Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of crop loss due to turcicum leaf blight caused by Exserohilum turcicum (Pass.) Leonard and Suggs in maize.

The field trials on crop loss estimation due to turcicum leaf blight in maize were carried out during kharif seasons of 2003 and 2004. Significant loss in grain yield, stover yield, test weight and reduction in plant height, cob length, cob diameter and shelling percentage was observed in unprotected treatments in all the genotypes tested as compared to protected treatments. The avoidable yield loss in various genotypes ranged from 2.87 to 51.93 per cent with a mean of 14.51 per cent. The losses were directly proportional to the disease severity. The yield and yield attributing parameters showed a progressive increasing trend with an increase in number of fungicide sprays. Significant and negative correlation was established between blight severity under various spray schedules and grain as well as stover yields in both the years. This relationship was expressed by simple linear regression model.
Distillation Applied to the Processing of Spirits and Aromas

3.1 Fundamentals of Distillation 76 3.1.1 Main Concepts in the Distillation Processes 76 3.1.2 Heat and Mass Balance Equations in Distillation Processes 82 3.1. 3 Vapor–Liquid Phase Equilibrium 86 3.2 Recent Advances in the Simulation of Spirits and Aroma Mixtures Distillation 97 3.3 Some Especial Applications of Distillation 101 3.3.1 Obtaining High Quality Cachaca 101 3.3.1.1 Batch Distillation in Alembic 102 3.3.1.2 Continuous Distillation in Tray Columns 109
Effects of different potassium and iron levels on seasonal changes of nutrient concentrations of tomato plant grown in soilless culture

Potassium and iron are the main elements that are of great importance in soilless medium in terms of tomato nutrition. However, the activities of plant nutrients are very complex and changes depending on growing stage, environmental condition and element concentrations in nutrient solution. It is necessary to have more information about the combination of K and Fe in different growing stages in soilless culture. Therefore, this study was carried out to determine the effects of different levels of potassium and iron applications on seasonal changes of plant nutrient concentrations of tomato plant grown in soilless culture. For this purpose, treatments were defined by a factorial combination of three potassium (150, 300 and 450 mg L-1) and three iron levels (1, 2 and 3 mg L-1) with 4 replicates. The leaf samples were taken in two periods [26 November 2006 (fruit set), 15th March 2007 (harvest time)] thereby seasonal changes of plant nutrient concentrations were investigated. The evidences provided by this experiment indicated that the different potassium and iron applications had significant effects on plant nutrient concentration of tomato leaves except P and Mn concentration of 2nd periods. High level of K and Fe applications caused antagonistic effect on nutrient uptake and resulted in imbalance on mineral nutrition of tomato plants. Potassium (K), magnesium (Mg), iron (Fe), zinc (Zn), manganese (Mn) and copper (Cu) concentrations of tomato leaves showed seasonal changes by K and Fe applications. While tomato leaves K, Zn and Mn concentrations were decreasing from fruit set to harvest time, Mg, Fe and Cu concentrations were increased. Key words: Tomato, perlite, potassium, iron, seasonal changes, plant nutrient.
ADAPTIVE EVOLUTION AND PHYLOGENETIC UTILITY OF ACR (ACROSIN), A RAPIDLY EVOLVING MAMMALIAN FERTILIZATION GENE

Abstract Many genes involved in reproduction have evolved at a rapid rate in diverse taxonomic groups. We use new data for the mammalian reproductive gene that encodes acrosin to document patterns of adaptive evolution and rapid divergence. Likelihood scores for neutral and selection models indicate that molecular evolution of the Acr gene is driven by positive selection. Comparisons of Acr sequences to mitochondrial genes and a nuclear intron show that reproductive genes can be informative phylogenetic markers. In bovid artiodactyls (cattle, sheep, goats, and antelopes), exon 5 of Acr is highly variable, is characterized by a low level of homoplasy, and has a fairly even spread of substitutions across the 3 codon positions. Impressive congruence with independent DNA data sets suggests that Acr, and perhaps additional rapidly evolving reproductive molecules, show promise for resolving evolutionary radiations of mammals.
Influences of Maternal Vulnerability and Antidepressant Treatment during Pregnancy on the Developing Offspring

Maternal vulnerability to adversity has long-term impact on the developing child. About 20% of the pregnant women suffer from affective disorders. Fetal exposure to maternal adversity may lead to detrimental consequences later in life. Maternal affective disorders are increasingly treated with antidepressants, especially selective serotonin reuptake inhibitors (SSRIs). However, the long-term consequences for the offspring after exposure to this medication are unclear. The interplay between maternal adversity and SSRI treatment has been under investigation and here we discuss how maternal adversity and SSRIs are able to shape offspring development. Specifically, we will discuss animal models addressing behavioral outcomes to understand how the prenatal environment influences the health of the developing child across the life span.
Estimating true instead of apparent survival using spatial Cormack–Jolly–Seber models

Survival is often estimated from capture–recapture data using Cormack–Jolly–Seber (CJS) models, where mortality and emigration cannot be distinguished, and the estimated apparent survival probability is the product of the probabilities of true survival and of study area fidelity. Consequently, apparent survival is lower than true survival unless study area fidelity equals one. Underestimation of true survival from capture–recapture data is a main limitation of the method. We develop a spatial version of the CJS model that allows estimation of true survival. Besides the information about whether a specific individual was encountered at a given occasion, it is often recorded where the encounter occurred. Thus, information is available about the fraction of dispersal that occurs within the study area, and we use it to model dispersal and estimate true survival. Our model is formulated hierarchically and consists of survival, dispersal and observation submodels, assuming that encounters are possible anywhere within a study area. In a simulation study, our new spatial CJS model produced accurate estimates of true survival and dispersal behaviour for various sizes and shapes of the study area, even if emigration is substantial. However, when the information about dispersal is scarce due to low survival, low recapture probabilities and high emigration, the estimators are positively biased. Moreover, survival estimates are sensitive to the assumed dispersal kernel. We applied the spatial CJS model to a data set of adult red‐backed shrikes (Lanius collurio). Apparent survival of males (c. 0·5) estimated with the CJS model was larger than in females (c. 0·4), but the application of the spatial CJS model revealed that both sexes had similar survival probabilities (c. 0·6). The mean breeding dispersal distance in females was c. 700 m, while males dispersed only c. 250 m between years. Spatial CJS models enable study of dispersal and survival independent of study design constraints such as imperfect detection and size of the study area provided that some of the dispersing individuals remain in the study area. We discuss possible extensions of our model: alternative dispersal models and the inclusion of covariates and of a habitat suitability map.
A Privacy-Preserving Online Learning Approach for Incentive-Based Demand Response in Smart Grid

Incentive-based demand response (IDR) programs enable smart grid customers to participate in the demand reduction, triggered by system contingencies or peak load, to improve reliability, sustainability, security, and efficiency of the power grid. However, the deployment of smart meters and the increasing number of customers in IDR programs make the data generated in the smart grid at a large scale. Meanwhile, fine-grained data from smart meters can deluge customers’ lifestyle and usage pattern, posing threat to customer privacy. Therefore, privacy-preserving demand source management techniques that support increasingly large-scale datasets are in urgent need. In this paper, we propose an online privacy-preserving IDR management system, in which social welfare is maximized through recommending the optimal consumer to the utility company. Since the contexts of electricity curtailment offers from the utility company are different, an adaptive context partition method is proposed to enable the system context awareness. In addition, we cluster the customers in a tree structure to make the analyses of the customers in the cluster level and thus enable the algorithm to support the large-scale system. Furthermore, a tree-based noise aggregation method is applied to guarantee both the differential privacy of customers’ sensitive information and the utility of the data. Theoretical analysis shows that our proposal guarantees differential privacy of customers, while converging to the optimal policy in a long run. Numerical results validate that our proposed algorithm supports the large-scale dataset while striking a balance between the privacy-preserving level and social welfare.
Geometric properties of satisfying assignments of random $\epsilon$-1-in-k SAT

We study the geometric structure of the set of solutions of random $\epsilon$-1-in-k SAT problem. For $l\geq 1$, two satisfying assignments $A$ and $B$ are $l$-connected if there exists a sequence of satisfying assignments connecting them by changing at most $l$ bits at a time. We first prove that w.h. p. two assignments of a random $\epsilon$-1-in-$k$ SAT instance are $O(\log n)$-connected, conditional on being satisfying assignments. Also, there exists $\epsilon_{0}\in (0,\frac{1}{k-2})$ such that w.h. p. no two satisfying assignments at distance at least $\epsilon_{0}\cdot n$ form a "hole" in the set of assignments. We believe that this is true for all $\epsilon >0$, and thus satisfying assignments of a random 1-in-$k$ SAT instance form a single cluster.
The US as the â€œdemander of last resortâ€ and its implications on Chinaâ€™s current account

This paper evaluates the degree to which current account patterns are explained by the variables suggested by the literature, and reflects on possible future patterns. We start with panel regressions explaining the current account of 69 countries during 1981-2006. We identify an asymmetric effect of the US as the â€œdemander of last resort:â€ a 1% increase in the lagged US imports/GDP is associated with 0.3% increase of current account surpluses of countries running surpluses, but with insignificant changes of current account deficits of countries running deficits. Overall, the panel regressions account for not more than 4/5 of the variation. We apply the regression results to assess Chinaâ€™s current account over the next six years, projecting a large drop in its account/GDP surpluses.
On Crepidostomum farionis O. F. Müll. (= Stephanophiala laureata Zeder), a Distome Parasite of the Trout and Grayling. I. The Life History

1. Crepidostomum farionis inhabits the gall bladder, as well as the intestine and pyloric caeca, of the trout and grayling. 2. The life history of Crepidostomum farionis has been worked out and is based on the similarity of organisation of the cercaria, encysted larval trematode and the adult. 3. The first intermediate hosts in the life history of this trematode are Pisidium amnicum (Müll.) and Sphaerium corneum (L.) though the latter is unusual. 4. The second intermediate host is the larva of the mayfly, Ephemera danica (Müll.). 5. There are two generations of rediae, the first gives rise to daughter rediae, which in turn produce cercariae. 6. The rediae are characterised by the absence of ambulatory processes and a functional intestine. 7. The cercaria (n.sp.) possesses “eye spots,” stylet and gland cells (salivary? ), and the excretory vesicle is tube-shaped. 8. The excretory system of the redia and the cercaria has been worked out in detail. 9. The relation of the parasites to their respective hosts is discussed. On account of the need for further observations definite conclusions are held over for a later paper.
A QoE-Driven Traffic Steering Algorithm for LTE Networks

Due to the diversity of mobile services and raising user expectations, mobile network management has changed its focus from Quality of Service (QoS) to Quality of Experience (QoE). As a consequence, classical network optimization procedures must be updated accordingly. One of these procedures is traffic sharing, whose aim is to redistribute traffic among adjacent cells so as to provide an adequate QoE to subscribers. In this work, a novel QoE-driven traffic sharing algorithm based on mobility load balancing is proposed for LTE networks offering services of very different nature. Unlike previous approaches, where the aim was to balance some QoS indicator, the aim here is to equalize the QoE provided by all cells in the network. For this purpose, the handover margins between adjacent cells are tuned on a per-adjacency or per-service basis based on QoE measurements collected in the network management system. Method assessment is based on a dynamic system-level simulator implementing a realistic LTE scenario. Results show that the proposed QoE-driven traffic sharing algorithm alleviates QoE problems by equalizing user QoE throughout the scenario.
NoiseModelling: An Open Source GIS Based Tool to Produce Environmental Noise Maps

The urbanisation phenomenon and related cities expansion and transport networks entail preventing the increase of population exposed to environmental pollution. Regarding noise exposure, the Environmental Noise Directive demands on main metropolis to produce noise maps. While based on standard methods, these latter are usually generated by proprietary software and require numerous input data concerning, for example, the buildings, land use, transportation network and traffic. The present work describes an open source implementation of a noise mapping tool fully implemented in a Geographic Information System compliant with the Open Geospatial Consortium standards. This integration makes easier at once the formatting and harvesting of noise model input data, cartographic rendering and output data linkage with population data. An application is given for a French city, which consists in estimating the impact of road traffic-related scenarios in terms of population exposure to noise levels in relation to both a threshold value and level classes.
Cochlear implant: On the number of channels

1 University Claude-Bernard Lyon1, 43 bd du 11 Novembre, Villeurbanne-Cedex 69622, France 2 Lyon neuroscience Research Center, (CRNL), INSERM U1028, 95 bd Pinel, Bron-Cedex 69675, France 3 ENT Department, Edouard-Herriot Hospital, 5 place d’Arsonval 69437 Lyon cedex 03, France 4 IFSTTAR, 25 Avenue François Mitterrand, 69500 Bron, France 5 Sensory and Cognitive Neuroscience Laboratory (LNSC), CNRS UMR 7260, Université d’Aix-Marseille, France
Helical structure of longitudinal vortices embedded in turbulent wall-bounded flow

), have been studied with respectto helical symmetry. The studies were carried out in a low-speed closed-circuit windtunnel utilizing stereoscopic particle image velocimetry (SPIV). The vortices havebeen shown to possess helical symmetry, allowing the ﬂow to be described in a simplefashion. Iso-contour maps of axial vorticity revealed a dominant primary vortexand a weaker secondary one for 20
MVAE: Multimodal Variational Autoencoder for Fake News Detection

In recent times, fake news and misinformation have had a disruptive and adverse impact on our lives. Given the prominence of microblogging networks as a source of news for most individuals, fake news now spreads at a faster pace and has a more profound impact than ever before. This makes detection of fake news an extremely important challenge. Fake news articles, just like genuine news articles, leverage multimedia content to manipulate user opinions but spread misinformation. A shortcoming of the current approaches for the detection of fake news is their inability to learn a shared representation of multimodal (textual + visual) information. We propose an end-to-end network, Multimodal Variational Autoencoder (MVAE), which uses a bimodal variational autoencoder coupled with a binary classifier for the task of fake news detection. The model consists of three main components, an encoder, a decoder and a fake news detector module. The variational autoencoder is capable of learning probabilistic latent variable models by optimizing a bound on the marginal likelihood of the observed data. The fake news detector then utilizes the multimodal representations obtained from the bimodal variational autoencoder to classify posts as fake or not. We conduct extensive experiments on two standard fake news datasets collected from popular microblogging websites: Weibo and Twitter. The experimental results show that across the two datasets, on average our model outperforms state-of-the-art methods by margins as large as ~ 6% in accuracy and ~ 5% in F1 scores.
Network Intrusion Classification Employing Machine Learning: A Survey

In this modern era computer network security is a vital issue. Network security is developed by an efficient Intrusion Detection System (IDS). It is used to identify unauthorized access, malicious attacks and give an alert when monitors any kind of unusual activity. Over the past 30 years, there have been lots of work on intrusion detection system using machine learning algorithms. Basically, realizing the present status of application of machine learning algorithms for solving intrusion classification task, this review work gives a proper guideline. This survey work selected 84 papers based on highest citations number from the years of 2009-2018. This thesis work gives an overview of a different intrusion detection systems, a statistical comparison based on different classifier like single, hybrid and ensemble learning. In addition, we have discussed best machine learning classifiers, best datasets and some feature selections process in this thesis work. This work is devoted to our mother and father. Acknowledgements First of all, we would like to thank our thesis supervisor Dr. Dewan Md. Farid, Associate Professor, Department of Computer Science and Engineering, United International University (UIU). Without his help it was impossible for us to complete this thesis work. His positive efforts towards us and pushing us to our limits were the only reason that we have made it till here. We would like to thank Dr. Swakkhar Swatabda, Associate professor, Department of Computer Science and Engineering, United International University (UIU). We would also want to thank our loving United International University (UIU).
Network Anomaly Detection by Means of Machine Learning: Random Forest Approach with Apache Spark

Nowadays the network security is a crucial issue and traditional intrusion detection systems are not a sufficient way. Hence the intelligent detection systems should have a major role in network security by taking into consideration to process the network big data and predict the anomalies behavior as fast as possible. In this paper, we implemented a well-known supervised algorithm Random Forest Classifier with Apache Spark on NSL-KDD dataset provided by the University of New Brunswick with the accuracy of 78.69% and 35.2% false negative ratio. Empirical results show this approach is well in order to use for intrusion detection system as well as we seeking the best number of trees to be used on Random Forest Classifier for getting higher accuracy and lower cost for the intrusion detection system.
Effect of nerve growth factor on colorectal visceral hypersensitivity in rats

Objective To study the potential role of nerve growth factor(NGF)on visceral hypersensitivity in rats.Methods Visceral hypersensitivity was induced by intraperitoneal injection of NGF with or without water avoidance stress in N group(n=8)and NW group(n=8),respectively.The rats in controI group(n=8)were intraperitoneaIly injected with normal saline and received shame water avoidance stress.Electromyogram activity of the external oblique musculature was measured by means of the visceromotor response(VMR)during colorectal distention(CRD). Statistical analysis was made by ANOVA.Results There was,nb statistical difference among three groups in the VMR at pressure of 20,40 or 60 mmHg(1 mmHg=0.133 kPa). When the pressure at 80 mmHg,the VMR was higher in NW group(3.54)than that in control group(2.12)(P=0.016). while it was 2.62 in N group with no difference to control group.Conclusion The colorectal visceral sensitivity in rats may be promoted by NGF in presence of water avoidance stress. Key words: Nerve growth factor; Visceral hypersensitivity; Stress; Visceromotor response
Age trends in economically important traits of Merino ewes subjected to 10 years of divergent selection for multiple rearing ability

Data were recorded for annual reproduction, wool traits and pre-joining live weight of between 992 (for staple strength) to approximately 1200 production records of Merino ewes over the period from 1997 to 2002. The resource population has been divergently selected from the same base since 1986, either for (H line) or against (L line) maternal multiple rearing ability. When expressed relative to mean L line performance, the advantage in reproduction for the H line amounted to 34% for number of lambs born per ewe, 49% for number of lambs weaned per ewe and 56% for weight of lamb weaned per ewe. Overall trends in reproduction with an increase in age from 2 - 7+ years were consistent with corresponding trends in the literature. The shape of these curves did not differ between selection lines, i.e. no significant interaction between selection line and ewe age was found. Maiden H line ewes were heavier than L line contemporaries. Ewe joining weight increased with age in both lines. Line differences were reduced to a tendency in 3-year old ewes, and no subsequent line differences were found. The random non-linear component of the spline for ewe age also interacted with selection line for clean fleece weight. Conclusive advantages in favour of L line ewes were obtained at 3 - 6 years of age. In maiden ewes the line difference was restricted to a tendency in favour of the L line while no line difference occurred in 7-year old ewes. Ewes in the L line outperformed H line contemporaries for staple strength at four years of age, but no line difference was found at other ages. Coefficient of variation of fibre diameter and mean fibre diameter did not differ between lines. Coefficient of variation of fibre diameter generally declined curvi-linearly with an increase in ewe age, while fibre diameter showed a near linear increase. Estimates of h² for reproduction traits were 0.09±0.05 for number of lambs born per ewe, 0.05±0.05 for number of lambs weaned per ewe, and 0.05±0.05 for weight of lamb weaned per ewe. Corresponding h² estimates for wool traits were 0.34±0.08 for clean fleece weight, 0.05±0.05 for staple strength, 0.74±0.02 for coefficient of variation and 0.76±0.02 for fibre diameter. A h² estimate of 0.37±0.09 was obtained for ewe live weight at joining. Ewe permanent environment (c²ewe) for the reproduction traits were 0.15±0.05 for number of lambs born per ewe, 0.19±0.05 for number of lambs weaned per ewe and 0.19±0.05 for weight of lamb weaned per ewe. The corresponding c²ewe estimate for ewe joining weight was 0.40±0.09, while those for annual wool production traits were 0.31±0.08 for clean fleece weight and 0.12±0.05 for staple strength. Coefficient of variation and mean fibre diameter were not influenced by the ewe permanent environment. Line differences in age trends for wool traits and ewe joining weight were attributed to the drainage by reproduction on the reserves of H line ewes.