Miracle-dz/UniFAR-FTUs huggingface dataset:
Artificial intelligence: From ethics to policy

Based on a framing of 'AI as a social experiment,' this study arrives at regulatory options for public administrations and governmental organisations who are looking to deploy AI/ML solutions, as well as the private companies who are creating AI/ML solutions for use in the public arena. The reasons for targeting this application sector concern: the need for a high standard of transparency, respect for democratic values, and legitimacy. The policy options presented in the study demand targeted procedural solutions. Together, these chart a path towards accountability in AI; procedures and decisions of an ethical nature are systematically logged prior to the deployment of an AI system. This logging is the first step in allowing ethics to play a formidable role in the implementation of AI for the public good.
RESPONSE OF GROWTH AND YIELD OF TWO VARIETIES OF RAPESEED (BRASSICA NAPUS L.) TO DIFFERENT CONCENTRATIONS OF HUMIC ACID

During the winter season of (2018-2019), a field experiment was conducted in two locations, the first was the station of research and agricultural experiments of the College of Agriculture and Forestry, Mosul University; and the second location was in Wana district in a muddy and sandy loam soils successively. The aim is to study the effect of two varieties of rapeseed which are (Srew and Pactol) and five concentrations of humic acid (0, 20, 40, 60, 80 mg/l) on the characters of growth and yield. The experiment was conducted as a Randomized Complete Block Design (RCBD) with three replications. The results revealed that there are abstract differences between the two varieties in all the studied features and for both locations of the college and Wana. The verity Pactol recorded the highest rate of the plant's height and the number of the branches of the plant successively. The variety Srew showed the highest rate of the number of the branches and the dry weight of the plant and the number of siliques in the plant and the number of seeds in a single silique and 1000 seed weight and seed yield of the seeds and percentage of oil and oil yield for both locations successively. The concentrations of humic acids affected abstractly all the studied features. The concentration (40 mg/l) recorded the highest rate of plant height, the branches of the plant, the number of siliques in the plant, the number of seeds in the one silique, seed yield, percentage of oil and oil yield. The concentration (60 mg/l) recorded the highest rate of plant height and 1000 seed weight in both locations successively. The overlap between the two varieties and the concentrations of the humic acid were abstract only in seed yield, the plants of the Srew verity and the sprayed with the humic acid (40 mg/l) recorded the highest rate of characters of seed yield in both locations.
A Review on Post Processing of Turmeric Rhizome

Turmeric is the most ancient medicinal species found in the world. It is found in most of the Asian countries. The post processing of turmeric rhizome is done 2 or 3 days after the harvesting. In post processing maintaining the curcumin content in turmeric is important and which is depends upon the methods used for processing the turmeric. The study of improving the turmeric processing is been done. For the drying of turmeric rhizome solar dryer is evaluated which reduces the drying time for turmeric. Post processing of turmeric rhizome involves curing (boiling), drying, polishing, grinding and packaging. This paper involve the information about the post processing of turmeric rhizome. Various methods are used to cure the turmeric and it has various effect on it's quality. A various literature is presented in this paper each has independent and dependent parameter having direct impact on final product. In this paper effort has been taken to understood the various methods used for post processing of turmeric rhizome. It is found that solar drying is the most efficient method for the post processing of turmeric rhizome.
Classifications of Pulsed Plasma Thrusters

1Dept. of Mechanical Engineering, Sinhgad Institute of Technology, Lonavala, Maharashtra, India. 2Dept. of Mechanical Engineering, A.P. Shah Institute of Technology, Maharashtra, India. ----------------------------------------------------------------------***--------------------------------------------------------------------Abstract – The group of pulsed plasma thrusters (PPTs) covers a wide scope of devices, propulsion execution, and level of advancement. A few devices have flown on spacecraft and others are still in the research facility in their improvement stage. All PPT work by ionizing a small amount of the propellent to make a current-conducting plasma. This paper will be investigating 4 kinds of pulsed plasma thrusters and specify the significant or governing factors that influence the choice of PPT's. PPTs use vitality stockpiling to work at a pulsed power level commonly higher than the normal power to the thruster. Plasma thrusters are electromagnetic space devices that make an enormous zone of plasma in transmitting a short arc that is removed to produce energy. Variable character and reliance on yield properties will be shown. PPTs were chosen since they lend themselves well to small satellites because of their solid-state nature. The PPT likewise offers an extremely high specific impulse contrasted with other candidate micro thrusters. The essentials of the PPT propulsion system are depicted and a primer format of the idea is explained.
Immunology of IL-12: An update on functional activities and implications for disease

As its first identified member, Interleukin-12 (IL-12) named a whole family of cytokines. In response to pathogens, the heterodimeric protein, consisting of the two subunits p35 and p40, is secreted by phagocytic cells. Binding of IL-12 to the IL-12 receptor (IL-12R) on T and natural killer (NK) cells leads to signaling via signal transducer and activator of transcription 4 (STAT4) and subsequent interferon gamma (IFN-γ) production and secretion. Signaling downstream of IFN-γ includes activation of T-box transcription factor TBX21 (Tbet) and induces pro-inflammatory functions of T helper 1 (TH1) cells, thereby linking innate and adaptive immune responses. Initial views on the role of IL-12 and clinical efforts to translate them into therapeutic approaches had to be re-interpreted following the discovery of other members of the IL-12 family, such as IL-23, sharing a subunit with IL-12. However, the importance of IL-12 with regard to immune processes in the context of infection and (auto-) inflammation is still beyond doubt. In this review, we will provide an update on functional activities of IL-12 and their implications for disease. We will begin with a summary on structure and function of the cytokine itself as well as its receptor and outline the signal transduction and the transcriptional regulation of IL-12 secretion. In the second part of the review, we will depict the involvement of IL-12 in immune-mediated diseases and relevant experimental disease models, while also providing an outlook on potential translational approaches.
Influence of the chirality of (R)-(-)- and (S)-(+)-carvone in the central nervous system: a comparative study.

Many terpenes are used therapeutically, and as flavor and fragrance materials. (R)-(−)-Carvone, the main constituent of spearmint oil, and (S)-(+)-carvone, found as major component of caraway and dill seed oils, have several applications and are used in cosmetic, food, and pharmaceutical preparations. In this study, the effect of enantiomers of carvone on the central nervous system (CNS) was evaluated in mice. The LD50 value was 484.2 mg/kg (358.9–653.2) for (S)-(+)-carvone, and 426.6 (389.0–478.6) mg/kg for (R)-(−)-carvone. Both enantiomers caused depressant effects, such as decrease in the response to the touch and ambulation, increase in sedation, palpebral ptosis, and antinociceptive effects. (S)-(+)- and (R)-(−)-carvone caused a significant decrease in ambulation. (R)-(−)-Carvone appeared to be more effective than its corresponding enantiomer at 0.5 and 2.0 h after administration. However, (S)-(+)-carvone was slightly more potent at 1 h. In potentiating pentobarbital sleeping time, (R)-(−)-carvone was more effective than (S)-(+)-carvone at 100 mg/kg, but was less potent at 200 mg/kg compared to the (+)-enantiomer, indicating a sedative action. (S)-(+)-Carvone at the dose of 200 mg/kg increased significantly the latency of convulsions induced by PTZ and PIC, but (R)-(−)-carvone was not effective against these convulsions. These results suggest that (S)-(+)-carvone and (R)-(−)-carvone have depressant effect in the CNS. (S)-(+)-Carvone appears to have anticonvulsant-like activity. Chirality, 2007. © 2007 Wiley-Liss, Inc.
The promise of fully-integrated PET/MR imaging: Non-invasive clinical quantification of cerebral glucose metabolism.

A fully-automated processing pipeline is presented to support non-invasive absolute quantification of cerebral metabolic rate of glucose (CMRGlc) in a clinical setting. This pipeline takes advantage of ‘anato-metabolic’ information associated with fully-integrated PET/MR imaging. Methods Ten healthy volunteers (5M/5F, 27 ± 7 years, 70 ± 10 kg) underwent a test-retest 18F-FDG PET/MRI examination of the brain. The imaging protocol consisted of a 60-min PET list-mode acquisition, with parallel MR-acquisitions, including 3D time-of-flight MR-angiography (TOF-MRA), MR-navigators (Nav) and a T1-w MR scan. State-of-art MR-based attenuation correction (MR-AC) was derived from T1-w MRI (pseudo-CT, pCT). For validation purposes a low-dose CT scan was also performed. Arterial blood samples were collected as the reference standard (AIF). The developed pipeline allows the derivation of an Image-derived-input function (IDIF), which is subsequently used to create CMRGlc maps by means of a Patlak analysis. The pipeline also includes motion correction using the Nav-sequence as well as a novel partial volume correction (PVC) that accounts for background heterogeneity. Finally, CMRGlc maps are used to generate a normative database (NDB) to facilitate detection of metabolic abnormalities in future patient scans. To assess the performance of the developed pipeline, IDIFs derived using both CT-AC (CT-IDIF) and MR-AC (pCT-IDIF) were compared against the reference standard of AIF using the absolute percentage difference (|%  |) between the area-under-the-curves (AUCs) (|%  AUC |), as well as |%  | in regional CMRGlc values (|%  CMRGlc |). The |%  AUC | was determined as 1.4 ± 1.0% and 3.4 ± 2.6% for the CT-IDIF and pCT-IDIF, respectively. The |%  CMRGlc | based on CT-IDIF and pCT-IDIF differed by less than 6% from the reference values obtained from the AIF. Taking advantage of the capabilities of fully-integrated PET/MR imaging, a fully-automated computational pipeline was developed that allows non-invasive determination of regional CMRGlc values in a clinical setting. This methodology might facilitate a proliferation of fully-quantitative imaging into the clinical arena and as a result might contribute to improved diagnostic efficacy.
ANTI-PROLIFERATIVE OF THE PHYTOSOME PROPOLIS, PHYTOSOME LYCOPENE AND SYNERGISTIC EFFECT ON THE BENIGN PROSTATIC HYPERPLASIA CELLS IN-VITRO

Propolis and lycopene compounds with potent pharmacological activities as anticancer, anti-inflammatory and antioxidant action. Propolis is a unique product produced by honeybees. Lycopene is phytochemical pigment belong to the group of carotenoids and found in different fruits and vegetative, as well as certain algae and fungi. This study was conducted to prepare and characterize phytosomal propolis and lycopene, then evaluate their in vitro anti-proliferative potential on rats prostatic hyperplasia cell line. Size of the nanoparticles determined by scanning electron microscope were 102.1±5.83 nm for phytosome propolis and 110.4±5.77 nm for phytosome lycopene. The encapsulation and loading efficiencies of phytosome formulations were 80.83 ± 4.41% and 64.66 ± 3.52% respectively for phytosome propolis and 75.82 ± 5.46% and 60.66 ± 4.37% respectively for phytosome lycopene. In order to ascertain the anti-proliferative activity of the phytosomal formulations, MTT assay was carried out on the prostate hyperplasia cells of rats. The half maximal inhibitory concentrations (IC50) of phytosome propolis was 58.46 1⁄4g/ml, phytosome lycopene was 89.74 1⁄4g/ml and their combination was 47.86 on the rats prostate hyperplasia cell line.
Global models for short-term earthquake forecasting and predictive skill assessment

We present rigorous tests of global short-term earthquake forecasts using Epidemic Type Aftershock Sequence models with two different time kernels (one with exponentially tapered Omori kernel (ETOK) and another with linear magnitude dependent Omori kernel (MDOK)). The tests are conducted with three different magnitude cutoffs for the auxiliary catalog ( M 3, M 4 or M 5) and two different magnitude cutoffs for the primary catalog ( M 5 or M 6), in 30 day long pseudo prospective experiments designed to forecast worldwide M ≥ 5 and M ≥ 6 earthquakes during the period from January 1981 to October 2019. MDOK ETAS models perform significantly better relative to ETOK ETAS models. The superiority of MDOK ETAS models adds further support to the multifractal stress activation model proposed by Ouillon and Sornette [J. Geophys. Res.: Solid Earth 110 , B04306 (2005)]. We find a significant improvement of forecasting skills by lowering the auxiliary catalog magnitude cutoff from 5 to 4. We unearth evidence for a self-similarity of the triggering process as models trained on lower magnitude events have the same forecasting skills as models trained on higher magnitude earthquakes. Expressing our forecasts in terms of the full distribution of earthquake rates at different spatial resolutions, we present tests for the consistency of our model, which is often found satisfactory but also points to a number of potential improvements, such as incorporating anisotropic spatial kernels, and accounting for spatial and depth dependant variations of the ETAS parameters. The model has been implemented as a reference model on the global earthquake prediction platform RichterX, facilitating predictive skill assessment and allowing anyone to review its prospective performance.
INVESTIGATION OF CITROBACTER FREUNDII FROM SHEEP USING CULTURAL AND MOLECULAR ANALYSIS

Citrobacter freundii is had an important in medical and economical issues, there are few local studies about it in animals, this study aimed to isolate and identify Citrobacter freundii from others that have a similar biochemical and morphological characteristics. One hundred fecal samples were collected from sheep’s (female and male) in Baghdad city, during december 2019 to Feburury 2020. 25 (25%) of Citrobacter isolates was isolated from the collected fecal samples by using culture media and identified by biochemical tests, antimicrobial susceptibility test was susceptibly to all antibiotic which tested and the identification was confirmed using Vitek 2 compact, polymerase chain reaction (PCR) and sequencing for 16S rRNA and the isolated positively identified as 98% C. freundii by vitke2 and 100% by sequencing when homology with references in Genbank. This study concluded that identification of C. freundii by PCR was in accordance with those of biochemical test and vitke2 it providing a valuable tool for rapid detection of C. freundii in clinical samples from sheep.
EVALUATING THE POTENTIAL OF BOTANICAL EXTRACTS AND FRACTIONS AS SUBSTITUTES OF CHEMICAL ANTIOXIDANTS IN EDIBLE OILS

In this study, extracts of Camellia sinensis (green tea), Trigonella gracecum foenum (fenugreek), Trachyspermum ammi (ajwain), Nigella sativa (black cumin seed), Viola odorata (sweet violet) and green tea fractions were evaluated for substitutes of chemical antioxidant in edible oils. All extracts/fractions were tested for free radical scavenging assay by 1, 1diphenyl-2-picryl hydroxyl (DPPH) in different dilutions. Fenugreek, green tea and ajwain extracts had maximum DPPH values (91.5, 86 and 85.75%) and were significantly better (p<0.05) than others. Each botanical extract/fraction was used (0.1%) in 100 ml samples of soybean, canola, sunflower and fish oil, stored for three months. In canola oil, green tea anthocyanin fraction (GTAF) proved to have least FFA (0.8%) followed by ajwain extracts (1.25%) and both were significantly different (p<0.05) than other antioxidants. FFA values for GTAF were best among extracts used in sunflower oil and soybean oil. After 3 months, canola oil peroxide value (POV) of untreated sample reached to 10.72 meq/kg, which was significantly (p<0.05) reduced by all extracts, especially GTAF (0.85 meq/kg). GTAF was equally leading oxygen scavenger in sunflower oil significantly (p<0.05) reducing POV of untreated oil from 8.65 to 1.65 meq/kg. Soybean and fish untreated oils POV elevated to 11.53 and14.74 meq/kg respectively, which were reduced down by all antioxidant sources used (p<0.05).
ORDINAL OPTIMIZATION WITH GENERALIZED LINEAR MODEL

Given a number of stochastic systems, we consider an ordinal optimization problem to find an optimal allocation of a finite sampling budget, which maximizes the likelihood of selecting the “best” system, where the “best” is defined as the one with the highest mean. The statistical characteristics of each system are described by the generalized linear model, where unknown parameters are estimated using maximum likelihood estimation. To formulate the problem in a tractable form, we use the large deviations theory to characterize the structural properties of the optimal allocation. Further, motivated by Euclidean information theory, we obtain an approximate solution for the optimal allocation, which is leveraged to design a sampling strategy that is near-optimal in a suitable asymptotic sense. The proposed sampling strategy is computationally tractable, and we show via numerical testing that it performs competitively even in the presence of model misspecification.
FINITE HORIZON MARKOV DECISION PROCESS BASED FUZZY OPTIMIZATION FOR RESOURCE ALLOCATION IN SDN ENABLED VIRTUAL NETWORKS IN IAAS CLOUD ENVIRONMENT

Network technologies are dealing with a massive urge to break through the fundamental endorsements of networks. Software-Defined Networking (SDN) has been leading cloud Data Centres (DC's) which states with different policy adaptation for ensuring resource management, concerning about Network Virtualization (NV) performance that is capable of finding the related hardware components to map a Virtual Machine (VM) or a virtual link which represents Virtual Network Embedding (VNE) problem. To overcome the VNE problems our work as proposed a Finite Horizon Markov Decision Process Based Fuzzy Optimization. Fuzzy inference provides an linguistic variables and set of rules to obtain best policy from the available cloud resource and predicts the execution cost for every network function virtualization. This stage also deals with uncertainities and imprecision.Based on the priority and schedulable ability the Finite Horizon Markov Decision Process dynamically allocates the resource for NFV components. Thus, our work obtains a substantial amount of energy utilization by optimizing the use of local host services and will therefore provide greater policy control for physical DCs.
UPTAKE OF COPPER OXIDE NANOPARTICLES BY DIFFERENT TISSUES OF FENUGREEK (TRIGONELLA FOENUM-GRAECUM L.) PLANT

The present study gave a scientific insight about the role of Copper (II) oxides (CuO) nanoparticles (NPS) in the seeds germination of fenugreek (Trigonella foenum-graecum L.) plants when placing them on the surface of solidified Murashige and Skoog (MS) medium supported with (0, 25, 50, 75, 100, 150) 1⁄4g/mL of those particles. The results showed superiority 75 1⁄4g/ml in induced of the seeds germination percentage with 100% after 2 days. The same concentration above has encouraged the best morphological and vegetative growth of the seedlings through the average length of their root and shoot system with 3.5 and 5.0 cm, respectively after 20 days. Also, this study success to initiate hairy roots on seedlings stems segments inoculated by Agrobacterium rhizogenes ATCC15834 with transformation percent reached up to 58.79% after 8 days. Freebacteria hairy roots cultures produced when the hairy roots formed were excised and placed on agar-solidified MS medium contain antibiotic Cefotaxime at 250 mg/L to eliminate bacteria. The Scanning Electron Microscopy (SEM) technique explained the clearly ability of the transgenic hairy roots for uptake those NPS from its medium and accumulated those nanoparticle on their cells surface more than other seedlings tissues.
Deep Learning Approach to Inpainting and Outpainting System

– Recent deep learning primarily based approaches have shown encouraging results on image inpainting for the difficult task of filling in giant missing regions in a picture. These ways will generate visually logical image structures and textures, however, they typically produce distorted structures or hazy textures inconsistent with encompassing areas. This is often in the main thanks to the impotency of convolutional neural networks in expressly borrowing or repeating info from distant abstraction locations. On the opposite hand, ancient texture and patch synthesis approach square measure notably appropriate once it has to borrow textures from the encircling regions. Accidental by these observations, we tend to propose a brand new deep generative model-based approach which might not solely synthesize novel image structures however additionally expressly utilize encompassing image options as references throughout network coaching to create higher predictions. The model may be a feed-forward, absolutely convolutional neural network which might method pictures with multiple holes at discretional locations and with variable sizes throughout the check time. Experiments on multiple datasets as well as faces, textures and natural pictures demonstrate that the planned approach generates higher-quality inpainting results than actual ones.
MULTI-LABEL ROAD SCENE PREDICTION FOR AUTONOMOUS VEHICLES USING DEEP NEURAL NETWORKS

---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract – Autonomous driving systems are becoming popularity nowadays. The detection of road conditions is vital for the efficient working of autonomous vehicles. Internet giants and academic institutes to spice up autonomous driving technologies; while progress has been witnessed in environmental perception tasks, like object detection and driver state recognition, the scene centric understanding and identiﬁcation still remain a virgin land. This mainly encompasses two key issues: the shortage of shared large datasets with comprehensively annotated road scene information and the difﬁculty to ﬁnd effective ways to coach networks concerning the bias of category samples, image resolutions, scene dynamics, and capturing conditions. We propose a multi-label neural network for road scene recognition, which includes both single-and multi-class classiﬁcation modes into a multi-level cost function for training with imbalanced categories and utilizes a deep data integration strategy to enhance the classiﬁcation ability on hard samples. Along side road conditions the situation of the vehicle and lane departure warning system is additionally included for the efficient autonomous system.