Miracle-dz/UniFAR-FTUs huggingface dataset:
Outlier detection for particle image velocimetry data using a locally estimated noise variance

This work describes an adaptive spatial variable threshold outlier detection algorithm for raw gridded particle image velocimetry data using a locally estimated noise variance. This method is an iterative procedure, and each iteration is composed of a reference vector field reconstruction step and an outlier detection step. We construct the reference vector field using a weighted adaptive smoothing method (Garcia 2010 Comput. Stat. Data Anal. 54 1167–78), and the weights are determined in the outlier detection step using a modified outlier detector (Ma et al 2014 IEEE Trans. Image Process. 23 1706–21). A hard decision on the final weights of the iteration can produce outlier labels of the field. The technical contribution is that the spatial variable threshold motivation is embedded in the modified outlier detector with a locally estimated noise variance in an iterative framework for the first time. It turns out that a spatial variable threshold is preferable to a single spatial constant threshold in complicated flows such as vortex flows or turbulent flows. Synthetic cellular vortical flows with simulated scattered or clustered outliers are adopted to evaluate the performance of our proposed method in comparison with popular validation approaches. This method also turns out to be beneficial in a real PIV measurement of turbulent flow. The experimental results demonstrated that the proposed method yields the competitive performance in terms of outlier under-detection count and over-detection count. In addition, the outlier detection method is computational efficient and adaptive, requires no user-defined parameters, and corresponding implementations are also provided in supplementary materials.
Astroglial Cell-to-Cell Interaction with Autoreactive Immune Cells in Experimental Autoimmune Encephalomyelitis Involves P2X7 Receptor, β3-Integrin, and Connexin-43

In multiple sclerosis (MS), glial cells astrocytes interact with the autoreactive immune cells that attack the central nervous system (CNS), which causes and sustains neuroinflammation. However, little is known about the direct interaction between these cells when they are in close proximity in the inflamed CNS. By using an experimental autoimmune encephalomyelitis (EAE) model of MS, we previously found that in the proximity of autoreactive CNS-infiltrated immune cells (CNS-IICs), astrocytes respond with a rapid calcium increase that is mediated by the autocrine P2X7 receptor (P2X7R) activation. We now reveal that the mechanisms regulating this direct interaction of astrocytes and CNS-IICs involve the coupling between P2X7R, connexin-43, and β3-integrin. We found that P2X7R and astroglial connexin-43 interact and concentrate in the immediate proximity of the CNS-IICs in EAE. P2X7R also interacts with β3-integrin, and the block of astroglial αvβ3-integrin reduces the P2X7R-dependent calcium response of astrocytes upon encountering CNS-IICs. This interaction was dependent on astroglial mitochondrial activity, which regulated the ATP-driven P2X7R activation and facilitated the termination of the astrocytic calcium response evoked by CNS-IICs. By further defining the interactions between the CNS and the immune system, our findings provide a novel perspective toward expanding integrin-targeting therapeutic approaches for MS treatment by controlling the cell–cell interactions between astrocytes and CNS-IICs.
Different Concentrations of Chemical Topping Agents Affect Cotton Yield and Quality by Regulating Plant Architecture

Manual removal of the main stem tips of cotton (Gossypium hirsutum L.) is a traditional topping approach in China. However, chemical topping has become an inevitable trend. Therefore, it is of great significance to study the effect and appropriate concentration of agents for advancement of cotton whole process mechanization management technology. A two-year field experiment was conducted to evaluate the effects of different methods of topping on cotton yield and plant architecture in Shihezi, Xinjiang, China. Plant topping included manual topping, non-topping as the control, and chemical topping (high, medium, and low concentrations of topping agent) to determine a suitable topping method and topping agent concentration for machine-picked cotton. Chemical topping was performed using fortified mepiquat chloride (DPC+). Chemical topping and manual topping increased seed cotton yield compared with non-topping. Compared with non-topping, high, medium, and low concentrations of topping agent significantly increased the yield by 19.5–27.9%, 24.1–29.4%, and 24.3–28.4%, respectively. Topping treatment mainly regulated yield and total boll number per unit area by affecting the boll number per plant and had a certain positive effect on fiber strength but no significant effect on boll weight. Chemical topping affected both vertical and horizontal plant architecture characteristics of cotton; the plant height of low-, medium-, and high-concentration treatments increased by 7.2–11.4 cm, 4.0–5.7 cm, and 2.3–4.4 cm, respectively, compared with manual topping and decreased by 5.1–7.8 cm, 8.3–13.5 cm, and 9.4–16.9 cm, respectively, compared with non-topping. The number of main stem internodes was significantly different between high- and low-concentration treatments, which showed that the higher the concentration, the lower the number of the main stem internodes. Chemical topping controlled the increase in the length of the upper branches, the higher the concentration, the lower the increase in the length of the upper fruit branch. Compared with non-topping, the medium concentration of topping agent controlled the number of fruit branches, similar to manual topping. The role of upper internode length of cotton cannot be ignored under chemical topping. The peak leaf area index (LAI) of medium- and high-concentration treatments was delayed for 1 week in the late growth period (after topping for 28 d) compared with manual topping. The LAI values were high, and the duration of high values was prolonged. The optimal chemical topping agent was the medium concentration.
Analytical Investigation of Forced Oxidized Anti-VEGF IgG Molecules: A Focus on the Alterations in Antigen and Receptor Binding Activities

Alterations in the biological activity of the molecules under stress conditions have not been documented as widely in the literature yet. This study was designed to reveal the functional impacts of various oxidation conditions on a model mAb, a commercial anti-VEGF IgG molecule. The responses to antigen binding, cell proliferation, FcRn receptors, and C1q binding, which rarely appear in the current literature, were investigated. The authors report peptide mapping data, post-translational modification (PTM) analysis, cell proliferation performance, and antigen (VEGF), C1q, and FcRn binding activities of the mAb under various stress conditions. The oxidation-prone site of the mAb was determined as Met252 in the DTLMISR peptide. The VEGF binding activity and anti-cell proliferation activity of the mAbs did not alter, while C1q and FcRn binding capacity significantly decreased under oxidative stress conditions. The full report is vital for many scientific and industrial processes about mAbs. The authors recommend performing functional analyses in addition to the structural studies while investigating the impacts of stress factors on therapeutic mAbs.
Moving toward low frequencies active vibration control with inertial actuators

In applications of vibration suppression, control forces ideally act on the structure increasing its damping. While the frequency response of the structure is guaranteed to have a positive real part under ideal conditions, in practice a stability limit exists when inertial actuators are used. In this case the system response is no longer guaranteed to be positive real and so the control system may become unstable at high gains. Moreover, traditional approaches suggest the use of inertial actuators only if its natural frequency is well below the natural frequency of the structure, thus preventing their use at low frequencies. This paper proposes an interesting technique to enlarge the operational range to lower frequencies and to allow the use of inertial actuators. The approach is numerically tested and experimentally validated on a test rig.
Excited state intramolecular proton transfer mechanism of o-hydroxynaphthyl phenanthroimidazole

By utilizing the density functional theory (DFT) and the time-dependent density functional theory (TDDFT), the excited state intramolecular proton transfer (ESIPT) mechanism of o-hydroxynaphthyl phenanthroimidazole (HNPI) is studied in detail. Upon photo is excited, the intramolecular hydrogen bond is obviously enhanced in the S1 state, which thus promotes the ESIPT process. Hydrogen bond is shown to be strengthened via comparing the molecular structures and the infrared vibration spectra of the S0 and S1 states. Through analyzing the frontier molecular orbitals, we can conclude that the excitation is a type of the intramolecular charge transfer excitation, which also indicates the trend of proton transfer in S1 state. The vertical excitation based on TDDFT calculation can effectively repeat the absorption and fluorescence spectra of the experiment. However, the fluorescence spectrum of normal structure, which is similar to the spectrum of isomer structure is not detected in the experiment. It can be concluded that the fluorescence measured in the experiment is attributed to both structures. In addition, by analyzing the potential energy curves (PECs) calculated by the B3LYP functional method, it can be derived that since the molecule to cross the potential barrier in the S1 state is smaller than in the S0 state and the reverse proton transfer process in the S1 state is more difficult than in the S0 state, the ESIPT occurs in the S1 state.
First astrometric reduction of Cassini Imaging Science Subsystem images using an automatic procedure: application to Enceladus images 2013–2017

We provide new astrometric observations of Enceladus from images taken using the Cassini Imaging Science Subsystem (ISS) Narrow-Angle Camera. Astrometric reduction was performed using a new fully automatic camera repointing technique built within the C AVIAR software package. The new automatic procedure is based on the k-d tree technique and has been developed as an alternative to the manual technique currently available in C AVIAR . We describe the new procedure and demonstrate its effectiveness compared with manual processing. Repointing corrections were computed using reference stars from the UCAC4 and Gaia DR1 star catalogues. We compare the observed-minus-computed (O − C) residuals of Ence-ladus based on UCAC4 with those based on Gaia DR1, relative to the JPL SAT375 ephemeris and the IMCCE NOE ephemeris, respectively. We reduced all available Cassini ISS images of Enceladus during the period 2013–2017, producing a total of 1109 Cassini -centred astrometric observations. These are provided in right ascension ( α ) and declination ( δ ) in the International Celestial Reference Frame (ICRF). Estimated mean O − C residuals relative to JPL’s SAT375 ephemeris were 0.7 km in α × cos( δ ) and 1.8 km in δ , with standard deviations of 2.4 and 3.2 km, respectively. No improvement in the precision of the observations was obtained when using the GAIA DR1 star catalogue compared with UCAC4.
Systematic examination of the incorporation of class relationships via multilabel, multiclass, hierarchical classification

Difficulties in multiclass classification problems often arise as a result of the transformation to a series of one‐class problems, where each class is determined without respect to the results from the other classes. Existing relationships between the classes themselves, rather than the individual samples in each class, are ignored, and the information is not incorporated into the classification model. Alternatively, classifying multiclass samples via a multilabel, hierarchical classification method can incorporate this information through alternative means of sample selection and comparison. In this paper, the possible methods are systematically examined and the results ranked in terms of two metrics, accuracy and F1 measure. This method constructed several models that outperformed models constructed by traditional classification methods, showing that incorporating the additional information available in class relationships offers an advantage in performance over traditional “flat” classification.
Lyapunov Arguments in Optimization

Author(s): Wilson, Ashia | Advisor(s): Jordan, Michael I; Recht, Benjamin | Abstract: Optimization is among the richest modeling languages in science. In statistics and machine learning, for instance, inference is typically posed as an optimization problem. While there are many algorithms designed to solve optimization problems, and a seemingly greater number of convergence proofs, essentially all proofs follow a classical approach from dynamical systems theory: they present a Lyapunov function and show it decreases. The primary goal of this thesis is to demonstrate that making the Lyapunov argument explicit greatly simplifies, clarifies, and to a certain extent, unifies, convergence theory for optimization.The central contributions of this thesis are the following results: we• present several variational principles whereby we obtain continuous-time dynamical systems useful for optimization;• introduce Lyapunov functions for both the continuous-time dynamical systems and discrete-time algorithms and demonstrate how to move between these Lyapunov functions;• utilize the Lyapunov framework as well as numerical analysis and integration techniques to obtain upper bounds for several novel discrete-time methods for optimization, a few of which have matching lower bounds.
Investigation of PBUC problem with RES and EV in restructured environment

This research proposes a novel solution for the optimal day-ahead scheduling problem in the GAMS environment using the BARON approach. The challenge is extended to include Renewable Energy Sources (RESs) and Electric Vehicles (EVs), making it more complex and practical. EVs serve as loads, energy suppliers, and storage during RESs’ uncertainties. The framework improves cost savings, quality, reliability, and stability of the power supply system by modeling solar, wind, and EV power in the scheduling problem. The solution is tested on a 10 -unit thermal system considering RESs and EVs under deterministic and stochastic environments. Stochastic scenarios are generated using Monte Carlo simulation, and the simultaneous scenario reduction approach enhances results. The BARON solver outperforms other solvers, achieving profits of $205,321 with wind, solar, and EVs, and $187,297 when considering uncertainty, resulting in a reduction of $18,024.
Study of the Drug-related Adverse Events with the Help of Electronic Health Records and Natural Language Processing

—Surveillance of pharmacovigilance, also known as drug safety surveillance, involves the monitoring and evaluation of drug-related adverse events or side effects to ensure the safe and effective use of medications. Pharmacovigilance is an essential component of healthcare systems worldwide and plays a crucial role in identifying and managing drug safety concerns. Natural language processing (NLP) can play a crucial role in surveillance activities within pharmacovigilance by analyzing and extracting information from various sources, such as clinical trial reports, electronic health records, social media, and scientific literature. It is important to note that while NLP can be a powerful tool in pharmacovigilance surveillance, it should always be used in conjunction with human expertise. NLP algorithms can assist in the identification and extraction of relevant information, but the final assessment and decision-making should involve the knowledge and judgment of trained pharmacovigilance professionals. In this paper, we intend to train and test our models using the dataset from the Medication, Indication, and Adverse Drug Events challenge. This dataset will include patient notes as well as entity categories such as Medication, Indication, and ADE, as well as various sorts of relationships between these entities. Because ADE-related information extraction is a two-stage process, the outcome of the second step (i.e., relation extraction) will be utilized to compare all models. The analysis of drug-related adverse events using electronic health records and automated approaches can considerably increase the effectiveness of ADE-related information extraction, although this depends on the methodology, data, and other aspects. Our findings can help with ADE detection and NLP research
Investigation of the Influence of Social Trust, Network, and Shared Goals on Sharing Knowledge Attitudes among Saudi Academics in Higher Education Institutions

For over ten years, research on knowledge sharing has been a subject of focus, with the understanding that it can contribute to an organization's success. However, in Saudi Arabia, relatively little research has been conducted on this topic compared to other countries. The present study explores the impact of social trust, networks, and shared goals on the perception of academics in high-learning educational institutions toward knowledge sharing in Saudi Arabia. The study employs social trust, networks, and shared goals as independent variables. It examines their influence on attitudes toward knowledge sharing while considering control variables such as gender and experience. Data was assembled through a survey method using purposive sampling, and 88 usable responses from HEIs were analyzed. The study's findings proposed a positive relationship between social trust, social network, shared goals, and academic attitudes toward knowledge sharing. These results can benefit Saudi HEIs in developing policies to become knowledge-based institutions. The researcher recommends building a supportive and inspiring work environment for academics in order to exchange their knowledge with each other. The researcher addresses the limitations of the current study and provides a valuable suggestion for future research; conducting a comparative study that focuses on knowledge-sharing practices is recommended. This study does not explore mediating variables, so considering incentives as a mediating factor may result in valuable results for both public and private higher education institutions and business organizations within the context of Saudi.
Evaluation of Phytochemicals, Antioxidant and Anti-inflammatory properties of leaves of Ocimum basilicum L.

In India, a wide variety of medicinal plants are reported and utilized by people for the treatment of various diseases for a long time. The present study deals with quantitative analysis of phytochemicals like total phenols, tannins, and flavonoids as well as in-vitro antioxidant and anti-inflammatory activity of ethanolic extract of Ocimum basilicum L. The values of total phenols, tannins, and flavonoids were found to be 5.02±0.06 µg Gallic acid equivalent/mg, 7.80±0.05 µg Gallic acid equivalent/mg, and 6.00±0.06 µg quercetin equivalent/mg alcoholic extract respectively. The antioxidant activity was measured by DPPH (2, 2-diphenyl-1-picryl-hydrazyl-hydrate) assay. The highest antioxidant activity of plant extract was observed at 60 µg/ml and maximum inhibition was recorded at 55.12%. The IC50 value of plant extract was found to be 24.81 µg/ml. In-vitro anti-inflammatory activity was measured by the human red blood cell (HRBC) membrane stabilization method. The hypo tonicity-induced HRBC were exposed to different concentrations of ethanolic extract of Ocimum basilicum L. and HRBC membrane lysis and membrane stabilization percentages were calculated against diclofenac sodium. The ethanolic extract exhibited significant HRBC membrane stabilization compared to diclofenac sodium; 98±0.57% membrane stabilization was observed at a dose of 1000 µg/ml.
Avaliação de Funcionalidades e Desenvolvimento de Protótipo de Aplicativo para Tratamento de Depressão

A depressão é um tópico de relevância na psicologia e com a evolução tecnológica é possível adotar novos métodos de tratamento, como o uso de aplicativos, que abrem oportunidades de melhoria na qualidade de vida e de saúde das pessoas. Então, os desenvolvedores devem prezar pelo auxílio de profissionais da área da saúde, para que as métricas adotadas sejam realmente eficazes e consistentes. Este trabalho apresenta uma pesquisa de funcionalidades a partir de seis aplicativos: Cíngulo, MoodTools, Como Vencer a Depressão, Flow Depression, Minha Cura e Conversa Comigo. Após a avaliação das funcionalidades por 14 psicólogos foi possível avaliar as funcionalidades e desenvolver uma proposta inicial de construção de aplicativo.
In‐Home Monitoring Using Wireless on the Walls for Future HealthCare: Real‐World Demonstration

Since the last decade radio frequency (RF) sensing has emerged as an alternative in‐home monitoring and tracking technology because of its inherent device‐free and privacy‐preserved features over camera and wearable technologies. In this work, contrary to conventional radar‐based sensing and WiFi‐based setups which require line‐of‐sight (LoS) to process and collect the RF signals for monitoring, it is shown for the first time in literature the potential of using RF sensing for vitals, that is, heartbeat detection in the non‐line‐of‐sight (NLoS) using an in‐house‐developed reconfigurable intelligent surface (RIS), that is, wireless on the walls. The developed RIS is the world's first prototype which consists of “4096 elements”. The unit cell elements are individually controlled via PIN diodes, 1‐bit, operating at 3.75 GHz specified for the fifth‐generation (5G) network. Near‐field beam steering is demonstrated, with a switching speed of 15 ms. For the first time in the literature its is demonstrated that RIS can assist in the detection of microactivities including the human heartbeat in NLoS indoor complex environment, a limitation with the existing RF sensing technologies to date. In addition, it is experimentally verified that the RIS can potentially reduce the e‐field magnitude at the user's by regulating the gain at the user terminal.
Linked Th17 and Calgranulin Responses in Maternal-cord Blood Dyads of Preterm Gestations with Histologic Chorioamnionitis

Introduction: Maternal–fetal immune crosstalk mechanisms are increasingly identified in the pathogenesis of gestational disorders, including histologic chorioamnionitis (HCA). Although an inflammatory Th17 immune phenotype has been described in preterm neonates with HCA, the associated maternal Th17 response is relatively unknown. To refine our understanding of Th17 biology in this context, we examined Th17 responses in maternal-cord blood dyads of preterm gestations. Materials and methods: Paired maternal and cord blood (CB) samples were prospectively collected from preterm gestations (23–34 weeks) with HCA or controls. Th17-linked cell frequencies and plasma calgranulin (S100A8, S100A12) levels were determined by flow cytometry and enzyme-linked immunoassay, respectively. Results: Analyses of 47 maternal-cord blood pairs showed striking parallel increases in Th17 cell frequencies as well as plasma calgranulin levels in the presence of fetal inflammation. Cord blood S100A12 levels were directly correlated with Th17 cell frequencies. In CB cultures, rh-S100A12 promoted in vitro propagation of Th17-type CD4+ cells. Conclusions: Maternal and CB Th17-linked responses are dually amplified in gestations with HCA, supporting a biological role for maternal–fetal interactions in this disorder. In addition to advancing current knowledge of neonatal Th17 mechanisms, these data shed new light on their association with maternal inflammation.