The biology of Canadian weeds. 102. Gaultheria shallon Pursh.

1993 ◽  
Vol 73 (4) ◽  
pp. 1233-1247 ◽  
Author(s):  
Lauchlan Fraser ◽  
Roy Turkington ◽  
C. P. Chanway
Keyword(s):  
Biological Data ◽  
Soil Types ◽  
Gaultheria Shallon ◽  
Weed Biology ◽  
Coniferous Species ◽  
Evergreen Shrub ◽  
Woody Perennial ◽  
Effective Form ◽  
Wide Range ◽  
Vegetative Spread

Gaultheria shallon Pursh., salal (Ericaceae), is a densely growing perennial evergreen shrub occurring only from the panhandle of Alaska along the entire coast of British Columbia to southern California; it is of native origin. Salal grows on a wide range of soil types and textures, and is abundant in open habitats near the coast particularly on rocky knolls and along bluffs. It is a persistent, pervasive woody perennial and is a serious competitor with coniferous species. The plant produces numerous seeds but the most significant and effective form of colonization is through vegetative spread. Several herbicides are recommended for control of the the weed but it is both resistant and resilient to many herbicides. This contribution summarizes the known biological data for this species. Key words: Gaultheria shallon, salal, evergreen shrub, weed biology, competition

THE BIOLOGY OF CANADIAN WEEDS.: 76. Vicia angustifolia L.,V. cracca L., V. sativa L., V. tetrasperma (L.) Schreb. and V. villosa Roth.

1986 ◽  
Vol 66 (3) ◽  
pp. 711-737 ◽  
Author(s):  
L. W. AARSSEN ◽  
IVAN V. HALL ◽  
K. I. N. JENSEN
Keyword(s):  
British Columbia ◽  
Biological Data ◽  
Crop Plants ◽  
Vicia Sativa ◽  
Coastal Regions ◽  
Eastern Canada ◽  
Weed Biology ◽  
Wide Range ◽  
Weedy Species ◽  
Vicia Cracca

This paper provides a summary of biological data on five weedy species of vetch (Vicia). All species are naturalized in Canada and are found in a wide range of habitats with their main centers of distribution in Eastern Canada and the south and coastal regions of British Columbia. Vicia cracca is the most common and serious problem and occurs nationwide. Vicia sativa is the most variable of the species; numerous subspecies, varieties, forms and hybrids are described. Tendrils allow vetches to attach to crop plants and form mat-like infestations. Vetch species are sensitive to a number of herbicides but there appears to be differential tolerance among species to chlorthal dimethyl, 2,4-DB and others. Vicia spp. are host to several economically important pathogens and parasites.Key words: Weed biology, vetches, Vicia spp., distribution

Fault Tolerant Reliable Protocol (FTRP) Performance Evaluation in Wireless Sensor Networks: An Extensitive Study

2019 ◽  
pp. 1-36
Keyword(s):  
Wireless Sensor Networks ◽  
Fault Tolerance ◽  
Sensor Networks ◽  
Fault Tolerant ◽  
Cluster Head ◽  
Biological Data ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Good Performer ◽  
Wide Range

Fault Tolerant Reliable Protocol (FTRP) is proposed as a novel routing protocol designed for Wireless Sensor Networks (WSNs). FTRP offers fault tolerance reliability for packet exchange and support for dynamic network changes. The key concept used is the use of node logical clustering. The protocol delegates the routing ownership to the cluster heads where fault tolerance functionality is implemented. FTRP utilizes cluster head nodes along with cluster head groups to store packets in transient. In addition, FTRP utilizes broadcast, which reduces the message overhead as compared to classical flooding mechanisms. FTRP manipulates Time to Live values for the various routing messages to control message broadcast. FTRP utilizes jitter in messages transmission to reduce the effect of synchronized node states, which in turn reduces collisions. FTRP performance has been extensively through simulations against Ad-hoc On-demand Distance Vector (AODV) and Optimized Link State (OLSR) routing protocols. Packet Delivery Ratio (PDR), Aggregate Throughput and End-to-End delay (E-2-E) had been used as performance metrics. In terms of PDR and aggregate throughput, it is found that FTRP is an excellent performer in all mobility scenarios whether the network is sparse or dense. In stationary scenarios, FTRP performed well in sparse network; however, in dense network FTRP’s performance had degraded yet in an acceptable range. This degradation is attributed to synchronized nodes states. Reliably delivering a message comes to a cost, as in terms of E-2-E. results show that FTRP is considered a good performer in all mobility scenarios where the network is sparse. In sparse stationary scenario, FTRP is considered good performer, however in dense stationary scenarios FTRP’s E-2-E is not acceptable. There are times when receiving a network message is more important than other costs such as energy or delay. That makes FTRP suitable for wide range of WSNs applications, such as military applications by monitoring soldiers’ biological data and supplies while in battlefield and battle damage assessment. FTRP can also be used in health applications in addition to wide range of geo-fencing, environmental monitoring, resource monitoring, production lines monitoring, agriculture and animals tracking. FTRP should be avoided in dense stationary deployments such as, but not limited to, scenarios where high application response is critical and life endangering such as biohazards detection or within intensive care units.

scholarly journals Predictive modelling of soils’ hydraulic conductivity using artificial neural network and multiple linear regression

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Charles Gbenga Williams ◽  
Oluwapelumi O. Ojuri
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Hydraulic Conductivity ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Coarse Grained ◽  
Soil Types ◽  
Wide Range ◽  
Artificial Neural ◽  
Input Variables

AbstractAs a result of heterogeneity nature of soils and variation in its hydraulic conductivity over several orders of magnitude for various soil types from fine-grained to coarse-grained soils, predictive methods to estimate hydraulic conductivity of soils from properties considered more easily obtainable have now been given an appropriate consideration. This study evaluates the performance of artificial neural network (ANN) being one of the popular computational intelligence techniques in predicting hydraulic conductivity of wide range of soil types and compared with the traditional multiple linear regression (MLR). ANN and MLR models were developed using six input variables. Results revealed that only three input variables were statistically significant in MLR model development. Performance evaluations of the developed models using determination coefficient and mean square error show that the prediction capability of ANN is far better than MLR. In addition, comparative study with available existing models shows that the developed ANN and MLR in this study performed relatively better.

Pharmacologic activities of 5, 6-Diaryl/heteroaryl-3-substituted-1, 2, 4-triazines as a privileged scaffold in drug development

2021 ◽  
Vol 21 ◽  
Author(s):  
Zahra Zakeri Khatir ◽  
Hamid Irannejad
Keyword(s):  
Biological Data ◽  
Pharmacological Activities ◽  
Drug Candidates ◽  
Structure Activity ◽  
Wide Range ◽  
Privileged Structure ◽  
Triazine Derivatives ◽  
Privileged Scaffold ◽  
Substituted 1 ◽  
Anti Hiv

: 1, 2, 4-Triazine derivatives have received much attention due to their multifunctional nature, especially in diverse pharmacological properties as well as a key fragment in many drug candidates. Introduction of a vicinal 5, 6-diaryl/heteroaryl moiety on the 1, 2, 4-triazine ring has attracted plentiful attention in the field of medicinal chemistry. 5, 6-Diaryl/heteroaryl-3-substituted-1, 2, 4-triazine is as a prominent scaffold in many drug candidates which has shown a wide range of pharmacological activities such as anti-diabetic, antifungal, anti-inflammatory, anticancer, anti-HIV, neuroprotective, anticonvulsant, anti- Alzheimer, anti-Parkinson and antioxidant. In this review, we have discussed synthesis, various pharmacological activities of 5, 6-diaryl/heteroaryl-3-substituted-1, 2, 4-triazines, their structure-activity relationship (SAR), pharmacophoric elements and their mechanism of action reported in the published articles during 2000-2019. Evaluation of compounds by PAINS filtering tool was accomplished and showed that this versatile structure could be considered as a privileged structure. Compilation of the biological data confirmed that the position 3 of the 1,2,4-triazine is a key location to determine the affinity and selectivity of the 5,6-diaryl/heteroaryl-3-substituted-1, 2, 4-triazines towards different biologic targets. Specific geometrical and thermodynamic characters of this motif have prompted it as a frequent hitter.

scholarly journals Data framework for efficient management of sequence and microsatellite data in biodiversity studies

2013 ◽  
Vol 56 (1) ◽  
pp. 50-64 ◽  
Author(s):  
C. V. C. Truong ◽  
Z. Duchev ◽  
E. Groeneveld
Keyword(s):  
Information System ◽  
Molecular Data ◽  
General Information ◽  
Biological Data ◽  
Efficient Management ◽  
Data Framework ◽  
Wide Range ◽  
Uniform Solution ◽  
General Data ◽  
General Data Model

Abstract. In recent years, software packages for the management of biological data have rapidly been developing. However, currently, there is no general information system available for managing molecular data derived from both Sanger sequencing and microsatellite genotyping projects. A prerequisite to implementing such a system is to design a general data model which can be deployed to a wide range of labs without modification or customization. Thus, this paper aims to (1) suggest a uniform solution to efficiently store data items required in different labs, (2) describe procedures for representing data streams and data items (3) and construct a formalized data framework. As a result, the data framework has been used to develop an integrated information system for small labs conducting biodiversity studies.

scholarly journals Denoising large-scale biological data using network filters

2021 ◽  
Author(s):  
Andrew J Kavran ◽  
Aaron Clauset
Keyword(s):  
Large Scale ◽  
Synthetic Data ◽  
Interaction Network ◽  
Learning Task ◽  
Biological Data ◽  
Data Sets ◽  
Proteomics Data ◽  
Life History Variation ◽  
Wide Range ◽  
Underlying Processes

Abstract Background: Large-scale biological data sets are often contaminated by noise, which can impede accurate inferences about underlying processes. Such measurement noise can arise from endogenous biological factors like cell cycle and life history variation, and from exogenous technical factors like sample preparation and instrument variation.Results: We describe a general method for automatically reducing noise in large-scale biological data sets. This method uses an interaction network to identify groups of correlated or anti-correlated measurements that can be combined or “filtered” to better recover an underlying biological signal. Similar to the process of denoising an image, a single network filter may be applied to an entire system, or the system may be first decomposed into distinct modules and a different filter applied to each. Applied to synthetic data with known network structure and signal, network filters accurately reduce noise across a wide range of noise levels and structures. Applied to a machine learning task of predicting changes in human protein expression in healthy and cancerous tissues, network filtering prior to training increases accuracy up to 43% compared to using unfiltered data.Conclusions: Network filters are a general way to denoise biological data and can account for both correlation and anti-correlation between different measurements. Furthermore, we find that partitioning a network prior to filtering can significantly reduce errors in networks with heterogenous data and correlation patterns, and this approach outperforms existing diffusion based methods. Our results on proteomics data indicate the broad potential utility of network filters to applications in systems biology.

The undrained strength of some thawed permafrost soils

1979 ◽  
Vol 16 (2) ◽  
pp. 420-427
Author(s):  
John F. Nixon ◽  
Alan J. Hanna
Keyword(s):  
Undrained Shear Strength ◽  
Soil Types ◽  
Density Range ◽  
Mackenzie Delta ◽  
Sample Depth ◽  
Wide Range ◽  
Permafrost Soils ◽  
Undrained Strength ◽  
Water Contents ◽  
Undrained Shear

A large number of undrained shear strengths have been measured for thawed, undrained permafrost samples obtained from the Niglintgak Peninsula area of the Mackenzie Delta, N.W.T. The samples are mostly deltaic silts, with a few clay tills, and cover a wide range of depths, water contents, and frozen density. The undrained shear strengths of the thawed samples have been correlated with water content, frozen density, and sample depth. For these soil types, the strength is shown to decrease to zero at frozen densities of less than about 1670 kg/m3 and at water contents greater than about 35–42%. In the Niglintgak area, the undrained shear strength of the thawed samples below a depth of 10 m becomes relatively constant in the range of 23–43 kPa. This corresponds to a frozen density range of 1780–1870 kg/m3, and previous experience with soils of this nature indicates that the corresponding thaw settlement at these depths would be less than 10%.

Hierarchical Profiling, Scoring and Applications in Bioinformatics

2011 ◽  
pp. 13-31
Author(s):  
Li Liao
Keyword(s):  
Biological Data ◽  
Classification Methods ◽  
Homology Detection ◽  
Domain Specific ◽  
Wide Range ◽  
Recent Developments ◽  
Potential Applications ◽  
Domain Specific Knowledge ◽  
Clustering And Classification ◽  
Biological Entities

Recently, clustering and classification methods have seen many applications in bioinformatics. Some are simply straightforward applications of existing techniques, but most have been adapted to cope with peculiar features of the biological data. Many biological data take a form of vectors, whose components correspond to attributes characterizing the biological entities being studied. Comparing these vectors, aka profiles, are a crucial step for most clustering and classification methods. We review the recent developments related to hierarchical profiling where the attributes are not independent, but rather are correlated in a hierarchy. Hierarchical profiling arises in a wide range of bioinformatics problems, including protein homology detection, protein family classification, and metabolic pathway clustering. We discuss in detail several clustering and classification methods where hierarchical correlations are tackled in effective and efficient ways, by incorporation of domain-specific knowledge. Relations to other statistical learning methods and more potential applications are also discussed.

Some aspects of fertilizer application to grassland in the Soviet Union

1968 ◽  
Vol 5 (5) ◽  
pp. 197-201
Author(s):  
N. G. Andreev ◽  
E. E. Ljubimova
Keyword(s):  
Soviet Union ◽  
Present Article ◽  
Fertilizer Application ◽  
Soil Types ◽  
The Soviet Union ◽  
Wide Range

Grasslands in the Soviet Union amount to about 370 million hectares, of which some 70 million are devoted to hay, the remaining 300 million being grazed. That the wide range of climate and soil types should be reflected in the variety of grassland problems is inevitable. The present article reviews the contributions of the Timiryazev Agricultural Academy and discusses many of the problems related to the use of fertilizers on grassland in the Soviet Union.

scholarly journals THE BIOLOGY OF CANADIAN WEEDS.: 77.Veratrum viride Ait.

1987 ◽  
Vol 67 (3) ◽  
pp. 777-786 ◽  
Author(s):  
GERALD A. MULLIGAN ◽  
DEREK B. MUNRO
Keyword(s):  
North America ◽  
Chromosome Number ◽  
Biological Data ◽  
Eastern Canada ◽  
The West ◽  
Weed Biology ◽  
Herbaceous Perennial

This paper provides a summary of biological data on Veratrum viride Ait., false hellebore. It is a herbaceous perennial, native to wet habitats in North America. Subspecies viride occurs primarily in eastern Canada and subspecies eschscholtzii (A. Gray) Löve and Löve in the west. Both subspecies have the chromosome number of n = 16, 2n = 32. Ingested material of false hellebore is poisonous to humans and livestock.Key words: False hellebore, Veratrum viride Ait., weed biology

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