), heart rate (HR), cardiac output (CO). We calculated mean differences (MDs) and associated 95% confidence intervals (CIs). Sensitivity and subgroup analyses on the primary and secondary endpoints, as well as a meta-regression on the primary endpoint using the year of publication as a covariate, were also conducted. Results: 11 studies (n = 142) were selected and entered in the meta-analysis. Primary unloading reduced IS (MD −28.82, 95% CI −35.78 to −21.86, I2 96%, p < 0.01) and LVEDP (MD −3.88, 95% CI −5.33 to −2.44, I2 56%, p = 0.02) and increased MAP (MD 7.26, 95% CI 1.40 to 13.12, I2 43%, p < 0.01) and HR (MD 5.26, 95% CI 1.97 to 8.55, I2 1%, p < 0.01), while being neutral on CO (MD −0.11, 95% CI −0.95 to 0.72, I2 88%, p = 0.79). Sensitivity and subgroup analyses showed, overall, consistent results. The meta-regression on the primary endpoint demonstrated a significant influence of the year of publication on effect estimate. Conclusions: in animal models of myocardial infarction, a primary unloading significantly reduces IS and exerts beneficial hemodynamic effects compared to a primary reperfusion.
Mechanistic Insights into the Pharmacological Significance of Silymarin

Medicinal plants are considered the reservoir of diverse therapeutic agents and have been traditionally employed worldwide to heal various ailments for several decades. Silymarin is a plant-derived mixture of polyphenolic flavonoids originating from the fruits and akenes of Silybum marianum and contains three flavonolignans, silibinins (silybins), silychristin and silydianin, along with taxifolin. Silybins are the major constituents in silymarin with almost 70–80% abundance and are accountable for most of the observed therapeutic activity. Silymarin has also been acknowledged from the ancient period and is utilized in European and Asian systems of traditional medicine for treating various liver disorders. The contemporary literature reveals that silymarin is employed significantly as a neuroprotective, hepatoprotective, cardioprotective, antioxidant, anti-cancer, anti-diabetic, anti-viral, anti-hypertensive, immunomodulator, anti-inflammatory, photoprotective and detoxification agent by targeting various cellular and molecular pathways, including MAPK, mTOR, β-catenin and Akt, different receptors and growth factors, as well as inhibiting numerous enzymes and the gene expression of several apoptotic proteins and inflammatory cytokines. Therefore, the current review aims to recapitulate and update the existing knowledge regarding the pharmacological potential of silymarin as evidenced by vast cellular, animal, and clinical studies, with a particular emphasis on its mechanisms of action.
Data-Driven Security and Stability Rule in High Renewable Penetrated Power System Operation

Power systems around the world are experiencing an energy revolution that substitutes fossil fuels with renewable energy. Such a transition poses two significant challenges: highly variable generators that add short-term and long-term difficulties for supply–demand balance, and a high proportion of convertor-based devices that may jeopardize power system security and stability. At the same time, machine learning techniques provide more opportunities to study the complex power system security and stability problems. This article summarizes the machine learning framework to embed security rules into power system operation optimization under high renewable energy penetration. First, we explore how high penetration renewable energy impacts power system security and stability. Then, we review how the complex security and stability boundary of power systems is modeled using various machine learning techniques. Finally, we show how the machine learning model is transformed into optimization constraints that can be embedded into the power system operation model. The framework is substantiated through case studies of practical power systems.
Dynamic Level Changing for Full Range ZVS in Flying Capacitor Multi-Level Converters

This paper presents a control technique for flying capacitor multi-level (FCML) converters to achieve zero-voltage switching (ZVS) across the full range of duty cycles, with application in high power density and high efficiency power converters. Previous works have used variable frequency control to enable ZVS at specific duty cycles in FCML converters, but have not been able to use these methods to enable ZVS across the full range. This work uses dynamic level selection and variable frequency control to increase inductor current ripple at duty cycle ranges for which ZVS was previously unattainable. An experimental 5-level FCML prototype has been built using GaN devices on a single-sided PCB to demonstrate this control technique. We demonstrate 4-level and 5-level operation with ZVS at duty cycles that are not possible with 5-level operation alone, as well as a dynamic level transition with active capacitor voltage balancing.
EmpowerSoC: An Open-Source Power Analysis Engine based on Qflow

The paper introduces EmpowerSoC which is an open-source power analysis engine based on the Qflow tool chain. Both active and standby power consumption can be estimated using this tool. Qflow is used to run the RTL to GDSII flow a target design and is a silicon proven flow [1]. Power estimation in EmpowerSoC is done by extracting transistor-level post-layout netlists for various building blocks/cells on an automated basis. It has a user-friendly GUI through which users can set input bit patterns and other simulation parameters. It has been tested on various digital blocks and the obtained results have been presented.
Asymptotic Behavior on a Linear Self-Attracting Diffusion Driven by Fractional Brownian Motion

Let BH={BtH,t≥0} be a fractional Brownian motion with Hurst index 12≤H<1. In this paper, we consider the linear self-attracting diffusion: dXtH=dBtH+σXtHdt−θ∫0tXsH−XuHdsdt+νdt with X0H=0, where θ>0 and σ,ν∈R are three parameters. The process is an analogue of the self-attracting diffusion (Cranston and Le Jan, Math. Ann.303 (1995), 87–93). Our main aim is to study the large time behaviors. We show that the solution t−σθHXtH−X∞H converges in distribution to a normal random variable, as t tends to infinity, and obtain two strong laws of large numbers associated with the solution XH.
Global dynamics in chemostat equations

In this paper, we prove the competitive exclusion principle in a chemostat with a single nutrient and N competing species. Growth rates are not required to be proportional to food uptake. The model was studied by B. Fiedler and S.B. Hsu [J. Math. Biol. (2009) 59:233-253]. Using a multidimensional Bendixon-Dulac criterion these authors prove the nonexistence of periodic orbits. Here we use a Lyapunov function approach. We construct Lyapunov functions which extend those functions used by Hsu [SIAM J. Appl. Math. (1978) 34:760-763] and by Wolkowicz and Lu [SIAM J. Appl. Math. (1997) 57:1019-1043] in the case when the growth rates are proportional to food uptake.
Light Intensity—A Key Factor Affecting Flavonoid Content and Expression of Key Enzyme Genes of Flavonoid Synthesis in Tartary Buckwheat

Tartary buckwheat, a polygonaceae family plant, is rich in abundant flavonoids, high-quality protein, and well-balanced essential amino acids. This study aimed to investigate the effects of climatic variables on the quality of Tartary buckwheat. In this study, six distinct types of Tartary buckwheat collected from the Sichuan Basin, Western Sichuan Plateau, and Yunnan-Guizhou Plateau in southwest China were chosen to investigate the impact of climatic conditions from the grain-filling stage to the harvest stage on the concentration of flavonoids and expression of key enzyme genes involved the synthesis of flavonoids. Meteorological data of three producing areas were collected from the China Meteorological Network, mainly including maximum temperature (Tmax), minimum temperature (Tmin), diurnal temperature difference (Tdif), and light intensity. Then, the contents of rutin, kaempferol-3-O-rutin glycoside, quercetin, and kaempferol in 30 batches of Tartary buckwheat from 6 varieties including Chuanqiao No. 1, Chuanqiao No. 2, Xiqiao No. 1, Xiqiao No. 2, Miqiao No. 1 and Di ku were determined by ultra performance liquid chromatography-mass spectrometry (UPLC-MS/MS). Furthermore, the expression levels of phenylalanine ammonia lyase (PAL), 4-coumaric acid coenzyme A ligase (4CL), and anthocyanin synthase (ANS) in six kinds of Tartary buckwheat were detected by real-time polymerase chain reaction (PCR). The seed photos were processed by ImageJ processing software. The partial least squares method was used to analyze the correlation. As a result, light intensity can promote the accumulation of flavonoids and the expression of key enzyme genes. Miqiao No. 1, which grows in Liangshan Prefecture, Sichuan Province, has the highest light intensity and is the dominant variety with flavonoid content. More importantly, the expression levels of PAL and 4CL in the secondary metabolic pathway of flavonoids were positively correlated with the content of Tartary buckwheat flavonoids. Interestingly, the expression level of ANS was negatively correlated with the content of PAL, 4CL, and flavonoids. In addition, ANS is a key gene affecting the seed coat color of Tartary buckwheat. The higher the expression of ANS, the darker the seed coat color. These findings provide a theoretical basis and reference for the breeding of fine buckwheat varieties.
A Peak Current-Mode Control Boost Converter Model for Stability Analysis: A Design Approach

A simplified model is described for a peak current-mode control boost converter. The proposed model is implemented by averaging the operating point of the converter such that closed-loop stability can be analyzed. This model behavior is verified in simulation by implementing a 3.9 V input to 5 V output peak current-mode control boost converter with 240 mA load current. The simulations showed a good matching of ac response and load step response, and a detailed analysis of the model is presented.
A Percolative Account of Tianjin Tone Sandhi

This paper presents data from Tianjin tritonal sandhi patterns that challenge both traditional derivational approaches and standard Optimality Theoretic (OT) approaches to phonological alternation. If construed derivationally, Tianjin tritonal sandhi requires derivational reversals; but if construed within OT, involves combinations of opacity and transparency. The account proposed here appeals to a percolative model where phonological information from terminal nodes finds correspondences in higher nodes, such that the correspondences may be imperfect when triggered by markedness requirements. While this requires a total reconceptualization of phonological representations, this paper argues that it is well worth it because it predicts that: (1) directionality is a derivate from branching; (2) the depth of derivational opacity is confined by structural depth; (3) constituency, not adjacency, provides the environment for triggering alternation so alternation rules can therefore be blocked when marked collocations belong to different constituencies; and (4) underlying entities can have split surface correspondences.
Chemistry and Production Technology of Hallstatt Period Glass Beads from Bohemia

The presented study evaluated a set of beads primarily originating from the Hallstatt period (800–400 BC) and uncovered in the region of Bohemia. Utilizing an SEM/EDS method, the chemical composition of the glass samples was determined and their homogeneity measured. Owing to the presence of opaque glass, Raman spectroscopy was applied, enabling the definition of the phases causing the opacity of the glass, as well as its coloring. This article discusses opacifying agents, including the possible ways in which they entered the artefacts. In addition, the techniques used to produce the glass beads are described, for both the single-colored beads, as well as the so-called eye beads that are present in a significant amount in the set. The majority of the beads examined were found to be made of the LMG glass type (low-magnesium soda-lime glass). An unexpected result was the identification of glass with a high content of K2O not corresponding to the mixed alkali type (LMHK), which is frequently discussed in the literature. The glass type in question most likely does not come from the traditional area of glass production: the eastern Mediterranean territory.
Fixed-Time Dynamic Surface Control for Pneumatic Manipulator System With Unknown Disturbances

In this article, a new nonlinear disturbance observer (NDO) based fixed-time dynamic surface control (FTDSC) approach is developed to achieve desired trajectory tracking control performances of the pneumatic manipulator system driven by pneumatic artificial muscles (PAMs). To achieve active disturbance rejection, an NDO is proposed to estimate the unknown disturbances in the pneumatic manipulator system. Then, a fixed-time dynamic surface controller is introduced, and the variable gains are designed to achieve desired control performances. Finally, comparative simulations and experiments verify that the proposed approach is effective to achieve desired trajectory tracking control performances.
Resistance Training Improves Beta Cell Glucose Sensing and Survival in Diabetic Models

Resistance training increases insulin secretion and beta cell function in healthy mice. Here, we explored the effects of resistance training on beta cell glucose sensing and survival by using in vitro and in vivo diabetic models. A pancreatic beta cell line (INS-1E), incubated with serum from trained mice, displayed increased insulin secretion, which could be linked with increased expression of glucose transporter 2 (GLUT2) and glucokinase (GCK). When cells were exposed to pro-inflammatory cytokines (in vitro type 1 diabetes), trained serum preserved both insulin secretion and GCK expression, reduced expression of proteins related to apoptotic pathways, and also protected cells from cytokine-induced apoptosis. Using 8-week-old C57BL/6 mice, turned diabetic by multiple low doses of streptozotocin, we observed that resistance training increased muscle mass and fat deposition, reduced fasting and fed glycemia, and improved glucose tolerance. These findings may be explained by the increased fasting and fed insulinemia, along with increased beta cell mass and beta cell number per islet, observed in diabetic-trained mice compared to diabetic sedentary mice. In conclusion, we believe that resistance training stimulates the release of humoral factors which can turn beta cells more resistant to harmful conditions and improve their response to a glucose stimulus.
Genetic Diversity of Tomato Black Ring Virus Satellite RNAs and Their Impact on Virus Replication

Viral satellite RNAs (satRNAs) are small subviral particles that are associated with the genomic RNA of a helper virus (HV). Their replication, encapsidation, and movement depend on the HV. In this paper, we performed a global analysis of the satRNAs associated with different isolates of tomato black ring virus (TBRV). We checked the presence of satRNAs in 42 samples infected with TBRV, performed recombination and genetic diversity analyses, and examined the selective pressure affecting the satRNAs population. We identified 18 satRNAs in total that differed in length and the presence of point mutations. Moreover, we observed a strong effect of selection operating upon the satRNA population. We also constructed infectious cDNA clones of satRNA and examined the viral load of different TBRV isolates in the presence and absence of satRNAs, as well as the accumulation of satRNA molecules on infected plants. Our data provide evidence that the presence of satRNAs significantly affects viral load; however, the magnitude of this effect differs among viral isolates and plant hosts. We also showed a positive correlation between the number of viral genomic RNAs (gRNAs) and satRNAs for two analysed TBRV isolates.