Miracle-dz/UniFAR-FTUs huggingface dataset:
Bacterial parasite of a plant nematode: morphology and ultrastructure

The life cycle of a bacterial endoparasite of the plant-parasitic nematode Meloidogyne incognita was examined by scanning and transmission electron microscopy. The infective stage begins with the attachment of an endospore to the surface of the nematode. A germ tube then penetrates the cuticle, and mycelil colonies form in the pseudocoelom. Sporulation is initiated when terminal cells of the mycelium enlarge to form sporangia. A septum within each sporangium divides the forespore from the basal or parasporal portion of the cell. The forespore becomes enclosed by several laminar coats. The parasporal cell remains attached to the forespore and forms the parasporal microfibers. After the newly formed spores are released into the soil, these microfibers apparently enable a mature spore to attach to the nematode. These results indicate that the endoparasite is a procaryotic organism having structural features that are more common to members of Actinomycetales and to the bacterium Pasteuria ramosa than to the sporozoans or to the family Bacillaceae, as previous investigatios have concluded.
Calcium/Calmodulin Modulation of Olfactory and Rod Cyclic Nucleotide-gated Ion Channels*

Cyclic nucleotide-gated (CNG) ion channels mediate sensory transduction in olfactory sensory neurons and retinal photoreceptor cells. In these systems, internal calcium/calmodulin (Ca2+/CaM) inhibits CNG channels, thereby having a putative role in sensory adaptation. Functional differences in Ca2+/CaM-dependent inhibition depend on the different subunit composition of olfactory and rod CNG channels. Recent evidence shows that three subunit types (CNGA2, CNGA4, and CNGB1b) make up native olfactory CNG channels and account for the fast inhibition of native channels by Ca2+/CaM. In contrast, two subunit types (CNGA1 and CNGB1) appear sufficient to mirror the native properties of rod CNG channels, including the inhibition by Ca2+/CaM. Within CNG channel tetramers, specific subunit interactions also mediate Ca2+/CaM-dependent inhibition. In olfactory CNGA2 channels, Ca2+/CaM binds to an N-terminal region and disrupts an interaction between the N- and C-terminal regions, causing inhibition. Ca2+/CaM also binds the N-terminal region of CNGB1 subunits and disrupts an intersubunit, N- and C-terminal interaction between CNGB1 and CNGA1 subunits in rod channels. However, the precise N- and C-terminal regions that form these interactions in olfactory channels are different from those in rod channels. Here, we will review recent advances in understanding the subunit composition and the mechanisms and roles for Ca2+/CaM-dependent inhibition in olfactory and rod CNG channels.
On a Predator-Prey System with Random Switching that Never Converges to its Equilibrium

We study the dynamics of a predator-prey system in a random environment. The dynamics evolves according to a deterministic Lotka-Volterra system for an exponential random time after which it switches to a different deterministic Lotka-Volterra system. This switching procedure is then repeated. The resulting process switches between two deterministic Lotka-Volterra systems at exponential times and therefore is a Piecewise Deterministic Markov Process (PDMP). In the case when the equilibrium points of the two deterministic Lotka-Volterra systems coincide we show that almost surely the trajectory does not converge to the common deterministic equilibrium. Instead, with probability one, the densities of the prey and the predator oscillate between $0$ and $\infty$. This proves a conjecture of Takeuchi et al (J. Math. Anal. Appl 2006). The proof of the conjecture is a corollary of a result we prove about linear switched systems. Assume $(Y_t, I_t)$ is a PDMP that evolves according to $\frac{dY_t}{dt}=A_{I_t} Y_t$ where $A_0,A_1$ are $2\times2$ matrices and $I_t$ is a Markov chain on $\{0,1\}$ with transition rates $k_0,k_1>0$. If the matrices $A_0$ and $A_1$ are not proportional and have purely imaginary eigenvalues, then the average growth rates of $\|Y_t\|$ are all equal and strictly positive. In particular, almost surely $\lim_{t\to\infty}\|Y_t\|=+\infty$.
Defoliation Effects on Yield and Bud and Tiller Numbers of Two Sandhills Grasses

Intensive grazing strategies for the Nebraska Sandhills must be based on time and frequency of defoliation of key warm-season grasses. A 3-year field study was conducted in the Nebraska Sandhills to determine the effects of defoliation on yield and bud and tiller number of sand bluestem [Andropogon gerardli var. paucipilus (ash) Fern. ] and prairie sandreed [Calamovilfa longifolia (Hook.) Scribn. ]. Defoliation (7 cm) treatments imposed on a 1.5 X 1-m plot were: a single defoliation on 10 June, 10 July, or 10 August; 2 successive defoliations on 10 June and 10 August; or 3 successive defoliations on 10 June, 10 July, and 10 August. All plots were harvested in October to obtain aftermath yield. Control plots were harvested only at the end of the growing season (October). Defoliation treatments were initiated in 1986, 1987, and 1988 on different plots and the effect of year of initiation as well as the effect of 3 successive years of repeated treatment (1986 plots) was evaluated. Annual dry matter (DM) yield, and bud and tiller numbers were measured. Following the initial year of treatment multiple defoliations increased yield of both grasses while bud and tiller numbers were similar to those of the control plants. After 3 years of repeated treatment, annual DM yield of sand bluestem for all defoliation treatments was lower than the control. A single defoliation of sand bluestem in August or a June-July-August defoliation reduced bud number compared to other treatments and the control. A June-August defoliation of prairie sandreed over a 3-year period increased annual DM yield compared to all treatments and the control although defoliation treatments reduced bud number. The optimum time and frequency of defoliation for annual DM yield and bud and tiller number was a single June or July defoliation for sand bluestem and a June-August defoliation for prairie sandreed.
High-performance distributed memory and computing algorithm for face recognition via conformal mapping

This work deals with a new distributed face recognition technique based on transformation invariant conformal mapping. Face recognition using digital images is constrained by several factors like rotation (in and out of plane), scaling, and is usually operated under strict lighting conditions. In a previous work, through a conformal mapping process, we demonstrated the ability to 1) recognize shapes, and 2) concisely represent shape boundaries using a set of polynomial coefficients derived in the mapping process. In this work we illustrate how these previous results can be applied to face recognition. Additionally, in the approach outlined herein, a syntactic representation is formed for polygonal and non-polygonal shapes representing a given face features whose representation we desire to extract and reproduce compactly. In particular, in this paper we focus on the face outline, left eyebrow, right eyebrow, left eye, right eye, nose, curve form the lower nose to upper lips, and lips as face features. Some of these face features are grouped together and then processed in parallel in a distributed network of workstations via a Message Passing Interface running over TCP/IP. In particular, we show that a master-salve paradigm is used here to implement the proposed parallel and distributed algorithm and is base don a distributed-memory approach. Test were performed with 1,2, and three workstations. The algorithm assumes no constraints in the lighting, and the size of the window that has the face. This work deals with face representation and recognition and face segmentation is not the subject of this paper. We finally show the potential of the proposed generalized technique in its ability to handle both polygonal, non- polygonal and mixed polygonal/non-polygonal object shapes. We also show that the proposed algorithm achieves high recognition rates for rotations in the plane, translation, and scaling and is robust in noisy environments.
Fate of the Biological Control AgentPseudomonas aureofaciens TX-1 after Application to Turfgrass

ABSTRACT The fate and impact of Pseudomonas aureofaciens TX-1 following application as a biocontrol agent for fungi in turfgrass were studied. The organism was applied with a modified irrigation system by using a preparation containing 1 × 106P. aureofaciens TX-1 CFU ml−1 about 100 times between May and August. We examined the impact of this repeated introduction ofP. aureofaciens TX-1 (which is known to produce the antimicrobial compound phenazine-1-carboxylic acid) on the indigenous microbial community of the turfgrass system and on establishment of introduced bacteria in the soil system. A PCR primer-DNA hybridization probe combination was developed to accurately monitor the fate ofP. aureofaciens TX-1 following application in irrigation water. To assess the impact of frequent P. aureofaciensTX-1 applications on the indigenous bacterial community, turfgrass canopy, thatch, and rhizosphere samples were obtained during the growing season from control and treated plots and subjected to DNA extraction procedures and denaturing gradient gel electrophoresis (DGGE). PCR amplification and hybridization of extracted DNA with theP. aureofaciens TX-1-specific primer-probe combination revealed that P. aureofaciens TX-1 not only became established in the rhizosphere and thatch but also was capable of overwintering. Separation of PCR-amplified partial 16S rRNA genes by DGGE showed that the repeated application of P. aureofaciens TX-1 in irrigation water resulted in transient displacement of a leaf surface bacterial community member. There was no obvious alteration of any dominant members of the thatch and rhizosphere microbial communities.
A Turbo Coded MIMO Scheme for Noncoherent Fast-Fading Channels

In this paper, we propose a turbo coded MIMO (multiple-input multiple-output) scheme for noncoherent fast fading channels, where neither the transmitter nor the receiver knows the channel state information. The turbo coded bits are alternatively transmitted by using the unitary space-time modulation (USTM) or spatial multiplexing (SM). At the receiver, a novel iterative detection-decoding algorithm is performed among the turbo decoder, the coherent demapper used for SM, and the noncoherent demapper for USTM. As compared to the scheme in the literature, the proposed scheme, in some cases, can provide better error performance with lower complexity.
Cluster overlay-dynamic source routing: Highly scalable routing protocol

Scalable routing is one of the key challenges in designing and operating large scale MANETs. Performance of routing protocols proposed so far is only guaranteed under the various limitation, i.e., dependent of the number of nodes in the network or needs the location information of destination node. Due to the dependency to the number of nodes in the network, as the number of nodes increases the performance of previous routing protocols degrade dramatically. We propose Cluster Overlay Dynamic Source Routing (CODSR) protocol. We conduct performance analysis by means of computer simulation under various conditions - diameter scaling and density scaling. Developed algorithm outperforms the DSR algorithm, e.g., more than 90\% improvement as for the normalized routing load. Operation of CODSR is very simple and we show that the message and time complexity of CODSR is independent of the number of nodes in the network which makes CODSR highly scalable.
Dynamic motion models in Monte Carlo Localization

Localization is the problem of determining a robot's location in an environment. Monte Carlo Localization (MCL) is a method of solving this problem by using a partially observable Markov decision process to find the robot's state based on its sensor readings, given a static map of the environment. MCL requires a model of each sensor in order to work properly. One of the most important sensors involved is the estimation of the robot's motion, based on its encoders that report what motion the robot has performed. Since these encoders are inaccurate, MCL involves using other sensors to correct the robot's location. Usually, a motion model is created that predicts the robot's actual motion, given a reported motion. The parameters of this model must be determined manually using exhaustive tests, but a single model cannot optimally represent a robot's motion in all cases. Thus, it is necessary to have a generalized model with enough error to compensate for all possible situations. However, if the localization algorithm is working properly, the result is a series of predicted motions, together with the corrections determined by the algorithm that alter the motions to the correct location. We demonstrate a technique to process these motions and corrections and dynamically determine revised motion parameters that more accurately reflect the robot's motion. We also link these parameters to different locations so that area dependent conditions, such as surface changes, can be taken into account. Finally, the dynamic technique allows various different motion models to be used with minimal work. By using the fact that MCL is working, we have improved the algorithm to adapt to changing conditions so as to handle even more complex situations.
Computed Tomographic Analysis of Meteorite Inclusions

The discovery of isotopic anomalies in the calcium- and aluminum-rich inclusions of the Allende meteorite has improved our knowledge of the origin of the solar system. Inability to find more inclusions without destroying the meteorite has hampered further study. By using a fourth-generation computed tomographic scanner with modifications to the software only, the interior of heterogeneous materials such as Allende can be nondestructively probed. The regions of material with high and low atomic numbers are displayed quickly. The object can then be cut to obtain for analysis just the areas of interest.
The Chromatin-Remodeling Enzymes BRG1 and CHD4 Antagonistically Regulate Vascular Wnt Signaling

ABSTRACT Canonical Wnt signaling plays an important role in embryonic and postnatal blood vessel development. We previously reported that the chromatin-remodeling enzyme BRG1 promotes vascular Wnt signaling. Vascular deletion of Brg1 results in aberrant yolk sac blood vessel morphology, which is rescued by pharmacological stimulation of Wnt signaling with lithium chloride (LiCl). We have now generated embryos lacking the chromatin-remodeling enzyme Chd4 in vascular endothelial cells. Unlike Brg1 mutants, Chd4 mutant embryos had normal yolk sac vascular morphology. However, concomitant deletion of Chd4 and Brg1 rescued vascular abnormalities seen in Brg1 mutant yolk sacs to the same extent as LiCl treatment. We hypothesized that Wnt signaling was upregulated in Chd4 mutant yolk sac vasculature. Indeed, we found that Chd4 deletion resulted in upregulation of the Wnt-responsive transcription factor Tcf7 and an increase in Wnt target gene expression in endothelial cells. Furthermore, we identified one Wnt target gene, Pitx2, that was downregulated in Brg1 mutant endothelial cells but was rescued following LiCl treatment and in Brg1 Chd4 double mutant vasculature, suggesting that PITX2 helps to mediate the restoration of yolk sac vascular remodeling under both conditions. We conclude that BRG1 and CHD4 antagonistically modulate Wnt signaling in developing yolk sac vessels to mediate normal vascular remodeling.
A GEE Approach for Estimating Correlation Coefficients Involving Left-censored Variables

HIV (Human Immunodeficiency Virus) researchers are often concerned with the correlation between HIV viral load measurements and CD4 + lymphocyte counts. Due to the lower limits of detection (LOD) of the available assays, HIV viral load measurements are subject to left-censoring. Motivated by these considerations, the maximum likelihood (ML) method under normality assumptions was recently proposed for estimating the correlation between two continuous variables that are subject to left-censoring. In this paper, we propose a generalized estimating equations (GEE) approach as an alternative to estimate such a correlation coefficient. We investigate the robustness to the normality assumption of the ML and the GEE approaches via simulations. An actual HIV data example is used for illustration.
Heart Transplant Outcome Prediction using UNOS Data

We analyze heart transplant data from the United Network for Organ Sharing (UNOS) program with the aim of developing accurate risk prediction models for mortality within 1 year of heart transplant using data mining techniques. The data used in this study is de-identified and consists of 50 predictor attributes, and 1-year posttranplant survial outcome for patients who underwent heart transplant between the years 2000 and 2009. Our dataset had 19,429 such patient instances. Several data mining classification techniques were used on this data along with various data mining optimizations and validations to build predictive models for the abovementioned outcome. Prediction results were evaluated using c-statistic metric, and the highest c-statistic obtained was 0.656. Further, we also applied feature selection techniques to reduce the number of attributes in the model from 50 to 8, while trying to have minimal degradation in c-statistic (0.645). We believe the resulting predictive model on the reduced dataset can be quite useful to integrate in a risk calculator to aid both physicians and patients in risk assessment.
Evolution de schéma par classification automatique pour les entrepôts de données

Résumé. Les modèles et outils OLAP actuels gèrent les dimensions d’a nalyse d’un entrepôt de données de manière statique. Par conséquen t, les axes d’analyse restent souvent figés malgré l’évolution des besoins et des données. Dans cet article, nous proposons une approche d’évolution de sch éma basée sur une technique de classification automatique. Pour cela, nous ch erchons le meilleur regroupement des instances d’un niveau d’analyse choisi pa r l’utilisateur en utilisant la méthode des k-means. Un nouvel axe d’analyse est en suit construit à partir du résultat de cette classification. Pour choisir le d scripteurs du niveau d’analyse à classifier, nous proposons deux solutions: la première utilise directement les attributs décrivant le niveau à classifier. Pa contre, la deuxième solution décrit le niveau d’analyse par les mesures dans la t ab e des faits. Pour valider notre approche, nous l’avons intégrée et testée à l’ intérieur du SGBD (Système de Gestion de Bases de Données) Oracle 10g.
Echinococcosis Affecting the Central Nervous System

Echinococcus granulosus is a ubiquitous parasite:'. * its worldwide range includes portions of the United States. It reaches its highest prevalence in major sheepand cattle-raising areas of the world, with the parasite cycling primarily between dog and sheep or cow. In addition, various sylvatic cycles exist (for example, dogcamel, fox-sheep, wolf-moose, dingo-wallaby) Echinococcus multilocularis, previously confined to subarctic areas and cycling primarily between dogs (or foxes) and rodents, has spread progressively southward in the past 40 years, having recently been identified as far south as Illinois3 and Turkey.4 The domestic cat is capable of serving as the definitive host for E. multilocularis, with various small rodents serving as intermediate hosts. A cat-mouse cycle would have obvious major public health irnpli~ations. ~'~ A possible example of this situation is suggested by Gamble et al,' in their report of an autochthonous case from Wisconsin. Man becomes involved as an intermediate host by the ingestion of eggs passed by the definitive host, primarily the dog. The eggs excyst in the small intestine, liberating the hexacanth embryo, which penetrates the mucosa and migrates by the portal system to the liver. There, the embryos develop into hydatid cysts. In E. granulosus infestation, hepatic cysts are found in over 60% of cases, with the lungs involved (usually concomitantly but also as the only site) in 10 to 40%. Other sites, such as pericardium, kidney, brain, or periorbital tissue, are involved in 5% of cases. E. multilocularis is almost always found in the liver, but may metastasize to lung or brain in 5 to 10% of cases (Table 1). Within viable hydatid cysts, protoscoleces develop from the inner germinal membrane. If the cyst ruptures, liberated protoscoleces may form new hydatid cysts wherever they lodge (autoinfection).
Profiting from intellectual capital

Intellectual capital (IC) is a significant resource for many companies. This paper explains what IC is, the benefits IC can generate, how a firm can utilize those benefits, the different roles a portfolio of IC assets can play, how firms can extract value from these portfolios, and the risks to a company that does not manage its intellectual property portfolio. The paper describes the steps for extracting value and outlines several ways to manage the firm’s IC assets. It discusses how a firm determines the three major elements of context and different procedures firms may opt to follow internally to realize their intellectual value. This paper also describes the ICM Gathering Group, the group of companies that have collectively created the knowledge the paper conveys. The paper explains how the Gathering has defined intellectual capital and how its member companies use their knowledge to the benefit of their respective organizations.
Dynamic power allocation using Stackelberg game in a wireless sensor network

Wireless sensor networks are characterized by a limited availability of resources such as the power required for data transmission. Cooperative communication enables transmission of data without using too much power. The fading of data is considerably less when the nodes are engaged in a cooperative communication protocol, rather than a competitive game. The quintessential concern for each node is the power it needs to allocate in order to relay the other nodes data. In cooperative communication, the nodes need to transmit not only their own data, but the data of the neighboring nodes too. An efficient solution to this problem can be determined by employing the Stackelberg game. From the determined solutions, improvement in the cooperation among the neighboring nodes can be worked upon. A cooperation region can be established within which the nodes work towards transmitting the data more efficiently. A similar concept can be applied to multi-hop networks and N relay multi-hop networks. Thus, an optimal region of cooperation for a single node, which permits it to achieve maximum cooperation amongst all the other nodes at the same time can be determined. Since we employ a game theoretic approach, we can determine a trade off between quantities such as power allocated and utility of the nodes, which results in maximum optimization of the network. Through this paper, we aim to improve the network utility factor of the wireless sensor network through dynamic power allocation using the Stackelberg game.