Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of the Graft Length on Nanocomposite Structure and Interfacial Dynamics

Both the dispersion state of nanoparticles (NPs) within polymer nanocomposites (PNCs) and the dynamical state of the polymer altered by the presence of the NP/polymer interfaces have a strong impact on the macroscopic properties of PNCs. In particular, mechanical properties are strongly affected by percolation of hard phases, which may be NP networks, dynamically modified polymer regions, or combinations of both. In this article, the impact on dispersion and dynamics of surface modification of the NPs by short monomethoxysilanes with eight carbons in the alkyl part (C8) is studied. As a function of grafting density and particle content, polymer dynamics is followed by broadband dielectric spectroscopy and analyzed by an interfacial layer model, whereas the particle dispersion is investigated by small-angle X-ray scattering and analyzed by reverse Monte Carlo simulations. NP dispersions are found to be destabilized only at the highest grafting. The interfacial layer formalism allows the clear identification of the volume fraction of interfacial polymer, with its characteristic time. The strongest dynamical slow-down in the polymer is found for unmodified NPs, while grafting weakens this effect progressively. The combination of all three techniques enables a unique measurement of the true thickness of the interfacial layer, which is ca. 5 nm. Finally, the comparison between longer (C18) and shorter (C8) grafts provides unprecedented insight into the efficacy and tunability of surface modification. It is shown that C8-grafting allows for a more progressive tuning, which goes beyond a pure mass effect.
XYZ physics at BESIII

In this talk, we present the recent study on the charmonium-like states from the BESIII Collaboration based on large data samples above D ¯ D threshold. The observation of X(3872) from the Y(4260) radiative transition, the study of the Y states from the e + e − → π + π − hc process, and the observation of the charged Zc states are included .
The Calculation of Robot Dynamics Using Articulated-Body Inertias

This paper describes a new method for calculating the acceleration of a robot in response to given actuator forces. The method is applicable to open-loop kinematic chains containing revolute and prismatic joints. The algorithm is based on recursive formulas involving quantities called articulated-body inertias, which represent the inertia properties of collections of rigid bodies connected together by joints allowing constrained relative motion between the bodies. A new, matrix-based notation is introduced to represent articulated-body inertias and other spatial quantities. This notation is used to develop the algorithm, and results in a compact representation of the equations. The new algorithm has a computational requirement that varies linearly with the number of joints, and its efficiency is compared with other published algorithms.
A modified QuEChERS method development to analyze tylosin and metronidazole antibiotics residue in shrimp (Penaeus monodon) using LC-ESI MS/MS

A modified QuEChERS method was developed for the simultaneous analysis of tylosin (Tyl) and metronidazole (MNZ) residues in shrimp samples using LC-ESI-MS/MS. The sample extraction procedure was based on modified QuEChERS, and the cleanup method was dispersive solid-phase extraction (dSPE). Octadecyl (C18) and primary secondary amine (PSA) sorbents were used in the dSPE cleanup. Analyte chromatographic separations were carried out using a ZORBAX RRHD Eclipse Plus C18 (100 × 2.1 mm, particle size 1.8 μm) column. The mobile phase consisted of dilluting 0.1% of formic acid with water and acetonitrile. The analyte was identified with multiple reaction monitoring and positive electrospray ionization. The analyte showed good linearity in the range of 0.5–50 μg/L for both analytes, and correlation coefficients (R2) were 0.9997 and 0.9998 for Tyl and MNZ, respectively. For the recovery study, three different concentration levels were spiked in triplicate. The recovery obtained a good result in the range of 81–85 % for Tyl with relative standard deviation (RSD) ≤ ± 4.9% and in the range of 85–88% for MNZ with RSD ≤ ± 4.07 %. The limit of detection (LOD) was estimated at 0.4 μg/kg for Tyl and 0.3 μg/kg for MNZ, and the limit of quantification (LOQ) was estimated at 1 μg/kg for Tyl and 0.9 μg/kg for MNZ. The linearity and recovery study showed that the method is validated and can be used to determine the Tyl and MNZ residues in shrimp. Finally, the method was applied to 25 real samples, which were collected from local markets and super shops in Dhaka and Khulna districts of Bangladesh, and only traces of Tyl were detected in one sample. This method is suitable for the regular analysis of Tyl and MNZ antibiotic residues in shrimp samples and can be used to ensure food safety in Bangladesh.
Preventing and Reducing Nurse Burnout in an Outpatient Military Facility

Practice Problem: Nurse burnout adversely affects nurses, patients, and healthcare organizations. Implementing changes to address key contributors to burnout can effectively reduce and prevent burnout. PICOT: The PICOT question that guided this project was: In outpatient clinic nurses (P), how does implementing a bundled strategy (I) compared to not providing interventions (C) affect nurse burnout (O) within eight weeks (T)? Evidence: Evidence from an extensive literature review showed that there is no single cause for burnout and therefore no single intervention to reduce or prevent it. The primary themes in the literature to address burnout include practicing mindfulness, building resilience, and changing the environment. Intervention: The intervention for the change project included bringing nurses together to build their community within the practicum site, teaching nurses about mindfulness and leading nurses through mindfulness exercises, educating nurses on building resilience, and empowering nurses to change their environments. Outcome: The interventions resulted in a statistically significant decrease in Emotional Exhaustion, one of the three domains of burnout. There were also improvements in the two other domains of burnout, Depersonalization and Personal Accomplishment. While there was not a statistically significant improvement in those domains, a decrease in Patient Safety events demonstrated the clinical significance of the change project. Conclusion: The project outcome demonstrates that interventions to address burnout have a positive effect on the three domains of burnout, Emotional Exhaustion, Depersonalization, and Personal Accomplishment. Burnout among the nurses improved while patient safety improved as well.
Effect of wetting-layer density of states on the gain and phase recovery dynamics of quantum-dot semiconductor optical amplifiers

We numerically investigate the effect of the wetting-layer (WL) density of states on the gain and phase recovery dynamics of quantum-dot semiconductor optical amplifiers in both electrical and optical pumping schemes by solving 1088 coupled rate equations. The temporal variations of the ultrafast gain and phase recovery responses at the ground state (GS) are calculated as a function of the WL density of states. The ultrafast gain recovery responses do not significantly depend on the WL density of states in the electrical pumping scheme and the three optical pumping schemes such as the optical pumping to the WL, the optical pumping to the excited state ensemble, and the optical pumping to the GS ensemble. The ultrafast phase recovery responses are also not significantly affected by the WL density of states except the optical pumping to the WL, where the phase recovery component caused by the WL becomes slowed down as the WL density of states increases.
Cortisol Immunosensors: A Literature Review

Cortisol is a steroid hormone that is involved in a broad range of physiological processes in human/animal organisms. Cortisol levels in biological samples are a valuable biomarker, e.g., of stress and stress-related diseases; thus, cortisol determination in biological fluids, such as serum, saliva and urine, is of great clinical value. Although cortisol analysis can be performed with chromatography-based analytical techniques, such as liquid chromatography–tandem mass spectrometry (LC-MS/MS), conventional immunoassays (radioimmunoassays (RIAs), enzyme-linked immunosorbent assays (ELISAs), etc.) are considered the “gold standard” analytical methodology for cortisol, due to their high sensitivity along with a series of practical advantages, such as low-cost instrumentation, an assay protocol that is fast and easy to perform, and high sample throughput. Especially in recent decades, research efforts have focused on the replacement of conventional immunoassays by cortisol immunosensors, which may offer further improvements in the field, such as real-time analysis at the point of care (e.g., continuous cortisol monitoring in sweat through wearable electrochemical sensors). In this review, most of the reported cortisol immunosensors, mainly electrochemical and also optical ones, are presented, focusing on their immunosensing/detection principles. Future prospects are also briefly discussed.
Reduction and control of air pollution: based on plant-microbe interactions

ABSTRACT Economic development brings environmental challenges of which air pollution poses serious risks to humans and ecosystems. Air pollutants include volatile organic compounds (VOCs), inorganic air pollutants (IAPs) and particulate matter (PMs). Plant leaves may reduce such air pollution through adsorption and stomatal absorption. At the same time, air pollutants enter soil and root zones due to its content in rain and leaf fall. Microorganisms degrade and transform air pollutions. However, the efficiency of phytoremediation and bioremediation is slow and the use of plant-microbe interactions may therefore greatly enhance the efficiency of phytoremediation. The release of chemicals from plants leads to a mutual interaction with the microbiome that promotes the growth of the plant itself, thus enhancing degradation and detoxification of interleaf and inter-root air pollutants. Here we review the current research progress on combined plant-microbe action and discusses the interaction between plants and associated microorganisms while providing perspectives for future research in phytotechnologies. Graphical Abstract
Transverse instability and low-frequency flapping in incompressible separated boundary layer flows: an experimental study

Abstract The unstable dynamics of a transitional laminar separation bubble behind a two-dimensional bump geometry is investigated experimentally using dye visualizations and particle image velocimetry measurements. For Reynolds numbers above a critical value, the initially two-dimensional recirculation bubble is subject to modulations in the spanwise direction which can trigger vortex shedding. Increasing the Reynolds number further, the unstable behaviour is dominated by a low-frequency flapping motion, well known in transonic flows, and here investigated for the first time experimentally in an incompressible flow regime. These phenomena are characterized by non-intrusive measurements of the spatial structure and the frequencies of the unsteady motion. The results are in excellent agreement with previous numerical and theoretical predictions for the same geometry.
Genetic variability in genotypes of safflower via SSR molecular marker

ABSTRACT The safflower is an oleaginous plant belonging to the Asteraceae family. It is used as a raw material for various purposes. These plants are popular for the quality and quantity of oil produced and, and thus, studying their genetic variability using markers is necessary for determining genetic resources to conduct breeding programs. Therefore, we evaluated the genetic variability of safflower genotypes using Simple Sequence Repeat (SSR) molecular markers. The study was conducted at the State University of Mato Grosso “Carlos Alberto Reyes Maldonado”, in the Campus of Cáceres-MT. In total, 121 safflower genotypes from the Germplasm collection were evaluated using 21 SSR markers. The programs GenAlEx 6.5, GENES, and Structure were used to analyze the data. We identified 158 alleles at 21 loci among the genotypes. The expected heterozygosity (He) was high (0.551 - 0.804), but the observed heterozygosity (Ho) was low (0.000 - 0.502), and the indices of the endogamy coefficient (F) were positive in all loci and all populations, with an overall average of 0.958. The genetic differentiation (FST) values among populations were low, with an average of 0.010, which suggested a low population structure. The modified Tocher clustering and the UPGMA hierarchical clustering yielded 19 and 15 distinct groups, respectively. The genetic structure showed two populations, with few intermixes in the genome. The evaluated safflower genotypes showed genetic variability, and these genetically different variants might be used in breeding programs to obtain cultivars adapted to Brazil.
Numerical modelling of landslide‐generated waves with the particle finite element method (PFEM) and a non‐Newtonian flow model

Landslide‐generated impulse waves may have catastrophic consequences. The physical phenomenon is difficult to model because of the uncertainties in the kinematics of the mobilised material and to the intrinsic complexity of the fluid–soil interaction. The particle finite element method (PFEM) is a numerical scheme that has successfully been applied to fluid–structure interaction problems. It uses a Lagrangian description to model the motion of nodes (particles) in both the fluid and the solid domains (the latter including soil/rock and structures). A mesh connecting the particles (nodes) is re‐generated at every time step, where the governing equations are solved. Various constitutive laws are used for the sliding mass, including rigid solid and the Newtonian and non‐Newtonian fluids. Several examples of application are presented, corresponding both to experimental tests and to actual full‐scale case studies. The results show that the PFEM can be a useful tool for analysing the risks associated with landslide phenomena, providing a good estimate to the potential hazards even for full‐scale events. Copyright © 2015 John Wiley & Sons, Ltd.
A dry phantom material composed of ceramic and graphite powder

Details of an artificially synthesized dry phantom material developed for experimental studies of microwave exposure to the human body are shown. The material is solid and can simulate electrical characteristics of high water content biological tissues such as muscles and the brain. The material is composed of high-/spl epsiv//sub r/ ceramic powder, graphite powder, and bonding resin. Any shape of phantom models can be constructed to simulate different parts of the body, as well as the head. The paper reports the synthesis technique to obtain the desired complex permittivity and the fabrication technique of the phantom models for usage of specific absorption rate (SAR) estimation at 900 MHz.
China in Transnational Extractives Governance: A Mapping Exercise

Abstract China became one of the biggest players in the global extractive resource supply chain, along with increasing extractive resource demand for green industries. Interestingly, over the last two decades, Chinese actors started participating in transnational extractive governance initiatives (TEGI) supporting transparency, a norm for governance-by-disclosure. This article aims to answer the question of what types of Chinese actors engage in what TEGIs regarding transparency. Based on mapping forty-eight TEGIs, this article shows a nuanced pattern of China’s involvement in extractives governance beyond a dualistic approach to China in global governance—whether China is a threat or nonthreat. Importantly, China does not act as a unified monolithic actor; rather, different types of actors engage TEGIs distinctively. Chinese corporations are most actively engaging in thin transparency TEGIs lacking stringent verification rules and featuring limited multistakeholder participation. It could potentially accelerate the risk of green washing of those companies and disempower weaker actors.
Dispersion in Fractal Fracture Networks

The solute transport equation describes dispersion as a diffusion-like process characterized by a constant dispersivity, implying that small pulses of contaminant grow as the square root of distance traveled. Measured dispersivities tend to be proportional to the scale of the measurement, suggesting that the pulses grow in linear proportion to distance. An exponent r, defined by the relationship d∼Lr where d is the standard deviation of position of a contaminant particle and L is the distance traversed, may be used to characterize dispersion. It takes a value ½ in the first case and 1 in the second. The movement of a contaminant particle is analyzed here as a random walk through a fracture network composed of fissures of varying transmissivity. If large-transmissivity fractures are sufficiently few, then one calculates r = ½. If large-transmissivity fractures are numerous, one obtains 2r = q + 1, where q is an exponent that describes the relationship between fracture spacing and transmissivity. Inserting the reasonable value q= 1 gives r = 1. This theory thus provides a physical basis for the observed scale-dependence of dispersivity.
Effectual switching filter for removing impulse noise using a SCM detector

An effectual method is proposed to remove impulse noise from corrupted color images. The spiking cortical model (SCM) is adopted as a noise detector to identify noisy pixels in each channel of color images, and detected noise pixels are saved in three marking matrices. According to the three marking matrices, the detected noisy pixels are divided into two types (type I and type II). They are filtered differently: an adaptive median filter is used for type I and an adaptive vector median for type II. Noise-free pixels are left unchanged. Extensive experiments show that the proposed method outperforms most of the other well-known filters in the aspects of both visual and objective quality measures, and this method can also reduce the possibility of generating color artifacts while preserving image details.
Double-Center-Based Iris Localization and Segmentation in Cooperative Environment with Visible Illumination

Iris recognition has been considered as one of the most accurate and reliable biometric technologies, and it is widely used in security applications. Iris segmentation and iris localization, as important preprocessing tasks for iris biometrics, jointly determine the valid iris part of the input eye image; however, iris images that have been captured in user non-cooperative and visible illumination environments often suffer from adverse noise (e.g., light reflection, blurring, and glasses occlusion), which challenges many existing segmentation-based parameter-fitting localization methods. To address this problem, we propose a novel double-center-based end-to-end iris localization and segmentation network. Different from many previous iris localization methods, which use massive post-process methods (e.g., integro-differential operator-based or circular Hough transforms-based) on iris or contour mask to fit the inner and outer circles, our method directly predicts the inner and outer circles of the iris on the feature map. In our method, an anchor-free center-based double-circle iris-localization network and an iris mask segmentation module are designed to directly detect the circle boundary of the pupil and iris, and segment the iris region in an end-to-end framework. To facilitate efficient training, we propose a concentric sampling strategy according to the center distribution of the inner and outer iris circles. Extensive experiments on the four challenging iris data sets show that our method achieves excellent iris-localization performance; in particular, it achieves 84.02% box IoU and 89.15% mask IoU on NICE-II. On the three sub-datasets of MICHE, our method achieves 74.06% average box IoU, surpassing the existing methods by 4.64%.
The General Distribution of the Error Rate of a Classification Procedure With Application to Logistic Regression Discrimination

Abstract The large-sample distribution of the error rate of an arbitrary estimator of the optimal classification rule is given. The asymptotic distribution of the logistic regression estimator is found. These results are used to show that the efficiency of logistic regression classification in some nonnormal cases is low. This suggests that maximum likelihood discrimination should be used whenever possible.
State Feedback and Deadbeat Predictive Repetitive Control of Three-Phase Z-Source Inverter

In this paper, a composite control method combining repetitive control (RC) and deadbeat predictive control (DPC) is proposed to reduce the harmonic content of output voltage and improve the quality of voltage waveform, in order to solve the problem of voltage distortion caused by linear and nonlinear loads at the common grid-connected point of microgrid. First, the mathematical model of three-phase Z-source inverters is established, and the model is transformed into a state space expression. Then, Lyapunov’s theory is used to find the design conditions of the state feedback control law based on linear matrix inequality. Finally, the parameters of the controller are solved by linear matrix inequality (LMI), and the parameter design of the improved repetitive controller is optimized. Furthermore, the system response speed is improved, and the system stability and robustness are guaranteed by combining the deadbeat predictive control technology. The simulation and experimental results verify the accuracy and superiority of the proposed deadbeat predictive repetitive control (DPRC) based on parameter optimization.
A search for substellar companions to southern solar-type stars

At the Mount John University Observatory relative radial velocities of solar-type stars have been obtained with a characteristic random error of 55 m s −1 using a fiber-fed echelle system and digital cross-correlation techniques. A program of obtaining radial velocities of 29 solar-type stars and 10 giant International Astronomical Union radial-velocity standard stars was carried out over 2.5 years with a view to the detection of low-mass companions to the dwarf stars. One dwarf star turned out to have a previously undiscovered stellar companion but no dwarfs showed radial-velocity variability suggestive of the presence of substellar companions, although one showed a possible variation. In contrast, at least half the giant or supergiant standard stars were variable in radial velocity
Singular 2D Behaviors: Fornasini–Marchesini and Givone–Roesser Models

Abstract In this paper we study 2D Fornasini–Marchesini and 2D Givone–Roesser models from the viewpoint developed in our recent paper [Lomadze, Rogers, Wood, Georgian Math. J. 15: 139–157, 2008]. We give necessary and sufficient conditions for a behavior to be expressable in Fornasini–Marchesini or Givone–Roesser form, and a canonical realization when the conditions are met. We also study the regularity, controllability and autonomy of these models. In particular, we provide the concepts of controllability in the sense of Kalman for each model, and show that they agree with the behavioral controllability as defined in [Lomadze, Rogers, Wood, Georgian Math. J. 15: 139–157, 2008].