Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Seed Treatments Pre-sowing and Organo-mineral Fertilizer on Spring Barley Production

The results of this experiment showed the effect of barley seeds pre-treatments and organo-mineral fertilizer on the morpho-physiological evaluation of seedlings, seed quality and productivity of spring barley (Mikhailovsky). Variance analysis results (ANOVA) showed extremely significant (p less than 0.05) variations between different treatments in all traits, where the treatments led to increasing the germination energy, laboratory germination, growth force and weight of 100 sprouts compared with control. There was a positive effect on the development of the barley root system. Pre-treatment of seeds in wet years have been proven to be the most effective, while the efficiency of seed treatment pre-sowing decreased when soil moisture was low. Therefore, in 2017 barley productivity increased when the seeds were treated with a mixture of Polaris with Siliplant by 25% compared to control, while in 2018 the yield increased (7.1%) when mixture of Siliplant with Polaris was applied compared to control.
Forecasting monthly airline passenger numbers with small datasets using feature engineering and a modified principal component analysis

In this study, a machine learning approach based on time series models, different feature engineering, feature extraction, and feature derivation is proposed to improve air passenger forecasting. Different types of datasets were created to extract new features from the core data. An experiment was undertaken with artificial neural networks to test the performance of neurons in the hidden layer, to optimise the dimensions of all layers and to obtain an optimal choice of connection weights – thus the nonlinear optimisation problem could be solved directly. A method of tuning deep learning models using H2O (which is a feature-rich, open source machine learning platform known for its R and Spark integration and its ease of use) is also proposed, where the trained network model is built from samples of selected features from the dataset in order to ensure diversity of the samples and to improve training. A successful application of deep learning requires setting numerous parameters in order to achieve greater model accuracy. The number of hidden layers and the number of neurons, are key parameters in each layer of such a network. Hyper-parameter, grid search, and random hyper-parameter approaches aid in setting these important parameters. Moreover, a new ensemble strategy is suggested that shows potential to optimise parameter settings and hence save more computational resources throughout the tuning process of the models. The main objective, besides improving the performance metric, is to obtain a distribution on some hold-out datasets that resemble the original distribution of the training data. Particular attention is focused on creating a modified version of Principal Component Analysis (PCA) using a different correlation matrix – obtained by a different correlation coefficient based on kinetic energy to derive new features. The data were collected from several airline datasets to build a deep prediction model for forecasting airline passenger numbers. Preliminary experiments show that fine-tuning provides an efficient approach for tuning the ultimate number of hidden layers and the number of neurons in each layer when compared with the grid search method. Similarly, the results show that the modified version of PCA is more effective in data dimension reduction, classes reparability, and classification accuracy than using traditional PCA.
P0311INFECTION-RELATED GLOMERULONEPHRITIS IN ADULTS: TIME FOR A DEFINITIVE PARADIGM SHIFT?

The recent decades have witnessed significant changes in the epidemiology and clinical course of infection-related glomerulonephritis (IRGN). We analyzed the clinicopathological features and long-term outcome of adult patients with biopsy-proven IRGN followed in a large Italian referral centre. We included patients with biopsy-proven IRGN diagnosed from 2000 to 2018. Clinical and laboratory findings, histological features, possible risk factors and therapy were assessed for both renal and patient outcome. Forty-one patients met the inclusion criteria (male:female ratio 3:1, mean age 61±16 years). Smoke habit (47.2%), alcoholism (30.6%), and diabetes (27.5%) were the most common risk factors. The most frequently identified sites of infection were skin, lung and heart (Table 1). Staphylococci spp. accounted for 76.5% of positive cultures (Figure 1). Hypocomplementaemia emerged in 48.5% of cases. The most frequent histologic patterns were diffuse proliferative (56.0%) and membranoproliferative (29.3%) glomerulonephritis. Haemodialysis was required by 22.5% of patients at inception. Two thirds of patients developed chronic kidney disease; half of them reached end-stage renal disease (ESRD). By multivariate analysis ESRD was associated with diabetes (HR 13.7; 95% CI, 1.6-121.0; p=0.018), crescents (HR 25.2; 95% CI, 2.7-235.7; p=0.005), and interstitial fibrosis (HR 31.0; 95% CI, 3.3-287.3; p=0.003). Male gender (HR 12.7; 95% CI, 10.8-14.6; p=0.008) hypertension (HR 40.8; 95% CI, 38.6-43.1; p=0.001), gross haematuria (HR 11.8; 95% CI, 9.4-14.2; p=0.047), need for haemodialysis at onset (HR 16.3; 95% CI, 14.7-17.8; p<0.0001), and interstitial infiltrate (HR 13.3; 95% CI, 11.6-15.0; p=0.003) significantly affected survival. Corticosteroids did not affect prognosis. While traditionally considered a “benign” disease with a favorable course in children, IRGN is a potentially severe disease in adults, particularly when a background of major comorbidities and older age are present. A significant proportion of patients does not recover renal function, with a remarkable risk of ESRD.
Three-dimensional Simulation of Effects of Electro-Thermo-Mechanical Multi-physical Fields on Cu Protrusion and Performance of Micro-bump Joints in TSVs Based High Bandwidth Memory (HBM) Structures

With taking into account the electric load, a simplified 4-hi stack HBM structure model containing through- silicon-vias (TSVs) with a 3×6 distributed matrix in each hierarchical level is built. Distributions of temperature, current density and voltage, as well as the mechanical behavior of TSVs and the micro-bump joints in the HBM model are characterized by finite element simulation. To clarify the roles of various coupled physical fields playing in influencing the performance of TSVs and micro-bump joints, the comprehensive simulations were conducted under the conditions of electro-thermo-mechanical fields, electro-mechanical fields and thermo-mechanical fields, respectively. The simulation results indicate that under the electro-thermo-mechanical fields, not only Joule heating occurs but also the current crowding effect appears at the corners between Cu pads and micro-bump joints, as well as at both ends of TSVs. Notably, the maximum current density under the electro-mechanical fields is larger than that under the electro-thermo-mechanical fields. In addition, the Cu protrusion height at lower ends of TSVs is larger than that at upper ends. For micro-bump joints with the viscoplastic deformation behavior, the strain concentration exhibits a symmetrical distribution along the ZY plane (X=0).
Protective Effect on Lipids Profile of Lion’s Foot (Alchemilla Vulgaris ) Leaves against Ccl4 Toxicity and its Fortified to Guava and Mango Pulp

Lion’s foot (Alchemilla vulgaris L.) which is widely known as lady’s mantle, bear’s foot or lion’s foot is traditionally used due to their tannin contents for the treatment of inflammations, diarrhea, wound healing and inhibit cardiovascular diseases and cystic fibrosis. The present work aims to high light the reverse effect of dried lion’s foot (Alchemilla vulgaris) leaves and its water and ethanol extracts at various ratios against the toxicity of CCl4 on serum lipids profile that may occur on albino rats. Also, preparation of guava and mango pulp that fortified with lion’s foot powder and its water and ethanol extracts as an available product rich in bioactive component to help hyperlipidemic patients. Fifty-six male albino rats were used in this experiment. These rats were divided into eight main groups (seven rats of each) and were fed on diets for 45 days as follows: Group 1: Negative control group was fed on basal diet. Forty nine rats were fed on basal diet and treated with CCl4 subcutaneous injection to induce toxicity, then divided into 7 groups form group 2 to group 8. Group 2: Positive control group will be fed on basal diet till final experiment. Groups 3:8 as the same of the second group with (50 and 100 ppm ethanol extract, 50 and 100 ppm water extract, 1% and 2% dry leaves powder respectively) daily orally. Moreover, guava and mango pulps were classified to 7 groups as follows: control sample, and the samples (2 to 7) were fortified with lion’s foot as follows ethanol extract 50ppm and 100ppm , water extract 50ppm and 100ppm, 1% and 2% dried leaves for sensory evaluation. All these samples were organoleptically evaluated for general appearance, color, flavor, taste, consistency and overall acceptability. Results: The results revealed that treatment with lion’s foot leaves and its ethanol and water extracts caused significant decreased levels of serum lipid profile of total cholesterol, triglycerides, total lipids, LDL-C and VLDL-C induced by CCl4 and enhancement HDL-C in all groups. The best result of lipid profile was in groups treatment with the high level 2% dried lion foot followed 1 % dried lion’s foot and 100ppm ethanol extract. These results due to the antioxidants content in Lion’s foot as polyphenols, flavonoids, tannins and saponins (359.65, 183.10, 150.64 and 296.32, respectively). The best sample of fortified guava pulp was 1% dried leaves. While, the best result of mango pulp was in the samples fortified with 50ppm ethanol extract, water extracts (50 and 100 ppm) and 1% dried leaves. Conclusion: This study showed that the fortification of Alchemilla vulgaris L. can be proposed to protect the toxicity induced by CCl4 in rats, also to help inhibit the improvement cardiovascular diseases and cystic fibrosis.
Behavioral and biological responses of black bean aphid (Aphis fabae, Scopoli, 1763) on seven Algerian local broad bean cultivars

We studied the behavioral and biological parameters of Aphis fabae (Homoptera: Aphididae, Scopoli, 1763) on seven local Vicia faba L. cultivars. The antixenosis was conducted under laboratory controlled conditions of the temperature, light regime and relative humidity (18 ± 0.25 °C; L16: D8; 37.5 ± 0.6 %) for test in light, and (19 °C; 42 % relative humidity) for test in dark. The least preferred host plants for attractivity was the cultivar 141 in both tests while the cultivar 145 was the most preferred in light test, and the cultivar 107 in dark test. The antibiotic experiment was conducted also under laboratory conditions (L16: D8 photoperiod, 17 ± 1 °C, and 43.5 ± 5 % r. h.). Antibiosis was determined by studying the pre-reproductive period, reproductive period, adult longevity, survival, daily and total fecundity. The analysis of variance indicated that no significant differences on pre-reproductive period and daily fecundity of the A. fabae among the cultivars. However, the longest times of reproductive period, adult longevity, and survival were recorded on cultivar 135 followed by cultivar 141. The highest (85.8) and the lowest (15.8) number of progeny were observed on 135 and 141 cultivars, respectively.
Meat quality and chemical assessment of porcine longissimus dorsi within different muscle pH

This study was carried out to investigate the influence of pH on the Berkshire’s pork longissimus dorsi muscle, by comparing physicochemical characteristics in a high pH group (5.92 ± 0.02) and a low pH group (5.55 ± 0.03) on the basis of muscle pH24 h post-mortem. Fifteen pigs were assigned to each group (n = 15). The low pH group showed higher filter-paper fluid uptake, cooking loss and National Pork Producers Council marbling scores but did not significantly differ from the high pH group (P > 0.05). The low pH group also showed higher Commission International de l’Eclairage L* and b*, drip loss, and shearing forces were significantly different from the high pH group. However, Commission International de l’Eclairage meat colour value (a*) and National Pork Producers Council colour were higher in the high pH group. The content of glutamic acid, threonine, and serine amino acids associated with a good flavour was higher in the high pH group. Also, amino acids associated with a bitter or poor flavour, such as valine, isoleucine, leucine, tyrosine, and histidine, was higher in the high pH group as well. The taste of umami was significantly (P < 0.01) higher in the high pH group. Levels of the nucleotide compounds hypoxanthine and inosine tended to be higher (P < 0.05) in the high pH group, whereas adenosine diphosphate levels were increased in the low pH group (P < 0.05). It is concluded that pH of pork could be a good indicator of pork quality and related to factors influencing pork eating quality. As pH of pork is not only positively associated with physical traits of pork but also closely related to chemical traits of which higher free amino acids and nucleotides enhance pork quality.
Effect of Combined Inoculation of Phosphate Solubilizing Bacteria and Endomycorrhizae Fungi on Microbial Population and NPK Uptake by Wheat (Triticum aestivum L.) Crop

Aim: To study the response of co-inoculation of Phosphate Solubilizing Bacteria (PSB) and Arbuscular Mycorrhizal (AM) fungi to microbial population of soil and nutrient uptake by wheat crop . Study Design: The used design was completely randomized design with three replications. Place of Study: The pot experiment was conducted during Rabi season of 2017 taking wheat (cv. HD 2967) as test crop in experimental unit of the department of Soil Science and Agricultural Chemistry, Bihar Agricultural College, Sabour, Bhagalpur (Bihar). Methodology: The present study includes eight treatments with three replications. N P K uptake by wheat crop was measured from each treatment and microbial populations of soil were determined from the rhizospheric soils collected from each treatment by using standard protocol. Results: Maximum microbial population viz., Bacteria, Actinomycetes, Fungi (39.00, 21.33, 24.66 Original Research Article Rani et al.; CJAST, 32(5): 1-9, 2019; Article no.CJAST. 46747 2 CFU × 10 g oven dry soil) were recorded under treatment T4 (T1+PSB @ 20 g kg1 seed+AM fungi @ 5.0 g pot -1 ) for bacteria and actinomycetes and T3 (T1+AM fungi @ 5.0 g pot -1 ) for fungi, at flowering stage and similar trend was followed at harvesting stage. The treatment T4 significantly increased available nitrogen, phosphorus and potassium in soil as well as also contributed to comparatively better plant growth and higher uptake of N, P and K by grain and shoot. The maximum N, P and K content of wheat was also recorded under treatment T4 which was found to be most effective in modifying soil microbial population, microbial community structure and grain yield of wheat crop. Conclusion: Application of co-inoculation of Phosphorus solubilizing bacteria and arbuscular mycorrhizal fungi enhance the microbial population and N P K uptake from soil by wheat crop.
The CIC-DUX4 fusion oncoprotein drives metastasis and tumor growth via distinct downstream regulatory programs and therapeutic targets in sarcoma

Transcription factor fusion genes create oncoproteins that drive oncogenesis, and represent challenging therapeutic targets. Understanding the molecular targets by which such fusion oncoproteins promote malignancy offers an approach to develop rational treatment strategies to improve clinical outcomes. CIC-DUX4 is a transcription factor fusion that defines certain undifferentiated round cell sarcomas with high metastatic propensity and poor clinical outcomes. The molecular targets regulated by the CIC-DUX4 oncoprotein that promote this aggressive malignancy remain largely unknown. We show that increased expression of ETV4 and CCNE1 occurs via neo-morphic, direct effects of CIC-DUX4 and drives tumor metastasis and survival, respectively. We demonstrate a molecular dependence on the CCNE-CDK2 cell cycle complex that renders CIC-DUX4 tumors sensitive to inhibition of the CCNE-CDK2 complex, highlighting a therapeutic strategy for CIC-DUX4 tumors. Our findings highlight a paradigm of functional diversification of transcriptional repertoires controlled by a genetically-aberrant transcriptional regulator, with therapeutic implications.
Performance of High-strength Concrete Made with Recycled Ceramic Aggregates (Research Note)

Recent scientific concerns to achieve sustainability in construction have suggested the implementation of using recycled aggregate in concrete; because it has the potential to reduce the demand for extraction of natural raw materials and decrease the volume of wastes landfilled. In this respect, this study aims to investigate the suitability of using ceramic tile (CT) and ceramic sanitary (CS) wastes as coarse aggregate in production of high-strength concrete (HSC). Different concrete mixes were produced by partial replacement of 10, 20 and 30% of natural coarse aggregate with recycled aggregates. Besides investigating the characteristics of recycled aggregate, slump, compressive strength, initial and final absorption and chloride ion penetration depth of HSC specimens were evaluated and compared with that of plain HSC. Results showed that using recycled ceramic aggregates increased the superplasticizer dosage to maintain the target slump. Although by incorporation of high percentage of CT or CS aggregate, compressive strength of HSCs was reduced compared with reference HSC, it is possible to produce HSC with 28-days compressive strength higher than 60.7 MPa. Moreover, the absorption and chloride ion penetration depth of recycled aggregate incorporated HSC were higher than those of estimated for plain concrete. Generally, waste ceramic aggregate at optimum replacement ratio can be used in the sustainable development of HSC.
Sub-fixed-time control for a class of second order system

In this paper, a new concept “sub-fixed-time stability” (SFTS) is proposed and studied, which means the states can converge to a region of equilibrium points in a fixed time for any initial states’ values. Then, a sufficient condition for it is given and proven. Though SFTS is similar to “practical fixed-time stability” (PFTS), they are not the same, and the sufficient condition for SFTS is much clearer and simpler than PFTS. Next, a sub-fixed-time controller is proposed for a class of second order system. The stability analyses are given in the case without disturbance and with disturbance, respectively. Finally, to illustrate the robustness of the proposed sub-fixed-time controller to different initial conditions, 100 numerical simulations are conducted for 100 initial states’ values.
The effectiveness of micro-learning in retail banking

In order to remain competitive in a global technological revolution, the learning and development departments of businesses are focusing on the emerging concept of micro-learning, to support the fast-paced, multitask orientated and digitally savvy learners. A survey was conducted among 7 673 employees of one of the major retail banks in South Africa, to determine the effectiveness of micro-learning and establish whether micro-learning is effective, as well as identify gaps and recommend strategies to close them. Through inferential statistical analysis of the data, it was concluded that learners reacted positively to micro-learning, the acquired relevant knowledge using micro-learning which improved work performance and business metrics. Although the micro-learning programme was deemed effective for the vast majority (80%) of the participants, two gaps were identified, namely, micro-learning did not fully embrace the social tenet of learning, and it is also not exempt from the distractions that learners experience. It is recommended that any organisation pursuing a micro-learning programme should incorporate a social knowledge-sharing element into the programme and provide users with tools to develop self-control and self-regulation habits needed to conquer constant distractions.
Feasibility of body weight estimation of Kalkoohi camels using digital image processing.

The aim of this study was to investigate the possibility of estimating the weight of Kalkoohi camels using digital image processing. For this purpose, Kalkoohi camels were weighed monthly on a private farm for one year. On the day of weighing, digital images were taken from all camels from their lateral side. These digital images were processed in MATLAB software environment and the required numerical features of each image including different morphological features were extracted. Among all extracted features, major axis length, minor axis length, the number of non-zero elements (NNZ) and equivalent diameter had a significant and high correlation with the weight of camels (P<0.01) and were considered as effective features in developing neural network. The multi-layer artificial neural network, which was trained by back propagation algorithm, was used to estimate the weight of camels based on their digital images. The accuracy of the final model in estimating the weight of Kalkoohi camels based on their image features was 99%. The correlation coefficient between the estimated weights by artificial neural network model and the actual weights of the camels was 98%, and the deviation of estimated weights from the measured weight of camels was 2.21 kg. The results of this study revealed that digital image processing technology has a good potential to estimate the weight of Kalkoohi camels, and this method could be a good alternative to weigh camels using a scale.
RECOLORED IMAGE DETECTION VIA A DEEP DISCRIMINATIVE MODEL

: Image recoloring is a method that can move picture shading or topic and result in an impalpable change in human eyes. In spite of the fact that picture recoloring is one of the most significant picture control procedures, there is no extraordinary technique intended for identifying this sort of imitation. Right now, propose a trainable start to finish framework for recognizing recolored pictures from normal pictures. The proposed arrange takes the first picture and two inferred inputs dependent on light consistency and between channel relationship of the first contribution to thought and yields the likelihood that it is recolored. Our calculation embraces a CNN-based profound design, which comprises of three component extraction squares and an element combination module. To prepare the profound neural system, we blend a dataset contained recolored pictures and relating ground truth utilizing diverse recoloring strategies.
Implementation on Voice based SQL query Generation using NLP

: This system has been developed to enable secure access of data to a voice-based user interface (UI) by enabling voice-based authentication and integration with an existing Natural Language Processing (NLP) system. We address the question of how to improve the fetching the results from query results. Traditional predefined query forms are not able to satisfy various ad-hoc queries from users on those databases. Here, we propose Machine learning based technique to generate the SQL query based on user voice, a novel database query form interface, which is able to dynamically generate query forms.