Miracle-dz/UniFAR-FTUs huggingface dataset:
Green Approach for Wastewater Treatment—Degradation and Mineralization of Aqueous Organic Pollutants by Discharge Plasma

A dielectric barrier discharge reactor was designed and tested for the degradation of a model aqueous pollutant crystal violet (CV). The specific advantage of the present configuration is the effective utilization of reactive species generated in the discharge plasma. The reactive species formed in the discharge, particularly the OH• radicals, may cause strong oxidizing effects in the degradation of CV. Mineralization of the dye was confirmed by TOC analyzer and infrared gas analyzer. It was observed that both degradation efficiency and TOC removal increased with increasing the input energy; however, the energy yield decreased. The highest energy yield achieved was 86.3 (g/kWh). Formation of hydrogen peroxide was quantified and addition of Fe2+ increased the performance of the reactor. The dye degradation followed first-order kinetics.
A Spatiotemporal Change Detection Method for Monitoring Pine Wilt Disease in a Complex Landscape Using High-Resolution Remote Sensing Imagery

Using high-resolution remote sensing data to identify infected trees is an important method for controlling pine wilt disease (PWD). Currently, single-date image classification methods are widely used for PWD detection in pure stands of pine. However, they often yield false detections caused by deciduous trees, brown herbaceous, and sparsely vegetated regions in complex landscapes, resulting in low user accuracies. Due to the limitations on the bands of the high-resolution imagery, it is difficult to distinguish wilted pine trees from such easily confused objects when only using the optical spectral characteristics. This paper proposes a spatiotemporal change detection method to reduce false detections in tree-scale PWD monitoring under a complex landscape. The framework consisted of three parts, which represent the capture of spectral, temporal, and spatial features: (1) the Normalized Green–Red Difference Index (NGRDI) was calculated as a descriptor of canopy greenness; (2) two NGRDI images with similar dates in adjacent years were contrasted to obtain a bitemporal change index that represents the temporal behaviors of typical cover types; and (3) a spatial enhancement was performed on the change index using a convolution kernel matching the spatial patterns of PWD. Finally, a set of criteria based on the above features were established to extract the wilted pine trees. The results showed that the proposed method effectively distinguishes wilted pine trees from other easily confused objects. Compared with single-date image classification, the proposed method significantly improved user’s accuracy (81.2% vs. 67.7%) while maintaining the same level of producer’s accuracy (84.7% vs. 82.6%).
UAVs for Vegetation Monitoring: Overview and Recent Scientific Contributions

This paper reviewed a set of twenty-one original and innovative papers included in a special issue on UAVs for vegetation monitoring, which proposed new methods and techniques applied to diverse agricultural and forestry scenarios. Three general categories were considered: (1) sensors and vegetation indices used, (2) technological goals pursued, and (3) agroforestry applications. Some investigations focused on issues related to UAV flight operations, spatial resolution requirements, and computation and data analytics, while others studied the ability of UAVs for characterizing relevant vegetation features (mainly canopy cover and crop height) or for detecting different plant/crop stressors, such as nutrient content/deficiencies, water needs, weeds, and diseases. The general goal was proposing UAV-based technological solutions for a better use of agricultural and forestry resources and more efficient production with relevant economic and environmental benefits.
Duality-Derived Models of High-Speed Electromagnetic Valves

The article analyzes a high-speed solenoid valve (HSV) whose core and moving armature are massive elements characterized by strong eddy currents, hysteresis, and saturation. The feedback control employed in obtaining a predetermined nonsinusoidal current in the core coil necessitates the use of a high-frequency pulsewidth modulation (PWM)-like voltage with parameters varying in a manner unknown in advance during the uninterrupted transient. In view of the known difficulties in using finite-element solvers, physical Cauer circuits are found to be a reliable engineering alternative. The use of the duality transformation is proposed to obtain a pure electric model of the core and armature. As a preliminary result, it is found that a threefold reduction in eddy-current loss is achieved by using the slotted core. The results obtained with the model are in a reasonable agreement with the experimental magnetizing current and the armature movement during successive valve operations.
Extrapolating Satellite-Based Flood Masks by One-Class Classification - A Test Case in Houston

Flood masks are among the most common remote sensing products, used for rapid crisis information and as input for hydraulic and impact models. Despite the high relevance of such products, vegetated and urban areas are still unreliably mapped and are sometimes even excluded from analysis. The information content of synthetic aperture radar (SAR) images is limited in these areas due to the side-looking imaging geometry of radar sensors and complex interactions of the microwave signal with trees and urban structures. Classification from SAR data can only be optimized to reduce false positives, but cannot avoid false negatives in areas that are essentially unobservable to the sensor, for example, due to radar shadows, layover, speckle and other effects. We therefore propose to treat satellite-based flood masks as intermediate products with true positives, and unlabeled cells instead of negatives. This corresponds to the input of a positive-unlabeled (PU) learning one-class classifier (OCC). Assuming that flood extent is at least partially explainable by topography, we present a novel procedure to estimate the true extent of the flood, given the initial mask, by using the satellite-based products as input to a PU OCC algorithm learned on topographic features. Additional rainfall data and distance to buildings had only minor effect on the models in our experiments. All three of the tested initial flood masks were considerably improved by the presented procedure, with obtainable increases in the overall κ score ranging from 0.2 for a high quality initial mask to 0.7 in the best case for a standard emergency response product. An assessment of κ for vegetated and urban areas separately shows that the performance in urban areas is still better when learning from a high quality initial mask.
Sensitivity Analysis of Sentinel-1 Backscatter to Oil Palm Plantations at Pluriannual Scale: A Case Study in Gabon, Africa

The present paper focuses on a sensitivity analysis of Sentinel-1 backscattering signatures from oil palm canopies cultivated in Gabon, Africa. We employed one Sentinel-1 image per year during the 2015–2021 period creating two separated time series for both the wet and dry seasons. The first images were almost simultaneously acquired to the initial growth stage of oil palm plants. The VH and VV backscattering signatures were analysed in terms of their corresponding statistics for each date and compared to the ones corresponding to tropical forests. The times series for the wet season showed that, in a time interval of 2–3 years after oil palm plantation, the VV/VH ratio in oil palm parcels increases above the one for forests. Backscattering and VV/VH ratio time series for the dry season exhibit similar patterns as for the wet season but with a more stable behaviour. The separability of oil palm and forest classes was also quantitatively addressed by means of the Jeffries–Matusita distance, which seems to point to the C-band VV/VH ratio as a potential candidate for discrimination between oil palms and natural forests, although further analysis must still be carried out. In addition, issues related to the effect of the number of samples in this particular scenario were also analysed. Overall, the outcomes presented here can contribute to the understanding of the radar signatures from this scenario and to potentially improve the accuracy of mapping techniques for this type of ecosystems by using remote sensing. Nevertheless, further research is still to be done as no classification method was performed due to the lack of the required geocoded reference map. In particular, a statistical assessment of the radar signatures should be carried out to statistically characterise the observed trends.
Application of Machine-Learning-Based Fusion Model in Visibility Forecast: A Case Study of Shanghai, China

A visibility forecast model called a boosting-based fusion model (BFM) was established in this study. The model uses a fusion machine learning model based on multisource data, including air pollutants, meteorological observations, moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) data, and an operational regional atmospheric environmental modeling System for eastern China (RAEMS) outputs. Extreme gradient boosting (XGBoost), a light gradient boosting machine (LightGBM), and a numerical prediction method, i.e., RAEMS were fused to establish this prediction model. Three sets of prediction models, that is, BFM, LightGBM based on multisource data (LGBM), and RAEMS, were used to conduct visibility prediction tasks. The training set was from 1 January 2015 to 31 December 2018 and used several data pre-processing methods, including a synthetic minority over-sampling technique (SMOTE) data resampling, a loss function adjustment, and a 10-fold cross verification. Moreover, apart from the basic features (variables), more spatial and temporal gradient features were considered. The testing set was from 1 January to 31 December 2019 and was adopted to validate the feasibility of the BFM, LGBM, and RAEMS. Statistical indicators confirmed that the machine learning methods improved the RAEMS forecast significantly and consistently. The root mean square error and correlation coefficient of BFM for the next 24/48 h were 5.01/5.47 km and 0.80/0.77, respectively, which were much higher than those of RAEMS. The statistics and binary score analysis for different areas in Shanghai also proved the reliability and accuracy of using BFM, particularly in low-visibility forecasting. Overall, BFM is a suitable tool for predicting the visibility. It provides a more accurate visibility forecast for the next 24 and 48 h in Shanghai than LGBM and RAEMS. The results of this study provide support for real-time operational visibility forecasts.
SIMULATION OF FIELD EMISSION FROM CARBON NANOTUBES USING TIME-DEPENDENT DENSITY FUNCTIONAL THEORY AND THE EFFECT OF NITROGEN AND BORON DOPING

We investigated the mechanism of electron field emission in prestine short carbon nanotubes using ab-initio computation in isolated and periodic simulation cells. We computed the evolution of the wave functions using Time-Dependent Density Functional Theory, where we have utilized the Crank-Nicholson propagator. We found that in prestine carbon nanotubes, emitted charge tends emerge mostly from electrons that are concentrated at the nanotube tip region, unlike metallic tips. The charge beam concentrates into specific channel structures as the wave function approaches the anode. Nitrogen doping of carbon nanotubes improves emission, in line with experimental findings, and the nitrogen dopant closer to the nanotube tip produces optimal emission performance. However, the nitrogen dopant causes dispersion of the charge cloud, which might lead to wasting of the emission current. Boron doping either impedes field emission in nanotubes or produces minimal effect.
Value of PET imaging for radiation therapy

Abstract This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.
Anti-Inflammatory Activity of Cinnamon Bark Oil (Cinnamomum burmannii (Nees & T. Nees) Blume from Lombok Timur Indonesia

Inflammation is the response of the human or animal body and the complex interactions between immune cells and mediator molecules1. This is a common problem in society as a result of lifestyle and health problems. Inflammation can play an important role in the pathogenesis of various types of acute and chronic diseases such as cardiovascular disease, neurodegenerative diseases, obesity, and type 2 diabetes mellitus. Pharmacotherapy for inflammatory conditions is still dominated by the use of non-steroidal anti-inflammatory drugs (NSAIDs). NSAIDs comprise a group of non-selective and selective NSAIDs. Non-selective NSAIDs work to inhibit the cyclooxygenase enzymes (COX-1 and COX2) which decrease prostaglandin production. The inhibitor group works by inhibiting the COX-2 enzyme. NSAIDs are commonly used to relieve pain and inflammation caused by various types of arthritis and musculoskeletal disorders. Although effective in reducing pain and inflammation, NSAIDs cause side effects including serious gastrointestinal toxicities such as gastric ulcers and bleeding2. Some NSAIDs that work to inhibit COX-2 induce an increase in blood pressure, increasing the risk of blockages that lead to heart failure, clotting, and heart muscle death3.
Dynamics in Interacting Scalar-Torsion Cosmology

In a spatially flat Friedmann–Lemaître–Robertson–Walker background space, we consider a scalar-torsion gravitational model which has similar properties to the dilaton theory. This teleparallel model is invariant under a discrete transformation similar to the Gasperini–Veneziano duality transformation. Moreover, in the gravitational action integral, we introduce the Lagrangian function of a pressureless fluid source which is coupled to the teleparallel dilaton field. This specific gravitational theory with interaction in the dark sector of the universe was investigated by using methods of the dynamical system analysis. We calculate that the theory provides various areas of special interest for the evolution of the cosmological history. Inflationary scaling solutions and the de Sitter universe are recovered. Furthermore, we calculate that there exist an attractor which provides a stable solution where the two fluid components, the scalar field and the pressureless matter, contribute in the cosmological fluid. This solution is of special interest because it can describe the present epoch. Finally, the qualitative evolution of the cosmographic parameters is discussed.
Growth efficiency and profitability indices of African catfish (Clarias gariepinus) fingerlings fed with different levels of Adansonia digitata (Baobab) seed meal

The effects of diet with different inclusion levels of baobab seed meal inclusions on the growth and gross margin analysis of Clarias gaiepinus fingerlings was evaluated under a controlled laboratory condition. Five inclusion levels of Baobab Seed Meal (BSM) to replace soya bean meal were studied at 0, 5, 10, 15 and 20% dietary protein. The experimental diets were uniform by targeting 40% crude protein with energy level of 20 MJ/kg. Fingerlings of C. gariepinus with an average weight (g) of 2.91 ± 0.16 g were reared for 90 days in plastic aquaria. Feed intake, weight gain, feed efficiency ratio (FER), protein efficiency ratio (PER) and survival rates (SR %) were evaluated, using standard formula. Significantly higher growth (p<0.05) was obtained from the fish fed with Diet Two (5% BSM) and Diet Three (10% BSM) than the fish fed with control diet. The best utilized diet for C. gariepinus was Diet Two in relation to weight gained and total fish production. Therefore, Baobab seed meal can serve as a worthy unconventional feed ingredient in the diet of C. gariepinus at 10% level of inclusion for maximum profit, although 5% BSM inclusion recorded the best growth performance. Key words: Growth parameter, Clarias gariepinus, Baobab seed meal, fingerlings.
Nonnative, Noninvasive Woody Species Can Enhance Urban Landscape Biodiversity

Increasingly, homeowner associations and municipalities are requiring a certain percentage of native trees and shrubs as part of any new landscape installation. These native species mandates make numerous claims as to the superiority of native plants over introduced species, including their ability to enhance ecosystem biodiversity. In contrast, nonnative trees and shrubs are labeled as harmful to biodiversity, primarily because they are improperly grouped with known invasive species. This review summarizes the current published science regarding the effects of native and nonnative woody species on urban landscape stability as measured by biodiversity of associated plants, birds, insects, reptiles, and mammals. The preponderance of studies demonstrate that parameters other than species nativity have the greatest influence on biodiversity of these groups. Rather than limiting tree and shrub selection lists to a narrow palette of native species, a more practical, science-based approach to enhancing urban landscape biodiversity is suggested.
The MENA Countries An Empirical Investigation by Using Panel data model

This paper will investigate the impact of institution on economic growth rates in MENA nations, using panel data model over the period 1995-2012. Within the framework of the neoclassical growth model, this study integrates a broad set of institutional variables such. Security of property rights, governance, political freedom and size of government are the indicators used in the study, facilitating identification of the most important institutions that account for the observed variations in economic growth rates among nations. We find that, the sign and significance of all of the variables are qualitatively similar to the results obtained by MRW (1992). We also find the human capital is highly significant at 99% with initial income and Investment Share in MENA countries. The Results indicate that the dummy variable for oil exporters is positive and significant, indicating that other things being equal, oil exporters would be expected to have higher economic growth rates in MENA Countries. Basic OLS results, as well as a variety of additional evidence, suggest that (a) security of property rights, is the most significant institutions that explain the variations in economic growth rates, (b) The significant and negative sign on the government consumption, indicating that smaller governments are "better" in MENA countries.
Psychosocial Determinants of Postpartum Depression and Maternal Well-Being among Postnatal Women

Postpartum depression, a major depressive disorder, predisposes postnatal mothers to physical, social, and psychological malfunctioning. Purpose: The study aimed to identify the psychosocial determinants of postpartum depression and maternal well-being among mothers in the Accra metropolis. Materials and Method: A sample of 205 postnatal women between the ages of 15 39 years and are 4 - 12 weeks old postpartum was drawn from 37 Military Hospital, Accra. Employing a sequential explanatory approach, participants were administered the Depression, Anxiety and Stress Scale (DASS-21), Multidimensional Scale of Perceived Social Support (MSPSS), Marital Adjustment Test (MAT), and the Edinburgh Postnatal Depression Scale (EPDS). Findings: The study revealed that 14.1% of postnatal women in the Accra metro-polis are at risk of developing PPD. A significant model emerged, [R2 = 0.488, F (7, 197) = 26.86, ρ < 0.05] and this was predicted by anxiety, stress and marital dissatisfaction among couples. On the other hand, results from Interpretive Phenomenological Analysis (IPA) of participants’ in- depth information revealed inadequate social support and dissatisfaction in marriage account for mothers’ at-risk behaviour of developing PPD; which impacts on maternal well-being. Conclusion: It is concluded that PPD is patent among postnatal women and psychosocial variables contribute a significant role in their experience of mental health problems following childbirth. This, in effect, requires attention from health professionals for holistic healthcare. The implications of these outcomes are discussed concerning mental healthcare delivery, the general public, and stakeholders in the health sector.
CMAR_A_317809 5101..5111

1Musculoskeletal Tumor Center, Peking University, People’s Hospital, Beijing, 100044, People’s Republic of China; 2Department of Medicine, OrigiMed, Shanghai, 201114, People’s Republic of China Objective: The limited understanding of correlation between genomic features and biological behaviors has impeded the therapeutic breakthrough in osteosarcoma (OS). This study aimed to reveal the correlation of mutational and evolutionary traits with clinical outcomes. Methods: We applied a case-based targeted and whole exome sequencing of eleven matched primary, recurrent and metastatic samples from three OS patients characterized by different clinical behaviors in local recurrence or systematic progression pattern. Results: Extensive OS-associated driver genes were detected including TP53, RB1, NF1, PTEN, SPEN, CDKN2A. Oncogenic signaling pathways including cell cycle, TP53, MYC, Notch, WNT, RTK-RAS and PI3K were determined. MYC amplification was observed in the patient with shortest disease-free interval. Linear, branched or mixed evolutionary models were constructed in the three OS cases. A branched evolution with limited root mutation was detected in patient with shorter survival interval. ADAM17 mutation and HEY1 amplification were identified in OS happening dedifferentiation. Signatures 21 associated with microsatellite instability (MSI) was identified in OS patient with extra-pulmonary metastases. Conclusion: OS was characterized by complex genomic alterations. MYC aberration, limited root mutations, and a branched evolutionary model were observed in OS patient with relatively aggressive course. Extra-pulmonary metastases of OS might attribute to distinct mutational process pertaining to MSI. Further research in a larger number of people is needed to confirm these findings.
Physicochemical and sensory evaluation of greek style yoghurt with bovine colostrum

Colostrum is the first secretion of the mammary gland from 2 to 4 days after calving and differs from milk because of the greater amounts of fat, protein, minerals and vitamins, in addition to a high concentration of immunoglobulins that provide passive immunity to the newborn. This specific composition of colostrum may reveal particular biological activities. Antioxidant activity is among the fundamental biological activities important for life (Oussaief et al., 2020).
Effects of Dinotefuran and Imidacloprid on Target and Non-target Arthropods on American Elm

Neonicotinoid insecticides are a relatively new class of compounds with excellent efficacy against a broad assemblage of key insect pests of woody plants. Unfortunately, the use of one neonicotinoid, imidacloprid, has been linked to secondary outbreaks of several species of spider mites on different trees and shrubs. Dinotefuran is another neonicotinoid insecticide now widely used by arborists to manage insects, including egregious borers like emerald ash borer. Researchers tested a hypothesis that applications of dinotefuran to American elms (Ulmus americana) elevated populations of a spider mite, Tetranychus schoenei, and rust mites in the family Diptilomiopidae, and found no indication that dinotefuran elevated densities of either mite. Applications of imidacloprid elevated densities of T. schoenei, but not Diptilomiopidae. Both neonicotinoids were highly efficacious in reducing abundances of European elm scale, Eriococcus spuria, and elm cockscomb gall aphid, Colopha ulmicola.