Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Child Subsidies on Child Health, Well-being and Parental Investment in Human Capital: Evidence from Russian Longitudinal Monitoring Survey 2011-2017

This study evaluates the impact of introducing Maternity Capital (MC) program child subsidy of 250,000 Rub (7,150 euros or 10,000 USD, in 2007) for giving birth to /adopting 2nd and subsequent children since January 2007. The reform made it possible for eligible Russian families to allocate these funds to improve family housing conditions, to sponsor children education, or to invest them in mother's retirement fund. The objective of this study is to evaluate the impact of the MC claim eligibility on various child outcomes and household-level consumption patterns. Using data from representative Russian Longitudinal Monitoring Survey 2011-2017, I test regression discontinuity models and find no significant difference in health, educational and well-being outcomes between children raised in MC claim eligible and ineligible families. In addition, no such differences were found in terms of household-level dietary habits and preferences. The results are robust to different and functional, semi- and non-parametric RDD specifications.
Putative Dehalogenase uptake gene from Rhizobium sp. RC1

Halogenated compounds that are polluting the environment is becoming a huge concern that demands an efficient solution. The rising priority in the use of microorganisms that have the potential to be the most environmental-friendly way to degrade and dispose of halogenated compounds is crucial in solving this problem. Rhizobium sp. RC1 is a Gram-negative bacterium that was isolated from soil using 2,2dichloropropionic acid (Dalapon) and uses it as one of its primary sources of carbon. It is known that Rhizobium sp. RC1 is able to biodegrade halogenated compounds but the transport process of halogenated compounds into the cell is mostly unknown. There is a putative haloacid transport gene that is present in Rhizobium sp. RC1, dehrP, and the properties of the protein from the gene, DehrP, is ambiguous. It was concluded from this study that DehrP is a protein that belongs in the Major Facilitator Superfamily (MFS) and Metabolite:H symporter (MHS) classification of proteins by analysing the sequence and identifying the motifs that classify DehrP as a part of this classification of proteins. It was also found that the domains between DehrP and MFS/MHS proteins are conserved which provides a solid relation between them.
Detection of Ice Hockey Players and Teams via a Two-Phase Cascaded CNN Model

The accurate detection of ice hockey players and teams during a game is crucial to the tracking of individual players on the rink and team tactical decision making and is therefore becoming an important task for coaches and other analysts. However, hockey is a fluid sport due to its complex situation and the frequent substitutions by both teams, resulting in the players taking various postures during a game. Few player detection models from basketball and soccer take these characteristics into account, especially for team detection without prior annotations. Here, a two-phase cascaded convolutional neural network (CNN) model is designed for the detection of individual ice hockey players, and the jersey color of the detected players is extracted to further identify team affiliations. Our model filters most of the disturbing information, such as the audience and sideline advertising bars, in Phase I and refines the detection of the targeted players in Phase II, resulting in an accurate detection with a precision of 98.75% and a recall of 94.11% for individual players and an average accuracy of 93.05% for team classification with a self-built dataset of collected images from the 2018 Winter Olympics. The results for the regular season games of the 2019-2020 National Hockey League (NHL) covering all 31 teams are also presented to show the robustness of our model. Compared to state-of-the-art approaches, our player detection model achieves the highest accuracy with the self-built dataset.
Treatment by glyphosate-based herbicide allowed recovering native species after Oxalis pes-caprae L. invasion: indications from a Mediterranean island

Abstract Biological invasions represent a global threat to biodiversity. Particular attention should be devoted to the management of alien plants, focusing on the opportunity to obtain a rapid response to invasion and restoration of the invaded areas. In this study we aimed to evaluate five different methods for controlling Oxalis pes-caprae, a well-known invasive plant native to South Africa, also focusing on the restoration of the native flora. We set an experiment on the island of Montecristo (central Mediterranean). Treatment methods varied from chemical to low risk methods, including manual removal, covering with mulching sheets, and foliar spraying with acetic acid (30% solution) and two different concentrations of glyphosate (3 and 5% solutions, respectively). The total cover of O. pes-caprae and of other native plants was sampled before treatments, and then several times during the subsequent year; while the plant species composition was sampled in late winter (March 2015–2016) and late spring (May 2015–2016). The use of glyphosate was found to be the only efficient control method, leading to a significant decrease in O. pes-caprae cover as well as to a recovery in native species cover and richness. The effect of the other control methods was negligible.
Immune Response, Antioxidant Biomarkers and Histology of Caecal Tonsils of quail Supplemented with Sodium Butyrate

This study aimed to evaluate the impacts of dietary supplementation of sodium butyrate (SB) on antioxidant biomarkers, immune response and caecal tonsils (CT) histomorphometry of quail. A total of 240 one-day-old quails were randomly allocated into four groups with three replicates each. The first group was fed a basal diet (BD) without SB (control, T1), the 2nd group fed 1 g SB/kg BD during the first period from 0-3 weeks, then BD until the sixth week as early short feeding SB (ESFSB, T2), the 3rd group fed 1 g SB/kg BD during the whole period from 0-6 weeks as long feeding SB (LFSB, T3), and the 4th group fed BD from 0-3 week then fed 1 g SB/kg BD during the second period from 3-6 weeks as late short feeding SB (LSFSB, T4). The SB supplementation in quail diet significantly increased (P<0.05) serum total antioxidant capacity and declined malondialdehyde level compared with the control group. The inclusion of SB had a higher immune response through the increase of SRBCs titer value (P<0.05) in ESFSB, LSFSB and LFSB groups than the control group. Histomorphometry parameters of CT were significantly improved in ESFSB and LFSB compared the control. The LFSB group fed a diet containing SB from 0-6 weeks had better antioxidant biomarkers, immune response and histomorphometry parameters of CT of quail. In conclusion, it is suggested feeding quail on diets containing SB through the whole growth period to display its positive influence on the antioxidant biomarkers and immunity of quail
A multi-scale 3D convolution neural network for spectral-spatial classification of hyperspectral imagery

Along with the remarkable achievements of various neural networks in the field of computer vision, deep learning methods have gradually been applied to hyperspectral image (HSI) classification. Traditional classification methods have several outstanding issues, including the insufficient hand-craft features and time-consuming and laborious feature extraction. We therefore propose a multi-scale, 3D convolutional neural network (CNN) framework (MSCNN), trained in an end-to-end manner for hyperspectral image classification. Using the original hyperspectral image as an input, the MSCNN framework leverages two branches of a 3D residual neural network to extract deep and abstract HSI features. Then, the HSI spectral-spatial features of different scales are fused and fed into the SoftMax layer to achieve an end-to-end hyperspectral image classification. Besides, data augmentation, dynamic learning rate, and regularization methods are used to promote the rapid convergence of MSCNN and avoid model over-fitting. Three well-known hyperspectral datasets (Indian Pines, University of Pavia and Pavia Center) were used to evaluate the classification performance of the proposed MSCNN method. The results indicate that, compared with the existing deep learning methods, the proposed MSCNN method achieves the best classification performance within the 20 training epochs. The overall accuracy (OA), average accuracy (AA), and kappa statistic (K) of MSCNN are 97.16%, 98.69% and 0.9665, respectively, for Indian Pines; 99.17%, 98.97% and 0.9888 for University of Pavia; and 99.87%, 99.70% and 0.9981 for Pavia Center.
Chemical composition and insecticidal activity Mentha piperita L. essential oil against the cowpea seed beetle Callosobruchus maculatus F. (Coleoptera: Bruchidae)

Antifeedant activity of plant extract from Mentha piperita was tested against the cowpea seed beetle, Callosobruchus maculatus. Dry ground plant was subjected to hydrodistillation using a Clevenger-type apparatus. The resulting oil contained menthone (28.9%), menthol (28.5%), and pulegone (6.9%) as the major compounds. LC50 of M. piperita essential oil was 25.70 μL/L air and mortality increased as the doses of essential oil increased. LT50 values were 3.29, 2.74 and 1.89 h at 100, 200 and 500 μL/L air, respectively. The results of persistence test of oil revealed that essential oil of M. piperita on C. maculatus adults was 5.44 days. It was clear from the repellency index that M. piperita essential oil has strong repellency at 90, 180 and 360 μL/L air concentration. The results showed that M. piperita essential oil has significantly affected the relative growth rate, relative consumption rate and feeding deterrence index of C. maculatus adults and it was concentration-dependent. The efficiency of conversion of ingested food has decreased while the concentrations are not statistically different at 5% level compared to the control group. It seems that essential oil can be used as low-risk insecticides.
Enzymatic Activity and Plant Growth Promoting Potential of Endophytic Bacteria Isolated from Ocimum sanctum and Aloe vera

Endophytes are microbes that reside within living plant tissue for all or part of their life cycle without causing substantive harm to their host. Endophytes enter the plant tissues primarily from the rhizosphere through the root zone and become localized at the point of entry or are able to spread throughout the plant. One of the major contributions of these microorganisms towards plant growth is the production of auxin-like molecules (Spaepen et al., 2007) which is shown to be produced by many root associated bacteria including Enterobacter sp. , Pseudomonas sp. and Azospirillium sp. (El-Khawas and Adachi, 1999). In addition to the IAA production, plant growth promoting bacteria (PGPB) are International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 7 Number 06 (2018) Journal homepage: http://www.ijcmas. com
Titrimetric and spectrophotometric determination of albendazole with bromate and methyl orange

Two methods, titrimetric and spectrophotometric, are described for the quantitative determination of albendazole as pure substance and in dosage forms. The methods involve the use of bromate-bromide reagent and methyl orange dye. In titrimetry, a known excess of bromate-bromide reagent is added in acid medium, and after specified time, the residual reagent is determined iodometrically. Spearophotometry involves the addition of known excess of bromate-bromide reagent in the presence of hydrochloric acid, and determination of unreacted bromate by reacting with methyl orange and measuring the increase in absorbance at 510 nm. The absorbance is found to increase linearly with increasing concentration of albendazole, which is corroborated by the calculated correlation coefficient value of 0.9990. Working conditions have been optimised. Titrimetry permits micro determination (1-10 mg) while spectrophotometry is applicable in the concentration range 0.5-4.0 mug ml(-1) of drug. The molar absorptivity and the Sandell sensitivity Were calculated to be 2.89x10(4) 1 mol(-1)cm(-1) and 9.17 ng cm(-2), respectively. The proposed methods were applied successfully to the determination of albendazole in pharmaceutical preparations. The reliability of the assay was established by parallel determination by the reference method and recovery studies.
Performance enhancement of biological methanation with trickle bed reactors by liquid flow modulation

Experiments were carried out to investigate the influence of liquid flow modulation of trickle bed reactors (TBR) on biological hydrogen methanation (BHM). The modulation promises to improve the gas‐liquid mass transfer and has already been demonstrated in trickle bed reactors of other fields of application. Therefore, the influence of four different circulation intervals with pauses from two to 1,440 min was investigated in TBR for BHM. The results showed that as pause intervals without sprinkling became longer, the methane content increased from 88.61 ± 1.58 vol‐% at a circulation interval of 2 min to up to 97.19 ± 0.46 vol‐% at a circulation interval of 1,440 min. The analysis of the process liquid indicated a stable biological process at any trial phase. This study demonstrated that the performance of TBR on BHM can be significantly improved by liquid flow modulation, thus significantly reducing operating costs.
Visualization Classification and Prediction Based on Data Mining

The paper aims to solve huge amounts and noise of current internet information. In order to better excavate the user’s interests and provide accurate recommendations, improve the Internet environment and services and accurately analyze and evaluate the behavior of large-scale user groups. This article compares web pages with sentences in natural language, and uses the natural language processing algorithm Word2vec to extract the feature vectors of massive web pages browsed by users. PCA has been reduced to two dimensions, and webpage visualization and logistic regression have been implemented to classify webpages. A series of user clicks on webpages can be viewed as a walk in n-dimensional space. Probabilistic language models and Monte Carlo simulations are used as the next step for users. Click behavior to make predictions. Experiments show that the machine learning processing natural language algorithm used in this paper has a good performance in classification and prediction accuracy.
Preparation of spatial distribution maps of saffron water requirement in Kermanshah province

Water is one of the most important environmental elements used for a variety of purposes such as irrigation of farms, food production, domestic, industrial and commercial uses. In Iran, agriculture is the largest consumer of water. If water is consumed properly in agriculture and water losses is minimized, its productivity will increase and conditions for sustainable agriculture will be provided. The irrigation system is designed according to the water requirements of the plants. Saffron is an important crop in Kermanshah province and we conserve water by doing research on water requirement of saffron. In this research the water requirement of saffron and the effect of efficient rainfall is studied in Kermanshah province and the amount of supplemental irrigation water was calculated. Water requirement was obtained experimentally and by multiplying crop coefficient of saffron (KC) with evapotranspiration of the reference crop (ETO). To calculate evapotranspiration of the reference crop (ETO) the PenmanMonteith FAO equation was used as the most valid method for estimating water requirement. Amount of effective rainfall was estimated by cropwat model based on USDA method. The results show that water requirement during growing season for saffron is 211.43, 166.98, 249.59, 240.31, 237.74, 204.27, 194.82, 250.13, 282.83, 191.21 and 184.2 mm for Kermanshah, Kangavar, Ravansar, Sarpol-e Zahab, Eslamabad-e-Gharb, Sonqor, Sanandaj, Khorramabad, Ilam, Hamedan and Qorveh respectively. Also, the results show that amount of effective rainfall during growing season for saffron is 138.9, 129.1, 191.5, 147.2, 166.4, 119.8, 128.1, 178.9, 208.5, 85.8 and 96.9 mm for Kermanshah, Kangavar, Ravansar, Sarpol-e Zahab, Eslamabad-e-Gharb, Sonqor, Sanandaj, Khorramabad, Ilam, Hamedan and Qorveh respectively. Moreover, the results show that irrigation requirement during growing season for saffron is 72.53, 37.88, 58.09, 93.11, 71.34, 84.47, 66.72, 71.23, 74.33, 105.41 and 87.3 mm for Kermanshah, Kangavar, Ravansar, Sarpol-e Zahab, Eslamabad-e-Gharb, Sonqor, Sanandaj, Khorramabad, Ilam, Hamedan and Qorveh respectively. Maps showed that the highest saffron water requirement happened in May which was 0.829-1.432 mm/day. The highest and lowest water requirement of saffron were observed for Sarpol-e Zahab and Kangavar stations, respectively.
The complete mitochondrial genome of the critically endangered Cuora mccordi (Reptilia: Geoemydidae)

Abstract The complete mitochondrial genome (mitogenome) sequence of the MeCord's box turtle (Cuora mccordi) was firstly determined by shotgun sequencing. The total length of mitogenome is 16,688 bp, and contains 13 protein-coding genes, 22 transfer RNA genes, 2 ribosomal RNA genes and 2 main noncoding regions (the control region and the putative L-strand replication origin). The majority genes (12 protein-coding genes, 2 rRNA and 14 tRNA) were distributed on the H-strand, except for the ND6 subunit gene and eight tRNA genes which were encoded on the L-strand. The phylogenetic tree of C. mccordi and 10 other closely related species was built. The DNA data presented here will be useful to study the evolutionary relationships and genetic diversity of C. mccordi.
Production of Soybean Oil Nanoemulsion (SONE) and Evaluation of Angiogenic and Embryotoxic Activity

The SONE oil/water was prepared using the pseudo-ternary phase diagram, using a low energy method with phase inversion by changing the composition. In order to optimize the preparation of SONE, three speeds were used in the agitator arm and two different rods. The particle size and polydispersity index were determined by Dynamic Light Scattering (DLS) and the stability test by the freeze-thaw cycle. Angiogenesis in chicken embryo egg chorioallantoic membrane and zebrafish (Danio rerio) embryotoxicity was performed. The lower stirring speed and propeller shaft induced smaller particle size (550.2 nm). Regarding angiogenesis, there was a statistically significant difference for all the evaluated parameters (length, caliber, junctions, and number of blood vessel complexes) and the result was higher in SONE when compared to the inhibition control (Dexamethasone), but lower than the induction control (Regederm®) and there was no statistically significant difference between SONE and distilled water. It was observed that the exposure of the zebrafish embryos to SONE caused an increase in the mortality rate dependent on time and concentration. The LC50 for SONE decreased statistically with increasing exposure (p-value = 0.046). Heart rate decreased significantly with increasing concentration at all exposure times (p-value < 0.05), as a result of progressive embryo mortality. The hatching rate was late until the concentration of 0.0193 mg/mL and no hatching rate was verified from that concentration. Exposure of zebrafish embryos to different concentrations of SONE induced malformations such as spinal changes, pericardial edema and yolk sac edema, but there was no significant difference in the malformation rate of embryos exposed to SONE when compared to the control group. The SONE produced remained stable in the freeze-thaw cycle, with changes only in pH. Despite the low results for embryotoxicity, further studies are needed, aiming at the ideal formulation for angiogenesis purposes.
A Tractable Coverage Analysis in Dynamic Downlink Cellular Networks

In this work, we proposed a tractable mathematical framework to analyze the coverage probability in dynamic downlink cellular networks taking into account the queue dynamics. In particular, the static properties of the physical layer network are studied by stochastic geometry and dynamic properties of queue evolution are studied with discrete time Markov chain. We also analyze the stable region by giving explicit upper and lower bounds on the dynamic coverage probability.
The Performance of Responsible Equity Funds During Market Crises

The purpose of this thesis is to study the performance of responsible equity funds during periods market crises. Previous literature has found evidence of outperformance by stocks of responsible companies and responsible mutual funds during market crises. Additionally, this thesis provides evidence of the performance of responsible equity funds and compares risk-adjusted returns of responsible investing to those of conventional equity mutual funds during a sample period of almost two decades. This study employs a dataset of 110 US-based socially responsible funds and 120 US-based conventional equity funds from January 2000 to October 2019. These mutual fund groups are used to construct two time-series of the returns of an equal-weighted portfolio of the SRI funds and conventional funds, respectively. The abnormal returns of SRI and non-SRI are measured using the capital asset pricing model, the Fama-French three-factor model and the Carhart four-factor model. In order to measure the performance of these portfolios during crisis periods, these asset pricing models are extended to include crisis and non-crisis period alphas. The results suggest that both responsible funds and conventional funds do not generate abnormal returns during the whole sample period. In addition, SRI significantly underperforms nonSRI during crises and their non-crisis period performance are similar. However, during January 2010 – October 2019 the SRI portfolio outperforms the conventional portfolio during crises and normal market conditions, although, the difference between the two is not significant. Responsible investing does not provide investors with downside protection during periods of market turbulence. On the contrary, SRI underperforms during market crises which contradicts previous research. Additionally, the performance of SRI does not significantly differ from that of non-SRI during normal market conditions. These results suggest that investors should not expect abnormal returns while investing responsibly. However, investors should not favor non-SRI neither, since the risk-adjusted returns of SRI do not significantly differ from those of conventional mutual funds.
Statistical analysis of radiomic features in differentiation of glioma grades

Radiomics is an important quantitative feature extraction tool used in many areas such as image processing and computer-aided diagnosis. In this study, the discriminability of brain cancer tumour grades (Grade II and Grade III) with radiomic features were analysed statistically. The data set consists of 121 patients, 77 patients with Grade II tumours and 44 patients with Grade III tumours. A total of 107 radiomic features were extracted, including three groups of radiomic features such as morphological, first-order and texture. Relationships between the characteristics of each group were tested by Spearman’s correlation analysis. Differences between Grade II and Grade III tumour categories were analysed with Mann–Whitney U test. According to the results, it was seen that radiomic features can be used to differentiate the features of tumour levels evaluated in the same category. These results show that by employing radiomic features brain cancer grade detection can help machine learning technologies and radiological analysis. Keywords: Radiomics, glioma, image processing.