Miracle-dz/UniFAR-FTUs huggingface dataset:
Impression of (PEO+KBrO3+Plasticizer) Polymer Electrolyte as Carbon Monoxide Gas Sensor

Solid state polymer electrolytes have been prepared by with poly (ethylene oxide) (PEO), KBrO3 salt and plasticizer (Dimethyle Formamide [DMF]) by using solution – casting technique. These polymer electrolytes have been prepared in the weight ratios (90:10), (80:20) and (70:30). The complexations of salt and polymer have been examined by using X-ray diffraction (XRD) and Differential Scanning Calorimetry (DSC). Carbon monoxide gas sensors have been fabricated by using (PEO+KBrO3+Plasticizer) polymer electrolytes and premeditated its sensitivities at various temperatures. The sensitivity of the gas sensor has been observed at various concentrations of carbon monoxide gas.
The Use of Electrophoretic Isozymes to Detect Tungro Infected Rice

Tungro is one of the most common diseases of rice plants which caused by double infection of RTBV (Rice Tungro Bacilliform Virus) and RTSV (Rice Tungro Spherical Virus), and it gives a significant economic loss. These viruses are transmitted by green leaf hopper (Nephottetix virescens. Distant), and the interaction between host plant and the viruses were still quite difficult to be fully understood. In order to look at whether there are any differences between the healthy and tungro infected rice, this study was set to examine the character differences between the infected and the healthy plants based on isozyme banding pattern. The infected plants were collected from three districts around Surakarta (Sragen, Sukoharjo, Klaten) followed by Polyacrilamide Gel Electrophoresis (PAGE) to evaluate the isozyme banding patterns. There were peroxidase, esterase and acid phosphotase isozymes used. The results showed that the real differences of isozyme banding patterns of both healthy and tungro infected plants were discovered. In all cases, the Tungro infected rice had thicker and more band numbers compared to the healthy one. This evident suggested that Tungro infected rice could be detected early using PAGE method.
Improving effectiveness of rock Phosphate through mixing with Farmyard manure , Humic acid and Effective microbes to enhance yield and Phosphorus uptake by wheat

The cheaper rock phosphate (RP) could replace the commercial phosphatic fertilizer with pronounced advantages provided if the solubility and release of P form RP is enhanced through addition of some organic amendments. Combined application of RP with organic materials to soil reduces the dependence on chemical fertilizers and maintains higher levels of P in soil solution for a longer period than the fertilizer alone. Thus the present field study was conducted to investigate the effect of RP treated with farmyard manure (FYM), humic acid (HA) and effective microbes (EM) on the yield and uptake of P by wheat in marginal P calcareous alkaline soil during rabi 2011-12. The treatments was control (T1), 90 kg P2O5 ha -1 as single super phosphate (T2), 90 kg P2O5 ha -1 as RP (T3), RP+ 10 t FYM ha (T4), RP+ 5 kg HA ha (T5), RP+EM (T6), RP+HA+EM (T7), RP+FYM+EM (T8) and RP+FYM+HA+EM (T9) were arranged in a Randomized Complete Block (RCB) design with three replications. The SSP, RP and FYM was applied on soil surface; humic acid was first mixed with the sand and then applied whereas EM was first activated and then applied through spray on the soil surface at 200 L ha. After thorough mixing of treatments with soil, the wheat seeds cv. Atta Habib were sown in lines spacing 25 cm apart through seed drill with seed rate of 120 kg ha. The results showed that the application of RP alone significantly increased the grain yield from 3.74 in control to 4.42 t ha. This effect of RP was further enhanced when combined with FYM, HA, or EM and produced 4.98, 4.6 and 4.8 t grain yield ha, respectively suggesting improvement in P solubility. Among the amendments, FYM was superior to HA or EM but combining HA or EM with mixture of RP+FYM further enhanced the beneficial effect of RP. When RP was applied with FYM+HA+EM the grain yield jumped to the maximum (5.2 t ha ) which was statistically
Exercising During Pregnancy and Labor Outcome

Background: There is a direct link between healthy mothers and healthy infants. Exercise and appropriate nutrition are important contributors to maternal physical and psychological health. The benefits and potential risks of exercise during pregnancy have gained even more attention. Exercise programs remain a way of life for almost one quarter of women planning a pregnancy. The aim was to evaluate the effect of exercising during pregnancy on labor outcomes. Methods: the study used a randomized controlled trial research design. Setting: The study was conducted at the antenatal clinic of Mansoura New General Hospital from April 2017 to April 2019. The study sample was of 104 pregnant females admitted to the antenatal clinic in the previously mentioned setting. Tools: Two tools were used for data collection I: structured interview questionnaire this tool will include two parts: Part one: Demographic data of women (age, level of education, occupation, residence, marital status, and medication in use, etc.). Part two: Antenatal exercising card And Periodical gestational weight gains (GWG). II: Labor outcomes: which include maternal outcome and fetal outcome. Results: showed that, all of the study subjects had exercising during pregnancy with statistically significant correlation with better labor outcome either maternal or fetal. Recommendation, study recommended performing exercises during pregnancy in order to have better labor outcomes
The Multi-model of Peer Relationship from the Perspective of Constructivism

Peers play an important role in the students’ cognitive, emotional and social development. The modern technology, especially the Internet, not only changes different aspects of human life, but adds a new dimension to the peer relationship. Social constructivism attaches great important to the role of peer relationship in individual’s development. This paper researches into constructing peers relationship for learners in the environment of the Internet and other modern media, with a view of providing insights and references for other teachers and related professionals.
Right-wing ideology and numeracy: A perception of greater ability, but poorer performance

Right-wing ideology and cognitive ability, including objective numeracy, have been found to relate negatively. Although objective and subjective numeracy correlate positively, it is unclear whether subjective numeracy relates to political ideology in the same way. Replicating and extending previous research, across two samples of American adults (ns= 455, 406), those who performed worse on objective numeracy tasks scored higher on right-wing authoritarianism (RWA) and social dominance orientation (SDO), and they self-identified as more conservative on general, social, and economic continua. Controlling for objective numeracy, subjective numeracy related positively to measures of right-wing ideologies. In other words, those who strongly (vs. weakly) endorsed right-wing ideologies believed they are good with numbers yet performed worse on numeracy tasks. We discuss implications for the opposing direction of associations between ideology with objective versus subjective numeracy and similarities with literature on overconfidence.
Deep Reinforcement Learning-based Approach to Tackle Competitive Influence Maximization

Competitive Influence Maximization (CIM) problem studies the competition among multiple parties where each party aims to maximize their profit while competing against other parties. Recently, Reinforcement-Learning based models have been proposed to address the CIM problem. However, such models are unscalable and incapable of handling changes in the network structure. Motivated by the recent success of Deep Reinforcement Learning models and their capability to handle complex problems, we propose a novel Deep Reinforcement learning based framework (DRIM) to address the multi-round competitive influence maximization problem. DRIM framework considers the community structure of the social network for budget allocation and feature extraction with deep Q network in order to reduce the computational time of seed selection. The proposed framework employs the quota-based ε-greedy policy to explore the optimality of influence maximization strategies and budget allocation for each community. Experimental results show that the proposed DRIM framework performs better than the state-of-art algorithms to tackle the multi-round CIM problem.
Design and Analysis of Location Cache in a Network-on-Chip Based Multiprocessor System

In recent years, the direction of research to improve the performance of computing systems is focused toward chip multiprocessor (CMP) designs with multiple cores and shared caches integrated on a single chip. To meet the increased demand for data, large on-chip caches are being embedded on the chip, shared between the multiple cores. The traditional bus-based interconnect architectures are non-scalable for large caches and cannot support the higher cache demand from multiple cores, which motivates the design of a network-on-chip (NoC) interconnect structure for shared non-uniform cache architecture (NUCA). The concept of NUCA caches proposes the division of the cache into multiple banks connected by a switched network that can support the simultaneous transport of multiple packets. The larger on-chip cache designs also result in higher power consumption which is a serious concern as fabrication scales down to the nano-technologies. This research focuses on the implementation of the location cache design in a NoC-based NUCA system with multiple cores, in combination with low-leakage L2 cache based on the gated-ground technique. This system architecture helps to reduce the power of L2 cache along with the performance benefit of the on-chip network. The CMP cache system is implemented on a NoC-NUCA framework with a write-through coherency protocol. The features of CACTI and GEMS are extended to support a complete power and performance estimation of the system. A full-system simulation is performed on scientific and multimedia workloads to characterize the NoC-based system. An analysis of the power and performance of the proposed system is presented in comparison with the traditional cache structure in different configurations. The simulation results show that the NoC-based system with the location cache results in significantly saving the energy of the cache system over the traditional bus-based system in any configuration and also the NoC-based system without a location cache. The system also provides better performance compared to a bus-based system, emphasizing the need to shift to a network-based cache interconnect design which can scale to a large number of cores.
PHYSICO-CHEMICAL PROPERTIES OF SOME LISTERIA PHAGES [ 16 ]

Listeria monocytogenes is a food borne pathogenic bacteria and caused a dangerous infection of humans. Six lytic bacteriophages specific to L. monocytogenes were isolated from irrigation and sewage waters and named ØLG, ØLA, ØLM, ØLD, ØLN and ØLP. The phages were propagated, and then purified by the ultracentrifugation. Morphological properties of Listeria phages showed that the phages were tailed phages, varied in their sizes and assigned to be a member of Siphoviridae (ØLG, ØLA, ØLM) and Myoviridae (ØLN, ØLD, ØLP) families. All Listeria phages were highly stable under different temperature conditions and its thermal inactivation point was reached to 80°C. The longevity in vitro of the phages was up to 60 days, as well as phages were active at pH values ranging from 4.0 to 12.0. Listeria phages did not lose their infectivity after exposure to UV for 90 min at 35 and 53 cm distances. Results of SDS-PAGE showed that phages had 5-6 protein fragments with molecular weights of 66, 45, 37, 35, 33 and 28 kDa distributed among the six phages.
Endosomes are membrane-bound organelles that transport protein and lipid components internalized from the plasma membrane to be degraded in lysosomes or recycled back to the plasma membrane via early endosomes or recycling

Cytohesin-2 is a member of the guanine nucleotide exchange factors for ADP ribosylation factor 1 (Arf1) and Arf6, which are small GTPases that regulate membrane traffic and actin dynamics. In this study, we first demonstrated that cytohesin-2 localized to the plasma membrane and vesicles in various subcellular compartment in hippocampal neurons by immunoelectron microscopy. Next, to understand the molecular network of cytohesin-2 in neurons, we conducted yeast twohybrid screening of brain cDNA libraries using cytohesin-2 as bait and isolated pallidin, a component of the biogenesis of lysosome-related organelles complex 1 (BLOC-1) involved in endosomal trafficking. Pallidin interacted specifically with cytohesin-2 among cytohesin family members. Glutathione S-transferase pull-down and immunoprecipitation assays further confirmed the formation of a protein complex between cytohesin-2 and pallidin. Immunofluorescence demonstrated that cytohesin-2 and pallidin partially colocalized in various subsets of endosomes immunopositive for EEA1, syntaxin 12, and LAMP2 in hippocampal neurons. Knockdown of pallidin or cytohesin-2 reduced cytoplasmic EEA1-positive early endosomes. Furthermore, knockdown of pallidin increased the total dendritic length of cultured hippocampal neurons, which was rescued by co-expression of wild-type pallidin but not a mutant lacking the ability to interact with cytohesin-2. In contrast, knockdown of cytohesin-2 had the opposite effect on total dendritic length. The present results suggested that the interaction between pallidin and cytohesin-2 may participate in various neuronal functions such as endosomal trafficking and dendritic formation in hippocampal neurons.
NICT’s Unsupervised Neural and Statistical Machine Translation Systems for the WMT19 News Translation Task

This paper presents the NICT’s participation in the WMT19 unsupervised news translation task. We participated in the unsupervised translation direction: German-Czech. Our primary submission to the task is the result of a simple combination of our unsupervised neural and statistical machine translation systems. Our system is ranked first for the German-to-Czech translation task, using only the data provided by the organizers (“constraint’”), according to both BLEU-cased and human evaluation. We also performed contrastive experiments with other language pairs, namely, English-Gujarati and English-Kazakh, to better assess the effectiveness of unsupervised machine translation in for distant language pairs and in truly low-resource conditions.
Effect of Zinc Levels and Moisture Regimes on Yield and Economics of Direct Seeded Rice

A field experiment was conducted during rainy (kharif) season of 2017 in Split Plot Design with three replications at Crop Research Centre of Dr. Rajendra Prasad Central Agricultural University, Pusa, Bihar.The treatments consisted of four moisture regimes in main plots and four zinc levels in sub plots. The result showed that among the moisture regime treatments ,maximum value for no. of panicles/m (225.58), grain yield (33.14q/ha),harvest index (41.30%),gross return (70193 ₹/ha) was found with I1which was significantly superior over I3 and I4 but was statistically at par with I2 but maximum value for water productivity (3.51 ₹/m ), net return (34067 ₹/ha) and B:C ratio (0.99) was found with I2which was significantly superior over I4but was statistically at par with I1 and I3except water productivity which was significantly superior over I1 and I4 but was at par with I3. Test weight was not influenced significantly by moisture regime treatments. In context of sub-plot treatments maximum no.of panicles/m(223.87), grain yield (32.57 q/ha), harvest index (41.23 %), water productivity (3.46 ₹/m), gross return (69048 ₹/ha), net return (33464 ₹/ha) and B:C ratio (0.94) was found with Z3which was significantly superior over Z1 but was statically at par with Z2 and Z4 except gross return which was superior over Z1 and Z4 but statistically at par with Z2.Test weight was not influenced significantly by zinc levels.
Clustering with Outliers in a Biased Animal Movement Database

By putting accelerometers on horses, data was collected that can be classified into different behavioural patterns. Examples are ”walking”, ”resting”, ”running-rider”, and ”running-natural”. In order to study the behaviour of horses and investigate the structure of the data, the data has to be grouped according to these different behaviours. This research focused on grouping the horse data by means of clustering. Clustering is an unsupervised procedure to group data based on similarity. Unsupervised means that the clustering algorithm does not have classified (or labeled) data to train with. Finding the correct clustering algorithm is a challenge because the database is large, and the data is high-dimensional (21 dimensions). Furthermore, the data itself is biased. Most of the samples represent the horse trotting with a rider, and there are little samples available of other behaviour such as the horse shaking. Due to the small amount of samples for this behaviour, the algorithm could identify these samples as outliers (deviations from normal patterns) and remove them. In this research two algorithms were identified for clustering large and high-dimensional data: DBSCAN and OPTICS. The performance of the algorithms was evaluated using the V-measure. The algorithms were also assessed for biases towards clustering larger or smaller clusters as outliers, or clustering samples wrongly (False Negatives). After performing the tests, it was found that with the chosen parameter values, DBSCAN performed better. Although OPTICS had a far smaller percentage of False Negatives (21 percent per class on average compared to the 61 percent of DBSCAN), this could be explained by the high percentages of outliers that OPTICS had. DBSCAN was, in other words, better at identifying outliers. Furthermore, it had a higher V-measure (1 is the most desirable) with 0.512, whereas OPTICS had a V-measure value of 0.304. Further improvement of the performances can be achieved through extended parameter optimization.
Tuning word embeddings for neural dependency parsing of Norwegian

In the recent years, data driven dependency parsers using neural networks have been developed and show promising results in parsing accuracy. Another area that has seen an increase in interest among researchers is using distributional semantics in the form of word embeddings as input features in dependency parsers, replacing traditional feature engineering. No previous research has been done on systematically tuning of word embeddings for neural network parsing of Norwegian. We present the results of tuning word embeddings for the task of neural network dependency parsing of Norwegian. We also present the results of comparing the performance of word embeddings in dependency parsers, to their performance in intrinsic evaluation metrics.
Electronic structures and thermodynamic properties of HfAl 3 in L 1 2 , D 0 22 and D 0 23 structures

To better understand the relative stability and bonding characteristics of the L12, D022 and D023 structures for HfAl3, the formation enthalpies, electronic structures and thermodynamics properties were investigated by first-principles calculations. The agreement of calculated equilibrium lattice parameters and formation enthalpies with experimental results indicates the reliability of this work. The order of structural stability is D023>D022>L12. The results of densities of states, atomic Mulliken charge and bond population support the best structural stability for D023 structure. Variations of thermodynamic properties with temperature were predicted via phonon frequencies calculation. The enthalpy, entropy, free energy of D023 structure change more quickly than those of the other two structures. The Debye temperatures of L12, D022 and D023 structures are 399, 407 and 416 K, respectively. The volume thermal expansions for HfAl3 increase exponentially at the low temperature, whereas the thermal expansion coefficients increase linearly at the high temperature.
Teaching-learning Practical Wisdom (Phronesis) in Administration: A Systematic Review

The purpose of this systematic review is to investigate how the concept of phronesis is related to education, teaching and learning in the area of Administration and organizational studies. Phronesis is defined as practical wisdom, or prudence, present in processes of deliberation, decision and action. The search for articles on Scopus, Ebsco and Web of Science found 37 articles on the subject. The analysis of these works reveals the most referenced authors, the main definitions and the main research topics regarding teaching and learning in Administration. It is approached according to five main definitions: (a) disposition for judgment or deliberation; (b) perception of context and real situation; (c) type of practical knowledge; (d) phronetic social science, and, (e) multiple definitions. The themes are: (a) Teaching and curriculum related to Administration and business ethics; (b) teacher education and training; (c) teaching and elements of phronesis; (d) philosophy of education and phronesis; (e) occupations and other higher education; and, (f) early childhood education. Its relationship with the moral virtues could be more explored, since definitions related to experiential learning predominate. Future studies could discuss practices, praxis, and action-oriented approaches.