Miracle-dz/UniFAR-FTUs huggingface dataset:
RESPONSE OF GROWTH AND YIELD OF ONION PLANTS TO POTASSIUM FERTILIZER AND HUMIC ACID.

Two field experiments were carried out during the two successive seasons of 2001/2002 and 2002/2003 at the Experimental Station of National Research Centre at Shalkan, Kalubia Governorate to study the response of growth and yield of onion to potassium sulphate fertilizer at rates of 0, 150 and 300 kg/fed, as well as potassium humate at rate of 0, 3, 6 and 12 L/fed. The important obtained results were as follows:-1. Increasing the potassium addition level up to 150 kg/fed had a significant effect on the growth characters, i.e. plant height, number of leaves / plant, fresh and dry weight of whole plant as well as total yield and its components (bulb weight as g / bulb and bulb dimension. Also, gave the highest percentage of TSS, N, P, K, Fe, Mn, Zn and Cu. Increasing the potassium addition from 150 up to 300 kg/fed caused a reduction in growth characters, yield and chemical characters, (TSS, N, P, K and Fe, but increased Mn, Zn and Cu). 2. Foliar application of potassium humate at different levels, i.e. 0, 3, 6 and 12 L/fed. had a significant effect on growth characters and total yield and its components as well as chemical characters all of them resulted its highest values only with that onion plants, which sprayed with humic acid at 6 L/fed, but that onion plants, which sprayed with humic acid at levels of 12 L/fed resulted less plant growth as well as yield and its components, in addition caused an increment in TSS, N, P, K, Fe, Mn and Zn in bulb tissues.
Traditional Pattern Feature Extraction and Cultural Creative Design Application Based on Multilevel Histogram Shape Segmentation

Content-based stereo video and image retrieval relies on traditional pattern feature extraction and cultural creative design applications. In a 3D system, the 3D model is typically projected into a 2D point cloud, after which feature extraction takes place. A depth map is an image created by orthogonal projection of three-dimensional data or viewpoint matching, parallax calculation, and resampling into regular data based on depth value. In this paper, a multilevel histogram-based shape segmentation method is proposed. The threshold can be determined by analyzing the relationship between the peaks if there are several obvious peaks on the image histogram. This paper focuses on the use of traditional pattern feature extraction and cultural creative design based on the shape segmentation of multilevel histograms. Each algorithm can achieve good classification results in the experiment of rotation invariant similarity classification. The average accuracy of the HOD algorithm is 84.1%, the average accuracy of the RSDF algorithm is 86.2%, the average accuracy of the GIF algorithm is 81.3%, and the average accuracy of this paper’s algorithm is 89.9% when the rotation angle is 60–120°. The results show that this paper’s algorithm has a higher classification accuracy compared to the other algorithms and that it maintains a high average classification accuracy across all rotation angles, indicating that it is rotation invariant and robust. The histogram-based threshold method has the advantage of not requiring knowledge of the image’s prior information. The algorithm is easy to understand, straightforward, and quick. However, because the valley point in the histogram is not visible in images with low or high contrast between the target and the background area, it is difficult to select the threshold. The results of traditional pattern feature extraction can be improved using the retrieved pixels.
Development of High Extraction Magnetic Filteration by the Kaolin Industry of Georgia

An entirely new level of magnetic filtration technology was put into full commercial production by the kaolin industry of Georgia, U.S.A. during 1973 - 1975. At present, five kaolin producers in Georgia are operating large magnetic filters each capable of producing over 4000 liters of kaolin slurry per minute or over 60 tons of kaolin per hour on a dry basis. When operated at the 4000 liters per minute rate, these five large magnetic filters have a combined capacity approximating the entire waterwashed coating and filler kaolin produced in the U.S.
Comparison between constrained energy minimization based approaches for hyperspectral imagery

Constrained Energy Minimization (CEM) has been widely used for target detection in hyperspectral remote sensing imagery. It detects the desired target signal source using a unity constraint while suppressing noise and unknown signal sources by minimizing the average output power. Base on the design CEM can only detect one target source at a time. In order to simultaneously detect multiple targets in a single image, several approaches are developed, including Multiple-Target CEM (MTCEM), Sum CEM (SCEM) and Winner-Take-All CEM (WTACEM). Interestingly, the sensitivity of noise and interference seems to play a role in the detection performance. Unfortunately, this issue has not been investigated. In this paper, we take up this problem and conduct a quantitative study of the noise and interference suppression abilities of LCMV, SCEM, WTACEM for multiple-target detection.
Weighted Random Forests for Evaluating Financial Credit Risk

Credit evaluation of customers is a critical issue in financial organizations. Classification algorithms have been proposed for credit evaluation in recent years, and the class distribution in the financial data for those studies are not skewed. However, only a small proportion of customers will be the cases for bad credit. Financial records should be considered as an imbalanced data set for analyzing credit risk. Ensemble algorithms that make predictions by group decisions generally have relatively high accuracy than the ones inducing only one model from data. This study introduces a mechanism based on the weighted random forest to improve the prediction accuracy on the records with bad credit. This mechanism is tested on two financial data sets to demonstrate that it can achieve relatively high performance in evaluating credit risk and that the number of decision trees in a forest is not helpful. Critical attributes are also identified to provide practical meanings for credit risk analysis.
UvA-DARE (Digital Academic Repository) UvA@Home Team Description paper 2018 UvA@Home Team Description

This team description paper describes the approach that will be taken by the UvA@Home team to compete in Social Standard Platform League. The research challenges concern person recognition, object recognition, natural language processing and navigation. Modules implemented so far include people detection, face recognition, speech recognition and natural language processing. The remaining challenges will be solved using the previous research and achievements of the UvA teams in the RoboCup.
Paeonol increases levels of cytochrome oxidase and vascular actin, and improves behavior in a rat model of Alzheimer's disease

Paeonol(2 ′ -hydroxy-4 ′ -methoxyacetophenone;1-(2-hydroxy-4-methoxyphenyl)ethan-1-one) is aconstituentofthebarkoftheMoutanCortex( Paeoniasuffruticosa ). Thisbarkhasbeenusedasa traditional Chinese medicine and is reputed to possess a broad range of therapeutic properties probablybyvirtueofitsanti-inflammatoryandfreeradicalscavengingproperties.Theeffectsof paeonol on a variety of biochemical and behavioral parameters were studied in rat brain in rat brain after experimental animals had been subjected to an intra-hippocampal injection of amyloidpeptide,A β 1 – 42.Sprague – Dawleyratswererandomlydividedintogroups:saline,sham operated, β -amyloid (A β )-injected (intended to model Alzheimer's disease, (AD), and a group receiving both injected amyloid peptide and paeonol. Forty days after intra-hippocampal injection,H&Estainingrevealedthatthelesionsinthepaeonol-treatedgroupweresignificantly less than the untreated group. Levels of cytochrome oxidase and α -actin, determined immunohistochemically, were elevated in the paeonol treated group relative to the group receiving amyloid peptide alone. TUNEL staining revealed more apoptotic cells in the walls of the cerebral vascular elements in the AD model group than in the paeonol group. The paeonol-treated group also showed improvement in behavioral indices of learning relative to the group receiving A β 1 – 42 alone, as judged using a Y-type electric maze. Treatment with paeonol can protect against many of the alterations resulting from administration of A β 1 – 42. in a rat model of AD. These include morphological, biochemical and behavioral changes. Paeonol is a possible therapeutic measure in slowing down the pathogenic processes associated with AD. © 2011 Elsevier B.V. All rights reserved.
a new member of the renin-angiotensin system (RAS), attenuates collagen-induced arthritis in mice via inhibiting cytokine secretion in synovial fibroblastsAlamandine and inflammation in rheumatoid arthritis inhibiting

Alamandine is a novel component of the renin-angiotensin system (RAS) as well as an important biologically active peptide. It has predominantly been studied in cardiovascular context. However, its role in rheumatoid arthritis (RA) remains unknown. Here we illustrated its effects on inflammatory cytokines production by synovial fibroblasts from RA and pathological changes in collagen-induced arthritis (CIA) mice. Alamandine (0.1, 1 and 10 µg/ml) did not affect the survival of the synovial fibroblasts, but decreased the migration and proinflammatory cytokines expression in TNF-α (10 ng/ml) stimulated cells in vitro . Additionally, alamandine selectively decreased phosphorylated-JNK expression induced by TNF-a stimulation in RA FLS. DBA/1J mice were induced arthritis by a primary injection with an emulsion of bovine type II collagen (CII) and complete Freund’s adjuvant (day 0) and a booster injection of CII in incomplete Freund’s adjuvant (day 21). Mice were then given alamandine intraperitoneally in saline (50 μg/kg/day) from days 21 to 42. Histology and multiplex immunobead assay showed that alamandine treatment inhibited the development of arthritis and reduced the joint damage. This effect was accompanied by the reduced inflammatory cytokines (IL-6, IL-23, IFN-γ) mRNA expression in local joints, the decreased TNF-α, IL-6, IL-17 and the increased IL-10 levels in the serum from alamandine administrated CIA mice. In conclusion, alamandine attenuates the development of arthritis by suppressing inflammatory cytokines expression in RA synovial fibroblasts via MAPK signaling pathway, suggesting a potential therapeutic role for RA. rheumatoid arthritis (RA), alamandine (Ala), collagen-induced arthritis (CIA), fibroblast-like synoviocytes (FLS), fetal bovine serum (FBS), renin-angiotensin system (RAS), Angiotensin II (Ang II) in MH7A cells after 24 however, the increase showed a reduction trend and was significantly inhibited by alamandine treatment at the dosage of 10 μg/ml, compared to only TNF-α treated cells. Similarly, the inhibitory effect of alamandine on IL-6 and IL-8 mRNA levels was found in TNF-α treated primary RA FLS, and their decreased protein levels were also validated in TFN-α stimulated MH7A cells after alamandine treatment. These results suggest the anti-inflammatory effect of alamandine in RA FLS, which extends the understanding of alamandine in inflammation response.
DeepOWT: a global offshore wind turbine data set derived with deep learning from Sentinel-1 data

Abstract. Offshore wind energy is at the advent of a massive global expansion. To investigate the development of the offshore wind energy sector, optimal offshore wind farm locations, or the impact of offshore wind farm projects, a freely accessible spatiotemporal data set of offshore wind energy infrastructure is necessary. With free and direct access to such data, it is more likely that all stakeholders who operate in marine and coastal environments will become involved in the upcoming massive expansion of offshore wind farms. To that end, we introduce the DeepOWT (Deep-learning-derived Offshore Wind Turbines) data set (available at https://doi.org/10.5281/zenodo.5933967, Hoeser and Kuenzer, 2022b), which provides 9941 offshore wind energy infrastructure locations along with their deployment stages on a global scale. DeepOWT is based on freely accessible Earth observation data from the Sentinel-1 radar mission. The offshore wind energy infrastructure locations were derived by applying deep-learning-based object detection with two cascading convolutional neural networks (CNNs) to search the entire Sentinel-1 archive on a global scale. The two successive CNNs have previously been optimised solely on synthetic training examples to detect the offshore wind energy infrastructures in real-world imagery. With subsequent temporal analysis of the radar signal at the detected locations, the DeepOWT data set reports the deployment stages of each infrastructure with a quarterly frequency from July 2016 until June 2021. The spatiotemporal information is compiled in a ready-to-use geographic information system (GIS) format to make the usability of the data set as accessible as possible.
Counting in Regexes Considered Harmful: Exposing ReDoS Vulnerability of Nonbacktracking Matchers

In this paper, we study the performance characteristics of nonbacktracking regex matchers and their vulnerability against ReDoS ( regular expression denial of service ) attacks. We focus on their known Achilles heel, which are extended regexes that use bounded quantiﬁers (e.g., ‘ (ab){100} ’). We propose a method for generating input texts that can cause ReDoS attacks on these matchers. The method exploits the bounded repetition and uses it to force expensive simulations of the deterministic automaton for the regex. We perform an extensive experimental evaluation of our and other state-of-the-art ReDoS generators on a large set of practical regexes with a comprehensive set of backtracking and nonbacktracking matchers, as well as experiments where we demonstrate ReDoS attacks on state-of-the-art real-world security applications containing S NORT with Hyperscan and the HW-accelerated regex matching engine on the NVIDIA BlueField-2 card. Our experiments show that bounded repetition is indeed a notable weakness of nonbacktracking matchers, with our generator being the only one capable of signiﬁcantly increasing their running time.
Developing a Non-stationary Drought Index Using a Generalized Additive Model for Drought Risk Assessment

Drought is a multifaceted natural phenomenon with diverse spatial and temporal characteristics, affecting environment, society and economy significantly. The objective of this study is to model drought characteristics (duration and severity) under non-stationary environmental conditions, which is essential for early warning and effective management of drought. in reassess from eight rain gauge stations for the are fitted to non-stationary gamma distribution by using Generalized Additive Models in Location, Scale and Shape (GAMLSS) algorithm. Two major drought characteristics (duration and severity) derived from the SPI-NS are fitted to various probability distribution and best distribution is selected based on Akaike Information Criterion (AIC). The copula theory is employed for bivariate drought frequency analysis for drought risk assessment. and frequency) obtained are more severe than conventional standardized precipitation (SPI-C). The inter time is 41.46 and 39.86 for and respectively, results of bivariate analysis return period (TD and S) of drought having duration 5 months and is 13.86 and 8.28 for SPI-C and SPI-NS respectively at station. (e) the project relevant to congress themes of meteorological drought will reduce risk of agricultural drought and hydrological drought. Acknowledgement: This work was supported by Korea Environment Industry & Technology Institute(KEITI) through Advanced Water Management Research Program, funded by Korea Ministry of Environment(Grant. 83070).
FRENCH POLICY FOR SHELTER-IN-PLACE: AIRTIGHTNESS MEASUREMENTS ON INDOOR ROOMS

Accidental dispersion of toxic gas clouds may occur around industrial platforms or during hazardous materials transportation. In case of such a toxic risk, the best protection strategy is to remain inside a building and seek refuge in an airtight room identified as “shelter” until the toxic cloud has finally been swept off. This strategy called “passive shelter-in-place” also includes obstructing all external openings and turning off all mechanical ventilation systems Following the AZF chemical accident (Toulouse, 2001, 31 deaths), a French law was adopted in 2003 that can compel public and private building owners to adopt such a shelter-in-place strategy. To prove that the shelter airtightness is sufficient and that the occupants will not be exposed to irreversible effects, the shelter's air leakage measurement is compulsory for buildings owners. Envelope leakage does not need to be measured. This paper gives an overview and first analysis of collected airtightness measurements for these indoor shelters. More than 100 results have been collected, with information on the building use (one-family dwelling / multi-family dwelling / non residential), the required airtightness level, the volume, the floor area, the year of construction. The final goal of this database is to give a picture of the vulnerability of housing stock around industrial platforms. The aim is to help local decision makers with information related to the cost and the extent of works to be done on buildings in order to protect people against toxic risk, e.g. to reach the expected airtightness requirement, regarding some criteria like building use, geometric characteristics of the shelter, year of construction. These experimental data can also be used as inputs in multi-zone airflow and pollutant transfer model, when data on internal airtightness are needed to study inter-zone airflows.
Personal Growth Initiative Scale-II: validation of Spanish translation in Paraguay

Personal growth initiative is a construct that has been investigated in recent years, and has shown a cross-cultural character. Currently, it is linked to other concepts related to counseling and clinical psychology. To carry out studies in Latin American contexts, it is essential that instruments that measure this construct be translated and adapted. The present work describes the translation into Spanish and validation of the Personal Growth Initiative Scale-II in a sample of 219 university students from the city of Asunción (Paraguay). In addition, data for validity evidence in relation with other variables such as the constructs of hope and satisfaction with life are presented. Confirmatory factor analyses and an exploratory structural equation model demonstrated acceptable fit of a four-factor model with modifications, as suggested by other antecedents. On the other hand, correlations of this construct ______________________________________________________________________________________________ is underpinned, since the concept is closely related to motivational factors in the therapeutic process and can be a predictor of relapses in the long term.
Childcare, social skills, and the labor market to most recent version

This paper provides some of the ﬁrst large-scale evidence linking the eﬀects of childcare programs on long-term outcomes to social skills measured in adulthood. First, we evaluate the eﬀects of universal childcare in Finland following the sudden passing of the Childcare Law of 1973 and ﬁnd that small average eﬀects of public childcare access conceal considerable heterogeneity; public childcare levels the playing ﬁeld, reducing the family-son rank-rank income correlation by 0.05. Second, we attempt to understand how and why public childcare access shapes long-term outcomes. We ﬁnd that treatment eﬀects on income are most correlated with treatment eﬀects on skills related to social competence ( r = 0 . 38 ), somewhat correlated with treatment eﬀects on academic skills ( r = 0 . 22 ), and uncorrelated with treatment eﬀects on a measure of ﬂuid intelligence ( r = − 0 . 04 ). These treatment eﬀect correlations support the hypothesis that the long-term economic eﬀects of childcare programs are likely to operate through lasting eﬀects on social skills. Consistent with the view that childcare aﬀects long-term outcomes by changing early childhood socialization, we show that children likely to be exposed to lower quality socialization in their homes are likely to beneﬁt from public childcare access. for helpful feedback along the way. This work has beneﬁtted from the comments of participants at seminars at the CESifo Econometrics of School Reforms Workshop, Harvard (Department of Economics, Graduate School of Education, and Kennedy School), Helsinki (Faculty of Education, Graduate School of Economics, and Department of Social and Public Policy), the School in Economics, the on growth in public childcare spots following the Childcare (a) shows that the annual increase in childcare spots in the data corresponds to almost exactly 5,000 spots annually (scenario in gray) – the target number in the parliamentary proceedings from 1972. These years (1976-1981) are the only years that public childcare data is available for all municpalities (urban and rural). Figure (b) shows the annual number of public childcare spots by urban and rural status. Prior to 1973 there was almost no public childcare available rural of municipalities the of our
A Central Asia hydrologic monitoring dataset for food and water security applications in Afghanistan

Abstract. From the Hindu Kush mountains to the Registan Desert, Afghanistan is a diverse landscape where droughts, floods, conflict, and economic market accessibility pose challenges for agricultural livelihoods and food security. The ability to remotely monitor environmental conditions is critical to support decision making for humanitarian assistance. The Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) global and Central Asia data streams provide information on hydrologic states for routine integrated food security analysis. While developed for a specific project, these data are publicly available and useful for other applications that require hydrologic estimates of the water and energy balance. These two data streams are unique because of their suitability for routine monitoring, as well as for being a historical record for computing relative indicators of water availability. The global stream is available at ∼ 1-month latency, and monthly average outputs are on a 10 km grid from 1982–present. The second data stream, Central Asia (21–56∘ N, 30–100∘ E), at ∼ 1 d latency, provides daily average outputs on a 1 km grid from 2000–present. This paper describes the configuration of the two FLDAS data streams, background on the software modeling framework, selected meteorological inputs and parameters, and results from previous evaluation studies. We also provide additional analysis of precipitation and snow cover over Afghanistan. We conclude with an example of how these data are used in integrated food security analysis. For use in new and innovative studies that will improve understanding of this region, these data are hosted by U.S. Geological Survey data portals and the National Aeronautics and Space Administration (NASA). The Central Asia data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/VQ4CD3Y9YC0R (Jacob and Slinski, 2021), and the global data described in this paper can be accessed via the NASA repository at https://doi.org/10.5067/5NHC22T9375G (McNally, 2018).