Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive Architectures General Principles and Differences

An important component of creating future intelligent systems is a cognitive architecture. In the field of artificial intelligence research of cognitive architectures is important, because, inter alia, cognitive architectures are the contrast to “expert systems”, which means th at cognitive architectures have the goal to cover a broad variety of domains, instead of focalizing the acquisition of capabilities in slim domains. Therefore, this seminar paper considers the general components of three current cognitive architectures: SOAR, PRODIGY, and ICARUS. The Soar cognitive architecture is characterized by its competence in utilizing a broad spectrum of knowledge types and knowledge levels to solve (sub)problems . Prodigy’s main components are the general problem solving module and v arious learning modules. Whereas ICARUS contains modules for conceptual inference, goal choosing, and skill learning. Finally, the architectures’ general components are compared regarding the following properties: representation, organization, utilization, and acquisition and refinement of knowledge.
COMPARISON OF OSMOTIC REGULATION IN DEHYDRATION- AND SALINITY-STRESSED SUNFLOWER SEEDLINGS

Plant dry matter accumulation rate (DMAR), relative water content (RWC), electrolyte leakage percentage (ELP), chlorophyll content, osmotic adjustment ability (OAA), and osmotica accumulation in leaves of sunflower (Helianthus annuus L.) seedlings under different levels of dehydration and salinity stress induced by iso-osmotic PEG (polyethylene glycol) or sodium chloride (NaCl) were evaluated. Plants were subjected to four stress treatments for 10 days: −0.44 MPa PEG6000, −0.44 MPa NaCl, −0.88 MPa PEG6000, −0.88 MPa NaCl. Results showed that PEG and NaCl treatments decreased the plant's DMAR and RWC, and NaCl treatments had more severe inhibitory effect on the plants than PEG treatments. Leaf ELP in sunflower seedlings increased after NaCl and PEG treatments. However, leaf ELP under salt stress was higher than that under dehydration stress (PEG treatment). All stress treatments increased OAA in plant leaves. Leaf OAA was enhanced significantly as PEG concentration increases, while leaf OAA was less enhanced at higher concentration of NaCl. OAA of sunflower leaves under dehydration stress was due to an increase in potassium (K+), calcium (Ca2+), amino acid, organic acid, magnesium (Mg2+), and proline content. OAA of sunflower leaves under moderate salt stress was owing to an increase in K+, chlorine (Cl−), amino acid, organic acid, sodium (Na+), and proline content, and was mainly due to an accumulation of K+, Cl−, Na+, and proline under severe salt stress.
Studying the Impact of the Location of Air-Duct Lines on Methane Distribution and Concentration in Dog Headings

One of the basic issues associated with underground mi ing is providing a safe atmosphere in mine work ings. This includes its chemical composition and reduction of hazardous concentratio ns f harmful gases. In particular, this applies to driven dog headings that have a onesided connection to the central ventilation system in the mine. Therefore, it is necessary to use spec ial ventilation systems in these areas. The widespread current methane hazard present in mine w orkings additionally increases the requirements of these systems. For this reason, the following paper presents the methodology and result s of studies that looked at the ventilation system of driven dog headings. The aim of the study was to determine the impact of the location o f air-duct lines on methane distribution and concen tration in driven dog headings. The basis for the analysis were model studies carried o ut f r the real system and for three additional loc ation variants of air-duct lines forcing fresh air. The studies were carried out for the sam e real parameters of the air stream and methane emi ssion in the studied dog heading. The results clearly show that the location of studied a ir-duct lines has an impact on the distribution and concentration of methane in individual points of the driven dog heading. The study also in cluded the fracture zone as a porous centre around the driven dog heading, which enabled more accurate mapping of real conditions. The resul ts broaden knowledge in the field of ventilation is sues and should be used in practice .
EVALUATING THE NUTRITIVE VALUE AND DIGESTIBILITY OF LOWLAND ACACIA SPECIES AS RUMINANT FEED IN TIGRAY, NORTHERN ETHIOPIA

A study was conducted in Hawzen (Koraro) to evaluate the nutritive potential, digestibility and tannin content of Acacia tree species. Leaf samples were collected during wet season. Conventional chemical analysis procedures in vitro organic matter digestibility were used to determine the nutritional and anti-nutritional content of the Acacia species. A wide variability in chemical composition, digestibility and tannin content was recorded. Crude protein content ranged from 11.64 % to 21.38 %. The content of neutral detergent fiber, acid detergent fiber and acid detergent lignin ranged from 26.46 % to 47.59 %, 21.63% to 43.26% and 2.53 % to 6.06 % respectively and was significantly (p<0.001) different among the species. In vitro organic matter digestibility was highest (70.88 %) in Acacia coli while the lowest (62.59%) in Acacia glaucocaesia. The values reported for tannin content were ranged from 7.90 g/Kg in Acacia pychantha to 42.25 g/Kg in Acacia saligna local. The ranking order of the acacia species on the basis of their crude protein content was A. saligna local (Tigray) > A. glaucocaesia > A. tumida > A. pychantha > A. victoriae > A. coli. The results have shown that the CP content of Acacia species was sufficiently high to warrant consideration of their use as protein supplement to low quality diets. The potential nutritive value of the Acacia species was comparable to other browses and that the species had high digestibility. However, more work especially on animal responses, is needed to affirm the nutritional characteristics reported in this study.
Tra–c Splitting and Its Application to Network-Wise Performance Analysis

Tra–c in a network may split into several streams when passing through an intermediate node, e.g., router or switch. Then one question may arise: what do the resultant tra–c streams become? Trying to answer such question, we characterize the split traf-ﬂc routed by a probabilistic routing algorithm when the input tra–c is modelled by a Markov-modulated Poisson process (MMPP) in this paper. We ﬂnd out that each split tra–c under such splitting mechanism is also an MMPP with a proper parameter modiﬂcation which is investigated in this paper. After having characterized the split tra–c, we apply the result to enable us to get network-wise performance measures, i.e., end-to-end sojourn delay and delay variance in networks employing probabilistic routing algorithms via an approximate approach. With the evidence of numerical experiments, we show that the accuracy for those performance measures remains in an acceptable region. Therefore, such network-wise performance tool may have wide-spread applications in networks, such as the Internet and asynchronous transfer mode (ATM) network.
An Intelligent System for Improving Detection of Diabetic Symptoms in Retinal Images

: - In this paper a contribution towards an automatic detection of diabetic symptoms in retinal images is proposed by synthesizing an intelligent system for retinal image processing in diabetic retinopathies. Image contrast is firstly enhanced by means of a neurofuzzy subsystem, where properly codified fuzzy rules are implemented using a sparsely-connected (4x4)- cell Hopfield-type neural network. Enhanced contrast images are then properly segmented to isolate suspect areas in binary output images after computing the optimally global threshold by a NN-based subsystem. In bipolar output images, suspect diabetic areas are quite satisfactorily isolated. System performances are evaluated by means of an adequate index to provide percentage measures in the detection of eye suspect regions. Results are discussed and successively compared with results from other researchers. Future work is suggested as improvement of the proposed intelligent system for behaving as a diagnostic support tool.
Phosphorus and Potassium Fertilization Effects on Soybean Seed Quality and Composition

The effects of P and K fertilization on soybean [Glycine max (L.) Merr. ] seed quality are unclear. Fertilization rates can have a positive effect on yield and composition in some growing locations and years but not in others. As the cost of soybean seed production increases, seed companies are interested in improving seed quality of soybeans possibly through increased soil fertilization. The objectives of this study were to determine the effect of different levels of P and K fertilization on soybean seed quality defined as seed viability, vigor, and seed composition. Seed samples were obtained from a long-term P and K fertilization trial. Phosphorus and K treatments were 0, 28, or 56 kg P ha−1 yr−1 and 0, 66, or 132 kg K ha−1 yr−1. Results indicated that excessive levels of P and K fertility decreased seed quality. Seed composition changed across sites and treatments, but changes were generally inconsistent. Total seed protein and oil were not significantly affected by P and K fertilization in most locations. However, linolenic acid concentrations increased with excessively high P and K fertilization while linoleic acid concentrations decreased only with P. These results indicate that excessively high levels of soil fertility may have a negatively impacted on seed quality. Disciplines Agricultural Science | Agronomy and Crop Sciences | Plant Biology | Plant Breeding and Genetics Comments This is a mansucript of an article published as Krueger, K. , A. S. Goggi, A. P. Mallarino, and R. E. Mullen. 2013. Phosphorus and Potassium Fertilization Effects on Soybean Seed Quality and Composition. Crop Sci. 53:602-610. doi:10.2135/cropsci2012.06. 0372. Posted with permission. This article is available at Iowa State University Digital Repository: https://lib.dr.iastate.edu/agron_pubs/494 Publisher: AGRONOMY; Journal: CROPSCI:Crop Science; Copyright: Will notify. Volume: Will notify. ; Issue: Will notify. ; Manuscript: C12-06-0372; DOI: 10.2135/cropsci201; PII: TOC Head: ; Section Head: ; Article Type: ARTICLE Page 1 of 15 Phosphorus and Potassium Fertilization Effects on Soybean Seed Quality and Composition Keaton Krueger, A. Susana Goggi,* Antonio P. Mallarino, and Russell E. Mullen
Estimating Dynamic Merger Efficiencies with an Application to the 1997 Boeing-McDonnell

This paper evaluates the welfare effects of the 1997 merger between Boeing and McDonnell Douglas in the medium-sized wide-bodied aircraft industry. I develop an empirical model of multi-product firms, allowing for both learning-by-doing and product innovation in a dynamic game to quantify merger efficiency. Merger efficiency from learning-by-doing is then disentangled from the impact of innovation and the market power effect. The results show that the primary benefits from the 1997 Boeing-McDonnell Douglas merger come from accelerated learning-bydoing. Taking account of all static and dynamic effects, net consumer surplus is found to have increased by as much as $1.57 billion. In contrast, a static model ignoring dynamic learningby-doing and innovation predicts a consumer loss of about $20 billion. These results show that ignoring dynamic effects can lead to biased results and erroneous conclusions with regard to the welfare impact of a merger. ∗I am extremely indebted to my advisors Joseph E. Harrington, Jr., Przemyslaw Jeziorski, and Richard Spady for their continual guidance, support, and encouragement. I am grateful to C. Lanier Benkard for making the labor input data of Lockheed L-1011 available. I deeply appreciate Edmund S. Greenslet, publisher of The Airline Monitor, for numerous inspiring discussions about the aircraft industry and the merger. Also, I would like to thank Yonghong An, C. Lanier Benkard, Yingyao Hu, Elena Krasnokutskaya, Yiyang “Ellen” Li, Jonathan Wright, and participants of seminars at Johns Hopkins University for helpful comments, discussion, and suggestions. All remaining errors are mine. †Department of Economics, Johns Hopkins University, 3400 N. Charles St. Baltimore, MD 21218. Email: weizhao@jhu.edu
Development of techniques for the cultivation of Lessonia trabeculata Villouta et Santelices (Phaeophyceae: Laminariales) in Chile

Large quantities of brown algae have traditionally been exported from Chile as a raw material, of which Lessonia spp. has amounted to over 130 000 tons annually since 1995. To the export demand has recently been added the new demand for high-quality Lessonia spp. as a foodstuff for the expanding abalone culture industry in Chile. The present study is based on efforts to produce significant quantities of Lessonia trabeculata in long-line culture as food for tank-cultured Haliotis rufescens Swainson and Haliotis discus-hannae Ino, which accept it as an excellent source of nutrition. Small sporophytes of L. trabeculata were propagated in the laboratory from reproductive blades harvested by diving near Coquimbo (30°S). The best culture substrate was polyvinyl chloride (PVC) in small pieces, inserted into the nylon cord for final culturing. Enrichment of sea water with agricultural-grade fertilizer produced no differences in growth and development of the Lessonia compared with results obtained using Provasoli medium. Sporophytes 1–2 cm in length cultured on 12-mm cord were transferred to outdoor tanks with circulating sea water and strong aeration where they were outgrown to 15–20 cm length; at this size, they were transferred to a 50-m long line in the ocean. In a 1-year period, individual plants reached up to 1.7 kg in mass, with average values per cord of about 9 kg. Total production from the long line was about 500 kg fresh weight of the alga. In comparative testing, H. discus hannae grew as well on the cultured algae as on naturally occurring L. trabeculata.
Desenvolvimento de um submodelo bicompartimental para estimação da fração digestível da proteína bruta em bovinos a partir da composição química dos alimentos

The objective was to propose and validate a bicompartimental sub model to estimate the apparently digestible crude protein fraction (CPad) in feed offered to cattle in tropical conditions. The two theoretical compartments used as basis for the sub model were crude protein from cell content (CPCC) and crude protein from cell wall (CPCW). Feed content of neutral detergent insoluble protein (NDIP) was used as an analytical approach for CPCW. Evaluations of true digestible fractions of CPCC and CPCW were based on nutritional entity concept and on potential availability from undegradable neutral detergent insoluble protein (UNDIP), respectively. The basic structure of the sub model was: CPad (% DM) = 0.98 × (CP - NDIP) + 0.835 × (NDIP - UNDIP) - 1.61, and CPad (% DM) = 0.98 × (CP - NDIP) + 0.67 × (NDIP - UNDIP) - 0.97 for growing and finishing cattle and lactating dairy cows, respectively. The validation of sub model was made from results of two trials on growing and finishing cattle (eight feeds). The sub model showed estimates similar to those obtained in vivo. Estimates of CPad were also obtained from a previously proposed unicompartimental sub model. Estimates obtained by the bicompartimental sub model were more accurate and precise as compared to unicompartimental sub model.
Gobies from Rhodes and the systematic features of Zebrus zebrus (Teleostei: Gobiidae)

The gobiid fishes of Rhodes are listed from past records and a recent collection made in 1970. Problems of identification and selected diagnostic features are described and illustrated. Additions to the species-list include Chromogobius quadrivittatus, Ch. zebratus levanticus, Millerigobius macrocephalus, and Zebrus zebrus, although a number of productive habitats remain to be explored. The genus Zebrus is redefined, with osteological characters, and its single species, Z. zebrus, redescribed. A comparison with M. macrocephalus tabulates features which may be used to distinguish the two taxa.
Variabilidade genética de duas variedades de tilápia nilótica por meio de marcadores microssatélites

The objective of this work was to evaluate the genetic variability of two Nile tilapia strains (Oreochromis niloticus), Chitralada and Red Stirling, as well as its offsprings submitted to genetic enhancement programs, in intensive systems farming by microsatellites markers. Thirty individuals of each parental strain, 30 crossbred (CH) individuals from Chitralada and Red Stirling strains, and 30 individuals from Red Stirling progeny (RR) were used. Five microsatellites loci were utilized: UNH104, UNH108, UNH118, UNH222 e UNH231. Low values of inbreeding were observed with a negative FIS in both strains and their crossings. Genetic differences between the two strains were detected through FST = 0.131 and RST = 0.130. The parental strains Chitralada and Red Stirling presented 24.4% of genetic distance, which produced 23.5% of hybrid vigor in the CH stock.
Morphological Evidence for an Extended Tribe ‐ Coccocypseleae (Rubiaceae‐Rubioideae)

: Coccocypselum is a small neotropical genus of creeping herbs belonging to the Rubiaceae (Rubioideae). A recent macromolecular study suggested a previously unknown relationship between Coccocypselum and two other neotropical genera, Declieuxia and Hindsia, but the morphological evidence for this relationship was obscure. In the present paper, morphological characters supporting the conclusions from macromolecular data are presented. The most important similarities between Coccocypselum, Declieuxia, and Hindsia are found in their pollen and stipule morphology. Pollen of the three genera share a typical exine ornamentation, called a complex reticulum, which consists of a psilate suprareticulum and spinulate infrareticulum. In some specimens of Hindsia longiflora, a transitional stage between a complex reticulum and a simple, spinulate reticulum is encountered. The interpetiolar stipules of Hindsia, Declieuxia and Coccocypselum have an identical basic structure: they bear a central, colleter-tipped awn that extends downwards to the next node as a distinct stem ridge. Some less conspicuous similarities of habit, calyx, and corolla are also discussed. The morphological data are, in part, confirmed by distributional data, Declieuxia and Hindsia having a remarkably congruent centre of diversity in the southeast of Brazil. It is concluded that the macromolecular data, combined with this new morphological and distributional evidence, justify an extended tribe Coccocypseleae, comprising the genera Coccocypselum, Hindsia, and Declieuxia.
DairyMod and EcoMod: biophysical pasture-simulation models for Australia and New Zealand

DairyMod and EcoMod, which are biophysical pasture-simulation models for Australian and New Zealand grazing systems, are described. Each model has a common underlying biophysical structure, with the main differences being in their available management options. The third model in this group is the SGS Pasture Model, which has been previously described, and these models are referred to collectively as ‘the model’. The model includes modules for pasture growth and utilisation by grazing animals, water and nutrient dynamics, animal physiology and production and a range of options for pasture management, irrigation and fertiliser application. Up to 100 independent paddocks can be defined to represent spatial variation within a notional farm. Paddocks can have different soil types, nutrient status, pasture species, fertiliser and irrigation management, but are subject to the same weather. Management options include commonly used rotational grazing management strategies and continuous grazing with fixed or variable stock numbers. A cutting regime simulates calculation of seasonal pasture growth rates. The focus of the present paper is on recent developments to the management routines and nutrient dynamics, including organic matter, inorganic nutrients, leaching and gaseous nitrogen losses, and greenhouse gases. Some model applications are presented and the role of the model in research projects is discussed.
Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders

Random effect models are popular statistical models for detecting and correcting spurious sample correlations due to hidden confounders in genome-wide gene expression data. In applications where some confounding factors are known, estimating simultaneously the contribution of known and latent variance components in random effect models is a challenge that has so far relied on numerical gradient-based optimizers to maximize the likelihood function. This is unsatisfactory because the resulting solution is poorly characterized and the efficiency of the method may be suboptimal. Here we prove analytically that maximum-likelihood latent variables can always be chosen orthogonal to the known confounding factors, in other words, that maximum-likelihood latent variables explain sample covariances not already explained by known factors. Based on this result we propose a restricted maximum-likelihood method which estimates the latent variables by maximizing the likelihood on the restricted subspace orthogonal to the known confounding factors, and show that this reduces to probabilistic PCA on that subspace. The method then estimates the variance-covariance parameters by maximizing the remaining terms in the likelihood function given the latent variables, using a newly derived analytic solution for this problem. Compared to gradient-based optimizers, our method attains greater or equal likelihood values, can be computed using standard matrix operations, results in latent factors that don’t overlap with any known factors, and has a runtime reduced by several orders of magnitude. Hence the restricted maximum-likelihood method facilitates the application of random effect modelling strategies for learning latent variance components to much larger gene expression datasets than possible with current methods.
A Comprehensive Survey on Outlying Aspect Mining Methods

In recent years, researchers have become increasingly interested in outlying aspect mining. Outlying aspect mining is the task of finding a set of feature(s), where a given data object is different from the rest of the data objects. Remarkably few studies have been designed to address the problem of outlying aspect mining; therefore, little is known about outlying aspect mining approaches and their strengths and weaknesses among researchers. In this work, we have grouped existing outlying aspect mining approaches in three different categories. For each category, we have provided existing work that falls in that category and then provided their strengths and weaknesses in those categories. We also offer time complexity comparison of the current techniques since it is a crucial issue in the real-world scenario. The motive behind this paper is to give a better understanding of the existing outlying aspect mining techniques and how these techniques have been developed.