Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictors of Vaccine Acceptance, Confidence, and Hesitancy in General, and COVID-19 Vaccination Refusal in the Province of Quebec, Canada

Introduction A surge of COVID-19 variants is a major concern, and literatures that support developing an optimum level of herd immunity are meaningful. This study aimed to examine the factors associated with vaccine acceptance, confidence, and hesitancy in general, and COVID-19 vaccination refusal in the general population of Quebec, Canada. Methods A web-based cross-sectional survey was conducted in October and November 2020 among French-speaking participants above 18 years of age employing quota sampling technique. The questionnaire included socio-demographic and attitudinal variables towards vaccination. Logistic regression analyses were conducted to examine the association between independent and outcome variables. Results Of total 1599 participants, 88.9%, 87.5%, 78.5%, and 18.2%, respectively, indicated vaccine acceptance, high level of vaccine confidence, low level of vaccine hesitancy, and COVID-19 vaccination refusals. Participants having higher education, income, and fear of COVID-19 (FCV-19S) were more likely to get vaccinated, while smokers were less likely to get vaccinated. Similarly, age groups (40–59, and ≥60 years), higher education, income, permanent resident in Canada, country of parents from Canada, ever faced acute disease in the family, higher sense of coherence, and FCV-19S scores were predictors of high levels of vaccine confidence. Higher education, income, sense of coherence and FCV-19S scores, and higher health-related quality of life (CORE-6D) produced lower levels of vaccine hesitancy. Conversely, those acting as caretaker, other essential worker, smoker, and those with financial losses were more likely to have higher vaccine hesitancy. Additionally, ≥60 years of age, higher education and income, country of parents from Canada, higher scores of willingness to take risk and FCV-19S were less likely to have high level of COVID-19 vaccination refusal. Conclusion Over three quarters of the participants indicated positive attitudes toward vaccination. Some socio-demographic and health-related quality of life factors were associated with the outcome variables, and these should be sought while designing interventions to improve COVID-19 vaccination rates.
Optimization of Polyphenols’ Recovery from Purple Corn Cobs Assisted by Infrared Technology and Use of Extracted Anthocyanins as a Natural Colorant in Pickled Turnip

An ecofriendly extraction technology using infrared (IR) irradiation Ired-Irrad® was applied to purple corn cobs to enhance polyphenol recovery for the first time. The IR extraction efficiency was compared to that of the water bath (WB) method. Response surface methodology (RSM) using a central composite design was conducted to determine the effect of the experimental conditions (extraction time and treatment temperature) and their interactions on the total polyphenol and anthocyanin yields. Optimal extraction of total phenolic compounds (37 mg GAE/g DM) and total monomeric anthocyanins (14 mg C3G/g DM) were obtained at 63 °C for 77 min using IR as an extraction technique and water as a solvent. HPLC revealed that the recovery of peonidin 3-O-glucoside and cyanidin 3-O-glucoside was enhanced by 26% and 34%, respectively, when using IR. Finally, purple corn cobs’ spray-dried extract was proven to be an important natural colorant of pickled turnip. It offers great potential for use as a healthy alternative to the carcinogenic rhodamine B synthetic dye, which was banned.
Effects of Economic Policy Uncertainty on the Investment Behavior of Venture Capital Institutions: Evidence from China

Venture capital (VC) has played an important financial supplementary role in the development of high-tech enterprises. With the intensification of economic policy uncertainty, VC investment behavior has been affected to a certain extent. Under the framework of the impact of economic policy uncertainty (EPU) on general corporate investment behavior, this article examines the impact of EPU on the investment behavior of VC institutions from four aspects, namely, investment quantity, investment phase, investment industry, and investment region. The study finds that in China, EPU has a good news effect, and its intensification can boost the investment quantity of VC institutions and stimulate institutions to choose more specialized investment strategies in terms of investment phase, investment industry, and investment region. The impact of EPU on the investment behavior of VC institutions changes with the investment state of the institutions. The larger the investment quantity of the VC institutions, the greater the promotion effect. VC institutions with a higher degree of investment concentration will pay more attention to specialized investment strategies.
Chaos, Solitons and Fractals

Vegetation patterns in arid and semi-arid ecosystems as a self-organized response to resource scarcity is a well-documented issue. Their formation is often attributed to the symmetry-breaking type of instability. In this contribution, we focus on a regime far from any symmetry-breaking instability and consider a bistable regime involving uniformly vegetated covers and a bare state. We show that vegetation populations exhibit non-random two-phase structures where high biomass density regions are separated by sparsely covered areas or even bare soil. These structures are referred to as phase separation vegetation covers. We provide observations of this phenomenon in Gabon, Angola, Argentina, and Mexico. The inhomogeneities in environmental conditions are crucial to explain the origin of phase separation vegetation covers. We derive a simple equation from ecologically relevant models to explain various field observations. The bifurcation diagrams obtained from this model allow us to prove that inhomogeneity in the aridity parameter is a source of resilience for vegetation covers, avoiding collapsing towards a bare state. We characterize the natural observations and the equilibria from the model by using Fourier transform technique, spatial autocorrelation analysis, and size distribution of patches analysis.
Multidisciplinary Tumor Board in the Management of Patients with Colorectal Liver Metastases: A Single-Center Review of 847 Patients

Simple Summary A multispecialty discussion may represent a benefit for cancer patients in receiving the most updated pathway of cure. The aim of this study was to describe the activity of our multidisciplinary team (MDT) meeting on patients with colorectal liver metastases (CRLMs). Information about 847 consecutive CRLMs patients over an 11-year period was retrospectively collected. Their characteristics were analyzed, and the populations were compared based on received treatment. Abstract There is still debate over how reviewing oncological histories and addressing appropriate therapies in multidisciplinary team (MDT) discussions may affect patients’ overall survival (OS). The aim of this study was to describe MDT outcomes for a single cancer center’s patients affected by colorectal liver metastases (CRLMs). From 2010 to 2020, a total of 847 patients with CRLMs were discussed at our weekly MDT meeting. Patients’ characteristics and MDT decisions were analyzed in two groups: patients receiving systemic therapy (ST) versus patients receiving locoregional treatment (LRT). Propensity-score matching (PSM) was run to reduce the risk of selection bias. The median time from MDT indication to treatment was 27 (IQR 13–51) days. The median OS was 30 (95%CI = 27–34) months. After PSM, OS for patients undergoing LRT was 51 (95%CI = 36–64) months compared with 15 (95%CI = 13–20) months for ST patients (p < 0.0001). In this large retrospective study, the MDT discussions were useful in providing the patients with all available locoregional options.
Migration velocity analysis by the common image cube analysis (CICA)

Wavefield extrapolation methods are powerful for handling strong lateral velocity variations. However, they require an accurate velocity model to produce good images. There are many different migration velocity methods; but most of them make some simplifying assumptions about the subsurface, which reduces their ability to exploit the power of wavefield extrapolation methods. In this report, we reformulate some well-known migration velocity methods, like residual curvature analysis (RCA), depth focusing analysis (DFA), and common focus point (CFP) analysis into mathematical hypotheses. This reformulation puts them in the same context, so they are easier to understand and compare. Further, by restating the methods as mathematical hypotheses, they are easier to relate to other disciplines such as mathematics and physics. We also combine different aspects of the RCA, DFA, and CFP methods into a new migration velocity analysis approach called the common image cube analysis (CICA). Instead of simply taking the zero-lag crosscorrelation at each depth level, we store all the crosscorrelation lags. The result is a cube that contains more prestack information than the other methods. Slicing this cube at different lags forms a series of common image gathers (CIGs), where the conventional CIG can be obtained by slicing the cube at the zero lag. When the background velocity model used for migration is different from the true velocity model, the best-focused CIG is not at zero lag. Searching the cube at other lags for the most focused CIG gives the traveltime shift that is needed to approximately equalize the traveltimes of the upgoing and downgoing wavefields. From the updated traveltimes, the true velocity can be estimated. This approach is tested on models with constant velocity as well as velocity varying with depth, and the results show that it can be used to yield an accurate estimate of the true velocity when the wrong velocity model is used for migration.
Research on the Influencing Mechanism of Data Capital on Farmers’ Income

Based on the 2018 China Family Panel Studies data, this paper uses the OLS model, threshold regression model, and mediation effect model to analyze the influencing mechanism and degree of data capital on farmers’ income. The study found that data capital has a significant positive impact on farmers’ income, which can effectively promote farmers’ income. There is a nonlinear relationship between data capital and farmers’ income, and its marginal return increases with farmers’ human capital increasing. Social network plays a partial intermediary role between data capital and farmers’ income, that is, social network is an important channel for data capital to affect farmers’ income improvement. Based on the above conclusions, some reference suggestions are put forward.
Exploring effects of institutional, interpersonal, & individual communication on university students’ attitudes about diversity and institutional belongingness

University campuses are critical spaces where the importance of diversity, equity, and inclusion (DEI) in society are discussed, and debated. However, even as campus communities across the world grow more diverse, higher education institutions are facing an existential crisis—high dropout rates, low enroll-ments, growing disenchantment with education, and issues of otherization, sexism, and racism on campus. It has never been more necessary for administrators, faculty, staff and all stakeholders to understand the role of effective institutional, intergroup, and individual communication in increasing students’ uni versity belongingness, and positively affecting their attitudes towards ‘others. ’ Using the lens of systems theory and intergroup contact theory, this study analyzes how institutional, interpersonal, and individual level factors affect college students’ attitudes about diversity, and their university belongingness. An online survey of 432 students from a midsized public university in the U.S. indicated that specific inter personal communication (e.g., interactions with diverse faculty and peers), as well as institutional-level factors were positively correlated with student attitudes towards diversity. Results also indicated that microaggressions were a significant predictor of belongingness as were institution-level communication where students felt they had university support or when they felt their voices were heard. Other findings indicated that students of color felt less welcome on campus and reported lower university support than their Caucasian peers. Results highlighted both areas of hope, as well as key challenges for higher edu cation administrators. Implications, including recommendations for student success, greater intercultural collaboration, and creating a more inclusive campus community, are discussed. Some key implications include the need to recruit more international and culturally diverse staff; offering DEI courses, regular DEI training of staff, and actively promoting campus activities that encourage greater intergroup contact.
Lightning on Venus: Orbiter Detection of Whistler Signals (invited).

Recently Taylor et al. (1979a) presented preliminary evidence for lightning on Venus, based on Pioneer Venus orbiter detection of whistler mode signals as the spacecraft first traversed the nightside ionosphere near periapsis. The initial periapsis eclipse season for the orbiter has now been completed, and the plasma wave instrument (OEFD) obtained low-altitude nightside data for about 100 orbits. We present here an analysis of the impulsive whistler mode signals measured during these orbits, and we discuss the connection with atmospheric lightning. It is shown that the signals are detected in the 100-Hz channel when the local magnetic field is sufficiently strong and steady and when the field is oriented to point down below the ionosphere. These facts strongly support the previous lightning interpretation.
Grazing Cattle, Sheep, and Goats Are Important Parts of a Sustainable Agricultural Future

Simple Summary Increasing attacks on animal agriculture have forced many people to question the use of animals for food. Grazing livestock are part of a sustainable agricultural future. Vast amounts of land all around the world can only be used for grazing. It is either too arid or the terrain is too rough for growing crops. Rotating cattle, sheep, or other livestock between different pastures can improve both soil health and plant biodiversity. This is a sustainable use of land that cannot be cropped. On cropland, the rotation of conventional crops, such as corn or soybeans, with livestock grazing on a forage crop can improve both soil health and reduce the need for artificial fertilizer. Successful grazing programs must be adapted to local conditions. When grazing is performed correctly, it will improve the land. Abstract Many people believe that animal agriculture should be phased out and replaced with vegetarian substitutes. The livestock industry has also been attacked because it uses vast amounts of land. People forget that grazing cattle or sheep can be raised on land that is either too arid or too rough for raising crops. At least 20% of the habitable land on Earth is not suitable for crops. Rotational grazing systems can be used to improve both soil health and vegetation diversity on arid land. Grazing livestock are also being successfully used to graze cover crops on prime farmland. Soil health is improved when grazing on a cover crop is rotated with conventional cash crops, such as corn or soybeans. It also reduces the need for buying fertilizer. Grazing animals, such as cattle, sheep, goats, or bison, should be used as part of a sustainable system that will improve the land, help sequester carbon, and reduce animal welfare issues.
Comparisons between Model Forecast and Observed Boundary Layer Profiles and Related Comments on Cloud Prediction

Abstract In this study comparisons are made between Met Office mesoscale model boundary layer profiles, and radiosonde data collected in the central United Kingdom during three intensive boundary layer cloud experiments. Significant differences between forecast and observed profiles were found. An assessment of whether these differences are dominated by sonde random error or model error is performed. Results suggest that sonde random errors are insignificant for stratocumulus fields, but not for cumulus ones. Results show that model fields do not represent the fine vertical structure seen in the observations. The impact of this result for cloud prediction is discussed, and an estimate for the vertical resolution required to adequately parameterize the cloud field is provided.
A systematic review of grid-connected photovoltaic and photovoltaic/thermal systems: Benefits, challenges and mitigation

Solar energy is the powerhouse where all potential and classified renewable energies lug their sources. The energy transformation from the Sun to electricity requires an adequate control scheme to maximise the generated power and enhance the system efficiency. Besides, more than half of solar irradiation on conventional Photovoltaic (PV) panels is lost. The PV thermal (PV/T) modules have been introduced to convert the lost irradiation to heat. Thus, a systematic review of system components, development, and strategies for grid-connected solar PVs plants is presented. Two solar PVs, traditional PV and PV/T, are evaluated. Each grid-tied PV component is considered a subsystem to analyse the potential improvement of grid-connected PVs. This is from solar resources to grid-tied PV inverter techniques. An intensive assessment of the system improvements is presented to evaluate PV plants’ benefits, challenges, and potential solutions. The improvement trends for the novel generation of grid-connected PV systems consist of applying innovative approaches. It is also found that intelligent strategies optimally ensure the overall efficiency of grid-tied PVs using real-time control and measurement under innovative applications and technologies. These methods effectively assist in enhancing grid-tied diverse solar power approaches. Therefore, this paper would offer a significant foundation for advanced research into the subject of grid-tied PV and PV/T and their innovation and/or technology development.
Cinnamaldehyde-Based Self-Nanoemulsion (CA-SNEDDS) Accelerates Wound Healing and Exerts Antimicrobial, Antioxidant, and Anti-Inflammatory Effects in Rats’ Skin Burn Model

Cinnamaldehyde, the main phytoconstituent of the cinnamon oil, has been reported for its potential wound healing activity, associated to its antimicrobial and anti-inflammatory effects. In this study, we are reporting on the cinnamaldehyde-based self-nanoemulsifying drug delivery system (CA-SNEDDS), which was prepared and evaluated for its antimicrobial, antioxidant, anti-inflammatory, and wound healing potential using the rat third-degree skin injury model. The parameters, i.e., skin healing, proinflammatory, and oxidative/antioxidant markers, were evaluated after 3 weeks of treatment regimens with CA-SNEDDS. Twenty rats were divided randomly into negative control (untreated), SNEDDS control, silver sulfadiazine cream positive control (SS), and CA-SNEDDS groups. An aluminum cylinder (120 °C, 10-s duration) was used to induce 3rd-degree skin burns (1-inch square diameter each) on the rat’s dorsum. At the end of the experiment, skin biopsies were collected for biochemical analysis. The significantly reduced wound size in CA-SNEDDS compared to the negative group was observed. CA-SNEDDS-treated and SS-treated groups demonstrated significantly increased antioxidant biomarkers, i.e., superoxide dismutase (SOD) and catalase (CAT), and a significant reduction in the inflammatory marker, i.e., NAP-3, compared to the negative group. Compared to SNEDDS, CA-SNEDDS exhibited a substantial antimicrobial activity against all the tested organisms at the given dosage of 20 µL/disc. Among all the tested microorganisms, MRSA and S. typhimurium were the most susceptible bacteria, with an inhibition zone diameter (IZD) of 17.0 ± 0.3 mm and 19.0 ± 0.9 mm, respectively. CA-SNEDDS also exhibited strong antifungal activity against C. albicans and A. niger, with IZD of 35.0 ± 0.5 mm and 34.0 ± 0.5 mm, respectively. MIC and MBC of CA-SNEDDS for the tested bacteria ranged from 3.125 to 6.25 µL/mL and 6.25 to 12.5 µL/mL, respectively, while the MIC and MBC for C. albicans and A. niger were 1.56 µL/mL and 3.125 µL/mL, respectively. The MBIC and MBEC of CA-SNEDDS were also very significant for the tested bacteria and ranged from 6.25 to 12.5 µL/mL and 12.5 to 25.0 µL/mL, respectively, while the MBIC and MBEC for C. albicans and A. niger were 3.125 µL/mL and 6.25 µL/mL, respectively. Thus, the results indicated that CA-SNEDDS exhibited significant wound healing properties, which appeared to be attributed to the formulation’s antimicrobial, antioxidant, and anti-inflammatory effects.
Assessing Structural Complexity of Individual Scots Pine Trees by Comparing Terrestrial Laser Scanning and Photogrammetric Point Clouds

Structural complexity of trees is related to various ecological processes and ecosystem services. To support management for complexity, there is a need to assess the level of structural complexity objectively. The fractal-based box dimension (Db) provides a holistic measure of the structural complexity of individual trees. This study aimed to compare the structural complexity of Scots pine (Pinus sylvestris L.) trees assessed with Db that was generated with point cloud data from terrestrial laser scanning (TLS) and aerial imagery acquired with an unmanned aerial vehicle (UAV). UAV imagery was converted into point clouds with structure from motion (SfM) and dense matching techniques. TLS and UAV measured Db-values were found to differ from each other significantly (TLS: 1.51 ± 0.11, UAV: 1.59 ± 0.15). UAV measured Db-values were 5% higher, and the range was wider (TLS: 0.81–1.81, UAV: 0.23–1.88). The divergence between TLS and UAV measurements was found to be explained by the differences in the number and distribution of the points and the differences in the estimated tree heights and number of boxes in the Db-method. The average point density was 15 times higher with TLS than with UAV (TLS: 494,000, UAV 32,000 points/tree), and TLS received more points below the midpoint of tree heights (65% below, 35% above), while UAV did the opposite (22% below, 78% above). Compared to the field measurements, UAV underestimated tree heights more than TLS (TLS: 34 cm, UAV: 54 cm), resulting in more boxes of Db-method being needed (4–64%, depending on the box size). Forest structure (two thinning intensities, three thinning types, and a control group) significantly affected the variation of both TLS and UAV measured Db-values. Still, the divergence between the two approaches remained in all treatments. However, TLS and UAV measured Db-values were consistent, and the correlation between them was 75%.
Efficacy of Various Types of Berries Extract for the Synthesis of ZnO Nanocomposites and Exploring Their Antimicrobial Potential for Use in Herbal Medicines

Nanoscience has developed various greener approaches as an alternate method for the synthesis of nanoparticles and nanocomposites. The present study discusses the efficacy of berries extract for the synthesis of ZnO nanocomposites. Characterization of synthesized nanocomposite were done by SEM, UV/VIS spectrophotometry, Fourier transform infrared (FTIR) spectroscopy, and XRD techniques. The crystalline nature of the synthesized nanoparticles was verified by XRD pattern in the range of 10-80 nm. The UV absorption peak of Elaeagnus umbellata (ZnO-EU) nanocomposite at 340 nm, Rubus idaeus (ZnO-Ri) nanocomposite at 360 nm, and Rubus fruticosus (ZnO-Rf) nanocomposite at 360 nm was observed. The nanocomposites were analyzed for their antimicrobial activity and found to be effective against three phytopathogens. The antimicrobial activity of ZnO nanocomposites showed good results against Escherichia coli (341), Staphylococcus aureus (345B), and Pseudomonas aeruginosa (5994 NLF). This study presents a simple and inexpensive approach for synthesizing zinc oxide nanocomposites with effective antibacterial activity.